ArticleJournal of medical Internet research2018
Forecasting the Maturation of Electronic Health Record Functions Among US Hospitals: Retrospective Analysis and Predictive Model.
Article in Journal of medical Internet research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.
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Who cites it
37 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Electronic health record adaptation and innovation among healthcare professionals in hospitals: an integrative framework based on a systematic review.BMC health services research · 2026Pooled it
- The digital divide among U.S. Hospitals delivering health services to populations with high social disparities.Frontiers in digital health · 2026Article
- Assessing the Impact of Computable Type 2 Diabetes Phenotypes on Predicting Healthcare Utilization Using Electronic Health Records and Administrative Claims.Healthcare (Basel, Switzerland) · 2025Article
- Long-Range Forecasting for Emergency Care Systems in a Highly Dynamic Setting: A Singapore Case Study.Journal of the American College of Emergency Physicians open · 2025Article
- The effects of hospital information system adoption on techno-stress and job satisfaction of nurses working in pediatric clinics.BMC nursing · 2025Article
- Clinical signatures of genetic epilepsies precede diagnosis in electronic medical records of 32,000 individuals.Genetics in medicine : official journal of the American College of Medical Genetics · 2024Article
- Adoption of Electronic Medical Records in Healthcare Facilities in the Emirate of Dubai.Healthcare informatics research · 2024Article
- Natural language processing to identify social determinants of health in Alzheimer's disease and related dementia from electronic health records.Health services research · 2023Article
- An Assessment of Success Factors and Challenges in Implementation of Electronic Medical Record System in Referral Hospital in Northern Tanzania.The East African health research journal · 2023Article
- Evaluating Digital Health Capability at Scale Using the Digital Health Indicator.Applied clinical informatics · 2022Article
- Improving the Prediction of Persistent High Health Care Utilizers: Retrospective Analysis Using Ensemble Methodology.JMIR medical informatics · 2022Article
- Assessing the Value of Unsupervised Clustering in Predicting Persistent High Health Care Utilizers: Retrospective Analysis of Insurance Claims Data.JMIR medical informatics · 2021Article
- A scoping review of knowledge authoring tools used for developing computerized clinical decision support systems.JAMIA open · 2021Article
- Internet Access, Social Risk Factors, and Web-Based Social Support Seeking Behavior: Assessing Correlates of the "Digital Divide" Across Neighborhoods in The State of Maryland.Journal of medical systems · 2021Article
- Assessing seizure burden in pediatric epilepsy using an electronic medical record-based tool through a common data element approach.Epilepsia · 2021Article
- Adoption of Electronic Health Records (EHRs) in China During the Past 10 Years: Consecutive Survey Data Analysis and Comparison of Sino-American Challenges and Experiences.Journal of medical Internet research · 2021Article
- The Cosmos Collaborative: A Vendor-Facilitated Electronic Health Record Data Aggregation Platform.ACI open · 2021Article
- Measuring the Value of a Practical Text Mining Approach to Identify Patients With Housing Issues in the Free-Text Notes in Electronic Health Record: Findings of a Retrospective Cohort Study.Frontiers in public health · 2021Article
- A method for measuring the effect of certified electronic health record technology on childhood immunization status scores among Medicaid managed care network providers.Journal of biomedical informatics · 2020Article
- Trends in the use of computerized physician order entry by health-system affiliated ambulatory clinics in the United States, 2014-2016.BMC health services research · 2020Article
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5 authors.
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Abstract
backgroundThe Meaningful Use (MU) program has promoted electronic health record adoption among US hospitals. Studies have shown that electronic health record adoption has been slower than desired in certain types of hospitals; but generally, the overall adoption rate has increased among hospitals. However, these studies have neither evaluated the adoption of advanced functionalities of electronic health records (beyond MU) nor forecasted electronic health record maturation over an extended period in a holistic fashion. Additional research is needed to prospectively assess US hospitals' electronic health record technology adoption and advancement patterns.
objectiveThis study forecasts the maturation of electronic health record functionality adoption among US hospitals through 2035.
methodsThe Healthcare Information and Management Systems Society (HIMSS) Analytics' Electronic Medical Record Adoption Model (EMRAM) dataset was used to track historic uptakes of various electronic health record functionalities considered critical to improving health care quality and efficiency in hospitals. The Bass model was used to predict the technological diffusion rates for repeated electronic health record adoptions where upgrades undergo rapid technological improvements. The forecast used EMRAM data from 2006 to 2014 to estimate adoption levels to the year 2035.
resultsIn 2014, over 5400 hospitals completed HIMSS' annual EMRAM survey (86%+ of total US hospitals). In 2006, the majority of the US hospitals were in EMRAM Stages 0, 1, and 2. By 2014, most hospitals had achieved Stages 3, 4, and 5. The overall technology diffusion model (ie, the Bass model) reached an adjusted R-squared of .91. The final forecast depicted differing trends for each of the EMRAM stages. In 2006, the first year of observation, peaks of Stages 0 and 1 were shown as electronic health record adoption predates HIMSS' EMRAM. By 2007, Stage 2 reached its peak. Stage 3 reached its full height by 2011, while Stage 4 peaked by 2014. The first three stages created a graph that exhibits the expected "S-curve" for technology diffusion, with inflection point being the peak diffusion rate. This forecast indicates that Stage 5 should peak by 2019 and Stage 6 by 2026. Although this forecast extends to the year 2035, no peak was readily observed for Stage 7. Overall, most hospitals will achieve Stages 5, 6, or 7 of EMRAM by 2020; however, a considerable number of hospitals will not achieve Stage 7 by 2035.
conclusionsWe forecasted the adoption of electronic health record capabilities from a paper-based environment (Stage 0) to an environment where only electronic information is used to document and direct care delivery (Stage 7). According to our forecasts, the majority of hospitals will not reach Stage 7 until 2035, absent major policy changes or leaps in technological capabilities. These results indicate that US hospitals are decades away from fully implementing sophisticated decision support applications and interoperability functionalities in electronic health records as defined by EMRAM's Stage 7.
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