Faculty Bibliography

BACKGROUND:Evidence-based therapy for heart failure remains underutilized at hospital discharge, particularly for patients with heart failure who are hospitalized for another cause. We developed clinical decision support (CDS) to recommend an angiotensin converting enzyme (ACE) inhibitor during hospitalization to promote its continuation at discharge. The CDS was designed to be implemented in both interruptive and non-interruptive versions. OBJECTIVES/OBJECTIVE:To compare the effectiveness and implementation of interruptive and non-interruptive versions of a CDS to improve care for heart failure. METHODS:Hospitalizations of patients with reduced ejection fraction were pseudo-randomized to deliver interruptive or non-interruptive CDS alerts to providers based on even or odd medical record number. We compared discharge utilization of an ACE inhibitor or angiotensin receptor blocker (ARB) for these two implementation approaches. We also assessed adoption and implementation fidelity of the CDS. RESULTS:percentile) of 14 (5,32) alerts were triggered per hospitalization. CONCLUSIONS:A CDS implemented as an interruptive alert was associated with improved quality of care for heart failure. Whether the potential benefits of CDS in improving cardiovascular care were worth the high burden of interruptive alerts deserves further consideration. CLINICALTRIALS. GOV IDENTIFIER/UNASSIGNED:NCT02858674.

BACKGROUND:The Hospital Readmissions Reduction Program (HRRP) penalizes hospitals for higher-than-expected readmission rates. Almost 20% of Medicare fee-for-service (FFS) patients receive postacute care in skilled nursing facilities (SNFs) after hospitalization. SNF patients have high readmission rates. OBJECTIVE:The objective of this study was to investigate the association between changes in hospital referral patterns to SNFs and HRRP penalty pressure. DESIGN/METHODS:We examined changes in the relationship between penalty pressure and outcomes before versus after HRRP announcement among 2698 hospitals serving 6,936,393 Medicare FFS patients admitted for target conditions: acute myocardial infarction, heart failure, or pneumonia. Hospital-level penalty pressure was the expected penalty rate in the first year of the HRRP multiplied by Medicare discharge share. OUTCOMES/RESULTS:Informal integration measured by the percentage of referrals to hospitals' most referred SNF; formal integration measured by SNF acquisition; readmission-based quality index of the SNFs to which a hospital referred discharged patients; referral rate to any SNF. RESULTS:Hospitals facing the median level of penalty pressure had modest differential increases of 0.3 percentage points in the proportion of referrals to the most referred SNF and a 0.006 SD increase in the average quality index of SNFs referred to. There were no statistically significant differential increases in formal acquisition of SNFs or referral rate to SNF. CONCLUSIONS:HRRP did not prompt substantial changes in hospital referral patterns to SNFs, although readmissions for patients referred to SNF differentially decreased more than for other patients, warranting investigation of other mechanisms underlying readmissions reduction.

PURPOSE/OBJECTIVE:The aim of this study was to determine rates of and possible reasons for guideline-discordant ordering of CT pulmonary angiography for the evaluation of suspected pulmonary embolism (PE) in the emergency department. METHODS:A retrospective review was performed of 212 consecutive encounters (January 6, 2016, to February 25, 2016) with 208 unique patients in the emergency department that resulted in CT pulmonary angiography orders. For each encounter, the revised Geneva score and two versions of the Wells criteria were calculated. Each encounter was then classified using a two-tiered risk stratification method (PE unlikely versus PE likely). Finally, the rate of and possible explanations for guideline-discordant ordering were assessed via in-depth chart review. RESULTS:The frequency of guideline-discordant studies ranged from 53 (25%) to 79 (37%), depending on the scoring system used; 46 (22%) of which were guideline discordant under all three scoring systems. Of these, 18 (39%) had at least one patient-specific factor associated with increased risk for PE but not included in the risk stratification scores (eg, travel, thrombophilia). CONCLUSIONS:Many of the guideline-discordant orders were placed for patients who presented with evidence-based risk factors for PE that are not included in the risk stratification scores. Therefore, guideline-discordant ordering may indicate that in the presence of these factors, the assessment of risk made by current scoring systems may not align with clinical suspicion.

BACKGROUND:Reducing costs while increasing or maintaining quality is crucial to delivering high value care. OBJECTIVE:To assess the impact of a hospital value-based management programme on cost and quality. DESIGN/METHODS:Time series analysis of non-psychiatric, non-rehabilitation, non-newborn patients discharged between 1 September 2011 and 31 December 2017 from a US urban, academic medical centre. INTERVENTION/METHODS:NYU Langone Health instituted an institution-wide programme in April 2014 to increase value of healthcare, defined as health outcomes achieved per dollar spent. Key features included joint clinical and operational leadership; granular and transparent cost accounting; dedicated project support staff; information technology support; and a departmental shared savings programme. MEASUREMENTS/METHODS:Change in variable direct costs; secondary outcomes included changes in length of stay, readmission and in-hospital mortality. RESULTS:The programme chartered 74 projects targeting opportunities in supply chain management (eg, surgical trays), operational efficiency (eg, discharge optimisation), care of outlier patients (eg, those at end of life) and resource utilisation (eg, blood management). The study cohort included 160 434 hospitalisations. Adjusted variable costs decreased 7.7% over the study period. Admissions with medical diagnosis related groups (DRG) declined an average 0.20% per month relative to baseline. Admissions with surgical DRGs had an early increase in costs of 2.7% followed by 0.37% decrease in costs per month. Mean expense per hospitalisation improved from 13% above median for teaching hospitals to 2% above median. Length of stay decreased by 0.25% per month relative to prior trends (95% CI -0.34 to 0.17): approximately half a day by the end of the study period. There were no significant changes in 30-day same-hospital readmission or in-hospital mortality. Estimated institutional savings after intervention costs were approximately $53.9 million. LIMITATIONS/CONCLUSIONS:Observational analysis. CONCLUSION/CONCLUSIONS:A systematic programme to increase healthcare value by lowering the cost of care without compromising quality is achievable and sustainable over several years.

Background: The transition of care from hospital to home is a vulnerable time for patients, often leaving individuals with a suboptimal understanding of the care plan, which can lead to post-hospitalization morbidity and readmissions. Prominent national medical societies and health services interventions have identified important domains to be addressed on discharge. Yet, there remains variable implementation of these high value discharge practices and often little transparency surrounding roles of medical team members at discharge. Direct field observation from the perspective of the patient is critical to inform gaps in the delivery of high quality discharge care. This study is the first to capture the discharge process by the entire healthcare professional team from the patient perspective.
Method(s): Purposeful sampling was used to select patients designated for " discharge by noon" with complex care plans. On the day of discharge, a research assistant sat at the bedside of a single consented patient from 6am until time of discharge, and recorded all communication and time spent on discharge education. Field notes were deductively analyzed for how patients were educated on key domains: medications, appointments, self-management of illness, symptom expectations, red flags, teach back and patient activation.
Result(s): To date, 15 patients with a total of 92 hours of observations have been conducted. On average, interns spent about 4.5 minutes with the patient on discharge and less than 1 minute on discharge education. Nurses had variable discharge practices, which ranged from asking the patient to read printed discharge information to reading the discharge instructions to the patient. While most patients were told about medication changes, 40% were not told the purpose of medication changes. Similarly, the majority of patients were not told the purpose of follow-up medical appointments or pending Results. There was limited education surrounding the self-management of diseases, symptom expectations or red flags. When provided, discharge education was one-sided; no patients were engaged through teach-back or patient activation. One patient was asked about potential barriers to adherence with the care plan. The majority of discharge communication was on practical steps of leaving the hospital, not preparing the patient to care for their themselves at home.
Conclusion(s): There is significant opportunity for improved discharge techniques to enhance safety and quality of care for patients leaving the hospital-including teach-back and patient engagement. Interventions must be implemented to increase patient education, particularly interprofessional ones that clarify assumptions on each other's roles. Further studies on effective communication strategies as well as systems redesign that foster patient-centered discharge education are imperative

Background: Discharge to skilled nursing facilities (SNF) is common in patients with heart failure (HF). The goal of a SNF stay is to improve functional status to allow patients to return home safely. However, the second transition from SNF to home may also be risky. Here, we examine the association between receipt of home health care (HHC) and readmission risk among patients discharged from SNF to home following HF hospitalization.
Method(s): We examined all Medicare fee-for-service beneficiaries 65 and older admitted 2012-2015 with a HF diagnosis discharged to SNF then subsequently discharged home. The primary outcome was unplanned read-mission within 30 days of SNF to home discharge, using CMS's HF read-mission methodology. We plotted time to readmission with Kaplan-Meier curves and compared these groups with a log-rank test. Then, we compared time to readmission using an adjusted Cox model; this model included a frailty term to account for correlation of patient outcome by SNF.
Result(s): There were 67,585 HF hospitalizations discharged to SNF and subsequently discharged home; 13,257 (19.6%) were discharged with HHC, 54,328 (80.4%) without. Patients discharged home from SNF with HHC had lower 30-day readmission rates than patients discharged without HHC (22.8% vs 24.5%, p< 0.0001). Kaplan-Meier curves demonstrated that patients discharged home from SNF with HHC have a longer unadjusted time to readmission. Of those readmitted within 30 days, median time to readmission for those discharged home from SNF with HHC was 11 days and 9 days for those discharged home without HHC (p< 0.0001). After risk-adjustment, patients discharged home with HHC still had a lower hazard of 30-day readmission.
Conclusion(s): Patients who received HHC were less likely to be readmitted within 30 days compared to those discharged home without HHC. This is unexpected as patients discharged with HHC likely have more functional impairments and therefore at higher readmission risk. Since patients requiring a SNF stay after hospital discharge may have additional needs, they may be especially likely to benefit from restorative therapy through HHC; however only about 20% received such services

Background: Electronic health record (EHR) documentation may contribute to burnout, especially for those with substantial clinical effort. We assessed whether clinical effort is associated with working in the EHR after work hours.
Method(s): We included all ambulatory physicians in a medicine specialty continuously practicing at any NYU Langone Health Faculty Group Practice site between May 1 and October 31, 2018. We quantified minutes logged into the EHR on days without scheduled appointments, and minutes logged into the EHR 30 minutes before and after appointments on days with scheduled appointments. We termed this time " work after work." We categorized physicians by their average number of days with appointments per week. Data were analyzed using SAS 9.4 (SAS Institute, Cary, NC). We calculated least squares means of fixed effects to account for heterogeneous variances, and compared means using Tukey's multiple comparison test. This study met institutional review board criteria for quality improvement work.
Result(s): We included 300 physicians, of whom 28.6% were general internists. The average physician had 3 days/week with scheduled appointments, spent 114.9 min in the EHR on days without appointments, and spent 21.7 min in the EHR after work hours on days with appointments. Time spent in the EHR on days without appointments increased with the number of appointment days per week (14.7 min/unscheduled day for 1 day/week vs. 193.8 min/unscheduled day for > 4 days/week, p< 0.001). Time spent in the EHR after hours on days with scheduled appointments did not significantly differ (Table 1).
Conclusion(s): All ambulatory physicians spend a substantial amount of time working in the EHR after hours and on unscheduled days (including weekends), but physicians with more clinical time were disproportionately burdened. The most clinically active spent an average of 2.8 hours in the EHR each unscheduled day. These findings add to concerns about EHR usability and documentation burden, particularly for busier clinicians. Our institution is now building dashboards to track work after work, offloading tasks to ancillary team members to reduce physician work burden, and exploring whether outliers would benefit from personalized technical assistance and training. Work after work analyses could be employed elsewhere to motivate similar improvements

Background: Hospitalized patients often undergo interventional radiology (IR) procedures, many of which require individualized pre-procedure preparation and post-procedure care. Internists caring for these patients may not be familiar with requirements for these patients, causing procedural delays or periprocedural adverse events. Clear communication between IR and internal medicine is therefore necessary, but is often lacking.
Method(s): We conducted qualitative interviews with hospitalists, house staff, nurses and IR staff to identify common breakdowns in periprocedural communication between IR and referring medicine units. Utilizing insights from these interviews, we identified essential elements for pre-procedure and post-procedure communication. These elements were added as fields in templated pre-and post-procedure IR notes (Table 1). Each standardized template contains 16 elements. Outcome measures included proportion of key elements included in IR notes, inpatient provider satisfaction, and frequency of phone calls into and out of IR before and after the intervention.
Result(s): Before implementation of the standardized templates, pre-procedure consult notes (N=25) contained an average of 3.5 key elements (typically a brief medical history, assessment and plan), while post-implementation (N=50), these notes contained an average of 15.3 elements (p< 0.001). Similarly, post-procedure notes (N=25) contained an average of 4.7 elements (typically the names of the IR providers, a brief procedure description and patient condition) pre-intervention versus a mean of 15.0 elements post-intervention (N=50) (p< 0.001). Surveys of hospitalists pre-(N=17) and post-intervention (N=10) showed no significant difference in lack of confidence in preparing patients for IR procedures (52.9% vs. 30.0%, p=0.40), ineffective collaboration with IR (11.8% vs. 0%, p=0.44), and not receiving clear recommendations (35.3% vs. 10%, p=0.67); however analyses were underpowered. Total calls into and out of VIR decreased 15.6% overall (mean decrease of 7.7 calls/weekday and 24.5 calls/weekend, p=.006).
Conclusion(s): Standardizing pre-and post-procedure documentation can effectively increase the inclusion of key content, and this content may reduce internal medicine physician questions and concerns regarding periprocedural patient care

OBJECTIVE:Discharge to skilled nursing facilities (SNFs) is common in patients with heart failure (HF). It is unknown whether the transition from SNF to home is risky for these patients. Our objective was to study outcomes for the 30 days after discharge from SNF to home among Medicare patients hospitalized with HF who had subsequent SNF stays of 30 days or less. DESIGN/METHODS:Retrospective cohort study. SETTING AND PARTICIPANTS/METHODS:All Medicare fee-for-service beneficiaries 65 and older admitted during 2012-2015 with a HF diagnosis discharged to SNF then subsequently discharged home. MEASURES/METHODS:Patients were followed for 30 days following SNF discharge. We categorized patients by SNF length of stay: 1 to 6 days, 7 to 13 days, and 14 to 30 days. For each group, we modeled time to a composite outcome of unplanned readmission or death after SNF discharge. Our model examined 0-2 days and 3-30 days post-SNF discharge. RESULTS:Our study included 67,585 HF hospitalizations discharged to SNF and subsequently discharged home. Overall, 16,333 (24.2%) SNF discharges to home were readmitted within 30 days of SNF discharge. The hazard rate of the composite outcome for each group was significantly increased on days 0 to 2 after SNF discharge compared to days 3 to 30, as reflected in their hazard rate ratios: for patients with SNF length of stay 1 to 6 days, 4.60 (4.23-5.00); SNF length of stay 7 to 13 days, 2.61 (2.45-2.78); SNF length of stay 14 to 30 days, 1.70 (1.62-1.78). CONCLUSIONS/IMPLICATIONS/CONCLUSIONS:The hazard rate of readmission after SNF discharge following HF hospitalization is highest during the first 2 days home. This risk attenuated with longer SNF length of stay. Interventions to improve postdischarge outcomes have primarily focused on hospital discharge. This evidence suggests that interventions to reduce readmissions may be more effective if they also incorporate the SNF-to-home transition.