Literature DB >> 7723444

Including deaths when measuring health status over time.

P Diehr1, D Patrick, S Hedrick, M Rothman, D Grembowski, T E Raghunathan, S Beresford.   

Abstract

Measuring health status over time is problematic when some subjects die, because death does not have a defined value on most health status measures. This situation is different from the usual missing data problem because the health status of the dead is, in a sense, known. We examined eight strategies for incorporating deaths into such analyses using three health status measures taken from two data sets, after which we used computer simulation to explore more fully the effect of deaths. The strategies differed in the amount of influence given to the deaths, varying from none (deaths were discarded) to complete (mortality itself was the health measure). The strategies that gave less influence to deaths tended to show more favorable changes in health over time, and therefore, tended to favor the group that had more deaths. The strategies that were more influenced by death showed more negative changes over time and favored the group with fewer deaths. The choice of strategy should depend on the goals of an intervention. For health promotion studies, we recommend recoding the health variables to estimate the probability that a person will be healthy in 2 years (or in some other period that can be estimated from the data).

Entities:  

Mesh:

Year:  1995        PMID: 7723444

Source DB:  PubMed          Journal:  Med Care        ISSN: 0025-7079            Impact factor:   2.983


  11 in total

1.  Longitudinal Data with Follow-up Truncated by Death: Match the Analysis Method to Research Aims.

Authors:  Brenda F Kurland; Laura L Johnson; Brian L Egleston; Paula H Diehr
Journal:  Stat Sci       Date:  2009       Impact factor: 2.901

2.  Health-related quality of life: an indicator of quality of care?

Authors:  H F Treurniet; M L Essink-Bot; J P Mackenbach; P J van der Maas
Journal:  Qual Life Res       Date:  1997-05       Impact factor: 4.147

3.  Benefits gained, benefits lost: comparing baby boomers to other generations in a longitudinal cohort study of self-rated health.

Authors:  Elizabeth M Badley; Mayilee Canizares; Anthony V Perruccio; Sheilah Hogg-Johnson; Monique A M Gignac
Journal:  Milbank Q       Date:  2015-03       Impact factor: 4.911

4.  Randomised comparison of losartan vs. captopril on quality of life in elderly patients with symptomatic heart failure: the losartan heart failure ELITE quality of life substudy.

Authors:  A J Cowley; B L Wiens; R Segal; M W Rich; N C Santanello; E J Dasbach; B Pitt
Journal:  Qual Life Res       Date:  2000       Impact factor: 4.147

5.  Association of timing of surgery for hip fracture and patient outcomes.

Authors:  Gretchen M Orosz; Jay Magaziner; Edward L Hannan; R Sean Morrison; Kenneth Koval; Marvin Gilbert; Maryann McLaughlin; Ethan A Halm; Jason J Wang; Ann Litke; Stacey B Silberzweig; Albert L Siu
Journal:  JAMA       Date:  2004-04-14       Impact factor: 56.272

6.  Predicting Future Years of Life, Health, and Functional Ability: A Healthy Life Calculator for Older Adults.

Authors:  Paula Diehr; Michael Diehr; Alice Arnold; Laura M Yee; Michelle C Odden; Calvin H Hirsch; Stephen Thielke; Bruce M Psaty; W Craig Johnson; Jorge R Kizer Md; Anne Newman
Journal:  Gerontol Geriatr Med       Date:  2015-10-08

7.  Quality of life at the end of life.

Authors:  Paula Diehr; William E Lafferty; Donald L Patrick; Lois Downey; Sean M Devlin; Leanna J Standish
Journal:  Health Qual Life Outcomes       Date:  2007-08-03       Impact factor: 3.186

8.  Looking beyond 28-day all-cause mortality.

Authors:  Gordon Rubenfeld
Journal:  Crit Care       Date:  2002-07-08       Impact factor: 9.097

9.  Assessing response bias from missing quality of life data: the Heckman method.

Authors:  Anne E Sales; Mary E Plomondon; David J Magid; John A Spertus; John S Rumsfeld
Journal:  Health Qual Life Outcomes       Date:  2004-09-16       Impact factor: 3.186

10.  Predicting declines in physical function in persons with multiple chronic medical conditions: what we can learn from the medical problem list.

Authors:  Elizabeth A Bayliss; Martha S Bayliss; John E Ware; John F Steiner
Journal:  Health Qual Life Outcomes       Date:  2004-09-07       Impact factor: 3.186

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.