Stratified random sampling for estimating billing accuracy in health care systems

Abstract

This paper presents a stratified random sampling plan for estimating accuracy of bill processing performance for the health care bills submitted to third party payers in health care systems. Bill processing accuracy is estimated with two measures: percent accuracy and total dollar accuracy. Difficulties in constructing a sampling plan arise when the population strata structure is unknown, and when the two measures require different sampling schemes. To efficiently utilize sample resource, the sampling plan is designed to effectively estimate both measures from the same sample. The sampling plan features a simple but efficient strata construction method, called rectangular method, and two accuracy estimation methods, one for each measure. The sampling plan is tested on actual populations from an insurance company. Accuracy estimates obtained are then used to compare the rectangular method to other potential clustering methods for strata construction, and compare the accuracy estimation methods to other eligible methods. Computational study results show effectiveness of the proposed sampling plan.