Dataset Information

Predicting Risk of Potentially Preventable Hospitalization in Older Adults with Dementia.

ABSTRACT: OBJECTIVES:Reducing potentially preventable hospitalization (PPH) among older adults with dementia is a goal of Healthy People 2020, yet no tools specifically identify patients with dementia at highest risk. The objective was to develop a risk prediction model to identify older adults with dementia at high imminent risk of PPH. DESIGN:A 30-day risk prediction model was developed using multivariable logistic regression. Patients from fiscal years (FY) 2009 to 2011 were split into development and validation cohorts; FY2012 was used for prediction. SETTING:Community-dwelling older adults (?65 years of age) with dementia who received care through the Veterans Health Administration. PARTICIPANTS:There were 1 793 783 participants. MEASUREMENTS:Characteristics associated with hospitalization risk were (1) age and other demographic factors; (2) outpatient, emergency department, and inpatient utilization; (3) medical and psychiatric diagnoses; and (4) prescribed medication use including changes to psychotropic medications (eg, initiation or dosage increase). Model discrimination was determined by the C statistic for each of the three cohorts. Finally, to determine whether predicted 30-day risk strata were stable over time, the observed PPH rate was calculated out to 1 year. RESULTS:In the development cohort, .6% of patients experienced PPH within 30?days. The C statistic for the development cohort was .83 (95% confidence interval [CI] = .83-.84) and .83 in the prediction cohort (95% CI = .82-.84). Patients in the top 10% of predicted 30-day PPH risk accounted for more than 50% of 30-day PPH admissions in all three cohorts. In addition, those predicted to be at elevated 30-day risk remained at higher risk throughout a year of follow-up. CONCLUSION:It is possible to identify older adults with dementia at high risk of imminent PPH, and their risk remains elevated for an entire year. Given the negative outcomes associated with acute hospitalization for those with dementia, healthcare systems and providers may be able to engage these high-risk patients proactively to avoid unnecessary hospitalization. J Am Geriatr Soc 67:2077-2084, 2019.

SUBMITTER: Maust DT

PROVIDER: S-EPMC6896207 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Predicting Risk of Potentially Preventable Hospitalization in Older Adults with Dementia.

Maust Donovan T DT Kim H Myra HM Chiang Claire C Langa Kenneth M KM Kales Helen C HC

Journal of the American Geriatrics Society 20190618 10

<h4>Objectives</h4>Reducing potentially preventable hospitalization (PPH) among older adults with dementia is a goal of Healthy People 2020, yet no tools specifically identify patients with dementia at highest risk. The objective was to develop a risk prediction model to identify older adults with dementia at high imminent risk of PPH.<h4>Design</h4>A 30-day risk prediction model was developed using multivariable logistic regression. Patients from fiscal years (FY) 2009 to 2011 were split into d ...[more]

PMID: 31211418

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Project description:Background/objectivesDementia is associated with higher healthcare expenditures, in large part due to increased hospitalization rates relative to patients without dementia. Data on contemporary trends in the incidence and outcomes of potentially preventable hospitalizations of patients with dementia are lacking.DesignRetrospective cohort study using the National Inpatient Sample from 2012 to 2016.SettingU.S. acute care hospitals.ParticipantsA total of 1,843,632 unique hospitalizations of older adults (aged ≥65 years) with diagnosed dementia.MeasurementsAnnual trends in the incidence of hospitalizations for all causes and for potentially preventable conditions including acute ambulatory care sensitive conditions (ACSCs), chronic ACSCs, and injuries. In-hospital outcomes including mortality, discharge disposition, and hospital costs.ResultsThe survey weighted sample represented an estimated 9.27 million hospitalizations for patients with diagnosed dementia (mean [standard deviation] age = 82.6 [6.7] years; 61.4% female). In total, 3.72 million hospitalizations were for potentially preventable conditions (40.1%), 2.07 million for acute ACSCs, .76 million for chronic ACSCs, and .89 million for injuries. Between 2012 and 2016, the incidence of all-cause hospitalizations declined from 1.87 million to 1.85 million per year (P = .04) while the incidence of potentially preventable hospitalizations increased from .75 million to .87 million per year (P < .001), driven by an increased number of hospitalizations of community-dwelling older adults. Among patients with dementia hospitalized for potentially preventable conditions, inpatient mortality declined from 6.4% to 6.1% (P < .001), inflation-adjusted median costs increased from $7,319 to $7,543 (P < .001), and total annual costs increased from $7.4 to $9.3 billion. Although 86.0% of hospitalized patients were admitted from the community, only 32.7% were discharged to the community.ConclusionThe number of potentially preventable hospitalizations of older adults with dementia is increasing, driven by hospitalizations of community-dwelling older adults. Improved strategies for early detection and goal-directed treatment of potentially preventable conditions in patients with dementia are urgently needed. J Am Geriatr Soc 68:2240-2248, 2020.

Project description:BackgroundA significant number of late middle-aged adults with depression have a high illness burden resulting from chronic conditions which put them at high risk of hospitalization. Many late middle-aged adults are covered by commercial health insurance, but such insurance claims have not been used to identify the risk of hospitalization in individuals with depression. In the present study, we developed and validated a non-proprietary model to identify late middle-aged adults with depression at risk for hospitalization, using machine learning methods.MethodsThis retrospective cohort study involved 71,682 commercially insured older adults aged 55-64 years diagnosed with depression. National health insurance claims were used to capture demographics, health care utilization, and health status during the base year. Health status was captured using 70 chronic health conditions, and 46 mental health conditions. The outcomes were 1- and 2-year preventable hospitalization. For each of our two outcomes, we evaluated seven modelling approaches: four prediction models utilized logistic regression with different combinations of predictors to evaluate the relative contribution of each group of variables, and three prediction models utilized machine learning approaches - logistic regression with LASSO penalty, random forests (RF), and gradient boosting machine (GBM).ResultsOur predictive model for 1-year hospitalization achieved an AUC of 0.803, with a sensitivity of 72% and a specificity of 76% under the optimum threshold of 0.463, and our predictive model for 2-year hospitalization achieved an AUC of 0.793, with a sensitivity of 76% and a specificity of 71% under the optimum threshold of 0.452. For predicting both 1-year and 2-year risk of preventable hospitalization, our best performing models utilized the machine learning approach of logistic regression with LASSO penalty which outperformed more black-box machine learning models like RF and GBM.ConclusionsOur study demonstrates the feasibility of identifying depressed middle-aged adults at higher risk of future hospitalization due to burden of chronic illnesses using basic demographic information and diagnosis codes recorded in health insurance claims. Identifying this population may assist health care planners in developing effective screening strategies and management approaches and in efficient allocation of public healthcare resources as this population transitions to publicly funded healthcare programs, e.g., Medicare in the US.

Project description:ObjectivesApproximately 14% of Medicare beneficiaries are readmitted to a hospital within 30 days of home health care admission. Individuals with dementia account for 30% of all home health care admissions and are at high risk for readmission. Our primary objective was to determine the association between dementia severity at admission to home health care and 30-day potentially preventable readmissions (PPR) during home health care. A secondary objective was to develop a dementia severity scale from Outcome and Assessment Information Set (OASIS) items based on the Functional Assessment Staging Tool (FAST).DesignRetrospective cohort study.Setting and participantsHome health care; 126,292 Medicare beneficiaries receiving home health care (July 1, 2013-June 1, 2015) diagnosed with dementia (ICD-9 codes).Measures30-day PPR during home health care. Dementia severity categorized into 6 levels (nonaffected to severe).ResultsThe overall rate of 30-day PPR was 7.6% [95% confidence interval (CI) 7.4, 7.7] but varied by patient and health care utilization characteristics. After adjusting for sociodemographic and clinical characteristics, the odds ratio (OR) for dementia severity category 6 was 1.37 (95% CI 1.29, 1.46) and the OR for category 7 was 1.94 (95% CI 1.64, 2.31) as compared to dementia severity category 1/2.Conclusions and implicationsDementia severity in the later stages is associated with increased risk for potentially preventable readmissions. Our findings suggest that individuals admitted to home health during the later stages of Alzheimer's disease and related dementias may require greater supports and specialized care to minimize negative outcomes such as readmissions. Development of a dementia severity scale based on OASIS items and the FAST is feasible. Future research is needed to determine effective strategies for decreasing potentially preventable readmissions of individuals with severe dementia who receive home health care. Future research is also needed to validate the proposed dementia severity categories used in this study.

Project description:Background and objectivesAlthough patients with CKD are commonly hospitalized, little is known about those with frequent hospitalization and/or longer lengths of stay (high inpatient use). The objective of this study was to explore clinical characteristics, patterns of hospital use, and potentially preventable acute care encounters among patients with CKD with at least one hospitalization.Design, setting, participants, & measurementsWe identified all adults with nondialysis CKD (eGFR<60 ml/min per 1.73 m2) in Alberta, Canada between January 1 and December 31, 2009, excluding those with prior kidney failure. Patients with CKD were linked to administrative data to capture clinical characteristics and frequency of hospital encounters, and they were followed until death or end of study (December 31, 2012). Patients with one or more hospital encounters were categorized into three groups: persistent high inpatient use (upper 5% of inpatient use in 2 or more years), episodic high use (upper 5% in 1 year only), or nonhigh use (lower 95% in all years). Within each group, we calculated the proportion of potentially preventable hospitalizations as defined by four CKD-specific ambulatory care sensitive conditions: heart failure, hyperkalemia, volume overload, and malignant hypertension.ResultsDuring a median follow-up of 3 years, 57,007 patients with CKD not on dialysis had 118,671 hospitalizations, of which 1.7% of patients were persistent high users, 12.3% were episodic high users, and 86.0% were nonhigh users of hospital services. Overall, 24,804 (20.9%) CKD-related ambulatory care sensitive condition encounters were observed in the cohort. The persistent and episodic high users combined (14% of the cohort) accounted for almost one half (45.5%) of the total ambulatory care sensitive condition hospitalizations, most of which were attributed to heart failure and hyperkalemia. Risk of hospitalization for any CKD-specific ambulatory care sensitive condition was higher among older patients, higher CKD stage, lower income, registered First Nations status, and those with poor attachment to primary care.ConclusionsMany hospitalizations among patients with CKD and high inpatient use are ambulatory care sensitive condition related, suggesting opportunities to improve outcomes and reduce cost by focusing on better community-based care for this population.

Dataset Information

Predicting Risk of Potentially Preventable Hospitalization in Older Adults with Dementia.

Publications

Predicting Risk of Potentially Preventable Hospitalization in Older Adults with Dementia.

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