Barriers to Achieving Economies of Scale in Analysis of EHR DataA Cautionary TaleThis work was supported internally by the Duke Clinical Research Institute.
22 March 2017
accepted in revised form: 15 June 2017
20 December 2017 (online)
Signed in 2009, the Health Information Technology for Economic and Clinical Health Act infused $28 billion of federal funds to accelerate adoption of electronic health records (EHRs). Yet, EHRs have produced mixed results and have even raised concern that the current technology ecosystem stifles innovation. We describe the development process and report initial outcomes of a chronic kidney disease analytics application that identifies high-risk patients for nephrology referral. The cost to validate and integrate the analytics application into clinical workflow was $217,138. Despite the success of the program, redundant development and validation efforts will require $38.8 million to scale the application across all multihospital systems in the nation. We address the shortcomings of current technology investments and distill insights from the technology industry. To yield a return on technology investments, we propose policy changes that address the underlying issues now being imposed on the system by an ineffective technology business model.
Citation: Sendak MP, Balu S, Schulman KH. Barriers to Achieving Economies of Scale in Analysis of EHR Data. Appl Clin Inform 2017; 8: 826–831 https://doi.org/10.4338/ACI-2017-03-CR-0046
Damon M. Seils, MA, Duke University, assisted with manuscript preparation. Mr Seils did not receive compensation for his assistance apart from his employment at Duke University.
Clinical Relevance Statement
Health information technology can be used to improve the detection and management of chronic kidney disease at the population level, but requires significant investment. Unfortunately, existing electronic health record systems do not enable rapid and efficient use of data to drive population health management programs. Health care systems must transform their technology infrastructure to achieve efficiencies of scale and advance population health.
Human Subjects Protections
No human subjects were involved in this work. The study was approved by the institutional review board of the Duke University Health System.
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