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1.  Readmissions after Hospitalization for Heart Failure, Acute Myocardial Infarction, or Pneumonia among Young and Middle-Aged Adults: A Retrospective Observational Cohort Study 
PLoS Medicine  2014;11(9):e1001737.
Isuru Ranasinghe and colleagues compare readmissions after hospitalization for heart failure, acute myocardial infarction, or pneumonia in adults aged 18 to 64 years with readmissions in those aged 65 and older.
Please see later in the article for the Editors' Summary
Patients aged ≥65 years are vulnerable to readmissions due to a transient period of generalized risk after hospitalization. However, whether young and middle-aged adults share a similar risk pattern is uncertain. We compared the rate, timing, and readmission diagnoses following hospitalization for heart failure (HF), acute myocardial infarction (AMI), and pneumonia among patients aged 18–64 years with patients aged ≥65 years.
Methods and Findings
We used an all-payer administrative dataset from California consisting of all hospitalizations for HF (n = 206,141), AMI (n = 107,256), and pneumonia (n = 199,620) from 2007–2009. The primary outcomes were unplanned 30-day readmission rate, timing of readmission, and readmission diagnoses. Our findings show that the readmission rate among patients aged 18–64 years exceeded the readmission rate in patients aged ≥65 years in the HF cohort (23.4% vs. 22.0%, p<0.001), but was lower in the AMI (11.2% vs. 17.5%, p<0.001) and pneumonia (14.4% vs. 17.3%, p<0.001) cohorts. When adjusted for sex, race, comorbidities, and payer status, the 30-day readmission risk in patients aged 18–64 years was similar to patients ≥65 years in the HF (HR 0.99; 95%CI 0.97–1.02) and pneumonia (HR 0.97; 95%CI 0.94–1.01) cohorts and was marginally lower in the AMI cohort (HR 0.92; 95%CI 0.87–0.96). For all cohorts, the timing of readmission was similar; readmission risks were highest between days 2 and 5 and declined thereafter across all age groups. Diagnoses other than the index admission diagnosis accounted for a substantial proportion of readmissions among age groups <65 years; a non-cardiac diagnosis represented 39–44% of readmissions in the HF cohort and 37–45% of readmissions in the AMI cohort, while a non-pulmonary diagnosis represented 61–64% of patients in the pneumonia cohort.
When adjusted for differences in patient characteristics, young and middle-aged adults have 30-day readmission rates that are similar to elderly patients for HF, AMI, and pneumonia. A generalized risk after hospitalization is present regardless of age.
Please see later in the article for the Editors' Summary
Editors' Summary
Many elderly people who are admitted to hospital, successfully treated, and discharged are readmitted soon after, often for an unrelated illness. In the US, for example, nearly a fifth of Medicare beneficiaries are readmitted to hospital within 30 days of discharge (Medicare is a national insurance program that primarily pays for health care services for Americans aged 65 and older). Experts have recently coined the term “post-hospital syndrome” for the transient period of increased susceptibility to a range of adverse health events that elderly patients seem to experience and have suggested that exposure to stress during hospital stays may underlie the syndrome. For example, hospital patients frequently have their sleep disrupted because of hospital routines, they are often in pain, they may have insufficient food intake (sometimes because they are waiting for an operation), and they may lose physical conditioning because they are confined to bed. These and other stressors can reduce individuals' natural reserves and increase their vulnerability to a range of illnesses and conditions.
Why Was This Study Done?
Although stress is one possible determinant of the post-hospital syndrome, the underlying causes and patterns of hospital readmission are generally poorly understood. In particular, it is not known whether the post-hospital syndrome affects young and middle-aged patients as well as elderly patients. Importantly, a better understanding of the post-hospital syndrome is needed before effective strategies to reduce hospital readmissions can be developed. In this retrospective observational cohort study, the researchers compare readmission rates, timing, and diagnoses after hospitalization for heart failure (HF), acute myocardial infarction (AMI; heart attack), and pneumonia among patients aged 18–64 years living in California with readmission rates, timing, and diagnoses among patients aged 65 years or older hospitalized for the same conditions. A retrospective observational cohort study analyzes data that has been already been collected for a group (cohort) of people. Readmission is common among people of all ages who are admitted to hospital for HF, AMI, and pneumonia, and readmissions after hospitalization for these conditions among elderly Medicare patients are used in the US as a measure of hospital quality; hospitals with high readmission rates are subject to a Medicare reimbursement penalty.
What Did the Researchers Do and Find?
The researchers used the Healthcare Cost and Utilization Project inpatient dataset for California to identify all the hospitalizations for HF, AMI, and pneumonia in California in 2007–2009 and to obtain data on the 30-day unplanned rehospitalization rate, timing of readmission, and readmission diagnoses for the identified patients (more than half a million patients). Nearly 30% of all hospital readmissions after hospitalization for HF, AMI, and pneumonia in California occurred among patients aged 18–64. After hospitalization for AMI, pneumonia, and HF, 11.2%, 14.4%, and 23.4%, respectively, of young and middle-aged patients were readmitted. Notably, the 30-day readmission rate among patients aged 18–64 admitted for HF exceeded the readmission rate among elderly patients admitted for the same condition. After allowing for other factors likely to affect the risk of readmission such as other illnesses, the 30-day readmission risk in patients aged 18–64 was similar to that in patients aged 65 years or older admitted for HF and pneumonia and only marginally lower among patients admitted for AMI. Finally, the timing of readmission was similar in both age groups and diagnoses other than the index admission diagnosis accounted for a substantial proportion of readmissions in both age groups.
What Do These Findings Mean?
This study shows that after adjusting for differences in patient characteristics, the 30-day hospital readmission rates among young and middle-aged patients after hospitalization for HF, AMI, and pneumonia were similar to those among elderly patients. Moreover, the timing of readmission and the reasons for readmission among young and middle-aged patients were similar to those among elderly patients. These findings may not apply to other US states or to other countries and may not reflect the pattern of hospital readmissions following conditions other than HF, AMI, and pneumonia. Nevertheless, these findings suggest that the post-hospital syndrome affects young and middle-aged as well as elderly patients. Hospital readmission should therefore be considered as a potential problem for people of all ages and broad-based, multidisciplinary strategies that target patients of all ages should be developed to mitigate the risk of hospital readmissions.
Additional Information
Please access these websites via the online version of this summary at
The Institute for Healthcare Improvement provides information about reducing avoidable hospital readmissions
Information about the US Centers for Medicare & Medicaid Services readmissions reduction program is available
An article written by one of the study authors about the post-hospital syndrome is available
PMCID: PMC4181962  PMID: 25268126
2.  Readmission Rates of Patients Discharged against Medical Advice: A Matched Cohort Study 
PLoS ONE  2011;6(9):e24459.
We compared the readmission rates and the pattern of readmission among patients discharged against medical advice (AMA) to control patients discharged with approval over a one-year follow-up period.
A retrospective matched-cohort study of 656 patients(328 were discharged AMA) who were followed for one year after their initial hospitalization at an urban university-affiliated teaching hospital in Vancouver, Canada that serves a population with high prevalence of addiction and psychiatric disorders. Multivariate conditional logistic regression was used to examine the independent association of discharge AMA on 14-day related diagnosis hospital readmission. We fit a multivariate conditional negative binomial regression model to examine the readmission frequency ratio between the AMA and non-AMA group.
Principal Findings
AMA patients were more likely to be homeless (32.3% vs. 11%) and have co-morbid conditions such as psychiatric illnesses, injection drug use, HIV, hepatitis C and previous gastrointestinal bleeding. Patients discharged AMA were more likely to be readmitted: 25.6% vs. 3.4%, p<0.001 by day 14. The AMA group were more likely to be readmitted within 14 days with a related diagnosis than the non-AMA group (Adjusted Odds Ratio 12.0; 95% Confidence Interval [CI]: 3.7–38.9). Patients who left AMA were more likely to be readmitted multiple times at one year compared to the non-AMA group (adjusted frequency ratio 1.6; 95% CI: 1.3–2.0). There was also higher all-cause in-hospital mortality during the 12-month follow-up in the AMA group compared to non-AMA group (6.7% vs. 2.4%, p = 0.01).
Patients discharged AMA were more likely to be homeless and have multiple co-morbid conditions. At one year follow-up, the AMA group had higher readmission rates, were predisposed to multiple readmissions and had a higher in-hospital mortality. Interventions to reduce discharges AMA in high-risk groups need to be developed and tested.
PMCID: PMC3169593  PMID: 21931723
3.  Diagnoses and Timing of 30-Day Readmissions after Hospitalization For Heart Failure, Acute Myocardial Infarction, or Pneumonia 
To better guide strategies intended to reduce high rates of 30-day readmission after hospitalization for heart failure, acute myocardial infarction, or pneumonia, further information is needed about readmission diagnoses, readmission timing, and the relationship of both to patient age, sex, and race.
To examine readmission diagnoses and timing among Medicare beneficiaries readmitted within 30 days after hospitalization for heart failure, acute myocardial infarction, or pneumonia.
Design, Setting, and Patients
We analyzed 2007 to 2009 Medicare Fee-For-Service claims data to identify patterns of 30-day readmission by patient demographic characteristics and time after hospitalization for heart failure, acute myocardial infarction, or pneumonia. Readmission diagnoses were categorized using an aggregated version of the Centers for Medicare & Medicaid Services’ Condition Categories. Readmission timing was determined by day after discharge.
Main Outcomes Measures
We examined (1) the percentage of 30-day readmissions occurring on each day (0–30) after discharge; (2) the most common readmission diagnoses occurring during cumulative time periods (days 0–3, 0–7, 0–15, and 0–30) and consecutive time periods (days 0–3, 4–7, 8–15, and 16–30) after hospitalization; (3) median time to readmission for common readmission diagnoses; and (4) the relationship between patient demographic characteristics and readmission diagnoses and timing.
From 2007 to 2009, we identified 329,308 30-day readmissions after 1,330,157 heart failure hospitalizations (24.8% readmitted), 108,992 30-day readmissions after 548,834 acute myocardial infarction hospitalizations (19.9% readmitted), and 214,239 30-day readmissions after 1,168,624 pneumonia hospitalizations (18.3% readmitted). The proportion of patients readmitted for the same condition was 35.2% after index heart failure hospitalization, 10.0% after index acute myocardial infarction hospitalization, and 22.4% after index pneumonia hospitalization. Of all readmissions within 30 days, 61.0%, 67.6%, and 62.6% occurred with 15 days of discharge after hospitalization for heart failure, acute myocardial infarction, or pneumonia, respectively. The diverse spectrum of readmission diagnoses was largely similar in both cumulative (days 0–3, 0–7, 0–15, and 0–30) and consecutive (days 0–3, 4–7, 8–15, and 16–30) time periods after discharge. Median time to 30-day readmission was 12 days, 10 days, and 12 days for patients initially hospitalized with heart failure, acute myocardial infarction, or pneumonia, respectively, and was comparable across common readmission diagnoses. Neither readmission diagnoses nor timing substantively varied by age, sex, or race.
Among Medicare Fee-for-Service beneficiaries hospitalized for heart failure, acute myocardial infarction, or pneumonia, 30-day readmissions are frequent throughout the month following hospitalization and result from a similar spectrum of readmission diagnoses regardless of age, sex, race, or time after discharge.
PMCID: PMC3688083  PMID: 23340637
4.  What happens to patients who leave hospital against medical advice? 
Patients who leave hospital against medical advice (AMA) may be at risk of adverse health outcomes and readmission. In this study we examined rates of readmission and predictors of readmission among patients leaving hospital AMA.
We prospectively studied 97 consecutive patients who left the general medicine service of an urban teaching hospital AMA. Each patient was matched according to age, sex and primary diagnosis with a control patient who was discharged routinely. Readmission rates were examined using Kaplan–Meier analysis. Regression models were used to test the hypothesis that readmissions among patients discharged AMA followed a biphasic curve.
Patients who left AMA were much more likely than the control patients to be readmitted within 15 days (21% v. 3%, p < 0.001). Readmissions occurred at an accelerated pace during the first 15 days, followed by a 75-day period during which readmissions occurred at a rate comparable to that among the control patients. Among the patients who left AMA, being male and having a history of alcohol abuse were significant predictors of readmission within 15 days; however, these characteristics were common among the patients who left AMA. In the Cox proportional hazard models, leaving AMA was the only significant predictor of readmission (adjusted hazard ratio 2.5, 95% confidence interval 1.4–4.4).
The significantly increased risk of readmission among general medicine patients who leave hospital AMA is concentrated in the first 2 weeks after discharge. However, it is difficult to identify which patients will likely be readmitted.
PMCID: PMC143546  PMID: 12591781
5.  Predictors of 30 Day Readmission after Intracerebral Hemorrhage: A single-center approach for identifying potentially modifiable associations with readmission 
Critical care medicine  2013;41(12):10.1097/CCM.0b013e318298a10f.
To determine if patient demographics or severity of illness predict hospital readmission within 30 days following spontaneous intracerebral hemorrhage (ICH), to identify readmission associations that may be modifiable at the single center level, and to determine the impact of readmission on outcomes.
We collected demographic, clinical, and hospital course data for consecutive patients with spontaneous ICH enrolled in an observational study. Readmission within 30 days was determined retrospectively by an automated query with manual confirmation. We identified the reason for readmission and tested for associations between readmission and functional outcomes using modified Rankin Scale (mRS, a validated functional outcome measure from 0, no symptoms to 6, death) scores before ICH and at 14 days, 28 days, and three months after ICH.
Neurologic intensive care unit of a tertiary care hospital.
Critically ill patients with spontaneous ICH.
Patients received standard critical care management for ICH.
Measurements and Main Results
Of 246 patients (mean age 65 years, 51% female), 193 (78%) survived to discharge. Of these, 22 (11%) were re-admitted at a median of 9 [interquartile range (IQR) 4–15] days. The most common readmission diagnoses were infections after discharge (N=10) and vascular events (N=6). Age, history of stroke and hypertension, severity of neurologic deficit at admission, APACHE acute physiology score, ICU and hospital length of stay, ventilator free days, days febrile, and surgical procedures were not predictors of readmission. History of coronary artery disease was associated with readmission (p=0.03). Readmitted patients had similar mRS and severity of neurologic deficit at 14 days but higher (worse) mRS scores at three months (median [IQR], 5 [3–6] vs. 3 [1–4], p=0.01).
Severity of illness and hospital complications were not associated with 30-day readmission. The most common indication for readmission was infection after discharge, and readmission was associated with worse functional outcomes at three months. Preventing readmission after ICH may depend primarily on optimizing care after discharge and improve functional outcomes at three months.
PMCID: PMC3841230  PMID: 23963121
Intracerebral hemorrhage; critical care; readmission; quality metric; outcomes
6.  Risk Factors for Early Hospital Readmission in Patients with AIDS and Pneumonia 
To determine risk factors for early readmission to the hospital in patients with AIDS and pneumonia.
Case-control analysis.
A municipal teaching hospital serving an indigent population.
Case patients were all AIDS patients hospitalized with Pneumocystis carinii pneumonia or bacterial pneumonia between January 1992 and March 1995 who were readmitted for any nonelective reason within 2 weeks of discharge (n = 90). Control patients were randomly selected AIDS patients admitted during the study period who were not early readmissions (n = 87), matched by proportion of Pneumocystis carinii to bacterial pneumonia.
Demographics, social support, health-related behaviors, clinical aspects of the acute hospitalization, and general medical status were the main predictors measured.
Patients were at significantly increased risk of early readmission if they left the hospital unaccompanied by family or friend (odds ratio [OR] 4.76; 95% confidence interval [CI] 2.06, 11.0; p = .0003), used crack cocaine (OR 3.40; 95% CI 1.02, 11.3; p = .046), had one or more coincident AIDS diagnoses (OR 3.65; 95% CI 1.44, 9.26; p = .0065), or had been admitted in the preceding 6 months (OR 2.82; 95% CI 1.21, 6.57; p = .016). Demographic characteristics, alcoholism, intravenous drug use, illness severity on admission, and length of hospitalization did not predict early readmission.
Absence of companion at discharge and crack use were important risk factors for early readmission in patients with AIDS and pneumonia. Additional AIDS comorbidity and recent antecedent hospitalization were also risk factors; however, demographics and measures of acute illness during index hospitalization did not predict early readmission.
PMCID: PMC1496743  PMID: 10491241
hospital readmission; AIDS; pneumonia
7.  Institution specific risk factors for 30 day readmission at a community hospital: a retrospective observational study 
As of October 1, 2012, hospitals in the United States with excess readmissions based on the Centers for Medicare and Medicaid Services (CMS) risk-adjusted ratio began being penalized. Given the impact of high readmission rates to hospitals nationally, it is important for individual hospitals to identify which patients may be at highest risk of readmission. The objective of this study was to assess the association of institution specific factors with 30-day readmission.
The study is a retrospective observational study using administrative data from January 1, 2009 through December 31, 2010 conducted at a 257 bed community hospital in Massachusetts. The patients included inpatient medical discharges from the hospitalist service with the primary diagnoses of congestive heart failure, pneumonia or chronic obstructive pulmonary disease. The outcome was 30-day readmission rates. After adjusting for known factors that impact readmission, provider associated factors (i.e. hours worked and census on the day of discharge) and hospital associated factors (i.e. floor of discharge, season) were compared.
Over the study time period, there were 3774 discharges by hospitalists, with 637 30-day readmissions (17% readmission rate). By condition, readmission rates were 19.6% (448/2284) for congestive heart failure, 13.0% (141/1083) for pneumonia, and 14.7% (200/1358) for chronic obstructive lung disease. After adjusting for known risk factors (gender, age, length of stay, Elixhauser sum score, admission in the previous year, insurance, disposition, primary diagnosis), we found that patients discharged in the winter remained significantly more likely to be readmitted compared to the summer (OR 1.54, p = 0.0008). Patients discharged from the cardiac floor had a trend toward decreased readmission compared a medical/oncology floor (OR 0.85, p = 0.08). Hospitalist work flow factors (census and hours on the day of discharge) were not associated with readmission.
We found that 30 day hospital readmissions may be associated with institution specific risk factors, even after adjustment for patient factors. These institution specific risk factors may be targets for interventions to prevent readmissions.
PMCID: PMC3916302  PMID: 24467793
Readmission; Hospital quality; Risk factors
8.  Thirty-Day Hospital Readmission following Discharge from Post-acute Rehabilitation in Fee-for-Service Medicare Patients 
The Centers for Medicare and Medicaid Services (CMS) recently identified 30-day readmission after discharge from inpatient rehabilitation facilities as a national quality indicator. Research is needed to determine the rates and factors related to readmission in this patient population.
Determine 30-day readmission rates and factors related to readmission for patients receiving post-acute inpatient rehabilitation.
Retrospective cohort study.
1,365 post-acute inpatient rehabilitation facilities providing services to Medicare fee-for service beneficiaries.
Records for 736,536 post-acute patients discharged from inpatient rehabilitation facilities to the community in 2006 through 2011. Mean age 78.0 (SD = 7.3) years. Sixty-three percent of patients were female and 85.1% were non-Hispanic white.
Main Outcome and Measures
30-day readmission rates for the six largest diagnostic impairment categories receiving inpatient rehabilitation. These included stroke, lower extremity fracture, lower extremity joint replacement, debility, neurological disorders and brain dysfunction.
Mean rehabilitation length of stay was 12.4 (SD = 5.3) days. The overall 30-day readmission rate was 11.8% (95%CI, 11.7%, 11.8%). Rates ranged from 5.8% (95%CI, 5.8%, 5.9%) for patients with lower extremity joint replacement to 18.8% (95%CI, 18.8%, 18.9%). for patients with debility. Rates were highest in men (13.0%; 95%CI, 12.8%, 13.1%), non-Hispanic blacks, (13.8%; 95%CI, 13.5%, 14.1%), dual eligible beneficiaries (15.1%; 95%CI, 14.9%, 15.4%), and in patients with tier 1 comorbidities (25.6%; 95%CI, 24.9%, 26.3%). Higher motor and cognitive functional status were associated with lower hospital readmission rates across the six impairment categories. Variability in adjusted readmission rates by state ranged from 9.2% to 13.6%. Approximately 50% of patients who were rehospitalized within the 30-day period were readmitted within 11 days of discharge. MS-DRG codes for heart failure, urinary tract infection, pneumonia, septicemia, nutritional and metabolic disorders, esophagitis, gastroenteritis and digestive disorders were common reasons for readmission.
Conclusion and Relevance
Among post-acute rehabilitation facilities providing services to Medicare fee-for-service beneficiaries, 30-day readmission rates ranged from 5.8% to 18.8% for selected impairment groups. Further research is needed to understand the reasons for readmission.
PMCID: PMC4085109  PMID: 24519300
9.  Scheduled and Unscheduled Hospital Readmissions among Diabetes Patients 
The purpose of this study is to describe rates of scheduled and unscheduled readmissions among mid-life and older diabetes patients and examine associated factors.
Study Design and Methods
Using the 2006 California State Inpatient Dataset, we identified 124,967 patients aged 50 or older with diabetes who were discharged from acute care hospitals between April and September 2006, and examined readmissions in the 3 months following their index hospitalizations.
About 26.3% of the patients were readmitted within the 3-month period, 87.2% of which were unscheduled readmissions. Patients with unscheduled readmissions were more likely to have a higher comorbidity burden, be ethnic minorities with public insurance, and live in lower income neighborhoods. Having a history of hospitalization in the 3 months preceding the index hospitalization was also a strong predictor of unscheduled readmissions. Almost one fifth of the unscheduled readmissions were potentially preventable based on AHRQ’s PQI definitions, making up about 27,477 inpatient days and costing approximately 72.7 million dollars. Scheduled readmissions were less likely to occur in patients aged 80 or older, the uninsured, and those with an unscheduled index hospitalization.
The predictors of scheduled and unscheduled readmissions are different. Transition care to prevent unscheduled readmissions in acutely ill diabetes patients may help reduce rates, improving care. Further studies are needed on potential disparities in scheduled readmissions.
PMCID: PMC3024140  PMID: 20964472
Hospital Readmission; Preventable Hospitalization; Diabetes
10.  Is the emergency readmission rate a valid outcome indicator? 
Quality in Health Care : QHC  1999;8(4):234-238.
Objectives - The principal aim was to determine whether the emergency readmission rate varies between medical specialties, and to identify whether differences in emergency readmission rates between hospital trusts can be reduced by standardising for specialty. Possible factors influencing emergency readmission were also investigated, including frequency of previous admission and cause of readmission. Design - Emergency readmission rates were obtained from the Scottish Morbidity Record scheme (SMR1) using record linkage, standardised for age and sex. Rates throughout Scotland were analysed by specialty, and rates for general medicine compared among teaching hospital trusts. Cause of emergency readmission was determined from hospital records in a random sample (177 patients). Setting - Medical specialties throughout Scotland. Subjects - All patients readmitted as an emergency within 28 days of discharge (October 1990 to September 1994). Results - Emergency readmissions varied markedly between medical specialties, with highest rates in nephrology (24.2%, 95% CI 23.5 to 24.8) and haematology (20.4%, 95% CI 19.9 to 20.9), and the lowest in homeopathy (2.2%, 95% CI 1.6 to 2.7) and metabolic diseases (3.5%, 95% CI 2.4 to 4.5). The largest number of emergency readmissions was in general medicine, accounting for 63% of the total. Restricting emergency readmission rates to general medicine significantly altered previous rates. In the year preceding the emergency readmission, 59% of all patients had been admitted to hospital at least once, and most emergency readmissions (73.3%) resulted from a chronic underlying condition. Conclusions - Significant variations in emergency readmission rates occurred between medical specialties, suggesting that differences between hospital trusts are influenced by differences in specialties and thus case mix. The majority of emergency readmissions occurred in patients with an underlying chronic condition, and many had a history of multiple previous hospital admissions. The emergency readmission rate is therefore unlikely to be a valid outcome indicator reflecting quality of care until routine data are available for standardisation by case mix.
PMCID: PMC2483668  PMID: 10847885
11.  Hospital readmission performance and patterns of readmission: retrospective cohort study of Medicare admissions 
Objectives To determine whether high performing hospitals with low 30 day risk standardized readmission rates have a lower proportion of readmissions from specific diagnoses and time periods after admission or instead have a similar distribution of readmission diagnoses and timing to lower performing institutions.
Design Retrospective cohort study.
Setting Medicare beneficiaries in the United States.
Participants Patients aged 65 and older who were readmitted within 30 days after hospital admission for heart failure, acute myocardial infarction, or pneumonia in 2007-09.
Main outcome measures Readmission diagnoses were classified with a modified version of the Centers for Medicare and Medicaid Services’ condition categories, and readmission timing was classified by day (0-30) after hospital discharge. Hospital 30 day risk standardized readmission rates over the three years of study were calculated with public reporting methods of the US federal government, and hospitals were categorized with bootstrap analysis as having high, average, or low readmission performance for each index condition. High and low performing hospitals had ≥95% probability of having an interval estimate respectively less than or greater than the national 30 day readmission rate over the three year period of study. All remaining hospitals were considered average performers.
Results For readmissions in the 30 days after the index admission, there were 320 003 after 1 291 211 admissions for heart failure (4041 hospitals), 102 536 after 517 827 admissions for acute myocardial infarction (2378 hospitals), and 208 438 after 1 135 932 admissions for pneumonia (4283 hospitals). The distribution of readmissions by diagnosis was similar across categories of hospital performance for all three conditions. High performing hospitals had fewer readmissions for all common diagnoses. Median time to readmission was similar by hospital performance for heart failure and acute myocardial infarction, though was 1.4 days longer among high versus low performing hospitals for pneumonia (P<0.001). Findings were unchanged after adjustment for other hospital characteristics potentially associated with readmission patterns.
Conclusions High performing hospitals have proportionately fewer 30 day readmissions without differences in readmission diagnoses and timing, suggesting the possible benefit of strategies that lower risk of readmission globally rather than for specific diagnoses or time periods after hospital stay.
PMCID: PMC3898430  PMID: 24259033
12.  Readmission After Pancreatectomy for Pancreatic Cancer in Medicare Patients 
Journal of Gastrointestinal Surgery  2009;13(11):1963-1975.
The objective of this study was to use a population-based dataset to evaluate the number of readmissions and reasons for readmission in Medicare patients undergoing pancreatectomy for pancreatic cancer.
We used Surveillance, Epidemiology, and End Results–Medicare linked data (1992–2003) to evaluate the initial hospitalization, readmission rates within 30 days (early), and between 30 days and 1 year (late) after initial discharge and reasons for readmission in patients 66 years and older undergoing pancreatectomy.
We identified 1,730 subjects who underwent pancreatectomy for pancreatic cancer. The in-hospital mortality was 7.5%. The overall Kaplan–Meier readmission rate was 16% at 30 days and 53% at 1 year, accounting for 15,409 additional hospital days. Early readmissions were clearly related to operative complications in 80% of cases and unrelated diagnoses in 20% of cases. Late readmissions were related to recurrence in 48%, operative complications in 25%, and unrelated diagnoses in 27% of cases. In a multivariate analysis, only distal pancreatic resection (P = 0.02) and initial postoperative length of stay ≥10 days (P = 0.03) predicted early readmission. When compared to patients not readmitted, patients readmitted early had worse median survival (11.8 vs.16.5 months, P = 0.04), but the 5-year survival was identical (18%). Late readmission was associated with worse median and 5-year survival (19.4 vs. 12.1 months, 12% vs. 21%, P < 0.0001).
Our study demonstrates overall 30-day and 1-year readmission rates of 16% and 53%. The majority of early readmissions were related to postoperative complications but not related to patient and tumor characteristics. Complications causing early readmission are a cause of early mortality and are potentially preventable. Conversely, late readmissions are related to disease progression and are a marker of early mortality and not the cause.
PMCID: PMC2766461  PMID: 19760307
Readmission; Pancreatic resection; Kaplan–Meier; Operative complications
13.  Incidence of potentially avoidable urgent readmissions and their relation to all-cause urgent readmissions 
Urgent, unplanned hospital readmissions are increasingly being used to gauge the quality of care. We reviewed urgent readmissions to determine which were potentially avoidable and compared rates of all-cause and avoidable readmissions.
In a multicentre, prospective cohort study, we reviewed all urgent readmissions that occurred within six months among patients discharged to the community from 11 teaching and community hospitals between October 2002 and July 2006. Summaries of the readmissions were reviewed by at least four practising physicians using standardized methods to judge whether the readmission was an adverse event (poor clinical outcome due to medical care) and whether the adverse event could have been avoided. We used a latent class model to determine whether the probability that each readmission was truly avoidable exceeded 50%.
Of the 4812 patients included in the study, 649 (13.5%, 95% confidence interval [CI] 12.5%–14.5%) had an urgent readmission within six months after discharge. We considered 104 of them (16.0% of those readmitted, 95% CI 13.3%–19.1%; 2.2% of those discharged, 95% CI 1.8%–2.6%) to have had a potentially avoidable readmission. The proportion of patients who had an urgent readmission varied significantly by hospital (range 7.5%–22.5%; χ2 = 92.9, p < 0.001); the proportion of readmissions deemed avoidable did not show significant variation by hospital (range 1.2%–3.7%; χ2 = 12.5, p < 0.25). We found no association between the proportion of patients who had an urgent readmission and the proportion of patients who had an avoidable readmission (Pearson correlation 0.294; p = 0.38). In addition, we found no association between hospital rankings by proportion of patients readmitted and rankings by proportion of patients with an avoidable readmission (Spearman correlation coefficient 0.28, p = 0.41).
Urgent readmissions deemed potentially avoidable were relatively uncommon, comprising less than 20% of all urgent readmissions following hospital discharge. Hospital-specific proportions of patients who were readmitted were not related to proportions with a potentially avoidable readmission.
PMCID: PMC3185098  PMID: 21859870
14.  Patient and disease profile of emergency medical readmissions to an Irish teaching hospital 
Postgraduate Medical Journal  2004;80(946):470-474.
Objective: To determine whether there was a relationship between coded diseases at the time of hospital discharge, a pattern of ordering investigations, and hospital readmission in a major teaching hospital.
Design: Systematic review of data relating to emergency medical patients admitted to St James' Hospital Dublin between 1 January and 31 December 2002.
Data sources and methods: Data on discharges from hospital recorded in the Hospital In-Patient Enquiry (HIPE) system. The value of HIPE data in describing the relationship between the pattern of resource utilisation, diagnostic related groups, and hospital readmission has not previously been examined.
Results: Of 5038 episodes recorded among 4050 patients admitted, the number of readmissions was up to 15. Age and male gender were factors associated with readmission, and readmitted patients remained in hospital for longer. No particular test request predicted readmission, but computed tomography of the brain was associated with a reduced readmission rate. Discharge diagnostic related group coding at first discharge predicted readmission—codes related to heart failure, respiratory system, alcohol, malignancy, and anaemia.
Conclusions: It was found that clinical coding using the HIPE database strongly predicted hospital readmission. It may be argued that early hospital readmission reflects unsatisfactory patient care, alternatively that many readmissions are not preventable, representing either new events in elderly patients with chronic illnesses and frequent co-morbidity or related to social factors. The utility of specific interventions, in patients at high risk for hospital readmission, could be explored.
PMCID: PMC1743073  PMID: 15299157
15.  Early Primary Care Provider Follow-up and Readmission After High-Risk Surgery 
JAMA surgery  2014;149(8):821-828.
Follow-up with a primary care provider (PCP) in addition to the surgical team is routinely recommended to patients discharged after major surgery despite no clear evidence that it improves outcomes.
To test whether PCP follow-up is associated with lower 30-day readmission rates after open thoracic aortic aneurysm (TAA) repair and ventral hernia repair (VHR), surgical procedures known to have a high and low risk of readmission, respectively.
In a cohort of Medicare beneficiaries discharged to home after open TAA repair (n = 12 679) and VHR (n = 52 807) between 2003 to 2010, we compared 30-day readmission rates between patients seen and not seen by a PCP within 30 days of discharge and across tertiles of regional primary care use. We stratified our analysis by the presence of complications during the surgical (index) admission.
Thirty-day readmission rate.
Overall, 2619 patients (20.6%) undergoing open TAA repair and 4927 patients (9.3%) undergoing VHR were readmitted within 30 days after surgery. Complications occurred in 4649 patients (36.6%) undergoing open TAA repair and 4528 patients (8.6%) undergoing VHR during their surgical admission. Early follow-up with a PCP significantly reduced the risk of readmission among open TAA patients who experienced perioperative complications, from 35.0% (without follow-up) to 20.4% (with follow-up) (P < .001). However, PCP follow-up made no significant difference in patients whose hospital course was uncomplicated (19.4% with follow-up vs 21.9% without follow-up; P = .31). In comparison, early follow-up with a PCP after VHR did not reduce the risk of readmission, regardless of complications. In adjusted regional analyses, undergoing open TAA repair in regions with high compared with low primary care use was associated with an 18% lower likelihood of 30-day readmission (odds ratio, 0.82; 95% CI, 0.71–0.96; P = .02), whereas no significant difference was found among patients after VHR.
Follow-up with a PCP after high-risk surgery (eg, open TAA repair), especially among patients with complications, is associated with a lower risk of hospital readmission. Patients undergoing lower-risk surgery (eg, VHR) do not receive the same benefit from early PCP follow-up. Identifying high-risk surgical patients who will benefit from PCP integration during care transitions may offer a low-cost solution toward limiting readmissions.
PMCID: PMC4287962  PMID: 25074237
16.  Readmission after Colectomy for Cancer Predicts One-Year Mortality 
Annals of surgery  2010;251(4):659-669.
Early hospital readmission is a common and costly problem in the Medicare population. In 2009, the Centers for Medicaid and Medicare Services began mandating hospital reporting of disease-specific readmission rates. We sought to determine the rate and predictors of readmission after colectomy for cancer, as well as the association between readmission and mortality.
Medicare beneficiaries who underwent colectomy for stage I-III colon adenocarcinoma from 1992–2002 were identified from the SEER-Medicare database. Multivariate logistic regression identified predictors of early readmission and one-year mortality. Odds ratios were adjusted for multiple factors, including measures of comorbidity, socioeconomic status, and disease severity.
Of 42,348 patients who were discharged, 4,662 (11.0%) were readmitted within 30 days. The most common causes of rehospitalization were ileus/obstruction and infection. Significant predictors of readmission included male gender, comorbidity, emergent admission, prolonged hospital stay, blood transfusion, ostomy, and discharge to nursing home. Readmission was inversely associated with hospital procedure volume, but not surgeon volume. After adjusting for potential confounding variables, the predicted probability of one-year mortality was 16% for readmitted patients, compared to 7% for those not readmitted. This difference in mortality was significant for all stages of cancer.
Early readmission after colectomy for cancer is common and due in part to modifiable factors. There is a remarkable association between readmission and one-year mortality. Early readmission is therefore an important quality-of-care indicator for colon cancer surgery. These findings may facilitate the development of targeted interventions that will decrease readmissions and improve patient outcomes.
PMCID: PMC2951007  PMID: 20224370
Colon Cancer; Surgery; Colectomy; Readmission; Rehospitalization; Mortality; Hospital Discharge; Risk Factors; Outcomes
17.  Receiving Early Mobility During An ICU Admission Is A Predictor Of Improved Outcomes In Acute Respiratory Failure 
Hospitals are under pressure to provide care that not only shortens hospital length of stay, but reduces subsequent hospital admissions. Hospital readmissions have received increased attention in outcome reporting. We identified survivors of acute respiratory failure who then required subsequent hospitalization. A cohort of acute respiratory failure survivors, who participated in an early ICU-mobility program, was assessed to determine if variables from the index hospitalization predict hospital readmission or death, within 12 months of hospital discharge.
Hospital database and responses to letters mailed to 280 ARF survivors. Univariate predictor variables shown to be associated with hospital readmission or death (p<0.1) were included in a multiple logistic regression. A stepwise selection procedure was used to identify significant variables (p<0.05).
Of the 280 survivors, 132 (47%) had at least one readmission or died within the first year, 126 (45%) were not readmitted, and 22 (8%) were lost to follow-up. Tracheostomy [OR 4.02 (CI 1.72, 9.40)], female gender [OR1.94 (CI 1.13, 3.32)], a higher Charlson Comorbidity Index assessed upon index hospitalization discharge [OR 1.15 (CI 1.01, 1.31)], and lack of early ICU mobility therapy [OR 1.77 CI (1.04, 3.01)] predicted readmission or death in the first year post-Index hospitalization.
Tracheostomy, female gender, higher Charlson Comorbidity Index and lack of early ICU mobility were associated with readmissions or death during the first year. Although the mechanism(s) of increased hospital readmission are unclear, these findings may provide further support for early ICU mobility for acute respiratory failure patients.
PMCID: PMC3082620  PMID: 21358312
Critical Care; Rehabilitation; Acute Respiratory Failure; Long Term Outcomes; Mobility
18.  Evaluation of early discharge after hospital treatment of neutropenic fever in acute myeloid leukemia (AML) 
Leukemia Research Reports  2013;2(1):26-28.
Hospital admission for neutropenic fever in patients with AML is a standard practice. However, discharge practices vary once patients become afebrile, with many patients hospitalized until rise in the absolute neutrophil count (ANC) to >500 (ANC recovery). Data to support this practice are sparse. We hypothesized that patients admitted for neutropenic fever, particularly if in complete remission (CR) or about to enter CR following the chemotherapy course associated with neutropenic fever, might be safely discharged earlier (ED). Benefits of ED are less exposure to hospital pathogens, reduced cost, increased availability of beds for patients more in need of urgent care, and potentially, enhanced psychological well-being.
We identified patients age 18–70 with newly diagnosed AML who were admitted to the University of Washington Medical Center with neutropenic fever between January 2008 and May 2010. We compared subsequent (within 30 days of discharge) deaths, intensive care unit (ICU) admissions, and readmissions for neutropenic fever according to discharge ANC, regarded as a numerical variable using the Mann–Whitney U test and as <500 vs >500 using the Fisher Exact test. We used the Mann–Whitney U or Spearman correlation to analyze the relation between ANC at discharge and other covariates that might have affected outcome: age, ECOG performance status at admission for neutropenic fever, days inpatient, remission status, and type of infection (pneumonia, gram negative bacteremia, others).
We evaluated 49 patients discharged after admission for neutropenic fever, 26 of whom were discharged with an ANC <500. Thirty five of the patients were in CR or entered CR following the chemotherapy course associated with their neutropenic fever admission. Patients who were discharged with lower ANC were more likely to be readmitted with neutropenic fever (Mann–Whitney U p=0.03), although this was not true using ANC categorized as < vs >500 (Fisher Exact p=0.24, 95% confidence interval −0.47, 0.11). There was no relation between ANC at discharge and subsequent admission to an ICU (Mann–Whitney U p=0.50, Fisher Exact p=0.64, 95% confidence interval 0.2, 0.34 using the 500 ANC cut off). One patient died: a 55 year old discharged with ANC 0 after successful treatment of neutropenic fever died 19 days after hospital readmission with fever of unknown origin. Stenotrophomonas maltophilia pneumonia and sepsis were discovered 14 days after readmission. Assuming a beta distribution and rates of death of 1/26 for discharge with ANC<500 and 0/23 for discharge with ANC>500, the probability that a discharge ANC with <500 is associated with a higher death rate is 0.019. The number of events was too small for a multivariate analysis. However, patients with better performance status (
Our results suggest that an ANC of 500 is an excessively high cut off for discharge following hospitalization for neutropenic fever. The rate of rise of the ANC, as well as its absolute value, may also play a role.
PMCID: PMC3850377  PMID: 24371771
Leukemia; Neutropenic; Fever; Discharge; Neutrophil
Studies that identify reasons for readmissions are gaining importance in the light of the changing demographics worldwide which has led to greater demand for hospital beds. It is essential to profile the prevalence of avoidable readmissions and understand its drivers so as to develop possible interventions for reducing readmissions that are preventable. The aim of this study is to identify the magnitude of avoidable readmissions, its contributing factors and costs in Hong Kong.
This was a retrospective analysis of 332,453 inpatient admissions in the Medical specialty in public hospital system in Hong Kong in year 2007. A stratified random sample of patients with unplanned readmission within 30 days after discharge was selected for medical record reviews. Eight physicians reviewed patients' medical records and classified whether a readmission was avoidable according to an assessment checklist. The results were correlated with hospital inpatient data.
It was found that 40.8% of the 603 unplanned readmissions were judged avoidable by the reviewers. Avoidable readmissions were due to: clinician factor (42.3%) including low threshold for admission and premature discharge etc.; patient factor (including medical and health factor) (41.9%) such as relapse or progress of previous complaint, and compliance problems etc., followed by system factor (14.6%) including inadequate discharge planning, inadequate palliative care/terminal care, etc., and social factor (1.2%) such as carer system, lack of support and community services. After adjusting for patients' age, gender, principal diagnosis at previous discharge and readmission hospitals, the risk factors for avoidable readmissions in the total population i.e. all acute care admissions irrespective of whether there was a readmission or not, included patients with a longer length of stay, and with higher number of hospitalizations and attendance in public outpatient clinics and Accident and Emergency departments in the past 12 months. In the analysis of only unplanned readmissions, it was found that the concordance of the principal diagnosis for admission and readmission, and shorter time period between discharge and readmission were associated with avoidable readmissions.
Our study found that almost half of the readmissions could have been prevented. They had been mainly due to clinician and patient factors, in particular, both of which were intimately related to clinical management and patient care. These readmissions could be prevented by a system of ongoing clinical review to examine the clinical practice/decision for discharge, and improving clinical care and enhancing patient knowledge of the early warning signs for relapse. The importance of adequate and appropriate ambulatory care to support the patients in the community was also a key finding to reduce avoidable readmissions. Education on patient self-management should also be enhanced to minimize the patient factors with regard to avoidable readmission. Our findings thus provide important insights into the development of an effective discharge planning system which should place patients and carers as the primacy focus of care by engaging them along with the healthcare professionals in the whole discharge planning process.
PMCID: PMC2993701  PMID: 21080970
Acute respiratory exacerbations are the most frequent cause of medical visits, hospitalization and death for chronic obstructive pulmonary disease (COPD) patients and, thus, exert a significant social and economic burden on society.
To identify the risk factors associated with hospital readmission(s) for acute exacerbation(s) of COPD (AECOPD).
A review of admission records from three large urban hospitals in Vancouver, British Columbia, identified 310 consecutive patients admitted for an AECOPD between April 1, 2001, and December 31, 2002. Logistic regression analysis was performed to identify risk factors for readmissions following an AECOPD.
During the study period, 38% of subjects were readmitted at least once. The mean (± SD) duration from the index admission to the first readmission was 5±4.08 months. Comparative analysis among the three hospitals identified a significant difference in readmission rates (54%, 36% and 18%, respectively). Logistic regression analysis revealed that preadmission home oxygen use (OR 2.55; 95%CI 1.45 to 4.42; P=0.001), history of a lung infection within the previous year (OR 1.73; 95% CI 1.01 to 2.97; P=0.048), other chronic respiratory disease (OR 1.78; 95% CI 1.06 to 2.99; P=0.03) and shorter length of hospital stay (OR 0.97; 95% CI 0.945 to 0.995; P=0.021) were independently associated with frequent readmissions for an AECOPD.
Hospital readmission rates for AECOPD were high. Only four clinical factors were found to be independently associated with COPD readmission. There was significant variability in the readmission rate among hospitals. This variability may be a result of differences in the patient populations that each hospital serves or may reflect variability in health care delivery at different institutions.
PMCID: PMC2734440  PMID: 19707601
Chronic obstructive lung disease; Exacerbations; Hospitalization; Risk factors
Early hospital readmissions, defined as rehospitalization within 30 days from a previous discharge, represent an economic and social burden for public health management. As data about early readmission in Italy are scarce, we aimed to relate the phenomenon of 30-day readmission to factors identified at the time of emergency department (ED) visits in subjects admitted to medical wards of a general hospital in Italy.
We performed a retrospective 30-month observational study, evaluating all patients admitted to the Department of Medicine of the Hospital of Ferrara, Italy. Our study compared early and late readmission: patients were evaluated on the basis of the ED admission diagnosis and classified differently on the basis of a concordant or discordant readmission diagnosis in respect to the diagnosis of a first hospitalization.
Out of 13,237 patients admitted during the study period, 3,631 (27.4%) were readmitted; of those, 656 were 30-day rehospitalizations (5% of total admissions). Early rehospitalization occurred 12 days (median) later than previous discharge. The most frequent causes of rehospitalization were cardiovascular disease (CVD) in 29.3% and pulmonary disease (PD) in 29.7% of cases. Patients admitted with the same diagnosis were younger, had lower length of stay (LOS) and higher prevalence of CVD, PD and cancer. Age, CVD and PD were independently associated with 30-day readmission with concordant diagnosis and kidney disease with 30-day rehospitalization with a discordant diagnosis.
Comorbid patients are at higher risk for 30-day readmission. Reduction of LOS, especially in elderly subjects, could increase early rehospitalization rates.
PMCID: PMC4314760  PMID: 25623952
Hospitalization; Readmission; Length of stay; Mortality; Comorbidity; Internal medicine
Hospital discharge against medical advice, especially among substance-abusing populations, is a frustrating problem for health care pro-viders. Because of the high prevalence of injection drug use among HIV- positive patients admitted to hospital in Vancouver, we explored the factors associated with leaving hospital against medical advice in this population.
We reviewed records for all HIV/AIDS patients admitted to St. Paul's Hospital, Vancouver, between Apr. 1, 1997, and Mar. 1, 1999. After identifying the first (“index”) admission during this period, we followed the patients' records for 1 year. Multivariate models were applied to identify the determinants of discharge against medical advice and to estimate the impact of such discharge on readmission rate, readmission frequency and length of stay in hospital.
Of 981 index admissions among HIV/AIDS patients, 125 (13%) of the patients left the hospital against medical advice. Departure on the day on which welfare cheques were issued and a history of injection drug use were significant predictors of leaving against medical advice. After adjusting for sex, age, severity of illness, injection drug use and homelessness, we found that patients leaving against medical advice were readmitted more frequently than those who were formally discharged (frequency ratio 1.25, 95% confidence interval [CI] 1.11–1.42), were more likely to be readmitted with a related diagnosis within 30 days (odds ratio 5.00, 95% CI 3.04–8.24) and had significantly longer lengths of stay in the follow-up period.
Discharge against medical advice among HIV-positive patients was associated with frequent readmissions with the same diagnosis. Preventing such discharges is likely to benefit patients (by improving their health status) and the health care system (by reducing unnecessary readmissions).
PMCID: PMC122025  PMID: 12358196
Many patients with pneumonia and lower respiratory tract infection that could be treated as outpatients according to their clinical severity score, are in fact admitted to hospital. We investigated whether, with medical and social input, these patients could be discharged early and treated at home.
Objectives: (1) To assess the feasibility of providing an early supported discharge scheme for patients with pneumonia and lower respiratory tract infection (2) To assess the patient acceptability of a study comprising of randomisation to standard hospital care or early supported discharge scheme.
Design: Randomised controlled trial.
Setting: Liverpool, UK. Two University Teaching hospitals; one city-centre, 1 suburban in Liverpool, a city with high deprivation scores and unemployment rates.
Participants: 200 patients screened: 14 community-dwelling patients requiring an acute hospital stay for pneumonia or lower respiratory tract infection were recruited.
Intervention: Early supported discharge scheme to provide specialist respiratory care in a patient’s own home as a substitute to acute hospital care.
Main outcome measures: Primary - patient acceptability. Secondary – safety/mortality, length of hospital stay, readmission, patient/carer (or next of kin) satisfaction, functional status and symptom improvement.
42 of the 200 patients screened were eligible for early supported discharge; 10 were only identified at the point of discharge, 18 declined participation and 14 were randomised to either early supported discharge or standard hospital care. The total hospital length of hospital stay was 8.33 (1–31) days in standard hospital care and 3.4 (1–7) days in the early supported discharge scheme arm. In the early supported discharge scheme arm patient carers reported higher satisfaction with care and there were less readmissions and hospital-acquired infections.
Limitations: A small study in a single city. This was a feasibility study and therefore not intended to compare outcome data.
An early supported discharge scheme for patients with pneumonia and lower respiratory tract infection was feasible. Larger numbers of patients would be eligible if future work included patients with dementia and those residing in care homes.
Trial registration
PMCID: PMC3943804  PMID: 24571705
Early supported discharge; Pneumonia; Respiratory infection; Feasibility; Patient acceptability
Despite the known efficacy of highly active antiretroviral therapy (HAART), a large proportion of potentially-eligible HIV-infected patients do not access, and may stand to benefit from this treatment. In order to quantify these benefits in terms of reductions in hospitalizations and hospitalization costs, we sought to determine the impact of HAART on hospital readmission among HIV-infected patients hospitalized at St. Paul's Hospital (SPH) in Vancouver, BC, Canada.
All patients admitted to a specialized HIV/AIDS ward at SPH (Apr. 1997 – Oct. 2002) were selected and classified as being on HAART or not on HAART based upon their initial admission. Patients were then matched by their propensity scores, which were calculated based on patients' sociodemographics such as age, gender, injection drug use (IDU) status, and AIDS indication, and followed up for one year. Multivariate logistic regression was used to estimate the difference in the odds of hospital readmission between patients on and not on HAART.
Out of a total 1084 patients admitted to the HIV/AIDS ward between 1997 and 2002, 662 were matched according to their propensity score; 331 patients each on and not on HAART. Multivariate logistic regression revealed that patients on HAART had lower odds of AIDS hospital readmission (OR, 0.61; 95% CI, 0.42 – 0.89) compared to patients not on HAART. Odds of readmission among patients on HAART were also significantly lower for non-IDU related readmission (OR, 0.73; 95% CI, 0.53 – 0.99) and overall readmission (OR, 0.72; 95% CI, 0.53 – 0.98).
Propensity score matching allowed us to reliably estimate the association between exposure (on or not on HAART) and outcome (readmitted to hospital). We found that HIV-infected patients who were potentially eligible for, but not on HAART had higher odds of being readmitted to hospital compared to those on HAART. Given the low level of uptake (31%) of HAART observed in our pre-matched hospitalized cohort, a large potential to achieve clinical benefits, reduce hospitalization costs and possibly slow disease progression from improved HAART uptake still exists.
PMCID: PMC1617096  PMID: 17022826
BMJ Open  2012;2(2):e000428.
In the 30 days after hospital discharge, hospital utilisation is common and costly. This study evaluated the association between gender and hospital utilisation within 30 days of discharge.
Secondary data analysis using Poisson regression stratified by gender.
737 English-speaking hospitalised adults from general medical service in urban, academic safety-net medical centre who participated in the Project Re-Engineered clinical trial ( identifier: NCT00252057).
Main outcome measure
The primary end point was hospital utilisation, defined as total emergency department visits and hospital readmissions within 30 days after index discharge.
Female subjects had a rate of 29 events for every 100 people and male subjects had a rate of 47 events for every 100 people (incident rate ratio (IRR) 1.62, 95% CI 1.28 to 2.06). Among men, risk factors included hospital utilisation in the 6 months prior to the index hospitalisation (IRR 3.55, 95% CI 2.38 to 5.29), being unmarried (IRR 1.72, 95% CI 1.12 to 2.64), having a positive depression screen (IRR 1.53, 95% CI 1.09 to 2.13) and no primary care physician (PCP) visit within 30 days (IRR 1.64, 95% CI 1.08 to 2.50). Among women, the only risk factor was hospital utilisation in the 6 months prior to the index hospitalisation (IRR 3.08, 95% CI 1.86 to 5.10).
In our data, male subjects had a higher rate of hospital utilisation within 30 days of discharge than female subjects. For men—but not for women—risk factors were being retired, unmarried, having depressive symptoms and having no PCP visit within 30 days. Interventions addressing these factors might lower hospital utilisation rates observed among men.
Article summary
Article focus
Early hospital readmission is a common and costly occurrence in the USA. Men often use hospital emergency departments for usual source of medical care.
We aimed to study whether men are therefore more likely to be readmitted to the hospital within 30 days of an index discharge.
Key messages
Men have higher rates of 30-day readmission to hospital than women in this study group. Men also were less likely to complete a follow-up appointment with their primary care physician after discharge.
Interventions that promote connecting men to primary care, address social isolation and screen for depressive symptoms may reduce the risk for early readmission among men.
Strengths and limitations of this study
This analysis was conducted with the Project RED data set, which included, and allowed controlling for certain clinical and social confounders in our analysis such as subjects' comorbidity burden, depression symptoms, homelessness, substance abuse and other similar risk factors, in our analysis.
This study is limited in that it was conducted at an urban safety-net hospital and may not be generalisable to other types of hospital systems.
We also relied on subject self-report of any rehospitalisation events outside of the study site, however, were able to confirm 91% of all events using our hospital electronic medical record system.
PMCID: PMC3332240  PMID: 22514241

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