scholarly journals Potential of community-based risk estimates for improving hospital performance measures and discharge planning

2021 ◽  
Vol 10 (2) ◽  
pp. e001230
Author(s):  
Michael Reid ◽  
George Kephart ◽  
Pantelis Andreou ◽  
Alysia Robinson
Keyword(s):  
Discharge Planning ◽  
Care Transitions ◽  
Hospital Setting ◽  
Hospital Performance ◽  
Case Mix ◽  
Readmission Rates ◽  
Mixed Effect ◽  
Adjusted Risk ◽  
Community Risk ◽  
Effect Regression

BackgroundRisk-adjusted rates of hospital readmission are a common indicator of hospital performance. There are concerns that current risk-adjustment methods do not account for the many factors outside the hospital setting that can affect readmission rates. Not accounting for these external factors could result in hospitals being unfairly penalized when they discharge patients to communities that are less able to support care transitions and disease management. While incorporating adjustments for the myriad of social and economic factors outside of the hospital setting could improve the accuracy of readmission rates as a performance measure, doing so has limited feasibility due to the number of potential variables and the paucity of data to measure them. This paper assesses a practical approach to addressing this problem: using mixed-effect regression models to estimate case-mix adjusted risk of readmission by community of patients’ residence (community risk of readmission) as a complementary performance indicator to hospital readmission rates.MethodsUsing hospital discharge data and mixed-effect regression models with a random intercept for community, we assess if case-mix adjusted community risk of readmission can be useful as a quality indicator for community-based care. Our outcome of interest was an unplanned repeat hospitalisation. Our primary exposure was community of residence.ResultsCommunity of residence is associated with case-mix adjusted risk of unplanned repeat hospitalisation. Community risk of readmission can be estimated and mapped as indicators of the ability of communities to support both care transitions and long-term disease management.ConclusionContextualising readmission rates through a community lens has the potential to help hospitals and policymakers improve discharge planning, reduce penalties to hospitals, and most importantly, provide higher quality care to the people that they serve.

scholarly journals Length of hospital stay after uncomplicated esophagectomy. Hospital variation shows room for nationwide improvement

2020 ◽  
Author(s):  
Daan M. Voeten ◽  
◽  
Leonie R. van der Werf ◽  
Johanna W. van Sandick ◽  
Richard van Hillegersberg ◽  
...  
Keyword(s):  
Hospital Stay ◽  
Substantial Reduction ◽  
Length Of Hospital Stay ◽  
Hospital Performance ◽  
Uneventful Recovery ◽  
Case Mix ◽  
Median Length ◽  
Dutch Hospital ◽  
Readmission Rates ◽  
Hospital Variation

Abstract Background Within the scope of value-based health care, this study aimed to analyze Dutch hospital performance in terms of length of hospital stay after esophageal cancer surgery and its association with 30-day readmission rates. Since both parameters are influenced by the occurrence of complications, this study only included patients with an uneventful recovery after esophagectomy. Methods All patients registered in the Dutch Upper Gastrointestinal Cancer Audit (DUCA) who underwent a potentially curative esophagectomy between 2015 and 2018 were considered for inclusion. Patients were excluded in case of an intraoperative/post-operative complication, readmission to the intensive care unit, or any re-intervention. Length of hospital stay was dichotomized around the national median into ‘short admissions’ and ‘long admissions’. Hospital variation was evaluated using a case-mix-corrected funnel plot based on multivariable logistic regression analyses. Association of length of hospital stay with 30-day readmission rates was investigated using the χ2-statistic. Results A total of 1007 patients was included. National median length of hospital stay was 9 days, ranging from 6.5 to 12.5 days among 17 hospitals. The percentage of ‘short admissions’ per hospital ranged from 7.7 to 93.5%. After correction for case-mix variables, 3 hospitals had significantly higher ‘short admission’ rates and 4 hospitals had significantly lower ‘short admission’ rates. Overall, 6.2% [hospital variation (0.0–13.2%)] of patients were readmitted. Hospital 30-day readmission rates were not significantly different between patients with a short length of hospital stay and those with a long length of hospital stay (5.5% versus 7.6%; p = 0.19). Conclusions Based on these nationwide audit data, median length of hospital stay after an uncomplicated esophagectomy was 9 days ranging from 6.5 to 12.5 days among Dutch hospitals. There was no association between length of hospital stay and readmission rates. Nationwide improvement might lead to a substantial reduction of hospital costs.

scholarly journals The Role of Rehabilitation in Reducing Resource Use and Lowering Hospital Readmission Through Discharge Planning

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 804-804
Author(s):  
Kenneth Miller
Keyword(s):  
Health Care Providers ◽  
Resource Use ◽  
Hospital Readmission ◽  
Discharge Planning ◽  
Care Transitions ◽  
Healthcare Team ◽  
Transition Management ◽  
Care Providers ◽  
Initial Examination ◽  
The Individual

Abstract The transitions between medical settings, the community and back again is a complex and intimidating process for patients, families and caregivers. These transitions are vulnerable points where planning is key and must begin at the initial examination with rehabilitation providers (PTs/OTs,SLPs). These providers are key members of the healthcare team to facilitate effective transition management. In this session, attendees will learn the critical factors rehabilitation providers use to evaluate patients in order to facilitate successful care transitions. An overview of the indications for rehabilitation referral will be presented, as well as evidence for effective rehabilitation strategies. The speaker will present tools from the American Physical Therapy Association Home Health Toolbox and outline a decision-making process for care transitions based on the individual, caregivers, and health care providers to achieve successful transitions that reduce resource use and hospital readmission rates. Attendees will learn strategies to facilitate inter-professional collaboration, communication, and advocacy.

scholarly journals Is Health Information Exchange Use by Hospitals and Home Health Agencies Associated with Lower Readmission Rates?

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 914-914
Author(s):  
Christine Jones ◽  
Jacob Thomas ◽  
Marisa Roczen ◽  
Kate Ytell ◽  
Mark Gritz
Keyword(s):  
Health Information ◽  
Information Exchange ◽  
Transitional Care ◽  
Care Transitions ◽  
Home Health ◽  
Hospital Length Of Stay ◽  
Care Hospital ◽  
Readmission Rates ◽  
Health Agencies ◽  
Home Health Agencies

Abstract For older adults transitioning from the hospital to home health agencies (HHAs), clinical information exchange is key for optimal transitional care. Hospital and HHA participation in regional health information exchanges (HIEs) could address fragmented communication and improve patient outcomes. We examined differences in characteristics and outcomes for patients with either Medicare or Medicare Advantage (MA) insurance who transitioned from hospitals to HHAs based on HIE participation with 2014-2018 data from the Colorado All Payer Claims Database. We performed analyses including chi square and t tests to compare patient characteristics and 30-day readmission rates for high versus lower HIE use, determined by HIE participation (+) and non-participation (-) among HHAs and hospitals: High HIE use dyads (Hospital+/HHA+) were compared to lower HIE use dyads (Hospital+/HHA-, Hospital-/HHA+, Hospital-/HHA-). We identified 57,998 care transitions from 123 acute care hospitals to 71 HHAs. On average, patients were 75 years old, had a three day hospital length of stay, over half were female (58%), 82% had Medicare and 18% had MA insurance. Although most characteristics were similar between high versus lower HIE use dyads, high HIE use dyads had a higher proportion of Medicare patients compared to the lower HIE use dyads (85% vs 79%, p <0.001). Thirty-day readmissions were 12.4% for care transitions that occurred among high HIE use dyads (n=27,784) compared to 12.8% among lower HIE use dyads (n=32,929, p=0.102). For adults transitioning from hospitals to HHAs among high HIE use dyads, a trend toward lower 30-day readmission rates was identified.

scholarly journals Lens densitometry for assessment and prediction of cataract progression after pars plana vitrectomy with C3F8-gas for retinal detachment

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254370
Author(s):  
Philipp Schindler ◽  
Luca Mautone ◽  
Eileen Bigdon ◽  
Vasyl Druchkiv ◽  
Martin Stefan Spitzer ◽  
...  
Keyword(s):  
Retinal Detachment ◽  
Regression Model ◽  
Pars Plana Vitrectomy ◽  
Quantitative Model ◽  
Average Deviation ◽  
Mixed Effect ◽  
Lens Opacification ◽  
Effect Regression ◽  
Pars Plana ◽  
Mixed Effect Regression Model

Purpose Lens opacification is a common complication after pars plana vitrectomy (PPV) and knowing its progression would facilitate consulting patients. The purpose of this study was to evaluate a quantitative model for lens-status-monitoring after PPV with C3F8 gas. Our model was evaluated in rhegmatogenous retinal detachment (RRD) patients of various age and lens densitometry (LD). Methods Data between March 2018 and March 2020 were evaluated retrospectively. LD measurements of the PentacamHR® Nucleus Staging mode (PNS) were used to quantify lens opacification over time. A mixed-effect regression model was designed, to enable LD predictions at any time postoperatively. Calculations were based on patient’s age and baseline LD as dependent variables. Six patients were randomly excluded during model development, to be used for testing its power afterwards. Results 34 patients (male 19 [55.9%], female 15 [44.1%]) matched the inclusion criteria. Average age was 58.5 years (32–77;±4.3) and average follow-up was 7.2 months (3,4–23.1;±1,8). Mean baseline LD of the treated and fellow eye before surgery were 10.9% (8.7%-14.8%;±0.8) and 10.7% (8.5%-14.1%;±0.6), respectively. Using our prediction model, LD values for the six pre-selected patients closely match the observed data with an average deviation of 1.07%. Conclusions Evaluation of age and baseline LD using a mixed-effect regression model might predict cataract progression in RRD patients treated with PPV and C3F8-gas. Such a tool could be considered during cataract surgery consultation in these patients.

scholarly journals Trends in cardiovascular risk factors and treatment goals in patients with diabetes in Singapore-analysis of the SingHealth Diabetes Registry

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0259157
Author(s):  
Liang Feng ◽  
Amanda Lam ◽  
David Carmody ◽  
Ching Wee Lim ◽  
Gilbert Tan ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Glycated Hemoglobin ◽  
Temporal Trends ◽  
Vascular Complications ◽  
Housing Type ◽  
Risk Factor Control ◽  
Mixed Effect ◽  
Diabetes Registry ◽  
Adjusted Risk

Background Asian populations are at high risk of diabetes and related vascular complications. We examined risk factor control, preventive care, and disparities in these trends among adults with diabetes in Singapore. Methods The sample included 209,930 adults with diabetes aged≥18 years from a multi-institutional SingHealth Diabetes Registry between 2013 and 2019 in Singapore. We performed logistic generalized estimating equations (GEEs) regression analysis and used linear mixed effect modeling to evaluate the temporal trends. Results Between 2013 and 2019, the unadjusted control rates of glycated hemoglobin (4.8%, 95%CI (4.4 to 5.1) and low-density lipoprotein cholesterol (LDL-C) (11.5%, 95%CI (11.1 to 11.8)) improved, but blood pressure (BP) control worsened (systolic BP (SBP)/diastolic BP (DBP) <140/90 mmHg: -6.6%, 95%CI (-7.0 to -6.2)). These trends persisted after accounting for the demographics including age, gender, ethnicity, and housing type. The 10-year adjusted risk for coronary heart disease (CHD) (3.4%, 95% (3.3 to 3.5)) and stroke (10.4%, 95% CI (10.3 to 10.5)) increased. In 2019, the control rates of glycated hemoglobin, BP (SBP/DBP<140/90 mmHg), LDL-C, each, and all three risk factors together, accounted for 51.5%, 67.7%, 72.2%, and 24.4%, respectively. Conclusions Trends in risk factor control improved for glycated hemoglobin and LDL-C, but worsened for BP among diabetic adults in Singapore from 2013 to 2019. Control rates for all risk factors remain inadequate.

scholarly journals Dietary intake and prospective changes in cardiometabolic risk factors in children and youth

2017 ◽  
Vol 42 (1) ◽  
pp. 39-45 ◽  
Author(s):  
Solmaz Setayeshgar ◽  
John Paul Ekwaru ◽  
Katerina Maximova ◽  
Sumit R. Majumdar ◽  
Kate E. Storey ◽  
...  
Keyword(s):  
Risk Factors ◽  
Dietary Intake ◽  
Dietary Fat ◽  
Sodium Intake ◽  
Children And Youth ◽  
Excess Body Weight ◽  
Mixed Effect ◽  
Sensitivity Score ◽  
Effect Regression

Only few studies examined the effect of diet on prospective changes in cardiometabolic (CM) risk factors in children and youth despite its importance for understanding the role of diet early in life for cardiovascular disease in adulthood. To test the hypothesis that dietary intake is associated with prospective changes in CM risk factors, we analyzed longitudinal observations made over a period of 2 years among 448 students (aged 10–17 years) from 14 schools in Canada. We applied mixed effect regression to examine the associations of dietary intake at baseline with changes in body mass index, waist circumference (WC), systolic and diastolic blood pressure (SBP and DBP), and insulin sensitivity score between baseline and follow-up while adjusting for age, sex, and physical activity. Dietary fat at baseline was associated with increases in SBP and DBP z scores (per 10 g increase in dietary fat per day: β = 0.03; p < 0.05) and WC (β = 0.31 cm; p < 0.05) between baseline and follow-up. Every additional gram of sodium intake at baseline was associated with an increase in DBP z score of 0.04 (p < 0.05) between baseline and follow-up. Intake of sugar, vegetables and fruit, and fibre were not associated with changes in CM risk factors in a statistically significant manner. Our findings suggest that a reduction in the consumption of total dietary fat and sodium may contribute to the prevention of excess body weight and hypertension in children and youth, and their cardiometabolic sequelae later in life.

Abstract TP308: Transitional Care in Stroke Certified and Non-certified Hospitals: The Comprehensive Post-Acute Stroke Services (COMPASS) Study

Stroke ◽  
2017 ◽  
Vol 48 (suppl_1) ◽  
Author(s):  
Janet Prvu Bettger ◽  
Sara Jones ◽  
Anna Kucharska-Newton ◽  
Janet Freburger ◽  
Walter Ambrosius ◽  
...  
Keyword(s):  
Transitional Care ◽  
Discharge Planning ◽  
Care Transitions ◽  
Cluster Randomized Trial ◽  
Stroke Patients ◽  
Care Needs ◽  
Post Discharge ◽  
Exact Test ◽  
Chi Squared

Background: Greater than 50% of stroke patients are discharged home from the hospital, most with continuing care needs. In the absence of evidence-based transitional care interventions for stroke patients, procedures likely vary by hospital even among stroke-certified hospitals with requirements for transitional care protocols. We examined the standard of transitional care among NC hospitals enrolled in the COMPASS study comparing stroke-certified and non-certified hospitals. Methods: Hospitals completed an online, self-administered, web-based questionnaire to assess usual care related to hospitals’ transitional care strategy, stroke program structural components, discharge planning processes, and post-discharge patient management and follow-up. Response frequencies were compared between stroke certified versus non-certified hospitals using chi-squared statistics and Fisher’s exact test. Results: As of July 2016, the first 27 hospitals enrolled (of 40 expected) completed the survey (67% certified as a primary or comprehensive stroke center). On average, 54% of stroke patients were discharged home. Processes supporting hospital-to-home care transitions, such as timely follow-up calls and follow-up with neurology, were infrequent and overall less common for non-certified hospitals (Table). Assessment of post-discharge outcomes was particularly infrequent among non-certified sites (11%) compared with certified sites (56%). Uptake of transitional care management billing codes and quality metrics was low for both certified and non-certified hospitals. Conclusion: Significant variation exists in the infrastructure and processes supporting care transitions for stroke patients among COMPASS hospitals in NC. COMPASS as a pragmatic cluster-randomized trial will compare outcomes among hospitals that implement a CMS-directed model of transitional care with those hospitals that provide highly variable transitional care services.

Abstract 167: Correlation of 30-day Hospital Readmission Rates by Payer and Penalty Status

2017 ◽  
Vol 10 (suppl_3) ◽  
Author(s):  
Neel M Butala ◽  
Daniel B Kramer ◽  
Jordan B Strom ◽  
Kevin F Kennedy ◽  
Robert W Yeh
Keyword(s):  
Correlation Coefficients ◽  
Weighted Kappa ◽  
Hospital Performance ◽  
Teaching Hospitals ◽  
Kappa Statistics ◽  
Medicare Beneficiaries ◽  
Readmission Rates ◽  
Hospital Readmission Rates ◽  
Medicare Patients ◽  
Group B

Background: Readmission rates for heart failure (HF), acute myocardial infarction (MI), and pneumonia (PNA) hospitalizations among Medicare beneficiaries are used to assess hospital quality and determine global reimbursement. However, whether these measures reflect readmission rates for other conditions or insurance groups is unknown. Methods: All hospitals with >30 index admissions for HF, MI or pneumonia in 2013 in the all-payer Nationwide Readmissions Database (NRD) were included. For each hospital, we estimated 30-day all-cause risk-standardized readmission rates (RSRRs) for 3 groups: (A) Medicare beneficiaries admitted with HF/MI/PNA, (B) Medicare beneficiaries admitted for other conditions, and (C) non-Medicare beneficiaries admitted for HF/MI/PNA. Pair-wise correlations of these measures were assessed using Spearman correlation coefficients. Hospitals were divided into quartiles based on their calculated RSRR for each group, and inter-rater agreement between groups was assessed using weighted kappa statistics. We then examined pair-wise Spearman correlations among subgroups based on hospital characteristics (size, ownership status, and teaching status). Results: Among 1,228 hospitals, wide variation in RSRRs was seen across conditions and insurance type. Groups A vs. B had moderate correlation and agreement (Spearman 0.631, quartile weighted kappa 0.440). However, A vs. C had only modest correlation and fair agreement (Spearman 0.399, quartile weighted kappa 0.243). Compared with their quartile rank for the publicly reported group A, 46% of hospitals were ranked in the same quartile for group B and 35% for group C (Figure). Correlations between groups A vs. B and A vs. C were strongest among metro teaching hospitals (Spearman 0.674 and 0.507, respectively). Conclusions: Risk-standardized readmission rates for HF/MI/PNA are generalizable measures of a hospital’s readmission rate for other conditions among Medicare-insured patients. However, publicly reported RSRRs for HF/MI/PNA among Medicare patients are less suitable measures of hospital performance for non-Medicare patients admitted for these conditions.

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