Risk Factor Assessment of Hospice Patients Readmitted within 7 Days of Acute Care Hospital Discharge
Anthony WilsonDiana Martins-WelchMyia S. WilliamsLeanne M. TortezAndrzej KozikowskiBridget EarleLori AttivissimoLisa RosenRenée Pekmezaris
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Factors surrounding readmission rates for hospice patients within seven days are still relatively unknown. The present study specifically investigates the seven-day readmission rate of patients newly discharged to hospice, and the predictive factors associated with readmission for this population. In a retrospective case-control study, we seek to identify potential predictors by comparing the characteristics of patients discharged to hospice and readmitted within one week to patients who were not readmitted. Cases (n = 46) were patients discharged to home hospice and readmitted to the hospital within seven days. Controls (n = 117) were patients discharged to home hospice and not readmitted to the hospital within seven days. Significant risk factors for readmission within seven days were found to be: age (p < 0.01), race (p < 0.001), language (p < 0.001), and insurance (p < 0.001). Further study of these predictors may identify opportunities for interventions that address patient and family concerns that may lead to readmission.Keywords:
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Objective Frailty is an important prognostic factor in hospitalised patients but typically requires face-to-face assessment by trained observers to detect. Thus, frail patients are not readily apparent from a systems perspective for those interested in implementing quality improvement measures to optimise their outcomes. This study was designed to externally validate and compare two recently described tools using administrative data as potential markers for frailty: the Hospital Frailty Risk Score (HFRS) and the Hospital-patient One-year Mortality Risk (HOMR) Score. Design Retrospective cohort study. Setting Ontario, Canada. Participants All patients over 75 with at least one urgent non-psychiatric hospitalisation between 2004 and 2010. Main outcome measures Prolonged hospital length of stay (>10 days), 30-day mortality after admission and 30-day postdischarge rates of urgent readmission or emergency department (ED) visits. Results In 452 785 patients (25.9% with intermediate or high-risk HFRS), increased HFRS was associated with higher Charlson scores, older age and decreased likelihood of baseline independence. Patients with high or intermediate HFRS had significantly increased risks of prolonged hospitalisation (70.0% (OR 8.64, 95% CI 8.30 to 8.99) or 49.7% (OR 3.66, 95% CI 3.60 to 3.71) vs 21.3% in low-risk HFRS group) and 30-day mortality (15.5% (OR 1.27, 95% CI 1.20 to 1.33) or 16.8% (OR 1.39, 95% CI 1.36 to 1.41) vs 12.7% in low-risk), but decreased risks of 30-day readmission (10.0% (OR 0.74, 95% CI 0.69 to 0.79) and 11.2% (OR 0.84, 95% CI 0.82 to 0.86) vs 13.1%) or ED visit (7.3% (OR 0.41, 95% CI 0.38 to 0.45) and 11.1% (OR 0.66, 95% CI 0.38 to 0.45) vs 16.0%). Although only loosely associated (Pearson correlation coefficient 0.265, p<0.0001), both the HFRS and HOMR Score were independently associated with each outcome—HFRS was more strongly associated with prolonged length of stay (C-statistic 0.71) and HOMR Score was more strongly associated with 30-day mortality (C-statistic 0.71). Both poorly predicted 30-day readmissions (C-statistics 0.52 for HFRS and 0.54 for HOMR Score). Conclusions The HFRS best identified hospitalised older patients at higher risk of prolonged length of stay and the HOMR score better predicted 30-day mortality. However, neither score was suitable for predicting risk of readmission or ED visit in the 30 days after discharge. Thus, a single score is inadequate to prognosticate for all outcomes associated with frailty.
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Abstract Background: Higher prevalence rate of patients with prolonged mechanical ventilation, among them have ventilated at home. However, unplanned hospital readmission of home ventilated patients remains a critical issue. Therefore, to explore the characteristics and prognosis of unplanned readmissions of patients using a home ventilator and to analyze relevant pre-discharge factors that affect such unplanned readmissions. Methods: A retrospective study was conducted to collect medical record data for 2013–2017 on the readmission of home-ventilated patients in a medical center in northern Taiwan. In all, 127 cases were considered. Unplanned readmissions were divided by time intervals (≤ 30 days, 31–180 days, 181–365 days, ≥ 366 days) into an early readmission group (≤ 30 days) and a late readmission group (≥ 31 days). Statistical analysis, a chi-square test, and a multivariate logistic regression analysis model were used to verify the factors influencing the readmission of home-ventilated patients. Results: Patients’ populations according to the intervals of unplanned readmission (≤ 30 days, 31–180 days, 181–365 days, ≥ 366 days) were 42 (33.1%), 60 (47.2%), 17 (13.4%), and 8 (6.3%), respectively. The average intervals of home care for the early readmission group (≤ 30 days) and the late readmission group (≥ 31 days) were 15.1 ± 9.2 and 164.8 ± 143.2 days, respectively. Regarding risk factors of early and late unplanned hospital readmission, the odds ratio (OR) for patients with chronic cardiovascular disease compared with those without this disease was 4.535 (95% CI 1.253 -16.413). For maximum inspiratory pressure ≦ −30 cmH2O compared with > −30 cmH2O, the OR for early readmission was 0.207 (95% CI 0.056 - 0.767). For hemoglobin ≥ 10.1 g/dL compared with < 10.1 g/dL, the OR of early readmission was 0.280 (95% CI 0.082 - 0.958). Conclusion: Pre-discharge problems, including chronic cardiovascular disease, maximum inspiratory pressure, and reduced hemoglobin, are risk factors for unplanned early hospitalization readmission of patients using a ventilator at home. Therefore, attention should be paid to these risk factors during discharge planning.
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There is a lack of published literature that measures the impact of transitional care pharmacist (TCP) medication-related interventions within the skilled nursing facility (SNF) setting.To evaluate the impact of TCP medication-related interventions on 30-day hospital readmissions among SNF patients compared to current standard of care.This was a retrospective pilot study. All patients included in the study were discharged from an inpatient facility to a SNF. The control group received transitional services from a care team with no pharmacist. The intervention group received transitional services from a care team plus a pharmacist.The 30-day readmission rates in the intervention group were 14 (12%)/116 compared to the control group, 19 (16%)/116; however, the difference was not statistically significant (P = .35). The median time to readmission was statistically significantly longer in the intervention group, 17.5 days, compared to the control group, 10 days (P = .02). One hundred seventy-four medication-related interventions were performed in the intervention group during the study period.This study demonstrates that TCP interventions in an SNF are associated with a significant delay in readmission. A continuation of the pilot program may show a role in reducing all-cause 30-day readmission and ED visit rates.
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Background Previous studies have shown that approximately 20% of hospital readmissions can be medication-related and 70% of these readmissions are possibly preventable. This retrospective medical records study aimed to find risk factors associated with medication-related readmissions to hospital within 30 days of discharge in older adults (≥65 years). Methods 30-day readmissions (n = 360) were assessed as being either possibly or unlikely medication-related after which selected variables were used to individually compare the two groups to a comparison group (n = 360). The aim was to find individual risk factors of possibly medication-related readmissions focusing on living arrangements, polypharmacy, potentially inappropriate medication therapy, and changes made to medication regimens at initial discharge. Results A total of 143 of the 360 readmissions (40%) were assessed as being possibly medication-related. Charlson Comorbidity Index (OR 1.15, 95%CI 1.5–1.25), excessive polypharmacy (OR 1.74, 95%CI 1.07–2.81), having adjustments made to medication dosages at initial discharge (OR 1.63, 95%CI 1.03–2.58) and living in your own home, alone, were variables identified as risk factors of such readmissions. Living in your own home, alone, increased the odds of a possibly medication-related readmission 1.69 times compared to living in your own home with someone (p-value 0.025) and 2.22 times compared to living in a nursing home (p-value 0.037). Conclusion Possibly medication-related readmissions within 30 days of discharge, in patients 65 years and older, are common. The odds of such readmissions increase in comorbid, highly medicated patients living in their own home, alone, and if having medication dosages adjusted at initial discharge. These results indicate that care planning before discharge and the provision of help with, for example, managing medications after discharge, are factors especially important if aiming to reduce the amount of medication-related readmissions among this population. Further research is needed to confirm this hypothesis.
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Abstract Exploring the characteristics and prognosis of unplanned readmissions of patients using a home ventilator and analyzing relevant pre-discharge factors that affect such unplanned readmissions.A retrospective study was conducted to collect medical record data for 2013–2017 on the readmission of home-ventilated patients in a medical center in northern Taiwan. The average intervals of home care for the early readmission group (≤ 30 days) and the late readmission group (≥ 31 days) were 15.1 ± 9.2 and 164.8 ± 143.2 days, respectively. Regarding risk factors of early and late unplanned hospital readmission, the odds ratio (OR) for patients with chronic cardiovascular disease compared with those without this disease was 4.535 (95% CI 1.253 -16.413). For maximum inspiratory pressure ≦ −30 cmH2O compared with > −30 cmH2O, the OR for early readmission was 0.207 (95% CI 0.056 - 0.767). For hemoglobin ≥ 10.1 g/dL compared with < 10.1 g/dL, the OR of early readmission was 0.280 (95% CI 0.082 - 0.958). So, pre-discharge problems, including chronic cardiovascular disease, maximum inspiratory pressure, and reduced hemoglobin, are risk factors for unplanned early hospitalization readmission of patients using a ventilator at home. Therefore, attention should be paid to these risk factors during discharge planning.
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Reducing hospital readmissions requires deploying appropriate interventions to groups at highest risk for readmission. Long-term medication adherence may indicate one's ability to manage recovery and chronic illness after discharge. If so, medication adherence also may be a predictor of hospital readmission.The objective of this study was to test the association of long-term medication adherence with hospital readmission in a cohort of beneficiaries enrolled in a Medicare Cost Plan.The study employed a retrospective cohort design using administrative pharmacy and health care claims for a sample hospitalized in 2009. Medication adherence was measured with the medication possession ratio (MPR) for the 12 months prior to the first hospitalization in 2009. The likelihood of readmission within 30 days from the first hospitalization in 2009 was estimated using the logistic regression model.Long-term medication adherence was not associated with likelihood of 30-day hospital readmission (odds ratio [OR] = 0.82, P = .71). However, older age (OR = 1.07, P = .003) and longer length of hospital stay (OR = 1.2, P < .001) were associated with higher likelihood of 30-day readmission, while having an office visit within 30 days of discharge (OR = 0.38, P = .03) was associated with lower odds of readmission.Except for older age, variables associated with likelihood of readmission are difficult for clinical teams to access during a hospital stay to identify those at risk for readmission. Additional work is needed to identify indicators of readmission risk that can be utilized during hospitalization to identify patients needing post-discharge support to help prevent readmission.
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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.
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