Faculty Bibliography

BACKGROUND: Sign-out is the process (written, verbal or both) by which one clinical team transmits information about patients to another team. Poor quality sign-outs are associated with adverse events and delayed treatment. How different specialties approach written sign-outs is unknown. OBJECTIVE: To compare written sign-out practices across specialties and to determine consistency of content, format and timeliness. METHODS: The authors evaluated all non-Intensive Care Unit written sign-outs from five inpatient specialties on 18 January 2012, at Yale-New Haven Hospital, focusing on content elements, format style and whether the sign-outs had been updated within 24 h. In our institution, all specialties used a single standardised sign-out template, which was built into the electronic medical record. RESULTS: The final cohort included 457 sign-outs: 313 medicine, 64 general surgery, 36 paediatrics, 30 obstetrics, and 14 gynaecology. Though nearly all sign-outs (96%) had been updated within 24 h, they frequently lacked key information. Hospital course prevalence ranged from 57% (gynaecology) to 100% (paediatrics) (p<0.001). Clinical condition prevalence ranged from 34% (surgery) to 72% (paediatrics) (p=0.005). CONCLUSIONS: Specialties have varied sign-out practices, and thus structured templates alone do not guarantee inclusion of critical content. Sign-outs across specialties often lacked complex clinical information such as clinical condition, anticipatory guidance and overnight tasks.

BACKGROUND: The most recent iteration of the Accreditation Council for Graduate Medical Education duty-hour regulations includes language mandating handoff education for trainees and assessments of handoff quality by residency training programs. However, there is a lack of validated tools for the assessment of handoff quality and for use in trainee education. METHODS: Faculty at 2 sites (University of Chicago and Yale University) were recruited to participate in a workshop on handoff education. Video-based scenarios were developed to represent varying levels of performance in the domains of communication, professionalism, and setting. Videos were shown in a random order, and faculty were instructed to use the Handoff Mini-Clinical Examination Exercise (CEX), a paper-based instrument with qualitative anchors defining each level of performance, to rate the handoffs. RESULTS: Forty-seven faculty members (14 at site 1; 33 at site 2) participated in the validation workshops, providing a total of 172 observations (of a possible 191 [96%]). Reliability testing revealed a Cronbach alpha of 0.81 and Kendall coefficient of concordance of 0.59 (>0.6 = high reliability). Faculty were able to reliably distinguish the different levels of performance in each domain in a statistically significant fashion (ie, unsatisfactory professionalism mean 2.42 vs satisfactory professionalism 4.81 vs superior professionalism 6.01, P < 0.001 trend test). Two-way analysis of variance revealed no evidence of rater bias. CONCLUSIONS: Using standardized video-based scenarios highlighting differing levels of performance, we were able to demonstrate evidence that the Handoff Mini-CEX can draw reliable and valid conclusions regarding handoff performance. Future work to validate the tool in clinical settings is warranted.

Transfers of care have been associated with adverse events. High quality sign-out may help mitigate this risk. The authors sought to characterize the clinical questions asked of physicians covering patients overnight and to determine the adequacy of current sign-out practice to anticipate inquiries. The authors conducted a prospective, self-report study of interns' overnight experience at two hospitals. We collected data from novice interns (July 7-August 3, 2010) and experienced interns (March 2-March 29, 2011) in an Internal Medicine residency program. Interns recorded information about overnight inquiries regarding cross-covered patients. For each inquiry about a patient, the intern was asked to record what the situation was about, who initiated the contact, where the intern found the desired information, whether all required data was located, whether the call could have been anticipated by the primary team, if so, whether the call was anticipated, whether the sign-out was sufficient, the time required to address the question, and whether the patient was physically visited. Twenty-one interns (13 novice, 8 experienced) reported 167 overnight inquiries. Most were from nursing staff (87%) about a wide range of topics, with orders (25%) and plan of care (20%) being most common. Trainees used the oral or written sign-out to answer 56% of inquiries. The proportion of inquiries successfully anticipated (47% overall) significantly decreased as the academic year progressed (AOR = 0.4, 95% CI 0.2, 0.8). Trainees rely on sign-out to answer nearly half of overnight inquiries, but the quality of sign-out may decrease over the course of the academic year. The deterioration of sign-out quality from novice to experienced interns and the common use of sign-out as a reference by covering interns suggest continued education, support and oversight by supervising physicians may be beneficial.

The objective was to assess use of a physician handoff tool embedded in the electronic medical record by nurses and other non-physicians. We administered a survey to nurses, physical therapists, discharge planners, social workers, and others to assess integration into daily practice, usefulness, and accuracy of the handoff tool. 231 individuals (61% response) participated. 60% used the tool often or usually/always during a shift. Nurses (46%) used the tool for shift transitions and found it helpful for medical history (79%) but not for acquiring medication, allergy, and responsible physician information. Nurses (96%) and others (75%) rated the tool as accurate. Medical nurses rated the tool more useful than surgical nurses, and pediatric nurses rarely used the tool. The tool was integrated into the daily workflow of non-physicians despite being designed for physician use. Non-physicians should be included in the design and implementation of electronic patient handoff systems.

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.