Barriers to Hospital Electronic Public Health Reporting and Implications for the COVID-19 Pandemic

We sought to identify barriers to hospital reporting of electronic surveillance data to local, state, and federal public health agencies and the impact on areas projected to be overwhelmed by the COVID-19 pandemic. Using 2018 American Hospital Association data, we identified barriers to surveillance data reporting and combined this with data on the projected impact of the COVID-19 pandemic on hospital capacity at the hospital referral region level. Our results find the most common barrier was public health agencies lacked the capacity to electronically receive data, with 41.2% of all hospitals reporting it. We also identified 31 hospital referral regions in the top quartile of projected bed capacity needed for COVID-19 patients in which over half of hospitals in the area reported that the relevant public health agency was unable to receive electronic data. Public health agencies’ inability to receive electronic data is the most prominent hospital-reported barrier to effective syndromic surveillance. This reflects the policy commitment of investing in information technology for hospitals without a concomitant investment in IT infrastructure for state and local public health agencies

Opt-in consent policies: potential barriers to hospital health information exchange

Objectives: First, to assess whether hospitals in states requiring explicit patient consent (“opt-in”) for health information exchange (HIE) are more likely to report regulatory barriers to HIE. Second, to analyze whether these policies correlate with hospital volume of HIE. Study Design: Cross-sectional analysis of US non-federal acute care hospitals in 2016. Methods: We combined legal scholarship surveying HIE-relevant state laws with the AHA Annual IT Supplement for regulatory barriers and hospital characteristics. Data from CMS reports for hospitals attesting to Meaningful Use Stage 2 in 2016 (MU2, renamed “Promoting Interoperability” in 2018) captured hospital HIE volume. We used multivariate logistic regression and linear regression to estimate the association between opt-in state consent policies and reported regulatory barriers and HIE volume, respectively. Results: Hospitals in states with opt-in consent policies were 7.8 percentage points more likely than hospitals in opt-out states to report regulatory barriers to HIE (p=0.03). In subgroup analyses, this finding held among hospitals that did not attest to MU2 (7.7pp, p=0.02). Among hospitals attesting, we did not find a relationship between opt-in policies and regulatory barriers (8.0pp, p=0.13), nor evidence of a relationship between opt-in policies and HIE volume (ß=0.56, p=0.76). Conclusions: Our findings suggest that opt-in consent laws may carry greater administrative burdens compared to opt-out policies. However, less technologically advanced hospitals may bear more of this burden. Furthermore, opt-in policies may not impact HIE volume for hospitals that have already achieved a degree of technological sophistication. Policymakers should carefully consider the incidence of administrative burdens when crafting laws pertaining to HIE

A decade post-HITECH: Critical access hospitals have electronic health records but struggle to keep up with other advanced functions

Objective: Despite broad electronic health record (EHR) adoption in U.S. hospitals, there is concern that an "advanced use" digital divide exists between critical access hospitals (CAHs) and non-CAHs. We measured EHR adoption and advanced use over time to analyzed changes in the divide. Materials and methods: We used 2008 to 2018 American Hospital Association Information Technology survey data to update national EHR adoption statistics. We stratified EHR adoption by CAH status and measured advanced use for both patient engagement (PE) and clinical data analytics (CDA) domains. We used a linear probability regression for each domain with year-CAH interactions to measure temporal changes in the relationship between CAH status and advanced use. Results: In 2018, 98.3% of hospitals had adopted EHRs; there were no differences by CAH status. A total of 58.7% and 55.6% of hospitals adopted advanced PE and CDA functions, respectively. In both domains, CAHs were less likely to be advanced users: 46.6% demonstrated advanced use for PE and 32.0% for CDA. Since 2015, the advanced use divide has persisted for PE and widened for CDA. Discussion: EHR adoption among hospitals is essentially ubiquitous; however, CAHs still lag behind in advanced use functions critical to improving care quality. This may be rooted in different advanced use needs among CAH patients and lack of access to technical expertise. Conclusions: The advanced use divide prevents CAH patients from benefitting from a fully digitized healthcare system. To close the widening gap in CDA, policymakers should consider partnering with vendors to develop implementation guides and standards for functions like dashboards and high-risk patient identification algorithms to better support CAH adoption

Patient Safety Informatics : Criteria Development for Assessing the Maturity of Digital Patient Safety in Hospitals

With the start of the 21st century, patient safety as a topic of special interest has attracted increasing attention in both academia and clinical practice. As technology has continued to develop since then, questions and focal points surrounding the topic have also shifted. In particular, questions regarding the impact of digitalization on patient safety and its measurement are now of high interest. This work aims to develop a maturity assessment instrument in the form of a criteria set for measuring structural requirements for digital patient safety in hospitals. Based on the results of a literature review and a derivation of maturity objects (MO) from known maturity models, 64 criteria across 11 categories were developed. Written comments of two digital patient safety experts as well as subsequent interviews were used to evaluate and refine the criteria catalog. The resulting catalog offers hospitals guidance for detecting possible areas of structural improvements in their information systems with regard to patient safety and represents a unique instrument for assessing digital maturity in this particular area

Hospital organizational strategies associated with advanced EHR adoption

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

Differences in Clinician Electronic Health Record Use Across Adult and Pediatric Primary Care Specialties.

This cross-sectional study examines differences in electronic health record use across adult and pediatric primary care specialties

Differences in Clinician Electronic Health Record Use Across Adult and Pediatric Primary Care Specialties.

This cross-sectional study examines differences in electronic health record use across adult and pediatric primary care specialties

Variation in Family Physicians’ Experiences Across Different Electronic Health Record Platforms: a Descriptive Study

Background: Electronic health records (EHRs) have been connected to excessive workload and physician burnout. Little is known about variation in physician experience with different EHRs, however. Objective: To analyze variation in reported usability and satisfaction across EHRs. Design: Internet-based survey available between December 2021 and October 2022 integrated into American Board of Family Medicine (ABFM) certification process. Participants: ABFM-certified family physicians who use an EHR with at least 50 total responding physicians. Measurements: Self-reported experience of EHR usability and satisfaction. Key Results: We analyzed the responses of 3358 physicians who used one of nine EHRs. Epic, athenahealth, and Practice Fusion were rated significantly higher across six measures of usability. Overall, between 10 and 30% reported being very satisfied with their EHR, and another 32 to 40% report being somewhat satisfied. Physicians who use athenahealth or Epic were most likely to be very satisfied, while physicians using Allscripts, Cerner, or Greenway were the least likely to be very satisfied. EHR-specific factors were the greatest overall influence on variation in satisfaction: they explained 48% of variation in the probability of being very satisfied with Epic, 46% with eClinical Works, 14% with athenahealth, and 49% with Cerner. Conclusions: Meaningful differences exist in physician-reported usability and overall satisfaction with EHRs, largely explained by EHR-specific factors. User-centric design and implementation, and robust ongoing evaluation are needed to reduce physician burden and ensure excellent experience with EHRs