Effects of prior authorization on medication discontinuation among Medicaid beneficiaries with bipolar disorder

Use of interrupted time series analysis in evaluating health care quality improvements

Interrupted time series (ITS) analysis is arguably the strongest quasi-experimental research design. ITS is particularly useful when a randomized trial is infeasible or unethical. The approach usually involves constructing a time series of population-level rates for a particular quality improvement focus (eg, rates of attention-deficit/hyperactivity disorder [ADHD] medication initiation) and testing statistically for a change in the outcome rate in the time periods before and time periods after implementation of a policy/program designed to change the outcome. In parallel, investigators often analyze rates of negative outcomes that might be (unintentionally) affected by the policy/program. We discuss why ITS is a useful tool for quality improvement. Strengths of ITS include the ability to control for secular trends in the data (unlike a 2-period before-and-after t test), ability to evaluate outcomes using population-level data, clear graphical presentation of results, ease of conducting stratified analyses, and ability to evaluate both intended and unintended consequences of interventions. Limitations of ITS include the need for a minimum of 8 time periods before and 8 after an intervention to evaluate changes statistically, difficulty in analyzing the independent impact of separate components of a program that are implemented close together in time, and existence of a suitable control population. Investigators must also be careful not to make individual-level inferences when population-level rates are used to evaluate interventions (though ITS can be used with individual-level data). A brief description of ITS is provided, including a fully implemented (but hypothetical) study of the impact of a program to reduce ADHD medication initiation in children younger than 5 years old and insured by Medicaid in Washington State. An example of the database needed to conduct an ITS is provided, as well as SAS code to implement a difference-in-differences model using preschool-age children in California as a comparison group.

Medicaid medication access problems and increased psychiatric hospital and emergency care

OBJECTIVES

To quantify the extent to which Medicaid programs may incur increased psychiatric emergency department and hospital use associated with clinically unintended medication discontinuations, gaps, switches and other access problems attributed to prescription drug coverage and management.

METHOD

This study uses clinically detailed, physician-reported data. A total of 4866 psychiatrists in 10 states were randomly selected from the AMA Masterfile; 62% responded and 32% treated Medicaid patients and reported on 1625 systematically selected Medicaid patients. Propensity score multivariate models assessed predicted probabilities and mean number of emergency department visits and hospital days.

RESULTS

Many patients (46.0%, S.E.=1.3%) had medication access problems reported during the past year, including discontinuing or switching medications or inability to obtain clinically indicated prescriptions because of drug coverage or management. The expected number of emergency department visits was estimated to be 73.8% higher among patients with medication access problems reported compared to matched patients without access problems reported. Among acute stay inpatients, the expected number of hospital days was 71.7% higher for patients with medication access problems reported.

CONCLUSIONS

Medication access problems may have significant implications for Medicaid programs. The potential indirect costs of these policies in psychiatric and social services utilization should be considered in addition to direct pharmacy costs.