Open Source Electronic Health Records: Will They Support the Clinical Data Needs of the Future? (Part 1 of 2)

Open source software missed out on making a major advance into health care when it was bypassed during hospitals’ recent stampede toward electronic health records, triggered over the past few years by Meaningful Use incentives. Some people blame the neglect of open source alternatives on a lack of marketing (few open source projects are set up to woo non-technical adoptors), some on conservative thinking among clinicians and their administrators, and some on the readiness of the software. I decided to put aside the past and look toward the next stage of EHRs. As Meaningful Use ramps down and clinicians have to look for value in EHRs, can the open source options provide what they need?

The oncoming end of Meaningful Use payments (which never came close to covering the costs of proprietary EHRs, but nudged many hospitals and doctors to buy them) may open a new avenue to open source. Deanne Clark of DSS, which markets a VistA-based product called vxVistA, believes open source EHRs are already being discovered by institutions with tight budgets, and that as Meaningful Use reimbursements go away, open source will be even more appealing.

My question in this article, though, is whether open source EHRs will meet the sophisticated information needs of emerging medical institutions, such as Accountable Care Organizations (ACOs). Shahid Shah has suggested some of the EHR requirements of ACOs. To survive in an environment of shrinking reimbursement and pay-for-value, more hospitals and clinics will have to beef up their uses of patient data, leading to some very non-traditional uses for EHRs.

EHRs will be asked to identify high-risk patients, alert physicians to recommended treatments (the core of evidence-based medicine), support more efficient use of clinical resources, contribute to population health measures, support coordinated care, and generally facilitate new relationships among caretakers and with the patient. A host of tools can be demanded by users as part of the EHR role, but I find that they reduce to two basic requirements:

  • The ability to interchange data seamlessly, a requirement for coordinated care and therefore accountable care. Developers could also hook into the data to create mobile apps that enhance the value of the EHR.

  • Support for analytics, which will support all the data-rich applications modern institutions need.

Eventually, I would also hope that EHRs accept patient-generated data, which may be stored in types and formats not recognized by existing EHRs. But the clinical application of patient-generated data is far off. Fred Trotter, a big advocate for open source software, says, “I’m dubious at best about the notion that Quantified Self data (which can be very valuable to the patients themselves) is valuable to a doctor. The data doctors want will not come from popular commercial QS devices, but from FDA-approved medical devices, which are more expensive and cumbersome.”

Some health reformers also cast doubt on the value of analytics. One developer on an open source EHR labeled the whole use of analytics to drive ACO decisions as “bull” (he actually used a stronger version of the word). He aired an opinion many clinicians hold, that good medicine comes from the old-fashioned doctor/patient relationship and giving the patient plenty of attention. In this philosophy, the doctor doesn’t need analytics to tell him or her how many patients have diabetes with complications. He or she needs the time to help the diabetic with complications keep to a treatment plan.

I find this attitude short-sighted. Analytics are proving their value now that clinicians are getting serious about using them–most notably since Medicare penalizes hospital readmissions with 30 days of discharge. Open source EHRs should be the best of breed in this area so they can compete with the better-funded but clumsy proprietary offerings, and so that they can make a lasting contribution to better health care.

The next installment of this article looks at current support for interoperability and analytics in open-source EHRs.

About the author

Andy Oram

Andy Oram

Andy Oram writes and edits documents about many aspects of computing, ranging in size from blog postings to full-length books. Topics cover a wide range of computer technologies: data science and machine learning, programming languages, Web performance, Internet of Things, databases, free and open source software, and more. My editorial output at O'Reilly Media included the first books ever published commercially in the United States on Linux, the 2001 title Peer-to-Peer (frequently cited in connection with those technologies), and the 2007 title Beautiful Code. He is a regular correspondent on health IT and health policy for He also contributes to other publications about policy issues related to the Internet and about trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business.


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