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Multifactorial interventions: nurse-led (general population)

Health Care: Falls Prevention for Older Adults
Benefit-cost methods last updated December 2019.  Literature review updated November 2017.
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Multifactorial falls prevention programs offer more than one type of intervention, with each participant receiving a tailored combination of interventions following a falls risk assessment. The single study included in this analysis was of the Stay Active and Independent for Life Program (SAIL). Participants received an initial risk assessment by a nurse during a home visit, followed by assigned group exercise classes and falls prevention education. Participants typically received 1-hour group exercise classes three times per week for 12 months; an average of 1.3 hours of phone-follow-up by a nurse to encourage adherence; and six 1-hour falls education classes led by a nurse. The nurse mailed assessment results to the participant’s primary care provider.

This meta-analysis includes only interventions delivered to community-dwelling older adults. It excludes interventions delivered to participants with a high risk of falling. We analyze nurse-led multifactorial interventions for community-dwelling older adults at high risk separately.
The estimates shown are present value, life cycle benefits and costs. All dollars are expressed in the base year chosen for this analysis (2018). The chance the benefits exceed the costs are derived from a Monte Carlo risk analysis. The details on this, as well as the economic discount rates and other relevant parameters are described in our Technical Documentation.
Benefit-Cost Summary Statistics Per Participant
Benefits to:
Taxpayers $140 Benefits minus costs ($207)
Participants $18 Benefit to cost ratio $0.70
Others $22 Chance the program will produce
Indirect $306 benefits greater than the costs 20 %
Total benefits $485
Net program cost ($692)
Benefits minus cost ($207)
1In addition to the outcomes measured in the meta-analysis table, WSIPP measures benefits and costs estimated from other outcomes associated with those reported in the evaluation literature. For example, empirical research demonstrates that high school graduation leads to reduced crime. These associated measures provide a more complete picture of the detailed costs and benefits of the program.

2“Others” includes benefits to people other than taxpayers and participants. Depending on the program, it could include reductions in crime victimization, the economic benefits from a more educated workforce, and the benefits from employer-paid health insurance.

3“Indirect benefits” includes estimates of the net changes in the value of a statistical life and net changes in the deadweight costs of taxation.
Detailed Monetary Benefit Estimates Per Participant
Benefits from changes to:1 Benefits to:
Taxpayers Participants Others2 Indirect3 Total
Health care associated with falls $140 $18 $22 $70 $249
Mortality associated with falls $0 $0 $0 $582 $582
Adjustment for deadweight cost of program $0 $0 $0 ($346) ($346)
Totals $140 $18 $22 $306 $485
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $666 2016 Present value of net program costs (in 2018 dollars) ($692)
Comparison costs $0 2016 Cost range (+ or -) 20 %
The per-participant cost estimate is based on provider hours and materials in the included study. Participants typically received 1-hour group exercise classes three times per week over a period of 12 months; an average of 1.3 hours of phone-follow-up by a nurse to encourage adherence; and six 1-hour falls education classes led by a nurse. We include the costs of fitness instructor time and training, and assume an average exercise class size of ten students. We include the costs of nurse time for phone follow-up and class instruction. We also include costs of course manuals and weights distributed to participants and instructors. We use 2016 U.S. Bureau of Labor Statistics information (retrieved March 2018) to estimate Washington State mean wages for fitness instructors and registered nurses. We increase wages by a factor of 1.441 to account for the cost of employee benefits. Information on costs of course materials, cost of weights, and number of participants per class provided by Carolyn Ham at the Washington State Department of Health, March 2018.
The figures shown are estimates of the costs to implement programs in Washington. The comparison group costs reflect either no treatment or treatment as usual, depending on how effect sizes were calculated in the meta-analysis. The cost range reported above reflects potential variation or uncertainty in the cost estimate; more detail can be found in our Technical Documentation.
Estimated Cumulative Net Benefits Over Time (Non-Discounted Dollars)
The graph above illustrates the estimated cumulative net benefits per-participant for the first fifty years beyond the initial investment in the program. We present these cash flows in non-discounted dollars to simplify the “break-even” point from a budgeting perspective. If the dollars are negative (bars below $0 line), the cumulative benefits do not outweigh the cost of the program up to that point in time. The program breaks even when the dollars reach $0. At this point, the total benefits to participants, taxpayers, and others, are equal to the cost of the program. If the dollars are above $0, the benefits of the program exceed the initial investment.

The effect size for this outcome indicates an incidence rate ratio (IRR), not a standardized mean difference effect size. An IRR less than one indicates a lower rate of the outcome in the treatment group relative to the comparison group; an IRR greater than one indicates a higher rate of the outcome. The treatment n for this outcome represents person-years.

Meta-analysis is a statistical method to combine the results from separate studies on a program, policy, or topic in order to estimate its effect on an outcome. WSIPP systematically evaluates all credible evaluations we can locate on each topic. The outcomes measured are the types of program impacts that were measured in the research literature (for example, crime or educational attainment). Treatment N represents the total number of individuals or units in the treatment group across the included studies.

An effect size (ES) is a standard metric that summarizes the degree to which a program or policy affects a measured outcome. If the effect size is positive, the outcome increases. If the effect size is negative, the outcome decreases.

Adjusted effect sizes are used to calculate the benefits from our benefit cost model. WSIPP may adjust effect sizes based on methodological characteristics of the study. For example, we may adjust effect sizes when a study has a weak research design or when the program developer is involved in the research. The magnitude of these adjustments varies depending on the topic area.

WSIPP may also adjust the second ES measurement. Research shows the magnitude of some effect sizes decrease over time. For those effect sizes, we estimate outcome-based adjustments which we apply between the first time ES is estimated and the second time ES is estimated. We also report the unadjusted effect size to show the effect sizes before any adjustments have been made. More details about these adjustments can be found in our Technical Documentation.

Meta-Analysis of Program Effects
Outcomes measured Treatment age No. of effect sizes Treatment N Adjusted effect sizes(ES) and standard errors(SE) used in the benefit - cost analysis Unadjusted effect size (random effects model)
First time ES is estimated Second time ES is estimated
ES SE Age ES SE Age ES p-value
Falls 76 1 222 0.752 0.058 76 1.000 0.000 77 0.752 0.001

Citations Used in the Meta-Analysis

Shumway-Cook, A., Silver, I.F., LeMier, M., York, S., Cummings, P., & Koepsell, T.D. (2007). Effectiveness of community-based multifactorial intervention on falls and fall risk factors in community-living older adults: A randomized, controlled trial. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 62(12), 1420–1427.