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A systematic literature review of health information systems for healthcare.

1. Introduction

2. material and method, 3. discussion, 3.1. the evolution of health information systems, 3.2. his structural deployment, 3.3. health information systems benefits, 3.4. information system and knowledge management in the healthcare arena, 3.4.1. information system, 3.4.2. knowledge management, 4. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Epizitone, A.; Moyane, S.P.; Agbehadji, I.E. A Systematic Literature Review of Health Information Systems for Healthcare. Healthcare 2023 , 11 , 959. https://doi.org/10.3390/healthcare11070959

Epizitone A, Moyane SP, Agbehadji IE. A Systematic Literature Review of Health Information Systems for Healthcare. Healthcare . 2023; 11(7):959. https://doi.org/10.3390/healthcare11070959

Epizitone, Ayogeboh, Smangele Pretty Moyane, and Israel Edem Agbehadji. 2023. "A Systematic Literature Review of Health Information Systems for Healthcare" Healthcare 11, no. 7: 959. https://doi.org/10.3390/healthcare11070959

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Health Care Comes Home: The Human Factors (2011)

Chapter: 7 conclusions and recommendations.

7 Conclusions and Recommendations

Health care is moving into the home increasingly often and involving a mixture of people, a variety of tasks, and a broad diversity of devices and technologies; it is also occurring in a range of residential environments. The factors driving this migration include the rising costs of providing health care; the growing numbers of older adults; the increasing prevalence of chronic disease; improved survival rates of various diseases, injuries, and other conditions (including those of fragile newborns); large numbers of veterans returning from war with serious injuries; and a wide range of technological innovations. The health care that results varies considerably in its safety, effectiveness, and efficiency, as well as its quality and cost.

The committee was charged with examining this major trend in health care delivery and resulting challenges from only one of many perspectives: the study of human factors. From the outset it was clear that the dramatic and evolving change in health care practice and policies presents a broad array of opportunities and problems. Consequently the committee endeavored to maintain focus specifically on how using the human factors approach can provide solutions that support maximizing the safety and quality of health care delivered in the home while empowering both care recipients and caregivers in the effort.

The conclusions and recommendations presented below reflect the most critical steps that the committee thinks should be taken to improve the state of health care in the home, based on the literature reviewed in this report examined through a human factors lens. They are organized into four areas: (1) health care technologies, including medical devices and health information technologies involved in health care in the home; (2)

caregivers and care recipients; (3) residential environments for health care; and (4) knowledge gaps that require additional research and development. Although many issues related to home health care could not be addressed, applications of human factors principles, knowledge, and research methods in these areas could make home health care safer and more effective and also contribute to reducing costs. The committee chose not to prioritize the recommendations, as they focus on various aspects of health care in the home and are of comparable importance to the different constituencies affected.

HEALTH CARE TECHNOLOGIES

Health care technologies include medical devices that are used in the home as well as information technologies related to home-based health care. The four recommendations in this area concern (1) regulating technologies for health care consumers, (2) developing guidance on the structure and usability of health information technologies, (3) developing guidance and standards for medical device labeling, and (4) improving adverse event reporting systems for medical devices. The adoption of these recommendations would improve the usability and effectiveness of technology systems and devices, support users in understanding and learning to use them, and improve feedback to government and industry that could be used to further improve technology for home care.

Ensuring the safety of emerging technologies is a challenge, in part because it is not always clear which federal agency has regulatory authority and what regulations must be met. Currently, the U.S. Food and Drug Administration (FDA) has responsibility for devices, and the Office of the National Coordinator for Health Information Technology (ONC) has similar authority with respect to health information technology. However, the dividing line between medical devices and health information technology is blurring, and many new systems and applications are being developed that are a combination of the two, although regulatory oversight has remained divided. Because regulatory responsibility for them is unclear, these products may fall into the gap.

The committee did not find a preponderance of evidence that knowledge is lacking for the design of safe and effective devices and technologies for use in the home. Rather than discovering an inadequate evidence base, we were troubled by the insufficient attention directed at the development of devices that account, necessarily and properly, for users who are inadequately trained or not trained at all. Yet these new users often must

rely on equipment without ready knowledge about limitations, maintenance requirements, and problems with adaptation to their particular home settings.

The increased prominence of the use of technology in the health care arena poses predictable challenges for many lay users, especially people with low health literacy, cognitive impairment, or limited technology experience. For example, remote health care management may be more effective when it is supported by technology, and various electronic health care (“e-health”) applications have been developed for this purpose. With the spectrum of caregivers ranging from individuals caring for themselves or other family members to highly experienced professional caregivers, computer-based care management systems could offer varying levels of guidance, reminding, and alerting, depending on the sophistication of the operator and the criticality of the message. However, if these technologies or applications are difficult to understand or use, they may be ignored or misused, with potentially deleterious effects on care recipient health and safety. Applying existing accessibility and usability guidelines and employing user-centered design and validation methods in the development of health technology products designed for use in the home would help ensure that they are safe and effective for their targeted user populations. In this effort, it is important to recognize how the line between medical devices and health information technologies has become blurred while regulatory oversight has remained distinct, and it is not always clear into which domain a product falls.

Recommendation 1. The U.S. Food and Drug Administration and the Office of the National Coordinator for Health Information Technology should collaborate to regulate, certify, and monitor health care applications and systems that integrate medical devices and health information technologies. As part of the certification process, the agencies should require evidence that manufacturers have followed existing accessibility and usability guidelines and have applied user-centered design and validation methods during development of the product.

Guidance and Standards

Developers of information technologies related to home-based health care, as yet, have inadequate or incomplete guidance regarding product content, structure, accessibility, and usability to inform innovation or evolution of personal health records or of care recipient access to information in electronic health records.

The ONC, in the initial announcement of its health information technology certification program, stated that requirements would be forthcom-

ing with respect both to personal health records and to care recipient access to information in electronic health records (e.g., patient portals). Despite the importance of these requirements, there is still no guidance on the content of information that should be provided to patients or minimum standards for accessibility, functionality, and usability of that information in electronic or nonelectronic formats.

Consequently, some portals have been constructed based on the continuity of care record. However, recent research has shown that records and portals based on this model are neither understandable nor interpretable by laypersons, even by those with a college education. The lack of guidance in this area makes it difficult for developers of personal health records and patient portals to design systems that fully address the needs of consumers.

Recommendation 2. The Office of the National Coordinator for Health Information Technology, in collaboration with the National Institute of Standards and Technology and the Agency for Healthcare Research and Quality, should establish design guidelines and standards, based on existing accessibility and usability guidelines, for content, accessibility, functionality, and usability of consumer health information technologies related to home-based health care.

The committee found a serious lack of adequate standards and guidance for the labeling of medical devices. Furthermore, we found that the approval processes of the FDA for changing these materials are burdensome and inflexible.

Just as many medical devices currently in use by laypersons in the home were originally designed and approved for use only by professionals in formal health care facilities, the instructions for use and training materials were not designed for lay users, either. The committee recognizes that lack of instructional materials for lay users adds to the level of risk involved when devices are used by populations for whom they were not intended.

Ironically, the FDA’s current premarket review and approval processes inadvertently discourage manufacturers from selectively revising or developing supplemental instructional and training materials, when they become aware that instructional and training materials need to be developed or revised for lay users of devices already approved and marketed. Changing the instructions for use (which were approved with the device) requires manufacturers to submit the device along with revised instructions to the FDA for another 510(k) premarket notification review. Since manufacturers can find these reviews complicated, time-consuming, and expensive, this requirement serves as a disincentive to appropriate revisions of instructional or training materials.

Furthermore, little guidance is currently available on design of user

training methods and materials for medical devices. Even the recently released human factors standard on medical device design (Association for the Advancement of Medical Instrumentation, 2009), while reasonably comprehensive, does not cover the topic of training or training materials. Both FDA guidance and existing standards that do specifically address the design of labeling and ensuing instructions for use fail to account for up-to-date findings from research on instructional systems design. In addition, despite recognition that requirements for user training, training materials, and instructions for use are different for lay and professional users of medical equipment, these differences are not reflected in current standards.

Recommendation 3. The U.S. Food and Drug Administration (FDA) should promote development (by standards development organizations, such as the International Electrotechnical Commission, the International Organization for Standardization, the American National Standards Institute, and the Association for the Advancement of Medical Instrumentation) of new standards based on the most recent human factors research for the labeling of and ensuing instructional materials for medical devices designed for home use by lay users. The FDA should also tailor and streamline its approval processes to facilitate and encourage regular improvements of these materials by manufacturers.

Adverse Event Reporting Systems

The committee notes that the FDA’s adverse event reporting systems, used to report problems with medical devices, are not user-friendly, especially for lay users, who generally are not aware of the systems, unaware that they can use them to report problems, and uneducated about how to do so. In order to promote safe use of medical devices in the home and rectify design problems that put care recipients at risk, it is necessary that the FDA conduct more effective postmarket surveillance of medical devices to complement its premarket approval process. The most important elements of their primarily passive surveillance system are the current adverse event reporting mechanisms, including Maude and MedSun. Entry of incident data by health care providers and consumers is not straightforward, and the system does not elicit data that could be useful to designers as they develop updated versions of products or new ones that are similar to existing devices. The reporting systems and their importance need to be widely promoted to a broad range of users, especially lay users.

Recommendation 4. The U.S. Food and Drug Administration should improve its adverse event reporting systems to be easier to use, to collect data that are more useful for identifying the root causes of events

related to interactions with the device operator, and to develop and promote a more convenient way for lay users as well as professionals to report problems with medical devices.

CAREGIVERS IN THE HOME

Health care is provided in the home by formal caregivers (health care professionals), informal caregivers (family and friends), and individuals who self-administer care; each type of caregiver faces unique issues. Properly preparing individuals to provide care at home depends on targeting efforts appropriately to the background, experience, and knowledge of the caregivers. To date, however, home health care services suffer from being organized primarily around regulations and payments designed for inpatient or outpatient acute care settings. Little attention has been given to how different the roles are for formal caregivers when delivering services in the home or to the specific types of training necessary for appropriate, high-quality practice in this environment.

Health care administration in the home commonly involves interaction among formal caregivers and informal caregivers who share daily responsibility for a person receiving care. But few formal caregivers are given adequate training on how to work with informal caregivers and involve them effectively in health decision making, use of medical or adaptive technologies, or best practices to be used for evaluating and supporting the needs of caregivers.

It is also important to recognize that the majority of long-term care provided to older adults and individuals with disabilities relies on family members, friends, or the individual alone. Many informal caregivers take on these responsibilities without necessary education or support. These individuals may be poorly prepared and emotionally overwhelmed and, as a result, experience stress and burden that can lead to their own morbidity. The committee is aware that informational and training materials and tested programs already exist to assist informal caregivers in understanding the many details of providing health care in the home and to ease their burden and enhance the quality of life of both caregiver and care recipient. However, tested materials and education, support, and skill enhancement programs have not been adequately disseminated or integrated into standard care practices.

Recommendation 5. Relevant professional practice and advocacy groups should develop appropriate certification, credentialing, and/or training standards that will prepare formal caregivers to provide care in the home, develop appropriate informational and training materials

for informal caregivers, and provide guidance for all caregivers to work effectively with other people involved.

RESIDENTIAL ENVIRONMENTS FOR HEALTH CARE

Health care is administered in a variety of nonclinical environments, but the most common one, particularly for individuals who need the greatest level and intensity of health care services, is the home. The two recommendations in this area encourage (1) modifications to existing housing and (2) accessible and universal design of new housing. The implementation of these recommendations would be a good start on an effort to improve the safety and ease of practicing health care in the home. It could improve the health and safety of many care recipients and their caregivers and could facilitate adherence to good health maintenance and treatment practices. Ideally, improvements to housing design would take place in the context of communities that provide transportation, social networking and exercise opportunities, and access to health care and other services.

Safety and Modification of Existing Housing

The committee found poor appreciation of the importance of modifying homes to remove health hazards and barriers to self-management and health care practice and, furthermore, that financial support from federal assistance agencies for home modifications is very limited. The general connection between housing characteristics and health is well established. For example, improving housing conditions to enhance basic sanitation has long been part of a public health response to acute illness. But the characteristics of the home can present significant barriers to autonomy or self-care management and present risk factors for poor health, injury, compromised well-being, and greater dependence on others. Conversely, physical characteristics of homes can enhance resident safety and ability to participate in daily self-care and to utilize effectively health care technologies that are designed to enhance health and well-being.

Home modifications based on professional home assessments can increase functioning, contribute to reducing accidents such as falls, assist caregivers, and enable chronically ill persons and people with disabilities to stay in the community. Such changes are also associated with facilitating hospital discharges, decreasing readmissions, reducing hazards in the home, and improving care coordination. Familiar modifications include installation of such items as grab bars, handrails, stair lifts, increased lighting, and health monitoring equipment as well as reduction of such hazards as broken fixtures and others caused by insufficient home maintenance.

Deciding on which home modifications have highest priority in a given

setting depends on an appropriate assessment of circumstances and the environment. A number of home assessment instruments and programs have been validated and proven to be effective to meet this need. But even if needed modifications are properly identified and prioritized, inadequate funding, gaps in services, and lack of coordination between the health and housing service sectors have resulted in a poorly integrated system that is difficult to access. Even when accessed, progress in making home modifications available has been hampered by this lack of coordination and inadequate reimbursement or financial mechanisms, especially for those who cannot afford them.

Recommendation 6. Federal agencies, including the U.S. Department of Health and Human Services and the Centers for Medicare & Medicaid Services, along with the U.S. Department of Housing and Urban Development and the U.S. Department of Energy, should collaborate to facilitate adequate and appropriate access to health- and safety-related home modifications, especially for those who cannot afford them. The goal should be to enable persons whose homes contain obstacles, hazards, or features that pose a home safety concern, limit self-care management, or hinder the delivery of needed services to obtain home assessments, home modifications, and training in their use.

Accessibility and Universal Design of New Housing

Almost all existing housing in the United States presents problems for conducting health-related activities because physical features limit independent functioning, impede caregiving, and contribute to such accidents as falls. In spite of the fact that a large and growing number of persons, including children, adults, veterans, and older adults, have disabilities and chronic conditions, new housing continues to be built that does not account for their needs (current or future). Although existing homes can be modified to some extent to address some of the limitations, a proactive, preventive, and effective approach would be to plan to address potential problems in the design phase of new and renovated housing, before construction.

Some housing is already required to be built with basic accessibility features that facilitate practice of health care in the home as a result of the Fair Housing Act Amendments of 1998. And 17 states and 30 cities have passed what are called “visitability” codes, which currently apply to 30,000 homes. Some localities offer tax credits, such as Pittsburgh through an ordinance, to encourage installing visitability features in new and renovated housing. The policy in Pittsburgh was impetus for the Pennsylvania Residential VisitAbility Design Tax Credit Act signed into law on October 28, 2006, which offers property owners a tax credit for new construction

and rehabilitation. The Act paves the way for municipalities to provide tax credits to citizens by requiring that such governing bodies administer the tax credit (Self-Determination Housing Project of Pennsylvania, Inc., n.d.).

Visitability, rather than full accessibility, is characterized by such limited features as an accessible entry into the home, appropriately wide doorways and one accessible bathroom. Both the International Code Council, which focuses on building codes, and the American National Standards Institute, which establishes technical standards, including ones associated with accessibility, have endorsed voluntary accessibility standards. These standards facilitate more jurisdictions to pass such visitability codes and encourage legislative consistency throughout the country. To date, however, the federal government has not taken leadership to promote compliance with such standards in housing construction, even for housing for which it provides financial support.

Universal design, a broader and more comprehensive approach than visitability, is intended to suit the needs of persons of all ages, sizes, and abilities, including individuals with a wide range of health conditions and activity limitations. Steps toward universal design in renovation could include such features as anti-scald faucet valve devices, nonslip flooring, lever handles on doors, and a bedroom on the main floor. Such features can help persons and their caregivers carry out everyday tasks and reduce the incidence of serious and costly accidents (e.g., falls, burns). In the long run, implementing universal design in more homes will result in housing that suits the long-term needs of more residents, provides more housing choices for persons with chronic conditions and disabilities, and causes less forced relocation of residents to more costly settings, such as nursing homes.

Issues related to housing accessibility have been acknowledged at the federal level. For example, visitability and universal design are in accord with the objectives of the Safety of Seniors Act (Public Law No. 110-202, passed in 2008). In addition, implementation of the Olmstead decision (in which the U.S. Supreme Court ruled that the Americans with Disabilities Act may require states to provide community-based services rather than institutional placements for individuals with disabilities) requires affordable and accessible housing in the community.

Visitability, accessibility, and universal design of housing all are important to support the practice of health care in the home, but they are not broadly implemented and incentives for doing so are few.

Recommendation 7. Federal agencies, such as the U.S. Department of Housing and Urban Development, the U.S. Department of Veterans Affairs, and the Federal Housing Administration, should take a lead role, along with states and local municipalities, to develop strategies that promote and facilitate increased housing visitability, accessibil-

ity, and universal design in all segments of the market. This might include tax and other financial incentives, local zoning ordinances, model building codes, new products and designs, and related policies that are developed as appropriate with standards-setting organizations (e.g., the International Code Council, the International Electrotechnical Commission, the International Organization for Standardization, and the American National Standards Institute).

RESEARCH AND DEVELOPMENT

In our review of the research literature, the committee learned that there is ample foundational knowledge to apply a human factors lens to home health care, particularly as improvements are considered to make health care safe and effective in the home. However, much of what is known is not being translated effectively into practice, neither in design of equipment and information technology or in the effective targeting and provision of services to all those in need. Consequently, the four recommendations that follow support research and development to address knowledge and communication gaps and facilitate provision of high-quality health care in the home. Specifically, the committee recommends (1) research to enhance coordination among all the people who play a role in health care practice in the home, (2) development of a database of medical devices in order to facilitate device prescription, (3) improved surveys of the people involved in health care in the home and their residential environments, and (4) development of tools for assessing the tasks associated with home-based health care.

Health Care Teamwork and Coordination

Frail elders, adults with disabilities, disabled veterans, and children with special health care needs all require coordination of the care services that they receive in the home. Home-based health care often involves a large number of elements, including multiple care providers, support services, agencies, and complex and dynamic benefit regulations, which are rarely coordinated. However, coordinating those elements has a positive effect on care recipient outcomes and costs of care. When successful, care coordination connects caregivers, improves communication among caregivers and care recipients and ensures that receivers of care obtain appropriate services and resources.

To ensure safe, effective, and efficient care, everyone involved must collaborate as a team with shared objectives. Well-trained primary health care teams that execute customized plans of care are a key element of coordinated care; teamwork and communication among all actors are also

essential to successful care coordination and the delivery of high-quality care. Key factors that influence the smooth functioning of a team include a shared understanding of goals, common information (such as a shared medication list), knowledge of available resources, and allocation and coordination of tasks conducted by each team member.

Barriers to coordination include insufficient resources available to (a) help people who need health care at home to identify and establish connections to appropriate sources of care, (b) facilitate communication and coordination among caregivers involved in home-based health care, and (c) facilitate communication among the people receiving and the people providing health care in the home.

The application of systems analysis techniques, such as task analysis, can help identify problems in care coordination systems and identify potential intervention strategies. Human factors research in the areas of communication, cognitive aiding and decision support, high-fidelity simulation training techniques, and the integration of telehealth technologies could also inform improvements in care coordination.

Recommendation 8 . The Agency for Healthcare Research and Quality should support human factors–based research on the identified barriers to coordination of health care services delivered in the home and support user-centered development and evaluation of programs that may overcome these barriers.

Medical Device Database

It is the responsibility of physicians to prescribe medical devices, but in many cases little information is readily available to guide them in determining the best match between the devices available and a particular care recipient. No resource exists for medical devices, in contrast to the analogous situation in the area of assistive and rehabilitation technologies, for which annotated databases (such as AbleData) are available to assist the provider in determining the most appropriate one of several candidate devices for a given care recipient. Although specialists are apt to receive information about devices specific to the area of their practice, this is much less likely in the case of family and general practitioners, who often are responsible for selecting, recommending, or prescribing the most appropriate device for use at home.

Recommendation 9. The U.S. Food and Drug Administration, in collaboration with device manufacturers, should establish a medical device database for physicians and other providers, including pharmacists, to use when selecting appropriate devices to prescribe or recommend

for people receiving or self-administering health care in the home. Using task analysis and other human factors approaches to populate the medical device database will ensure that it contains information on characteristics of the devices and implications for appropriate care recipient and device operator populations.

Characterizing Caregivers, Care Recipients, and Home Environments

As delivery of health care in the home becomes more common, more coherent strategies and effective policies are needed to support the workforce of individuals who provide this care. Developing these will require a comprehensive understanding of the number and attributes of individuals engaged in health care in the home as well as the context in which care is delivered. Data and data analysis are lacking to accomplish this objective.

National data regarding the numbers of individuals engaged in health care delivery in the home—that is, both formal and informal caregivers—are sparse, and the estimates that do exist vary widely. Although the Bureau of Labor Statistics publishes estimates of the number of workers employed in the home setting for some health care classifications, they do not include all relevant health care workers. For example, data on workers employed directly by care recipients and their families are notably absent. Likewise, national estimates of the number of informal caregivers are obtained from surveys that use different methodological approaches and return significantly different results.

Although numerous national surveys have been designed to answer a broad range of questions regarding health care delivery in the home, with rare exceptions such surveys reflect the relatively limited perspective of the sponsoring agency. For example,

• The Medicare Current Beneficiary Survey (administered by the Centers for Medicare & Medicaid Services) and the Health and Retirement Survey (administered by the National Institute on Aging) are primarily geared toward understanding the health, health services use, and/or economic well-being of older adults and provide no information regarding working-age adults or children or information about home or neighborhood environments.
• The Behavioral Risk Factors Surveillance Survey (administered by the Centers for Disease Control and Prevention, CDC), the National Health Interview Survey (administered by the CDC), and the National Children’s Study (administered by the U.S. Department of Health and Human Services and the U.S. Environmental Protection Agency) all collect information on health characteristics, with limited or no information about the housing context.
• The American Housing Survey (administered by the U.S. Department of Housing and Urban Development) collects detailed information regarding housing, but it does not include questions regarding the health status of residents and does not collect adequate information about home modifications and features on an ongoing basis.

Consequently, although multiple federal agencies collect data on the sociodemographic and health characteristics of populations and on the nation’s housing stock, none of these surveys collects data necessary to link the home, its residents, and the presence of any caregivers, thus limiting understanding of health care delivered in the home. Furthermore, information is altogether lacking about health and functioning of populations linked to the physical, social, and cultural environments in which they live. Finally, in regard to individuals providing care, information is lacking regarding their education, training, competencies, and credentialing, as well as appropriate knowledge about their working conditions in the home.

Better coordination across government agencies that sponsor such surveys and more attention to information about health care that occurs in the home could greatly improve the utility of survey findings for understanding the prevalence and nature of health care delivery in the home.

Recommendation 10. Federal health agencies should coordinate data collection efforts to capture comprehensive information on elements relevant to health care in the home, either in a single survey or through effective use of common elements across surveys. The surveys should collect data on the sociodemographic and health characteristics of individuals receiving care in the home, the sociodemographic attributes of formal and informal caregivers and the nature of the caregiving they provide, and the attributes of the residential settings in which the care recipients live.

Tools for Assessing Home Health Care Tasks and Operators

Persons caring for themselves or others at home as well as formal caregivers vary considerably in their skills, abilities, attitudes, experience, and other characteristics, such as age, culture/ethnicity, and health literacy. In turn, designers of health-related devices and technology systems used in the home are often naïve about the diversity of the user population. They need high-quality information and guidance to better understand user capabilities relative to the task demands of the health-related device or technology that they are developing.

In this environment, valid and reliable tools are needed to match users with tasks and technologies. At this time, health care providers lack the

tools needed to assess whether particular individuals would be able to perform specific health care tasks at home, and medical device and system designers lack information on the demands associated with health-related tasks performed at home and the human capabilities needed to perform them successfully.

Whether used to assess the characteristics of formal or informal caregivers or persons engaged in self-care, task analysis can be used to develop point-of-care tools for use by consumers and caregivers alike in locations where such tasks are encouraged or prescribed. The tools could facilitate identification of potential mismatches between the characteristics, abilities, experiences, and attitudes that an individual brings to a task and the demands associated with the task. Used in ambulatory care settings, at hospital discharge or other transitions of care, and in the home by caregivers or individuals and family members themselves, these tools could enable assessment of prospective task performer’s capabilities in relation to the demands of the task. The tools might range in complexity from brief screening checklists for clinicians to comprehensive assessment batteries that permit nuanced study and tracking of home-based health care tasks by administrators and researchers. The results are likely to help identify types of needed interventions and support aids that would enhance the abilities of individuals to perform health care tasks in home settings safely, effectively, and efficiently.

Recommendation 11. The Agency for Healthcare Research and Quality should collaborate, as necessary, with the National Institute for Disability and Rehabilitation Research, the National Institutes of Health, the U.S. Department of Veterans Affairs, the National Science Foundation, the U.S. Department of Defense, and the Centers for Medicare & Medicaid Services to support development of assessment tools customized for home-based health care, designed to analyze the demands of tasks associated with home-based health care, the operator capabilities required to carry them out, and the relevant capabilities of specific individuals.

Association for the Advancement of Medical Instrumentation. (2009). ANSI/AAMI HE75:2009: Human factors engineering: Design of medical devices. Available: http://www.aami.org/publications/standards/HE75_Ch16_Access_Board.pdf [April 2011].

Self-Determination Housing Project of Pennsylvania, Inc. (n.d.) Promoting visitability in Pennsylvania. Available: http://www.sdhp.org/promoting_visitability_in_pennsy.htm [March 30, 2011].

In the United States, health care devices, technologies, and practices are rapidly moving into the home. The factors driving this migration include the costs of health care, the growing numbers of older adults, the increasing prevalence of chronic conditions and diseases and improved survival rates for people with those conditions and diseases, and a wide range of technological innovations. The health care that results varies considerably in its safety, effectiveness, and efficiency, as well as in its quality and cost.

Health Care Comes Home reviews the state of current knowledge and practice about many aspects of health care in residential settings and explores the short- and long-term effects of emerging trends and technologies. By evaluating existing systems, the book identifies design problems and imbalances between technological system demands and the capabilities of users. Health Care Comes Home recommends critical steps to improve health care in the home. The book's recommendations cover the regulation of health care technologies, proper training and preparation for people who provide in-home care, and how existing housing can be modified and new accessible housing can be better designed for residential health care. The book also identifies knowledge gaps in the field and how these can be addressed through research and development initiatives.

Health Care Comes Home lays the foundation for the integration of human health factors with the design and implementation of home health care devices, technologies, and practices. The book describes ways in which the Agency for Healthcare Research and Quality (AHRQ), the U.S. Food and Drug Administration (FDA), and federal housing agencies can collaborate to improve the quality of health care at home. It is also a valuable resource for residential health care providers and caregivers.

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Health Information Systems in the COVID-19 Pandemic: A Short Survey of Experiences and Lessons Learned From the European Region

Associated data.

The datasets generated for this study will not be made publicly available due to maintaining confidentiality of identifiable country data.

Introduction: The COVID-19 crisis provides an opportunity to reflect on what worked during the pandemic, what could have been done differently, and what innovations should become part of an enhanced health information system in the future.

Methods: An online qualitative survey was designed and administered online in November 2020 to all the 37 Member States that are part of the WHO European Health Information Initiative and the WHO Central Asian Republics Information Network.

Results: Nineteen countries responded to the survey (Austria, Belgium, Croatia, Czech Republic, Finland, Greece, Iceland, Ireland, Israel, Italy, Kazakhstan, Latvia, Lithuania, Romania, Russian Federation, Sweden, Turkey, United Kingdom, and Uzbekistan). The COVID-19 pandemic required health information systems (HIS) to rapidly adapt to identify, collect, store, manage, and transmit accurate and timely COVID-19 related data. HIS stakeholders have been put to the test, and valuable experience has been gained. Despite critical gaps such as under-resourced public health services, obsolete health information technologies, and lack of interoperability, most countries believed that their information systems had worked reasonably well in addressing the needs arising during the COVID-19 pandemic.

Conclusion: Strong enabling environments and advanced and digitized health information systems are vital to controlling epidemics. Sustainable finance and government support are required for the continued implementation and enhancement of HIS. It is important to promote digital solutions beyond the COVID-19 pandemic. Now is the time to discuss potential solutions to obtain timely, accurate, and reliable health information and steer policy-making while protecting privacy rights and meeting the highest ethical standards.

Introduction

Health information systems (HIS) are systems that incorporate information generated by both population-based and institution-based data sources to provide information to support decision-making ( 1 ). The operational response to the COVID-19 pandemic required the rapid adaptation and leveraging of the capabilities of existing HIS to collect, transmit and analyze key health data in real-time that allowed to understand the epidemiological situation and craft appropriate control measures ( 2 ). Due to the unprecedented nature of the pandemic in severity and scale, HIS capabilities in many countries were overwhelmed by the information demands and the challenges encountered. Multiple technological gaps were exposed, especially in low and middle-income countries ( 3 , 4 ). Initial challenges ranged from new demands on key contributors at each health system level, who were already overburdened by the pandemic, to the urgency in determining how to effectively document seamless, continuous COVID-19 processes in electronic health record-embedded (EHR) databases ( 5 ).

The WHO Regional Office for Europe (WHO/Europe) unit on Data, Metrics, and Analytics within the Division of Country Health Policies and Systems (WHO/EURO/CPS/DMA) provides the Member States with guidance, tools, and examples of good practices for HIS based on what has worked in the past ( 6 ). The COVID-19 pandemic has provided a valuable opportunity to identify the strengths and weaknesses of existing HIS in the context of a global health emergency. Thus, the (WHO/EURO/CPS/DMA) conducted a short qualitative survey to assess Member States' experiences regarding the performance of their national HIS, intending to offer a snapshot of specific concerns, corrective measures adopted, and lessons learned throughout the COVID-19 pandemic.

In November 2020, the (WHO/EURO/CPS/DMA) designed and administered an online qualitative survey to assess lessons learned and experiences implementing health information systems (HIS) in the context of the COVID-19 pandemic.

The objectives were to identify experiences, capture valuable insights, and identify issues to be explored further within individual countries. Specifically, we aimed at assessing (1) which components of the HIS worked well, (2) which components of the HIS did not work well, (3) any practical workarounds or solutions, and (4) lessons learned.

The questionnaire included five open-ended questions, one rating scale question, and one yes/no question ( Table 1 ). Open-ended questions were used to gain deeper insights into specific issues and capture responses that would not have been well represented with quantitative data.

Survey questions.

The questionnaire, available in English and Russian, was administered to all the WHO National Focal Points (NFPs) of the 37 Member States of the WHO European Health Information Initiative (EHII) and the WHO Central Asian Republics Information Network (CARINFONET) via a secure internet-based system. The completion time was approximately 10 min to motivate respondents during this busy time and achieve a high response rate. The responses to each question were entered into a Microsoft Excel spreadsheet, combining the datasets from each language. Qualitative data analysis was performed, extracting common traits from the open-ended questions. Where possible, a summary analysis of the quantitative findings of the survey is offered. Results are presented in an aggregated and anonymized format.

Completed questionnaires were received from 19 out of 37 Member States contacted (51.3% response rate), namely, Austria, Belgium, Croatia, Czech Republic, Finland, Greece, Iceland, Ireland, Israel, Italy, Kazakhstan, Latvia, Lithuania, Romania, Russian Federation, Sweden, Turkey, United Kingdom, and Uzbekistan.

Participants were prompted to rate the HIS COVID-19 response using a 0-to-10 point scale (Question 7). Scores ranged from 2 to 10 with a median score of 8 (interquartile range [25, 75%]: 7, 8). Only two of the 19 countries gave a score below 5 ( Figure 1 ). The median value among all respondents indicates that most respondents felt that the HIS in their countries worked reasonably well and addressed the needs that arose during the COVID-19 pandemic to a satisfactory degree.

HIS rating scores.

Participants were asked to comment on which components of the HIS had worked well (Question 5). The majority (89.4%) indicated that a secure infrastructure for the electronic transmission of health data, already in place, had provided the foundation. In addition, dedicated disease registries, hospital statistics, and mortality registries, maintained over the years, had proven to be valuable data sources for monitoring population health and healthcare provision during the pandemic. Only 11% ( n = 2) mentioned that the linking of case-based data had been possible. One country indicated that:

“ A National patient portal was already in place and was relatively easy to enhance to provide services to citizens.”

Others ( n = 2) commented that reporting to the supranational level had been diligent and in compliance with international standards:

“ The mandatory reporting of clinical cases of some communicable diseases and deaths to a national register, and to the international level (ECDC and WHO) (…) worked well.”

At the same time, 36.8% ( n = 7) of participants indicated that HIS had been adapted rapidly:

“ The teams understood the sense of urgency and put everything in place to make things work.” “ Within a very short time, a series of surveys and panel studies were established to collect up-to-date data during the crisis.”

Some countries possessed an existing telemedicine infrastructure before the COVID-19 outbreak, while others developed it during the pandemic to avoid unnecessary patient and staff exposure:

“ e-Prescribing has become more feasible and comprehensive, generating a better capture of patterns and trends and even informing on prescribing patterns and epidemiological data.”

Two countries set up online workshops to train healthcare workers on COVID-19 clinical information and other instructions, speeding up the implementation of guidelines and protocols.

Regarding adjustments and solutions developed to adapt their HIS to respond to COVID-19 data requirements (Questions 3 and 4), all countries indicated that the existing disease surveillance systems had provided a foundation but needed to be upgraded and reorganized to keep pace with the dynamics of the pandemic. Novel screening processes, hospital-based and ambulatory testing, reporting and analytics tools were all developed or upgraded accordingly to inform public health decision-making:

“ There was an urgent need to develop a system to collect new information - from an emergency preparedness perspective (…). This system was designed specifically as decision support in an emergency and not to collect data for statistics.” “ Another main solution developed very quickly was a database containing data on covid-19 patients.” “ New dashboards and data pipelines were established to publish updated statistics on cases, deaths, health care and testing.” “ The hospital discharge registry was modified to include COVID-19 variables.” “ New information systems had to be set up rapidly, e.g., contact tracing information systems and ICU information systems.” “ A Public Health Management System (…) was integrated with the entire health system (…) and used at the border gates. Citizens brought to our country from abroad were recorded in this system.” “ First rollout of a, albeit temporary, unique patient identifier. The first in the country to be used.”

Increased reporting frequency (i.e., hospital statistics, prescribed drugs) was cited by 21% ( n = 4). Twenty-six percent ( n = 5) mentioned the establishment of new death registration systems to allow for timely calculation of excess mortality:

“ We moved to an electronic and more timely death registration system.”

Sixteen percent ( n = 3) of respondents explained that their national version of ICD-10/11 had been quickly updated as soon as COVID-19 coding advice ( 1 ) and WHO/ECDC case definitions and recommendations were available ( 2 , 3 ):

“ We were successful to quickly update the (…) version of ICD-10 when WHO issued coding and terminology recommendations for covid-19 early 2020, and to spread instructions to health care facilities through well-established networks.”

Eleven percent ( n = 2) indicated that they were exploring ways to facilitate access and usability of data for research purposes.

The majority of the countries (89%) reported that further adjustments to the HIS were still expected (Question 7). In this regard, two countries specified that additional improvements were anticipated to support the rollout of vaccination programs by setting up national electronic immunization registries.

Most respondents (89.5%) believed that the main issues were the lack of the required data infrastructure for effective information management and accurate reporting on relevant COVID-19 data (Question 6). Dedicated HIS components needed to be upgraded or set up from scratch, often in an uncoordinated manner due to the urgency, imposing a heavy burden on those involved:

“ Covid-19 imposed a heavy burden on both data providers and producers of statistics.” “ Increased reporting frequency (i.e., hospital statistics) brought the downside of allowing less data quality control compared to working on a more spaced basis.”

A transition period was necessary to achieve well-functioning operational processes because of the consequent technical glitches and delays in data reporting. There were instances of suboptimal data capture, poor timeliness, and limited use of information for action by decision-makers:

“ The lack of interoperability and a comprehensive EHR (…) did not allow for sound planning in terms of resources allocation.” “ Huge engagement for establishing timeliness, limited use of data at the decision-making level, insufficient interoperability between health care providers and public health authorities”

Apart from delays related to upgrading HIS components to respond to COVID-19, 31.5% ( n = 6) of respondents mentioned that a significant factor impacting timeliness, quality, and completeness of data was related to poor interoperability, as well as (in some cases) decentralized HIS operating in different regions or states. These led to problems in coordination, data exchange, and linkage of data:

“ The coordination between agencies and regional/local health authorities could be improved.” “ The number of tests, cases in long term care and infected staff were only available on a provincial level.” “ The lack of information from primary care settings and municipal health care had a negative impact on our ability to fully assess the interventions during the pandemic.” “ It was very difficult to obtain data from the residential and nursing homes, especially from the private ones.” “ Existing problems such as the fragmentation of data in several data silos led to problems during the pandemic.” “ Largest problems were timeliness and linkage of data.”

Registration delays on mortality statistics were also reported to have biased the results of excess mortality analyses. For example, one country mentioned that the usual time between a death occurring and being available for excess mortality analysis was three months at the beginning of the pandemic:

“ The national health registries, the causes of death registry, and other individual based registries (…) were not primarily designed to fulfill the more acute needs of emergency surveillance during a pandemic.” “ Time lags in mortality data (…) hampered estimates of excess deaths early in the pandemic.”

Furthermore, one country noted that a large amount of health data was being captured in unstructured clinical notes, making it much more difficult to process and analyze. Thirty-seven percent ( n = 7) of respondents noted that critical IT infrastructure and labor for effective contact-tracing were insufficient or non-existent before COVID-19. Tools for cluster identification and geo-localization, interpretation, and application of the General Data Protection Regulation (GDPR) were not in place. These were also deemed an important barrier for implementation:

“ The legal aspects and GDPR (interpretation/application) have been a barrier.” “ There were some challenges to balance the demand for timely HIS information vs. the need to prevent unauthorized access to confidential information.”

One NFP reported that resources had been primarily allocated to COVID data collection, negatively impacting effective information management for other diseases:

“ The IT resources allocated to COVID data collection had a negative impact on other data collections.”

Another respondent mentioned that due to the dramatic increase in the general public and media interest in COVID-19 epidemiology, HIS professionals had to communicate more clearly and widely about data collection specifications, data analysis, and interpretation for different purposes.

Finally, NFPs were asked to elaborate on experiences and lessons learned throughout the COVID-19 pandemic (Question 9). The consensus across the sample was that information needs in an emergency vs. general public health or health system monitoring were very different, and the existing HIS processes and protocols had been developed to serve the latter. Comments from survey respondents are shown in Box 1 .

Lessons learned: comments from survey respondents.

• - “ The timeliness aspect is central, and the demand for rapid data capture, analysis and response is quite different in an emergency scenario such as the covid-19-pandemic, compared to the general health system monitoring”
• - “ There is still a lot of work to do to improve data capture, timeliness and interoperability of different information systems”
• - “ The dashboard has been especially successful as a transparency tool”
• - “ Coordinated communication efforts to the political level, the general public and media are essential as the final output from any surveillance system”
• - “ Development of information systems needs good coordination to ensure good interoperability across the health sector”
• - “ Planning and systematic approach in building Health Information Systems were far from desired”
• - “ Advanced HIS is a fundamental component for both expertise advise/evidence, policy development and political action”
• - “ Strong and competent legal teams are needed to quickly assess new situations and to support actions in any area, including information management”
• - “ There is a need for clarifying the application and limits of existing laws governing privacy during the emergency”
• - “ Constant investment and funding will be required for the health information system going into the future”
• - “ Underinvestment in public health administration and in public health research has a negative effect on pro-active interventions”
• - “ Better use of health data for secondary purposes, linkage, sharing and accessing will become the norm due to COVID”

This brief qualitative research describes how countries in the WHO European Region experienced HIS challenges brought by the pandemic. The limitations of this research relate to the lack of a quantitative approach that would have allowed the measurement of HIS performance by quantifying the distributions of given variables. We preferred a qualitative approach which allowed us to explore the countries' experiences, perceptions, and understanding and determine divergent and common traits from COVID-19 responders at a national level. The survey was designed to be responded in a few minutes to encourage participation, considering COVID-19 priorities. We also hypothesized that providing response options in a more structured questionnaire could have led to acquiescence bias; that is why many of the questions were open-ended. Furthermore, the COVID-19 pandemic is ongoing, and consequently, our assessment captured respondents' perceptions at a single point in time. Although only a bit more than half of the countries (51.3 percent) chose to participate, those which responded represented a wide geographical and economic range.

Information needs during public health emergencies are different from routine health monitoring, and existing HIS were developed to serve the latter ( 7 ). The pandemic prompted a greater need for accurate and timely epidemiological data on various topics to understand the impact and plan for an adequate response ( 8 ). The capabilities of HIS in every country underwent corrections and enhancements to collect these COVID-19-related data. Typically, HIS upgrades encompass budgeting, planning, design, project oversight, pretesting, communication with end-users, and, finally, implementation ( 9 ). However, due to the urgency of the situation, insufficient material and human resources, and lack of proper strategic planning, these stages were improvised or completely skipped, resulting, in some cases, in inadequate data for the COVID-19 information needs and implementation delays. These challenges forced countries to face the limitations of their HIS, raising awareness of the relevance of such systems in public health emergencies. In any case, overall, countries reported satisfaction in how their systems had reacted to the changes in workload, information density, and typology of data.

Social, economic, and cultural differences also shaped how different information strategies coped with the COVID-19 outbreak ( 10 ). While some countries had a more developed informatics framework resulting from previous HIS enhancements, others lacked appropriate health information infrastructures capable of meeting the COVID-19 information needs. The pandemic has also exacerbated existing inequalities across HIS globally and highlighted their weaknesses. Although funding was released to support HIS during the emergency, the systems should be prepared for any health crisis in advance ( 4 ). Unfortunately, COVID-19 will not be the last global health emergency; thus, it is paramount that both regular funding and government support are secured to continue the implementation and improvement of health information management ( 11 ).

The COVID-19 pandemic accelerated the adoption of new health information technologies, and a wide array of digital tools were developed to address health information needs ( 12 – 14 ). For example, the Internet of Things (IoT) provided new data sources. Big data, such as location-based and contact tracing data, were integrated to model epidemiological trends, providing key information to decision-makers ( 15 ). However, some of these digital tools brought concerns related to national standards, access, acceptability, usability, adoption, and data protection ( 2 ). The General Data Protection Regulation (GDPR) ( 16 ) and the ePrivacy Directive ( 17 ) provide the safeguards for personal data protection in the European Union. The GDPR states that apps should not identify the individual, and no geolocation or movement data should be used ( 18 ). In Norway, “Smittestopp,” the COVID-19 contact-tracing app, was discontinued on 15 June 2020 after receiving a warning from the Norwegian Data Protection Authority ( 19 ). Likewise, the UK government was forced to abandon a centralized coronavirus contact-tracing app due to technical (i.e., unsupported by some devices, inaccurate distance measures) and personal privacy concerns ( 20 ). In addition, some of the new digital tools that the pandemic has brought have focused on the interests of organizational stakeholders without considering important ethical, social, and cultural values. Despite rapid increases in digital adoption, mobile phone ownership is not equally embraced by all nations. Global mobile users are still under 67 percent of the population ( 21 ). Thus, mobile phone location records will not capture these non-mobile phone users (i.e., lower-income, elderly, marginalized groups) ( 22 ). These issues need to be reassessed to support information management while meeting the highest ethical standards during health emergencies.

Despite data dashboards being mentioned only by two participants, these have been extensively used to display relevant COVID-19 data ( 14 ). However, it is important to note that several facets of a dashboard can be misrepresented without background knowledge of how the data were originally captured, characteristics of the data, and any biases that might affect interpretation ( 23 ).

Some survey respondents identified the lack of interoperability as a critical issue, highlighting the importance of the timely exchange of health information across platforms. Integration of multiple data sources remains challenging despite decades of technological advances. Some of the barriers to interoperability include lack of standards, large amounts of unstructured data ( 8 ), data breaches, and mistrust ( 24 ). There are promising uses for blockchain technology for system integration, specifically in combination with standards for exchanging healthcare information electronically; however, challenges such as immaturity, high cost, data privacy, poor scalability, and low general performance still need to be addressed ( 24 ).

Coordination and data sharing have been particularly challenging in countries with a high degree of regional and local decentralization in their health care and social protection and welfare services. Furthermore, coordination and data exchange also need to be improved between organizations within and outside of the health system (i.e., education, internal affairs, etc.).

The COVID-19 pandemic has also stressed the need to tackle infodemics and find efficient ways to communicate and engage with the population to establish trust in public health officials and the information they provide. Coordinated communication efforts to the political ranks, the public, the media, and between agencies and regional and local health authorities are essential, as knowledge translation is the final output from any surveillance system. The HIS-related issues that emerged during the COVID-19 pandemic need to be addressed by responsible information technology research. Developing a holistic view of complex data ecosystems involves the engagement of various data entities in the research process to allow integration and interoperability ( 22 ). Also, questions about the usefulness, applicability, and ethical aspects of some digital surveillance technologies still need to be addressed.

Health information systems with their multiple stakeholders have been put to the test, and valuable experience has been gained. Critical gaps have been revealed, such as under-resourced public health services, obsolete health information technologies, and a lack of interoperability to enable seamless data exchange among disparate organizations within the healthcare sector and administrative divisions. The COVID-19 pandemic has provided an opportunity to recognize and close those gaps to ensure better preparedness against future health emergencies.

Adequate financing into out-of-the-box data management systems is needed. People-centered, cradle-to-grave digitized health records that are seamless across health services and shared with public health and social services are key elements for better policy-making.

The advancements made in artificial intelligence and machine learning can potentially establish linkages between animal, environmental, and human health perspectives, ensuring quality health data and accurate information while respecting privacy rights.

The foundation of quality health data is one of the signs of mature health systems, along with universal health coverage and well-functioning community health and social services. The WHO European Region continues to support countries in developing the health information systems of the future.

Data Availability Statement

Author contributions.

All authors contributed sufficiently and meaningfully to the manuscript's conception, design, drafting, editing, revising, approved the final version for submission, and agreed to be accountable for all aspects of the work.

Author Disclaimer

The authors alone are responsible for the views expressed in this publication, and those views do not necessarily represent the views, decisions, or policies of the World Health Organization.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

The authors thank the WHO European Health Information Initiative (EHII) and the WHO Central Asian Republics Information Network (CARINFONET) for their participation and contribution in this study.

Health Information System Evaluation Essay

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The age of rapid technological development forces all industries and professions to adjust to the new conditions and integrate new approaches to their work. Indeed, health information technology (HIT) systems are adopted in most clinics, and nurses interact with them to optimize patient care and daily repeatable operations (Rahimi & Vimarlund, 2007). It is essential to evaluate the effectiveness of HIT for healthcare and the approaches distinguished from the standard systems’ assessment.

Nursing professionals must have the basic informatics skills to interact with modern HIT, and knowledge about the most workable methods to implement them is essential for decision-making (American Nurses Association, 2008). This paper aims to differentiate the HIT systems from other evaluation types, identify its strategies, and assess the challenges of designing a successful analysis approach.

Health HIT systems are integrated into several industry segments, such as chronic disease treatment, differential diagnosis, wearables, surgery, and artificial organ construction. Each technology’s interactions with patients are unlike and require separate evaluation for nurses to understand if they are practical and reliable. For instance, health information technology systems must be assessed through the creditability of databases utilized and algorithms for proceeding with the results.

In contrast, surgery systems require accurate evaluation, and health wearables need to be tested on patients to be considered workable (Yen et al., 2017). HIT assessment strategies can be based on comparing the results of human research for specific data to the automated one (Yen et al., 2017). Furthermore, the tactic of revising the databases separately from the technology can be employed by a nursing professional.

The HIT system’s effectiveness can be judged through its helpfulness in daily operations as it must optimize and empower working processes. Rahimi and Vimarlund (2007) claim that “there is no standard framework for evaluation effects and outputs of implementation and use of IT in the healthcare setting” (p. 400). However, the results of HIT systems operations can be identified in the decisions made with their assistance, quickness, and correctness compared to the manual processes. Speed of selecting specific treatment approaches is crucial for nurses in an emergency, therefore this factor is influential.

Designing a successful HIT system assessment strategy requires addressing the field where it is exercised, the volume of operations it is capable of performing, and the purpose of a healthcare facility to implement it. Neame et al. (2020) state that “HIT evaluations are important, but they are challenging to conduct and appraise” (p. 104247). Indeed, there are at least two obstacles to creating an optimal strategy: lack of systematic algorithms and a broad field of using the technology.

The first challenge prevents designing a successful HIT evaluation system due to the absence of strict standards and the inability to compare to the other facilities’ solutions because of data privacy (Neame et al., 2020). The second difficulty is related to the demand in using HIT systems for various operations simultaneously and proceeding with a significant volume of data. Consequently, designing the evaluation system requires an individualized approach based on the initial purpose of implementing HIT and the desired outcomes for nursing practitioners.

HIT systems are the reality for most healthcare facilities, therefore nursing professionals need to have basic knowledge about these tools’ capabilities and be able to evaluate their efficiency. Assessment strategies vary based on the technology and segment of implementation. HIT systems evaluation strategies might lack strict algorithms nurses could exercise to study the effectiveness and significance of the volume of information to process. Nursing professionals must identify the reasons to implement HIT and have clear expectations about the outcomes to assess their usefulness.

American Nurses Association. (2008). Nursing informatics: Scope and standards of practice. Silver Spring, MD.

Neame, M. T., Sefton, G., Roberts, M., Harkness, D., Sinha, I. P., & Hawcutt, D. B. (2020). Evaluating health information technologies: A systematic review of framework recommendations . International Journal of Medical Informatics, 142, 104247. Web.

Rahimi, B., & Vimarlund, V. (2007). Methods to evaluate health information systems in healthcare settings: A literature review. Journal of Medical Systems, 31 (5), 397- 432. Web.

Yen, P. Y., McAlearney, A. S., Sieck, C. J., Hefner, J. L., & Huerta, T. R. (2017). Health information technology (HIT) adaptation: refocusing on the journey to successful HIT implementation . JMIR Medical Informatics, 5 (3), e28. Web.

• Information Systems and Changing Organizational Culture
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Browse Theses

January 2012

• State University of New York at Buffalo
• Computer Science Department 226 Bell Hall Buffalo, NY
• United States

Information technology has been transforming health care industry. This dissertation investigates the use of health information technology by health care providers and patients as well as its outcomes. This dissertation consists of three essays studying workflow optimization in hospital emergency departments, people's search for online health information, and the relationships between EMR (Electronic Medical Records) usage and health care outcomes, respectively.

Hospital emergency departments' capacities to deal with a patient surge play an important role in preparedness for natural or man-made disasters. The first essay examines how emergency departments could optimize workflows during extreme events when there is a patient surge. This essay proposes a framework to reconfigure workflows while maintaining treatment quality. Our results show that reorganizing lower-priority processes and relocating the resources associated with those processes can shorten total waiting time in emergency departments, allowing better management of patient flows.

People are increasingly using the Internet to access health information and the information obtained has an impact on their health care outcomes. The second essay examines the impacts of IT enablers and health motivators on people's online health information search behaviors. We characterize users' online health information search behaviors along three dimensions: the frequency of online health information search, the diversity of online health information usage, and the preference of the Internet for initial search. Using the 2003 Health Information National Trends Survey (HINTS) data on cancers, we find that ease of access to Internet and trust in online health information could affect all three dimensions of search behaviors. While perceived quality of communication with doctors has an impact on diversity of search and preference of search, we surprisingly do not find an impact on the frequency of search for online health information. In addition, our results find that perceived health status could affect both frequency and diversity of search for online health information. But we do not find evidence that perceived health status could lead to a preference for using the Internet as a source for health information.

The US government has initiated incentive programs to encourage the adoption of Electronic Medical Records (EMR). To qualify for the incentive payment, health care providers need to demonstrate "meaningful use" of EMR systems, which requires the use of certified EMRs and the implementation of a set of standard functionalities. In the third essay, we examine how the meaningful use of EMRs would affect health care outcomes in outpatient settings. Our results show that the use of core functionalities required by "meaningful use" criteria and the use of certified EMRs have a positive impact on the quality and efficiency of care. In addition, we find the relationship between the "meaningful use" and quality of care is moderated by the length of EMR use.

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Health Information System Essays

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Peer-reviewed

Research Article

Understanding the impacts of health information systems on patient flow management: A systematic review across several decades of research

Roles Conceptualization, Data curation, Formal analysis, Resources, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Department of Human-Centred Computing, Faculty of Information Technology, Monash University, Melbourne, Australia

Roles Conceptualization, Supervision, Writing – review & editing

Roles Supervision, Writing – review & editing

Affiliation Office of Research and Ethics, Eastern Health, Melbourne, Australia

Affiliation Monash Centre for Health Research and Implementation, Monash University, Melbourne, Australia

• Quy Nguyen, 
• Michael Wybrow, 
• Frada Burstein, 
• David Taylor, 
• Joanne Enticott

• Published: September 12, 2022
• https://doi.org/10.1371/journal.pone.0274493
• Peer Review
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Patient flow describes the progression of patients along a pathway of care such as the journey from hospital inpatient admission to discharge. Poor patient flow has detrimental effects on health outcomes, patient satisfaction and hospital revenue. There has been an increasing adoption of health information systems (HISs) in various healthcare settings to address patient flow issues, yet there remains limited evidence of their overall impacts.

To systematically review evidence on the impacts of HISs on patient flow management including what HISs have been used, their application scope, features, and what aspects of patient flow are affected by the HIS adoption.

A systematic search for English-language, peer-review literature indexed in MEDLINE and EMBASE, CINAHL, INSPEC, and ACM Digital Library from the earliest date available to February 2022 was conducted. Two authors independently scanned the search results for eligible publications, and reporting followed the PRISMA guidelines. Eligibility criteria included studies that reported impacts of HIS on patient flow outcomes. Information on the study design, type of HIS, key features and impacts was extracted and analysed using an analytical framework which was based on domain-expert opinions and literature review.

Overall, 5996 titles were identified, with 44 eligible studies, across 17 types of HIS. 22 studies (50%) focused on patient flow in the department level such as emergency department while 18 studies (41%) focused on hospital-wide level and four studies (9%) investigated network-wide HIS. Process outcomes with time-related measures such as ‘length of stay’ and ‘waiting time’ were investigated in most of the studies. In addition, HISs were found to address flow problems by identifying blockages, streamlining care processes and improving care coordination.

HIS affected various aspects of patient flow at different levels of care; however, how and why they delivered the impacts require further research.

Citation: Nguyen Q, Wybrow M, Burstein F, Taylor D, Enticott J (2022) Understanding the impacts of health information systems on patient flow management: A systematic review across several decades of research. PLoS ONE 17(9): e0274493. https://doi.org/10.1371/journal.pone.0274493

Editor: Yong-Hong Kuo, University of Hong Kong, HONG KONG

Received: May 17, 2022; Accepted: August 28, 2022; Published: September 12, 2022

Copyright: © 2022 Nguyen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data is provided in the article and in the supporting file S3. Copies of the included studies are freely available online.

Funding: QDN was supported by a Ph.D. scholarship jointly funded by the Monash University Graduate Research Industry Partnership (GRIP) program and by Eastern Health. The Funders of this work did not have any direct role in the design of the study, its execution, analyses, interpretation of the data, or decision to submit results for publication.

Competing interests: No authors have competing interests

1. Introduction

Patient flow refers to the progressive movement of patients through different units or departments of the care setting. The aim of patient flow management is to provide safe and efficient patient care while assuring the best use of resources [ 1 ]. Hospitals around the world have undertaken several efforts and strategies to tackle patient flow problems and to provide high-quality care at the right time and right place. Meanwhile, there is an extensive stream of research reporting methods and interventions addressing patient flow problems. A recent umbrella review [ 2 ] found that over 25 different interventions have been used by hospitals around the world to solve the overcrowding issues in the emergency department (ED). However, previous studies focused primarily on interventions for a single, isolated hospital unit or ward with ED being the most frequently mentioned [ 3 , 4 ]. While many systematic reviews related to patient flow interventions have been done, a summary of these systematic reviews shows that most of these reviews have focused on traditional, non-IT interventions such as triage, streaming, and fast track. Systematic reviews on using health information systems (HISs) to tackle patient flow problems exist; however, they are often limited to a single specific system, such as computer provider order entry (CPOE) system [ 5 ]; methods such as computer simulation modelling [ 6 ]; or measures such as length of stay (LOS) [ 7 ].

HISs have been adopted by health providers to improve patient flow in various healthcare settings. For example, in emergency care, the automatic push notification system was used to address ED congestion, reduce LOS, and decrease patient load by providing updated information and improving patient navigation [ 8 ]. Dashboard systems were adopted to coordinate ambulance services and improve access to emergency services across multiple hospitals [ 9 ]. HISs provides data about ED visits which were used to create a robust prediction about hospital admissions and increase logistical efficiency [ 10 ]. In addition, Blaya et al. [ 11 ] investigated the use of HISs in improving access to laboratory results and the quality of care. These are a few examples illustrating the impacts of HISs on patient flow management.

In recent patient flow research, it has been suggested that utilising advanced data analytics techniques for patient flow management can be achieved by adopting HISs. For example, Rutherford et al. [ 12 ] claim that data analytics is essential in achieving improvement in systematic-wide flows through its capabilities in matching patient demand and hospital supply. Real-time demand capacity has been successfully implemented in many healthcare organisations to predict and match supply and demand [ 13 ]. Similarly, Berg et al. [ 14 ] called for a shift in the research paradigm from predicting and controlling to analysing and managing to achieve better flow outcomes. This can be done through the application of information technology in analysing data to proactively manage patient flows. Despite the rich tradition of inquiry in research about the use of HISs in patient flow management, to date, to the best of our knowledge, no systematic review has been conducted to assess the impacts of a broad range of HISs on patient flow management, highlighting an evidence gap in the literature. Therefore, a systematic review of this topic will provide more complete insights as to how HISs have been adopted for and impacted patient flow management practice.

2. Objectives

This systematic literature review aimed to examine and summarise information from published studies on the use of HISs in healthcare settings to manage and improve patient flows. We are interested in exploring what information systems have been adopted for managing patient flow and solving flow problems such as blockages, delays, and overcrowding, and their effectiveness. We examined studies that focused on department-level (e.g., ED), hospital-wide, and network-wide interventions. Particularly, our objectives are to provide critical analysis on:

• Study characteristics: Chronological and geographical distribution of the studies, study settings, and research designs.
• Study contents: What types and features of information system have been used for patient flow management, their results and effectiveness on patient flow outcomes.

3. Research questions

This review addresses the following research questions:

• What HISs have been used for hospitals’ patient flow management?
• What are the impacts of HISs on patient flow outcomes?
• In what ways, have HISs been used to manage patient flow?

4.1 Search strategy

We searched for peer-reviewed journal articles published in English from MEDLINE and EMBASE via Ovid, CINAHL, INSPEC, and ACM Digital Library from the earliest date available to February 2022. In addition, we examined the reference lists of the search results to retrieve further eligible papers. The search was conducted from June 2020 to July 2020 and then re-run in February 2022 before the data extraction process.

With the assistance of a subject librarian, we developed a systematic search strategy for this review ( S1 File ). To obtain the most comprehensive search results, we employed medical subject headings (MeSH) keywords when they are available in combination with free text keywords from the PICOS framework. We combined the following terms ( Table 1 ) in our search for relevant studies.

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https://doi.org/10.1371/journal.pone.0274493.t001

4.2 Eligibility

Table 2 specifies the inclusion and exclusion criteria used in the title and abstract screening process for this review.

https://doi.org/10.1371/journal.pone.0274493.t002

We included studies that described the impacts of HISs that were actually implemented and adopted for managing patient flow or solving patient flow problems. We excluded papers describing prototype systems, systems that were not implemented in practice or papers without real impacts of HISs on patient flow management such as those just reporting simulated results, simulation tests, or prediction models. Studies that focused on measures such as length of stay (LOS), and waiting time for clinical purposes without any relation to or discussion of patient flow management purposes were also excluded from this review.

Type of studies.

Apart from excluding simulation studies and review papers, we imposed no restrictions on the study’s design or publication date as long as the studies examined the effects of HIS on patient flow management.

Participants.

We included studies that were conducted in various healthcare settings including teaching hospitals, specialist hospitals and general hospitals (both public and private) and clinical centres. As long as the studies were conducted in these settings, we imposed no restrictions on the number of departments, units or wards involved. We also selected studies that addressed patient flow management at the network level, i.e., between different hospital sites and hospital centres. Studies investigating interventions in services not directly related to patient flow and patient access (such as financial services or insurance) were excluded from our review.

Type of intervention.

Health information system is a broad concept and hospitals generally adopt and use several types of information systems to manage their operations. In this review, we selected studies that addressed any type of computerised information systems that have been implemented and had impacts on patient flow outcomes. We also excluded paper-based information management systems, personal digital assistance devices, and medical tools such as surgery robots, CT scanners, heart rate measuring devices.

4.3 Study selection

To assist the selection of eligible studies for this review, we used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines with four key phases [ 16 ].

Initially, the first author searched through the pre-identified online databases by using combinations of the keywords to identify related studies. Duplicates were subsequently removed by using a tool called Covidence [ 17 ] and manually double checking by the first author. In the second step, two reviewers scanned the abstract of all studies to remove irrelevant or ineligible studies based on the predefined inclusion and exclusion criteria. The remaining studies went into the third step in which two reviewers assessed the full-text studies and further eliminated irrelevant papers. The final phase involved extracting data from included studies. We endeavoured to look for full-text files of the eligible papers in all resources available including using intra-library service to retrieve as many as possible

4.4 Data extraction and quality assessment

Information from the papers was extracted in the final list using an electronic data extraction form. Each study was given a unique identification number to ensure a consistent way of identifying studies between the two reviewers. The following data were extracted: authors, journals where the studies were published, year of publication, hospital’s country, the study settings, study objectives, study design, description of the information systems used, factors affecting the adoption of HISs for patient flow management, the effects of HISs on patient flow outcomes, study results, study limitation and research gaps ( S4 File , Example of data extraction form).

The GRADE [ 18 ] approach was adopted to assess the overall quality level of the evidence based on their design. GRADE approach provides particular useful guidelines for assessing health technology studies with heterogeneous study designs. Using the guidelines, the quality of evidence would be assessed as follows:

• High quality for randomized trial studies without serious limitations
• Low quality for observational studies
• ‘0’ level of quality for studies where quality is not assessable such as expert opinion and studies without objective evidence.

4.5 Analytic frameworks

We adopted literature review and expert opinion to develop frameworks that describe types of HISs, their functional capabilities, and associated benefits ( Table 3 ). We also used the conceptual model of Donabedian [ 19 ] as a framework for the analysis on patient flow outcomes. Donabedian’s model categorises care quality into three groups: structure, process, and outcomes.

https://doi.org/10.1371/journal.pone.0274493.t003

The literature search returned 5996 studies and the removal of duplicates reduced the number to 5095. After the first level of screening in which we screened the titles and abstracts and applied the exclusion criteria, 4824 studies were removed. We then proceeded to screen the full-text of 271 studies and 231 of them were excluded. In addition, four studies were added to the final pool through the reverse snowballing technique. Details of the screening process is summarised in Fig 1 , following the PRISMA flow diagram [ 16 ].

From : Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group (2009). Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Med 6(7): e1000097. doi: 10.1371/journal.pmed1000097 .

https://doi.org/10.1371/journal.pone.0274493.g001

We included 44 studies for our systematic review. The included studies reported mixed impacts of HISs on patient flow management, which can be categorised as follows:

• 33 studies reported positive impacts [ 9 , 20 – 51 ]
• 7 studies reported negative impacts [ 52 – 58 ] and 4 studies reported no impacts of ISs [ 59 – 62 ]. However, among the seven studies with negative impacts, two [ 55 , 58 ] found that the negative effects were temporary and the patient flow measures returned back at pre-implementation baselines.

5.1 Types and features of the HIS

The included 44 studies reported the impacts of 17 different types of HIS on patient flow: eight EHR systems, eight EMR systems, seven patient tracking systems, four computerised provider order entry systems (CPOE), three patient flow dashboard systems, three departmental information systems including ED (1) and Radiology (2), and one each for workflow management, admission prediction, documentation management, patient scheduling, medical prescribing, patient discharge management, patient referral management system, bed management, consultation management, clinical information management, and Asthma management. Table 4 summarises details of the study site and publication profile of the included studies (publication year, country and study settings).

https://doi.org/10.1371/journal.pone.0274493.t004

Research on the application of HISs to patient flow management can be dated back to the 1980s; however, it has gained prominence over the last decade. A majority of included studies were published in the period 2011–2020 (63.6%), compared to 29.5% of the 2001–2010 period and 6.8% of the 1988–2000 period. In addition, most of the studies selected for this review were published in developed countries where their governments have implemented promotional programs to increase the adoption of HISs in the healthcare sector. The number of studies from the USA was the highest with 24 studies, followed by Australia with nine studies. Canada and South Korea contributed three and two studies, respectively. One study was conducted in each of the followings: England, Italy, Japan, Portugal, Uganda, and Taiwan.

In terms of settings, 20 of the reviewed studies discussed the impacts of HIS interventions at the department level, while eleven studies addressed hospital-wide level and three studies address network-wide level. Within the department level, 15 studies focused on EDs, three in Radiology and two in Paediatrics. Studies focused on hospital-wide patient flow when they include the coordination between several departments or units. For example, Westbrook et al. [ 51 ] discussed the impacts of CPOE on the flow of patients between ED and Pathology departments in Australian hospitals. In addition, we found that four studies described the impacts of HISs on patient flow across hospital networks [ 9 , 31 , 39 , 42 ]. Fig 2 depicts where the reported HIS were studied in the care continuum and the number of studies.

The numbers in the circles correspond to the number of relevant studies reviewed.

https://doi.org/10.1371/journal.pone.0274493.g002

Specific functions of the 17 types of HIS that were described in the 44 studies included patient or event tracking (12 studies), clinical documentation management (12 studies), order entry (8 studies), patient registration (3 studies). Bed management, decision support, discharge management, patient flow reporting and prescription management were each included in three studies. Alert, disease detection, picture archiving, staff performance management, referral management, and reminder, were each discussed in one study. Almost all of the included HISs had the capability to integrate data from other systems. Twelve studies did not describe system features. Details of the HIS features and reported benefits are provided in S2 File .

5.2 Impacts on patient flow measures

Table 5 provides a summary of how key patient flow measures were grouped into three categories based on Donabedian model [ 19 ] and the number of studies that included these measures. Details of the included studies and HISs’ impacts on patient flow measures are provided in S3 File , Characteristics of all included studies and their findings.

https://doi.org/10.1371/journal.pone.0274493.t005

Impacts on outcome measures.

Outcomes measures were the most studied measures in the included papers. This is not surprising because health outcomes are the end products of care and the target of health interventions. Studies examined two main types of outcome measures: individual outcomes and organisational outcomes. Almost all studies focused on individual outcome measures in which time-related measures included LOS (25), waiting time (13), treatment time (6), test turnaround time (TAT) (6), and boarding time (2). The effects of HISs on these time related measures were mixed. With regard to LOS, following the use of HISs: 14 studies [ 22 – 25 , 29 , 32 , 33 , 36 , 38 , 39 , 41 , 43 , 45 , 51 ] reported a decrease in LOS, 7 studies [ 9 , 52 – 55 , 57 , 62 ] reported an increased LOS and 4 studies [ 58 – 61 ] found no difference. While most of these studies measured LOS in the ED, five studies [ 25 , 39 , 41 , 43 , 45 ] measured inpatient LOS and two studies [ 23 , 59 ] reported changes in patient LOS at paediatrics centres. The ED LOS was not consistently defined. ED LOS was defined as the difference between ED exit time and the recorded arrival time [ 52 ]. Whereas some studies [ 22 , 59 ] calculated detailed components which constitute the total LOS including time from arrival to triage, arrival to doctor, doctor to disposition, most other studies just reported the mean LOS.

Similarly, 14 studies reported impacts of HISs on waiting time. The results were mixed with 10 positive changes (reduction in waiting time), 2 negative and one with no statistically significant difference. Waiting time measures included waiting for the doctor, waiting for medical treatment, waiting for consultation and for examination. Three studies [ 43 , 58 , 59 ] examined impacts of EHRs on patients waiting for doctor time. In one study [ 59 ], investigators measured the mean patient flow time in a paediatric practice in the USA and found that although the mean patient flow time increased from 56.24 min to 81.43 min one month after the EHR implementation and to 64.60 min 12 months later, patients’ waiting time (check-in to front desk and front desk to triage) actually dropped down by 1.51 and 9.33 min. Their findings suggested the EHR led to more positive results than negative because it reduced waiting for administrative works, allowing more time to be spent on treatment activities. Two studies [ 54 , 56 ] reported negative impacts of HIS on the waiting time of ED patients. Gray and Fernandes [ 54 ] examined the adoption of CPOE in an ED in London Health Sciences Centre with around 100,000 patients per year to determine that CPOE caused an average increase of 5 min in waiting time. A more significant increase in waiting time from 40 to 78 min was observed in a 54,000 patient-per-year ED with the EMR system by Mohan, Bishop, and Mallows [ 56 ].

Treatment time is an important component of LOS and it directly influences health outcomes. However, in this review, we could only identify six studies that used this measure to assess the effectiveness of HIS. Unfortunately, these studies did not provide detailed explanation how the HIS affected treatment time. Three studies [ 22 , 23 , 44 ] found that health providers reduced treatment time when using an ED information system and a patient tracking system for their practice. The patient tracking system was used in a paediatric centre with 24,000 visits annually and it reduced the time of faculty paediatricians spent in Exam room from 11.33 to 6.53 min [ 23 ]. Meanwhile Baumlin et al. [ 22 ] determined a dramatic decrease by 1.90 h in the doctor-to-disposition time after an ED information system was implemented. Two studies about the EHR systems [ 58 , 59 ] and an asthma management system [ 60 ] did not identify a significant difference in treatment caused by the interventions.

TAT is another time-related measure and it was investigated in 6 studies [ 21 , 22 , 38 , 41 , 48 , 51 ]. TAT is defined as the time lapse between when the test is ordered and when the result is available [ 41 ]. Four studies [ 21 , 22 , 39 , 41 ] examined TAT of the radiology examinations and laboratory results; one study [ 48 ] investigated TAT of housekeeping services and one study [ 51 ] reported pathology examinations. All of the studies reported impressive reductions in TAT after the implementation of a HIS. For example, Nitrosi et al. [ 41 ] noted a decrease in the mean chest exam TAT from 33.9 to 9.62 h.

Finally, boarding time is an important patient flow measure that is often referred to as access block or bed block and it is a main patient flow problem [ 63 ]. Two studies [ 22 , 52 ] examined this measure although Pyron and Carter-Templeton [ 43 ] investigated provider discharge-to-nurse discharge time, which can be related to boarding time, but they did not explain or describe how this measure was calculated. Baumlin et al. [ 22 ] reported that the use of an ED information system reduced boarding time for the patient by 28% from 6.77 h to 4.90 h. By contrast, Feblowitz et al. [ 52 ] noticed an increase in the mean boarding time per patient from 211.2 min to 221.4 min in the long term (1 year after the implementation of an electronic documentation system) in an ED. However, neither study provided a causal relationship between HIS implementation and the changes in boarding time.

In addition to time-related measures, included studies also investigated other important individual outcomes including: four studies on the percentage of patients who left without being seen (LWBS), three studies on patient satisfaction, one each for mortality rate, and readmission rate. LWBS was studied in the ED setting. Three studies [ 54 , 56 , 61 ] reported increases of LWBS percentage with the most significant increase being reported in the study about a CPOE system from 24.3% to 42.0% [ 54 ], while Jensen [ 33 ] determined a reduction of 7.6%, but this study did not provide any subjective evidence. Patient satisfaction was measured in three studies with one positive result [ 35 ], one negative [ 62 ], and one neutral result [ 58 ]. The EHR system was found to reduce ED patient satisfaction because it increased LOS; however, the negative impacts lasted for only eight weeks before returning to the baseline from before the intervention implementation [ 62 ]. One study reported that the use of a patient discharging system [ 37 ] was associated with improvement in LOS for early discharge patients without higher rates of readmission. In another study, Inokuchi et al. [ 32 ] investigated the impacts of a newly-developed EMR system on the mortality rate at 28 days after hospitalisation and found no changes resulting from the intervention, which is a positive outcome.

Apart from the patient-related outcome measures above, studies also examined organisational outcomes including four studies about hospital costs, and one each for staff satisfaction, film saving and staff stress level. Three studies [ 33 , 47 , 53 ] calculated the reduction in LOS as hospital cost saving. The first study found that EMR systems were associated with 5.9% to 10.3% higher cost per discharge while with the implementation of a patient flow system, Jensen [ 33 ] reported that the hospital saved between 67,800 and 214,200 USD. The transition from traditional into digital radiology room through the implementation of a PACS system was found to reduce 90% of the film [ 41 ]. Staff satisfaction was examined in a study [ 49 ] which reported positive outcomes after the implementation of an electronic prescribing system. In a study about a workflow management system, Li et al. [ 35 ] found that the intervention greatly improved sonographers’ productivity while reducing their stress level, which was measured by a 5-point Likert scale. Measures related to organisational outcome are an interesting part of the HIS literature because most of the evidence in patient flow intervention focused primarily on patient-related outcome measures.

Impacts on process measures.

Studies examined a variety of measures related to staff productivity in clinical processes, and medical guideline adherence. Four studies examined the effect of HIS on the number of medical services performed by the staff. Two studies showed increased number of surgeries [ 31 ] and radiology tests [ 41 ]. Nitrosi and colleagues [ 41 ] studied the impacts of a PACS and found that the number of imaging procedures increased by 7% although the number of technologies and radiologists remained unchanged. An increase of 37% in the number of surgeries after a surgery information system was observed by Gomes and Lapao [ 31 ]. However, EHR implementation was found to decrease the number of patients that clinical staff could see [ 55 ] although the negative impact was only temporary and resolved three months post-implementation. The implementation of HIS did not change the medical guideline adherence of the staff when they are already providing care that adheres to the relevant guideline [ 60 ]. The number of patients seen per shift by medical staff was measured by Mohan, Bishop, and Mallows [ 56 ] in an investigation of the effectiveness of an EMR system and the impact was negative. Mathews et al. [ 37 ] and Tran et al. [ 49 ] both measured the impact of HIS on the percentage of early discharged patients and show positive outcomes. Finally, Tran et al. [ 49 ] reported an increase in the number of prescriptions prepared the day before discharge as a positive effect of a prescription system.

Impacts on structure measures.

Evidence on the impact of HIS on structure measures was more limited than data on process and outcome measures. Six of the 44 studies reported some data on structure measures. These structure measures are related to flow problems facing healthcare organisations and they were studied in ED settings. Almost all of the six studies reported positive impacts of HIS on these structure measures including the number of patient diversions and the number of ED patients with LOS over 12h [ 33 ], the proportion of early discharged patients [ 37 ], ED avoidance percentage [ 38 ], and the number and proportion of access blocks and hospital occupancy rates [ 27 ]. The study of Crilly et al. [ 27 ] found that the number of access blocks and hospital occupancy rates did not change after the implementation of a patient admission prediction system, but this is actually a positive outcome because the hospital presentations were increasing during the study period. By contrast, in one study, Mohan, Bishop, and Mallows [ 56 ] investigated the effect of an EMR system on the percentage of ambulance offloading time of more than 30 min which is also known as ambulance boarding and they found that the percentage went up from 10.5% to 13.3%.

5.3 Quality assessment of the included studies

Using the GRADE approach to assess the quality level of the evidence through their study design, two RCT studies [ 32 , 60 ] were assessed as high quality and 38 observational studies using retrospective or prospective data were rated low quality. Four studies including three expert opinions and one stating improvement without figures did not provide objective evidence and they were rated ‘0’ (the lowest rating). Two studies using multi-method design with both qualitative and quantitative components were rated low quality, based on the assessment of their quantitative component. Details of the quality assessment are provided in S5 File , Quality assessment of the included studies.

6. Discussion

6.1 summary of key findings.

This systematic review summarised and synthesised evidence from studies about HISs that have been applied to improve patient flow in both inpatient and outpatient settings. Overall, 33 out of the 44 included studies reported positive impacts of HIS on patient flow measures while 7 determined negative impacts, and 4 studies reported no significant impact. Half of the studies focused on patient flow at the departmental level; however, 18 studies reported the impact of HIS on the hospital-wide level and 4 studies reported network-wide impacts on HIS. Healthcare settings adopted at least 17 types of HIS to address patient flow problems and improve care efficiency.

We found that core features of the HIS interventions, that affected patient flow, included patient tracking, documentation management, order entry, patient registration, bed management, decision support, discharge management, prescription management and patient flow reporting. When it comes to the impacts of HIS on specific patient flow measures, most studies focused on outcome measures at both: patient (individual) and organisational level. Changes in individual outcomes were evident in time-related measures including length of stay (LOS), waiting time, treatment time, test turnaround time (TAT), and boarding time, and other measures such as left without being seen and patient satisfaction. Organisational outcome measures were noted in hospital costs, film saving, staff satisfaction, and staff stress level. Process measures and structure measures, although less examined in the included studies than outcome measures, are important measures. While process measures related to staff productivity and guideline adherence, structure measures included flow problems such as patient diversion, access block, hospital occupancy, ambulance offloading time, and ED patient with LOS over 12 h.

Noted HIS benefits included improvements in various patient flow aspects: access to needed information, staff communication, care coordination, work processes, and decision support. Ineffective interaction between hospital units is one of the most common causes of poor patient flow [ 64 ]. HISs were effective in fostering care coordination and collaboration among multidisciplinary teams by imposing a common set of flow key performance indicators (KPIs), and metrics into practice. The application of these common, sometimes “simple”, rules help develop common understandings and it is a key to governing complex systems [ 12 ]. In addition, the involvement of all team members in the development process of HIS is critical to achieving shared understandings. In this review, the effectiveness of HIS in care coordination was evident in many care processes such as patient check-in [ 59 ], elective waiting list management [ 31 ], bed management [ 36 , 48 ], ambulance distribution [ 38 ], and discharge [ 36 , 37 , 49 ]. By integrating information from multiple siloed systems, patient flow-related HIS reduce the time needed for care providers to acquire sufficient information to make critical decisions. Real-time data, notifications, and alerts functions are key features that enabled users to get the most updated information in a timely manner. The development of HISs often included redesigning the embedded care process or processes, an opportunity for care settings to eliminate redundant steps and apply best practices to their care processes. Streamlined work processes helped reduce waiting time for test results and free up staff from redundant information [ 22 , 34 ]. In addition, high degree of automation resulting from the HIS adoption contributed to the reduction in human errors, which can cause medical and health complications, and cognitive workload for hospital staff as they were not required to remember complex rules.

However, it still remains unclear how and why these interventions produced or did not produce positive or negative impacts. Most of the included studies were observational, before and after studies, making it challenging to establish the cause and effect link between HIS interventions and changes in patient flow measures. This has important implications because without a thorough understanding of why and how HIS affected patient flow, it is difficult to generalise the findings to other healthcare settings.

6.2 Strength and limitations

To date, several systematic reviews have been conducted to investigate interventions addressing patient flow problems; however, they focused mostly on operational methods such as triage, fast track, streaming [ 2 ]. Systematic reviews on the impact of HIS on patient flow are small in number and limited to single specific systems such as CPOE [ 5 ]. To the best of our knowledge, this review was the first attempt to evaluate a broad range of HISs applied in patient flow management. The novelty of this review lies in its research aim, and inclusion criteria, unlike most previous reviews on patient flow interventions, here, we included different types of HISs and broad scope of healthcare settings including departmental, organisational and network levels. Our findings provide different stakeholders with important insights for their implementation and adoption of HISs to optimise patient flow.

However, this review has several limitations. The first relates to the heterogeneous nature of the search terminology and the quantity and scope of the evidence. Although we conducted a comprehensive search, in many important domains, we could only identify a limited number of studies. The second limitation relates to the synthesis of varied outcomes and a broad range of HISs. In this review, we attempted to address this limitation by adopting analytic frameworks, which were based on domain experts and published literature, and by synthesising not only the health information system but also their functional features. Third, descriptions of the HIS interventions and the implementation process were often very limited, making it challenging to fully assess the system features and associated benefits. Fourth, most of the included studies are before-and-after, observational studies and therefore understanding of how and why HISs affected patient flow outcomes was very limited. Finally, we decided not to include a meta-analysis because of the diverse, heterogeneous outcomes reported in the included studies. A meta-analysis, in this case, is inappropriate and can be more of a hindrance than a help [ 65 ].

6.3 Implications for patient flow management practice

Hospitals and care centres have implemented several interventions to tackle patient flow problems to deliver optimal care. However, up until recently, most of the efforts were focused on addressing ED overcrowding problems [ 3 , 66 , 67 ]. It is evident in the literature that focusing solely on ED problems will not likely achieve optimal flow because EDs do not operate separately, rather they are part of an interconnected system [ 68 ]. Therefore, literature has urged that patient flow needs to be viewed from the whole system of care viewpoint and called for a shift from ED-focused to system-wide or hospital-wide interventions [ 12 , 69 ]. However, the gap between understanding the problem and having solutions to solve the problem seems still far. For example, even a holistic approach like Lean healthcare was still attached to a specific department or care process [ 4 ]. The frequently reported intervention to improve inpatient flow was implementing a specialised staff or team to coordinate patient flow across hospital units; however, the solution still posed significant challenges [ 3 ]. This systematic review found that apart from 22 studies focusing on department level, many studies reported hospital-wide or even network-wide level. HISs’ potential to address patient flow at the hospital-wide level were noted in their ability to improve communication between multidisciplinary teams [ 25 , 36 ], enhance care coordination [ 36 , 49 ], improve access to needed information [ 41 , 43 ], and streamline care processes [ 25 , 59 ]. One of the prominent causes of admission bottleneck is inefficient discharges [ 68 ] because any delays in inpatient discharge will increase hospital occupancy and ED overcrowding [ 69 ]. HISs showed their effectiveness in discharge prediction and established standardised discharge criteria for improving the discharge process [ 37 ]. These “medical-readiness criteria” have been shown to facilitate efficient planning and care coordination [ 37 ]. Addressing patient flow problems sometimes goes beyond hospital scope to a higher level of network-wide scope. A dashboard system was developed in Alberta, Canada to address ED overcrowding by coordinating emergency services between different emergency rooms within the region [ 9 ]. HISs were also used within a network of different hospitals to address the need for rehabilitation care services and improve the consultation process [ 42 ]. HISs can be scalable to a nationwide level to reduce waiting time for elective surgical patients [ 31 ]. By providing information about capacity, occupancy and demand, they can be highly effective in addressing the mismatch between supply and demand to improve patient flow.

6.4 Implications for future research

Moving forward, this review suggests important areas for future research in the field. First, additional studies need to explore barriers and facilitators of the HISs related to patient flow management. This will offer valuable implications for healthcare organisations to drive their HIS project to success and derive the most from their investment. Second, learning about the effectiveness of HISs on patient flow and associated factor during the post-implementation phase could help to advance the field. This is because of the evolutionary nature of HIS development in which factors associated with the application of HIS can be captured and used as lessons learned for the next evolution of the HIS [ 70 ]. In this review, only the study of Inokuchi et al. [ 32 ] addressed this topic. Patient flow is often negatively affected during the implementation of HIS because of changes in the workflow and human resources. Although the effect seemed temporary, learning about these periods and associated factors will bring implications for researchers and policymakers when considering the project timeline and expected challenges. Furthermore, although HISs are found to help healthcare organisations address patient flow management areas such as care coordination, timely access to information, and communication barriers, understanding why and how HIS could enhance each of these aspects can be extremely helpful. Part of the reasons to explain this is because most of the selected studies in this review did not include adequate details of the underlining technologies of the HIS interventions such as: what are the technical supports and architectures, what are the input and output data, or how the output data are represented in the user interface. The lack of technical specifications of the HIS interventions made it hard to fully comprehend how they contributed to the changes in patient flow management. Finally, during the last two years, the COVID-19 pandemic has completely disrupted patient flow management all over the world. Yet, we could not identify any studies on the role of HIS in remedying the impacts of the pandemic on patient flow.

7. Conclusion

Health information systems (HISs) provide clear benefits in managing patient flow over traditional paper record management systems. However, without a systematic evaluation and summary of the available evidence, stakeholders interested in adopting HISs in healthcare settings for patient low management might be lost in the ocean of information. This is especially true when it comes to the questions of what HIS to invest, what benefits and impacts to expect and how to maximize the values from their investment. This systematic review has revealed an increasing interest in adopting HIS to address patient flow issues in healthcare settings in the last decade. HISs can be effective solutions for patient flow management at the organisational-wide or even network-wide levels due to their great scalability and integrability. HISs were often found to be effective in improving communication and care coordination between team members, providing timely access to high quality information for decision making, and streamlining care processes. These improvements contributed to more efficient patient flow throughout the care continuum. As more healthcare and health-related data are generated, there are great opportunities for HISs such as decision support systems, and dashboard systems to help healthcare organisations harness the power of big-data analytics and achieve optimal patient flow. This review shows that HISs can impact various aspects of patient flow at different levels of care; however, how and why they delivered the impacts will require further research.

Supporting information

S1 file. search strategy..

https://doi.org/10.1371/journal.pone.0274493.s001

S2 File. Reported benefits of HISs on patient flow management.

https://doi.org/10.1371/journal.pone.0274493.s002

S3 File. Table of all included studies and findings.

https://doi.org/10.1371/journal.pone.0274493.s003

S4 File. Example of data extraction form.

https://doi.org/10.1371/journal.pone.0274493.s004

S5 File. Quality assessment of the included studies.

https://doi.org/10.1371/journal.pone.0274493.s005

S6 File. PRISMA checklist.

https://doi.org/10.1371/journal.pone.0274493.s006

Acknowledgments

We would like to thank the Faculty of Information Technology (Monash University) subject librarian, Mario Sos for his great expertise and valuable feedback in developing the search strategy. We are grateful for generous help from Quang H Vo in screening the titles, abstracts and full-text papers in our review. Also, Angela Melder from Monash Centre for Health Research and Implementation, Monash University and Monash Health gave us valuable feedback on the inclusion/exclusion criteria during the screening process.

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Imperiled by Volcanic Eruptions, Iceland Scoops Up Answers From the Deep

Earth scientists are working to determine the course of future lava flows in Iceland’s southwestern corner one bucketful at a time.

Lava from the April 2024 eruptions in the Svartsengi area of the Reykjanes Peninsula, Iceland. Credit...

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Photographs by Gaia Squarci

Text by Robin George Andrews

• Aug. 30, 2024

Iceland is a citadel built from volcanic fire. Its residents are familiar with their country’s frequent volcanic eruptions, most of which are more beautiful than bothersome. But in 2021, the nation was left awe-struck when part of a long-dormant corner of the island burst into magmatic flames, starting a fire that could burn for decades to come.

The first eruption came as a shock. But today, lava regularly snaking across the landscape is the new normal . “This was so strange at the beginning,” said Rebekka Hlin Runarsdottir , a geologist and technician at the University of Iceland. “And now, we’re just living in this reality.”

It’s been 800 years since the southwestern Reykjanes Peninsula was host to active streams of lava. Hoping to find out why volcanism has re-emerged there, scientists are snatching samples of molten rock whenever it bleeds out of the crust.

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