Annie Wicker

Factors Determining Medical Students’ and Residents’ Satisfaction During Va-based Training: Findings from the Va Learners’ Perceptions Survey

Purpose To compare medical students’ and physician residents’ satisfaction with Veterans Affairs (VA) training to determine the factors that were most strongly associated with trainee satisfaction ratings. Method Each year from 2001 to 2006, all medical students and residents in VA teaching facilities were invited to complete the Learners’ Perceptions Survey. Participants rated their overall training satisfaction on a 100-point scale and ranked specific satisfaction in four separate educational domains (learning environment, clinical faculty, working environment, and physical environment) on a five-point Likert scale. Each domain was composed of unique items. Results A total of 6,527 medical students and 16,583 physician residents responded to the survey. The overall training satisfaction scores for medical students and physician residents were 84 and 79, respectively (P < .001), with significant differences in satisfaction reported across the training continuum. For both medical students and residents, the rating of each of the four educational domains was statistically significantly associated with the overall training satisfaction score (P < .001). The learning environment domain had the strongest association with overall training satisfaction score, followed by the clinical preceptor, working environment, and physical environment domains; no significant differences were found between medical students and physician residents in the rank order. Satisfaction with quality of care and faculty teaching contributed significantly to training satisfaction. Conclusions Factors that influence training satisfaction were similar for residents and medical students. The domain with the highest association was the learning environment; quality of care was a key item within this domain.

An Empirical Analysis of Cost Outcomes of the Texas Medication Algorithm Project

OBJECTIVE Disease management systems that incorporate medication algorithms have been proposed as cost-effective means to offer optimal treatment for patients with severe and chronic mental illnesses. The Texas Medication Algorithm Project was designed to compare health care costs and clinical outcomes between patients who received algorithm-guided medication management or usual care in 19 public mental health clinics. METHODS This longitudinal cohort study for patients with major depression (N=350), bipolar disorder (N=267), and schizophrenia (N=309) applied a multi-part declining-effects cost model. Outcomes were assessed by the Inventory of Depressive Symptomatology and the Brief Psychiatric Rating Scale. RESULTS Compared with patients in usual care, patients in algorithm-based care incurred higher medication costs and had more frequent physician visits, although these differences often became smaller with time. For major depression, algorithm-based care achieved better outcomes sustainable with time but at higher agency and non-agency costs (mixed cost-effective). For bipolar disorder, patients in algorithm-based management achieved better outcomes at lower agency costs (cost-effective). For schizophrenia, patients in algorithm-based care achieved better outcomes that diminished with time, with no detectable difference in health care costs (cost-effective). CONCLUSIONS Cost outcomes of algorithm-based care and usual care varied by disorder and over time. For bipolar disorder and schizophrenia, algorithm-based care improved outcomes without higher costs for health care services. For major depression, substantively better and sustained outcomes were obtained but at greater costs.

Measuring use and cost of care for patients with mood disorders: the utilization and cost inventory.

Background:Researchers conducting cost-outcome studies must account for all materially relevant care that subjects receive from their care providers. However, access to provider records is often limited. This article describes and tests the Utilization and Cost Inventory (UAC-I), a structured patient interview designed to measure costs of care when access to provider records is limited. Methods:UAC-I was tested on 212 consenting adult veterans with mood disorder attending a VA medical center. Counts (inpatient days and outpatient encounters) and costs (dollars) computed from survey responses were compared with estimates from medical records and an alternative structured questionnaire. Results:The agreement between inpatient costs computed from provider records and from UAC-I responses, assessed using the intraclass correlation coefficient (ICC), was 0.66, 95% confidence interval (CI), 0.30–0.84; the bias was −3.7%, 95% CI, −48 to 41. The ICC for the service data (inpatient days) was 0.97, 95% CI, 0.95–0.99; the bias was <1%, 95% CI, −14 to 15. The ICC for outpatient costs computed from provider records and from UAC-I responses was 0.53 95% CI, 0.38–0.65; the bias was <1%, 95% CI, −27 to 27. The ICC for outpatient encounters was 0.74, 95% CI, 0.65–0.80; the bias was <1%, 95% CI, −16 to 18. Conclusions:These results indicate that it may be feasible for cost-outcome studies to compare patient groups for inpatient and outpatient costs computed from patient self-reports.

The Impact of Nonclinical Factors on Care Use for Patients with Depression: A STAR*D Report

Introduction: This article presents baseline findings that describe how nonclinical factors were associated with patient use of psychiatric and general medical care and how those relationships changed after patients enrolled in the 41‐site Sequenced Treatment Alternatives to Relieve Depression study (STAR*D). Aims: STAR*D offered adult outpatients with major depression diligently delivered, measurement‐based care. To achieve full remission within a tolerable medication dose, recommendations for treatment based on routine symptom and side‐effect measurements were discussed with patients by clinical research coordinators and offered to clinicians who could flexibly tailor that guidance to accommodate individual patient needs. Medications were provided gratis. Pre‐ and post‐enrollment data came from provider records and from patient face‐to‐face, telephone, and computer‐assisted surveys. Two‐part nested mixed models assessed patient likelihood and volume of mental and general medical care services. Results: Prior to enrollment, predisposing (gender, race, education, and care attitude), affordability (private insurance), and clinical factors (depressive symptoms and mental and physical functioning) were found to be important drivers of patient use of psychiatric and general medical care. After STAR*D enrollment, however, predisposing factors were less important drivers of psychiatric service use but remained important drivers of general medical care. Conclusions: Data suggest diligent, measurement‐based mental health programs may reduce race, gender, and education disparities in the use of needed mental health care.

Release bias in accessing medical records in clinical trials: A STAR*D report

Clinical trials often require subjects to sign medical record releases to allow investigators to measure treatment fidelity, off‐protocol care use, and care costs. Little is known, however, if limiting samples to those willing to sign releases impacts external validity. Data came from outpatients with non‐psychotic major depressive disorder who enrolled in the multisite Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study. Differences between those who signed (n = 3116) and who did not sign (n = 925) releases were assessed using logistic regression and two‐part, three‐level log‐transformed regression models, corrected for site clustering and repeated measures. Patients who released records tended to believe care was helpful, were younger, and married. However, release status had little material or consistent associations with patient health outcomes or use of care. With appropriate adjustments to data, requiring patient medical records may pose only minimal challenges to external validity in cost‐outcome studies. Copyright