Discharge Destination and Repeat Hospitalizations

Camberg, Lois; Smith, Nancy E.; Beaudet, Marie P.; Daley, Jennifer; Cagan, Michael; Thibault, George E.

doi:10.1097/00005650-199708000-00002

Cited by 64 publications

(73 citation statements)

References 18 publications

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“…7 The majority of studies examining risk factors associated with frequent hospital admissions focus only on patients with specific diagnoses such as HIV, congestive heart failure or psychiatric disease, or in specific age ranges such as infants or the elderly. [8][9][10] This limits the ability of policy makers and providers to determine whether unifying factors that could be targeted for intervention exist amongst a more general population of patients with frequent hospital admissions.…”

Section: Introductionmentioning

confidence: 99%

Medicaid Patients at High Risk for Frequent Hospital Admission: Real-Time Identification and Remediable Risks

et al. 2008

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Patients with frequent hospitalizations generate a disproportionate share of hospital visits and costs. Accurate determination of patients who might benefit from interventions is challenging: most patients with frequent admissions in 1 year would not continue to have them in the next. Our objective was to employ a validated regression algorithm to case-find Medicaid patients at high-risk for hospitalization in the next 12 months and identify intervention-amenable characteristics to reduce hospitalization risk. We obtained encounter data for 36,457 Medicaid patients with any visit to an urban public hospital from 2001 to 2006 and generated an algorithm-based score for hospitalization risk in the subsequent 12 months for each patient (0=lowest, 100= highest). To determine medical and social contributors to the current admission, we conducted in-depth interviews with high-risk hospitalized patients (scores 950) and analyzed associated Medicaid claims data. An algorithm-based risk score 950 was attained in 2,618 (7.2%) patients. The algorithm's positive predictive value was equal to 0.67. During the study period, 139 high-risk patients were admitted: 60 met inclusion criteria and 50 were interviewed. Fifty-six percent cited the Emergency Department as their usual source of care or had none. Sixty-eight percent had 91 chronic medical conditions, and 42% were admitted for conditions related to substance use. Sixty percent were homeless or precariously housed. Mean Medicaid expenditures for the interviewed patients were $39,188 and $84,040 per patient for the years immediately prior to and following study participation, respectively. Findings including high rates of substance use, homelessness, social isolation, and lack of a medical home will inform the design of interventions to improve community-based care and reduce hospitalizations and associated costs.

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Section: Introductionmentioning

confidence: 99%

Medicaid Patients at High Risk for Frequent Hospital Admission: Real-Time Identification and Remediable Risks

et al. 2008

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“…Readmission can be an important outcome of the quality of hospital care for patients with stroke. 3,4 Readmissions within 1 month of discharge may reflect unresolved problems at discharge, 5 the quality of immediate posthospital care, a more chronically ill population, or because of a combination of these factors. 6 A study in the United States provided evidence that patients with acute stroke who were readmitted within 30 days had a worse chance of survival and incurred greater healthcare costs than patients who were not readmitted.…”

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confidence: 99%

“…8 Several studies have been undertaken to examine the frequency of readmissions within 1 month of discharge after stroke, mainly from the United States, Australia, Denmark, and Taiwan (Table 1). [3][4][5][8][9][10][11][12][13][14][15] Common data sources used to calculate hospital readmissions rates include Medicare data, registry data, patient interviews, or medical records. Evidence from these studies show that the frequency of hospital readmissions may vary from 6.5% to ≈24.3%.…”

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confidence: 99%

“…Evidence from these studies show that the frequency of hospital readmissions may vary from 6.5% to ≈24.3%. [3][4][5][8][9][10][11][12][13][14][15] The potential factors that may be associated with being readmitted after an initial hospitalization for stroke can be grouped into 5 broad categories: patient characteristics, social circumstances, health system, clinical care or process, and health outcome ( Figure 1). A recent systematic review and other subsequent studies investigating factors associated with readmission after stroke have focused on <30 factors, which fall mainly within patient or health system categories (Table 1).…”

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confidence: 99%

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Factors Associated With 28-Day Hospital Readmission After Stroke in Australia

Kilkenny

Longworth

Pollack

et al. 2013

Stroke

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Background and Purpose-Understanding the factors that contribute to early readmission after discharge following stroke is limited. We aimed to describe the factors associated with 28-day readmission after hospitalization for stroke. Methods-Factors associated with readmission were classified from the medical record standardized audits of 50 to 100 consecutively admitted patients with stroke from 35 Australian hospitals during multiple time periods (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010).Factors were compared between patients readmitted and not readmitted after stroke hospitalization (n=43) grouped using 5 categories: patient characteristics (n=16; eg, age), clinical processes of care (n=13; eg, admitted into a stroke unit), social circumstances (n=3; eg, living home alone prior), health system (n=6; eg, location of hospital), and health outcome (n=5; eg, length of stay). Multilevel logistic regression modeling was used to examine the association with these independent factors selected if statistical significance P<0.15 or if considered clinically important and readmission status. Results-Among 3328 patients, 6.5% were readmitted within 28 days (mean age, 75; 48% female; 92% ischemic). After bivariate analyses 14/43 factors from 4/5 categories were associated with readmission after hospitalization for stroke. Two factors from patient and health outcome categories remained independently associated with readmission after multivariable analyses. These were dependent premorbid functional status (adjusted odds ratio, 1.87; 95% confidence interval, 1.25-2.81) and having a severe adverse event during the initial hospitalization for stroke (adjusted odds ratio, 2.81; 95% confidence interval, 1.55-5.12). Conclusions-This is the first study to comprehensively evaluate factors associated with 28-day readmission after stroke.The factors associated with 28-day readmission are diverse and include potentially modifiable and nonmodifiable factors. (Stroke. 2013;44:2260-2268.)

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“…ej., coma o gangrena en los pacientes diabéticos) 27,28 o la reducción de los reingresos hospitalarios y de la estancia media (p. ej., insuficiencia cardíaca) 29 . El resumen de las actividades propuestas refleja la importancia de la preLo conocido sobre el tema • Una atención primaria (APS) a tiempo y efectiva puede reducir la hospitalización por los problemas de salud definidos como ambulatory care sensitive conditions (ACSC).…”

Section: Discussionunclassified

Comentario: Hospitalizaciones inadecuadas: un nuevo reto para la atención primaria

Cao

2003

Aten Primaria

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Discharge Destination and Repeat Hospitalizations

Abstract: These findings have important implications for adjusting hospital performance profiles based on discharge destination and for focussing efforts to reduce the frequency and associated costs of hospital readmissions.

Cited by 64 publications

References 18 publications

Medicaid Patients at High Risk for Frequent Hospital Admission: Real-Time Identification and Remediable Risks

Medicaid Patients at High Risk for Frequent Hospital Admission: Real-Time Identification and Remediable Risks

Factors Associated With 28-Day Hospital Readmission After Stroke in Australia

Comentario: Hospitalizaciones inadecuadas: un nuevo reto para la atención primaria

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