Dataset Information

Comparing Dementia Classification by Self-Report and Administrative Records in the National Core Indicators-Aging and Disability Survey: A Predictive Modeling Approach.

ABSTRACT: Policymakers are interested in the long-term services and supports (LTSS) needs of people living with dementia. The National Core Indicators-Aging and Disability (NCI-AD) survey is conducted to evaluate LTSS care needs. However, dementia reporting in NCI-AD varies across states, and is either obtained from state administrative records or self-reported during the survey. We explored the implications of identifying dementia from administrative records versus self-report. We analyzed 24,569 NCI-AD respondents age 65+, of which 22.4% had dementia. To assess dementia accuracy by data source, we fit separate logistic regression models using the administrative and self-reported subsamples. We applied model coefficients to the population whose dementia status came from the opposite source. Using the administrative model to predict self-reported dementia resulted in higher sensitivity than using the self-report model to predict administrative dementia (43.8% vs. 37.9%). The self-report model's diminished sensitivity suggests administrative records may capture cases of dementia missed by self-report.

SUBMITTER: Mulcahy JF

PROVIDER: S-EPMC10524095 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Publications

Comparing Dementia Classification by Self-Report and Administrative Records in the National Core Indicators-Aging and Disability Survey: A Predictive Modeling Approach.

Mulcahy John F JF Bucy Taylor T Shippee Tetyana T Jutkowitz Eric E

Journal of applied gerontology : the official journal of the Southern Gerontological Society 20230417 9

Policymakers are interested in the long-term services and supports (LTSS) needs of people living with dementia. The National Core Indicators-Aging and Disability (NCI-AD) survey is conducted to evaluate LTSS care needs. However, dementia reporting in NCI-AD varies across states, and is either obtained from state administrative records or self-reported during the survey. We explored the implications of identifying dementia from administrative records versus self-report. We analyzed 24,569 NCI-AD ...[more]

PMID: 37070133

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Project description:ObjectiveThis study aimed to evaluate the value of odors in the olfactory identification (OI) test and other known risk factors for predicting incident dementia in the prospective Shanghai Aging Study.MethodsAt baseline, OI was assessed using the Sniffin' Sticks Screening Test 12, which contains 12 different odors. Cognition assessment and consensus diagnosis were conducted at both baseline and follow-up to identify incident dementia. Four different multivariable logistic regression (MLR) models were used for predicting incident dementia. In the no-odor model, only demographics, lifestyle, and medical history variables were included. In the single-odor model, we further added one single odor to the first model. In the full model, all 12 odors were included. In the stepwise model, the variables were selected using a bidirectional stepwise selection method. The predictive abilities of these models were evaluated by the area under the receiver operating characteristic curve (AUC). The permutation importance method was used to evaluate the relative importance of different odors and other known risk factors.ResultsSeventy-five (8%) incident dementia cases were diagnosed during 4.9 years of follow-up among 947 participants. The full and the stepwise MLR model (AUC = 0.916 and 0.914, respectively) have better predictive abilities compared with those of the no- or single-odor models. The five most important variables are Mini-Mental State Examination (MMSE) score, age, peppermint detection, coronary artery disease, and height in the full model, and MMSE, age, peppermint detection, stroke, and education in the stepwise model. The combination of only the top five variables in the stepwise model (AUC = 0.901 and sensitivity = 0.880) has as a good a predictive ability as other models.ConclusionThe ability to smell peppermint might be one of the useful indicators for predicting dementia. Combining peppermint detection with MMSE, age, education, and history of stroke may have sensitive and robust predictive value for dementia in older adults.

Project description:BackgroundCongenital anomalies are a major cause of co-morbidity in children. Diagnostic code lists are increasingly used to identify congenital anomalies in administrative health records. Evidence is lacking on comparability of these code lists.ObjectivesTo compare prevalence of congenital anomalies and prognostic outcomes for children with congenital anomalies identified in administrative health records using three different code lists.MethodsWe developed national cohorts of singleton livebirths in England (n = 7 354 363, 2003-2014) and Scotland (n = 493 556, 2003-2011). Children with congenital anomalies were identified if congenital anomaly diagnosis was recorded at birth, during subsequent hospital admission or as cause of death before 2 years old. We used three code lists: the EUROCAT list for congenital anomaly surveillance in Europe; the Hardelid list developed to identify children with chronic conditions (including congenital anomalies) admitted to hospital in England; and the Feudtner list developed to indicate children with complex chronic conditions (including congenital anomalies) admitted to hospitals in the United States. We compared prevalence, and risks of postnatal hospital readmission and death according to each code list in England and Scotland.ResultsPrevalence of congenital anomalies was highest using the EUROCAT list (4.1% of livebirths in England, 3.7% in Scotland), followed by Hardelid (3.1% and 3.0% of livebirths, respectively) and Feudtner (1.8% and 1.5% of livebirths, respectively). 67.2%-73.3% of children with congenital anomalies in England and 65.2%-77.0% in Scotland had at least one postnatal hospital admission across the three code lists; mortality ranged between 42.6-75.4 and 41.5-88.7 deaths per 1000 births in England Scotland, respectively. The risk of these adverse outcomes was highest using Feudtner and lowest using EUROCAT code lists.ConclusionsThe prevalence of congenital anomalies varied by congenital anomaly code list, over time and between countries, reflecting in part differences in hospital coding practices and admission thresholds. As a minimum, researchers using administrative health data to study congenital anomalies should report sensitivity analyses using different code lists.

Project description:BackgroundThe concept of participation is recognized as an important rehabilitation outcome and instruments have been developed to measure participation using the International Classification of Functioning, Disability and Health (ICF). To date, few studies have examined the content of these instruments to determine how participation has been operationalized. The purpose of this study was to compare the content of participation instruments using the ICF classification.MethodsA systematic literature search was conducted to identify instruments that assess participation according to the ICF. Instruments were considered to assess participation and were included if the domains contain content from a minimum of three ICF chapters ranging from Chapter 3 Communication to Chapter 9 Community, social and civic life in the activities and participation component. The instrument content was examined by first identifying the meaningful concepts in each question and then linking these concepts to ICF categories. The content analysis included reporting the 1) ICF chapters (domains) covered in the activities and participation component, 2) relevance of the meaningful concepts to the activities and participation component and 3) context in which the activities and participation component categories are evaluated.ResultsEight instruments were included: Impact on Participation and Autonomy, Keele Assessment of Participation, Participation Survey/Mobility, Participation Measure-Post Acute Care, Participation Objective Participation Subjective, Participation Scale (P-Scale), Rating of Perceived Participation and World Health Organization Disability Assessment Schedule II (WHODAS II). 1351 meaningful concepts were identified in the eight instruments. There are differences among the instruments regarding how participation is operationalized. All the instruments cover six to eight of the nine chapters in the activities and participation component. The P-Scale and WHODAS II have questions which do not contain any meaningful concepts related to the activities and participation component. Differences were also observed in how other ICF components (body functions, environmental factors) and health are operationalized in the instruments.ConclusionLinking the meaningful concepts in the participation instruments to the ICF classification provided an objective and comprehensive method for analyzing the content. The content analysis revealed differences in how the concept of participation is operationalized and these differences should be considered when selecting an instrument.

Project description:BACKGROUND:Administrative health records (AHRs) and electronic medical records (EMRs) are two key sources of population-based data for disease surveillance, but misclassification errors in the data can bias disease estimates. Methods that combine information from error-prone data sources can build on the strengths of AHRs and EMRs. We compared bias and error for four data-combining methods and applied them to estimate hypertension prevalence. METHODS:Our study included rule-based OR and AND methods that identify disease cases from either or both data sources, respectively, rule-based sensitivity-specificity adjusted (RSSA) method that corrects for inaccuracies using a deterministic rule, and probabilistic-based sensitivity-specificity adjusted (PSSA) method that corrects for error using a statistical model. Computer simulation was used to estimate relative bias (RB) and mean square error (MSE) under varying conditions of population disease prevalence, correlation amongst data sources, and amount of misclassification error. AHRs and EMRs for Manitoba, Canada were used to estimate hypertension prevalence using validated case definitions and multiple disease markers. RESULTS:The OR method had the lowest RB and MSE when population disease prevalence was 10%, and the RSSA method had the lowest RB and MSE when population prevalence increased to 20%. As the correlation between data sources increased, the OR method resulted in the lowest RB and MSE. Estimates of hypertension prevalence for AHRs and EMRs alone were 30.9% (95% CI: 30.6-31.2) and 24.9% (95% CI: 24.6-25.2), respectively. The estimates were 21.4% (95% CI: 21.1-21.7), for the AND method, 34.4% (95% CI: 34.1-34.8) for the OR method, 32.2% (95% CI: 31.8-32.6) for the RSSA method, and ranged from 34.3% (95% CI: 34.1-34.5) to 35.9% (95% CI, 35.7-36.1) for the PSSA method, depending on the statistical model. CONCLUSIONS:The OR and AND methods are influenced by correlation amongst the data sources, while the RSSA method is dependent on the accuracy of prior sensitivity and specificity estimates. The PSSA method performed well when population prevalence was high and average correlations amongst disease markers was low. This study will guide researchers to select a data-combining method that best suits their data characteristics.

Dataset Information

Comparing Dementia Classification by Self-Report and Administrative Records in the National Core Indicators-Aging and Disability Survey: A Predictive Modeling Approach.

Publications

Comparing Dementia Classification by Self-Report and Administrative Records in the National Core Indicators-Aging and Disability Survey: A Predictive Modeling Approach.

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