Effectiveness of a Brief Care Management Intervention for Reducing Psychiatric Hospitalization Readmissions

This study examines a recovery-focused care management bridging strategy implemented during time of inpatient stay with the goal to increase engagement in aftercare and reduce early psychiatric readmissions. The sample included 195 individuals who received care from a large psychiatric specialty hospital. Eighty-seven individuals were assigned to receive the intervention, while 108 individuals were assigned to the control group. Individuals in the intervention group received a brief interview prior to inpatient discharge plus usual care, and individuals in the control group received usual care. After controlling for age, living situation, and utilization, individuals in the control group were more likely to be readmitted within 30 days of an index readmission than individuals in the intervention group (OR?=?2.44, p?=?.02). Bridging strategies utilized prior to discharge for individuals at higher risk of early mental health inpatient readmission may be used as an effective alternative to more costly interventions.     

Factors associated with inpatient readmission among managed care enrollees with COPD

Objective. To assess factors associated with inpatient readmission among a US managed care population with chronic obstructive pulmonary disease (COPD). Background. COPD is often accompanied by intermittent acute exacerbations, which may result in hospitalizations. These exacerbations are often associated with an increased frequency of subsequent exacerbations, which may lead to inpatient readmissions. Methods. We assessed US managed care claims data for enrollees ≥ 40 years old with an inpatient admission with a primary diagnosis of COPD (ICD-9-CM codes 491.xx, 492.xx or 496.xx) between 1 January 2010 and 31 December 2013 (discharge date of first observed inpatient admission defined the “index date”). Patients were required to be continuously enrolled for ≥ 12 months before the index date. Two non-mutually exclusive cohorts were analyzed: (1) patients with ≥ 30 days of post-index date continuous enrollment (to evaluate 30-day readmission) and (2) patients with ≥ 90 days of post-index date continuous enrollment (to evaluate 90-day readmission). Logistic regression evaluated the association between patient characteristics and risk of 30- and 90-day COPD-related and all-cause readmission. Results. After applying selection criteria, 140,981 patients had ≥ 30 days of enrollment post-index date, and 123,545 patients had ≥ 90 days of enrollment post-index date. Within 30 days, nearly 20% of patients had an all-cause readmission and 7% had a COPD-related readmission. Within 90 days, 28% had an all-cause readmission and 12% had a COPD-related readmission. Logistic regression indicated that longer length of stay, older age, greater comorbidity burden, specific comorbidities and COPD complexity were associated with significantly greater odds of COPD-related 30- and 90-day readmission. Results for all-cause readmission were generally similar. Conclusions. Many of the factors associated with inpatient readmission documented here can be ascertained at discharge and may be used to inform discharge plans, with the end goal of improving patient outcomes, including reducing the risk of readmission.     

The impact of utilization management on readmissions among patients with cardiovascular disease

OBJECTIVE: To determine if prospective utilization reviews that lead to reduced hospital length of stay (LOS) relative to days requested by an attending physician affect the likelihood of readmission for privately insured patients with cardiovascular disease. DATA SOURCES: Data obtained from a private insurance company on utilization management decisions from 1989 through 1993. During this five-year period, 39,117 inpatient reviews were conducted, 4,326 (11.1 percent) on patients with cardiovascular disease. We selected for analysis all 4,326 reviews performed on patients with cardiovascular disease. STUDY DESIGN: We used proportional hazard analysis (Cox regression) to investigate the relationship between LOS reductions relative to days requested by a patient's attending physician and the likelihood of readmission within 60 days of discharge. Separate analyses were performed for medical and procedural admissions. PRINCIPAL FINDINGS: There were 2,813 requests for medical admission, and 1,513 requests for procedural admission. Requests for admission were rarely denied. Length of stay was reduced relative to that requested by the treating physician for 17 percent and 19 percent of medical and procedural admissions, respectively. Cumulative 60-day readmission rates were 9.5 percent for medical admissions and 12.3 percent for procedural admissions. We found no relationship between LOS reduction and the likelihood of readmission for medical admissions. However, patients admitted for procedures who had their length of stay reduced by two or more days were 2.6 times as likely to be readmitted within 60 days as those who had no reduction in their length of stay (95% CI: 1.3-5.1; p < .005). CONCLUSIONS: Utilization management (UM) rarely denies requests for inpatient treatment of cardiovascular disease. The association between LOS reduction and the likelihood of readmission for patients admitted for cardiovascular procedures raises concern that UM may adversely affect clinical outcome for some patients. Further research is needed to definitively elucidate any relationship that might exist between utilization review decisions and quality of care.     

Early primary care follow-up after ED and hospital discharge – does it affect readmissions?

Objectives: After hospitalization, timely discharge follow-up has been linked to reduced readmissions in the heart failure population, but data from general inpatients has been mixed. The objective of this study was to determine if there was an association between completed follow-up appointments within 14 days of hospital discharge and 30-day readmission amongst primary care patients at an urban academic medical center. Index discharges included both inpatient and emergency room settings. A secondary objective was to identify patient factors associated with completed follow-up appointments within 14 days.

Methods: We conducted a retrospective review of primary care patients at an urban academic medical center who were discharged from either the emergency department (ED) or inpatient services at the Weill Cornell Medical Center/New York Presbyterian Hospital from 1 January 2014-31 December 2014. Cox proportional hazard models were used to identify the relationship between follow-up in primary care within 14 days and readmission within 30 days. Logistic regression was used to evaluate the association of patient factors with 14-day follow-up.

Results: Among 9,662 inpatient and ED discharges, multivariable analysis (adjusting for age, gender, race/ethnicity, insurance, number of diagnoses on problem list, length of stay, and discharge service) showed that follow-up with primary care within 14 days was not associated with a lower hazard of readmission within 30 days (HR = 0.78; 95% CI 0.56–1.09). A higher number of diagnoses on the problem list was associated with greater odds of follow-up for both inpatient and emergency department discharges (inpatient: HR = 1.03, 95% CI 1.02–1.04; ED: HR = 1.02, 95% CI 1.00–1.04). For inpatient discharges, each additional day in length of stay was associated with 3% lower odds of follow-up (HR = 0.97, 95% CI 0.96–0.99).

Conclusion: Early follow-up within 14 days after discharge from general inpatient services was associated with a trend toward lower hazard of 30-day readmission though this finding was not significant. Future studies should focus on identifying additional cohorts of patients in which readmission is reduced by early follow-up, so that access to primary care appointments is not compromised.     

The Effect of a Medicaid Managed Care Program on Patterns of Psychiatric Readmission Among Adolescents: Evidence from Maryland

This study evaluates the effect of Maryland’s Medicaid managed care program on patterns of psychiatric readmission for adolescents. Rates and frequency of readmissions are compared before (FY 1997) and after (FY 1998) the implementation of Maryland’s Medicaid managed care program. Medicaid claims files were reviewed for 881 adolescents consecutively admitted to three major Maryland psychiatric hospitals between July 1, 1996 and June 30, 1998. Adolescents admitted after the managed care reforms were more likely to experience multiple readmissions. The 1-year cumulative rate of readmission pre- and postmanaged care was 33% and 38%, respectively; the highest risk period fell within the first 15–30 days postdischarge. The high rate of early readmissions raises concern about the quality of care and the adequacy of community-based services. Findings also suggest that youths with serious emotional disturbances who are high users of inpatient care may be adversely affected by the managed care reforms. Cynthia A. Fontanella, PhD, is a postdoctoral fellow at Institute for Health, Health Care Policy, and Aging Research (IHHCPAR), Rutgers University, 30 College Avenue, New Brunswick, NJ 08901 USA. Susan J. Zuravin, PhD, is a professor at University of Maryland School of Social Work, 525 West Redwood Street, Baltimore, MD 21201 USA. Caroline L. Burry, PhD, is a associate professor at University of Maryland School of Social Work, 525 West Redwood Street, Baltimore, MD 21201 USA.     

Does case mix matter for substance abuse treatment? A comparison of observed and case mix-adjusted readmission rates for inpatient substance abuse treatment in the Department of Veterans Affairs.

OBJECTIVE: To develop a case mix model for inpatient substance abuse treatment to assess the effect of case mix on readmission across Veterans Affairs Medical Centers (VAMCs). DATA SOURCES/STUDY SETTING: The computerized patient records from the 116 VAMCs with inpatient substance abuse treatment programs between 1987 and 1992. STUDY DESIGN: Logistic regression was used on patient data to model the effect of demographic, psychiatric, medical, and substance abuse factors on readmission to VAMCs for substance abuse treatment within six months of discharge. The model predictions were aggregated for each VAMC to produce an expected number of readmissions. The observed number of readmissions for each VAMC was divided by its expected number to create a measure of facility performance. Confidence intervals and rankings were used to examine how case mix adjustment changed relative performance among VAMCs. DATA COLLECTION/EXTRACTION METHODS: Ward where care was provided and ICD-9-CM diagnosis codes were used to identify patients receiving treatment for substance abuse (N = 313,886). PRINCIPAL FINDINGS: The case mix model explains 36 percent of the observed facility level variation in readmission. Over half of the VAMCs had numbers of readmissions that were significantly different than expected. There were also noticeable differences between the rankings based on actual and case mix-adjusted readmissions. CONCLUSIONS: Secondary data can be used to build a reasonably stable case mix model for substance abuse treatment that will identify meaningful variation across facilities. Further, case mix has a large effect on facility level readmission rates for substance abuse treatment. Uncontrolled facility comparisons can be misleading. Case mix models are potentially useful for quality assurance efforts.     

Implementation of discharge management for geriatric patients at risk of readmission or institutionalization.

OBJECTIVE: To evaluate whether implementation of discharge management by trained social workers or nurses reduces hospital readmissions and institutionalizations of geriatric patients in a real-world setting. DESIGN: Quasi-experimental design. SETTING: Six general hospitals in Belgium. PARTICIPANTS: A representative sample of 824 patients, 355 of whom were assigned to the experimental group receiving comprehensive discharge management and 469 to the control group receiving usual care. Inclusion criteria were patients admitted to a geriatric, rehabilitation, or internal medicine ward, not residing in a nursing home, and showing risk of readmission or institutionalization on admission in the hospital. INTERVENTION: In-hospital discharge planning according to a case management protocol allowing for adjustment to participating hospitals' case mix and patients' and families' specific needs. MAIN OUTCOME MEASURES: Hospital readmission within 15 and 90 days post discharge; institutionalization at discharge and within 15 and 90 days post discharge. RESULTS: Discharge management resulted in fewer institutionalizations (n = 53; 14.9%) compared with usual care (n = 130; 23.7%) (adjusted odds ratio = 0.47; CI 95% = 0.31-0.70). Readmission rates between the intervention and usual care group were not significantly different. CONCLUSIONS: This implementation project showed that a discharge planning intervention can reduce institutionalization rates of elderly patients in real-life settings.     

Do Older Rural and Urban Veterans Experience Different Rates of Unplanned Readmission to VA and Non‐VA Hospitals?

ABSTRACT:  Context: Unplanned readmission within 30 days of discharge is an indicator of hospital quality. Purpose: We wanted to determine whether older rural veterans who were enrolled in the VA had different rates of unplanned readmission to VA or non-VA hospitals than their urban counterparts. Methods: We used the combined VA/Medicare dataset to examine 3,513,912 hospital admissions for older veterans that occurred in VA or non-VA hospitals between 1997 and 2004. We calculated 30-day readmission rates and odds ratios for rural and urban veterans, and we performed a logistic regression analysis to determine whether living in a rural setting or initially using the VA for hospitalization were independent risk factors for unplanned 30-day readmission, after adjusting for age, sex, length of stay of the index admission, and morbidity. Findings: Overall, rural veterans had slightly higher 30-day readmission rates than their urban counterparts (17.96% vs 17.86%; OR 1.006, 95% CI: 1.0004, 1.013). For both rural- and urban-dwelling veterans, readmission after using a VA hospital was more common than after using a non-VA hospital (20.7% vs 16.8% for rural veterans, 21.2% vs 16.1% for urban veterans). After adjusting for other variables, readmission was more likely for rural veterans and following admission to a VA hospital. Conclusions: Our findings suggest that VA should consider using the unplanned readmission rate as a performance metric, using the non-VA experience of veterans as a performance benchmark, and helping rural veterans select higher performing non-VA hospitals.     

Is Readmission a Valid Indicator of the Quality of Inpatient Psychiatric Care?

Early return to hospital is a frequently measured outcome in mental health system performance monitoring yet its validity for evaluating quality of inpatient care is unclear. This study reviewed research conducted in the last decade on predictors of early readmission (within 30 to 90 days of discharge) to assess the association between this indicator and quality of inpatient psychiatric care. Only 13 studies met inclusion criteria. Results indicated that risk is greatest in the 30-day period immediately after discharge. There was modest support that attending to stability of clinical condition and preparing patients for discharge can protect against early readmission. A history of repeated admission increases risk, suggesting that special efforts are required to break the revolving door cycle. The authors identified a need for more standardization in measurement of client status at discharge and related care processes, more intervention studies on discharge practices, and studies of the effect of community care on early readmission.     

Impact of physician training level on emergency readmission within internal medicine

OBJECTIVES: The research question was whether training level of admitting physicians and referrals from practitioners in primary health care (PHC) are risk factors for emergency readmission within 30 days to internal medicine. METHODS: This report is a prospective multicenter study carried out during 1 month in 1997 in seven departments of internal medicine in the County of Stockholm, Sweden. Two of the units were at university hospitals, three at county hospitals and two in district hospitals. The study area is metropolitan-suburban with 1,762,924 residents. Data were analyzed by multiple logistic regression. RESULTS: A total of 5,131 admissions, thereby 408 unplanned readmissions (8 percent) were registered (69.8 percent of 7348 true inpatient episodes). The risk of emergency readmission increased with patient's age and independently 1.40 times (95 percent confidence interval [CI], 1.13-1.74) when residents decided on hospitalization. Congestive heart failure as primary or comorbid condition was the main reason for unplanned readmission. Referrals from PHC were associated with risk decrease (odds ratio, 0.53; 95 percent CI, 0.38-0.73). CONCLUSION: The causes of unplanned hospital readmissions are mixed. Patient contact with primary health care appears to reduce the recurrence. In addition to the diagnoses of cardiac failure, training level of admitting physicians in emergency departments was an independent risk factor for early readmission. Our conclusion is that it is cost-effective to have all decisions on admission to hospital care confirmed by senior doctors. Inappropriate selection of patients to inpatient care contributes to poor patient outcomes and reduces cost-effectiveness and quality of care.     

Hospital Readmissions Among Post-acute Nursing Home Residents: Does Obesity Matter?

ObjectivesTo explore profiles of obese residents who receive post-acute care in nursing homes (NHs) and to assess the relationship between obesity and hospital readmissions and how it is modified by individual comorbidities, age, and type of index hospitalizations.DesignRetrospective cohort study.Setting and participantsMedicare fee-for-service beneficiaries who were newly admitted to free-standing US NHs after an acute inpatient episode between 2011 and 2014 (N = 2,323,019).MeasuresThe Minimum Data Set 3.0 were linked with Medicare data. The outcome variable was 30-day hospital readmission from an NH. Residents were categorized into 3 groups based on their body mass index (BMI): nonobese, mildly obese, moderate-to-severely obese. We tested the relationship between obesity and 30-day readmissions by fixed-effects logit models and stratified analyses by the type of index hospitalization and residents' age.ResultsForty percent of the identified residents were admitted after a surgical episode, and the rest were admitted after a medical episode. The overall relationship between obesity and readmissions suggested that obesity was associated with higher risks of readmission among the oldest old (≥85 years) residents but with lower risks of readmission among the youngest group (65-74 years). After accounting for individual co-covariates, the association between obesity and readmissions among the oldest old residents became weaker; the adjusted odds ratio was 1.061 (P = .049) and 1.004 (P = .829) for moderate-to-severely obese patients with surgical and medical index hospitalizations, respectively. The protective effect of obesity among younger residents reduced after adjusting for covariates.Conclusions/RelevanceThe relationship between obesity and hospital readmission among post-acute residents could be affected by comorbidities, age, and the type of index hospitalization. Further studies are also warranted to understand how to effectively measure NH quality outcomes, including hospital readmissions, so that policies targeting at quality improvement can successfully achieve their goals without unintended consequences.     

Effects of Postacute Settings on Readmission Rates and Reasons for Readmission Following Total Knee Arthroplasty

Objectives

Examine the effects of postacute discharge setting on unplanned hospital readmissions following total knee arthroplasty (TKA) in older adults.

Effects of health care cost-containment programs on patterns of care and readmissions among children and adolescents.

OBJECTIVES: This study examined the effects of a utilization management program on patterns of medical care among children and adolescents. METHODS: From 1989 through 1993, the program conducted 8568 reviews of pediatric patients, ranging in age from birth to 18 years. The program used preadmission and concurrent review procedures to review and certify patients' need for care. This study used multivariate analyses to assess changes in the number of days of inpatient care approved by the program and to determine whether limitations imposed on length of stay affected the risk of 60-day readmission. RESULTS: Concurrent review reduced the number of requested days of inpatient care by 3.2 days per patient. Low-birthweight infants and adolescent patients with depression or alcohol or drug dependence accounted for a disproportionate share of the reduction. Patients classified as admitted for medical or mental health care and whose stay was restricted by concurrent review were more likely (P < .05) to be readmitted within 60 days after discharge. CONCLUSIONS: By limiting care through its review procedures, the utilization management program decreased inpatient resource consumption but also increased the risk of readmission for some patients. Continued investigation should be conducted of the effects of cost-containment programs on the quality of care given to children and adolescents, especially in the area of mental health.     

PMH2 Assessment of Health-Related Quality of Life During Treatment of Opiate Dependence using the Short Form-36

In the U.S., acute general hospitals increasingly provide treatment for patients with schizophrenia.
OBJECTIVE: To estimate the average annual cost of inpatient schizophrenia care per patient in an acute general hospital setting.
METHODS: Using ICD9 codes to identify disease and procedure-level data in five state (CA, FL, MA, MD, NC) acute care, all payer, discharge databases, an average cost per admission was estimated and combined with the frequency of admission calculated from the MA database to derive a mean annual acute care inpatient cost. Physician costs were calculated by applying 1997 Medicare fees to a resource use profile derived from the databases and published treatment recommendations. All costs are reported in 1997 US$, appropriately adjusted for medical inflation and cost-to-charge ratios.
RESULTS: Of 7.5 millions discharges, 73,000 were identified as having been admitted primarily due to schizophrenia. The average length of stay was 13.5 days, with 90% of time spent in a designated psychiatric bed. Over 90% were discharged within one month, most (∼80%) to home without documentation of further services. The mean cost per stay (including physician fees) was $8,963. Most (68%) patients had only one admission, and 96% had less than five in one year, leading to annual hospitalization cost per schizophrenic patient of $13,854.
CONCLUSIONS: Of schizophrenic patients admitted to an acute general hospital, the majority are admitted only once per year, spend their stay in a designated psychiatric unit bed, and are discharged within two weeks. Although these patients may have subsequent admissions to another type of inpatient facility, the majority are not transferred to such a facility at the time of discharge.     

Predictors of short-term readmission of asthmetic children

BACKGROUND: Bronchial asthma admission rate has increased dramatically all over the world. Part of this increase in hospital admissions is due to patients' readmission. OBJECTIVE: Determining what risk factors are associated with short-term hospital readmission of pediatric patients with asthma within two months of the last hospital admission. METHODS AND SETTING: A retrospective case-control study using registration books of both admissions and discharges to identify patients groups. All hospital records were reviewed for patients admitted from August 1998 through December 2002 at Assir Central Hospital, southwestern of Saudi Arabia. Patients who were admitted at this period of study and they were readmitted to the hospital within two months constituted the study group (n = 28) and those patients who were admitted within the same period but not readmitted within two months constituted the control group (n = 45). Demographic variables, route of admission, patient previous medical history, clinical assessment, hospital treatment as well as discharge treatment were extracted from medical records. RESULTS: twenty eight patients were readmitted within two months of the discharge from hospital (17 boys and 11 girls), seventy percent of these were below four years of age. Significant predictors of readmission were; prior history of asthma admission (adjusted OR 1.81 (1.20-2.73), NICU graduate (adjusted OR 4.44 (1.67-6.34), chronic lung disease (adjusted OR 3.06, 95% CI 2.01-4.95), tracheosphageal fistula (Adjusted OR 3.19, 95% CI 1.08-8.74), recurrent aspiration (adjusted OR 3.14, 95% CI 1.90-4.27), duration of asthma symptoms more than four days (adjusted OR 0.23, CI 0.21-0.42), moderate to severe clinical assessment (adjusted OR 1.67-95% CI 1.15-3.04), intensive care admission (adjusted OR 2.96, 95% CI 1.09-8.63), intravenous steroids ( adjusted OR 2.21,95% CI 1.36-4.67), and chest x-ray findings (adjusted OR 0.39, 95% CI:0.20-0.64). CONCLUSION: Previous NICU admission, bronchopulmonary dyspalsia, and history of previous asthma admissions, tracheosophageal fistula, recurrent aspirations, intensive care admission, intubation and intravenous steroids were significant predictors of asthma short readmission.     

Passing the SNF Test: A Secondary Analysis of a Sepsis Transition Intervention Trial Among Patients Discharged to Post-Acute Care

ObjectivesSepsis survivors discharged to post-acute care facilities experience high rates of mortality and hospital readmission. This study compared the effects of a Sepsis Transition and Recovery (STAR) program vs usual care (UC) on 30-day mortality and hospital readmission among sepsis survivors discharged to post-acute care.DesignSecondary analysis of a multisite pragmatic randomized clinical trial.Setting and ParticipantsSepsis survivors discharged to post-acute care.MethodsWe conducted a secondary analysis of patients from the IMPACTS (Improving Morbidity During Post-Acute Care Transitions for Sepsis) randomized clinical trial who were discharged to post-acute care. IMPACTS evaluated the effectiveness of STAR, a nurse-navigator-led program to deliver best practice post-sepsis care. Subjects were randomized to receive either STAR or UC. The primary outcome was 30-day readmission and mortality. We also evaluated hospital-free days alive as a secondary outcome.ResultsOf 691 patients enrolled in IMPACTS, 175 (25%) were discharged to post-acute care [143 (82%) to skilled nursing facilities, 12 (7%) to long-term acute care hospitals, and 20 (11%) to inpatient rehabilitation]. Of these, 87 received UC and 88 received the STAR intervention. The composite 30-day all-cause mortality and readmission endpoint occurred in 26 (29.9%) patients in the UC group vs 18 (20.5%) in the STAR group [risk difference −9.4% (95% CI −22.2 to 3.4); adjusted odds ratio 0.58 (95% CI 0.28 to 1.17)]. Separately, 30-day all-cause mortality was 8.1% in the UC group compared with 5.7% in the STAR group [risk difference −2.4% (95% CI −9.9 to 5.1)] and 30-day all-cause readmission was 26.4% in the UC group compared with 17.1% in the STAR program [risk difference −9.4% (95% CI −21.5 to 2.8)].Conclusions and ImplicationsThere are few proven interventions to reduce readmission among patients discharged to post-acute care facilities. These results suggest the STAR program may reduce 30-day mortality and readmission rates among sepsis survivors discharged to post-acute care facilities.     

Do Hospital Length of Stay and Staffing Ratio Affect Elderly Patients' Risk of Readmission? A Nation‐wide Study of Norwegian Hospitals

OBJECTIVE: To test whether there is an association between hospital operating conditions such as average length of stays (LOS) and staffing ratio, and elderly patients' risk of readmission. DATA SOURCES: The main data source was a national patient database of admissions to all acute-care Norwegian hospitals during the year of 1996. STUDY DESIGN: It is a cross-sectional study, where Cox' regression analysis was used to test the factors acting on the probability of early unplanned readmission (within 30 days), and later occuring ones. The principal hospital variables included average hospital LOS and staffing ratio (discharges per man-years of personnel). Adjusting patient variables in the model included age, gender, and cost-weights of the Diagnosis Related Groups (DRGs). DATA EXTRACTION METHODS: The selected material included discharges from 59 hospitals, and 113,055 elderly patients (> or = 67 years). Multiple admissions to the same hospital were linked together chronologically, and additional hospital data were matched on. To maximize the association between the index stay and the defined outcome (unplanned readmission), no intervening planned admission was accepted. PRINCIPAL FINDINGS: Being admitted to a hospital with relatively short average LOS increased the patient's risk of early readmission significantly. In addition it was found that more intensive care (more staff) could have a compensatory effect. Furthermore, the predictive factors were shown to be time dependent, as hospital variables had much less impact on readmissions occurring late (within 90-180 days). CONCLUSIONS: The results give support to the assumption of a link between hospital operating conditions and patient outcome.     

Machine-Learning Modeling to Predict Hospital Readmission Following Discharge to Post-Acute Care

ObjectivesPrimary purpose was to generate a model to identify key factors relevant to acute care hospital readmission within 90 days from 3 types of post-acute care (PAC) sites: home with home care services (HC), skilled nursing facility (SNF), and inpatient rehabilitation facility (IRF). Specific aims were to (1) examine demographic characteristics of adults discharged to 3 types of PAC sites and (2) compare 90-day acute hospital readmission rate across PAC sites and risk levels.DesignRetrospective, secondary analysis design was used to examine hospital readmissions within 90 days for persons discharged from hospital to SNF, IRF, or HC.Settings and ParticipantsCohort sample was composed of 2015 assessment data from 3,592,995 Medicare beneficiaries, including 1,536,908 from SNFs, 306,878 from IRFs, and 1,749,209 patients receiving HC services.MeasuresInitial level of analysis created multiple patient profiles based on predictive patient characteristics. Second level of analysis consisted of multiple logistic regressions within each profile to create predictive algorithms for likelihood of readmission within 90 days, based on risk profile and PAC site.ResultsTotal sample 90-day hospital readmission rate was 27.48%. Patients discharged to IRF had the lowest readmission rate (23.34%); those receiving HC services had the highest rate (31.33%). Creation of model risk subgroups, however, revealed alternative outcomes. Patients seem to do best (i.e., lowest readmission rates) when discharged to SNF with one exception, those in the very high risk group. Among all patients in the low-, intermediate-, and high-risk groups, the lowest readmission rates occurred among SNF patients.Conclusions and ImplicationsThe proposed model has potential use to stratify patients’ potential risk for readmission as well as optimal PAC destination. Machine-learning modeling with large data sets is a useful strategy to increase the precision accuracy in predicting outcomes among patients who have nonhome discharges from the hospital.