OBJECTIVES: To inform initiatives to improve the interoperability of healthcare data, we described the experience of distinct phenotypes of physicians when obtaining information from outside sources. MATERIALS AND METHODS: A total of 6175 family physicians across the United States responded to information technology questions on the 2022 and 2023 American Board of Family Medicine Continuous Certification Questionnaire (100% response rate). Latent class analysis grouped physicians by individual and practice characteristics and then compared reported experience with interoperability. RESULTS: A 4-class model ("Safety Net," "Health System," "Independent Practice," and "Large Practice") best fit. Health system and large practice physicians (predominately Epic users) were more likely to report information was integrated in their Electronic Health Record (EHR) than independent practice physicians (38% and 40%, respectively, compared to 24%), and to report that information from organizations using the same EHR was usable (52% and 51%, respectively, compared to 25%). Safety net physicians were least likely to report that information from outside organizations was usable (17% compared to 23% of independent physicians). Between 42% and 50% of each phenotype reported commonly encountering external records with a large volume of low-value information. DISCUSSION: Independent practice and safety net physicians reported worse experience in some dimensions of interoperability, likely driven by differences in access to information from organizations using the same EHR. Many other challenges were consistent across physician phenotypes. CONCLUSION: Initiatives to improve interoperability among physicians may be most effective if targeted at independent practices and safety net practices; however, broad improvements will be necessary to address similar challenges across phenotypes.

OBJECTIVE: To use more precise measures of which hospitals are electronically connected to determine whether health information exchange (HIE) is associated with lower emergency department (ED)-related utilization. MATERIALS AND METHODS: We combined 2018 Medicare fee-for-service claims to identify beneficiaries with 2 ED encounters within 30 days, and Definitive Healthcare and AHA IT Supplement data to identify hospital participation in HIE networks (HIOs and EHR vendor networks). We determined whether the 2 encounters for the same beneficiary occurred at: the same organization, different organizations connected by HIE, or different organizations not connected by HIE. Outcomes were: (1) whether any repeat imaging occurred during the second ED visit; (2) for beneficiaries with a treat-and-release ED visit followed by a second ED visit, whether they were admitted to the hospital after the second visit; (3) for beneficiaries discharged from the hospital followed by an ED visit, whether they were admitted to the hospital. RESULTS: In adjusted mixed effects models, for the first two outcomes, beneficiaries returning to the same organization had significantly lower utilization compared to those going to different organizations; for the third outcome, those returning had higher utilization. Comparing only those going to different organizations, HIE was not associated with lower levels of repeat imaging or likelihood of admission following hospital discharge. HIE was associated with lower likelihood of hospital admission following a treat-and-release ED visit (1.83 percentage points [-3.44 to 0.21]). DISCUSSION: Differing utilization for beneficiaries returning to the same organization could reflect better access to information or other factors such as aligned incentives. CONCLUSION: HIE is not consistently associated with utilization outcomes reflecting more coordinated care in the ED setting.

OBJECTIVES: We analyzed trends in adoption of advanced patient engagement and clinical data analytics functionalities among critical access hospitals (CAHs) and non-CAHs to assess how historical gaps have changed. MATERIALS AND METHODS: We used 2014, 2018, and 2023 data from the American Hospital Association Annual Survey IT Supplement to measure differences in adoption rates (ie, the "adoption gap") of patient engagement and clinical data analytics functionalities across CAHs and non-CAHs. We measured changes over time in CAH and non-CAH adoption of 6 "core" clinical data analytics functionalities, 5 "core" patient engagement functionalities, 5 new patient engagement functionalities, and 3 bulk data export use cases. We constructed 2 composite measures for core functionalities and analyzed adoption for other functionalities individually. RESULTS: Core functionality adoption increased from 21% of CAHs in 2014 to 56% in 2023 for clinical data analytics and 18% to 49% for patient engagement. The CAH adoption gap in both domains narrowed from 2018 to 2023 (both P < .01). More than 90% of all hospitals had adopted viewing and downloading electronic data and clinical notes by 2023. The largest CAH adoption gaps in 2023 were for Fast Healthcare Interoperability Resources (FHIR) bulk export use cases (eg, analytics and reporting: 63% of CAHs, 81% of non-CAHs, P < .001). DISCUSSION: Adoption of advanced electronic health record functionalities has increased for CAHs and non-CAHs, and some adoption gaps have been closed since 2018. However, CAHs may continue to struggle with clinical data analytics and FHIR-based functionalities. CONCLUSION: Some crucial patient engagement functionalities have reached near-universal adoption; however, policymakers should consider programs to support CAHs in closing remaining adoption gaps.

OBJECTIVE: To describe the prevalence of and trends in practices that interfere with the exchange of patient health information (potential information blocking) 2 years after implementation of information-blocking regulations. MATERIALS AND METHODS: Drawing from the American Hospital Association Information Technology (IT) Supplement and a national survey of health information organizations (HIOs), we described rates and methods of potential information blocking from these organizations' perspectives in 2023 and compared them to prior years. RESULTS: Twenty-seven percent of hospitals sometimes or often observed potential information blocking by any actor in 2023, down from 42% in 2021 and 33% in 2022. Thirty percent of HIOs routinely observed potential information blocking by health IT developers, down from 50% in 2015. 13% of HIOs routinely observed potential information blocking by hospitals and health systems, down from 25% in 2015. According to both hospitals and HIOs, the most prevalent method of potential information blocking by developers in 2023 was through price, while the most prevalent by healthcare providers/health systems was by focusing exchange on strategic affiliations. Few hospitals and HIOs that experienced potential information blocking said that they had reported it to the Department of Health and Human Services. DISCUSSION: Hospitals and HIOs perceived lower rates of potential information blocking in 2023 than in prior years indicating some impact of regulations addressing information blocking. However, both respondent types reported that substantial potential information blocking persisted in 2023 and negatively impacted the exchange of information. CONCLUSION: While potential information-blocking practices have decreased, they have not been eliminated, indicating the value of continued and robust enforcement of information-blocking regulations.

OBJECTIVE: To understand barriers to obtaining and using interoperable information at US hospitals. MATERIALS AND METHODS: Using 2023 nationally representative survey data on US hospitals (N = 2420), we examined major and minor barriers to exchanging information with other organizations, and how barriers vary by hospital characteristics and methods used to obtain information. Using a series of regression models, we examined how hospital experiences with barriers relate to routine use of information at responding hospitals. RESULTS: In 2023, most hospitals experienced at least one minor (81%) or major (62%) barrier to exchange, with the most common major barriers relating to different vendors and exchange partners' capabilities. Higher-resourced hospitals and those often using network-based exchange tended to experience more minor barriers whereas lower-resourced hospitals and those often using mail/fax or direct access to outside electronic health records experienced more major barriers. In multivariate regression, hospitals indicating "Patient matching" and "Costs to exchange" were a major or minor barrier had the strongest independent negative association with the likelihood of reporting providers at their hospital frequently use information from outside organizations. DISCUSSION: Despite progress in interoperable exchange, various barriers remain. The prevalence of barriers varied by hospital type and methods used, with barriers more often preventing exchange for lower-resourced hospitals and those using outdated exchange methods. CONCLUSION: While several technical and policy efforts are underway to address prevalent barriers, it will be important to monitor whether efforts are successful in ensuring information from outside organizations can be seamlessly exchanged and used to inform patient care.

OBJECTIVES: To understand how health-related social needs (HRSN) data are collected at US hospitals and implications for use. MATERIALS AND METHODS: Using 2023 nationally representative survey data on US hospitals (N = 2775), we described hospitals' routine and structured collection and use of HRSN data and examined the relationship between methods of data collection and specific uses. Multivariate logistic regression was used to identify characteristics associated with data collection and use and understand how methods of data collection relate to use. RESULTS: In 2023, 88% of hospitals collected HRSN data (64% routinely, 72% structured). While hospitals commonly used data for internal purposes (eg, discharge planning, 79%), those that collected data routinely and in a structured format (58%) used data for purposes involving coordination or exchange with other organizations (eg, making referrals, 74%) at higher rates than hospitals that collected data but not routinely or in a non-structured format (eg, 93% vs 67% for referrals, P< .05). In multivariate regression, routine and structured data collection was positively associated with all uses of data examined. Hospital location, ownership, system-affiliation, value-based care participation, and critical access designation were associated with HRSN data collection, but only system-affiliation was consistently (positively) associated with use. DISCUSSION: While most hospitals screen for social needs, fewer collect data routinely and in a structured format that would facilitate downstream use. Routine and structured data collection was associated with greater use, particularly for secondary purposes. CONCLUSION: Routine and structured screening may result in more actionable data that facilitates use for various purposes that support patient care and improve community and population health, indicating the importance of continuing efforts to increase routine screening and standardize HRSN data collection.

OBJECTIVES: To develop indices of US hospital interoperability to capture the current state and assess progress over time. MATERIALS AND METHODS: A Technical Expert Panel (TEP) informed selection of items from the American Hospital Association Health IT Supplement survey, which were aggregated into interoperability concepts (components) and then further combined into indices. Indices were refined through psychometric analysis and additional TEP input. Final indices included a "Core Index" measuring adoption of foundational interoperability capabilities, a "Pathfinder Index" representing adoption of advanced interoperability technologies and auxiliary exchange activities, and a "Friction Index" quantifying barriers. The first 2 indices were scored from 0 (no interoperability) to 100 (full interoperability); the Friction Index was scored 0 (no friction) to 100 (maximum friction). We calculated indices annually from 2021 to 2023, stratifying by hospital characteristics. RESULTS: Items within components created reliable and meaningful measures, and associations between components within indices followed the TEP's expectations. Weighted mean scores for the Core (2023), Pathfinder (2022), and Friction (2023) Indices were 61, 57, and 30, respectively. Hospitals with 500+ beds (large), not designated as critical access, in metropolitan areas, and using market leading electronic health records had statistically significant higher mean scores on all indices. Index values also improved modestly over time. DISCUSSION: Hospitals performed best on the Core Index. Given recent policy and programmatic initiatives, we anticipate continued improvement across all indices. CONCLUSION: Ongoing index tracking can inform policy impact evaluations and highlight persistent interoperability disparities across hospitals.

OBJECTIVE: To identify impacts of different survey methodologies assessing primary care physicians' (PCPs') experiences with electronic health records (EHRs), we compared three surveys: the 2022 Continuous Certification Questionnaire (CCQ) from the American Board of Family Medicine, the 2022 University of California San Francisco (UCSF) Physician Health IT Survey, and the 2021 National Electronic Health Records Survey (NEHRS). MATERIALS AND METHODS: We evaluated differences between survey pairs using Rao-Scott corrected chi-square tests, which account for weighting. RESULTS: CCQ received 3991 responses from PCPs (100% response rate), UCSF received 1375 (3.6% response rate), and NEHRS received 858 (18.2% response rate). Substantial, statistically significant differences in demographics were detected across the surveys. CCQ respondents were younger and more likely to work in a health system; NEHRS respondents were more likely to work in private practice; and UCSF respondents disproportionately practiced in larger academic settings. Many EHR experience indicators were similar between CCQ and NEHRS, but CCQ respondents reported higher documentation burden. DISCUSSION: The UCSF approach is unlikely to supply reliable data. Significant demographic differences between CCQ and NEHRS raise response bias concerns, and while there were similarities in some reported EHR experiences, there were important, significant differences. CONCLUSION: Federal EHR policy monitoring and maintenance require reliable data. This test of existing and alternative sources suggest that diversified data sources are necessary to understand physicians' experiences with EHRs and interoperability. Comprehensive surveys administered by specialty boards have the potential to contribute to these efforts, since they are likely to be free of response bias.

OBJECTIVE: The 21st Century Cures Act Final Rule's information blocking provisions, which prohibited practices likely to interfere with, prevent, or materially discourage access, exchange, or use of electronic health information (EHI), began to apply to a limited set of data elements in April 2021 and expanded to all EHI in October 2022. We sought to describe hospital leaders' perceptions of the prevalence of practices that may constitute information blocking, by actor and hospital characteristics, following the rule's applicability date. MATERIALS AND METHODS: Cross-sectional analysis of a national survey of hospitals fielded in 2021. The analytic sample included 2092 nonfederal acute care hospitals in the United States. We present descriptive statistics on the perception of the prevalence of information blocking and results of multivariate regression models examining the association between hospital, health information technology (IT) developer and market characteristics and the perception of information blocking. RESULTS: Overall, 42% of hospitals reported observing some behavior they perceived to be information blocking. Thirty-six percent of responding hospitals perceived that healthcare providers either sometimes or often engaged in practices that may constitute information blocking, while 17% and 19% perceived that health IT developers (such as EHR developers) and State, regional and/or local health information exchanges did the same, respectively. Prevalence varied by health IT developer market share, hospital for-profit status, and health system market share. CONCLUSIONS AND RELEVANCE: These results support the value of efforts to further reduce friction in the exchange of EHI and support the need for continued observation to provide a sense of the prevalence of information blocking practices and for education and awareness of information blocking regulations.

OBJECTIVES: To assess whether previously observed differences in interoperable exchange by physician practice size persisted in 2019 and identify the role of 3 factors shaping interoperable exchange among physicians in practices of varying sizes: Federal incentive programs designed to encourage health IT use, value-based care, and selection of electronic health record (EHR) developer. MATERIALS: Cross-sectional analysis of a 2019 survey of physicians. We used multivariable Poisson models to estimate the relative risk of interoperable exchange based on the size of the practice accounting for other characteristics and the mediating role of 3 factors. RESULTS: Seventeen percent of solo practice physicians integrated outside data relative to 51% of large practice physicians. This difference remained substantial in initial multivariable models including physician characteristics. When included in models, Federal incentive programs partially mediated the relationship between practice size and interoperable exchange status. In final models including EHR developer, developer was strongly associated with both exchange and integration while practice size was no longer an independent predictor. These trends persisted when comparing practices with 4 or fewer physicians to those with 5 or more. DISCUSSION: Public and private initiatives that increase the benefits of interoperable exchange may encourage small practices to pursue it. Technical and policy changes that reduce the costs and complexity of supporting exchange could make it easier for small developers to advance their capabilities to support small practices. CONCLUSION: Addressing the gap between small and large practices will take a 2-pronged approach that targets both small EHR developers and small practices.

OBJECTIVE: Hospitals have multiple methods available to engage in health information exchange (HIE); however, it is not well understood whether these methods are complements or substitutes. We sought to characterize patterns of adoption of HIE methods and examine the association between these methods and increased availability and use of patient information. MATERIALS AND METHODS: Cross-sectional analysis of 3208 nonfederal acute care hospitals in the 2019 American Hospital Association Information Technology Supplement. RESULTS: The median hospital obtained outside information through 4 methods. Hospitals that obtained data through a regional HIE organization were 2.2 times more likely to also obtain data via Direct using a health information service provider (HISP) than hospitals that did not (P < .001). Hospitals in a single electronic health record (EHR) vendor network were no more or less likely to participate in a HISP or HIE. Six of 7 methods were associated with greater information availability. Only 4 of 7 methods (portals, interfaces, single vendor networks and multi-vendor networks but not access to outside EHR, regional exchange or Direct using a HISP) were associated with more frequent use of information, and single vendor networks were most strongly associated with more frequent use (odds ratio = 4.7, P < .001). DISCUSSION: Adoption of some methods was correlated, indicating complementary use. Few methods were negatively correlated, indicating limited competition. Although information availability was common, low correlation with use indicated that challenges related to integration may be slowing use of information. CONCLUSION: Complementarities between methods, and the role of integration in supporting information use, indicate the potential value of efforts aimed at ensuring exchange methods work well together, such as the Trusted Exchange Framework and Common Agreement.

OBJECTIVE: Recent policy making aims to prevent health systems, lectronic health record (EHR) vendors, and others from blocking the electronic sharing of patient data necessary for clinical care. We sought to assess the prevalence of information blocking prior to enforcement of these rules. MATERIALS AND METHODS: We conducted a national survey of health information exchange organizations (HIEs) to measure the prevalence of information blocking behaviors observed by these third-party entities. Eighty-nine of 106 HIEs (84%) meeting the inclusion criteria responded. RESULTS: The majority (55%) of HIEs reported that EHR vendors at least sometimes engage in information blocking, while 30% of HIEs reported the same for health systems. The most common type of information blocking behavior EHR vendors engaged in was setting unreasonably high prices, which 42% of HIEs reported routinely observing. The most common type of information blocking behavior health systems engaged in was refusing to share information, which 14% of HIEs reported routinely observing. Reported levels of vendor information blocking was correlated with regional competition among vendors and information blocking was concentrated in some geographic regions. DISCUSSION: Our findings are consistent with early reports, revealing persistently high levels of information blocking and important variation by actor, type of behavior, and geography. These trends reflect the observations and experiences of HIEs and their potential biases. Nevertheless, these data serve as a baseline against which to measure the impact of new regulations and to inform policy makers about the most common types of information blocking behaviors. CONCLUSION: Enforcement aimed at reducing information blocking should consider variation in prevalence and how to most effectively target efforts.

OBJECTIVE: Hospital engagement in electronic health information exchange (HIE) has increased over recent years. We aimed to 1) determine the change in adoption of 3 types of information exchange: secure messaging, provider portals, and use of an HIE; and 2) to assess if growth in each approach corresponded to increased ability to access and integrate patient information from outside providers. METHODS: Panel analysis of all nonfederal, acute care hospitals in the United States using hospital- and year-fixed effects. The sample consisted of 1917 hospitals that responded to the American Hospital Association Information Technology Supplement every year from 2014 to 2016. RESULTS: Adoption of each approach increased by 9-15 percentage points over the study period. The average number of HIE approaches used by each hospital increased from 1.0 to 1.4. Adoption of each approach was associated with increased likelihood that providers routinely had necessary outside information of 4.2-12.7 percentage points and 4.5-13.3 percentage points increase in information integration. Secure messaging was associated with the largest increase in both. Adoption of 1 approach increased the likelihood of having outside information by 10.3 percentage points, while adopting a second approach further increased the likelihood by 9.5 percentage points. Trends in number of approaches and integration were similar. DISCUSSION/CONCLUSION: No single HIE tool provided high levels of usable, integrated health information. Instead, hospitals benefited from adopting multiple tools. Policy initiatives that reduce the complexity of enabling high value HIE could result in broader adoption of HIE and use of information to inform care.

OBJECTIVE: In 2009, a prominent national report stated that 9% of US hospitals had adopted a "basic" electronic health record (EHR) system. This statistic was widely cited and became a memetic anchor point for EHR adoption at the dawn of HITECH. However, its calculation relies on specific treatment of the data; alternative approaches may have led to a different sense of US hospitals' EHR adoption and different subsequent public policy. MATERIALS AND METHODS: We reanalyzed the 2008 American Heart Association Information Technology supplement and complementary sources to produce a range of estimates of EHR adoption. Estimates included the mean and median number of EHR functionalities adopted, figures derived from an item response theory-based approach, and alternative estimates from the published literature. We then plotted an alternative definition of national progress toward hospital EHR adoption from 2008 to 2018. RESULTS: By 2008, 73% of hospitals had begun the transition to an EHR, and the majority of hospitals had adopted at least 6 of the 10 functionalities of a basic system. In the aggregate, national progress toward basic EHR adoption was 58% complete, and, when accounting for measurement error, we estimate that 30% of hospitals may have adopted a basic EHR. DISCUSSION: The approach used to develop the 9% figure resulted in an estimate at the extreme lower bound of what could be derived from the available data and likely did not reflect hospitals' overall progress in EHR adoption. CONCLUSION: The memetic 9% figure shaped nationwide thinking and policy making about EHR adoption; alternative representations of the data may have led to different policy.

Objective: Hospitals that routinely share patients are those that most critically need to engage in electronic health information exchange (HIE) with each other to ensure clinical information is available to inform treatment decisions. We surveyed pairs of hospitals in a nationwide sample to describe whether and how hospitals within each hospital referral region (HRR) that have the highest shared patient (HSP) volume engaged in HIE with each other. Methods: We used Medicare's Physician Shared Patient Patterns data to identify hospital pairs with the highest shared patient volume in each hospital referral region. We surveyed a purposeful sample of pairs and then calculated descriptive statistics to compare: (1) HIE with the HSP hospital vs HIE with other hospitals, and (2) HIE with the HSP hospital versus federal measures of HIE engagement that are not partner-specific. Results: We received responses from 25.5% of contacted hospitals and 33.5% of contacted pairs, allowing us to examine information sharing among 68 hospitals in 63 pairs. 23% of respondents reported worse information sharing with their HSP hospital than with other hospitals while 17% indicated better sharing with their HSP hospital and 48% indicated no difference. Our HSP-specific measures of HIE differed from federal measures of HIE engagement: while 97% of respondents are classified as routinely sending information electronically in federal measures, in our data only 63% did so with their HSP hospital. Conclusions: Despite increased HIE engagement, our descriptive results indicate that HIE is not developing in a way that facilitates information exchange where it might benefit the most patients. New policy efforts, particularly those emerging from the 21st Century Cures Act, need to explicitly pursue strategies that ensure that HSP providers engage in exchange with each other.

OBJECTIVE: To assess whether electronic health information exchange (HIE) is associated with improved emergency department (ED) care processes and utilization through more timely clinician viewing of information from outside organizations. MATERIALS AND METHODS: Our data included 2163 patients seen in the ED of a large academic medical center for whom clinicians requested and viewed outside information from February 14, 2014, to February 13, 2015. Outside information requests w.ere fulfilled via HIE (Epic's Care Everywhere) or fax/scan to the electronic health record (EHR). We used EHR audit data to capture the time between the information request and when a clinician accessed the data. We assessed whether the relationship between method of information return and ED outcomes (length of visit, odds of imaging [computed tomography (CT), magnetic resonance imaging (MRI), radiographs] and hospitalization, and total charges) was mediated by request-to-access time, controlling for patient demographics, case mix, and acuity. RESULTS: In multivariate analysis, there was no direct association between return of information via HIE vs fax/scan and ED outcomes. HIE was associated with faster outside information access (58.5 minutes on average), and faster access was associated with changes in ED care. For each 1-hour reduction in access time, visit length was 52.9 minutes shorter, the likelihood of imaging was lower (by 2.5, 1.6, and 2.4 percentage points for CT, MRI, and radiographs, respectively), the likelihood of admission was 2.4 percentage points lower, and average charges were $1187 lower ( P ≤ .001 for all). CONCLUSION: The relationship between HIE and improved care processes and reduced utilization in the ED is mediated by faster accessing of information from outside organizations.

OBJECTIVE: To examine whether there is a common sequence of adoption of electronic health record (EHR) functions among US hospitals, identify differences by hospital type, and assess the impact of meaningful use. MATERIALS AND METHODS: Using 2008 American Hospital Association (AHA) Information Technology (IT) Supplement data, we calculate adoption rates of individual EHR functions, along with Loevinger homogeneity (H) coefficients, to assess the sequence of EHR adoption across hospitals. We compare adoption rates and Loevinger H coefficients for hospitals of different types to assess variation in sequencing. We qualitatively assess whether stage 1 meaningful use functions are those adopted early in the sequence. RESULTS: There is a common sequence of EHR adoption across hospitals, with moderate-to-strong homogeneity. Patient demographic and ancillary results functions are consistently adopted first, while physician notes, clinical reminders, and guidelines are adopted last. Small hospitals exhibited greater homogeneity than larger hospitals. Rural hospitals and non-teaching hospitals exhibited greater homogeneity than urban and teaching hospitals. EHR functions emphasized in stage 1 meaningful use are spread throughout the scale. DISCUSSION: Stronger homogeneity among small, rural, and non-teaching hospitals may be driven by greater reliance on vendors and less variation in the types of care they deliver. Stage 1 meaningful use is likely changing how hospitals sequence EHR adoption--in particular, by moving clinical guidelines and medication computerized provider order entry ahead in sequence. CONCLUSIONS: While there is a common sequence underlying adoption of EHR functions, the degree of adherence to the sequence varies by key hospital characteristics. Stage 1 meaningful use likely alters the sequence.