Feby Savira1,2, Zanfina Ademi1, Bing H Wang1,2, Andrew R Kompa3, Alice J Owen1, Danny Liew1, Ella Zomer4. 1. School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia. 2. Biomarker Discovery Laboratory, Baker Heart and Diabetes Institute, Melbourne, Australia. 3. Department of Medicine, University of Melbourne, St Vincent's Hospital, Fitzroy, Australia. 4. School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia ella.zomer@monash.edu.
Abstract
BACKGROUND: Kidney disease is associated with impaired work productivity. However, the collective effect of missed work days, reduced output at work, and early withdrawal from the workforce is rarely considered in health-economic evaluations. METHODS: To determine the effect on work productivity of preventing incident cases of kidney disease, using the novel measure "productivity-adjusted life year" (PALY), we constructed a dynamic life table model for the Australian working-age population (aged 15-69 years) over 10 years (2020-2029), stratified by kidney-disease status. Input data, including productivity estimates, were sourced from the literature. We ascribed a financial value to the PALY metric in terms of gross domestic product (GDP) per equivalent full-time worker and assessed the total number of years lived, total PALYs, and broader economic costs (GDP per PALY). We repeated the model simulation, assuming a reduced kidney-disease incidence; the differences reflected the effects of preventing new kidney-disease cases. Outcomes were discounted by 5% annually. RESULTS: Our projections indicate that, from 2020 to 2029, the estimated number of new kidney-disease cases will exceed 161,000. Preventing 10% of new cases of kidney disease during this period would result in >300 premature deaths averted and approximately 550 years of life and 7600 PALYs saved-equivalent to a savings of US$1.1 billion in GDP or US$67,000 per new case avoided. CONCLUSIONS: Pursuing a relatively modest target for preventing kidney disease in Australia may prolong years of life lived and increase productive life years, resulting in substantial economic benefit. Our findings highlight the need for investment in preventive measures to reduce future cases of kidney disease.
BACKGROUND: Kidney disease is associated with impaired work productivity. However, the collective effect of missed work days, reduced output at work, and early withdrawal from the workforce is rarely considered in health-economic evaluations. METHODS: To determine the effect on work productivity of preventing incident cases of kidney disease, using the novel measure "productivity-adjusted life year" (PALY), we constructed a dynamic life table model for the Australian working-age population (aged 15-69 years) over 10 years (2020-2029), stratified by kidney-disease status. Input data, including productivity estimates, were sourced from the literature. We ascribed a financial value to the PALY metric in terms of gross domestic product (GDP) per equivalent full-time worker and assessed the total number of years lived, total PALYs, and broader economic costs (GDP per PALY). We repeated the model simulation, assuming a reduced kidney-disease incidence; the differences reflected the effects of preventing new kidney-disease cases. Outcomes were discounted by 5% annually. RESULTS: Our projections indicate that, from 2020 to 2029, the estimated number of new kidney-disease cases will exceed 161,000. Preventing 10% of new cases of kidney disease during this period would result in >300 premature deaths averted and approximately 550 years of life and 7600 PALYs saved-equivalent to a savings of US$1.1 billion in GDP or US$67,000 per new case avoided. CONCLUSIONS: Pursuing a relatively modest target for preventing kidney disease in Australia may prolong years of life lived and increase productive life years, resulting in substantial economic benefit. Our findings highlight the need for investment in preventive measures to reduce future cases of kidney disease.
Authors: Laura C Plantinga; Kirsten Johansen; Deidra C Crews; Vahakn B Shahinian; Bruce M Robinson; Rajiv Saran; Nilka Ríos Burrows; Desmond E Williams; Neil R Powe Journal: Am J Kidney Dis Date: 2010-10-30 Impact factor: 8.860
Authors: Thomas R Hird; Ella Zomer; Alice Owen; Lei Chen; Zanfina Ademi; Dianna J Magliano; Danny Liew Journal: Diabetologia Date: 2019-04-27 Impact factor: 10.122
Authors: M L R Wyld; C M Y Lee; X Zhuo; S White; J E Shaw; R L Morton; S Colagiuri; S J Chadban Journal: Intern Med J Date: 2015-07 Impact factor: 2.048