Evaluating rural health outcomes: A methodological approach using population-level data

Gal Av-Gay, Anshu Parajulee, Kathrin Stoll, Jude Kornelsen
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Abstract

Background

The sustainability of rural surgical and obstetrical facilities depends on their efficacy and quality of care, which are difficult to measure in a rural context. In an evaluation of rural practice, it is often the case that the only comparators are larger referral facilities, for which facility-level comparisons are difficult due to differences in population demographics, acuity of patients, and services offered. This publication outlines these limitations and highlights a best-practice approach to making facility-level comparisons using population-level data, risk stratification, tests of noninferiority, and Firth logistic regression analysis. This includes an investigation of minimum sample-size requirements through Monte Carlo power analysis in the context of low-acuity rural surgical care.

Methods

Monte Carlo power analysis was used to estimate the minimum sample size required to achieve a power of 0.8 for both logistic regression and Firth logistic regression models that compare the proportion of surgical adverse events against facility type, among other confounders. We provide guidelines for the implementation of a recommended methodology that uses risk stratification, Firth penalized logistic regression, and tests of noninferiority.

Results

We illustrate limitations in facility-level comparison of surgical quality among patients undergoing one of four index procedures including hernia repair, colonoscopy, appendectomy, and cesarean delivery. We identified minimum sample sizes for comparison of each index procedure that fluctuate depending on the level of risk stratification used.

Conclusion

The availability of administrative data can provide an adequate sample size to allow for facility-level comparisons in surgical quality, at the rural level and elsewhere. When they are made appropriately, these comparisons can be used to evaluate the efficacy of general practitioners and nurse practitioners in performing low-acuity procedures.

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评估农村健康成果:使用人口数据的方法论
农村外科和产科医疗机构的可持续性取决于其疗效和医疗质量,而这在农村地区很难衡量。在对农村医疗机构进行评估时,往往只能将较大的转诊机构作为比较对象,而由于人口统计、患者病情严重程度和所提供服务等方面的差异,很难对这些机构进行机构层面的比较。本刊物概述了这些局限性,并重点介绍了使用人群数据、风险分层、非劣效性检验和 Firth logistic 回归分析进行机构级别比较的最佳实践方法。蒙特卡洛功率分析用于估算逻辑回归和 Firth 逻辑回归模型达到 0.8 功率所需的最小样本量,该模型将手术不良事件的比例与设施类型及其他混杂因素进行比较。我们说明了对接受疝修补术、结肠镜检查、阑尾切除术和剖宫产术等四种指标手术之一的患者进行设施水平手术质量比较的局限性。我们确定了每种指标手术的最低比较样本量,这些样本量会根据所使用的风险分层水平而波动。行政数据的可用性可以提供足够的样本量,以便在农村和其他地区进行医疗机构层面的手术质量比较。在适当的情况下,这些比较可用于评估全科医生和执业护士在进行低急性手术时的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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