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Big Patient Data – How will Doctors cope?

Ambulatory Medical Records (AMR) for practices and Electronic Medical Records (EMR) for hospitals are broadly deployed. Interoperability is still a barrier to creating the “patient longitudinal medical record” (the white whale of policy makers!).  Health Information Exchanges (HIEs) and supporting technologies struggle with patient identity reconciliation, variations of AMR/EMR data structures, medical language, and myriad other inconsistencies. For now, little has changed for doctors other than technical presentation and method of documentation when it comes to their personal tools and use of patient medical data.

Doctors use what they create or is created for them, within the four walls of their practice. They may have added transmissions from their hospital of choice for patient care reports. These “feeds” have been personally and painfully defined to support each doctor’s information preferences. Patient data originates from one or a few trusted and well-understood venues. There is an assumption of credibility, interpretation, and data provenance which makes patient data reliably useful to clinical decision making. Let’s call this small patient data. The physician user has intimate oversight of all the content and some degree of confidence in its usefulness and reliability.

What happens to the clarity of presentation, interpretation, and confidence of credibility when small patient data becomes big patient data? HIEs and data interoperability lower barriers to patient data consolidation, doctors are thrilled with all this newly accessible history and insight into evaluations and care plans by other physicians engaged by the patient to handle medical conditions, outside their field of expertise. Being more data-enabled can only be an asset to providing the most effective care patients deserve and physicians are committed to deliver.  Right?

But what about data provenance? Who created the data being viewed?  Is use of medical language consistent across all contributors?  How are conflicts in medication lists, allergies, and medical histories be reconciled? How confident should a doctor be that all data presented in the emerging longitudinal patient record belongs to the patient being treated? If a physician is going to use patient data to make serious medical decisions (and they are all serious) then shouldn’t they be confident of the credibility of patient information supplied and of their interpretation of that data?

Confidence in newly accessible patient data is one challenge that must be addressed, but the challenges of practice in a “post HIE world” do not end there.

Physicians already struggle to consume patient information efficiently from digital presentations. How will doctors sift through oceans of patient data to recognize and use those elements that are meaningful and relevant to making informed clinical decisions?

How will sensitive medical information be handled to provide some measure of privacy and confidence to patients?   Policymakers and lawmakers must establish frameworks for managing patient data they have encouraged providers to create. Ideally, frameworks address new legal liabilities arising from questions about information used in clinical care. Health Informaticists need to get busy analyzing electronic patient data quality to construct standards for data provenance. HIEs and tool suppliers must develop screening mechanisms to apply data provenance guidelines as practitioners seek to join an HIE and when submitting data from their clinical practice for general use. HIT vendors must work to incorporate learning software technologies into physician-patient data presentations to assist doctors by sorting out relevant information from the unrelated patient data available to them. Informaticists and research physicians must analyze the issues of relevancy determination. Reliance on tool- and standards-based patient data use must be a protected clinical practice if physicians are to be expected to rely on patient medical data that they were not involved in creating.

Welcome to big patient data!

Building a patient data governance/management/tool strategy?  We can help.  Contact BrightWork Advisory to discuss a consulting engagement to support your efforts today.

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