Examining the relationship between health-related quality of life and increasing numbers of diagnoses.
Purpose: Little is known about estimating utilities for comorbid (or 'joint') health states. Several joint health state prediction models have been suggested (for example, additive, multiplicative, best-of-pair, worst-of-pair, etc.), but no general consensus has been reached. The purpose of the stud...
| Publicado en: | Quality of Life Research Vol. 24; no. 12; pp. 2823 - 2833 |
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| Autores principales: | , , , , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Springer Nature
Dec2015
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=110483419&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 110483419 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09629343 GPQ jtl: Quality of Life Research issn: 09629343 maglogo: N pubinfo: dt: Dec2015 vid: 24 iid: 12 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 110483419 110483419 NLM26068730 110483419 10.1007/s11136-015-1026-3 NLM26068730 PMC4615667 110483419 ppf: 2823 ppct: 10 formats: fmt: @attributes: type: P tig: atl: Examining the relationship between health-related quality of life and increasing numbers of diagnoses. aug: au: Barra, Mathias Augestad, Liv Whitehurst, David Rand-Hendriksen, Kim Augestad, Liv Ariane Whitehurst, David G T affil: Health Services Research Center, Akershus University Hospital, 1478 Lørenskog Norway sug: subj: Quality of Life Comorbidity Human Secondary Analysis Quality-Adjusted Life Years Models, Statistical Demography Descriptive Statistics Age Factors Sex Factors Severity of Illness Clinical Assessment Tools ab: Purpose: Little is known about estimating utilities for comorbid (or 'joint') health states. Several joint health state prediction models have been suggested (for example, additive, multiplicative, best-of-pair, worst-of-pair, etc.), but no general consensus has been reached. The purpose of the study is to explore the relationship between health-related quality of life (HRQoL) and increasing numbers of diagnoses.Methods: We analyzed a large dataset containing respondents' ICD-9 diagnoses and preference-based HRQoL (EQ-5D and SF-6D). Data were stratified by the number of diagnoses, and mean HRQoL values were estimated. Several adjustments, accounting for the respondents' age, sex, and the severity of the diagnoses, were carried out. Our analysis fitted additive and multiplicative models to the data and assessed model fit using multiple standard model selection methods.Results: A total of 39,817 respondents were included in the analyses. Average HRQoL values were represented well by both linear and multiplicative models. Although results across all analyses were similar, adjusting for severity of diagnoses, age, and sex strengthened the linear model's performance measures relative to the multiplicative model. Adjusted R (2) values were above 0.99 for all analyses (i.e., all adjusted analyses, for both HRQoL instruments), indicating a robust result.Conclusions: Additive and multiplicative models perform equally well within our analyses. A practical implication of our findings, based on the presumption that a linear model is simpler than an additive model, is that an additive model should be preferred unless there is compelling evidence to the contrary. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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