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Related Experiment Video

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Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

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Published on: January 8, 2020

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

Gal Av-Gay¹, Anshu Parajulee¹, Kathrin Stoll¹

¹Department of Family Practice, Faculty of Medicine University of British Columbia Vancouver British Columbia Canada.

Health Care Science

|July 1, 2024

Summary

Comparing rural surgical quality is challenging. This study proposes a best-practice method using population data and risk stratification, determining minimum sample sizes for accurate facility-level comparisons.

Keywords:

administrative data uses cohort analysis epidemiology evaluation methodology

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Area of Science:

Healthcare quality assessment
Rural health services research
Surgical outcomes analysis

Background:

Rural surgical and obstetrical facility sustainability relies on measurable efficacy and quality of care.
Facility-level comparisons are often hindered by differences in patient demographics, acuity, and services between rural and referral facilities.
Existing comparison methods face limitations due to inherent disparities between healthcare settings.

Purpose of the Study:

To outline limitations in current rural practice evaluations.
To highlight a best-practice approach for facility-level comparisons using population-level data.
To investigate minimum sample-size requirements for reliable rural surgical quality assessment.

Main Methods:

Monte Carlo power analysis to estimate minimum sample sizes for logistic regression and Firth logistic regression.
Comparison of surgical adverse events proportion against facility type, incorporating confounders.
Development of guidelines for a methodology using risk stratification, Firth penalized logistic regression, and noninferiority tests.

Main Results:

Illustrated limitations in facility-level surgical quality comparisons for procedures like hernia repair, colonoscopy, appendectomy, and cesarean delivery.
Identified procedure-specific minimum sample sizes that vary based on the level of risk stratification employed.
Demonstrated the influence of risk stratification on sample size requirements for comparative analyses.

Conclusions:

Administrative data can provide adequate sample sizes for robust facility-level surgical quality comparisons.
Appropriate comparisons can effectively evaluate the efficacy of healthcare providers, including general practitioners and nurse practitioners, in low-acuity procedures.
The proposed methodology enhances the evaluation of rural healthcare quality and provider performance.