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ObjectiveTo identify organizational complementarities of adoption and use of electronic health records (EHRs) and assess what organizational strategies were associated with more advanced EHR use.Data sourcesPrimary survey data of US hospitals combined with secondary data from the American Hospital Association Annual Survey and IT Supplement.Study designIn this cross-sectional study, we describe hospital organizational practices around EHR adoption and use and identify how these practices coalesce into distinct strategies. We then assess the association between those organizational strategies and adoption of advanced EHR functions.Data collectionPrimary data collection consisted of surveys sent to 797 US acute care hospitals in 2018-2019, with 451 complete respondents.Principal findingsThere was significant variation in hospital organizational practices for EHR adoption and use. Factor analysis identified practices in three domains: leadership engagement, human capital, and systems integration. Hospitals in the top quartile of the leadership engagement factor were 14 percentage points more likely to have adopted patient engagement EHR functions (P=0.01) while hospitals in the top quartile of human capital were 14 percentage points less likely to have adopted these functions (P=0.02). Hospitals in the top quartile of systems integration were 12 percentage points more likely to have adopted patient engagement functions (P=0.02) and 14 percentage points more likely to have adopted EHR data analytics functions (P=0.02).ConclusionsOur findings suggest that specific organizational strategies are associated with more advanced EHR adoption. Hospital leaders interested in realizing more value from their EHR investment may find it useful to know that there is an association between adoption of more advanced EHR functions, and engaging senior leadership as well as building connectivity between clinical and administrative systems.

OBJECTIVE: To compare the performance of widely used approaches for defining groups of hospitals and a new approach based on network analysis of shared patient volume. STUDY SETTING: Non‐federal acute care hospitals in the United States. STUDY DESIGN: We assessed the measurement properties of four methods of grouping hospitals: hospital referral regions (HRRs), metropolitan statistical areas (MSAs), core‐based statistical areas (CBSAs), and community detection algorithms (CDAs). DATA EXTRACTION METHODS: We combined data from the 2014 American Hospital Association Annual Survey, the Census Bureau, the Dartmouth Atlas, and Medicare data on interhospital patient travel patterns. We then evaluated the distinctiveness of each grouping, reliability over time, and generalizability across populations. PRINCIPLE FINDINGS: Hospital groups defined by CDAs were the most distinctive (modularity = 0.86 compared to 0.75 for HRRs and 0.83 for MSAs; 0.72 for CBSA), were reliable to alternative specifications, and had greater generalizability than HRRs, MSAs, or CBSAs. CDAs had lower reliability over time than MSAs or CBSAs (normalized mutual information between 2012 and 2014 CDAs = 0.93). CONCLUSIONS: Community detection algorithm‐defined hospital groups offer high validity, reliability to different specifications, and generalizability to many uses when compared to approaches in widespread use today. They may, therefore, offer a better choice for efforts seeking to analyze the behaviors and dynamics of groups of hospitals. Measures of modularity, shared information, inclusivity, and shared behavior can be used to evaluate different approaches to grouping providers.

Policy Points: Historically, in addition to economic and technical hurdles, state and federal health information privacy laws have been cited as a significant obstacle to expanding electronic health information exchange (HIE) in the United States. Our review finds that over the past decade, several helpful developments have ameliorated the legal barriers to HIE, although variation in states' patient consent requirements remains a challenge. Today, health care providers' complaints about legal obstacles to HIE may be better understood as reflecting concerns about the economic and competitive risks of information sharing. Context Although the clinical benefits of exchanging patients' health information electronically across providers have long been recognized, participation in health information exchange (HIE) has lagged behind adoption of electronic health records. Barriers erected by federal and state health information privacy law have been cited as a leading reason for the slow progress. A comprehensive assessment of these issues has not been undertaken for nearly a decade, despite a number of salient legal developments. Methods Analysis of federal and state health information privacy statutes and regulations and secondary materials. Findings Although some legal barriers to HIE persist, many have been ameliorated-in some cases, simply through improved understanding of what the law actually requires. It is now clear that the Health Insurance Portability and Accountability Act presents no obstacles to electronically sharing protected health information for treatment purposes and does not hold providers who properly disclose information liable for privacy breaches by recipients. The failure of federal efforts to establish a unique patient identifier number does slow HIE by inhibiting optimal matching of patient records, but other action to facilitate matching will be taken under the 21st Century Cures Act. The Cures Act also creates the legal architecture to begin to combat "information blocking." Varying patient consent requirements under federal and state law are the most important remaining legal barrier to HIE progress. However, federal rules relating to disclosure of substance-abuse treatment information were recently liberalized, and development of a technical standard, Data Segmentation for Privacy, or DS4P, now permits sensitive data requiring special handling to be segmented within a patient's record. Even with these developments, state-law requirements for patient consent remain daunting to navigate. Conclusions Although patient consent requirements make HIE challenging, providers' expressed worries about legal barriers to participating in HIE likely primarily reflect concerns that are economically motivated. Lowering the cost of HIE or increasing financial incentives may boost provider participation more than further reducing legal barriers.

Objective To assess whether the level of health information exchange (HIE) in U.S. hospitals is related to technology capabilities, incentives to exchange, or both. Study Setting A total of 1,812 hospitals attesting to stage 2 of Medicare's Meaningful Use Incentive Program through April 2016. Study Design Hospital-level, multivariate OLS regression with state fixed effects was used to analyze the relationship between technology capability and incentives measures, and percent of care transitions with summary of care records (SCRs) sent electronically to subsequent providers. Principal Findings Stage 2 hospitals reported sending SCRs electronically for an average of 41 percent (median = 33 percent) of transitions. HIE level is related to four capability measures, one incentive measure, and one measure that is related to both capability and incentive. Percent of transitions with SCRs sent electronically was 3 percentage points higher (95 percent CI: 0.1–5.1) for hospitals with a third-party HIE vendor, 3 percentage points higher (95 percent CI: 0.5–5.4) for hospitals with an EHR vendor as their HIE vendor, and 3 percentage points higher (95 percent CI: 0.4–5.4) for hospitals that automatically alert primary care providers. The direction and statistical significance of the relationships between specific EHR vendor and electronic SCR transmission level varied by vendor. Nonprofits and government hospitals performed 5 percentage points higher (95 percent CI: 1.5–9.1) and 8 percentage points higher (95 percent CI: 3.4–12.3) than for-profits. Hospitals in systems performed 3 percentage points higher (95 percent CI: 0.8–6.1). Conclusion The overall level of HIE is low, with hospitals sending an SCR electronically for less than half of patient transitions. Specific hospital characteristics related to both technology capabilities and incentives were associated with higher levels of HIE.

Electronic health information exchange (HIE) was a foundational goal of the 2009 Health Information Technology for Economic and Clinical Health (HITECH) Act, but 7 years later we are far from a nationally interoperable health system. Connected electronic health records have the potential to enable fast access to a wealth of clinical data and can deliver a solution to the highly fragmented US healthcare system. In this review, we present a history and background of HIE, including its potential to deliver significant cost savings to the healthcare system. We examine the key components of HIE, including exchanges, the mechanism, and options available to providers. Health information exchange faces significant challenges, ranging from technical issues to lack of a clear goal, but continued policy initiatives and new technologies represent a promising path to providing clinicians with routine, electronic patient data. Journal of Hospital Medicine 2017;12:193-198.

Policy Points: Congress has expressed concern about electronic health record (EHR) vendors and health care providers knowingly interfering with the electronic exchange of patient health information. These “information blocking” practices would privately benefit vendors and providers but limit the societal quality and efficiency benefits from EHR adoption. We found that information blocking is reported to frequently occur among EHR vendors as well as hospitals and health systems, and that it is perceived to be motivated by opportunities for revenue gain. Because information blocking is largely legal today, the most effective policy response likely involves a combination of direct enforcement and the altering of market conditions that promote information blocking. Context Congress has raised concerns about providers and electronic health record (EHR) vendors knowingly engaging in business practices that interfere with electronic health information exchange (HIE). Such “information blocking” is presumed to occur because providers and vendors reap financial benefits, but these practices harm public good and substantially limit the value to be gained from EHR adoption. Crafting a policy response has been difficult because, beyond anecdotes, there is no data that captures the extent of information blocking. Methods We conducted a national survey of leaders of HIE efforts who work to enable HIE across provider organizations. We asked them about the frequency of information blocking, its specific forms, and the effectiveness of various policy strategies to address it. We received responses from 60 individuals (57% response rate). We calculated descriptive statistics across responses. Findings Half of respondents reported that EHR vendors routinely engage in information blocking, and 25% of respondents reported that hospitals and health systems routinely do so. Among EHR vendors, the most common form of information blocking was deploying products with limited interoperability. Among hospitals and health systems, the most common form was coercing providers to adopt particular EHR or HIE technology. Increasing transparency of EHR vendor business practices and product performance, stronger financial incentives for providers to share information, and making information blocking illegal were perceived as the most effective policy remedies. Conclusions Information blocking appears to be real and fairly widespread. Policymakers have some existing levers that can be used to curb information blocking and help information flow to where it is needed to improve patient care. However, because information blocking is largely legal today, a strong response will involve new legislation and associated enforcement actions.

Introduction The growth of data science has led to an explosion in new knowledge alongside various approaches to representing and sharing biomedical knowledge in computable form. These changes have not been matched by an understanding of what healthcare delivery organizations need to do to adapt and continuously deploy computable knowledge. It is therefore important to begin to conceptualize such changes in order to facilitate routine and systematic application of knowledge that improves the health of individuals and populations. Methods An AHRQ‐funded conference convened a group of experts from a range of fields to analyze the current state of knowledge management in healthcare delivery organizations and describe how it needs to evolve to enable computable knowledge management. Presentations and discussions were recorded and analyzed by the author team to identify foundational concepts and new domains of healthcare delivery organization knowledge management capabilities. Results Three foundational concepts include 1) the current state of knowledge management in healthcare delivery organizations relies on an outdated biomedical library model, and only a small number of organizations have developed enterprise‐scale knowledge management approaches that “push” knowledge in computable form to frontline decisions, 2) the concept of Learning Health Systems creates an imperative for scalable computable knowledge management approaches, and 3) the ability to represent data science discoveries in computable form that is FAIR (findable, accessible, interoperable, reusable) is fundamental to spread knowledge at scale. For healthcare delivery organizations to engage with computable knowledge management at scale, they will need new organizational capabilities across three domains: policies and processes, technology, and people. Examples of specific capabilities were developed. Conclusions Healthcare delivery organizations need to substantially scale up and retool their knowledge management approaches in order to benefit from computable biomedical knowledge.