Incorporating Acute Conditions into Risk-Adjustment for Provider Profiling: The Case of the US News and World Report Best Hospitals Rankings Methodology.

Several years ago, the US News and World Report changed their risk-adjustment methodology, now relying almost exclusively on chronic conditions for risk adjustment. The impacts of adding selected acute conditions like pneumonia, sepsis, and electrolyte disorders ("augmented") to their current risk models ("base") for 4 specialties-cardiology, neurology, oncology, and pulmonology-on estimates of hospital performance are reported here. In the augmented models, many acute conditions were associated with substantial risks of mortality. Compared to the base models, the discrimination and calibration of the augmented models for all specialties were improved. While estimated hospital performance was highly correlated between the 2 models, the inclusion of acute conditions in risk-adjustment models meaningfully improved the predictive ability of those models and had noticeable effects on hospital performance estimates. Measures or conditions that address disease severity should always be included when risk-adjusting hospitalization outcomes, especially if the goal is provider profiling.

Neighborhood socioeconomic deprivation, healthcare access, and 30-day mortality and readmission after sepsis or critical illness: findings from a nationwide study.

BACKGROUND: To determine if neighborhood socioeconomic deprivation independently predicts 30-day mortality and readmission for patients with sepsis or critical illness after adjusting for individual poverty, demographics, comorbidity burden, access to healthcare, and characteristics of treating healthcare facilities. METHODS: We performed a nationwide study of United States Medicare beneficiaries from 2017 to 2019. We identified hospitalized patients with severe sepsis and patients requiring prolonged mechanical ventilation, tracheostomy, or extracorporeal membrane oxygenation (ECMO) through Diagnosis Related Groups (DRGs). We estimated the association between neighborhood socioeconomic deprivation, measured by the Area Deprivation Index (ADI), and 30-day mortality and unplanned readmission using logistic regression models with restricted cubic splines. We sequentially adjusted for demographics, individual poverty, and medical comorbidities, access to healthcare services; and characteristics of treating healthcare facilities. RESULTS: A total of 1,526,405 admissions were included in the mortality analysis and 1,354,548 were included in the readmission analysis. After full adjustment, 30-day mortality for patients was higher for those from most-deprived neighborhoods (ADI 100) compared to least deprived neighborhoods (ADI 1) for patients with severe sepsis (OR 1.35 95% [CI 1.29-1.42]) or with prolonged mechanical ventilation with or without sepsis (OR 1.42 [95% CI 1.31, 1.54]). This association was linear and dose dependent. However, neighborhood socioeconomic deprivation was not associated with 30-day unplanned readmission for patients with severe sepsis and was inversely associated with readmission for patients requiring prolonged mechanical ventilation with or without sepsis. CONCLUSIONS: A strong association between neighborhood socioeconomic deprivation and 30-day mortality for critically ill patients is not explained by differences in individual poverty, demographics, measured baseline medical risk, access to healthcare resources, or characteristics of treating hospitals.

Neighborhood Socioeconomic Disadvantage, Healthcare Access, and Outcomes of Hospitalizations for Common Pulmonary Conditions: A National Study of Medicare Beneficiaries.

Rationale: Understanding how systemic forces and environmental exposures impact patient outcomes is critical to advancing health equity and improving population health for patients with pulmonary disease. This relationship has not yet been assessed at the population level nationally. Objectives: To determine whether neighborhood socioeconomic deprivation is independently associated with 30-day mortality and readmission for hospitalized patients with pulmonary conditions, after controlling for demographics, access to healthcare resources, and characteristics of admitting healthcare facilities. Methods: This was a retrospective, population-level cohort study of 100% of United States nationwide Medicare inpatient and outpatient claims from 2016-2019. Patients were admitted for one of four pulmonary conditions (pulmonary infections, chronic lower respiratory disease, pulmonary embolism, and pleural and interstitial lung diseases), defined by diagnosis-related group. The primary exposure was neighborhood socioeconomic deprivation, measured by the area deprivation index. The main outcomes were 30-day mortality and 30-day unplanned readmission, defined by Centers for Medicare and Medicaid Services methodologies. Generalized estimating equations were used to estimate logistic regression models for the primary outcomes, addressing clustering by hospital. A sequential adjustment strategy was first adjusted for age, legal sex, Medicare-Medicaid dual eligibility, and comorbidity burden, then adjusted for metrics of access to healthcare resources, and finally adjusted for characteristics of the admitting healthcare facility. Results: After full adjustment, patients from low socioeconomic status neighborhoods had greater 30-day mortality after admission for pulmonary embolism (odds ratio [OR], 1.26; 95% confidence interval [CI], 1.13-1.40), respiratory infections (OR, 1.20; 95% CI, 1.16-1.25), chronic lower respiratory disease (OR, 1.31; 95% CI, 1.22-1.41), and interstitial lung disease (OR, 1.15; 95% CI, 1.04-1.27) when compared to patients from the highest SES neighborhoods. Low neighborhood socioeconomic status was also associated with 30-day readmission for all groups except the interstitial lung disease group. Conclusions: Neighborhood socioeconomic deprivation may be a key factor driving poor health outcomes for patients with pulmonary diseases.

Association Between Neighborhood Socioeconomic Status and 30-Day Mortality and Readmission for Patients With Common Neurologic Conditions.

BACKGROUND AND OBJECTIVES: Patients of low individual socioeconomic status (SES) are at a greater risk of unfavorable health outcomes. However, the association between neighborhood socioeconomic deprivation and health outcomes for patients with neurologic disorders has not been studied at the population level. Our objective was to determine the association between neighborhood socioeconomic deprivation and 30-day mortality and readmission after hospitalization for various neurologic conditions. METHODS: This was a retrospective study of nationwide Medicare claims from 2017 to 2019. We included patients older than 65 years hospitalized for the following broad categories based on diagnosis-related groups (DRGs): multiple sclerosis and cerebellar ataxia (DRG 058-060); stroke (061-072); degenerative nervous system disorders (056-057); epilepsy (100-101); traumatic coma (082-087), and nontraumatic coma (080-081). The exposure of interest was neighborhood SES, measured by the area deprivation index (ADI), which uses socioeconomic indicators, such as educational attainment, unemployment, infrastructure access, and income, to estimate area-level socioeconomic deprivation at the level of census block groups. Patients were grouped into high, middle, and low neighborhood-level SES based on ADI percentiles. Adjustment covariates included age, comorbidity burden, race/ethnicity, individual SES, and sex. RESULTS: After exclusions, 905,784 patients were included in the mortality analysis and 915,993 were included in the readmission analysis. After adjustment for age, sex, race/ethnicity, comorbidity burden, and individual SES, patients from low SES neighborhoods had higher 30-day mortality rates compared with patients from high SES neighborhoods for all disease categories except for multiple sclerosis: magnitudes of the effect ranged from an adjusted odds ratio of 2.46 (95% CI 1.60-3.78) for the nontraumatic coma group to 1.23 (95% CI 1.19-1.28) for the stroke group. After adjustment, no significant differences in readmission rates were observed for any of the groups. DISCUSSION: Neighborhood SES is strongly associated with 30-day mortality for many common neurologic conditions even after accounting for baseline comorbidity burden and individual SES. Strategies to improve health equity should explicitly consider the effect of neighborhood environments on health outcomes.

Safety Culture and Workforce Well-Being Associations with Positive Leadership WalkRounds.

BACKGROUND: Interventions to decrease burnout and increase well-being in health care workers (HCWs) and improve organizational safety culture are urgently needed. This study was conducted to determine the association between Positive Leadership WalkRounds (PosWR), an organizational practice in which leaders conduct rounds and ask staff about what is going well, and HCW well-being and organizational safety culture. METHODS: This study was conducted in a large academic health care system in which senior leaders were encouraged to conduct PosWR. The researchers used data from a routine cross-sectional survey of clinical and nonclinical HCWs, which included a question about recall of exposure of HCWs to PosWR: "Do senior leaders ask for information about what is going well in this work setting (e.g., people who deserve special recognition for going above and beyond, celebration of successes, etc.)?"-along with measures of well-being and safety culture. T-tests compared work settings in the first and fourth quartiles for PosWR exposure across SCORE (Safety, Communication, Operational Reliability, and Engagement) domains of safety culture and workforce well-being. RESULTS: Electronic surveys were returned by 10,627 out of 13,040 possible respondents (response rate 81.5%) from 396 work settings. Exposure to PosWR was reported by 63.1% of respondents overall, with a mean of 63.4% (standard deviation = 20.0) across work settings. Exposure to PosWR was most commonly reported by HCWs in leadership roles (83.8%). Compared to work settings in the fourth (< 50%) quartile for PosWR exposure, those in the first (> 88%) quartile revealed a higher percentage of respondents reporting good patient safety norms (49.6% vs. 69.6%, p < 0.001); good readiness to engage in quality improvement activities (60.6% vs. 76.6%, p < 0.001); good leadership accessibility and feedback behavior (51.9% vs. 67.2%, p < 0.001); good teamwork norms (36.8% vs. 52.7%, p < 0.001); and good work-life balance norms (61.9% vs. 68.9%, p = 0.003). Compared to the fourth quartile, the first quartile had a lower percentage of respondents reporting emotional exhaustion in themselves (45.9% vs. 32.4%, p < 0.001), and in their colleagues (60.5% vs. 47.7%, p < 0.001). CONCLUSION: Exposure to PosWR was associated with better HCW well-being and safety culture.

Clinician Burnout Associated With Sex, Clinician Type, Work Culture, and Use of Electronic Health Records.

Importance: Electronic health records (EHRs) are considered a potentially significant contributor to clinician burnout. Objective: To describe the association of EHR usage, sex, and work culture with burnout for 3 types of clinicians at an academic medical institution. Design, Setting, and Participants: This cross-sectional study of 1310 clinicians at a large tertiary care academic medical center analyzed EHR usage metrics for the month of April 2019 with results from a well-being survey from May 2019. Participants included attending physicians, advanced practice providers (APPs), and house staff from various specialties. Data were analyzed between March 2020 and February 2021. Exposures: Clinician demographic characteristics, EHR metadata, and an institution-wide survey. Main Outcomes and Measures: Study metrics included clinician demographic data, burnout score, well-being measures, and EHR usage metadata. Results: Of the 1310 clinicians analyzed, 542 (41.4%) were men (mean [SD] age, 47.3 [11.6] years; 448 [82.7%] White clinicians, 52 [9.6%] Asian clinicians, and 21 [3.9%] Black clinicians) and 768 (58.6%) were women (mean [SD] age, 42.6 [10.3] years; 573 [74.6%] White clinicians, 105 [13.7%] Asian clinicians, and 50 [6.5%] Black clinicians). Women reported more burnout (survey score ≥50: women, 423 [52.0%] vs men, 258 [47.6%]; P = .008) overall. No significant differences in EHR usage were found by sex for multiple metrics of time in the EHR, metrics of volume of clinical encounters, or differences in products of clinical care. Multivariate analysis of burnout revealed that work culture domains were significantly associated with self-reported results for commitment (odds ratio [OR], 0.542; 95% CI, 0.427-0.688; P < .001) and work-life balance (OR, 0.643; 95% CI, 0.559-0.739; P < .001). Clinician sex significantly contributed to burnout, with women having a greater likelihood of burnout compared with men (OR, 1.33; 95% CI, 1.01-1.75; P = .04). An increased number of days spent using the EHR system was associated with less likelihood of burnout (OR, 0.966; 95% CI, 0.937-0.996; P = .03). Overall, EHR metrics accounted for 1.3% of model variance (P = .001) compared with work culture accounting for 17.6% of variance (P < .001). Conclusions and Relevance: In this cross-sectional study, sex-based differences in EHR usage and burnout were found in clinicians. These results also suggest that local work culture factors may contribute more to burnout than metrics of EHR usage.

Prospective and External Evaluation of a Machine Learning Model to Predict In-Hospital Mortality of Adults at Time of Admission.

Importance: The ability to accurately predict in-hospital mortality for patients at the time of admission could improve clinical and operational decision-making and outcomes. Few of the machine learning models that have been developed to predict in-hospital death are both broadly applicable to all adult patients across a health system and readily implementable. Similarly, few have been implemented, and none have been evaluated prospectively and externally validated. Objectives: To prospectively and externally validate a machine learning model that predicts in-hospital mortality for all adult patients at the time of hospital admission and to design the model using commonly available electronic health record data and accessible computational methods. Design, Setting, and Participants: In this prognostic study, electronic health record data from a total of 43 180 hospitalizations representing 31 003 unique adult patients admitted to a quaternary academic hospital (hospital A) from October 1, 2014, to December 31, 2015, formed a training and validation cohort. The model was further validated in additional cohorts spanning from March 1, 2018, to August 31, 2018, using 16 122 hospitalizations representing 13 094 unique adult patients admitted to hospital A, 6586 hospitalizations representing 5613 unique adult patients admitted to hospital B, and 4086 hospitalizations representing 3428 unique adult patients admitted to hospital C. The model was integrated into the production electronic health record system and prospectively validated on a cohort of 5273 hospitalizations representing 4525 unique adult patients admitted to hospital A between February 14, 2019, and April 15, 2019. Main Outcomes and Measures: The main outcome was in-hospital mortality. Model performance was quantified using the area under the receiver operating characteristic curve and area under the precision recall curve. Results: A total of 75 247 hospital admissions (median [interquartile range] patient age, 59.5 [29.0] years; 45.9% involving male patients) were included in the study. The in-hospital mortality rates for the training validation; retrospective validations at hospitals A, B, and C; and prospective validation cohorts were 3.0%, 2.7%, 1.8%, 2.1%, and 1.6%, respectively. The area under the receiver operating characteristic curves were 0.87 (95% CI, 0.83-0.89), 0.85 (95% CI, 0.83-0.87), 0.89 (95% CI, 0.86-0.92), 0.84 (95% CI, 0.80-0.89), and 0.86 (95% CI, 0.83-0.90), respectively. The area under the precision recall curves were 0.29 (95% CI, 0.25-0.37), 0.17 (95% CI, 0.13-0.22), 0.22 (95% CI, 0.14-0.31), 0.13 (95% CI, 0.08-0.21), and 0.14 (95% CI, 0.09-0.21), respectively. Conclusions and Relevance: Prospective and multisite retrospective evaluations of a machine learning model demonstrated good discrimination of in-hospital mortality for adult patients at the time of admission. The data elements, methods, and patient selection make the model implementable at a system level.

Work-life balance behaviours cluster in work settings and relate to burnout and safety culture: a cross-sectional survey analysis.

BACKGROUND: Healthcare is approaching a tipping point as burnout and dissatisfaction with work-life integration (WLI) in healthcare workers continue to increase. A scale evaluating common behaviours as actionable examples of WLI was introduced to measure work-life balance. OBJECTIVES: (1) Explore differences in WLI behaviours by role, specialty and other respondent demographics in a large healthcare system. (2) Evaluate the psychometric properties of the work-life climate scale, and the extent to which it acts like a climate, or group-level norm when used at the work setting level. (3) Explore associations between work-life climate and other healthcare climates including teamwork, safety and burnout. METHODS: Cross-sectional survey study completed in 2016 of US healthcare workers within a large academic healthcare system. RESULTS: 10 627 of 13 040 eligible healthcare workers across 440 work settings within seven entities of a large healthcare system (81% response rate) completed the routine safety culture survey. The overall work-life climate scale internal consistency was α=0.830. WLI varied significantly among healthcare worker role, length of time in specialty and work setting. Random effects analyses of variance for the work-life climate scale revealed significant between-work setting and within-work setting variance and intraclass correlations reflected clustering at the work setting level. T-tests of top versus bottom WLI quartile work settings revealed that positive work-life climate was associated with better teamwork and safety climates, as well as lower personal burnout and burnout climate (p<0.001). CONCLUSION: Problems with WLI are common in healthcare workers and differ significantly based on position and time in specialty. Although typically thought of as an individual difference variable, WLI appears to operate as a climate, and is consistently associated with better safety culture norms.

HEART Failure? Episodes of Missed Major Cardiac Events When Applying the HEART Pathway to an Observation Unit Population.

OBJECTIVE: The HEART Pathway risk prediction tool (HEART score plus serial troponin measures at 0 and 3 hours post-presentation) is used to identify low-risk patients with chest pain who may qualify for safe, early discharge. We calculated the percentage of patients in our observation unit that qualified as low risk using HEART Pathway, as well as their associated outcomes. METHODS: We retrospectively reviewed charts on 966 consecutive patients admitted to our observation unit for chest pain (January 2015 to February 2016); HEART Pathway scores were retrospectively calculated and serial cardiac troponin values logged. The primary outcome was 42-day major adverse cardiac events (MACE), including acute myocardial infarction, urgent revascularization, and all-cause death. RESULTS: The patients' mean age was 59, 42% were male, 46% white, and 68 (7.7%) had MACE. HEART Pathway defined 384 patients as low risk (39.8%) and eligible for early discharge. Applying HEART Pathway would have missed 1.2% of patients with MACE; however, all adverse cardiac events occurred in patients with a HEART Pathway score of 3 (4 of 193, 2.1%) and none in those with a HEART Pathway score ≤2 (0 of 134). CONCLUSIONS: While the HEART Pathway identifies a pooled population at low risk for MACE, risk is not homogenous within this population. Patients with a score of 3 may have higher risk of 42-day MACE that may be unacceptable to some providers, while scores ≤2 saw no events. Caution is advised for those with HEART Pathway score of 3 until more data is available to accurately estimate risk.

Improving Resident and Fellow Engagement in Patient Safety Through a Graduate Medical Education Incentive Program.

BACKGROUND: Collaboration between graduate medical education (GME) and health systems is essential for the success of patient safety initiatives. One example is the development of an incentive program aligning trainee performance with health system quality and safety priorities. OBJECTIVE: We aimed to improve trainee safety event reporting and engagement in patient safety through a GME incentive program. METHODS: The incentive program was implemented to provide financial incentives to drive behavior and engage residents and fellows in safety efforts. Safety event reporting was measured beginning in the 2014-2015 academic year. A training module was introduced and the system reporting link was added to the institution's Resident Management System homepage. The number of reports by trainees was tracked over time, with a target of 2 reports per trainee per year. RESULTS: Baseline data for the year prior to implementation of the incentive program showed less than 0.5% (74 of 16 498) of safety reports were submitted by trainees, in contrast with 1288 reports (7% of institutional reports) by trainees in 2014-2015 (P < .0001). A total of 516 trainees (57%), from 37 programs, received payment for the metric, based on a predefined program target of a mean of 2 reports per trainee. In 2015-2016 and 2016-2017 the submission rate was sustained, with 1234 and 1350 reports submitted by trainees, respectively. CONCLUSIONS: An incentive program as part of a larger effort to address safety events is feasible and resulted in increased reporting by trainees.

Improving Timely Resident Follow-Up and Communication of Results in Ambulatory Clinics Utilizing a Web-Based Audit and Feedback Module.

BACKGROUND: Failure to follow up and communicate test results to patients in outpatient settings may lead to diagnostic and therapeutic delays. Residents are less likely than attending physicians to report results to patients, and may face additional barriers to reporting, given competing clinical responsibilities. OBJECTIVE: This study aimed to improve the rates of communicating test results to patients in resident ambulatory clinics. METHODS: We performed an internal medicine, residency-wide, pre- and postintervention, quality improvement project using audit and feedback. Residents performed audits of ambulatory patients requiring laboratory or radiologic testing by means of a shared online interface. The intervention consisted of an educational module viewed with initial audits, development of a personalized improvement plan after Phase 1, and repeated real-time feedback of individual relative performance compared at clinic and program levels. Outcomes included results communicated within 14 days and prespecified "significant" results communicated within 72 hours. RESULTS: A total of 76 of 86 eligible residents (88%) reviewed 1713 individual ambulatory patients' charts in Phase 1, and 73 residents (85%) reviewed 1509 charts in Phase 2. Follow-up rates were higher in Phase 2 than Phase 1 for communicating results within 14 days and significant results within 72 hours (85% versus 78%, P < .001; and 82% versus 70%, P = .002, respectively). Communication of "significant" results was more likely to occur via telephone, compared with communication of nonsignificant results. CONCLUSIONS: Participation in a shared audit and feedback quality improvement project can improve rates of resident follow-up and communication of results, although communication gaps remained.

The Burden of Burnout.

This study sought to determine burnout prevalence and factors associated with burnout in internal medicine residents after introduction of the 2011 ACGME duty hour rules. Burnout was evaluated using an anonymized, abbreviated version of the Maslach Burnout Inventory. Surveys were collected biweekly for 48 weeks during the 2013-2014 academic year. Burnout severity was compared across subgroups and time. A score of 3 or higher signified burnout. Overall, 944 of 3936 (24%) surveys were completed. The mean burnout score across all surveys was 2.8. Categorical residents had higher burnout severity than noncategorical residents (2.9 vs 2.7, P = .005). Postgraduate year 2 residents had the highest burnout severity by year (3.1, P < .001). Residents on inpatient rotations had higher burnout severity than residents on outpatient or consultation rotations (3.1 vs 2.2 vs 2.2, P < .001). Night float rotations had the highest severity (3.8). Burnout remains a significant problem even with recent duty hour modifications.

The associations between work-life balance behaviours, teamwork climate and safety climate: cross-sectional survey introducing the work-life climate scale, psychometric properties, benchmarking data and future directions.

BACKGROUND: Improving the resiliency of healthcare workers is a national imperative, driven in part by healthcare workers having minimal exposure to the skills and culture to achieve work-life balance (WLB). Regardless of current policies, healthcare workers feel compelled to work more and take less time to recover from work. Satisfaction with WLB has been measured, as has work-life conflict, but how frequently healthcare workers engage in specific WLB behaviours is rarely assessed. Measurement of behaviours may have advantages over measurement of perceptions; behaviours more accurately reflect WLB and can be targeted by leaders for improvement. OBJECTIVES: 1. To describe a novel survey scale for evaluating work-life climate based on specific behavioural frequencies in healthcare workers.2. To evaluate the scale's psychometric properties and provide benchmarking data from a large healthcare system.3. To investigate associations between work-life climate, teamwork climate and safety climate. METHODS: Cross-sectional survey study of US healthcare workers within a large healthcare system. RESULTS: 7923 of 9199 eligible healthcare workers across 325 work settings within 16 hospitals completed the survey in 2009 (86% response rate). The overall work-life climate scale internal consistency was Cronbach α=0.790. t-Tests of top versus bottom quartile work settings revealed that positive work-life climate was associated with better teamwork climate, safety climate and increased participation in safety leadership WalkRounds with feedback (p<0.001). Univariate analysis of variance demonstrated differences that varied significantly in WLB between healthcare worker role, hospitals and work setting. CONCLUSIONS: The work-life climate scale exhibits strong psychometric properties, elicits results that vary widely by work setting, discriminates between positive and negative workplace norms, and aligns well with other culture constructs that have been found to correlate with clinical outcomes.

Incorporating Patient Acuity Rating Score Into Patient Handoffs and the Correlation With Rapid Responses and Unexpected ICU Transfers.

Handoffs and rapid response team (RRT) activations have been a focus for quality improvement in hospital medicine. This study aimed to incorporate a previously used scoring system (1-7) for severity of illness on initial encounter as a handoff adjunct and to determine its impact on the number of RRTs and intensive care unit transfers. The Patient Acuity Rating (PAR) scale correlates with subsequent RRTs and transfers to a higher level of care, with higher scores leading to increased rates of RRTs and transfers. Patients who experienced an RRT at any time (mean score 4.69), within 24 hours (4.74), or an unplanned transfer (5.16) had higher PAR scores on assessment than those who did not (4.02; all P < .05). There was an increased likelihood of RRTs and transfers with scores of 6 or higher. There was no reduction in the quantity of RRTs or unplanned intensive care unit transfers comparing preintervention and postintervention data.

Doctor Who? A Quality Improvement Project to Assess and Improve Patients' Knowledge of Their Inpatient Physicians.

Background Patient-physician communication is an integral part of high-quality patient care and an expectation of the Clinical Learning Environment Review program. Objective This quality improvement initiative evaluated the impact of an educational audit and feedback intervention on the frequency of use of 2 tools-business cards and white boards-to improve provider identification. Methods This before-after study utilized patient surveys to determine the ability of those patients to name and recognize their physicians. The before phase began in July 2013. From September 2013 to May 2014, physicians received education on business card and white board use. Results We surveyed 378 patients. Our intervention improved white board utilization (72.2% postintervention versus 54.5% preintervention, P < .01) and slightly improved business card use (44.4% versus 33.7%, P = .07), but did not improve physician recognition. Only 20.3% (14 of 69) of patients could name their physician without use of the business card or white board. Data from all study phases showed the use of both tools improved patients' ability to name physicians (OR = 1.72 and OR = 2.12, respectively; OR = 3.68 for both; P < .05 for all), but had no effect on photograph recognition. Conclusions Our educational intervention improved white board use, but did not result in improved patient ability to recognize physicians. Pooled data of business cards and white boards, alone or combined, improved name recognition, suggesting better use of these tools may increase identification. Future initiatives should target other barriers to usage of these types of tools.

An evaluation of physician predictions of discharge on a general medicine service.

The goal of this study was to evaluate general medicine physicians' ability to predict hospital discharge. We prospectively asked study subjects to predict whether each patient under their care would be discharged on the next day, on the same day, or neither. Discharge predictions were recorded at 3 time points: mornings (7-9 am), midday (12-2 pm), or afternoons (5-7 pm), for a total of 2641 predictions. For predictions of next-day discharge, the sensitivity (SN) and positive predictive value (PPV) were lowest in the morning (27% and 33%, respectively), but increased by the afternoon (SN 67%, PPV 69%). Similarly, for same-day discharge predictions, SN and PPV were highest at midday (88% and 79%, respectively). We found that although physicians have difficulty predicting next-day discharges in the morning prior to the day of expected discharge, their ability to correctly predict discharges continually improved as the time to actual discharge decreased. Journal of Hospital Medicine 2015;10:808-810. © 2015 Society of Hospital Medicine.

Development and assessment of a web-based clinical quality improvement curriculum.

BACKGROUND: Understanding quality improvement (QI) is an important skill for physicians, yet educational interventions focused on teaching QI to residents are relatively rare. Web-based training may be an effective teaching tool in time-limited and expertise-limited settings. INTERVENTION: We developed a web-based curriculum in QI and evaluated its effectiveness. METHODS: During the 2011-2012 academic year, we enrolled 53 first-year internal medicine residents to complete the online training. Residents were provided an average of 6 hours of protected time during a 1-month geriatrics rotation to sequentially complete 8 online modules on QI. A pre-post design was used to measure changes in knowledge of the QI principles and self-assessed competence in the objectives of the course. RESULTS: Of the residents, 72% percent (37 of 51) completed all of the modules and pretests and posttests. Immediate pre-post knowledge improved from 6 to 8.5 for a total score of 15 (P < .001) and pre-post self-assessed competence in QI principles on paired t test analysis improved from 1.7 to 2.7 on a scale of 5 for residents who completed all of the components of the course. CONCLUSIONS: Web-based training of QI in this study was comparable to other existing non-web-based curricula in improving learner confidence and knowledge in QI principles. Web-based training can be an efficient and effective mode of content delivery.