Instrumental variable methods to assess quality of care the marginal effects of process-of-care on blood pressure change and treatment costs.

BACKGROUND

Hypertension is poorly controlled. Team-based care and changes in the process of care have been proposed to address these quality problems. However, assessing care processes is difficult because they are often confounded even in randomized behavioral studies by unmeasured confounders based on discretion of health care providers.

OBJECTIVE

To evaluate the effects of process measures including number of counseling sessions about lifestyle modification and number of antihypertensive medications on blood pressure change and payer-perspective treatment costs.

METHODS

Data were obtained from two prospective, cluster randomized controlled clinical trials (Trial A and B) implementing physician-pharmacist collaborative interventions compared with usual care over six months in community-based medical offices in the Midwest. Multivariate linear regression models with both instrumental variable methods and as-treated methods were utilized. Instruments were indicators for trial and study arms. Models of blood pressure change and costs included both process measures, demographic variables, and clinical variables.

RESULTS

The analysis included 496 subjects. As-treated methods showed no significant associations between process and outcomes. The instruments used in the study were insufficient to simultaneously identify distinct process effects. However, the post-hoc instrumental variable models including one process measure at a time while controlling for the other process demonstrated significant associations between the processes and outcomes with estimates considerably larger than as-treated estimates.

CONCLUSIONS

Instrumental variable methods with combined randomized behavioral studies may be useful to evaluate the effects of different care processes. However, substantial distinct process variation across studies is needed to fully capitalize on this approach. Instrumental variable methods focusing on individual processes provided larger and stronger outcome relationships than those found using as-treated methods which are subject to confounding.