Assessing Physician Resident Contributions to Outpatient Clinical Workload.

BACKGROUND: Graduate medical education is centered in hospitals despite a care system where patients mostly receive their care in an outpatient setting. Such gaps may exist because of inadequate funding for residency positions in community and hospital-based clinics. OBJECTIVE: Determine if physician residents' contribution to outpatient workload offsets their costs for supervision, salary, and fringe benefits as residents acquire skills to become independent practitioners. RESEARCH DESIGN: VA's electronic patient records from 2005 through 2018 were analyzed using generalized linear mixed models to estimate resident and staff contributions to workload in relative value units. MEASURES: Resident participation rate is resident contributed workload net of supervision as a percent of total clinic workload. Productivity is per diem resident workload as a percent of per diem staff workload. Efficiency is per dollar resident workload as a percent of per dollar staff workload. Progressive independence is annual rate of change in resident productivity. RESULTS: Average participation rates varied by specialty from 6% to 22%, with 11% (primary care) and 13% (psychiatry). Productivity rates ranged from 21% to 94%, with 57% (primary care) and 61% (psychiatry). Efficiency rates varied from 0.63 to 3.81, with 1.69 (primary care), 1.89 (psychiatry). Progressive independence rates varied from 2.7%/year (psychiatry) to 39.7%/year (specialty care). CONCLUSIONS: Although residents rotating through most VA clinics generate revenue to cover their direct costs as they learn, some federal subsidies may be necessary to encourage hospital- and community-based clinics to accept residents from the less profitable primary care and mental health specialties.

Assessing Interpersonal Relationships in Medical Education: the Connection Index.

OBJECTIVE: The relationship between a resident physician and his/her supervising attending is foundational to graduate medical education and may impact the clinical learning environment and resident well-being. This paper focuses on how to measure connection between a resident and their clinical supervisor. Connection includes the subdomains of psychological safety, empathy, educational alliance, and feedback. METHODS: After reviewing the literature, the authors designed the 12-item, 7-point Connection Index (CI12) to quantitatively measure connections between a resident and his/her supervisor during a 6-month period (supervision dyad), and based on educational alliance, empathy, psychological safety, and effective feedback. A 9-criteria evaluation framework was applied to assess its reliability and validity on a sample of psychiatry residents at a residency program, July 2016 through June 2018. RESULTS: Out of a total possible number of 50 residents, 100% participated to rate 41 supervisors over 201 supervision dyads; the CI12 satisfied all eight of the eight testable criteria, including high scalability (H = 0.78), consistency (alpha = 0.98), test-retest validity (ICC = 0.95), and construct validity where CI12 was found to have statistically significant correlations with outcomes measures (greater connection was associated with less negative emotional experiences, less mistreatment or bias, less burnout, and higher attendance to supervision sessions). CONCLUSION: The authors showed the CI12 can be a valid and reliable instrument to quantify whether a resident and his/her supervisor connects during a 6-month supervision with respect to empathy, psychological safety, educational alliance, and feedback. We recommend assessing connections as part of the overall evaluation of a resident's experience with the clinical learning environment.

A systematic approach to subgroup analyses in a smoking cessation trial.

BACKGROUND: Traditional approaches to subgroup analyses that test each moderating factor as a separate hypothesis can lead to erroneous conclusions due to the problems of multiple comparisons, model misspecification, and multicollinearity. OBJECTIVE: To demonstrate a novel, systematic approach to subgroup analyses that avoids these pitfalls. METHODS: A Best Approximating Model (BAM) approach that identifies multiple moderators and estimates their simultaneous impact on treatment effect sizes was applied to a randomized, controlled, 11-week, double-blind efficacy trial on smoking cessation of adult smokers with attention-deficit/hyperactivity disorder (ADHD), randomized to either OROS-methylphenidate (n = 127) or placebo (n = 128), and treated with nicotine patch. Binary outcomes measures were prolonged smoking abstinence and point prevalence smoking abstinence. RESULTS: Although the original clinical trial data analysis showed no treatment effect on smoking cessation, the BAM analysis showed significant subgroup effects for the primary outcome of prolonged smoking abstinence: (1) lifetime history of substance use disorders (adjusted odds ratio [AOR] 0.27; 95% confidence interval [CI] 0.10-0.74), and (2) more severe ADHD symptoms (baseline score >36; AOR 2.64; 95% CI 1.17-5.96). A significant subgroup effect was also shown for the secondary outcome of point prevalence smoking abstinence--age 18 to 29 years (AOR 0.23; 95% CI 0.07-0.76). CONCLUSIONS: The BAM analysis resulted in different conclusions about subgroup effects compared to a hypothesis-driven approach. By examining moderator independence and avoiding multiple testing, BAMs have the potential to better identify and explain how treatment effects vary across subgroups in heterogeneous patient populations, thus providing better guidance to more effectively match individual patients with specific treatments.

Patient Surgical Outcomes When Surgery Residents Are the Primary Surgeon by Intensity of Surgical Attending Supervision in Veterans Affairs Medical Centers.

Objective: Using health records from the Department of Veterans Affairs (VA), the largest healthcare training platform in the United States, we estimated independent associations between the intensity of attending supervision of surgical residents and 30-day postoperation patient outcomes. Background: Academic leaders do not agree on the level of autonomy from supervision to grant surgery residents to best prepare them to enter independent practice without risking patient outcomes. Methods: Secondary data came from a national, systematic 1:8 sample of n = 862,425 teaching encounters where residents were listed as primary surgeon at 122 VA medical centers from July 1, 2004, through September 30, 2019. Independent associations between whether attendings had scrubbed or not scrubbed on patient 30-day all-cause mortality, complications, and 30-day readmission were estimated using generalized linear-mixed models. Estimates were tested for any residual confounding biases, robustness to different regression models, stability over time, and validated using moderator and secondary factors analyses. Results: After accounting for potential confounding factors, residents supervised by scrubbed attendings in 733,997 nonemergency surgery encounters had fewer deaths within 30 days of the operation by 14.2% [0.3%, 29.9%], fewer case complications by 7.9% [2.0%, 14.0%], and fewer readmissions by 17.5% [11.2%, 24.2%] than had attendings not scrubbed. Over the 15 study years, scrubbed surgery attendings may have averted an estimated 13,700 deaths, 43,600 cases with complications, and 73,800 readmissions. Conclusions: VA policies on attending surgeon supervision have protected patient safety while allowing residents in selected teaching encounters to have limited autonomy from supervision.

Early blood product and crystalloid volume resuscitation: risk association with multiple organ dysfunction after severe blunt traumatic injury.

BACKGROUND: Elements of volume resuscitation from hemorrhagic shock, such as amount of blood product and crystalloid administration, have been shown to be associated with multiple organ dysfunction (MOD). However, it is unknown whether these are causative factors or merely markers of an underlying requirement for large-volume resuscitation. We sought to further delineate the relevance of the major individual components of early volume resuscitation to onset of MOD after severe blunt traumatic injury. METHODS: We performed a secondary analysis of a large, multicenter prospective observational cohort of severely injured blunt trauma patients, the NIGMS Trauma Glue Grant, to assess the relevance of individual components of resuscitation administered in the first 12 hours of resuscitation including packed red blood cells (PRBC), fresh frozen plasma (FFP), and isotonic crystalloid, to the onset of MOD within the first 28 days after injury. Deaths within 48 hours of injury were excluded. We used a two tiered, exhaustive logistic regression model search technique to adjust for potential confounders from clinically relevant MOD covariates, including indicators of shock severity, injury severity, comorbidities, age, and gender. RESULTS: The study cohort consisted of 1,366 severely injured blunt trauma patients (median new Injury Severity Score = 34). Incidence of 28-day Marshall MOD was 19.6%. Transfusion of ≥10 Units of PRBC in the first 12 hours (odds ratio, 2.06; 95% confidence interval 1.44-2.94), but not FFP (≥8 U) or large volume crystalloid administration (≥12 L), was independently associated with onset of 28-day Marshall MOD. PRBC:FFP ratio in the first 12 hours was not significantly associated with MOD. CONCLUSIONS: When controlling for all major components of acute volume resuscitation, massive-transfusion volumes of PRBC's within the first 12 hours of resuscitation are modestly associated with MOD, whereas FFP and large volume crystalloid administration are not independently associated with MOD. Previous reported associations of blood products and large-volume crystalloid with MOD may be reflecting overall resuscitation requirements and burden of injury rather than independent causation.

Training satisfaction for subspecialty fellows in internal medicine: findings from the Veterans Affairs (VA) Learners' Perceptions Survey.

BACKGROUND: Learner satisfaction assessment is critical in the design and improvement of training programs. However, little is known about what influences satisfaction and whether trainee specialty is correlated. A national comparison of satisfaction among internal medicine subspecialty fellows in the Department of Veterans Affairs (VA) provides a unique opportunity to examine educational factors associated with learner satisfaction. We compared satisfaction across internal medicine fellows by subspecialty and compared factors associated with satisfaction between procedural versus non-procedural subspecialty fellows, using data from the Learners' Perceptions Survey (LPS), a validated survey tool. METHODS: We surveyed 2,221 internal medicine subspecialty fellows rotating through VA between 2001 and 2008. Learners rated their overall training satisfaction on a 100-point scale, and on a five-point Likert scale ranked satisfaction with items within six educational domains: learning, clinical, working and physical environments; personal experience; and clinical faculty/preceptor. RESULTS: Procedural and non-procedural fellows reported similar overall satisfaction scores (81.2 and 81.6). Non-procedural fellows reported higher satisfaction with 79 of 81 items within the 6 domains and with the domain of physical environment (4.06 vs. 3.85, p <0.001). Satisfaction with clinical faculty/preceptor and personal experience had the strongest impact on overall satisfaction for both. Procedural fellows reported lower satisfaction with physical environment. CONCLUSIONS: Internal medicine fellows are highly satisfied with their VA training. Nonprocedural fellows reported higher satisfaction with most items. For both procedural and non-procedural fellows, clinical faculty/preceptor and personal experience have the strongest impact on overall satisfaction.

Calibration Bias and the Interpretation of Clinical Learning Environment Perceptions Surveys.

BACKGROUND: The clinical learning environment (CLE) is frequently assessed using perceptions surveys, such as the AAMC Graduation Questionnaire and ACGME Resident/Fellow Survey. However, these survey responses often capture subjective factors not directly related to the trainee's CLE experiences. OBJECTIVE: The authors aimed to assess these subjective factors as "calibration bias" and show how it varies by health professions education discipline, and co-varies by program, patient-mix, and trainee factors. METHODS: We measured calibration bias using 2011-2017 US Department of Veterans Affairs (VA) Learners' Perceptions Survey data to compare medical students and physician residents and fellows (n = 32 830) with nursing (n = 29 758) and allied and associated health (n = 27 092) trainees. RESULTS: Compared to their physician counterparts, nursing trainees (OR 1.31, 95% CI 1.22-1.40) and allied/associated health trainees (1.18, 1.12-1.24) tended to overrate their CLE experiences. Across disciplines, respondents tended to overrate CLEs when reporting 1 higher level (of 5) of psychological safety (3.62, 3.52-3.73), 1 SD more time in the CLE (1.05, 1.04-1.07), female gender (1.13, 1.10-1.16), 1 of 7 lower academic level (0.95, 1.04-1.07), and having seen the lowest tercile of patients for their respective discipline who lacked social support (1.16, 1.12-1.21) and had low income (1.05, 1.01-1.09), co-occurring addictions (1.06, 1.02-1.10), and mental illness (1.06, 1.02-1.10). CONCLUSIONS: Accounting for calibration bias when using perception survey scores is important to better understand physician trainees and the complex clinical learning environments in which they train.

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.

Impact of clinical training on recruiting graduating health professionals.

OBJECTIVES: Recruiting professional staff is an important business reason for hospitals allowing health trainees to engage in supervised patient care. Whereas prior studies have focused on educational institutions, this study focuses on teaching hospitals and whether trainees' clinical experiences affect their willingness to work (ie, recruitability) for the type of healthcare center where they trained. STUDY DESIGN: A pre-post, observational study based on Learners' Perceptions Survey data in which respondents served as their own controls. METHODS: Convenience sample of 15,207 physician, 11,844 nursing, and 13,012 associated health trainees who rotated through 1 of 169 US Department of Veterans Affairs (VA) medical centers between July 1, 2014, and June 30, 2017. Generalized estimating equations computed how clinical, learning, working, and cultural experiences influenced pre-post differences in willingness to consider VA for future employment. RESULTS: VA recruitability increased dramatically from 55% pretraining to 75% post training (adjusted odds ratio [OR], 2.1; 95% CI, 2.0-2.1; P <.001) in all 3 cohorts: physician (from 39% to 59%; OR, 1.6; 95% CI, 1.5-1.6; P <.001), nursing (from 61% to 84%; OR, 2.5; 95% CI, 2.4-2.6; P <.001), and associated health trainees (from 68% to 87%; OR, 2.7; 95% CI, 2.6-2.9; P <.001). For all trainees, changes in recruitability (P <.001) were associated with how trainees rated their clinical learning environment, personal experiences, and culture of psychological safety. Satisfaction ratings with faculty and preceptors (P <.001) were associated with positive changes in recruitability among nursing and associated health students but not physician residents, whereas nursing students who gave higher ratings for interprofessional team culture became less recruitable. CONCLUSIONS: Academic medical centers can attract their health trainees for future employment if they provide positive clinical, working, learning, and cultural experiences.

Survival from in-hospital cardiac arrest during nights and weekends.

CONTEXT: Occurrence of in-hospital cardiac arrest and survival patterns have not been characterized by time of day or day of week. Patient physiology and process of care for in-hospital cardiac arrest may be different at night and on weekends because of hospital factors unrelated to patient, event, or location variables. OBJECTIVE: To determine whether outcomes after in-hospital cardiac arrest differ during nights and weekends compared with days/evenings and weekdays. DESIGN AND SETTING: We examined survival from cardiac arrest in hourly time segments, defining day/evening as 7:00 am to 10:59 pm, night as 11:00 pm to 6:59 am, and weekend as 11:00 pm on Friday to 6:59 am on Monday, in 86,748 adult, consecutive in-hospital cardiac arrest events in the National Registry of Cardiopulmonary Resuscitation obtained from 507 medical/surgical participating hospitals from January 1, 2000, through February 1, 2007. MAIN OUTCOME MEASURES: The primary outcome of survival to discharge and secondary outcomes of survival of the event, 24-hour survival, and favorable neurological outcome were compared using odds ratios and multivariable logistic regression analysis. Point estimates of survival outcomes are reported as percentages with 95% confidence intervals (95% CIs). RESULTS: A total of 58,593 cases of in-hospital cardiac arrest occurred during day/evening hours (including 43,483 on weekdays and 15,110 on weekends), and 28,155 cases occurred during night hours (including 20,365 on weekdays and 7790 on weekends). Rates of survival to discharge (14.7% [95% CI, 14.3%-15.1%] vs 19.8% [95% CI, 19.5%-20.1%], return of spontaneous circulation for longer than 20 minutes (44.7% [95% CI, 44.1%-45.3%] vs 51.1% [95% CI, 50.7%-51.5%]), survival at 24 hours (28.9% [95% CI, 28.4%-29.4%] vs 35.4% [95% CI, 35.0%-35.8%]), and favorable neurological outcomes (11.0% [95% CI, 10.6%-11.4%] vs 15.2% [95% CI, 14.9%-15.5%]) were substantially lower during the night compared with day/evening (all P values < .001). The first documented rhythm at night was more frequently asystole (39.6% [95% CI, 39.0%-40.2%] vs 33.5% [95% CI, 33.2%-33.9%], P < .001) and less frequently ventricular fibrillation (19.8% [95% CI, 19.3%-20.2%] vs 22.9% [95% CI, 22.6%-23.2%], P < .001). Among in-hospital cardiac arrests occurring during day/evening hours, survival was higher on weekdays (20.6% [95% CI, 20.3%-21%]) than on weekends (17.4% [95% CI, 16.8%-18%]; odds ratio, 1.15 [95% CI, 1.09-1.22]), whereas among in-hospital cardiac arrests occurring during night hours, survival to discharge was similar on weekdays (14.6% [95% CI, 14.1%-15.2%]) and on weekends (14.8% [95% CI, 14.1%-15.2%]; odds ratio, 1.02 [95% CI, 0.94-1.11]). CONCLUSION: Survival rates from in-hospital cardiac arrest are lower during nights and weekends, even when adjusted for potentially confounding patient, event, and hospital characteristics.

Medical Graduates, Truthful and Useful Analytics With Big Data, and the Art of Persuasion.

The authors propose that the provision of state-of-the-art, effective, safe, and affordable health care requires medical school graduates not only to be competent practitioners and scientists but also to be policy makers and professional leaders. To meet this challenge in the era of big data and cloud computing, these graduates must be able to understand and critically interpret analyses of large, observational datasets from electronic health records, third-party claims files, surveys, and epidemiologic health datasets.The authors contend that medical students need to be exposed to three components. First, students should be familiar with outcome metrics that not only are scientifically valid but also are robust, useful for the medical community, understandable to patients and relevant to their preferences and health goals, and persuasive to health administrators and policy decision makers. Next, students must interact with an inclusive set of analysts including biostatisticians, mathematical and computational statisticians, econometrists, psychometricians, epidemiologists, informaticians, and qualitative researchers. Last, students should learn in environments in which data analyses are not static with a "one-size-fits-all" solution but, rather, where mathematical and computer scientists provide new, innovative, and effective ways of solving predictable and commonplace data limitations such as missing data; make causal inferences from nonrandomized studies and/or those with selection biases; and estimate effect size when patient outcomes are heterogeneous and surveys have low response rates.

A data accounting system for clinical investigators.

Clinical investigators often preprocess, process, and analyze their data without benefit of formally organized research centers to oversee data management. This article outlines a practical three-file structure to help guide these investigators track and document their data through processing and analyses. The proposed process can be implemented without additional training or specialized software. Thus, it is particularly well suited for research projects with small budgets or limited access to viable research/data coordinating centers.

Assessing the preventive effects of cognitive therapy following relief of depression: A methodological innovation.

BACKGROUND: Strategies to compute benefits from continuing cognitive therapy for patients with recurrent major depression do not take into account whether discontinuing treatments may induce temporary increases in the risk that symptoms return (discontinuation-effect). METHODS: We apply varying-effects analyses and compare findings with traditional methods to assess the effects of continuation-phase cognitive therapy. Two years of data came from 79 patients with recurrent major depression who responded to acute cognitive therapy. Patients were randomized to either an experimental cohort (n=39) who received 10-session, protocol continuation-phase therapy for 8 months, or a control cohort (n=40) who stopped protocol treatment after the acute-phase. Symptoms were assessed using the Longitudinal Interval Follow-up Evaluation (LIFE). Symptom risk rates were computed weekly by cohort as the proportion of patients at risk who were suffering from a major depressive episode. RESULTS: Significant discontinuation-effects occurred when protocol treatments stopped for both experimental and control cohorts. Following acute-phase care, traditional computation methods (week 1-35) revealed treated patients had 18% of the risk for symptoms as controls. Expanding the observation period (week 1-74) to include these discontinuation-effects revealed more modest initial effect sizes (43%), but significant long-term effects (54% for week 75-101). LIMITATIONS: Limitations include limited sample size, one-site study, confounds from patient-level interactions, and off-protocol use of depression-related care. CONCLUSIONS: Varying-effects analyses can describe how outcomes from cognitive therapy may unfold over time for patients with major depression. These analyses reveal complex longitudinal patterns that otherwise are not detectable with traditional time-to-event methods. Specifically, we observed discontinuation-effects, or temporary spikes in symptom risks that occur after treatment ends. Further research is needed to identify the mechanisms driving these effects. Future studies are needed to determine if higher risks result from the patients' anxiety as they attempt to maintain gains independent of ongoing therapy, or reflect residual symptoms previously suppressed by treatment. We also observed longer-term preventive effects from therapy. Again, further research is recommended to determine the extent to which lower risks result from coping and compensatory skills learned during cognitive therapy. These findings suggest that varying-effects analyses may provide an appealing paradigm for understanding treatment-related effects in episodic illness.

Assessing physicians' use of treatment algorithms: Project IMPACTS study design and rationale.

Effective treatments for major depressive disorder have been available for 35 years, yet inadequate pharmacotherapy continues to be widespread leading to suboptimal outcomes. Evidence-based medication algorithms have the potential to bring much-needed improvement in effectiveness of antidepressant treatment in "real-world" clinical settings. Project IMPACTS (Implementation of Algorithms using Computerized Treatment Systems) addresses the critical question of how best to facilitate integration of depression treatment algorithms into routine care. It tests an algorithm implemented through a computerized decision support system using a measurement-based care approach for depression against a paper-and-pencil version of the same algorithm and non-algorithm-based, specialist-delivered usual care. This paper reviews issues related to the Project IMPACTS study rationale, design, and procedures. Patient outcomes include symptom severity, social and work function, and quality of life. The economic impact of treatment is assessed in terms of health care utilization and cost. Data collected on physician behavior include degree of adherence to guidelines and physician attitudes about the perceived utility, ease of use, and self-reported effect of the use of algorithms on workload. Novel features of the design include a two-tiered study enrollment procedure, which initially enroll physicians as subjects, and then following recruitment of physicians, enrollment of subjects takes place based initially on an independent assessment by study staff to determine study eligibility. The study utilizes brief, easy-to-use symptom severity measures that facilitate physician decision making, and it employs a validated, phone-based, follow-up assessment protocol in order to minimize missing data, a problem common in public sector and longitudinal mental health studies. IMPACTS will assess the success of algorithm implementation and subsequent physician adherence using study-developed criteria and related statistical approaches. These new procedures and data points will also allow a more refined assessment of algorithm-driven treatment in the future.

Mental health, quality of life, and health functioning in women veterans: differential outcomes associated with military and civilian sexual assault.

The present study examined psychiatric, physical, and quality-of-life functioning in a sample of 270 women veterans receiving outpatient treatment at a Veterans Affairs medical center. Participants were interviewed regarding their civilian (CSA) and military sexual assault (MSA) histories, and data regarding quality of life and health outcomes were obtained through structured interviews and questionnaires. Women veterans with CSA histories reported significantly poorer physical, psychiatric, and quality-of-life functioning compared to those without a history of sexual assault. Furthermore, women veterans with an MSA history demonstrated additional negative consequences above and beyond the effects of CSA. The study sample was comparable to a national random sample of women veterans who access care in the Veterans Affairs healthcare system, increasing the generalizibility of the results.

Has Interprofessional Education Changed Learning Preferences? A National Perspective.

OBJECTIVE: To assess how changes in curriculum, accreditation standards, and certification and licensure competencies impacted how medical students and physician residents value interprofessional team and patient-centered care. PRIMARY DATA SOURCE: The Department of Veterans Affairs Learners' Perceptions Survey (2003-2013). The nationally administered survey asked a representative sample of 56,569 U.S. medical students and physician residents, with a comparison group of 78,038 nonphysician trainees, to rate satisfaction with 28 elements, in two overall domains, describing their clinical learning experiences at VA medical centers. STUDY DESIGN: Value preferences were scored as independent adjusted associations between an element (interprofessional team, patient-centered preceptor) and the respective overall domain (clinical learning environment, faculty, and preceptors) relative to a referent element (quality of clinical care, quality of preceptor). PRINCIPAL FINDINGS: Physician trainees valued interprofessional (14 percent vs. 37 percent, p < .001) and patient-centered learning (21 percent vs. 36 percent, p < .001) less than their nonphysician counterparts. Physician preferences for interprofessional learning showed modest increases over time (2.5 percent/year, p < .001), driven mostly by internal medicine and surgery residents. Preferences did not increase with trainees' academic progress. CONCLUSIONS: Despite changes in medical education, physician trainees continue to lag behind their nonphysician counterparts in valuing experience with interprofessional team and patient-centered care.

Comparison of self-report and clinician ratings on two inventories of depressive symptomatology.

OBJECTIVE: This study evaluated the concordance between the self-report and the clinician-rated versions of the Inventory of Depressive Symptomatology (IDS-30) and between the two versions of the briefer 16-item Quick Inventory of Depressive Symptomatology (QIDS-16). METHODS: Data were gathered for 544 adult outpatients with psychotic (N = 106) or nonpsychotic (N = 438) major depressive disorder at 14 public sector mental health clinics in the Texas Medication Algorithm Project. Data for the QIDS-16 were extracted from the IDS-30. Baseline scores and scores from the final study visit at or before month 12 were analyzed. The clinician-rated and the self-report versions of each scale were compared in their identification of response to treatment and remission. RESULTS: The average baseline IDS-SR-30 total score was 2.2 points higher (indicating greater severity) than the IDS-C-30 score; the average QIDS-SR-16 total score was only .3 points higher than the QIDS-C-16 score. The IDS-SR-30 and the IDS-C-30, as well as the QIDS-C-16 and QIDS-SR-16, agreed substantially in classifying response and remission for patients, regardless of whether the patients had psychotic features. None of a large number of clinical and demographic features accounted for differences between the QIDS-SR-16 and QIDS-C-16 total scores. CONCLUSIONS: Either the IDS-30 or the QIDS-16 self-report adequately assesses depressive symptom severity among public-sector outpatients with major depressive disorder. The briefer QIDS-16 may be preferred to save time and cost.

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.

Does Psychological Safety Impact the Clinical Learning Environment for Resident Physicians? Results From the VA's Learners' Perceptions Survey.

BACKGROUND: Psychological safety (PS) is the perception that it is safe to take interpersonal risks in the work environment. In teaching hospitals, PS may influence the clinical learning environment for trainees. OBJECTIVE: We assessed whether resident physicians believe they are psychologically safe, and if PS is associated with how they rate satisfaction with their clinical learning experience. METHODS: Data were extracted from the Learners' Perceptions Survey (LPS) of residents who rotated through a Department of Veterans Affairs health care facility for academic years 2011-2014. Predictors of PS and its association with resident satisfaction were adjusted to account for confounding and response rate biases using generalized linear models. RESULTS: The 13 044 respondents who completed the LPS (30% response rate) were comparable to nonpediatric, non-obstetrics-gynecology residents enrolled in US residency programs. Among respondents, 11 599 (89%) agreed that ". . . members of the clinical team of which I was part are able to bring up problems and tough issues." Residents were more likely to report PS if they were male, were in a less complex clinical facility, in an other medicine or psychiatry specialty, or cared for patients who were aged, had multiple illnesses, or had social supports. Nonpsychiatric residents felt safer when treating patients with no concurrent mental health diagnoses. PS was strongly associated with how residents rated their satisfaction across 4 domains of their clinical learning experience (P < .001). CONCLUSIONS: PS appears to be an important factor in resident satisfaction across 4 domains that evaluators of graduate medical education programs should consider when assessing clinical learning experiences.