The Influence of Respondent Characteristics on the Validity of Self-Reported Survey Responses

• Published in: Health services research 2016-06, Vol.51 (3), p.937-952
• Main Authors: Guerard, Barbara, Omachonu, Vincent, Harvey, Raymond A., Hernandez, S. Robert, Sen, Bisakha
• Format: Article
• Language: English
• Subjects: Age Factors; Aged; Aged, 80 and over; agreement; Analysis; Bias; chronic condition; Chronic conditions; Chronic Disease - epidemiology; Chronic illnesses; Company systems management; Concordance; Concordances; Conditions; Data Collection - methods; Data Collection - standards; Data Collection, Validity and Use; Drugs; Economic aspects; elderly; Female; Government programs; Health care; Health care information services; Humans; Information management; Insurance Claim Review - statistics & numerical data; Insurance claims; Male; Medical advice systems; Medical records; Medicare; Medicare Part C - statistics & numerical data; Policy making; Polls & surveys; Prescription drugs; Prescription Drugs - administration & dosage; Primary care; Regression analysis; Reporting; Self Report; Sex Factors; Socioeconomic Factors; Statistical methods; Survey; Surveys and Questionnaires; United States; Validity
• ISSN: 0017-9124; 1475-6773
• DOI: 10.1111/1475-6773.12356

Objective To examine concordance between member self‐reports and the organization's administrative claims data for two key health factors: number of chronic conditions, and number of prescription drugs. Data Medicare Advantage plan claims data and member survey data from 2011 to 2012. Design Mailed surveys to 15,000 members, enrolled minimum 6 months, drawn from a random sample of primary care physician practices with at least 200 members. Methods Descriptive statistics were generated for extent of concordance. Multivariable logistic regressions were used to analyze the association of selected respondent characteristics with likelihood of concordance. Findings Concordance for number of chronic conditions was 58.4 percent, with 27.3 percent under‐reporting, 14.2 percent over‐reporting. Concordance for number of prescription drugs was 56.6 percent with 38.9 percent under‐reporting, 4.5 percent over‐reporting. Number of prescriptions and assistance in survey completion were associated with higher likelihood of concordance for chronic conditions. Assistance in survey completion and number of chronic conditions were associated with higher concordance, and age and number of prescriptions were associated with lower concordance, for prescription drugs. Conclusions Self‐reported number of chronic conditions and prescription medications are not in high concordance with claims data. Health care researchers and policy makers using patient self‐reported data should be aware of these potential biases.