Successes and Barriers of Health Information Exchange Participation Across Hospitals in South Carolina From 2014 to 2020: Longitudinal Observational Study
Bibliographic record
Abstract
BACKGROUND: The 2009 Health Information Technology for Economic and Clinical Health Act sets three stages of Meaningful Use requirements for the electronic health records incentive program. Health information exchange (HIE) technologies are critical in the meaningful use of electronic health records to support patient care coordination. However, HIE use trends and barriers remain unclear across hospitals in South Carolina (SC), a state with the earliest HIE implementation. OBJECTIVE: This study aims to explore changes in the proportion of HIE participation and factors associated with HIE participation, and barriers to exchange and interoperability across SC hospitals. METHODS: This study derived data from a longitudinal data set of the 2014-2020 American Hospital Association Information Technology Supplement for 69 SC hospitals. The primary outcome was whether a hospital participated in HIE in a year. A cross-sectional multivariable logistic regression model, clustered at the hospital level and weighted by bed size, was used to identify factors associated with HIE participation. The second outcome was barriers to sending, receiving, or finding patient health information to or from other organizations or hospital systems. The frequency of hospitals reporting each barrier related to exchange and interoperability were then calculated. RESULTS: Hospitals in SC have been increasingly participating in HIE, improving from 43% (24/56) in 2014 to 82% (54/66) in 2020. After controlling for other hospital factors, teaching hospitals (adjusted odds ratio [AOR] 3.7, 95% CI 1.0-13.3), system-affiliated hospitals (AOR 6.6, 95% CI 3.2-13.7), and rural referral hospitals (AOR 8.0, 95% CI 1.2-53.4) had higher odds to participate in HIE than their counterparts, whereas critical access hospitals (AOR 0.1, 95% CI 0.02-0.6) were less likely to participate in HIE than their counterparts reimbursed by the prospective payment system. Hospitals with greater ratios of Medicare or Medicaid inpatient days to total inpatient days also reported higher odds of HIE participation. Despite the majority of hospitals reporting HIE participation in 2020, barriers to exchange and interoperability remained, including lack of provider contacts (27/40, 68%), difficulty in finding patient health information (27/40, 68%), adapting different vendor platforms (26/40, 65%), difficulty matching or identifying same patients between systems (23/40, 58%), and providers that do not typically exchange patient data (23/40, 58%). CONCLUSIONS: HIE participation has been widely adopted in SC hospitals. Our findings highlight the need to incentivize optimization of HIE and seamless information exchange by facilitating and implementing standardization of health information across various HIE systems and by addressing other technical issues, including providing providers' addresses and training HIE stakeholders to find relevant information. Policies and efforts should include more collaboration with vendors to reduce platform compatibility issues and more user engagement and technical training and support to facilitate effective, accurate, and efficient exchange of provider contacts and patient health information.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".