Faculty Bibliography

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.

BACKGROUND:Unplanned readmissions following elective total hip (THA) and knee (TKA) arthroplasty as a result of surgical complications likely have different quality improvement targets and cost implications than those for nonsurgical readmissions. We compared payments, timing, and location of unplanned readmissions with Center for Medicare and Medicaid Services (CMS)-defined surgical complications to readmissions without such complications. METHODS:We performed a retrospective analysis on unplanned readmissions within 90 days of discharge following elective primary THA/TKA among Medicare patients discharged between April 2013 and March 2016. We categorized unplanned readmissions into groups with and without CMS-defined complications. We compared the location, timing, and payments for unplanned readmissions between both readmission categories. RESULTS:Among THA (N = 23,231) and TKA (N = 43,655) patients with unplanned 90-day readmissions, 27.1% (n = 6307) and 16.4% (n = 7173) had CMS-defined surgical complications, respectively. These readmissions with surgical complications were most commonly at the hospital of index procedure (THA: 84%; TKA: 80%) and within 30 days postdischarge (THA: 73%; TKA: 77%). In comparison, it was significantly less likely for patients without CMS-defined surgical complications to be rehospitalized at the index hospital (THA: 63%; TKA: 63%; P < .001) or within 30 days of discharge (THA: 58%; TKA: 59%; P < .001). Generally, payments associated with 90-day readmissions were higher for THA and TKA patients with CMS-defined complications than without (P < .001 for all). CONCLUSION/CONCLUSIONS:Readmissions associated with surgical complications following THA and TKA are more likely to occur at the hospital of index surgery, within 30 days of discharge, and cost more than readmissions without CMS-defined surgical complications, yet they account for only 1 in 5 readmissions.

PURPOSE/OBJECTIVE:To develop natural language processing (NLP) to identify incidental lung nodules (ILNs) in radiology reports for assessment of management recommendations. METHOD AND MATERIALS/METHODS:We searched the electronic health records for patients who underwent chest CT during 2014 and 2017, before and after implementation of a department-wide dictation macro of the Fleischner Society recommendations. We randomly selected 950 unstructured chest CT reports and reviewed manually for ILNs. An NLP tool was trained and validated against the manually reviewed set, for the task of automated detection of ILNs with exclusion of previously known or definitively benign nodules. For ILNs found in the training and validation sets, we assessed whether reported management recommendations agreed with Fleischner Society guidelines. The guideline concordance of management recommendations was compared between 2014 and 2017. RESULTS:The NLP tool identified ILNs with sensitivity and specificity of 91.1% and 82.2%, respectively, in the validation set. Positive and negative predictive values were 59.7% and 97.0%. In reports of ILNs in the training and validation sets before versus after introduction of a Fleischner reporting macro, there was no difference in the proportion of reports with ILNs (108 of 500 [21.6%] versus 101 of 450 [22.4%]; P = .8), or in the proportion of reports with ILNs containing follow-up recommendations (75 of 108 [69.4%] versus 80 of 101 [79.2%]; P = .2]. Rates of recommendation guideline concordance were not significantly different before and after implementation of the standardized macro (52 of 75 [69.3%] versus 60 of 80 [75.0%]; P = .43). CONCLUSION/CONCLUSIONS:NLP reliably automates identification of ILNs in unstructured reports, pertinent to quality improvement efforts for ILN management.

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.

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.

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.

BACKGROUND:The Medicare Hospital Readmissions Reduction Program has led to fewer readmissions following hospitalizations with a principal diagnosis of heart failure (HF). Patients with HF are frequently hospitalized for other causes. OBJECTIVES/OBJECTIVE:This study sought to compare trends in Medicare risk-adjusted, 30-day readmissions following principal HF hospitalizations and other hospitalizations with HF. METHODS:This was a retrospective study of 12,973,853 Medicare hospitalizations with a principal or secondary diagnosis of HF between January 2008 and June 2015. Hospitalizations were categorized as follows: principal HF hospitalizations; principal acute myocardial infarction or pneumonia hospitalizations with secondary HF; and other hospitalizations with secondary HF. The study examined trends in risk-adjusted, 30-day, all-cause readmission rates for each cohort and trends in differences in readmission rates among cohorts by using linear spline regression models. RESULTS:Before passage of the Affordable Care Act in March 2010, risk-adjusted, 30-day readmission rates were stable for all 3 cohorts, with mean monthly rates of 26.1%, 24.9%, and 24.4%, respectively. Risk-adjusted readmission rates started declining after passage of the Affordable Care Act by 1.09% (95% confidence interval [CI]: 0.51% to 1.68%), 1.24% (95% CI: 0.92% to 1.57%), and 1.05% (95% CI: 0.52% to 1.58%) per year, respectively, until implementation of the Hospital Readmissions Reduction Program in October 2012 and then stabilized for all 3 cohorts. CONCLUSIONS:Patients with HF are often hospitalized for other causes, and these hospitalizations have high readmission rates. Policy changes led to decreases in readmission rates for both principal and secondary HF hospitalizations. Readmission rates in both groups remain high, suggesting that initiatives targeting all hospitalized patients with HF continue to be warranted.