Health-Related Productivity Loss: NICE to Recognize Soon, Good to Discuss Now

Zhang, Wei; Anis, Aslam H.

doi:10.1007/s40273-014-0149-7

Cited by 9 publications

(7 citation statements)

References 20 publications

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“…Productivity costs can be measured using average wage figures (human capital methods) or replacement costs (friction cost models) . Friction costs are not recommended over the timescale of calculating incremental costs per day . We therefore used average wage rates, adjusted for on‐costs (employment costs less salary costs), to measure the productivity burden related to hospital admissions over 1 year.…”

Section: Methodsmentioning

confidence: 99%

“…19 Friction costs are not recommended over the timescale of calculating incremental costs per day. 21 We therefore used average wage rates, 22 adjusted for on-costs (employment costs less salary costs), 23 to measure the productivity burden related to hospital admissions over 1 year. We used the same rate for paid and unpaid work.…”

Section: Monetising Days Off Work and Informal Carementioning

confidence: 99%

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Measuring the financial and productivity burden of paediatric hospitalisation on the wider family network

Mumford

Baysari

Kalinin

et al. 2018

J Paediatrics Child Health

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Aim: To estimate the non-medical out-of-pocket costs for families with a child in hospital. Methods: This study was a survey of 225 parents of paediatric inpatients on nine wards of an Australian public paediatric teaching hospital on two separate days. Our primary outcomes were the costs associated with: (i) time taken off work to care for the child in hospital; (ii) time off work or contributed by family and friends to care for other dependents; and (iii) travel, meals, accommodation and incidental expenses during the child's stay. Demographic data included postcode (to assess distance, socio-economic status and remoteness), child's age, ward and whether this was their child's first admission. Results: Mean patient age was 6.5 years (standard deviation 5.2). On an average per patient day basis, parents took 1.12 days off work and spent 0.61 (standard deviation 0.53) nights away from home, with 83.8% of nights away at the child's bedside. Parents spent Australian dollars (AUD)89 per day on travel and AUD36 on meals and accommodation. Total costs (including productivity costs) were AUD589 per patient day. Higher costs per patient day were correlated with living in a more remote area (0.48) and a greater travel distance to the hospital (0.41). A higher number of days off work was correlated (0.69) with number of school days missed.Conclusion: These results demonstrate the considerable time and financial resources expended by families caring for a child in hospital and are important inputs in evaluating health-care interventions that affect risk of hospitalisation and length of stay in paediatric care.

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Section: Methodsmentioning

confidence: 99%

Section: Monetising Days Off Work and Informal Carementioning

confidence: 99%

Measuring the financial and productivity burden of paediatric hospitalisation on the wider family network

Mumford

Baysari

Kalinin

et al. 2018

J Paediatrics Child Health

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“…The authors concluded that the inclusion of productivity costs significantly affected the incremental costs between treatments in a number of studies, and that studies which ignore these costs may poorly reflect the full societal costs (or savings) of an intervention. Further to this, the National Institute for Clinical Excellence in the UK (NICE) has recently announced that they will soon consider the societal benefit of pharmaceuticals, including their impact on productivity, in their assessment of treatments for reimbursement (Zhang and Anis 2014). The inclusion of this additional set of financial gains will enrich the information available to decision makers in allocating scarce resources between competing priorities and as such may provide valuable information to governments seeking to improve not only the health but also the productivity of the nation.…”

Section: Discussionmentioning

confidence: 99%

LifeLossMOD: A microsimulation model of the economic impacts of premature mortality in Australia

Carter¹,

Schofield²,

Shrestha³

2013

IJM

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While the direct costs of mortality to the health care system are known to be significant, there is less information regarding the wider economic impacts of mortality including the implications for productivity, household incomes and government revenue. This paper outlines the development of LifeLossMOD, a new microsimulation model to estimate the economic impacts of premature mortality in Australia. The model is based on a census of 2003 mortality records and applies projections from the APPSIM microsimulation model to estimate the counterfactual lifetime trajectories forgone to the year 2030. We estimated that mortality in 2003 accounted for over 280,000 full time working years lost to the Australian economy. Future applications of LifeLossMOD will explore the distributional impacts of mortality on employment, GDP, government revenue and household income, wealth and retirement savings. These estimates INTERNATIONAL JOURNAL OF MICROSIMULATION (2014) 7(3) 33-52 34 CARTER, SCHOFIELD, SHRESTHA LifeLossMOD: A microsimulation model of the economic impacts of premature mortality in Australia will allow decision makers and others to more accurately determine the full economic impacts of mortality by cause. In addition, the model will be able to quantify the financial gains likely to accrue with preventative health care interventions, which can in turn be reported on in cost effectiveness analyses.

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“…Testing criterion validity of iPCQ self-reported long-term absenteeism is feasible by validating against public registry data, which might be considered as a “golden standard”. Testing criterion validity of the remaining domains (presenteeism and costs related to unpaid work) poses significant challenges due to the lag of a “gold standard” or objective measures [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

Comparison of self-reported and public registered absenteeism among people on long-term sick leave due to musculoskeletal disorders: criterion validity of the iMTA Productivity Cost Questionnaire

et al. 2021

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Objective To evaluate criterion validity of the iMTA Productivity Cost Questionnaire (iPCQ) by comparing iPCQ-reported occurrence and duration of long-term absenteeism (> 4 weeks) with public registry data collected from the Norwegian Labour and Welfare Administration (NAV) among people on sick leave due to musculoskeletal disorders. Method Baseline data from a cohort study was used, in which people on sick leave for at least 4 weeks due to musculoskeletal disorders were recruited electronically through the NAV website. To compare the occurrence of long-term absenteeism overall agreement between the two methods was measured by percentages. To compare the duration (number of days with absenteeism) and adjusted duration (number of days with complete absenteeism) of long-term absenteeism we conducted intraclass correlation coefficient (ICC) two-way random average agreement, descriptive statistic and Wilcoxon signed-rank test. Results In total, 144 participants with a median age (range) of 49 (24–67) were included. The overall agreement on the occurrence of long-term absenteeism was 100%. The ICC value was 0.97 and 0.86 for duration and adjusted duration of long-term absenteeism, respectively. The median difference(iPCQ-registry) between the two methods was 0 and 17 days for long-term absenteeism duration and adjusted duration, respectively. A significant difference between the two methods was observed (Wilcoxon signed-rank test, p < 0.001) with regards to adjusted duration of long-term absenteeism. Conclusion The iPCQ showed good agreement with public registry data regarding the occurrence and duration of long-term absenteeism among people with musculoskeletal disorders on long-term sick-leave in Norway. However, the iPCQ does not cover part-time sick-leave and thereby potentially overestimate the total amount of long-term absenteeism. Trial registration ClinicalTrials.gov Identifier no. NCT04196634.

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Health-Related Productivity Loss: NICE to Recognize Soon, Good to Discuss Now

Cited by 9 publications

References 20 publications

Measuring the financial and productivity burden of paediatric hospitalisation on the wider family network

Measuring the financial and productivity burden of paediatric hospitalisation on the wider family network

LifeLossMOD: A microsimulation model of the economic impacts of premature mortality in Australia

Comparison of self-reported and public registered absenteeism among people on long-term sick leave due to musculoskeletal disorders: criterion validity of the iMTA Productivity Cost Questionnaire

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