Is it worth it? Cost-effectiveness analysis of a commercial physical activity app

Rondina, Renante; Hong, Michael; Sarma, Sisira; Mitchell, Marc

doi:10.1186/s12889-021-11988-y

Cited by 8 publications

(5 citation statements)

References 82 publications

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“…Indeed, t tests conducted on final propensity score–matched groups indicated that efforts to minimize confounding bias were successful. Additionally, there are limited studies that examine the cost-effectiveness of behavior change and physical activity–based apps [ 25 , 26 ].…”

Section: Discussionmentioning

confidence: 99%

The Influence of a Wearable-Based Reward Program on Health Care Costs: Retrospective, Propensity Score–Matched Cohort Study

Zaleski¹,

Sigler²,

Leggitt³

et al. 2023

J Med Internet Res

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Background Mobile health (mHealth) technology holds great promise as an easily accessible and effective solution to improve population health at scale. Despite the abundance of mHealth offerings, only a minority are grounded in evidence-based practice, whereas even fewer have line of sight into population-level health care spending, limiting the clinical utility of such tools. Objective This study aimed to explore the influence of a health plan–sponsored, wearable-based, and reward-driven digital health intervention (DHI) on health care spending over 1 year. The DHI was delivered through a smartphone-based mHealth app available only to members of a large commercial health plan and leveraged a combination of behavioral economics, user-generated sensor data from the connected wearable device, and claims history to create personalized, evidence-based recommendations for each user. Methods This study deployed a propensity score–matched, 2-group, and pre-post observational design. Adults (≥18 years of age) enrolled in a large, national commercial health plan and self-enlisted in the DHI for ≥7 months were allocated to the intervention group (n=56,816). Members who were eligible for the DHI but did not enlist were propensity score–matched to the comparison group (n=56,816). Average (and relative change from baseline) medical and pharmacy spending per user per month was computed for each member of the intervention and comparison groups during the pre- (ie, 12 months) and postenlistment (ie, 7-12 months) periods using claims data. Results Baseline characteristics and medical spending were similar between groups (P=.89). On average, the total included sample population (N=113,632) consisted of young to middle-age (mean age 38.81 years), mostly White (n=55,562, 48.90%), male (n=46,731, 41.12%) and female (n=66,482, 58.51%) participants. Compared to a propensity score–matched cohort, DHI users demonstrated approximately US $10 per user per month lower average medical spending (P=.02) with a concomitant increase in preventive care activities and decrease in nonemergent emergency department admissions. These savings translated to approximately US $6.8 million in avoidable health care costs over the course of 1 year. Conclusions This employer-sponsored, digital health engagement program has a high likelihood for return on investment within 1 year owing to clinically meaningful changes in health-seeking behaviors and downstream medical cost savings. Future research should aim to elucidate health behavior–related mechanisms in support of these findings and continue to explore novel strategies to ensure equitable access of DHIs to underserved populations that stand to benefit the most.

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Section: Discussionmentioning

confidence: 99%

The Influence of a Wearable-Based Reward Program on Health Care Costs: Retrospective, Propensity Score–Matched Cohort Study

Zaleski¹,

Sigler²,

Leggitt³

et al. 2023

J Med Internet Res

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“…Time horizon, which was expected to be long-term for decision-analytic studies on (chronic) disease prevention, was relatively short for two studies -two years [30] and five years [33] -but longer for all the others (e.g. lifetime perspective).…”

Section: Evaluation Methodsmentioning

confidence: 99%

“…Figure 2 shows the characteristics of assessed DiPH interventions (for details of individual studies, see Additional file 2). The interventions subject to economic evaluation pursued different goals: increase physical activity [30][31][32][33][34], lose weight [35][36][37][38], stop smoking [39][40][41], change health-related behaviours [42], and manage menstrual health [43]. Thus, most interventions aimed to prevent typical chronic diseases such as diabetes or heart disease.…”

Section: Assessed Diph Interventionsmentioning

confidence: 99%

“…The third physical-activity intervention delivered the same advice via a website and by mail, while also providing exercise videos; it targeted people over 50 [32]. The fourth intervention was a commercial smartphone app [33], while the fifth promoted existing apps to increase physical activity, targeting adults in New Zealand [34].…”

Section: Assessed Diph Interventionsmentioning

confidence: 99%

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Health economic evaluation of preventive digital public health interventions using decision-analytic modelling: a systematized review

Lange

2023

BMC Health Serv Res

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Background Digital public health (DiPH) provides novel approaches for prevention, potentially leading to long-term health benefits in resource-limited health systems. However, cost-effectiveness of DiPH interventions is unclear. This systematized review investigates the use of decision-analytic modelling in health economic evaluations of DiPH primary prevention and health promotion interventions, focusing on intervention’s design, methods used, results, and reporting quality. Methods PubMed, CINAHL, and Web of Science were searched for studies of decision-analytic economic evaluations of digital interventions in primary prevention or health promotion, published up to June 2022. Intervention characteristics and selected items were extracted based on the Consolidated Health Economic Evaluation Reporting Standards (CHEERS). Incremental cost-effectiveness ratios (ICERs) were then extracted and price-adjusted to compare the economic evaluation results. Finally, the included studies’ reporting quality was assessed by building a score using CHEERS. Results The database search (including search update) produced 2,273 hits. After removing duplicates, 1,434 titles and abstracts were screened. Of the 89 studies meeting the full-text search criteria, 14 were ultimately reviewed. The most common targets were physical activity (five studies) and weight loss (four). Digital applications include text messages, web-based inventions, app-based interventions, e-learning devices, and the promotion of smartphone apps. The mean ICER of the 12 studies using quality-adjusted life years (QALYs) is €20,955 per QALY (min. − €3,949; max. €114,211). The mean of reported CHEERS items per study is 81% (min. 59%; max. 91%). Conclusions This review only includes primary prevention and health promotion, and thus excludes other DiPH fields (e.g. secondary prevention). It also focuses on decision-analytic models, excluding study-based economic evaluations. Standard methods of economic evaluation could be adapted more to the specifics of DiPH by measuring the effectiveness of more current technologies through alternative methods, incorporating a societal perspective, and more clearly defining comparators. Nevertheless, the review demonstrates using common thresholds that the new field of DiPH shows potential for cost-effective preventive interventions.

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“…Along with workplace mindfulness programs, organizations are increasingly incorporating mindfulness mobile applications (i.e., apps) into employee health benefit offerings 16) . Mindfulness apps are a scalable and cost-effective strategy for promoting mental well-being in the workplace 17) . Because mindfulness apps can be accessed "on-demand," they can remove potential barriers to accessing or utilizing mindfulness interventions by allowing employees to easily and discreetly use the app from any location on a mobile device 18) .…”

Section: Mindfulness In the Workplacementioning

confidence: 99%

Examining the associations of using the Calm app with team mindfulness and psychological safety in remote workers

Puzia¹,

Green

Clarke

et al. 2022

EOH-P

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Objective:The purposes of this study were to (1) illustrate how remote workers engage with an employer-provided mindfulness meditation app in the workplace and (2) examine the relationship between workplace app engagement, team mindfulness, and psychological safety among remote workers. Methods: A cross-sectional survey was administered to employees within the United States who had received a subscription to Calm as part of their health benefits. Employees reported on three types of engagement with the Calm app in the context of the workplaceopportunities use to Calm together during the workday, using Calm with team members, and discussing Calm content with teams -and completed measures of team mindfulness and psychological safety. Fixed-effects regression models were used to assess effects of workplace app engagement on psychological safety and team mindfulness in remote workers. Results: Of 60,000 workers contacted, 801 employees completed the survey (1.3%) and 437 were full-time remote workers (0.7%). Only 20% of remote workers reported having opportunities to use Calm at work. Opportunities to use Calm at work was positively associated with team mindfulness (β = 2.39, p = 0.005) and psychological safety (β = 1.85, p = 0.005). Using Calm with team members was only significantly associated with team mindfulness (β = 2.99, p = 0.046) and discussing Calm with team members was only significantly associated with psychological safety (β = 1.17, p = 0.029). Conclusions: Creating opportunities for employees to engage with a mindfulness meditation app while at work may help foster team mindfulness and psychological safety, especially for remote workers. Considering the research limitations, future studies should investigate longitudinal relationships within workplace teams.

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Is it worth it? Cost-effectiveness analysis of a commercial physical activity app

Cited by 8 publications

References 82 publications

The Influence of a Wearable-Based Reward Program on Health Care Costs: Retrospective, Propensity Score–Matched Cohort Study

The Influence of a Wearable-Based Reward Program on Health Care Costs: Retrospective, Propensity Score–Matched Cohort Study

Health economic evaluation of preventive digital public health interventions using decision-analytic modelling: a systematized review

Examining the associations of using the Calm app with team mindfulness and psychological safety in remote workers

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