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Monitoring and Management for Metabolic Effects of Antipsychotics
Richard R. Owen, MD
Central Arkansas Veterans Healthcare System Eugene J. Towbin Healthcare Center, Little Rock, AR
No. Little Rock, AR
Funding Period: September 2010 - September 2015
Second-generation antipsychotics (SGAs) are prescribed to over 80% of veterans with psychotic disorders. Unfortunately, treatment with many SGAs is associated with metabolic side effects such as obesity, diabetes, and hyperlipidemia. Recommendations for monitoring and management of these effects are contained in VA clinical practice guidelines for psychoses, obesity, diabetes, and dyslipidemia. However, research has found low rates of metabolic monitoring and significant delays in management of metabolic abnormalities among patients treated with antipsychotics. In 2008, VA Mental Health Services developed a national implementation strategy, which involved education (including a 2010 national meeting) and a technical support center to increase rates of metabolic side effect monitoring and appropriate management of these effects. The proposed study tested an implementation intervention to enhance uptake of evidence-based tools and strategies to improve monitoring and management of metabolic side effects of antipsychotics, within the context of the national implementation effort.
Objective 1: To test the effect of an Evidence-Based Quality Improvement / Facilitation (EBQI/F) intervention as an augmentation to the national implementation strategy on monitoring of metabolic side effects of antipsychotics.
Objective 2: To test the effect of the EBQI/F intervention as an augmentation to the national implementation strategy on management of metabolic side effects of antipsychotics.
Objective 3: To assess the direct costs of the EBQI/F intervention, and to explore variations in costs of the EBQI/F intervention in sites with low- versus high- organizational readiness-to-change.
The study employed a cluster-randomized design to test the EBQI/F intervention combined with the national implementation strategy, compared to the national implementation strategy alone. The study was conducted at 12 facilities that were systematically selected based on performance on relevant clinical indicators. Sites were matched on a measure of organizational stress and randomized to intervention or control conditions. The intervention included a site visit, during which EBQI methods were used to facilitate the development of an implementation plan by site personnel; ongoing external facilitation by a study team member; and access to effective quality improvement tools and strategies, e.g., a VistA computer routine that produced weekly reports of patients due for monitoring or management actions.
Rates of monitoring for weight, glucose/hemoglobin A1c, and LDL within 30 days of a new antipsychotic prescription (baseline) and 31-120 days later (follow-up) were determined using CDW data. CPRS record review was performed to assess management of weight gain, hyperglycemia/elevated hemoglobin A1c, and elevated LDL. Descriptive analyses were conducted and repeated measures regression analyses were performed to examine intervention effects on performance of guideline-recommended metabolic monitoring and management during pre-implementation, implementation, and post-implementation study periods, controlling for sociodemographic variables. Formative evaluation methods were also used to support development of local implementation strategies, document and evaluate the process and success of the EBQI/F intervention, identify barriers/facilitators, and identify potential refinements to the intervention for future implementation efforts.
Qualitative analysis of developmental formative evaluation interviews with providers (N = 91) identified numerous barriers to following metabolic monitoring and management recommendations, including inadequate staffing, insufficient provider time, missing equipment, lab issues, lack of provider knowledge, issues with relevant clinical reminders, inter-provider communication, missed appointments, patient preferences, and lack of patient education.
A total of 16,476 patients were identified throughout the study periods as having a new antipsychotic prescription requiring metabolic monitoring. Monitoring rates were low overall. Interestingly, monitoring rates at all sites tended to decline throughout the study. However, at intervention sites, rates of baseline monitoring for the three metabolic parameters decreased less from pre-implementation to implementation periods than did monitoring for the comparable parameters at control sites. The intervention x time interaction terms were significant both for baseline weight monitoring (OR = 1.19, 95% CI 1.02-1.38) and follow-up weight monitoring (OR = 1.20, 95% CI 1.03-1.39). Intervention x time interactions were not significant for monitoring rates of glucose/hemoglobin A1c or LDL. Over 1,000 medical records of patients who developed new metabolic side effects were reviewed. Rates of management actions were modest (e.g., only 32.9% of patients with elevated glucose had management action(s) within 30 days). There were no substantial differences between intervention and control groups with regard to change over time, except for glucose management, which increased from 28.6% to 48.6% at intervention sites, but only from 32.3% to 40.5% at control sites.
Implementation-focused and summative formative evaluation found that uptake of quality improvement tools was limited, in part due to insufficient staff time, staff turnover, and competing demands to complete other initiatives. Costs of implementation efforts were similar to those reported in previous studies, and mainly consisted of external facilitators' time.
This project addressed an important patient safety concern for Veterans taking antipsychotic medications, specifically the need for timely monitoring and management of metabolic side effects of antipsychotics. The EBQI intervention only affected weight monitoring, at baseline and follow-up, but these effects were smaller than expected, and not clinically significant. There are several contextual and study-related factors that could help explain study results. Study sites were systematically selected and many had substantial organizational stress, and thus, would be expected to have substantial difficulty mounting a quality improvement intervention in addition to addressing other performance measures, directives, and organizational issues. The levels of organizational stress were evident in our interactions with sites, with turnover of mental health and facility leadership and some changes in key EBQI team members. In such organizationally-stressed sites, 6 months of external facilitation may be insufficient to effect clinically significant change in metabolic monitoring and management. In contrast, other research has shown positive outcomes from more intensive external plus internal facilitation strategies (applied over longer durations) in implementing complex clinical innovations in sites that have previously been unsuccessful.
This study was planned in conjunction with a national effort (see above) to improve metabolic monitoring and management for Veterans prescribed antipsychotic medications. However, this study's implementation activities started after the end of the national effort. A broader implication for future improvement efforts, including implementation research, is that projects should be closely aligned, not only with evidence-based recommendations and mental health leaders' clinical priorities, but also with specific regional or national initiatives.
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DRA: Mental, Cognitive and Behavioral Disorders, Diabetes and Other Endocrine Disorders
DRE: Treatment - Observational, Prevention, Prognosis
Keywords: Adverse events, Pharmaceuticals, Schizophrenia
MeSH Terms: none