Article Text

Home safety assessment and modification to reduce injurious falls in community-dwelling older adults: cost-utility and equity analysis
1. Frank Pega,
3. Tony Blakely,
4. June Atkinson,
5. Nick Wilson
1. Burden of Disease Epidemiology, Equity and Cost-Effectiveness Programme (BODE3), Department of Public Health, University of Otago, Wellington, New Zealand
1. Correspondence to Dr Frank Pega, Department of Public Health, University of Otago, 23a Mein Street, Newtown, Wellington 6242, New Zealand; frank.pega{at}otago.ac.nz

Abstract

Background This study aimed to improve on previous modelling work to determine the health gain, cost-utility and health equity impacts from home safety assessment and modification (HSAM) for reducing injurious falls in older people.

Methods The model was a Markov macrosimulation one that estimated quality-adjusted life-years (QALYs) gained. The setting was a country with detailed epidemiological and cost data (New Zealand (NZ)) for 2011. A health system perspective was taken and a discount rate of 3% was used (for both health gain and costs). Intervention effectiveness estimates came from a Cochrane systematic review and NZ-specific intervention costs were from a randomised controlled trial.

Utility values

The key utility value was a disability weight of 0.10 with a 95% uncertainty interval (UI) of 0.06 to 0.15, which was estimated based on Salomon et al,18 assuming that each injurious fall accrued the disability weight for fracture of 0.30 applied for a 4-month period over the 1 year cycle.

Intervention effectiveness

The measure of effectiveness was a synthesis-based estimate extracted from a Cochrane systematic review of interventions for preventing falls in older people.7 This effect size was of a 19% reduction in the rate of injurious falling (95% CI 3% to 32%).7 We assumed the parameter to have a log-normal distribution. Since evidence on the effectiveness of HSAM on injurious falls is inconclusive,21 we assumed that HSAM reduces the rate of falling7 to the same degree as it reduces the rate of injurious falling.

Intervention costs came from a NZ-based randomised controlled trial of HSAM in the general population.22 We extracted cost data (ie, labour and material costs) for indoor components of the HSAM in households with one or more members aged 65 years or above. The net intervention cost per person was NZ$250 (95% UI NZ$165 to NZ$355), in 2011 dollar values.22 Additional methods details, scenario and uncertainty analyses Specific details on transition probabilities and rates used in the model are detailed in the online supplementary web appendix. So are the details on the scenario analyses and uncertainty analyses performed. Results Base analyses For the total NZ population of older people, the modelled HSAM programme cost a total of NZ$145 (US$98) million (95% UI NZ$96 (US$65) million to NZ$206 (US$139) million) to implement nationally (table 1). The net health system costs (intervention costs plus health sector costs throughout the remaining lives of the modelled cohort) were NZ$110 (US$74) million (95% UI: cost saving to NZ$196 (US$132) million). Health impacts in this older population were 34 000 QALYs gained (95% UI: 2300 to 38 000). The estimated ICER was NZ$9000 (US$6000) per QALY gained (95% UI: cost saving to NZ$20 000 (US$13 000)) suggesting that the HSAM programme intervention would be highly cost-effective as per WHO standard thresholds.23 Table 1 Scenario analyses with incremental costs, QALYs gained and ICERs (expected value analysis for population-level results for the lifetime of the modelled cohort of community-dwelling older people) Scenario analyses Scenario analyses are presented in table 1. Targeting HSAM only to older people with previous injurious falls (10% of the older population) lowered upfront programme costs (to NZ$18 million) and net health system costs (to NZ$6 million) and further improved cost-effectiveness (ICER=$2000 per QALY gained). But this resulted in lower total health gain (20 000 QALYs).

Targeting HSAM only to older people aged 75 years and above (44% of the older population) also lowered programme costs (to NZ$63 million) and net health system costs (to NZ$59 million), but reduced total health gain (9000 QALYs) and reduced cost-effectiveness (NZ$17 000 per QALY gained). Setting the discount rate to 0% and 6% also resulted in comparable ICERs of$8000 ($1000 to$16 000) and of $11 000 (cost saving to$25 000), respectively.

When HSAM was targeted to ‘at-risk’ older people (those aged 65 years and above with one or more previous injurious falls) but with declining intervention effectiveness over 10 years (linearly decreasing to nil), the ICER was smaller, but still highly cost-effective (ICER=$20 000 per QALY gained, 95% UI:$400 to $41 000). When intervention costs for HSAM targeted to at-risk older people aged 65 years and above were reduced by one-third, then the intervention's cost-effectiveness further improved, compared with the baseline model (ICER=$6000, 95% UI: cost saving to $13 000). To contextualise the results, we also considered the impact of a hypothetically improved HSAM intervention that eliminated all falls (ie, 100% effective). In this hypothetical scenario, the ICER would be$100 (95% UI: cost saving to $3000). Finally, when we modelled a different RR reduction for those with and without a history of prior injurious falls taken from a Cochrane systematic review7 the HSAM was also highly cost-effective (ICER=$4800, 95% UI: cost saving to $22 200). Uncertainty analyses Uncertainty analyses for the key model parameters for incremental costs and QALYs gained are shown in tornado plots in the online supplementary appendix figure A2. For incremental costs, the parameter contributing the most uncertainty was the scaler for the probability of death from falling, with individual-level incremental cost ranging from a small cost saving of NZ$34 to additional costs of NZ$420. The scalers for cost of hospitalised and non-hospitalised falls and the probability of hospitalisation were the next most important sources of uncertainty. For QALYs gained, the parameter contributing the most uncertainty was the rate of falling, followed by the scaler for the probability of death from falling. Population group and equity analyses Health gain and cost-effectiveness were comparable for women and men, and for the Indigenous Māori and non-Māori populations in this community-dwelling population (table 2). The ICERs indicated that HSAM was highly cost-effective among all studied ethnic groups and genders. Table 2 Analyses by ethnicity and gender within the baseline model: incremental costs, QALYs gained and ICERs (expected value analysis per person for the lifetime of the modelled cohort, with 95% UI) Discussion Main findings and interpretation This study provides modelling-level evidence that the HSAM intervention produces considerable health gain and is highly cost-effective among older people in the high-income country setting of NZ. Targeting HSAM to older people with previous injurious falls reduces upfront intervention and incremental health system costs, as well as improves the cost-effectiveness. But it does reduce total health gain relative to the universal (all adults aged 65 years and above) approach. Targeting the intervention to only adults aged 75 years and above also reduced intervention and incremental health system costs, but reduces total health gain and cost-effectiveness (though the latter remains favourable). All except for one14 of the nine previously economic analyses of HSAM concluded that the intervention was cost-effective when compared with no HSAM. So this NZ study is compatible with this past work but it also adds an equity perspective that was missing from the previous literature. Nevertheless, it found that all groups benefited and there was no differential impact or differential cost-effectiveness by ethnicity and gender, suggesting that the intervention does not have the added advantage of reducing relative health inequalities. Strengths and limitations This study has five key strengths. First, we assumed two distinct risk groups with their own fall rates, based on history of injurious falls, determined from the national injury claim and hospitalisation registries. In contrast, in a previous model of different risk groups the probability of falling in these groups has been based on expert opinion.15 Second, to our knowledge, this study is the first cost-effectiveness model of HSAM to model heterogeneity by key population characteristics, and to provide an equity perspective. Third, the study strongly relies on empirical data from national official registries to estimate the incidence of injurious falls, the associated healthcare use and the associated costs (rather than relying considerably on expert opinion), and ultimately QALY gains, net costs and cost-effectiveness. Fourth, the model also considers inflows and outflows of the target population from homes with and without HSAM. We assumed independence in estimating the rate of moving into and out of homes and of injurious falling in the low-risk and high-risk groups. Finally, the relative effectiveness and cost-effectiveness of targeting HSAM to community-dwelling older people at high risk of injurious falling (ie, with one or more injurious falls in the previous 5 years) and providing the intervention prospectively over time (as opposed to at one point in time) has not previously been studied. Nevertheless, as with all modelling studies there are limitations. First, best practice guidelines for economic analyses of social determinants of health (including housing) interventions recommend that such analyses are conducted from a societal perspective to cover wider social benefits and costs beyond the health system and explicitly include valuation of impacts on health equity.1 Our study was limited to a health system perspective, and so we did not capture any economic benefits from keeping employed older people in the workforce or being able to contribute to the informal economy, such as care for their grandchildren. Second, the model likely underestimates the health gain of the intervention due to modelling a cohort of older adults (65 years and above from 2011) only, meaning that the additional benefit from the intervention for people not included in the cohort, but who move into a modified house, would not be captured by our model. Indeed, even younger people moving into a modified house might achieve some fall prevention benefit. Third, because New Zealand Health Tracker and the Accident Compensation Corporation injury claims registry were not individually linked, in combining counts for injurious falls from these registries, we may have slightly overestimated the number of injured fallers each year. For example, a person who fell with a hospitalisation would have been counted as an injured faller in the New Zealand Health Tracker data, and if the person fell again in the same year, but without requiring hospitalisation, they would have also appeared as an injured faller in the Accident Compensation Corporation injury claims registry, and thus would have been counted as two fallers. We assumed that the healthcare events registered in the official injury claims registry excluded hospitalisation, but a small number of hospitalisation events were likely included in the registry. Moreover, because a small number of hospitalisations were likely double counted (due to being registered in both the official hospitalisation and injury claims registries), health gains may have been slightly overestimated and hence the resulting ICER may have appeared more favourable than otherwise. Fourth, in terms of non-fall-related background health costs, there were likely higher such costs for injured fallers than for other citizens of the same age and gender. But our model did not account for this. However, other factors might have shifted it in the other direction (eg, cost savings from preventing falls in younger people—especially in Western societies like NZ with relatively high levels of hazardous alcohol use). Fifth, while we assumed that the effectiveness measure on the rate of falling was equal to the rate of injurious falls, it is possible that HSAM has a different effect on all falls compared with just injurious falls. Generalisability This study is likely to have some generalisability to the general community-dwelling population of older adults (65 years and above) residing in private dwellings in other high-income countries. In particular, it may be generalisable to other countries with similar burden of disease from injurious falls and with substantially publicly funded health systems. Nevertheless, relatively low labour costs for the HSAM intervention may have reduced costs in NZ compared with other Organisation for Economic Co-operation and Development countries. In contrast, though health savings might be less in this model compared with countries with more expensive health systems on a per capita basis. Potential policy and research implications Given the results of this study and the other international literature (see Introduction), HSAM is likely to be a highly cost-effective policy intervention to reduce injurious falls in community-dwelling older people in high-income country settings. If upfront intervention costs are a concern, then targeting this intervention to older adults with a prior injurious fall could potentially be an optimal place for policymakers to start, as it would provide the opportunity to collect better data on the exact costs and feasibility of the intervention, before scaling HSAM up. However, HSAM is unlikely to impact on relative health inequalities and so policymakers should look to other interventions to achieve this particular goal. In settings where a government could not mobilise resources for an HSAM intervention, it could still consider researching the effectiveness and cost-effectiveness of such alternative options as: (i) running a mass media education campaign to encourage do-it-yourself home modifications to reduce the risk of falls, (ii) regulations that require all rental properties to have state-of-the-art home modifications for falls prevention and/or (iii) regulations that require all newly built homes to have such modifications. Of these interventions, it is possible that the rental property intervention might have greater scope for equity gain by benefiting the lower income elderly who disproportionately use rental accommodation. Conclusions This study provides modelling-level evidence that the HSAM intervention can produce considerable health gain and is likely to be highly cost-effective among older people in a high-income country setting. Targeting HSAM to older people with previous injurious falls appeared to reduce upfront intervention costs and improved the cost-effectiveness, but reduced total health gain. While the HSAM intervention benefited all gender and ethnic groups of the older population, it did so equally and so did not contribute to changes in relative inequalities. What is already known on this subject • There is good evidence that home safety assessment and modification (HSAM) is both effective and cost-effective for preventing falls in older people. • But there are many aspects which are still unclear such as the relative cost-effectiveness of targeting HSAM to people with previous injurious falls, targeting certain age groups (eg, those aged 75 years and above), and the impacts on health inequalities. What this study adds • This study found that HSAM was likely to be highly cost-effective in this national population (at US$6000 per quality-adjusted life-years gained, 95% uncertainty interval: cost saving to US\$13 000).

• Targeting HSAM only to older people with previous injurious falls was even more cost-effective, suggesting that this is where programmes with limited start-up funds could begin.

• There was no evidence for differential cost-effectiveness by gender or by ethnicity (Indigenous New Zealanders: Māori vs non-Māori).

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Comment: Unfortunately HSA chose to produce a series of videos.

Acknowledgments

We thank the Ministry of Health for access to the official hospitalisation registry and the Accident Compensation Corporation for provision of the aggregated data from the official accident compensation claims registry. Any views/conclusions in this publication are those of the authors and may not reflect the position of the Ministry of Health or Accident Compensation Corporation. We also thank Associate Professor Michael Keall and Dr Nevil Pierse (both University of Otago) who provided assistance and cost data from their randomised controlled trial. We also thank Professor Michael Baker and Dr Melissa McLeod (both University of Otago) for their feedback on an earlier draft of this paper.

Footnotes

• Contributors FP lead the overall study design and development. GK lead and all other authors contributed to model development. FP lead and all authors contributed to the interpretation of findings and the development of the manuscript.

• Funding This study was conducted as part of the BODE3 of the University of Otago. This programme is primarily funded by the Health Research Council of New Zealand (grant no: 10/248). This study was funded through this programme and also the University of Otago via a Health Sciences Career Development Postdoctoral Fellowship to Pega. No financial disclosures were reported by the authors of this paper.

• Competing interests None declared.

• Provenance and peer review Not commissioned; externally peer reviewed.

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