Abstract
BackgroundMost available quality indicators for hospitals are represented by simple ratios or proportions, and are limited to specific events. A generalized method that can be applied to diverse clinical events has not been developed. The aim of this study was to develop a simple method of evaluating physicians' prescription patterns for diverse events and their level of awareness of clinical practice guidelines.Methods and FindingsWe developed a quantitative method called Prescription pattern Around Clinical Event (PACE), which is applicable to electronic health records (EHRs). Three discrete prescription patterns (intervention, maintenance, and discontinuation) were determined based on the prescription change index (PCI), which was calculated by means of the increase or decrease in the prescription rate after a clinical event. Hyperkalemia and Clostridium difficile-associated diarrhea (CDAD) were used as example cases. We calculated the PCIs of 10 drugs related to hyperkalemia, categorized them into prescription patterns, and then compared the resulting prescription patterns with the known standards for hyperkalemia treatment. The hyperkalemia knowledge of physicians was estimated using a questionnaire and compared to the prescription pattern. Prescriptions for CDAD were also determined and compared to clinical knowledge. Clinical data of 1698, 348, and 1288 patients were collected from EHR data. The physicians prescribing behaviors for hyperkalemia and CDAD were concordant with the standard knowledge. Prescription patterns were well correlated with individual physicians' knowledge of hyperkalemia (κ = 0.714). Prescribing behaviors according to event severity or clinical condition were plotted as a simple summary graph.ConclusionThe algorithm successfully assessed the prescribing patterns from the EHR data. The prescription patterns were well correlated with physicians' knowledge. We expect that this algorithm will enable quantification of prescribers' adherence to clinical guidelines and be used to facilitate improved prescribing practices.
Highlights
Treatment adherence to clinical practice guidelines is emphasized because these guidelines help physicians keep their practice current [1]
prescription change index (PCI) and prescription patterns To determine whether the number of prescriptions increased or decreased after a specific clinical event, we defined PCI as follows: PCI ~ slopeD{1,Dz1 slopeD{4,D{2 where, slopet1,t2 refers to the average slope of the cumulative sum of prescription counts from t1 to t2 (Figure 1)
The first proof-of-concept study was designed to test whether the prescription patterns derived electronic health records (EHRs) data corresponded to current knowledge on hyperkalemia management
Summary
Treatment adherence to clinical practice guidelines is emphasized because these guidelines help physicians keep their practice current [1]. Many quality indicators for hospitals are available, such as those provided by the Agency for Healthcare Research and Quality; many of these are simple ratios or proportions that consider quantitative clinical outcomes, such as rates of admission, adverse events, and mortality. A quality indicator applied to a specific outcome usually cannot be used to measure other unintended clinical events. No generalized method that can be applied to diverse clinical events or behaviors of physicians has been developed. Existing methods cannot evaluate whether physicians recognize clinical practice guidelines. A generalized method that can be applied to diverse clinical events has not been developed. The aim of this study was to develop a simple method of evaluating physicians’ prescription patterns for diverse events and their level of awareness of clinical practice guidelines
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