Using hospital readmission rates to track the quality of care in public hospitals in Singapore

Background: Readmissions after acute hospitalizations are a cause of both risk and expense, and many of them are potentially preventable. Importantly, risk-standardized hospital readmission rates are sometimes used as a yardstick of the quality of care offered. However, racial variability in readmissions might involve factors beyond quality of care and has not been studied extensively. Objective: To identify differences in readmissions between African Americans and other races and determine preventable readmissions from a pragmatic viewpoint. Methods: We obtained deidentified data from Medical University of South Carolina (MUSC) Electronic Data Warehouse (EDW) on adult admissions with index diagnosis considered as an ischemic stroke (or closely related) using International Classification of Diseases, Ninth Revision (ICD-9) codes 433.x, 434.x, 436.x, 437.x between January 2011 and June 2014. Of these, we determined readmission and reason for readmission over 90-day period. Readmission can be hospital or emergency room readmission. We obtained race as the only linked demographic. Results: Of the 1953 patients admitted with index diagnoses of stroke, 765 (39%), 1148 (59%) and 50 (1%) were African Americans, Caucasians and others, respectively. At 90-days, 256 patients were readmitted as in-patient, of which 128 (50%), 126 (49%) and 2 (1%) were African Americans, Caucasians and others, respectively. On the other hand, 241 patients visited Emergency Room, of which 175 (73%), 65 (26%) and 1 (1%) were African Americans, Caucasians and others, respectively. On adjusting readmissions to index admissions, 17%, 11% and 4% of African Americans, Caucasians and others, respectively, were readmitted in hospital, while 23%, 6% and 2% of African Americans, Caucasians and others, respectively, visited Emergency Room over 90-days period. Conclusions: 90-days readmission rates involve African Americans in a disproportionate manner. This demands further investigation on the etiology of readmission and the care offered.

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Integrating the Principles of Evidence Based Medicine and Evidence Based Public Health: Impact on the Quality of Patient Care and Hospital Readmission Rates in Jordan

International Journal of Integrated Care ◽

10.5334/ijic.2436 ◽

2016 ◽

Vol 16 (3) ◽

pp. 12 ◽

Cited By ~ 2

Author(s):

Mohammad S. Alyahya ◽

Heba H. Hijazi ◽

Hussam A. Alshraideh ◽

Mohammad Aser Alsharman ◽

Rabah Al Abdi ◽

...

Keyword(s):

Public Health ◽

Evidence Based Medicine ◽

Hospital Readmission ◽

Health Impact ◽

Evidence Based ◽

Readmission Rates ◽

Hospital Readmission Rates ◽

Quality Of Patient Care ◽

Based Medicine

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Multi-level models for heart failure patients’ 30-day mortality and readmission rates: the relation between patient and hospital factors in administrative data

BMC Health Services Research ◽

10.1186/s12913-019-4818-2 ◽

2019 ◽

Vol 19 (1) ◽

Cited By ~ 1

Author(s):

Afsaneh Roshanghalb ◽

Cristina Mazzali ◽

Emanuele Lettieri

Keyword(s):

Heart Failure ◽

Quality Of Care ◽

Public Hospitals ◽

Unplanned Readmission ◽

Hospital Level ◽

Readmission Rates ◽

Heart Failure Patients ◽

Multi Level ◽

Hospital Factors

Abstract Background This study aims at gathering evidence about the relation between 30-day mortality and 30-day unplanned readmission and patient and hospital factors. By definition, we refer to 30-day mortality and 30-day unplanned readmission as the number of deaths and non-programmed hospitalizations for any cause within 30 days after the incident heart failure (HF). In particular, the focus is on the role played by hospital-level factors. Methods A multi-level logistic model that combines patient- and hospital-level covariates has been developed to better disentangle the role played by the two groups of covariates. Later on, hospital outliers in term of better-than-expected/worst-than-expected performers have been identified by comparing expected cases vs. observed cases. Hospitals performance in terms of 30-day mortality and 30-day unplanned readmission rates have been visualized through the creation of funnel plots. Covariates have been selected coherently to past literature. Data comes from the hospital discharge forms for Heart Failure patients in the Lombardy Region (Northern Italy). Considering incident cases for HF in the timespan 2010–2012, 78,907 records for adult patients from 117 hospitals have been collected after quality checks. Results Our results show that 30-day mortality and 30-day unplanned readmissions are explained by hospital-level covariates, paving the way for the design and implementation of evidence-based improvement strategies. While the percentage of surgical DRG (OR = 1.001; CI (1.000–1.002)) and the hospital type of structure (Research hospitals vs. non-research public hospitals (OR = 0.62; CI (0.48–0.80)) and Non-research private hospitals vs. non-research hospitals OR = 0.75; CI (0.63–0.90)) are significant for mortality, the mean length of stay (OR = 0.96; CI (0.95–0.98)) is significant for unplanned readmission, showing that mortality and readmission rates might be improved through different strategies. Conclusion Our results confirm that hospital-level covariates do affect quality of care, and that 30-day mortality and 30-day unplanned readmission are affected by different managerial choices. This confirms that hospitals should be accountable for their “added value” to quality of care.

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Predictors of hospital admission and mortality in patients with chronic obstructive pulmonary disease

Reviews in Clinical Gerontology ◽

10.1017/s0959259801011194 ◽

2001 ◽

Vol 11 (1) ◽

pp. 99-106 ◽

Cited By ~ 3

Author(s):

AM Yohannes ◽

MJ Connolly

Keyword(s):

Chronic Obstructive Pulmonary Disease ◽

Pulmonary Disease ◽

Hospital Readmission ◽

Chronic Obstructive ◽

Readmission Rates ◽

Obstructive Pulmonary Disease ◽

Hospital Readmission Rates ◽

Copd Patients ◽

Impaired Quality

Hospital readmission rates for COPD patients are high, with two-week readmission rates of 22% being recorded in one study of patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD). In a separate study, patients admitted with PaCO2> 50 mm Hg had a readmission rate of 40% at six months. There are no agreed clinical evidence factors that determine readmission. A few studies have reported that readmission is associated with an individual’s inability to cope with the disease, and that anxiety and socioeconomic status are important variables. Others argue that readmission relates to severity of lung function abnormality, changes in atmospheric pollution, and impaired quality of life (QoL).

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Care Strategies for Reducing Hospital Readmissions Using Stochastic Programming

Healthcare ◽

10.3390/healthcare9080940 ◽

2021 ◽

Vol 9 (8) ◽

pp. 940

Author(s):

Behshad Lahijanian ◽

Michelle Alvarado

Keyword(s):

Quality Of Care ◽

Stochastic Programming ◽

Hospital Readmission ◽

Programming Model ◽

Hospital Readmissions ◽

Cost Of Care ◽

Probabilistic Constraints ◽

Expected Improvement ◽

Readmission Rates

A hospital readmission occurs when a patient has an unplanned admission to a hospital within a specific time period of discharge from an earlier or initial hospital stay. Preventable readmissions have turned into a critical challenge for the healthcare system globally, and hospitals seek care strategies that reduce the readmission burden. Some countries have developed hospital readmission reduction policies, and in some cases, these policies impose financial penalties for hospitals with high readmission rates. Decision models are needed to help hospitals identify care strategies that avoid financial penalties, yet maintain balance among quality of care, the cost of care, and the hospital’s readmission reduction goals. We develop a multi-condition care strategy model to help hospitals prioritize treatment plans and allocate resources. The stochastic programming model has probabilistic constraints to control the expected readmission probability for a set of patients. The model determines which care strategies will be the most cost-effective and the extent to which resources should be allocated to those initiatives to reach the desired readmission reduction targets and maintain high quality of care. A sensitivity analysis was conducted to explore the value of the model for low- and high-performing hospitals and multiple health conditions. Model outputs are valuable to hospitals as they examine the expected cost of hitting its target and the expected improvement to its readmission rates.

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Quality of surgical care and readmission in elderly glioblastoma patients

Neuro-Oncology Practice ◽

10.1093/nop/npu008 ◽

2014 ◽

Vol 1 (2) ◽

pp. 33-39 ◽

Cited By ~ 3

Author(s):

Miriam Nuño ◽

Diana Ly ◽

Debraj Mukherjee ◽

Alicia Ortega ◽

Keith L. Black ◽

...

Keyword(s):

Quality Of Care ◽

Surgical Care ◽

Patient Characteristics ◽

Readmission Rates ◽

Vein Thrombosis ◽

Complex Interactions ◽

Hospital Readmission Rates ◽

Medicare Database ◽

Deep Vein

Abstract Background Thirty-day readmissions post medical or surgical discharge have been analyzed extensively. Studies have shown that complex interactions of multiple factors are responsible for these hospitalizations. Methods A retrospective analysis was conducted using the Surveillance, Epidemiology and End Results (SEER) Medicare database of newly diagnosed elderly glioblastoma multiforme (GBM) patients who underwent surgical resection between 1991 and 2007. Hospitals were classified into high- or low-readmission rate cohorts using a risk-adjusted methodology. Bivariate comparisons of outcomes were conducted. Multivariate analysis evaluated differences in quality of care according to hospital readmission rates. Results A total of 1,273 patients underwent surgery in 338 hospitals; 523 patients were treated in 228 high-readmission hospitals and 750 in 110 low-readmission hospitals. Patient characteristics for high-versus low-readmission hospitals were compared. In a confounder-adjusted model, patients treated in high- versus low-readmission hospitals had similar outcomes. The hazard of mortality for patients treated at high- compared to low-readmission hospitals was 1.06 (95% CI, 0.095%–1.19%). While overall complications were comparable between high- and low-readmission hospitals (16.3% vs 14.3%; P = .33), more postoperative pulmonary embolism/deep vein thrombosis complications were documented in patients treated at high-readmission hospitals (7.5% vs 4.1%; P = .01). Adverse events and levels of resection achieved during surgery were comparable at high- and low-readmission hospitals. Conclusions For patients undergoing GBM resection, quality of care provided by hospitals with the highest adjusted readmission rates was similar to the care delivered by hospitals with the lowest rates. These findings provide evidence against the preconceived notion that 30-day readmissions can be used as a metric for quality of surgical and postsurgical care.

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Effective coverage and budget implications of skill-mix change to improve neonatal nursing care: an explorative simulation study in Kenya

BMJ Global Health ◽

10.1136/bmjgh-2019-001817 ◽

2019 ◽

Vol 4 (6) ◽

pp. e001817 ◽

Cited By ~ 2

Author(s):

Apostolos Tsiachristas ◽

David Gathara ◽

Jalemba Aluvaala ◽

Timothy Chege ◽

Edwine Barasa ◽

...

Keyword(s):

Quality Of Care ◽

Neonatal Mortality ◽

Nursing Care ◽

Public Hospitals ◽

Sensitivity Analyses ◽

Full Time ◽

Skill Mix ◽

Neonatal Nursing ◽

Low Middle Income Countries

IntroductionNeonatal mortality is an urgent policy priority to improve global population health and reduce health inequality. As health systems in Kenya and elsewhere seek to tackle increased neonatal mortality by improving the quality of care, one option is to train and employ neonatal healthcare assistants (NHCAs) to support professional nurses by taking up low-skill tasks.MethodsMonte-Carlo simulation was performed to estimate the potential impact of introducing NHCAs in neonatal nursing care in four public hospitals in Nairobi on effectively treated newborns and staff costs over a period of 10 years. The simulation was informed by data from 3 workshops with >10 stakeholders each, hospital records and scientific literature. Two univariate sensitivity analyses were performed to further address uncertainty.ResultsStakeholders perceived that 49% of a nurse full-time equivalent could be safely delegated to NHCAs in standard care, 31% in intermediate care and 20% in intensive care. A skill-mix with nurses and NHCAs would require ~2.6 billionKenyan Shillings (KES) (US$26 million) to provide quality care to 58% of all newborns in need (ie, current level of coverage in Nairobi) over a period of 10 years. This skill-mix configuration would require ~6 billion KES (US$61 million) to provide quality of care to almost all newborns in need over 10 years.ConclusionChanging skill-mix in hospital care by introducing NHCAs may be an affordable way to reduce neonatal mortality in low/middle-income countries. This option should be considered in ongoing policy discussions and supported by further evidence.

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