Dataset Information

Predicting Disability among Community-Dwelling Medicare Beneficiaries Using Claims-Based Indicators.

ABSTRACT:

Objectives

To assess the feasibility of using existing claims-based algorithms to identify community-dwelling Medicare beneficiaries with disability based solely on the conditions for which they are being treated, and improving on these algorithms by combining them in predictive models.

Data source

Data on 12,415 community-dwelling fee-for-service Medicare beneficiaries who first responded to the Medicare Current Beneficiary Survey (MCBS) in 2003-2006.

Study design

Logistic regression models in which six claims-based disability indicators are used to predict self-reported disability. Receiver operating characteristic (ROC) curves were used to assess the performance of the predictive models.

Principal findings

The predictive performance of the regression-based models is better than that of the individual claims-based indicators. At a predicted probability threshold chosen to maximize the sum of sensitivity and specificity, sensitivity is 0.72 for beneficiaries age 65 or older and specificity is 0.65. For those under 65, sensitivity is 0.54 and specificity is 0.67. The findings also suggest ways to improve predictive performance for specific disability populations of interest to researchers.

Conclusions

Predictive models that incorporate multiple claims-based indicators provide an improved tool for researchers seeking to identify people with disabilities in claims data.

SUBMITTER: Ben-Shalom Y

PROVIDER: S-EPMC4722209 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Predicting Disability among Community-Dwelling Medicare Beneficiaries Using Claims-Based Indicators.

Ben-Shalom Yonatan Y Stapleton David C DC

Health services research 20150525 1

<h4>Objectives</h4>To assess the feasibility of using existing claims-based algorithms to identify community-dwelling Medicare beneficiaries with disability based solely on the conditions for which they are being treated, and improving on these algorithms by combining them in predictive models.<h4>Data source</h4>Data on 12,415 community-dwelling fee-for-service Medicare beneficiaries who first responded to the Medicare Current Beneficiary Survey (MCBS) in 2003-2006.<h4>Study design</h4>Logistic ...[more]

PMID: 26015332

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Project description:BackgroundDisability in Activities of Daily Living (ADL) is an adverse outcome of frailty that places a burden on frail elderly people, care providers and the care system. Knowing which physical frailty indicators predict ADL disability is useful in identifying elderly people who might benefit from an intervention that prevents disability or increases functioning in daily life. The objective of this study was to systematically review the literature on the predictive value of physical frailty indicators on ADL disability in community-dwelling elderly people.MethodsA systematic search was performed in 3 databases (PubMed, CINAHL, EMBASE) from January 1975 until April 2010. Prospective, longitudinal studies that assessed the predictive value of individual physical frailty indicators on ADL disability in community-dwelling elderly people aged 65 years and older were eligible for inclusion. Articles were reviewed by two independent reviewers who also assessed the quality of the included studies.ResultsAfter initial screening of 3081 titles, 360 abstracts were scrutinized, leaving 64 full text articles for final review. Eventually, 28 studies were included in the review. The methodological quality of these studies was rated by both reviewers on a scale from 0 to 27. All included studies were of high quality with a mean quality score of 22.5 (SD 1.6). Findings indicated that individual physical frailty indicators, such as weight loss, gait speed, grip strength, physical activity, balance, and lower extremity function are predictors of future ADL disability in community-dwelling elderly people.ConclusionsThis review shows that physical frailty indicators can predict ADL disability in community-dwelling elderly people. Slow gait speed and low physical activity/exercise seem to be the most powerful predictors followed by weight loss, lower extremity function, balance, muscle strength, and other indicators. These findings should be interpreted with caution because the data of the different studies could not be pooled due to large variations in operationalization of the indicators and ADL disability across the included studies. Nevertheless, our study suggests that monitoring physical frailty indicators in community-dwelling elderly people might be useful to identify elderly people who could benefit from disability prevention programs.

Project description:ImportanceFood insecurity has a known association with prevalent impaired cognition. However, it is unknown whether food insecurity has a longitudinal association with cognitive decline among older adults.ObjectiveTo determine whether food insecurity is associated with a faster decline in cognitive function among community-dwelling older adults.Design, setting, and participantsThis retrospective cohort study used data from a nationally representative sample of Medicare beneficiaries 65 years and older recruited for the National Health and Aging Trends Study (NHATS). Community-dwelling NHATS participants were followed up for a maximum of 7 years (mean [SD] follow-up duration, 5.4 [1.1] years). Data were collected from January 1, 2012, to December 31, 2020, and analyzed from December 23, 2021, to December 6, 2022.ExposuresSelf-reported food insecurity assessed from 2012 to 2019.Main outcomes and measuresPrimary outcomes were immediate memory, delayed memory, and executive function collected from 2013 to 2020. Immediate and delayed recall were assessed by a 10-item word-list memory task (range, 0-10, with higher scores indicating more words recalled). Executive function was measured by the clock drawing test (range, 0-5, with higher scores indicating more accurate depiction of a clock). Each year's cognitive functions were linked to the prior year's food insecurity data. Linear mixed-effects models with random slopes and intercepts were used to examine the association between food insecurity and cognitive decline. Analytic weights in each year were applied to represent community-dwelling Medicare beneficiaries 65 years and older in 2011.ResultsOf 3037 participants, a weighted 57.8% (raw count, 1345) were younger than 75 years, 56.2% (raw count, 1777) were women, and most (84.9% [raw count, 2268]) were White. Over 7 years, 417 (weighted proportion, 12.1%) experienced food insecurity at least once. Food insecurity was associated with a faster decline in executive function in a fully adjusted model: the mean difference of annual change in executive function score between people exposed to and not exposed to food insecurity was -0.04 (95% CI, -0.09 to -0.003) points. However, food insecurity was not associated with changes in immediate and delayed memory (0.01 [95% CI, -0.05 to 0.08] and -0.01 [95% CI, -0.08 to 0.06], respectively).Conclusions and relevanceAmong community-dwelling older adults, food insecurity was prevalent and associated with a decline in executive function. Interventions and policies aiming to increase healthy food access or reduce food insecurity should be assessed for their impact on older adults' cognitive outcome.

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Project description:ObjectivesLoss of appetite in older adults can lead to malnutrition, weight loss, frailty, and death, but little is known about its epidemiology in the United States (US). The objective of this study was to estimate the annual prevalence and incidence of anorexia in older adults with Medicare fee-for-service (FFS) health insurance.DesignRetrospective and observational analysis of administrative health insurance claims data.SettingThis study included Medicare FFS claims from all settings (eg, hospital inpatient/outpatient, office, assisted living facility, skilled nursing facility, hospice, rehabilitation facility, home).ParticipantsThis study included all individuals aged 65 to 115 years old with continuous Medicare FFS medical coverage (Parts A and/or B) for at least one 12-month period from October 1, 2015, to September 30, 2021 (ie, approximately 30 million individuals each year).InterventionNot applicable.MeasurementsAnorexia was identified using medical claims with the ICD-10 diagnosis code "R63.0: Anorexia". This study compared individuals with anorexia to a control group without anorexia with respect to demographics, comorbidities using the Charlson Comorbidity Index (CCI), Claims-based Frailty Index (CFI), and annual mortality. The annual prevalence and incidence of anorexia were estimated for each 12-month period from October 1, 2015, to September 30, 2021.ResultsThe number of individuals with anorexia ranged from 317,964 to 328,977 per year, a mean annual prevalence rate of 1.1%. The number of individuals newly diagnosed with anorexia ranged from 243,391 to 281,071 per year, a mean annual incidence rate of 0.9%. Individuals with anorexia had a mean (±standard deviation) age of 80.5±8.7 years (vs 74.9±7.5 years without anorexia; p<.001), 64.4% were female (vs 53.8%; p<.001), and 78.4% were White (vs 83.2%; p<.001). The most common CCI comorbidities for those with anorexia were chronic pulmonary disease (39.4%), dementia (38.3%), and peripheral vascular disease (38.0%). Median (interquartile range [IQR]) CCI with anorexia was 4 [5] (vs 1 [3] without anorexia; p<.001). The annual mortality rate among those with anorexia was 22.3% (vs 4.1% without anorexia; relative risk 5.49 [95% confidence interval, 5.45-5.53]).ConclusionApproximately 1% of all adults aged 65-115 years old with Medicare FFS insurance are diagnosed with anorexia each year based on ICD-10 codes reported in claims. These individuals have a higher comorbidity burden and an increased risk of annual mortality compared to those without a diagnosis of anorexia. Further analyses are needed to better understand the relationship between anorexia, comorbidities, frailty, mortality, and other health outcomes.

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Dataset Information

Predicting Disability among Community-Dwelling Medicare Beneficiaries Using Claims-Based Indicators.

Objectives

Data source

Study design

Principal findings

Conclusions

Publications

Predicting Disability among Community-Dwelling Medicare Beneficiaries Using Claims-Based Indicators.

Similar Datasets

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