Faculty Bibliography

BACKGROUND: Increasing frequency of shift-to-shift handoffs coupled with regulatory requirements to evaluate handoff quality make a handoff evaluation tool necessary. OBJECTIVE: To develop a handoff evaluation tool. DESIGN: Tool development. SETTING: Two academic medical centers. SUBJECTS: Nurse practitioners, medicine housestaff, and hospitalist attendings. INTERVENTION: Concurrent peer and external evaluations of shift-to-shift handoffs. MEASUREMENTS: The Handoff CEX (clinical evaluation exercise) consists of 6 subdomains and 1 overall assessment, each scored from 1 to 9, where 1 to 3 is unsatisfactory and 7 to 9 is superior. We assessed range of scores, performance among subgroups, internal consistency, and agreement among types of raters. RESULTS: We conducted 675 evaluations of 97 unique individuals during 149 handoff sessions. Scores ranged from unsatisfactory to superior in each domain. The highest rated domain for handoff providers was professionalism (median: 8; interquartile range [IQR]: 7-9); the lowest was content (median: 7; IQR: 6-8). Scores at the 2 institutions were similar, and scores did not differ significantly by training level. Spearman correlation coefficients among the CEX subdomains for provider scores ranged from 0.71 to 0.86, except for setting (0.39-0.40). Third-party external evaluators consistently gave lower marks for the same handoff than peer evaluators did. Weighted kappa scores for provider evaluations comparing external evaluators to peers ranged from 0.28 (95% confidence interval [CI]: 0.01, 0.56) for setting to 0.59 (95% CI: 0.38, 0.80) for organization. CONCLUSIONS: This handoff evaluation tool was easily used by trainees and attendings, had high internal consistency, and performed similarly across institutions. Because peers consistently provided higher scores than external evaluators, this tool may be most appropriate for external evaluation.

IMPORTANCE: To better guide strategies intended to reduce high rates of 30-day readmission after hospitalization for heart failure (HF), acute myocardial infarction (MI), or pneumonia, further information is needed about readmission diagnoses, readmission timing, and the relationship of both to patient age, sex, and race. OBJECTIVE: To examine readmission diagnoses and timing among Medicare beneficiaries readmitted within 30 days after hospitalization for HF, acute MI, or pneumonia. DESIGN, SETTING, AND PATIENTS: We analyzed 2007-2009 Medicare fee-for-service claims data to identify patterns of 30-day readmission by patient demographic characteristics and time after hospitalization for HF, acute MI, or pneumonia. Readmission diagnoses were categorized using an aggregated version of the Centers for Medicare & Medicaid Services' Condition Categories. Readmission timing was determined by day after discharge. MAIN OUTCOME MEASURES: We examined the percentage of 30-day readmissions occurring on each day (0-30) after discharge; the most common readmission diagnoses occurring during cumulative periods (days 0-3, 0-7, 0-15, and 0-30) and consecutive periods (days 0-3, 4-7, 8-15, and 16-30) after hospitalization; median time to readmission for common readmission diagnoses; and the relationship between patient demographic characteristics and readmission diagnoses and timing. RESULTS: From 2007 through 2009, we identified 329,308 30-day readmissions after 1,330,157 HF hospitalizations (24.8% readmitted), 108,992 30-day readmissions after 548,834 acute MI hospitalizations (19.9% readmitted), and 214,239 30-day readmissions after 1,168,624 pneumonia hospitalizations (18.3% readmitted). The proportion of patients readmitted for the same condition was 35.2% after the index HF hospitalization, 10.0% after the index acute MI hospitalization, and 22.4% after the index pneumonia hospitalization. Of all readmissions within 30 days of hospitalization, the majority occurred within 15 days of hospitalization: 61.0%, HF cohort; 67.6%, acute MI cohort; and 62.6%, pneumonia cohort. The diverse spectrum of readmission diagnoses was largely similar in both cumulative and consecutive periods after discharge. Median time to 30-day readmission was 12 days for patients initially hospitalized for HF, 10 days for patients initially hospitalized for acute MI, and 12 days for patients initially hospitalized for pneumonia and was comparable across common readmission diagnoses. Neither readmission diagnoses nor timing substantively varied by age, sex, or race. CONCLUSION AND RELEVANCE: Among Medicare fee-for-service beneficiaries hospitalized for HF, acute MI, or pneumonia, 30-day readmissions were frequent throughout the month after hospitalization and resulted from a similar spectrum of readmission diagnoses regardless of age, sex, race, or time after discharge.

Student-run clinics increasingly serve as primary care providers for patients of lower socioeconomic status, but studies show that quality of care at student-run clinics has room for improvement. PURPOSE: To examine change in provision of preventive services in a student-run free clinic after implementation of a student-led QI intervention involving prompting. METHOD: Review of patient charts pre- and post-intervention, examining adherence to screening guidelines for diabetes, dyslipidemia, HIV, and cervical cancer. RESULTS: Adherence to guidelines among eligible patients increased after intervention in 3 of 4 services examined. Receipt of HIV testing increased from 33% (80/240) to 48% (74/154; p = 0.004), fasting lipid panel increased from 53% (46/86) to 72% (38/53; p = 0.033), and fasting blood glucose increased from 59% (27/46) to 82% (18/22; p = 0.059). CONCLUSIONS: This student-run free clinic implemented a student-led QI intervention that increased provision of prevention. Such a model for QI could extend to other student-run clinics nationally.