The Advanced Visualization Branch of the National Institute of Nursing Research uses computer technologies to study information visualization in support of self-care management. Advanced technologies, such as immersive virtual reality (IVR), afford researchers the opportunity to study health information visualization where user-initiated information search in visually dense settings precedes acquisition, interpretation, and use. While IVR has broad applicability in healthcare, we chose to target lay people managing chronic disease because of the growing unmet need to translate clinical recommendations into everyday behaviors. To explore how lay people seek, acquire, and interpret health information in everyday settings, we developed an IVR grocery store. In this environment, a person can locate food products, read and compare nutrition labels, and use information to make food selections. The goal of this perspective is to introduce the opportunities afforded by IVR to both present and study health information visualization and to highlight critical design considerations.

Suzanne (Sue) Bakken, RN, PhD and Editor-in-Chief of the Journal of the American Medical Informatics Association (JAMIA), has been selected to receive the 2023 Morris F. Collen Award from the American College of Medical Informatics to honor her lifetime contributions to the field of biomedical informatics. Bakken has advanced the field by integrating leading-edge research with training successive generations of informaticians and by working with underserved communities to bring the results of research to people’s lives. We have created an on-line collection of selected papers from among Bakken’s publications in JAMIA that is available at academic.oup.com/jamia/pages/morris-collen-award-2023. The first paper in the collection appeared in the inaugural issue of JAMIA and reported her analysis of terms used by nurses to describe patient problems as a test of the feasibility of using SNOMED III as a nursing data standard.1 This article exhibits the hallmarks of her work: rigorous grounding in existing frameworks, in this case, a comparative review of healthcare classification schemes and published evaluation studies related to their use to represent clinical data; explicit research questions; appropriate use of both qualitative and quantitative analysis; and discussion including an actionable path forward for the field. The collection provides a glimpse of her progression from first author researcher1–6 to senior author with a mentee as first author,7–15 as well as the evolution of her research foci.

After 25 years of service to the American Medical Informatics Association (AMIA), Ms Karen Greenwood, the Executive Vice President and Chief Operating Officer, is leaving the organization. In this perspective, we reflect on her accomplishments and her effect on the organization and the field of informatics nationally and globally. We also express our appreciation and gratitude for Ms Greenwood's role at AMIA.

Ensuring that federally funded health research keeps pace with the explosion of health data depends on better information technology (IT), access to high-quality electronic health data, and supportive policies. Because it prominently funds and conducts health research, the U.S. federal government needs health IT to rapidly evolve and has the ability to drive that evolution. The Office of the National Coordinator for Health Information Technology developed the National Health IT Priorities for Research: A Policy and Development Agenda (the Agenda) that identifies health IT priorities for research in consultation with relevant federal agencies. This article describes support for the Agenda from the Food and Drug Administration, the National Institutes of Health, and the Veterans Health Administration. Advancing the Agenda will benefit these agencies and support their missions as well as the entire ecosystem leveraging the health IT infrastructure or using data from health IT systems for research.

Big data and data science investigations hold great promise for making efficient use of data generated in the course of daily life: from social media transactions, news, and a variety of apps used by a large portion of the world’s population, including data generated for health care and life sciences research. Data science brings new insights when large-scale datasets are brought together to characterize and address complex problems. The past decade has seen a plethora of federal and private investments in biomedical data science collection, organization, and analysis, including the National Institutes of Health’s Big Data to Knowledge program, the Patient-Centered Outcomes Research Institute’s PCORnet, and investments from various industries. The work is maturing and interesting, and exciting results are emerging. Biomedical data science offers new and powerful tools to better understand health and disease through insights gleaned from data. Linking data science advances with knowledge representation and clinical information understanding, which have been traditional topics in the biomedical informatics field since its early days, has the potential to accelerate data-driven discovery. Biomedical informatics has also been addressing data-driven discovery. However, until this decade, examples where big data were available for this type of pursuit were limited. Biomedical informatics has thus evolved and overlaps significantly with biomedical data science, the subfield of data science that is concerned with discoveries using primarily clinical and other health-relevant data. All data science investigations must address important and interesting questions that are relevant to the areas they are applied to, have access to comprehensible datasets, and devise and apply methods robust enough to cope with complex unstructured observations.

A basic premise of macroergonomic theory is that better physical and psychological outcomes and reduced unintended consequences are achieved when there is alignment between a technology and the user’s work system. The user’s work system is defined as the social subsystem, technical subsystem, and the external environment within which work is performed. Cultural context has been conceptualized as part of the external environment. Thus, from a theoretical viewpoint, creating technology that is aligned with users’ cultural contexts will result in better performance outcomes. The need to align with cultural context is particularly important for technologies such as consumer health information technology, which are intended for use within the naturalistic spaces of patients’ homes and communities. Traditional means of accounting for cultural context in the human factors and consumer health informatics literatures are narrow and unlikely to capture the potential richness and complexity of patients’ cultural contexts. The case study presented here sought to understand cultural context from a patient perspective. Eighteen patients with type 2 diabetes were engaged in a series of interviews about their health information communication practices, their cultural contexts, and the relationships between these. Participants identified a wide range of cultural identities comprising their cultural contexts, including race, ethnicity, nationality, experience, religion, and socioeconomic status. They also identified multiple ways in which cultural identity may be operationalized; qualitative content analysis was used to group these into three main themes: experience (ways in which culture is learned), manifestation (ways in which culture is exhibited), structure (ways in which culture is a social organization or system). Across participants, each of these operationalizations was perceived as influencing health information communication practices. Consequently, the findings suggest that the fields of human factors and consumer health informatics must reconceptualize users’ cultural contexts as encompassing a wider range of identities and as neither constant nor stable. Rather, cultural contexts are situation dependent, are subject to interpretation, and vary across individuals. Such a conclusion implies that existing approaches of aligning specific technologies with specific cultural identities may no longer be appropriate nor scalable. Instead, a more feasible alternative may be to meet the needs of individuals embedded in multiple cultural contexts simultaneously while also enabling users to self-select salient attributes of the technology.

The field of biomedical informatics experienced a productive 2015 in terms of research. In order to highlight the accomplishments of that research, elicit trends, and identify shortcomings at a macro level, a 19-person team conducted an extensive review of the literature in clinical and consumer informatics. The result of this process included a year-in-review presentation at the American Medical Informatics Association Annual Symposium and a written report (see supplemental data). Key findings are detailed in the report and summarized here. This article organizes the clinical and consumer health informatics research from 2015 under 3 themes: the electronic health record (EHR), the learning health system (LHS), and consumer engagement. Key findings include the following: (1) There are significant advances in establishing policies for EHR feature implementation, but increased interoperability is necessary for these to gain traction. (2) Decision support systems improve practice behaviors, but evidence of their impact on clinical outcomes is still lacking. (3) Progress in natural language processing (NLP) suggests that we are approaching but have not yet achieved truly interactive NLP systems. (4) Prediction models are becoming more robust but remain hampered by the lack of interoperable clinical data records. (5) Consumers can and will use mobile applications for improved engagement, yet EHR integration remains elusive.

In 20 years the National Library of Medicine (NLM) will enter its third century of service to the nation. From a small bookshelf in the office of an army surgeon to a dynamic suite of resources for discovery and care, the NLM assures that the information needed for discovery and care is available where needed, when needed, and, increasingly, in the format needed. This week I begin my tenure as the 19th appointed director of the NLM. I am using this opportunity to reach out to colleagues in the biomedical and health informatics community to solicit your guidance about how to invest in and grow the NLM. What kind of library and library services are needed to determine whether a foodborne pathogen is a new species or a known species? How many infrastructure standards, predictive algorithms, natural language processing–guided tumor interpretations, and vocabulary cross-mappings must be in place to support an automated query soliciting the next step in cancer screening for a specific patient in a given community? Is it possible to describe and instantiate the reference genome datasets necessary to characterize zoonotic diseases? Where does a participant in the Precision Medicine Initiative cohort turn to get help with understanding the results of a recently returned genetic assay? Each of these poses significant and important challenges that draw on the current human and technical resources of the NLM. Complex data structures, analytical tools that allow exploration of huge databases, meaningful information presentation, and the infrastructure to support inquiry comprise but a few of the innovative efforts found among the intramural and extramural programs of the NLM. I would like the NLM to provide the answers to all of these questions in an authoritative, timely, human- and/or machine-interpretable manner. For this to happen, all stakeholders, everywhere, must envision a bold future of data-driven care enabled by a trusted, cost-effective, federated resource. Come along with me and help craft this third-century vision. What we lay down now will guide investments over the next 20 years, leading up to the launch of the third century. Input is needed now for near-term investments in methodologies and demonstration projects as well as the analytical and retrieval tools necessary to make use of data. To start your thinking, let me share with you some of the advice I’ve already received as we envision a third-century NLM. The push is to “store everything.” Not only is this not possible, it has within it its own limitations. What should be stored? How? Where? Is the cloud the solution? In what ways can patient privacy be preserved as we increasingly can know who you are, not simply because of the presence of personal health information, but because of the configurations of personally unique organization of one’s genome and epigenome? Preprints are necessary to accelerate knowledge discovery, even at the expense of preserving intellectual property rights of discovery. Visions of data sharing, stewardship, and reuse of data must align with presently held ideas and values of reproducibility and rigor. The federal government is the trusted party overseeing research dissemination. How do we conceptualize data as an information resource? It should be possible to apply the same knowledge formalizations used in curating the published literature to effectively curate published datasets. Decisions about data definitions, metadata, and access/authorization rights should remain within the purview of the individual investigator. Think about these questions. Are they presaging critical directions for health and biomedical informatics? What’s missing? What should be emphasized? Here are some other questions I would like to take on: What is the nature of journals in a digital future? How do we preserve the context of individual study reports in a manner similar to volumes of a journal in a world where direct access to a singular article. Importantly, what kind of training is needed not only to build the data science workforce, but also to prepare data-intensive clinical practitioners and data-informed citizens? In addition to fair use and intellectual property protection, what public policy issues should claim the attention of the NLM? I bring to the directorship 30 years of experience in a vibrant biomedical informatics community, where my work spanned the application of game theory to the development of health information exchanges, the alignment of clinical information systems with extant and emerging professional practice models, and the design, deployment, and evolution of specialized computer tools to support self-management and self-care in the home. In my first 90 days, I will work with the NLM Board of Regents to launch a strategic planning process. In addition, I will work with the NIH leadership to foster a sustainable strategy for data science. My other priorities include fostering our education and training initiatives, using the Institute of Medicine report on social and behavioral domains to guide new information models, and meeting key NLM-funded researchers and trainees. In addition, I plan to continue my more than 20-year affiliation with JAMIA as an associate editor for special projects. Crafting a vision for the third-century NLM requires participation from every stakeholder community. The biomedical informatics community brings special knowledge to this discussion, and its members must help guide the evolution of this essential institution. Watch for opportunities to participate, or send me your thoughts directly at [email protected] .

In alignment with a major shift toward patient-centered care as the model for improving care in our health system, informatics is transforming patient-provider relationships and overall care delivery. AMIA's 2013 Health Policy Invitational was focused on examining existing challenges surrounding full engagement of the patient and crafting a research agenda and policy framework encouraging the use of informatics solutions to achieve this goal. The group tackled this challenge from educational, technical, and research perspectives. Recommendations include the need for consumer education regarding rights to data access, the need for consumers to access their health information in real time, and further research on effective methods to engage patients. This paper summarizes the meeting as well as the research agenda and policy recommendations prioritized among the invited experts and stakeholders.

Consistent collection and use of social and behavioral determinants of health can improve clinical care, prevention and general health, patient satisfaction, research, and public health. A recent Institute of Medicine committee defined a panel of 11 domains and 12 measures to be included in electronic health records. Incorporating the panel into practice creates a number of informatics research opportunities as well as challenges. The informatics issues revolve around standardization, efficient collection and review, decision support, and support for research. The informatics community can aid the effort by simultaneously optimizing the collection of the selected measures while also partnering with social science researchers to develop and validate new sources of information about social and behavioral determinants of health.

Large amounts of personal health data are being collected and made available through existing and emerging technological media and tools. While use of these data has significant potential to facilitate research, improve quality of care for individuals and populations, and reduce healthcare costs, many policy-related issues must be addressed before their full value can be realized. These include the need for widely agreed-on data stewardship principles and effective approaches to reduce or eliminate data silos and protect patient privacy. AMIA's 2012 Health Policy Meeting brought together healthcare academics, policy makers, and system stakeholders (including representatives of patient groups) to consider these topics and formulate recommendations. A review of a set of Proposed Principles of Health Data Use led to a set of findings and recommendations, including the assertions that the use of health data should be viewed as a public good and that achieving the broad benefits of this use will require understanding and support from patients.

OBJECTIVE: To describe an analytical framework for quantifying the societal savings and financial consequences of a health information exchange (HIE), and to demonstrate its use in designing pricing policies for sustainable HIEs. MATERIALS AND METHODS: We developed a linear programming model to (1) quantify the financial worth of HIE information to each of its participating institutions and (2) evaluate three HIE pricing policies: fixed-rate annual, charge per visit, and charge per look-up. We considered three desired outcomes of HIE-related emergency care (modeled as parameters): preventing unrequired hospitalizations, reducing duplicate tests, and avoiding emergency department (ED) visits. We applied this framework to 4639 ED encounters over a 12-month period in three large EDs in Milwaukee, Wisconsin, using Medicare/Medicaid claims data, public reports of hospital admissions, published payer mix data, and use data from a not-for-profit regional HIE. RESULTS: For this HIE, data accesses produced net financial gains for all providers and payers. Gains, due to HIE, were more significant for providers with more health maintenance organizations patients. Reducing unrequired hospitalizations and avoiding repeat ED visits were responsible for more than 70% of the savings. The results showed that fixed annual subscriptions can sustain this HIE, while ensuring financial gains to all participants. Sensitivity analysis revealed that the results were robust to uncertainties in modeling parameters. DISCUSSION: Our specific HIE pricing recommendations depend on the unique characteristics of this study population. However, our main contribution is the modeling approach, which is broadly applicable to other populations.

OBJECTIVE: With the advent of personal health records and other patient-focused health technologies, there is a growing need to better understand factors that contribute to acceptance and use of such innovations. In this study, we employed the Unified Theory of Acceptance and Use of Technology as the basis for determining what predicts patients' acceptance (measured by behavioral intention) and perceived effective use of a web-based, interactive self-management innovation among home care patients. DESIGN: Cross-sectional secondary analysis of data from a randomized field study evaluating a technology-assisted home care nursing practice with adults with chronic cardiac disease. MEASUREMENT AND ANALYSIS: A questionnaire was designed based on validated measurement scales from prior research and was completed by 101 participants for measuring the acceptance constructs as part of the parent study protocol. Latent variable modeling with item parceling guided assessment of patients' acceptance. RESULTS: Perceived usefulness accounted for 53.9% of the variability in behavioral intention, the measure of acceptance. Together, perceived usefulness, health care knowledge, and behavioral intention accounted for 68.5% of the variance in perceived effective use. Perceived ease of use and subjective norm indirectly influenced behavioral intention, through perceived usefulness. Perceived ease of use and subjective norm explained 48% of the total variance in perceived usefulness. CONCLUSION: The study demonstrates that perceived usefulness, perceived ease of use, subjective norm, and healthcare knowledge together predict most of the variance in patients' acceptance and self-reported use of the web-based self-management technology.

OBJECTIVE: To develop and validate the Readiness for Implementation Model (RIM). This model predicts a healthcare organization's potential for success in implementing an interactive health communication system (IHCS). The model consists of seven weighted factors, with each factor containing five to seven elements. DESIGN: Two decision-analytic approaches, self-explicated and conjoint analysis, were used to measure the weights of the RIM with a sample of 410 experts. The RIM model with weights was then validated in a prospective study of 25 IHCS implementation cases. MEASUREMENTS: Orthogonal main effects design was used to develop 700 conjoint-analysis profiles, which varied on seven factors. Each of the 410 experts rated the importance and desirability of the factors and their levels, as well as a set of 10 different profiles. For the prospective 25-case validation, three time-repeated measures of the RIM scores were collected for comparison with the implementation outcomes. RESULTS: Two of the seven factors, 'organizational motivation' and 'meeting user needs,' were found to be most important in predicting implementation readiness. No statistically significant difference was found in the predictive validity of the two approaches (self-explicated and conjoint analysis). The RIM was a better predictor for the 1-year implementation outcome than the half-year outcome. LIMITATIONS: The expert sample, the order of the survey tasks, the additive model, and basing the RIM cut-off score on experience are possible limitations of the study. CONCLUSION: The RIM needs to be empirically evaluated in institutions adopting IHCS and sustaining the system in the long term.

As the field of biomedical informatics matures, investigators and systems implementers increasingly rely on theories, models, and frameworks to guide their work. Of these three, theory provides the greatest value to any discipline, because theory provides well-validated pathways to link observed phenomena with foundational knowledge, thus enhancing efficiency and generalizability. Theories are sets of propositional statements that explain, predict, or prescribe the relationship between concepts capable of being tested, verified, or refuted through empirical work. Theories serve to illuminate concepts deemed essential to understanding complex situations, such as why people with AIDS accept an electronic coaching system,1 or predict future states, such as how quickly physicians will adopt electronic health records.2 Reliance on theory demonstrates a level of sophistication in any discipline, and, as such, this increase in attention to theory-driven research and practice is much welcomed in biomedical informatics. So long as an applicable theory or theories exist, the necessary first step in any investigation or implementation should be to select the theory that will guide the endeavor. This is a significant right and responsibility. Each time a researcher or systems implementer selects a theory to guide his or her work, he or she is purposely attending to certain aspects of a given situation, and leaving other aspects in the shadows. This is not to say that the shadowed dimensions of a situation are unimportant, but rather that the particular story that the investigator wishes to tell, or the specific implementation process the implementers want to address, is best characterized by the theory selected. The article by Callen and colleagues3 highlights the importance and value of employing theory when implementing and evaluating clinical information systems (CIS). Resting their arguments on critical contributions from previous investigations of successful and unsuccessful implementations of clinical information systems, the authors argue for careful, systematic considerations of the context within which clinical information systems are implemented, calling for attention to user characteristics, clinical department, and organizational features that influence the process of adoption of clinical information systems. As aptly documented by Callen and colleagues, many theories have proved useful to guiding the design and implementation of clinical information systems and predicting or explaining their consequences. Like health informatics standards, the good thing about theories for CIS implementation is that there are so many to choose from! Some direct CIS implementers select theoretical underpinnings that attend to key actors and early adopters; others choose theories that emphasize critical work flows or institutional policies that inhibit or advance the adoption of clinical information systems applications. Theory serves many purposes in biomedical informatics. Some theories are structural, identifying key elements or players in a given situation. Others are process-focused, highlighting the actions and consequences expected when particular events initiate a sequence of actions. Theories serve to identify key elements of a critical situation, such as a clinical practice environment, which highlight where attention should be paid. Some theories not only address the critical elements of a situation, but also explicate the relationship between predictors and outcomes, for example, the contribution of computerized provider-order entry systems to patient safety goals. The summary provided by Callen and colleagues illustrates the wide range of theories, models, frameworks, and guiding principles that abound in the literature attempting to prescribe, guide, and predict successful CIS implementation. They criticize existing theories as being insufficient to guide CIS implementation, having left too many key ideas in the shadows. Basing their assessment on observations gleaned through interaction with clinicians actually using a special-purpose CIS, Callen and colleagues complete and posit expanding existing sociotechnical theories with attention to characteristics of clinical environment (diversity and differentiation) currently left in the shadows by existing theories. Theories best serve biomedical informatics investigators and clinical information systems implementers when the theories originate from a plausible set of premises, there is a logical congruence between elements, and, most importantly, when they are validated empirically. The utility of any theory applied to CIS implementation is bounded by the scope of the theory itself. While it is tempting to seek an omnibus, complex theory to examine all possible components of a situation, as Callen and colleagues did, it is also worthwhile to select more focused theories that highlight specific phenomena and processes. Selection of theory to guide a study or a systems implementation rests on both scholarly reasoning and artful insight. But, always, theories leave some aspects of the actual unaddressed and unattended to—i.e., standing in the shadows. These ignored aspects still continue to exert influence on the situation, but because of the specific theory's perspective are not considered germane to the understanding of the phenomena of interest. This ‘shadow play’ does not negate the value of the theory, but rather serves as a reminder of the responsibilities for those who select theories that other forces may be at play that interest their phenomena. Biomedical informatics investigators and systems implementers are urged to strengthen the rigor and potential value of their works though judicious selection of theories. Selection of theory to guide a study or a systems implementation rests on both scholarly reasoning and artful insight. Selection rests on the congruence between what the theory highlights, as well as what is left in the shadows. Most importantly, theories that are well validated with empirical work and scholarly review hold the greatest value. While theory-driven research has significant value both for the individual project as well as for extending knowledge in the field, sometimes no suitable theory can be found. In those cases, investigators and implementers may rely on theories external to the biomedical informatics domain (e.g., sociotechnical system theory) or use their project to generate the foundations for new theories that may prove valuable to the field as a whole. We look forward to greater specification and validation of Callen and colleagues' work, demonstrating the contributions of the ideas of diversity and differences to explicating good ways to implement CIS.

Computerized provider order entry (CPOE) systems facilitate safe, effective care for patients by insuring that clinical care directions are communicated in a timely, accurate, and complete manner. Integrating clinical decision support functions into CPOE systems enhances the value of the CPOE systems by incorporating contemporary knowledge and best practice recommendations into the clinical management process. Insuring the quality, accuracy, and relevance of the decision logic integrated within CPOE systems is a sine qua non of safe and effective practice. The special section on CPOE presented within this issue of JAMIA offers practical advice on taking the next steps toward insuring the availability of CPOE systems enriched by decision support. Institutions hoping to deploy decision-support enhanced CPOE systems require evidence to justify acquisition and use of such systems. They require evidence that the CPOE developers have embedded and maintained a sufficient quantity and quality of knowledge upon which to base actionable clinical recommendations, such as prescribing. They need functional tools and strategies to integrate actionable advice into order sets and other decision support venues. Ideally, such order sets first undergo professional vetting and peer review to insure quality and safety, and then “go live” through efficient tools that integrate order sets into user-friendly and effective clinical information systems. Most importantly, pragmatic evidence should demonstrate not only the efficacy of the order sets' recommendations, but also the effectiveness of their actual deployment in clinical care practices. Despite the uneven and incomplete patchwork of existing evidence addressing the safety and efficacy of clinical decision support in CPOE settings, hospitals and other health care delivery systems are faced with a need to act now, basing such decisions on the available evidence. To discuss the state of the art in both CPOE practices and supporting evidence, a group of experts in clinical practice, healthcare informatics, and healthcare safety gathered in San Francisco in June, 2005 at a conference on Computerized Provider Order Entry and Clinical Decision Support. Several of the papers in the special section, Focus on CPOE, in the current issue of JAMIA, report key outcomes from that meeting. The papers provide pragmatic directions for institutions considering deployment of decision-support enhanced CPOE. Gross and Bates1 present an overview of the meeting, summarizing meeting goals and recommendations gleaned throughout the presentations. Kuperman et al.2 describe the basic and advanced clinical decision support afforded for electronic prescribing within CPOE and review some of the related evidence of its effectiveness. Bobb, Payne, and Gross3 explore challenges and benefits of using evidence-based order sets within CPOE systems. Classen and colleagues4 review approaches to evaluation and credentialing CPOE systems. Two additional articles were not part of the San Francisco conference but add relevance to the JAMIA Focus on CPOE section. The article by Weir and colleagues5 sheds light on the complexity of the tasks involved in CPOE. Ko and colleagues6 solicited evaluation of CPOE-generated alerts and warnings from physicians and pharmacists in the Veterans Affairs system; clinicians were not excessively bothered by the alerts, nor did they find them particularly helpful, preferring to have more detail about alternative management provided along with the alert. Publication of the special Focus on CPOE section represents JAMIA's commitment to bringing knowledge into the public domain as quickly as possible. Authors' models for these papers are meritorious—comprising reasoned, professionally vetted recommendations that are informed by underlying clinical trials and basic research findings. However, publication of these papers does not signal an end to the need for research on decision support in CPOE. Rather, the papers help to focus future research on investigations of how to develop better models of decision support, how to keep decision support systems “current” with best practices, and how to support full, successful deployment of robust provider order entry systems in all settings. Such future investigations must: generate basic science knowledge regarding identification of proper therapeutic approaches to clinical problems; promote clinical and translational research activities that focus on efficient, effective decision support (including, for example, order sets) that address commonly seen constellations of clinical problems; encourage as a “standard of care” the human factors evaluation of clinical systems, before and after their implementation, to determine the most effective ways to present recommendations from clinical decision support to the ordering clinicians in a manner that maximizes use and adoption; and provide healthcare systems administrators with guidelines for the best ways to implement the treatment planning and care coordination benefits afforded by CPOE systems.

As new directions and priorities emerge in health care, nursing informatics leaders must prepare to guide the profession appropriately. To use an analogy, where a road bends or changes directions, guideposts indicate how drivers can stay on course. The AMIA Nursing Informatics Working Group (NIWG) produced this white paper as the product of a meeting convened: 1) to describe anticipated nationwide changes in demographics, health care quality, and health care informatics; 2) to assess the potential impact of genomic medicine and of new threats to society; 3) to align AMIA NIWG resources with emerging priorities; and 4) to identify guideposts in the form of an agenda to keep the NIWG on course in light of new opportunities. The anticipated societal changes provide opportunities for nursing informatics. Resources described below within the Department of Health and Human Services (HHS) and the National Committee for Health and Vital Statistics (NCVHS) can help to align AMIA NIWG with emerging priorities. The guideposts consist of priority areas for action in informatics, nursing education, and research. Nursing informatics professionals will collaborate as full participants in local, national, and international efforts related to the guideposts in order to make significant contributions that empower patients and providers for safer health care.

Despite growing support for the adoption of electronic health records (EHR) to improve U.S. healthcare delivery, EHR adoption in the United States is slow to date due to a fundamental failure of the healthcare information technology marketplace. Reasons for the slow adoption of healthcare information technology include a misalignment of incentives, limited purchasing power among providers, variability in the viability of EHR products and companies, and limited demonstrated value of EHRs in practice. At the 2004 American College of Medical Informatics (ACMI) Retreat, attendees discussed the current state of EHR adoption in this country and identified steps that could be taken to stimulate adoption. In this paper, based upon the ACMI retreat, and building upon the experiences of the authors developing EHR in academic and commercial settings we identify a set of recommendations to stimulate adoption of EHR, including financial incentives, promotion of EHR standards, enabling policy, and educational, marketing, and supporting activities for both the provider community and healthcare consumers.

OBJECTIVE: Contemporary health care places enormous health information management demands on laypeople. Insights into their skills and habits complements current developments in consumer health innovations, including personal health records. Using a five-element human factors model of work, health information management in the household (HIMH) is characterized by the tasks completed by individuals within household organizations, using certain tools and technologies in a given physical environment. DESIGN: We conducted a descriptive-exploratory study of the work of HIMH, involving 49 community-dwelling volunteers from a rural Midwestern community. MEASUREMENTS: During in-person interviews, we collected data using semistructured questionnaires and photographs of artifacts used for HIMH. RESULTS: The work of HIMH is largely the responsibility of a single individual, primarily engaged in the tasks of acquiring, managing, and organizing a diverse set of health information. Paper-based tools are most common, and residents develop strategies for storing information in the household environment aligned with anticipated use. Affiliative relationships, e.g., parent-child or spousal, within the household serve as the organization that gives rise to health information management practices. Synthesis of these findings led to identification of several storage strategies employed in HIMH. These strategies are labeled "just-in-time," "just-because," "just-in-case," and "just-at-hand," reflecting location of the artifacts of health information and anticipated urgency in the need to retrieve it. CONCLUSION: Laypeople develop and employ robust, complex strategies for managing health information in the home. Capitalizing on these strategies will complement and extend current consumer health innovations to provide functional support to people who face increasing demands to manage personal health information.

BACKGROUND: Improving the safety, quality, and efficiency of health care will require immediate and ubiquitous access to complete patient information and decision support provided through a National Health Information Infrastructure (NHII). METHODS: To help define the action steps needed to achieve an NHII, the U.S. Department of Health and Human Services sponsored a national consensus conference in July 2003. RESULTS: Attendees favored a public-private coordination group to guide NHII activities, provide education, share resources, and monitor relevant metrics to mark progress. They identified financial incentives, health information standards, and overcoming a few important legal obstacles as key NHII enablers. Community and regional implementation projects, including consumer access to a personal health record, were seen as necessary to demonstrate comprehensive functional systems that can serve as models for the entire nation. Finally, the participants identified the need for increased funding for research on the impact of health information technology on patient safety and quality of care. Individuals, organizations, and federal agencies are using these consensus recommendations to guide NHII efforts.

William W. Stead, MD, recently completed a decade of service to AMIA and to our profession as the founding editor of the Journal of the American Medical Informatics Association. We, the associate editor group who worked under him, take this opportunity to thank him for his profound contributions. Dr. Stead imparted a number of important characteristics to the editorship and to JAMIA by demonstrating: A massive, passionate commitment to moving the field forward through dissemination of scholarship and innovation. A commitment to scientific rigor and quality of publication, sometimes at the expense of decreased page count. A strong desire to represent the breadth and depth of this multidisciplinary field. A long view on the course of events, favoring broad perspectives over provincial ones. A palpable, deep and genuine respect extended to every author and reviewer, often expressed through tactful, direct, and honest feedback. An ability to find the kernel of good and truth in almost any paper and to help authors find it also—sometimes by working with authors to rewrite manuscripts interactively. A polite but persistent approach to editorial disagreements, combined with a polite and good natured acceptance of editorial advice, even when it differed from his perspective. A ready opinion—usually strongly held, on any topic—balanced by a willingness to remodel himself and his skill set to adapt to changing times. Bill Stead has been a visionary leader in biomedical informatics. He has brought extraordinary perspective and insight into creating a new journal “from scratch.” In an era when academic “triple threats” are said to be nearing extinction, he has shown that one can still understand and support clinical practice, conduct research and build an academic enterprise and contribute to excellent institutional management. One of his favorite expressions is, “We shouldn't do it if it isn't scalable and sustainable,” which he has applied both to development of informatics systems at Vanderbilt, and to practices within JAMIA. His keen business sense has helped to make JAMIA a break-even endeavor for the American Medical Informatics Association from its inception. His experience in team building has led to a cohesive and coordinated editorial board and staff that turns around submissions with exemplary efficiency. And on top of all that, he has big shoes. In recognition of his pioneering leadership, the American Medical Informatics Association will initiate a Janet and Bill Stead Lectureship (details forthcoming later). Thank you, Dr. Stead, for creating the “industry standard” for excellence in medical informatics editorial leadership.

AMIA released recommendations late last year to assist in the fight against national health threats. These recommendations and other collaborative efforts by the AMIA National Health Threats Task Force during the AMIA 2001 Annual Symposium are presented in a special section on Bioterrorism in this issue of JAMIA. This report tracks follow-up developments of the AMIA National Health Threats Task Force, including attendance at key meetings and the development of bioterrorism resources on the AMIA Web site. In addition, key points from the AMIA Primary Care Informatics Working Group (PCIWG) special sessions at the AMIA Annual Symposium, and recommendations developed by the PCIWG, contribute to AMIA's growing involvement in this area. The AMIA Prevention and Public Health Working Group has also been involved, presenting recommendations on information systems for bioterrorism and public health. Throughout this news report the term surveillance is defined as “the ongoing systematic collection, analysis, and interpretation of outcome-specific data for use in the planning, implementation and evaluation of public health practice.”1

The paper by Staggers and Thompson in this issue enriches the ongoing challenge of defining the field of medical informatics. Medical informatics is a maturing field whose research base is well grounded in the basic sciences of computation, information, and decision making; the full range of bench and social sciences supporting health care; the clinical sciences, including medicine, nursing, and pharmacy; and the practical realities of developing and deploying information systems for patient care. The Staggers and Thompson paper takes the perspective of a single clinical discipline, nursing, and explores the development of informatics in that context. It is important in nursing, as in any basic or clinical health science, to systematically examine how a derived field, such as medical informatics, grows and develops within its boundaries. Three important reasons for this examination emerge. First, the definition of medical informatics, as a discipline derived from health professions and health care policies and practices, is continually changing as it is informed by, and as it informs, the referent clinical discipline. Second, as a discipline that is, itself, continually evolving, medical informatics merits consideration for its concurrent utility to the disciplines in which it is applied. Finally, as science develops and technology changes, the scope of the referent discipline changes and so might the scope of medical informatics.

The terrorist attacks of September 2001 and the subsequent deliberate dissemination of anthrax have stimulated public awareness of the need in both the public health and clinical health care systems to quickly detect and respond to altered patterns of disease in communities across the nation. Debate over the capacity of the existing systems to fully respond to these demands has created a sense of urgency for immediate action to improve these functions. Public health resources were taxed to provide early detection and rapid response. The clinical care delivery system faced challenges of emergency response to urban casualties, highlighting the value of clinical information systems that facilitate information management in crisis situations. The effective application of informatics to these data collection, analysis, and dissemination tasks could allow the rapid deployment of systems that would greatly enhance our preparedness. Much of the informatics experience gained in health information system implementation efforts over the past several decades is directly applicable to the new challenges of bioterrorism and emergency response. By utilizing this collective knowledge in areas such as architecture, infrastructure, standards, and knowledge representation, newly created systems are more likely to yield maximum benefits. As an organization, AMIA is already focused on issues of public health informatics, having developed a national consensus agenda for the field at its 2001 Spring Congress.1

The track entitled "Consumer Informatics Supporting Patients as Co-Producers of Quality" at the AMIA Spring 2000 Congress was devoted to examining the new field of consumer health informatics. This area is developing rapidly, as worldwide changes are occurring in the organization and delivery of health care and in the traditional roles of patient and provider. This paper describes the key themes of the track; implications of the growing area of consumer health informatics; and recommendations for informatics research, design, and policy. Key themes that emerged from the panels and discussions involved changes in roles of consumers and providers; supporting a patient-provider-information technology partnership; virtual, not physical, structure for health care and health care information delivery; and health care as an integrated part of one's life. Panelists and participants at the Congress developed recommendations for informatics research, design, and policy, with an overarching focus on how to support the patient-provider-information technology partnership to provide more patient-centered health care. They recommended that AMIA take an active leadership role in consumer health informatics. Specific recommendations were made concerning research, new patient record systems, provider support, information access and evaluation, and policy and regulation.

As we have advanced in medical informatics and created many impressive innovations, we also have learned that technologic developments are not sufficient to bring the value of computer and information technologies to health care systems. This paper proposes a model for improving how we develop and deploy information technology. The authors focus on trends in people, organizational, and social issues (POI/OSI), which are becoming more complex as both health care institutions and information technologies are changing rapidly. They outline key issues and suggest high-priority research areas. One dimension of the model concerns different organizational levels at which informatics applications are used. The other dimension draws on social science disciplines for their approaches to studying implications of POI/OSI in informatics. By drawing on a wide variety of research approaches and asking questions based in social science disciplines, the authors propose a research agenda for high-priority issues, so that the challenges they see ahead for informatics may be met better.

In September 2000, the Agency for Healthcare Quality and Research and the American Academy of Pediatrics Center for Child Health Research sponsored a meeting of experts and knowledgeable stakeholders to identify 1) the special information needs of pediatric care and 2) health service research questions related to the use of information technology in children's health care. Technologies that support the care of children must address issues related to growth and development, children's changing physiology, and the unique diseases of children and interventions of pediatric care. Connectivity and data integration are particular concerns for child health care workers. Consumer health information needs for this population extend beyond the needs of one individual to the needs of the family. Recommendations of the attendees include rapid implementation of features in electronic health information systems that support pediatric care and involvement of child health experts in policy making, standards setting, education, and advocacy. A proposed research agenda should address both effectiveness and costs of information technology, with special consideration for the needs of children, the development and evaluation of clinical decision support in pediatric settings, understanding of the epidemiology of iatrogenic injury in childhood, supplementation of vocabulary standards with pediatrics-specific terminology, and improvement in health care access for children, using telemedicine.

The best medical informatics research is grounded in an understanding of both the medical content area and the informatics techniques. For example, it is not attention to the medical literature alone that makes medical informatics different from information science. The difference comes from the integration of medical knowledge and the strategies or structures needed to formalize or represent it. The paper by Piniewski-Bond et al.1 provides an example of the need for collaboration of informatics experts with application domain experts. It compares two methods for identifying the set of ideas contained in a test set of papers from the published literature. The researchers use the set of ideas contained in three published review papers as a gold standard, and they use the papers that are referenced in those three reviews as the test set. The reader will recognize two potential sources of error in this analysis. First, Piniewski-Bond et al. may not have correctly identified all the ideas contained in the three review papers. Second, the authors of those review papers may have included ideas based on their prior experience that did not come directly from any of the papers that they reference. Such limits are not unusual, and they do not constitute a reason to reject a manuscript for publication in a medical informatics journal as long as they are correctly stated in the manuscript. The review of the manuscript pointed out a limitation that may not be as obvious. The subject of the three published review papers is the specific association between human papillomavirus and cervical cancer. The expert in that clinical area among the reviewers of this paper stated clearly that the three published reviews were not the best available on this clinical topic. Accordingly, neither the ideas contained in them nor the ideas identified by examining their reference constitute a valid review of this clinical problem. In other words, the paper provides an apt demonstration of an information science technique; however, when viewed from the perspective of medicine, the clinical content is sub-par. We accepted the paper for publication because the author states clearly that she is not trying to provide a review of the clinical topic, the reviewers indicate that the paper adds to the base of knowledge in informatics; and we judge the risk of a clinical reader mistaking this paper for a clinical review as remote. Nonetheless, this limitation might have been easily avoided if a clinical subject expert had participated at the start of the project to identify a clinically valid test set. If the test set had been clinically valid, the quantitative data could be placed in clinical context. A reader could judge whether differences in results were significant clinically. One reviewer explained the problem with a fishing example. “The crappie is a round, slow fish not known for much of anything, pretty easy to catch. The musky, on the other hand, is a sleek and wily fish that hides in weeds, very difficult to catch. Would you have confidence in your new fishing rod if it had been tested on crappie and you wanted to catch musky?”

The papers by Stein et al.1 and Aronsky and Haug2 address the quality of the data found in clinical record systems. Stein et al. approach the problem as one of internal consistency. Their paper explores concordance within record systems, exploring the extent to which evidence found in one part of a clinical database is consistent with evidence found in another part. Specifically, they examine agreement between entries in a free-text narrative field with data found in coded fields. Aronsky and Haug examine concordance across two different clinical record systems—the HELP computerized clinical record system and a reference standard consisting of the sum of all information available in the paper chart and the computerized clinical record. Aronsky and Haug complement their appraisal of concordance with an outcome evaluation, determining the level of agreement in clinical severity indexes resulting from the information contained in the different record systems. Stein et al. use the measure of internal concordance to alert users of a computerized record system to the fact that they may get misleading answers unless they query each field that might contain a piece of information and resolve any discrepancies. Aronsky and Haug argue the need for equivalence in recommendations based on the clinical record, regardless of which form of a clinical record is used; they are saying, in effect, that records with higher concordance should lead to similar recommendations. The use of the term “concordance” is appropriate for framing the question posed in each of these papers. Concordance originated in the 14th century church, referring to a companion text to an original document, the companion text consisting of an enumeration of all terms appearing in the original document. These authors extended the target object from “terms” to “concepts” and restricted the enumeration of concepts to only those relevant to specific clinical phenomena. The authors' uses of the term “concordance” implies that the question of interest is the extent to which all clinically significant concepts found in one section (Stein et al.) or form (Aronsky and Haug) are evident in another section or form. The evidence presented in the two papers clearly indicates that the two sections or forms are not in complete accord, and the discussions evaluate the consequences of the discord. Clinical records, be they paper or electronic, are no more and no less than representations of the true state of the patient and the events occurring during the process of care for the patient. Concordance is a characteristic of representations: It is possible to estimate the degree of similarity within or between representations, such as patient records. While one could dispute the merits of different computational forms employed to characterize concordance, the basic intent of such a statistic is valid—to gauge the level of agreement between two documents. At the same time, it is critical to recognize that concordance offers no indication as to whether the representations themselves are true and accurate depictions of the real state of the patient. Clinical data are a scarce and expensive resource. These studies advance our understanding of the degree to which we can re-use data recorded in today's clinical information systems for practice management, decision support, and clinical or health services research. This type of work should be extended in two directions—prospective studies of data accuracy in extant clinical records and methodological studies of strategies to produce more robust language structures for representing clinical phenomena. Hogan and Wagner3 provide a model for examining data accuracy by assessing correctness and completeness. The approach they use enhances the concordance studies not only by examining data in the clinical record but by prospectively constructing a gold standard so that the patient and care provider can be used as information sources. In essence, this approach goes further than concordance to ensure that the record is a correct representation of the state of the patient. At best, however, data concordance and accuracy studies are only as good as the underlying representations. These studies have an inherent limitation, because they rely on the vocabulary primitive of term or phrase. Almost all studies in this realm employ some type of parsing strategy to select specific words or phrases on which to evaluate agreement. These words and phrases themselves may be overly limiting the ability of clinical records to represent the true state of the patient, because they force the reduction of expressions of complex clinical phenomena into atomic words and phrases. Studies based on the vocabulary primitive of “terms” rather than on more sophisticated representations of patient phenomena remain restricted by the fundamental nature of records. It is possible to envision language structures in the clinical record that are more robust than simple words and phrases. Emerging work in concept maps and compositional vocabularies promises to provide tools for characterizing patient phenomena in a manner that can be dynamically manipulated and provide a more meaningful image of the true state of the patient and the actual care process. Based on thinking originating more than 70 years ago in the work of Ogden and Richards, 4 it is logical to expect that any representation system should be appraised for its ability to provide truthful depictions of the real-life state of the patient and for equivalence across representational forms. The current state of research in formal language focuses on the development of computable language structures for creating textual representations of clinical phenomena. That work, in essence, strives to ensure that the words and phrases used to depict clinical observations in the patient record remain as true-to-life as possible, by capturing not only syntactic meaning but also semantic interpretability. Records based on these representations should be assessed for validity and manipulability. A valid representation would provide an honest, true-to-life depiction of the patient. A manipulable representation would support knowledge-based interpretation of clinical observations and automatic application of decision support tools. Therefore, there is need, and room, in the field of medical informatics for multiple research trajectories that converge on the problem of ensuring the validity of the clinical record as a representation of the true state of the patient. Papers such as those presented by Stein et al. and Aronsky and Haug are necessary but not sufficient endeavors in the quest for the Holy Grail of medical informatics—the computer based patient record.

The 1999 debate of the American College of Medical Informatics focused on the proposition that medical informatics and nursing informatics are distinctive disciplines that require their own core curricula, training programs, and professional identities. Proponents of this position emphasized that informatics training, technology applications, and professional identities are closely tied to the activities of the health professionals they serve and that, as nursing and medicine differ, so do the corresponding efforts in information science and technology. Opponents of the proposition asserted that informatics is built on a re-usable and widely applicable set of methods that are common to all health science disciplines, and that "medical informatics" continues to be a useful name for a composite core discipline that should be studied by all students, regardless of their health profession orientation.

What gives guidance for patient care decisions? Clinical practice guidelines and patient preferences provide two complementary sources of guidance for clinicians and patients alike. Clinical practice guidelines bring the best scientific and clinical advice to bear on specific patient situations. Patient preferences temper clinical guidelines. The papers from the Nursing Informatics 1997 conference in Stockholm, Sweden, that are included in this issue provide a rich array of perspectives on the roles of informatics in eliciting and communicating guidelines and patient preferences and in ensuring strong infrastructures for practice. Duff1 offers the perspective of a health services researcher, looking to the informatics community to both provide the evidence necessary to build solid guidelines and also to build the tools necessary to deliver guidelines at the point of care. Zielstorff2 and Henry et al.3 answer Duff's call by outlining strategies and illustrating prototypic systems for delivering guidelines at the point of care. Ensuring that patients truly understand the complexity of choices for which they assent presents a challenge that many times exceeds the talent and time available to clinicians. Jimison et al.4 describe the use of multimedia programs to guide patients through the process of giving informed consent. Targeted at the moment for research participation, this application could also be extended to help patients think through many of the complex choices they face in contemporary health care. Brennan and Strombom5 explore the use of computer programs to elicit patient preferences necessary to make clear clinical choices. Gassert6 and Hovenga et al.7 provide a broad perspective on some of the infrastructure resources needed to make guidelines and patient preferences accessible in clinical practice. Gassert presents the agenda established for the United States by the National Nursing Informatics Working Group, calling for test beds and model systems that train clinicians to use guidelines and preferences in clinical practice. Hovenga addresses the special needs of rural areas, illustrating how telecommunications networks support outreach and communication to remote clinical care facilities. These papers represent the second report of an IMIA Nursing Special Interest Group Working Group, building on and expanding the first report “Informatics: the Infrastructure for Quality Assessment and Quality Improvement in Nursing.”8 Each presenter at the Nursing Informatics 1997 Conference was given the opportunity to recast his or her material in a manuscript for review and revision through the JAMIA editorial process. The papers in this issue therefore represent a subset of the ideas discussed at the conference. The complete proceedings of the conference are being released by the Swedish Nurses Association simultaneously with this issue of JAMIA. Where is the nursing in these papers? one may ask. Most, but not all, authors were nurses. Therefore, it is likely that one should discern a common theme or perspective through the papers, and it is in fact detectable in the attention to the person in context. However, the papers themselves represent a subtle but important step in the growth of the informatics field as a truly interdisciplinary effort. Neither guidelines nor patient preferences are the exclusive purview of any single clinical discipline. The lessons from these papers apply equally well to all health clinicians concerned about quality decision-making and quality care. Yet, could these papers have arisen any where but in a nursing conference? Probably not—because of nursings' special focus on the diagnosis and treatment of human responses9, nurse authors target as the focus of their attention the ability of an individual to cope with health challenges and health care choices. Additionally, guidelines and patient preferences take on special meaning in the practice of nursing, which is characterized by an enduring, intimate knowing of an individual. Nurses, perhaps more than all other health professionals, are best situated to learn of patients' most private desires and values and have a unique opportunity to tailor the scientific recommendations of clinical guidelines in a manner that best fits within the lifestyle of the person. It remains a challenge for the next triennial IMIA Nursing Special Interest Group conference to introduce new informatics applications to further extend our abilities to deliver quality of care.

If nurses, physicians, and health care planners knew more about patients' health-related preferences, care would most likely be cheaper, more effective, and closer to the individuals' desires. In order for patient preferences to be effectively used in the delivery of health care, it is important that patients be able to formulate and express preferences, that these judgments be made known to the clinician at the time of care, and that these statements meaningfully inform care activities. Decision theory and health informatics offer promising strategies for eliciting subjective values and making them accessible in a clinical encounter in a manner that drives health choices. Computer-based elicitation and reporting tools are proving acceptable to patients and clinicians alike. It is time for the informatics community to turn their attention toward building computer-based applications that support clinicians in the complex cognitive process of integrating patient preferences with scientific knowledge, clinical practice guidelines, and the realities of contemporary health care.

As health care moves into the community, nurses and physicians are not the only ones with new jobs—patients have new and increasing responsibilities for self-care and disease management. Information technologies can provide the necessary tools to ensure that patients are well equipped to meet these challenges. Under the umbrella of the theme “Information Technology in Community Health,” the participants at the 1997 AMIA Spring Congress learned of new and emerging technologies with the potential to enhance patients' abilities to engage in self-help, promote self-care, and implement disease-management strategies. This issue of JAMIA includes four papers addressing developments in information technologies designed to better equip patients and consumers to meet these challenges. Mary Gardiner Jones opened the congress with a plenary address1 exhorting the Health Informatics community to participate in shaping the national information infrastructure. From her perspective as a consumer advocate, Ms. Jones cautioned that the current trajectory of progress for the NII is more responsive to the communications and education sectors of society than to the needs of the health care system. She advocated that we who work at the nexus of technology and health care must in turn serve as advocates for our patients and clients whose chance to benefit from the NII depends on our ability to garner its resources for health care delivery. Rosenthal reported a prototype voice-enabled system for generating structured reports.2 Voice technology remains elusive as a reliable mechanism for providing input into computer systems. Consumers and patients may best be served by information systems that support voice data entry. Efficient and effective use of voice technologies removes the barriers to consumer access to health information once posed by typing skill and access to computers. Other papers addressed clinical, rather than technology, issues. Choice of appropriate therapy relies heavily on understanding patients' preferences for health outcomes and clinical treatments. Elicitation of these highly individualistic values is complex and time consuming, far exceeding the resources available in the contemporary health care encounter. Lenert and colleagues describe a WWW-accessible system to assess a patient's quality of life.3 Such tools also could be used to aid patients in value clarification. Use of such programs affords patients the time and privacy to conduct personal introspection and helps prepare them to better participate in clinical decision making. Patient participation in contemporary health care also involves learning about health promotion strategies, disease- and condition-specific etiology and treatment, and available health care resources. The Telephone Linked Computer (TLC) system, described by Friedman,4 represents a mature example of an academic medical center's attempt to create an interactive environment in which a patient at home can provide information about a condition and get consumer information or help in designing an intervention. Addressed from the perspective of the developers, this article details the challenges of structuring the patient interaction—a key component of organizing health information resources and making them accessible to a lay public. Evaluation of consumer health informatics interventions, such as the TLC program, served as the focus of discussion for many hallway conversations and panel presentations. Evaluation involves two components: ensuring the quality and relevance of the health information presented, and determining the impact on the health of the community. Two AMIA Working Groups, the Internet Working Group and the Prevention/Health Education Working group, debated the issues surrounding ensuring the quality and relevance of health information. Two perspectives emerged: credentialing consumer health informatics offerings and educating consumers to be better able to evaluate these resources. Resolution of the evaluation question rests in both perspectives. Developers and purchasers of consumer health informatics tools will be challenged in the future to show that their offerings meet acceptable standards. Given the plethora of consumer health informatics, however, the lay person will need to become a discerning consumer to make most effective use of the knowledge contained in these resources. Congress papers addressed additional dimensions of community health under the theme of “Information Technology in Community Health.” Privacy and confidentiality issues were addressed from the perspectives of technologies to ensure them and the ethical principles necessary to evaluate them. Disease management models that capitalized on technologies accessible in the home and community are emerging. Public health advantages of large data sets, reporting schemes, and geographic information systems were explored through papers and demonstrations. Information technology has the power to bring patients into full partnership with health care providers. Now that both the “work” and “workers” of health care have changed, it is time to develop the technologies and tools to ensure that the job is done right!

OBJECTIVE: Evaluators must develop methods to characterize the use of the rapidly proliferating electronic networks that link patients with health services. In this article the 4-S framework is proposed for characterizing the use of health services delivered via computer networks. The utility of the 4-S framework is illustrated using data derived from a completed, randomized field experiment in which 47 caregivers of persons who had Alzheimer's disease accessed ComputerLink, a special computer network providing information, communication, and decision support to homebound caregivers of persons who have Alzheimer's disease. DESIGN: Human-computer interaction theories characterize the use of health services delivered via computer networks in behavioral terms. The 4-S framework incorporates perspectives based on user (subject) behavior: access to and use of the total system, use of specific services, behavior within single sessions, and enduring behavioral characteristics. The 4-S framework was tested in a secondary analysis of data from over 3,800 uses of ComputerLink. MEASUREMENT: The 4-S framework was instantiated using data obtained from the ComputerLink evaluation. Three types of secondary data were obtained. A passive monitor of access to the computer network provided quantitative information, such as time of day when access occurred, duration of access, and sequence of services used. Full-text messages were available from the public message postings. Subjective appraisal of use was obtained from self-reporting by users at the end of the experiment. RESULTS: The components of the 4-S framework were suitable to characterize operational aspects of ComputerLink use by Alzheimer's disease caregivers. Through application of the 4-S framework, an understanding of both quantitative use and qualitative use emerged (e.g., insight was gained into the differential use of specific services). CONCLUSIONS: The 4-S framework provided a mechanism for combining various measures of use into a coherent whole. The framework promotes a precise characterization of use and thereby facilitates evaluation of health services delivered via computer networks. It is suitable for evaluation of user satisfaction, measurement of needs resolution, and ascertainment of selected clinical outcomes.

This article explores the application of normative decision theory (NDT) to the challenge of facilitating and measuring patient satisfaction. Patient satisfaction is the appraisal, by an individual, of the extent to which the care provided has met that individual's expectations and preferences. Classic decision analysis provides a graphic and computational strategy to link patient preferences for outcomes to the treatment choices likely to produce the outcomes. Multiple criteria models enable the complex judgment task of measuring patient satisfaction to be decomposed into elemental factors that reflect patient preferences, thus facilitating evaluation of care in terms of factors relevant to the individual patient. Through the application of NDT models, it is possible to use patient preferences as a guide to the treatment planning and care monitoring process and to construct measures of patient satisfaction that are meaningful to the individual. Nursing informatics, with its foundations in both information management and decision sciences, provides the tools and data necessary to promote care provided in accord with patient preferences and to ensure appraisal of satisfaction that aptly captures the complex, multidimensional nature of patient preferences.

Patricia Flatley Brennan, PhD, RN; On the Relevance of Discipline to Informatics, Journal of the American Medical Informatics Association, Volume 1, Issue 2, 1