Faculty Bibliography

BACKGROUND: Hospital quality improvement efforts absorb substantial time and resources, but many innovations fail to integrate into organizational routines, undermining the potential to sustain the new practices. Despite a well-developed literature on the initial implementation of new practices, we have limited knowledge about the mechanisms by which integration occurs. METHODS: We conducted a qualitative study using a purposive sample of hospitals that participated in the State Action on Avoidable Rehospitalizations (STAAR) initiative, a collaborative to reduce hospital readmissions that encouraged members to adopt new practices. We selected hospitals where risk-standardized readmission rates (RSRR) had improved (n = 7) or deteriorated (n = 3) over the course of the first 2 years of the STAAR initiative (2010-2011 to 2011-2012) and interviewed a range of staff at each site (90 total). We recruited hospitals until reaching theoretical saturation. The constant comparative method was used to conduct coding and identification of key themes. RESULTS: When innovations were successfully integrated, participants consistently reported that a small number of key staff held the innovation in place for as long as a year while more permanent integrating mechanisms began to work. Depending on characteristics of the innovation, one of three categories of integrating mechanisms eventually took over the role of holding new practices in place. Innovations that proved intrinsically rewarding to the staff, by making their jobs easier or more gratifying, became integrated through shifts in attitudes and norms over time. Innovations for which the staff did not perceive benefits to themselves were integrated through revised performance standards if the innovation involved complex tasks and through automation if the innovation involved simple tasks. CONCLUSIONS: Hospitals have an opportunity to promote the integration of new practices by planning for the extended effort required to hold a new practice in place while integration mechanisms take hold. By understanding how integrating mechanisms correspond to innovation characteristics, hospitals may be able to foster integrating mechanisms most likely to work for particular innovations.

BACKGROUND: It is desirable not to include planned readmissions in readmission measures because they represent deliberate, scheduled care. OBJECTIVES: To develop an algorithm to identify planned readmissions, describe its performance characteristics, and identify improvements. DESIGN: Consensus-driven algorithm development and chart review validation study at 7 acute-care hospitals in 2 health systems. PATIENTS: For development, all discharges qualifying for the publicly reported hospital-wide readmission measure. For validation, all qualifying same-hospital readmissions that were characterized by the algorithm as planned, and a random sampling of same-hospital readmissions that were characterized as unplanned. MEASUREMENTS: We calculated weighted sensitivity and specificity, and positive and negative predictive values of the algorithm (version 2.1), compared to gold standard chart review. RESULTS: In consultation with 27 experts, we developed an algorithm that characterizes 7.8% of readmissions as planned. For validation we reviewed 634 readmissions. The weighted sensitivity of the algorithm was 45.1% overall, 50.9% in large teaching centers and 40.2% in smaller community hospitals. The weighted specificity was 95.9%, positive predictive value was 51.6%, and negative predictive value was 94.7%. We identified 4 minor changes to improve algorithm performance. The revised algorithm had a weighted sensitivity 49.8% (57.1% at large hospitals), weighted specificity 96.5%, positive predictive value 58.7%, and negative predictive value 94.5%. Positive predictive value was poor for the 2 most common potentially planned procedures: diagnostic cardiac catheterization (25%) and procedures involving cardiac devices (33%). CONCLUSIONS: An administrative claims-based algorithm to identify planned readmissions is feasible and can facilitate public reporting of primarily unplanned readmissions. Journal of Hospital Medicine 2015. (c) 2015 Society of Hospital Medicine.

Purpose: To characterize the utility of shoulder imaging in the outpatient setting; Define predictor variables for useful shoulder imaging in terms of guiding the selection of the primary diagnosis and treatment Materials and Methods: We conducted a retrospective review of adult patients over a 32 month period evaluated and imaged for a primary complaint of shoulder pain in one of three outpatient settings: (1) orthopaedics, (2) emergency department [ED], and (3) internal medicine [IM]. Our sample population was chosen through a review of electronic medical records, using shoulder related ICD-9 codes and physician names. The main outcome variable for this study was imaging utility. A useful imaging examination was defined as a study that satisfied at least one of the following 4 criteria: changed the clinical diagnosis, guided a change in treatment selection, provided a final diagnosis, or guided definitive treatment. A utility score was assigned to each study based on the number of criteria satisfied (range 0-4) with a score of 0 defined as no utility, 1 low utility, 2 moderate utility, and score of > 3 high utility. For patients receiving multiple sequential imaging studies during their workup, each study was included and scored separately. The potential predictor variables evaluated for useful imaging included age, gender, trauma history, symptom chronicity, and injury setting (sports vs. non-sports). Statistical analysis included 95 % confidence intervals and binary logistic regression. Results: A total of 122 patients (70 female/52 male; mean age 47 years (range 18-84)) underwent a total of 171 imaging studies (109 radiographs/57 MRIs/3 CT/2 ultrasound) as part of their initial workup. 106 studies were ordered from orthopaedics, 64 from ED, and 1 from IM. CT and ultrasound utility were not assessed due to low number of cases. Overall, 95.9 % of the imaging studies met the minimum criteria for utility, most commonly helping guide the selection of a definitive treatment (71.9 %). 30.4 % of the studies were categorized as moderately useful, while 12.9 % were classified as highly useful. 95.4 % of radiographs met the criteria for utility, the majority of which were categorized as low utility (78.9 %). Both sports related injury history and trauma were predictive of at least moderate utility for radiographs (p = 0.039, p = 0.004). Younger age was a significant predictor of at least moderate utility for radiographs, most commonly in patients under 32 (p=0.003, AUC 0.748). 96.5 % of MRIs met the criteria for utility, the majority of which were categorized as moderate or high utility (84.2 %). None of the variables investigated were found to significantly predict MRI utility. For patients undergoing radiographs and MRI, MRI was found more useful than radiographs in 53 % of patients with an average utility score of 2.1. Equal utility was found in 42 % of cases, while radiographs were found most useful in 5 % of patients. Conclusion: Our study suggests that both radiographs and MRI have utility in the outpatient evaluation of shoulder pain. This serves as a potential first step towards the development of evidence based imaging algorithms that can be used and tested in future studies

BACKGROUND: Despite recent reductions in national unplanned readmission rates, we have relatively little understanding of which hospital strategies are most associated with changes in risk-standardized readmission rates (RSRR). OBJECTIVE: We examined associations between the change in hospital 30-day RSRR for patients with heart failure and the uptake of strategies over 12-18 months in a national sample of hospitals. DESIGN: We conducted a prospective study of hospitals using a Web-based survey at baseline (November 2010-May 2011, n = 599, 91.0 % response rate) and 12-18 months later (November 2011-October 2012, n = 501, 83.6 % response rate), with RSRR measured at the same time points. The final analytic sample included 478 hospitals. PARTICIPANTS: The study included hospitals participating in the Hospital-to-Home (H2H) and State Action on Avoidable Rehospitalizations (STAAR) initiatives. MAIN MEASURES: We examined associations between change in hospital 30-day RSRR for patients with heart failure and the uptake of strategies previously demonstrated to have increased between baseline and follow-up, using unadjusted and adjusted linear regression. KEY RESULTS: The average number of strategies taken up from baseline to follow-up was 1.6 (SE = 0.06); approximately one-quarter (25.3 %) of hospitals took up at least three new strategies. Hospitals that adopted the strategy of routinely discharging patients with a follow-up appointment already scheduled experienced significant reductions in RSRR (reduction of 0.63 percentage point, p value < 0.05). Hospitals that took up three or more strategies had significantly greater reductions in RSRR compared to hospitals that took up only zero to two strategies (reduction of 1.29 versus 0.57 percentage point, p value < 0.05). Among the 117 hospitals that took up three or more strategies, 93 unique combinations of strategies were used. CONCLUSIONS: Although most individual strategies were not associated with RSRR reduction, hospitals that took up any three or more strategies showed significantly greater reduction in RSRR compared to hospitals that took up fewer than three strategies.

BACKGROUND: Hospitalized patients with diabetes have experienced a disproportionate reduction in mortality over the past decade. OBJECTIVE: To examine whether this differential decrease affected all patients with diabetes, and to identify explanatory factors. DESIGN: Serial, cross-sectional observational study. SETTING: Academic medical center. PATIENTS: All adult, nonobstetric patients with an inpatient discharge between January 1, 2000 and December 31, 2010. MEASUREMENT: We assessed in-hospital mortality; inpatient glycemic control (percentage of hospital days with glucose below 70, above 299, and between 70 and 179 mg/dL, and standard deviation of glucose measurements), and outpatient glycemic control (hemoglobin A1c). RESULTS: We analyzed 322,938 admissions, including 76,758 (23.8%) with diabetes. Among 54,645 intensive care unit (ICU) admissions, there was a 7.8% relative reduction in the odds of mortality in each successive year for patients with diabetes, adjusted for age, race, payer, length of stay, discharge diagnosis, comorbidities, and service (odds ratio [OR]: 0.923, 95% confidence interval [CI]: 0.906-0.940). This was significantly greater than the 2.6% yearly reduction for those without diabetes (OR: 0.974, 95% CI: 0.963-0.985; P < 0.001 for interaction). In contrast, the greater decrease in mortality among non-ICU patients with diabetes did not reach significance. Results were similar among medical and surgical patients. Among ICU patients with diabetes, the significant decline in mortality persisted after adjustment for inpatient and outpatient glucose control (OR: 0.953, 95% CI: 0.914-0.994). CONCLUSIONS: Patients with diabetes in the ICU have experienced a disproportionate reduction in mortality that is not explained by glucose control. Potential explanations include improved cardiovascular risk management or advances in therapies for diseases commonly affecting patients with diabetes. Journal of Hospital Medicine 2015. (c) 2015 Society of Hospital Medicine.