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The American Journal of Managed Care April 2019
Time to Fecal Immunochemical Test Completion for Colorectal Cancer
Cameron B. Haas, MPH; Amanda I. Phipps, PhD; Anjum Hajat, PhD; Jessica Chubak, PhD; and Karen J. Wernli, PhD
From the Editorial Board: Kavita K. Patel, MD, MS
Kavita K. Patel, MD, MS
Comment on Generalizability of GLP-1 RA CVOTs in US T2D Population
Maureen J. Lage, PhD
Authors’ Reply to “Comment on Generalizability of GLP-1 RA CVOTs in US T2D Population”
Eric T. Wittbrodt, PharmD, MPH; James M. Eudicone, MS, MBA; Kelly F. Bell, PharmD, MSPhr; Devin M. Enhoffer, PharmD; Keith Latham, PharmD; and Jennifer B. Green, MD
Deprescribing in the Context of Multiple Providers: Understanding Patient Preferences
Amy Linsky, MD, MSc; Mark Meterko, PhD; Barbara G. Bokhour, PhD; Kelly Stolzmann, MS; and Steven R. Simon, MD, MPH
The Health and Well-being of an ACO Population
Thomas E. Kottke, MD, MSPH; Jason M. Gallagher, MBA; Marcia Lowry, MS; Sachin Rauri, MS; Juliana O. Tillema, MPA; Jeanette Y. Ziegenfuss, PhD; Nicolaas P. Pronk, PhD, MA; and Susan M. Knudson, MA
Effect of Changing COPD Triple-Therapy Inhaler Combinations on COPD Symptoms
Nick Ladziak, PharmD, BCACP, CDE; and Nicole Paolini Albanese, PharmD, BCACP, CDE
Deaths Among Opioid Users: Impact of Potential Inappropriate Prescribing Practices
Jayani Jayawardhana, PhD; Amanda J. Abraham, PhD; and Matthew Perri, PhD
Do Health Systems Respond to the Quality of Their Competitors?
Daniel J. Crespin, PhD; Jon B. Christianson, PhD; Jeffrey S. McCullough, PhD; and Michael D. Finch, PhD
Currently Reading
Impact of Clinical Training on Recruiting Graduating Health Professionals
Sheri A. Keitz, MD, PhD; David C. Aron, MD; Judy L. Brannen, MD; John M. Byrne, DO; Grant W. Cannon, MD; Christopher T. Clarke, PhD; Stuart C. Gilman, MD; Debbie L. Hettler, OD, MPH; Catherine P. Kaminetzky, MD, MPH; Robert A. Zeiss, PhD; David S. Bernett, BA; Annie B. Wicker, BS; and T. Michael Kashner, PhD, JD
Continuity of Outpatient Care and Avoidable Hospitalization: A Systematic Review
Yu-Hsiang Kao, PhD; Wei-Ting Lin, PhD; Wan-Hsuan Chen, MPH; Shiao-Chi Wu, PhD; and Tung-Sung Tseng, DrPH

Impact of Clinical Training on Recruiting Graduating Health Professionals

Sheri A. Keitz, MD, PhD; David C. Aron, MD; Judy L. Brannen, MD; John M. Byrne, DO; Grant W. Cannon, MD; Christopher T. Clarke, PhD; Stuart C. Gilman, MD; Debbie L. Hettler, OD, MPH; Catherine P. Kaminetzky, MD, MPH; Robert A. Zeiss, PhD; David S. Bernett, BA; Annie B. Wicker, BS; and T. Michael Kashner, PhD, JD
A business case is made for medical centers to offer high-quality clinical training experiences to recruit graduating health professionals.
Training Experiences

The LPS also asks respondents to rate their clinical training during their VA rotation on 6 satisfaction and 3 assessment domains. Satisfaction was rated on a 5-point scale for the 7-item clinical environment, 9-item working environment, 8-item physical environment, 7-item personal experience, 15-item learning environment, and 13-item clinical faculty and preceptors domains. To compute satisfaction domain scores, a value of 1 was assigned to responses of very dissatisfied, 2 to somewhat dissatisfied, 3 to neither satisfied nor dissatisfied, 4 to somewhat satisfied, and 5 to very satisfied. Domains were scored as Likert scales24 by taking the mean response across all items within each domain. This is appropriate because the items have been shown to constitute a single dimension.22,23

Assessment domains were computed based on how much respondents agreed or disagreed with a statement describing their training experiences. Items were scored by assigning a value of 1 to responses of strongly disagree, 2 to disagree, 3 to neither disagree nor agree, 4 to agree, and 5 to strongly agree. As with satisfaction, assessments were scored as the mean responses across n items for 2-item psychological safety, 16-item patient-centered care, and 9-item interprofessional team care domains.

Structural Factors

LPS responses were also used to assess other covariates. Facility-level factors include complexity as scored officially by VA on a 5-level scale based on number of beds, clinical services offered, number and diversity of trainees, and dollars of research support.25 VA also computes a rurality index as the ratio of a facility’s census of rural and highly rural patients to total patient census. At the respondent level, factors are the trainee’s gender, length of time in VA, academic program, and academic level. The mix of patients seen during their VA rotations is computed across 8 variables. These variables describe the percent of patients the respondent saw who were 65 years or older; female; with a chronic mental illness, a chronic medical illness, multiple medical illnesses, and alcohol/substance dependence; with low income/socioeconomic status; or lacking social/family support. To avoid confounding with professional discipline, patient mix factors were centered around the mean for all respondents with the same professional discipline, specialty, and academic level. Finally, as described elsewhere,8,22 associations were calibrated to reflect differences in how trainees apply thresholds when classifying the intensity of their satisfaction into 1 of the 5 response levels. This calibration index is computed by taking the respondent’s mean satisfaction rating for facility-level items (facility convenience, parking, and electronic health record) and subtracting the average of these mean ratings across all respondents at the respondent’s VA facility and reporting year.


Recruitability, both before and after training, was measured on a 5-point ordinal scale and treated analytically as repeated measures, based on generalized estimating equations with a multinomial distribution and cumulative logit link function. The training effect was computed as an odds ratio by discipline based on estimates of the coefficient to an independent time indicator variable that equals 1 if post VA training and 0 if pre–VA training. Factors related to these associations were estimated using interaction terms calculated by multiplying a suspected mediator with the time indicator variable. Academic level (years of training) was centered to reflect a referent academic level that describes the level at which a trainee was most likely to be exposed to VA for the first time in that discipline (eg, third-year medical student, PGY1 physician resident, PGY4 resident in medicine subspecialty; see Table 2). Finally, the mean-centered patient mix and calibration index variables were included as control variables to reduce confounding in estimated associations between training experience and recruitability. For this exploratory study, a Wald χ2 test statistic is computed, and 95% CIs and P values provided, to indicate precision of effect size estimates, and not for hypothesis testing.



Table 1 describes characteristics of survey respondents; they represent a broad range of professional disciplines, subspecialties, academic levels, gender, mix of patients seen, facility location (rural or urban), complexity of care, and respondents’ perceptions of training experiences across 9 domains. The domains are presented in descending rank of satisfaction or agreement for all trainees. Overall, physician trainees tended to rate their clinical training experiences lower than their nursing or AH counterparts. Faculty/preceptors was the highest-rated and interprofessional team care was the lowest-rated domain across professions.

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