Development of a Medical Record Problem List Reconciliation Algorithm to Enhance Healthcare Accuracy
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2022
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University of Hawaii at Manoa
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The complexity of chronic disease and multimorbidity requires coordination and referral of care to specialists and/or hospitalizations. Access to electronic medical records has led to the use of problem lists as a tool to obtain a snapshot of the patient’s current health status and assist in clinical decision making. Deficits have surfaced within problem list use including a lack of common approach, no standardized process for maintenance, a lack of education regarding problem list construction, problem list completeness, and problem list clutter, such as inactive or resolved conditions. The goal of this project was to develop an evidence-based algorithm for medical record problem list reconciliation to assure quality patient care. The algorithm was piloted on a sample of 82 patients through a problem list reconciliation to evaluate efficacy and reliability in a primary care office setting over a six-month period. Results post-reconciliation consisted of 98% previously diagnosed conditions with the remaining 2% added and confirmed suggesting a superior problem list completeness. Results post-reconciliation revealed challenges with problem list inaccuracy as removal of problems from 93% of the reconciled problem lists was required with a 34% mean reduction post-reconciliation. The pilot test suggests appropriate result of the evidence-based algorithm, which may be incorporated as is into practice or adapted to suit clinic- and/or specialty-specific use. Suggestions for adaptations are presented for subsequent pilot tests as well as implications for future use in practice.
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Medical records--Data processing
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