MedicalResearch.com Interview with:
Hayley D. Germack PHD, MHS, RN
Assistant Professor, School of Nursing
University of Pittsburgh
MedicalResearch.com: What is the background for this study? What are the main findings?Response: As nurse scientists, we repeatedly witness the impact of having a serious mental illness (i.e. schizophrenia, bipolar disorder, and major depression disorder) on patients’ inpatient and discharge experience. As health services researchers, we know how to make use of large secondary data to illuminate our firsthand observations.
In 2016, Dr. Hanrahan and colleagues (https://www.sciencedirect.com/science/article/pii/S0163834316301347) published findings of a secondary data analysis from a large urban hospital system that found 1.5 to 2.4 greater odds of readmission for patients with an serious mental illness diagnosis compared to those without. We decided to make use of the AHRQ’s HCUP National Readmissions Database to illuminate the magnitude of this relationship using nationally representative data. We found that even after controlling for clinical, demographic, and hospital factors, that patients with SMI have nearly 2 times greater odds of 30-day readmission. (more…)
MedicalResearch.com Interview with:
Sunil Sharma MD, FAASM
Associate Professor of Medicine
Director, Pulmonary Sleep Medicine
Associate Director, Jefferson Sleep Disorders Center
Thomas Jefferson University and Hospitals
Philadelphia, PA 19107
Medical Research: What is the background for this study? Dr. Sharma: Congestive heart failure (CHF) is the most common cause of hospital admission and readmissions in United States. More health care dollars are spent on CHF than any other diagnosis. A large chunk of this cost is due to hospital admission. An estimated 50% of the CHF patients are readmitted within 6 months of discharge. The recent Protection Affordable Care Act (ACA) imposes penalties on hospitals for readmissions within first 30-days. It is therefore imperative to find ways to impact the natural history of the disease.
Sleep disordered breathing is a common disorder associated with CHF. It is estimated that up to 70% of the patient with CHF may have SDB. Studies have shown that untreated SDB can worsen CHF and treatment of Sleep disordered breathing has been shown to improve heart function (ejection fraction).(more…)
MedicalResearch.com Interview with:
Timothy M. Pawlik, MD, MPH, MTS, PhD, FACS, FRACS (Hon.)
Professor of Surgery and Oncology
John L. Cameron M.D. Professor of Alimentary Tract Diseases
Chief, Division of Surgical Oncology
Program Director, Surgical Oncology Fellowship
Director, Johns Hopkins Medicine Liver Tumor Center Multi-Disciplinary Clinic
Johns Hopkins Hospital Baltimore, MD 21287
MedicalResearch: What is the background for this study? What are the main findings?Dr. Pawlik: In 2012, the Centers for Medicare and Medicaid Services (CMS) introduced the Hospital Readmission Reduction Program (HRRP) whereby hospitals with higher than expected 30-day readmission incur financial penalties. Initially proposed to target readmissions following acute myocardial infarction, pneumonia and congestive heart failure, the program has since expanded to encompass knee and hip replacement surgery with the inclusion of additional surgical procedures anticipated in the near future. Although initial results from the Hospital Readmission Reduction Program have been promising, several concerns have been raised regarding potential limitations in methodological approach; specifically in the ability to adequately risk-adjust and account for variations in patient, provider and disease. As a consequence, many fear that the Hospital Readmission Reduction Program may disproportionately penalize safety-net hospitals as well as hospitals caring for “sicker” and more vulnerable populations.
In the current study we sought to investigate factors associated with the variability in 30-day readmission among a cohort of 22,559 patients discharged following a major surgical procedure at the Johns Hopkins Hospital between 2009 and 2013. Overall, 30-day readmission was noted to be 13.2% varying from 2.1% to 24.8% by surgical specialty / procedure and from 2.1% to 32.9% by surgeon. Non-modifiable patient specific factors such as preoperative comorbidity, insurance status and race / ethnicity, were found to be most predictive of 30-day readmission as well as postoperative factors such as complications and length of stay both of which may also be influenced by preoperative comorbidity. Overall, we noted that 2.8% of the variation in 30-day readmission was attributed to provider-specific factors, 14.5% of the variability was due differences in surgical specialty / procedure while over 84% of the variability in 30-day readmission remained unaccounted for due to non-modifiable patient-specific factors.
(more…)
MedicalResearch.com Interview with:
Jordan M. Cloyd, MD
Department of Surgery
Stanford University
Stanford, California
Medical Research: What is the background for this study? What are the main findings?
Dr. Cloyd: The motivation for the study was that, anecdotally, we had noticed that several of our patients who had been discharged on a weekend required readmission for potentially preventable reasons. We wanted to investigate whether the data supported the idea that weekend discharge was associated with a higher risk of hospital readmission.
(more…)
MedicalResearch.com Interview with:
Jeffrey C. Schneider, M.D.
Medical Director, Trauma, Burn & Orthopedic Program
Assistant Professor, Dept. of Physical Medicine and Rehabilitation
Harvard Medical School
Spaulding Rehabilitation Hospital
Boston, MA 02129
Medical Research: What is the background for this study? What are the main findings?
Response: Hospitalizations account for the largest share of healthcare costs in the U.S., comprising nearly one-third of all healthcare expenditures. In 2011, readmissions within 30 days of hospital discharge represented more than $41 billion in hospital costs. Financial penalties for excess 30-day hospital readmissions were instituted by the Centers for Medicare and Medicaid Services in 20124; more than 2,200 hospitals were fined a total of $280 million in reduced Medicare payments in fiscal year 2013.
Most readmission risk prediction models have targeted specific medical diagnoses and have utilized comorbidities and demographic data as the central risk factors for hospital readmission. Yet, large U.S. administrative datasets have demonstrated poor discriminative ability (c-statistics: 0.55-0.65) in predicting readmissions. However, few studies have considered functional status as potential readmission risk factors.
There is increasing evidence that functional status is a good predictor of other health outcomes. To date, acute care hospital administrative databases do not routinely include functional status measures. Therefore, inpatient rehabilitation setting is an ideal population in which to examine the impact of functional status on readmission risk, because:
(1) inpatient rehabilitation patients often have complex care transitions after acute care discharge, and represent a significant proportion of total readmissions;
2) inpatient rehabilitation facilities routinely document functional status using a valid instrument—the FIM®; and
(3) a majority of U.S. IRFs participate in one of the only national datasets that contain standardized functional data—the Uniform Data System for Medical Rehabilitation.
Limitations of prior work include small and single-center study designs, narrowly defined patient populations, and defining readmissions beyond the 30-day period. Overall, there is a lack of literature on the utility of function as a readmission predictor in a large population of medical patients. Moreover, function is a modifiable risk factor with potential to impact readmission outcomes if function-based interventions are instituted early. Therefore, the objective of this study was to compare functional status with medical comorbidities as predictors of acute care readmissions in the medically complex rehabilitation population. We hypothesized that acute care readmission prediction models based on functional status would outperform models based on comorbidities,and that the addition of comorbidity variables to function-based models would not significantly enhance predictive performance.
(more…)
MedicalResearch.com Interview with:
Kumar Dharmarajan MD MBA
Section of Cardiovascular Medicine
Yale University School of Medicine, New Haven, CT 06510
Medical Research: What is the background for this study? What are the main findings?
Dr. Dharmarajan: We know that patients are at high risk for rehospitalization and death in the month after hospital discharge. Yet little is known about how these risks dynamically change over time for the full year after hospitalization. This information is needed for patients and hospitals to set realistic goals and plan for appropriate care.
We found that the risk of rehospitalization and death decline slowly following hospitalization and remain elevated for many months. We also found that specific risk trajectories vary by discharge diagnosis and outcome. For example, risk remains elevated for a longer period of time following hospitalization for heart failure compared with hospitalization for acute myocardial infarction. For all 3 conditions we studied (heart failure, heart attacks, and pneumonia), risk of rehospitalization remained elevated for a longer period of time than the risk of death.
(more…)
MedicalResearch.com Interview with:
Mark Brittan MD MPH
Assistant Professor, Pediatric Hospital Medicine
Children's Hospital Colorado
University of Colorado School of Medicine
MedicalResearch:What is the background for this study? What are the main findings?Dr. Brittan: As hospitals face reimbursement penalties for excess readmissions, clinicians are increasingly focused on improving care transitions in order to reduce readmissions. We are interested in learning about feasible ways to reduce pediatric readmissions so that we can improve the quality of care and experience of children and families who are being discharged from the hospital. The purpose of this study was to assess whether outpatient follow-up visits after hospital discharge can help to prevent readmissions. We chose to examine this question in a population of medically complex children enrolled in Medicaid. Children with medical complexity account for a growing proportion of pediatric hospitalizations and inpatient costs. These children are often dependent on technology (for example, ventilator machines, feeding tubes, and chronic indwelling catheters), and can have very complex care plans and medication regimens. Publically insured children are also vulnerable to increased hospital utilization and may not always have optimal or easy access to outpatient services. Showing a relationship between post-discharge outpatient visits and fewer readmissions would suggest that improvements in coordination of care or access to outpatient follow-up care may help to reduce readmissions in these children. To assess this relationship, we retrospectively analyzed 2006-2008 Colorado Medicaid claims data from which we were able to gather demographic, clinical, and visit information for all enrollees.
In our study, we excluded children who were readmitted within 3 days of hospital discharge so that we could evaluate children who had a chance to follow-up. The study cohort included 2415 medically complex children aged 6 months to 18 years who were hospitalized at least once. Of these children, 6.3% were readmitted on days 4 – 30 after hospital discharge. Almost 22% of the children had an outpatient follow-up visit within 3 days of discharge, and 40% had a visit on days 4-29 after discharge. In the final analysis, we found expected associations between readmission and previously described risk factors, including number of patient comorbidities and longer initial hospital length of stay. Examining the relationship between outpatient follow-up and readmission, we found that children with later outpatient follow-up visits (days 4-29) were significantly less likely to be readmitted than those who did not have an outpatient visit on days 4-29 after discharge.
(more…)
MedicalResearch.com Interview with:
Greg D. Sacks, MD, MPH
Department of Surgery, David Geffen School of Medicine at UCLAMedicalResearch: What are the main findings of this study?
Dr. Sacks: This study evaluated the all-cause readmissions measure developed by the Centers for Medicare and Medicaid Services to penalize hospitals for unplanned readmissions. By evaluating readmissions of surgical patients at a single academic medical center, we found that the readmissions measure was able to identify only a third of the planned readmissions and mislabeled the remaining two thirds of planned readmissions as unplanned. This discrepancy was a result of the measure’s reliance on administrative claims data, which disagreed in 31% of cases with clinical data abstracted from the patient’s chart. Also, almost a third (27%) of the readmissions in this study were for reasons unrelated to the original hospitalization.
(more…)
MedicalResearch.com Interview with: Cindy Feltner, MD, MPH
Assistant Professor, Division of General Medicine
University of North Carolina--Chapel Hill
RTI- UNC Evidence-based Practice Center
MedicalResearch: What are the main findings of the study?Dr. Feltner:We conducted a systematic review and meta-analysis to assess the efficacy, comparative effectiveness, and harms of transitional care interventions to reduce readmission and mortality rates for adults hospitalized with heart failure. We included a broad range of intervention types applicable to adults transitioning from hospital to home that aimed to prevent readmissions. Although 30-day readmissions are the focus of quality measures, we also included readmissions measured over 3 to 6 months because these are common, costly, and potentially preventable. Forty-seven trials were included, most enrolled adults with moderate to severe heart failure and a mean age of 70 years. We found that interventions providing multiple home visits soon after hospital discharge can reduce 30-day readmission rates. Both home-visiting programs and multidisciplinary heart failure clinics visits can improve mortality and reduce all-cause readmission in the six months after hospitalization. Telephone support interventions do not appear to reduce all-cause readmission, but can improve survival and reduce readmission related to heart failure. Programs focused on telemonitoring or providing education only did not appear to reduce readmission or improve survival.
(more…)
MedicalResearch.com Interview with:
Alex Blum, MD MPH FAAP
Chief Medical Officer
Evergreen Health, Baltimore MD 21211
MedicalResearch.com: What are the main findings of the study?Dr. Blum:Accounting for the social risk of patients using a measure of neighborhood socioeconomic status (SES), did not alter the hospital rankings for congestive heart failure (CHF) readmission rates. (more…)
MedicalResearch.com Interview with:Dr. Takatoshi Kasai, MD, PhD
Department of Cardiology and Cardio-Respiratory Sleep Medicine,
Juntendo University School of Medicine, Tokyo, Japan
MedicalResearch.com: What are the main findings of the study?
Dr. Kasai: Sleep disordered breathing, determined using predischarge nocturnal pulse oximetry, is prevalent and is an independent predictor of the combined end point of readmission and mortality in hospitalized patients with left ventricular systolic dysfunction after acute decompensated heart failure.
(more…)
MedicalResearch.com Interview with: Allan Garland, MD, MA
Co-Head, Section of Critical Care Medicine
Associate Professor of Medicine and Community Health Sciences
University of Maniitoba
820 Sherbrook St / GF-222
Winnipeg, Manitoba R3A 1R9
MedicalResearch.com: What are the main findings of the study?Answer: Our study evaluated consequences of leaving the hospital against medical advice (AMA). It is a large, population-based analysis, that evaluated all hospitalizations from which patients were discharged alive, among all adults in the Canadian province of Manitoba over a 19 year period; this was over 1.9 million hospitalizations. Outcomes assessed were hospital readmission and death over 6 months after the event. Specifically, we compared these outcomes for those who left the hospital against medical advice, compared to those who remained in the hospital until their doctors felt it was safe to be discharged -- and these comparisons adjusted for a variety of patient and illness characteristics.
Among the 1.9 million hospitalizations, there were 21,417 that ended with the patients leaving against medical advice, this is 1.1% of the total. Without adjustment for other variables, leaving against medical advice was associated with double the rate of unscheduled hospital readmission within 30 days (24.0 vs. 12.1%); after adjustment, the odds of unscheduled hospital readmission within 30 days was 3-fold higher for someone who left against medical advice compared to one who did not. After adjustment, the odds of death at 90 days were 2.51-fold higher for those who left against medical advice.
(more…)
MedicalResearch.com Interview with: Dr. Finlay McAlister
Division of General Internal Medicine
Patient Health Outcomes Research and Clinical Effectiveness Unit
University of Ottawa, Ottawa Hospital Research Institute, Ottawa, Ont.
MedicalResearch.com: What are the main findings of the study?Answer: Heart Failure carries a high risk of readmission/death in the first 30 days after hospital discharge (approximately 20%) - even in this cohort of patients with first time diagnosis of heart failure who were discharged home to the community. Patients who do not have an outpatient physician follow-up visit in the first 30 days after discharge have poorer outcomes at 30 days, 3 months, 6 months, and 12 months. Although outcomes are similar for patients who see an unfamiliar or a familiar physician in that first 30 days, over the longer term follow-up with a familiar physician is associated with better outcomes than follow-up with unfamiliar physician(s).
(more…)
This website uses cookies to improve your experience. We'll assume you're ok with this, but you can opt-out if you wish.AcceptRejectRead More
Privacy & Cookies Policy
Privacy Overview
This website uses cookies to improve your experience while you navigate through the website. Out of these cookies, the cookies that are categorized as necessary are stored on your browser as they are as essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may have an effect on your browsing experience.
Necessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensures basic functionalities and security features of the website. These cookies do not store any personal information.