Catching up on health outcomes: The Texas medication algorithm project

T. Michael Kashner, Thomas J. Carmody, Trisha Suppes, A. John Rush, M. Lynn Crismon, Alexander L Miller, Marcia Toprac, Madhukar Trivedi

Research output: Contribution to journalArticle

27 Citations (Scopus)

Abstract

Objective. To develop a statistic measuring the impact of algorithm-driven disease management programs on outcomes for patients with chronic mental illness that allowed for treatment-as-usual controls to "catch up" to early gains of treated patients. Data Sources/Study Setting. Statistical power was estimated from simulated samples representing effect sizes that grew, remained constant, or declined following an initial improvement. Estimates were based on the Texas Medication Algorithm Project on adult patients (age ≥ 18) with bipolar disorder (n = 267) who received care between 1998 and 2000 at 1 of 11 clinics across Texas. Study Design. Study patients were assessed at baseline and three-month follow-up for a minimum of one year. Program tracks were assigned by clinic. Data Collection/Extraction Methods. Hierarchical linear modeling was modified to account for declining-effects. Outcomes were based on 30-item Inventory for Depression Symptomatology - Clinician Version. Principal Findings. Declining-effect analyses had significantly greater power detecting program differences than traditional growth models in constant and declining-effects cases. Bipolar patients with severe depressive symptoms in an algorithm-driven, disease management program reported fewer symptoms after three months, with treatment-as-usual controls "catching up" within one year. Conclusions. In addition to psychometric properties, data collection design, and power, investigators should consider how outcomes unfold over time when selecting an appropriate statistic to evaluate service interventions. Declining-effect analyses may be applicable to a wide range of treatment and intervention trials.

Original languageEnglish (US)
Pages (from-to)311-331
Number of pages21
JournalHealth Services Research
Volume38
Issue number1 I
StatePublished - Feb 2003

Fingerprint

medication
Health
health
Disease Management
statistics
Depression
Disease
Information Storage and Retrieval
great power
Bipolar Disorder
management
Psychometrics
mental illness
psychometrics
chronic illness
Chronic Disease
Therapeutics
Research Personnel
Equipment and Supplies
Growth

Keywords

  • Disease management systems
  • Program evaluation
  • Severe mental illness
  • Treatment algorithm

ASJC Scopus subject areas

  • Nursing(all)
  • Health(social science)
  • Health Professions(all)
  • Health Policy

Cite this

Kashner, T. M., Carmody, T. J., Suppes, T., Rush, A. J., Crismon, M. L., Miller, A. L., ... Trivedi, M. (2003). Catching up on health outcomes: The Texas medication algorithm project. Health Services Research, 38(1 I), 311-331.

Catching up on health outcomes : The Texas medication algorithm project. / Kashner, T. Michael; Carmody, Thomas J.; Suppes, Trisha; Rush, A. John; Crismon, M. Lynn; Miller, Alexander L; Toprac, Marcia; Trivedi, Madhukar.

In: Health Services Research, Vol. 38, No. 1 I, 02.2003, p. 311-331.

Research output: Contribution to journalArticle

Kashner, TM, Carmody, TJ, Suppes, T, Rush, AJ, Crismon, ML, Miller, AL, Toprac, M & Trivedi, M 2003, 'Catching up on health outcomes: The Texas medication algorithm project', Health Services Research, vol. 38, no. 1 I, pp. 311-331.
Kashner TM, Carmody TJ, Suppes T, Rush AJ, Crismon ML, Miller AL et al. Catching up on health outcomes: The Texas medication algorithm project. Health Services Research. 2003 Feb;38(1 I):311-331.
Kashner, T. Michael ; Carmody, Thomas J. ; Suppes, Trisha ; Rush, A. John ; Crismon, M. Lynn ; Miller, Alexander L ; Toprac, Marcia ; Trivedi, Madhukar. / Catching up on health outcomes : The Texas medication algorithm project. In: Health Services Research. 2003 ; Vol. 38, No. 1 I. pp. 311-331.
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