Literature DB >> 7964359

Health expectancy: an indicator for change? Technology Assessment Methods Project Team.

J J Barendregt1, L Bonneux, P J Van der Maas.   

Abstract

STUDY
OBJECTIVE: Health expectancy is an increasingly used indicator of population health status. It collapses both mortality and morbidity into a single indicator, and is therefore preferred to the total life expectancy index for populations with low mortality but high morbidity rates. Three methods of calculation exist: the Sullivan, double decrement, and multi-state methods. This report aims to describe their relative advantages and limitations when used to monitor changes in population health status over time.
DESIGN: The differences between the three methods are explained. Using a dynamic model of heart disease, the effect of the introduction of thrombolytic treatment on the survival of patients with acute myocardial infarction is calculated. The resulting changes in health expectancy are calculated according to the Sullivan and multi-state methods. MAIN
RESULTS: As opposed to the double decrement and the multi-state methods, the Sullivan method produces spurious trends in health expectancy in response to the change in survival.
CONCLUSIONS: Estimates of health expectancy in a dynamic situation can be very misleading when based on the Sullivan method, with its attractively moderate data requirements. The multi-state method, which requires longitudinal studies of population health status, is often indispensable.

Entities:  

Mesh:

Year:  1994        PMID: 7964359      PMCID: PMC1060012          DOI: 10.1136/jech.48.5.482

Source DB:  PubMed          Journal:  J Epidemiol Community Health        ISSN: 0143-005X            Impact factor:   3.710


  8 in total

1.  Measurement and utilization of healthy life expectancy: conceptual issues.

Authors:  J M Robine; J P Michel; L G Branch
Journal:  Bull World Health Organ       Date:  1992       Impact factor: 9.408

Review 2.  International efforts to measure health expectancy.

Authors:  M R Bone
Journal:  J Epidemiol Community Health       Date:  1992-12       Impact factor: 3.710

3.  Forecasting coronary heart disease incidence, mortality, and cost: the Coronary Heart Disease Policy Model.

Authors:  M C Weinstein; P G Coxson; L W Williams; T M Pass; W B Stason; L Goldman
Journal:  Am J Public Health       Date:  1987-11       Impact factor: 9.308

4.  A single index of mortality and morbidity.

Authors:  D F Sullivan
Journal:  HSMHA Health Rep       Date:  1971-04

5.  Aging, natural death, and the compression of morbidity.

Authors:  J F Fries
Journal:  N Engl J Med       Date:  1980-07-17       Impact factor: 91.245

6.  Impact of clinical trials on clinical practice: example of thrombolysis for acute myocardial infarction.

Authors:  D Ketley; K L Woods
Journal:  Lancet       Date:  1993-10-09       Impact factor: 79.321

7.  Estimating clinical morbidity due to ischemic heart disease and congestive heart failure: the future rise of heart failure.

Authors:  L Bonneux; J J Barendregt; K Meeter; G J Bonsel; P J van der Maas
Journal:  Am J Public Health       Date:  1994-01       Impact factor: 9.308

8.  Healthy life expectancy: evaluation of global indicator of change in population health.

Authors:  J M Robine; K Ritchie
Journal:  BMJ       Date:  1991-02-23
  8 in total
  24 in total

1.  Health expectancy in New Zealand, 1981-1991: social variations and trends in a period of rapid social and economic change.

Authors:  P Davis; P Graham; N Pearce
Journal:  J Epidemiol Community Health       Date:  1999-09       Impact factor: 3.710

2.  Decomposition of differences in health expectancy by cause.

Authors:  Wilma J Nusselder; Caspar W Looman
Journal:  Demography       Date:  2004-05

Review 3.  Cost implications of prehospital emergency drug administration. The case of prehospital thrombolytics.

Authors:  S Barton; T Walley
Journal:  Pharmacoeconomics       Date:  1996-11       Impact factor: 4.981

4.  On the Estimation of Disability-Free Life Expectancy: Sullivan' Method and Its Extension.

Authors:  Kosuke Imai; Samir Soneji
Journal:  J Am Stat Assoc       Date:  2007       Impact factor: 5.033

Review 5.  Counting backward to health care's future: using time-to-death modeling to identify changes in end-of-life morbidity and the impact of aging on health care expenditures.

Authors:  Greg Payne; Audrey Laporte; Raisa Deber; Peter C Coyte
Journal:  Milbank Q       Date:  2007-06       Impact factor: 4.911

6.  The elimination of selected chronic diseases in a population: the compression and expansion of morbidity.

Authors:  W J Nusselder; K van der Velden; J L van Sonsbeek; M E Lenior; G A van den Bos
Journal:  Am J Public Health       Date:  1996-02       Impact factor: 9.308

7.  Obtaining multistate life table distributions for highly refined subpopulations from cross-sectional data: A Bayesian extension of Sullivan's method.

Authors:  Scott M Lynch; J Scott Brown
Journal:  Demography       Date:  2010-11

8.  How good is Sullivan's method for monitoring changes in population health expectancies?

Authors:  J J Barendregt; L Bonneux; P J van der Maas
Journal:  J Epidemiol Community Health       Date:  1997-10       Impact factor: 3.710

9.  How good is Sullivan's method for monitoring changes in population health expectancies?

Authors:  C D Mathers; J M Robine
Journal:  J Epidemiol Community Health       Date:  1997-02       Impact factor: 3.710

10.  Educational inequalities in health expectancy during the financial crisis in Denmark.

Authors:  Henrik Brønnum-Hansen; Mikkel Baadsgaard; Mette Lindholm Eriksen; Karen Andersen-Ranberg; Bernard Jeune
Journal:  Int J Public Health       Date:  2015-08-20       Impact factor: 3.380

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