Abstract

BackgroundEstimating harm rates for specific patient populations and detecting significant changes in them over time are essential if patient safety in general practice is to be improved. Clinical record review (CRR) is arguably the most suitable method for these purposes, but the optimal values and combinations of its parameters (such as numbers of records and practices) remain unknown. Our aims were to: 1. Determine and quantify CRR parameters; 2. Assess the precision and power of feasible CRR scenarios; and 3. Quantify the minimum requirements for adequate precision and acceptable power.MethodWe explored precision and power of CRR scenarios using Monte Carlo simulation. A range of parameter values were combined in 864 different CRR scenarios, with 1000 random data sets generated for each, and harm rates were estimated and tested for change over time by fitting a generalised linear model with a Poisson response.ResultsCRR scenarios with ≥100 detected harm incidents had harm rate estimates with acceptable precision. Harm reductions of 20% or ≥50% were detected with adequate power by those CRR scenarios with at least 100 and 500 harm incidents respectively. The number of detected harm incidents was dependent on the baseline harm rate multiplied by: the period of time reviewed in each record; number of records reviewed per practice; number of practices who reviewed records; and the number of times each record was reviewed.ConclusionWe developed a simple formula to calculate the minimum values of CRR parameters required to achieve adequate precision and acceptable power when monitoring harm rates. Our findings have practical implications for health care decision-makers, leaders and researchers aiming to measure and reduce harm at regional or national level.

Highlights

  • Estimating harm rates for specific patient populations and detecting significant changes in them over time are essential if patient safety in general practice is to be improved

  • Harm reductions of 20% or ≥50% were detected with adequate power by those Clinical record review (CRR) scenarios with at least 100 and 500 harm incidents respectively

  • We developed a simple formula to calculate the minimum values of CRR parameters required to achieve adequate precision and acceptable power when monitoring harm rates

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Summary

Introduction

Estimating harm rates for specific patient populations and detecting significant changes in them over time are essential if patient safety in general practice is to be improved. It is generally accepted that a significant minority of patients may suffer preventable harm as a result of their interaction with health care [1]. A number of explicit patient safety risks have been identified, the incidence of harm in primary care has not yet been quantified reliably [4]. This is essential to understand the scale of the safety problem and to inform the design and implementation of improvement initiatives. The second challenge is to evaluate the impact of these interventions through serial monitoring to determine if improvement efforts are beneficial and leading to safer care or to otherwise adapt them to ensure they are

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