Multimorbidity in Medicare Beneficiaries: Performance of an ICD‐Coded Multimorbidity‐Weighted Index

Wei, Melissa Y.; Ratz, David; Mukamal, Kenneth J.

doi:10.1111/jgs.16310

Cited by 25 publications

(67 citation statements)

References 20 publications

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“…Codes were identified and checked independently for agreement by four individuals (including authors MYW, JEL, CC). To validate the accuracy of these mapped conditions without validation studies and the overall mapping of ICD-9 codes to conditions in the multimorbidity-weighted index, we examined the construct validity and conducted direct comparisons of the ICD-coded multimorbidityweighted index with traditional metrics [7].…”

Section: Resultsmentioning

confidence: 99%

“…We examined 81 chronic conditions in the multimorbidityweighted index that predicts HRQOL [5] and created a comprehensive mapping of ICD-9 codes for each of these conditions [7] (Additional File, Table 1).…”

Section: Candidate Condition Selectionmentioning

confidence: 99%

“…Prevalence was determined using any ICD-9 codes available for each condition [7] from 8933 Health and Retirement Study participants who provided access to their Medicare outpatient, inpatient, or skilled nursing facility claims in 2014. ICD-9 codes for the 10 most prevalent conditions are summarized in Table 1.…”

Section: Validation Statisticsmentioning

confidence: 99%

“…The index was externally validated in the nationally-representative Health and Retirement Study, with additional physical and cognitive functioning outcomes assessed to demonstrate construct validity [6]. Finally, the conditions were mapped to ICD-9 codes and validated in HRS-Medicare data to facilitate use in claims data [7]. These 81 conditions also predict mortality, HRQOL, social participation, and disability [6,[8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

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Comprehensive review of ICD-9 code accuracies to measure multimorbidity in administrative data

Wei

Luster

Chan

et al. 2020

BMC Health Serv Res

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Background: Quantifying the burden of multimorbidity for healthcare research using administrative data has been constrained. Existing measures incompletely capture chronic conditions of relevance and are narrowly focused on risk-adjustment for mortality, healthcare cost or utilization. Moreover, the measures have not undergone a rigorous review for how accurately the components, specifically the International Classification of Diseases, Ninth Revision (ICD-9) codes, represent the chronic conditions that comprise the measures. We performed a comprehensive, structured literature review of research studies on the accuracy of ICD-9 codes validated using external sources across an inventory of 81 chronic conditions. The conditions as a weighted measure set have previously been demonstrated to impact not only mortality but also physical and mental health-related quality of life. Methods: For each of 81 conditions we performed a structured literature search with the goal to identify 1) studies that externally validate ICD-9 codes mapped to each chronic condition against an external source of data, and 2) the accuracy of ICD-9 codes reported in the identified validation studies. The primary measure of accuracy was the positive predictive value (PPV). We also reported negative predictive value (NPV), sensitivity, specificity, and kappa statistics when available. We searched PubMed and Google Scholar for studies published before June 2019. Results: We identified studies with validation statistics of ICD-9 codes for 51 (64%) of 81 conditions. Most of the studies (47/51 or 92%) used medical chart review as the external reference standard. Of the validated using medical chart review, the median (range) of mean PPVs was 85% (39-100%) and NPVs was 91% (41-100%). Most conditions had at least one validation study reporting PPV ≥70%. Conclusions: To help facilitate the use of patient-centered measures of multimorbidity in administrative data, this review provides the accuracy of ICD-9 codes for chronic conditions that impact a universally valued patientcentered outcome: health-related quality of life. These findings will assist health services studies that measure chronic disease burden and risk-adjust for comorbidity and multimorbidity using patient-centered outcomes in administrative data.

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Section: Resultsmentioning

confidence: 99%

Section: Candidate Condition Selectionmentioning

confidence: 99%

Section: Validation Statisticsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Comprehensive review of ICD-9 code accuracies to measure multimorbidity in administrative data

Wei

Luster

Chan

et al. 2020

BMC Health Serv Res

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“…Em sua maioria, estes sintomas ou padrões implicam perda funcional de maior ou menor magnitude e o fato de ocorrerem de forma concomitante, muitas vezes, dificulta a avaliação precisa. Nesse sentido, Wei et al, (2020) desenvolveram e validaram um índice ponderado por multimorbidade, que incorpora o funcionamento físico por meio de ponderações de doenças em idosos participantes do Health and Retirement Study (HRS). Dessa forma, a avaliação adequada de tais comorbidades e do seu impacto na funcionalidade e qualidade de vida dos idosos pode ser uma ferramenta útil no manejo clínico desta população.…”

Section: Discussionunclassified

Expectativa de vida com e sem multimorbidade entre idosos brasileiros: Pesquisa Nacional de Saúde 2013

Guimarães

Andrade

2020

Rev. bras. estud. popul.

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O objetivo do presente estudo é analisar diferenças na expectativa de vida com e sem multimorbidade (duas ou mais condições crônicas) entre idosos nos estados brasileiros, segundo sexo e idade. Foram utilizados os dados de mortalidade do Sistema de Informações sobre Mortalidade e projeções populacionais do Instituto Brasileiro de Geografia e Estatística (IBGE) para elaborar tábuas de vida para os estados, por sexo. Informação sobre a prevalência de multimorbidade foi obtida a partir da Pesquisa Nacional de Saúde (PNS) de 2013. A partir do método de Sullivan, estimaram-se a expectativa de vida com e sem multimorbidade e a proporção de anos vividos com multimorbidade. A amostra de idosos da PNS possuía um total de 11.697 entrevistados, cuja idade média foi de 70,08 anos (DP 0,09 ano). A proporção de anos a serem vividos com multimorbidade aumenta com a idade (53,6% aos 60 anos e 57,3% aos 75 anos). Mulheres possuem expectativa de vida maior do que os homens, mas convivem mais com multimorbidade. Aos 60 anos, as mulheres brasileiras esperam viver, em média, 13,5 anos com multimorbidade e os homens 8,3 anos. Constatou-se grande diferença na expectativa de vida com multimorbidade quando comparadas as unidades da federação, com amplitude de 8,2 a 14,2 anos (aos 60 anos de idade). É importante considerar estas diferenças na priorização de ações e grupos para intervenção em saúde pública.

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Medication and Road Test Performance Among Cognitively Healthy Older Adults

Carr,

Beyene,

Doherty

et al. 2023

JAMA Netw Open

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ImportanceOlder adults are increasingly prescribed medications that have adverse effects. Prior studies have found a higher risk of motor vehicle crashes to be associated with certain medication use.ObjectiveTo determine whether specific medication classes were associated with performance decline as assessed by a standardized road test in a community sample of cognitively healthy older adults, to evaluate additional associations of poor road test performance with comorbid medical conditions and demographic characteristics, and to test the hypothesis that specific medication classes (ie, antidepressants, benzodiazepines, sedatives or hypnotics, anticholinergics, antihistamines, and nonsteroidal anti-inflammatory drugs or acetaminophen) would be associated with an increase in risk of impaired driving performance over time.Design, Setting, and ParticipantsThis was a prospective cohort study of 198 cognitively healthy adults 65 years and older with a valid driver’s license who were followed up annually, with rolling enrollment. Data were collected from participants in St Louis, Missouri, and neighboring Illinois who were enrolled in the Knight Alzheimer’s Disease Research Center. Data were collected from August 28, 2012, to March 14, 2023, and analyzed from April 1 to 25, 2023. Participants with healthy cognition, defined as a Clinical Dementia Rating score of 0 at baseline and subsequent visits, who had available clinical, neuropsychological, road tests, and self-reported medication data were included.ExposurePotentially driver-impairing medication use.Main Outcomes and MeasuresThe primary outcome measure was performance on the Washington University Road Test (pass or marginal/fail). Multivariable Cox proportional hazards models were used to evaluate associations between potentially driver-impairing medication use and road test performance.ResultsOf the 198 included adults (mean [SD] baseline age, 72.6 [4.6] years; 87 female [43.9%]), 70 (35%) received a marginal/fail rating on the road test over a mean (SD) follow-up of 5.70 (2.45) years. Any use of antidepressants (adjusted hazard ratio [aHR], 2.68; 95% CI, 1.69-4.71), serotonin and norepinephrine reuptake inhibitors (aHR, 2.68; 95% CI, 1.54-4.64), sedatives or hypnotics (aHR, 2.70; 95% CI, 1.40-5.19), or nonsteroidal anti-inflammatory drugs (aHR, 2.72; 95% CI, 1.31-5.63) was associated with an increase in risk of receiving a marginal/fail rating on the road test compared with control individuals. Conversely, participants taking lipid-lowering agents had a lower risk of receiving a marginal/fail rating compared to control individuals. There were no statistically significant associations found between anticholinergic or antihistamines and poor performance.Conclusions and RelevanceIn this prospective cohort study, specific medication classes were associated with an increase in risk of poor road test performance over time. Clinicians should consider this information and counsel patients accordingly when prescribing these medications.

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Multimorbidity in Medicare Beneficiaries: Performance of an ICD‐Coded Multimorbidity‐Weighted Index

Cited by 25 publications

References 20 publications

Comprehensive review of ICD-9 code accuracies to measure multimorbidity in administrative data

Comprehensive review of ICD-9 code accuracies to measure multimorbidity in administrative data

Expectativa de vida com e sem multimorbidade entre idosos brasileiros: Pesquisa Nacional de Saúde 2013

Medication and Road Test Performance Among Cognitively Healthy Older Adults

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