OJS  Vol.4 No.10 , December 2014
Improving Model Specifications When Estimating Treatment Effects across Alternative Medical Interventions
Abstract: Objective: The purpose of this paper is to critique the list of independent variables commonly used in observational research and test the impact of variables for prior use and treatment history on estimates of treatment effects. Methods: Using data from the California Medicaid program, this study generated a series of OLS estimates of the effect of atypical antipsychotic medications on costs and duration of therapy to illustrate the impact of alternative model specifications on treatment effects. The first sequence of estimates consisted of six model specifications, the last of which included variables reflecting the type of episode defined according to prior treatment history and compliance. The second sequences repeated the specification of the first 6 models but were carried out separately by episode type to examine the heterogeneity of treatment effect. The second sequence of models documented the impact of additional drug history variables. Results: Estimates of the impact of atypical antipsychotic use on total costs and duration on initial drug were statistically significant in the first 6 models. Estimates changed significantly when dummy variables indicating prior use of inpatient service and nursing home care were included in the model specification. Estimated effects changed substantially when prior total cost was included in cost analysis, or when prior treatment duration was included in duration analysis. Significant variation also existed in estimated effects across episode types, and it was particularly pronounced before controlling for prior cost/duration. Conclusion: It is important to add prior measures of the outcome variable to control for unobserved bias in retrospective studies. Also, the accuracy and utility of results to clinicians can be improved significantly if analyses are performed by episode type.
Cite this paper: Jiang, Y. and McCombs, J. (2014) Improving Model Specifications When Estimating Treatment Effects across Alternative Medical Interventions. Open Journal of Statistics, 4, 857-867. doi: 10.4236/ojs.2014.410081.

[1]   Faries, D.E., Leon, A.C., Haro, J.M. and Obenchain, R.L. (2010) Analysis of Observational Health Care Data Using SAS. SAS Institute.

[2]   Berger, M.L., Dreyer, N., Anderson, F., Towse, A., Sedrakyan, A. and Normand, S.L. (2012) Prospective Observational Studies to Assess Comparative Effectiveness: The ISPOR Good Research Practices Task Force Report. Value in Health, 15, 217-230.

[3]   Soumerai, S.B., Zhang, F., Ross-Degnan, D., Ball, D.E., LeCates, R.F., Law, M.R., Hughes, T.E., Chapman, D. and Adams, A.S. (2008) Use of Atypical Antipsychotic Drugs for Schizophrenia in Maine Medicaid Following a Policy Change. Health Affairs, 27, 185-195.

[4]   Greene, W.H. (2012) Econometric Analysis. Pearson Education, Inc., Upper Saddle River.

[5]   Chen, L., McCombs, J.S. and Park, J. (2008) Duration of Antipsychotic Drug Therapy in Real-World Practice: A Comparison with CATIE Trial Results. Value in Health, 11, 487-496.

[6]   Chen, L., McCombs, J.S. and Park, J. (2008) The Impact of Atypical Antipsychotic Medications on the Use of Health Care by Patients with Schizophrenia. Value in Health, 11, 34-43.

[7]   Narayan, S., Sterling, K.L. and McCombs, J.S. (2006) The Impact of Open Access to Atypical Antipsychotics on Treatment Costs for Medical Patients with Bipolar Disorder. Disease Management & Health Outcomes, 14, 287-301.

[8]   Weiden, P.J. (2004) Partial Compliance and Risk of Rehospitalization among California Medicaid Patients with Schizophrenia. Psychiatric Services, 55, 886-891.

[9]   Gianfrancesco, F.D., Grogg, A.L., Mahmoud, R.A., Wang, R.-H. and Nasrallah, H.A. (2002) Differential Effects of Risperidone, Olanzapine, Clozapine, and Conventional Antipsychotics on Type 2 Diabetes: Findings from a Large Health Plan Database. The Journal of Clinical Psychiatry, 63, 920-930.

[10]   Gianfrancesco, F., Pesa, J., Wang, R.-H. and Nasrallah, H. (2006) Assessment of Antipsychotic-Related Risk of Diabetes Mellitus in a Medicaid Psychosis Population: Sensitivity to Study Design. American Journal of Health-System Pharmacy, 63, 431-441.