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A. Current healthcare information systems environment
The Role of Information Systems in Healthcare: Current Research and Future Trends
Information systems have great potential to reduce healthcare costs and improve outcomes. The purpose of this special issue is to offer a forum for theory-driven research that explores the role of IS in the delivery of healthcare in its diverse organizational and regulatory settings. \/Ve identify six theoretically distinctive elements of the healthcare context and d iscuss how these elements increase the motivation for, and the salience of, the research results reported in the nine papers comprising this special issue. 'vVe also provide recommendations for future IS research focusing on the implications of technology-driven advances in three areas: social media,evidence-based medicine, and personalized medicine.
The Digital Transformation of Healthcare: Current Status and the Road Ahead
As the United States expends extraordinary efforts toward the digitization of its health-care system, and as policy makers across the globe look to information technology (IT) as a means of making health-care systems safer, more affordable, and more accessible, a rare and remarkable opportunity has emerged for the information systems research community to leverage its in-depth knowledge to both advance theory and influence practice and policy. Although health IT (HIT) has tremendous potential to improve quality and reduce costs in healthcare, significant challenges need to be overcome to fully realize this potential. In this commentary, we survey the landscape of existing studies on HIT to provide an overview of the current status of HIT research. We
then identify three major areas that warrant further research: (1) HIT design, implementation, and meaningful use; (2) measurement and quantification of HIT payoff and impact; and (3) extending the traditional realm of HIT. We discuss specific research questions in each domain and suggest appropriate methods to approach them.
We encourage information systems scholars to become active participants in the global discourse on health-care transformation through IT.
B. Healthcare data and information
5 Reasons Healthcare Data Is Unique and Difficult to Measure
Healthcare data tends toreside in multiple places.From different source systems, like EMRs or HR software, to different departments, like radiology or pharmacy.
The data comes from all over the organization.
Data, Information, Knowledge: A Healthcare Enterprise Case Study
An efficient, integrated health services delivery enterprise requires the ability to coordinate service delivery across the provider network and avoid duplic
ation of services. It must be able to associate relevant clinical information with patients regardless of which facility delivered the services. There are significant challenges in collecting, organizing, and ex
tracting value from data collected in the course of providing healthcare. This paper follows a large urban public healthcare enterprise in its attempts to address some of these challenges. Using a case-study
methodology, the paper shows how information technology (IT) can help a healthcare organization derive improved information and generate knowledge
from data stored in disjoint systems.
Personal health records: Consumer attitudes toward privacy and security of their personal health information
Personal health record (PHR) systems are a subject of intense interest in the move to improve healthcare
availability and quality. Although several vendors continue to put forward PHR systems, user-centered
design research has lagged, and it has not been clear what features are important to prospective PHR users.
Here, we report on a user-centered design study that combines qualitative and quantitative approaches to
investigate several dimensions relevant to PHR design and examine the effect of health status on user
needs. The results indicate that health status, especially disability and chronic illness, is relevant to PHR design.
Further, the results provide empirical evidence about the role of privacy and security in users’ attitudes
toward PHR use. The exact nature of these attitudes differs from widely held perceptions about consumer
values in healthcare information management.
Why Healthcare Data is Difficult
Computer Medical Databases: The First Six Decades (1950-2010)
Computer Medical Databases: The First Six Decades (1950-2010)
This series is directed to healthcare professionals leading the transformation of healthcare by using information and knowledge. For over 20 years, Health
Informatics has offered a broad range of titles: some address specific professions such as nursing, medicine, and health administration; others cover special areas of practice such as trauma and radiology; still other books in the series focus on
interdisciplinary issues, such as the computer based patient record, electronic health records, and net- worked healthcare systems. Editors and authors, eminent experts in their fields, offer their accounts of innovations in health informatics. Increasingly, these accounts go beyond hardware and software to address the role of information in influencing the transformation of healthcare delivery systems around the world. The series also increasingly focuses on the users of the information and systems: the organizational, behavioral, and societal changes that accompany the diffusion of information technology in health services environments. Developments in healthcare delivery are constant; in recent years, bioinformatics has emerged as a new field in health informatics to support emerging and ongoing
developments in molecular biology. At the same time, further evolution of the field of health informatics is reflected in the introduction of concepts at the macro or health systems delivery level with major national initiatives related to electronic health records (EHR), data standards, and public health informatics. These changes will continue to shape health services in the twenty-fi rst century. By making full and creative use of the technology to tame data and to transform
information, Health Informatics will foster the development and use of new knowledgein healthcare.
Kathryn J. Hannah
Marion J. Ball
C. Patient-specific data and information
Meaningful use of patient-centric health records for healthcare transformation.
Healthcare transformation through the use of information technologies is partly dependent on effectively applying the most up-to-date knowledge to the complete representation of the patient's past medical history at the point of care. In order for health knowledge to be effectively used, patient information should be sufficiently detailed, and more importantly, the semantics of the data should be made explicit and machine processable. Often, the semantics of data are represented implicitly and are hidden in unstructured and disconnected descriptions of the data. Alternatively, they may be known to human experts, such as the researchers or caregivers involved in the generation of that data. Predefined schemas of health information systems are insufficient; it is extremely important to explicitly represent the patient-specific context of each discrete data item and how it relates to other data items (e.g., indications and outcomes of an operation), as well as how it fits into the entire health history of an individual. Dispersed and disparate medical records of a patient are often inconsistent and incoherent. An independent patient-centric electronic health record may provide an explicit, coherent, and complete representation of contextual data. This paper reviews healthcare transformations, with consideration of an independent health record. [ABSTRACT FROM AUTHOR]
Assessing the accuracy of an inter-institutional automated patient-specific health problem list
In its second report 'Crossing the Quality Chasm'[1], the Institute of Medicine identified patient safety and free flow of information as key issues to improve care. Functionalities of electronic health records (EHR) such as electronic prescribing[2, 3, 4, 5, 6], clinical decision support systems[7] and automated reminders [8] have been shown to be effective in improving patient safety and chronic disease management. Timely access to accurate and complete information on a person's health problems or diseases is critical to detecting drug interactions [9], preventing prescribing problems [10] and developing decision support systems based on disease-specific guidelines [11, 12]. Indeed, diseases or health problems have been shown to be involved in drug interactions in more than 20% of patients in an emergency department [9] and in 6.5% of prescribing problems generated by family physicians[13]. Thus, health problem lists that are coded to enable automated surveillance and decision-support [13, 14] are a key component of the Electronic Medical Record (EMR) and are instrumental in the development of decision systems that encourage best practices and optimal patient safety.
Context-based electronic health record: toward patient specific healthcare
Due to the increasingly data-intensive clinical environment,physicians now have unprecedented access to detailed
clinical information from a multitude of sources. However, applying
this information to guide medical decisions for a specific patient case remains challenging. One issue is related to presenting information to the practitioner: displaying a large (irrelevant) amount of information often leads to information overload. Next-generation interfaces for the electronic health record (EHR) should not only
make patient data easily searchable and accessible, but also synthesize fragments of evidence documented in the entire record to
understand the etiology of a disease and its clinical manifestation in individual patients. In this paper, we describe our efforts toward
creating a context-based EHR, which employs biomedical ontologies and (graphical) disease models as sources of domain knowledge
to identify relevant parts of the record to display. We hypothesize that knowledge (e.g., variables, relationships) from these sources
can be used to standardize, annotate, and contextualize information from the patient record, improving access to relevant parts
of the record and informing medical decision making. To achieve this goal, we describe a framework that aggregates and extracts
findings and attributes from free-text clinical reports, maps findings to concepts in available knowledge sources, and generates a tailored presentation of the record based on the information needs of the user. We have implemented this framework in a system
called Adaptive EHR, demonstrating its capabilities to present and synthesize information from neurooncology patients. This paper highlights the challenges and potential applications of leveraging disease models to improve the access, integration, and interpretation of clinical patient data.
Electronic Health Records
Clinical care increasingly requires healthcare professionals to access patient record
information that may be distributed across multiple sites, held in a variety of paper
and electronic formats, and represented as mixtures of narrative, structured, coded and
multimedia entries. A longitudinal person-centred electronic health record (EHR) is a
much-anticipated solution to this problem, but the challenge of providing clinicians of
any profession or speciality with an integrated view of the complete health and
healthcare history of each patient under their care has so far proved difficult to meet.
This need is now widely recognised to be a major obstacle to the safe and effective
delivery of health services, by clinical professions, by health service organisations and
by governments internationally.
Integrated Health Management: The Patient-Centred Future of Demand Management.
Patients now have a more active role in medical decisions than ever before. Their growing participation has influenced the health industry enormously, and is undoubtedly an irreversible trend. With access to abundant health information, patients are more informed about disease, diagnosis, and treatment options. Demand management supports patients by encouraging and enabling appropriate use of this information by using decision and self-management support. Demand management call centres also integrate information from other sources, and measure and report the outcomes of care. An effective demand management programme enhances a physician's practice by helping patients make use of relevant information and accomplish the directives for care. Physicians also benefit from increasingly efficient communication technologies that allow electronic transfer of ‘real-time’ patient care data. Thus, the demand management programme becomes an essential liaison between patient and physician rather than an unwanted interloper. Moreover, involving physicians in the development, implementation, and management of the demand management programme will promote acceptance and cooperation. Transcending the boundaries of their original design, demand management programmes have expanded their utility by providing non-clinical customer services and by reaching out to individuals who are most likely to benefit from support. Through inbound and outbound telephonic exchange, the demand management programme has become an excellent repository for collecting and consolidating patient-specific data that can be used to monitor health status, influence health behaviours and track outcomes. Demand management may soon become the fundamental backbone of integrated health management's web of coordinated data streaming from multiple sources, delivering information where and when it will be used most effectively, and ensuring the programme's continuing focus on the patient. [ABSTRACT FROM AUTHOR]
D. Aggregate data and information
Aggregate health data in the United States: Steps toward a public good
The rise of electronic medical records promotes the collection and aggregation of medical data. These data have tremendous potential utility for health policy and public health; yet there are gaps in the scholarly literature. No articles in the medical or legal literature have mapped the “information flows” from patient to database, and commentary has focused more on privacy than on data’s social value and incentives for production. Utilizing short case studies of data flows, I show that ample data exist, much of them are available online through government websites or hospital trade associations. However, available information comes from billing records rather than medical records. Turning to legal and policy recommendations for better provision, I note that weak intellectual property law has ironically led to stronger control over health data through private contracts and technological barriers, as these methods of protection lack any exceptions for noncommercial use. I conclude with a series of policy proposals to make data more available.
