Interactive voice response reminder effects on preventive service utilization.

This study evaluated the effects of interactive voice response (IVR) system reminders to managed care organization (MCO) members to obtain mammograms, Papanicolaou (Pap) tests, and influenza immunizations. The MCO identified 3 member cohorts and sent IVR reminders to get preventive services. Analyses employed claims data to examine relationships between IVR reminders and preventive service use 5 to 9 months post-intervention among members without prior utilization. Multivariate logistic regressions controlling for age, gender (for influenza immunizations), and risk stratum confirmed hypothesized relationships between intervention and preventive services: mammograms, odds ratio (OR) = 1.263 (95% confidence interval [CI] = 1.104, 1.444); Pap tests, OR = 1.241 (1.107, 1.391); influenza immunizations, OR = 2.072 (1.665, 2.580). IVR reminders are associated with higher rates of mammograms, Pap tests, and influenza immunizations. Study limitations include unknown generalizability of results and possible self-selection. There is justification for more IVR interventions and research to enhance MCO members' preventive service utilization.

Assessing return on investment of defined-population disease management interventions.

BACKGROUND: Strategies to reduce health expenditures through the improvement of health and quality of care are in high demand. A group of experts formed a nonpartisan, independent work group, under the sponsorship of the National Managed Health Care Congress. Its goal was to establish a list of easy-to-understand, actionable, and usable recommendations to enable disease management program advocates to conduct basic-level evaluations. RECOMMENDATIONS: The work group made recommendations concerning identification of reference and intervention population, population definitions, quantitative methods and data quality, confounding and bias, and stakeholder agreements/contracting. CASE STUDY: A case study was created to quantitatively illustrate some of the major issues raised by the work group. Five typical errors were simulated by applying different rules to the intervention population than to the reference population: differential inclusion (high versus low risk), differential exclusion (high versus low risk) and differential claims run-out. Compared with the true impact, four of the five errors resulted in a bias toward "intervention effect," while one (differential inclusion of high-risk patients) was biased against the "intervention effect." The direction and magnitude of the bias in natural settings will not necessarily follow this pattern.