Streamlining the process for initial review of pharmacy residency applications: An analytic approach

2013 
Purpose An analytics-driven process for improving the efficiency of initial candidate screening by pharmacy residency programs is described. Methods In an initiative to streamline pharmacy resident selection at Johns Hopkins Hospital, retrospective analyses of materials submitted by prospective residents during two application periods ( n = 277) were conducted to identify the applicant characteristics most strongly associated with the ultimate extension of an invitation to interview. Multiple two-member teams of pharmacist reviewers independently scored each application on 13 variables, with the resultant item scores tallied to derive rank sum scores. Univariate and multivariate logistic regression analyses were performed to identify the factors most important in distinguishing candidates invited for an interview from those not invited. Results Univariate analysis indicated that all 13 evaluated applicant characteristics correlated with the likelihood of an interview invitation, but some were relatively less determinative; these factors were excluded from a final multivariate logistic regression model containing only the 7 factors most strongly predictive of an invitation to interview: grade point average, pharmacy work experience, professional association involvement, rotation experiences, presentations, publications, and skills and certifications. The final model was found to be highly explanatory ( r 2 = 0.66) of variances in interview-invitation decisions and has been adopted as a guide to future initial screening of candidate applications. Conclusion By analyzing the relative importance of specific residency applicant characteristics and focusing on those deemed most useful in determining which candidates are invited for interviews, a large teaching institution streamlined preliminary application screening while maintaining an equitable candidate selection process.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    11
    References
    36
    Citations
    NaN
    KQI
    []