4110.1: Tuesday, November 14, 2000 - Board 5

Abstract #5129

Assessing the validity of managed care quality assurance data: a model

Rohit Bhalla, MD, Public Health/Preventive Medicine Residency, New York City Department of Health, 346 Broadway, CN-12, New York, NY 10013, 212-442-3534, rbhalla@dohlan.cn.ci.nyc.ny.us and Linda Barr Gale, RD, MPH, MS, Division of Health Care Access, NYC Dept. of Health, 225 Broadway, 17th Floor, New York, NY 10007.

NP Objective: The purpose of this paper is to present a model for evaluating the validity of quality assurance data. Managed care prenatal care access and low birth weight quality assurance measures are used for illustration. Methods: A correlational (ecologic) study design is proposed to analyze quality assurance data. The model assumes that there is a linear relationship between increasing level of prenatal care and decreasing level of low birth weight across the managed care population for which quality assurance data are available, as implied from current quality assurance and policy initiatives. Prenatal care access is represented as percentage of eligible pregnant women receiving a desired number of prenatal care visits or percentage initiating prenatal care in the first trimester of pregnancy (x-axis). These process measures are plotted by managed care plan, against the outcome measure of percentage of women delivering a low birth weight infant (y-axis). Results: A correlation coefficient of close to -1 would be expected. Implications for the validity of the corresponding quality assurance methodology are examined across the range of possible results from -1 to +1. Possible results are assessed in the context of characteristics of monitored populations, methods of quality assurance data measurement and procurement, limitations of correlational study designs, and policy efforts to reduce infant mortality. Conclusions: A correlational analysis of corresponding process and outcome quality asurance indicators is a useful tool for assessing the quality of quality assurance data and monitoring contracts.

Learning Objectives: 1. Define the nature of the underlying relationship between prenatal care access and low birth weight implied in current quality assurance programs. 2. Apply correlational study methods in analyzing quality assurance data. 3. Interpret possible results from such an analysis. 4. Recognize the value of assessing the quality of quality assurance data

Keywords: Quality Assurance, Managed Care

Presenting author's disclosure statement:
Organization/institution whose products or services will be discussed: None
I do not have any significant financial interest/arrangement or affiliation with any organization/institution whose products or services are being discussed in this session.

The 128th Annual Meeting of APHA