TY  - JOUR
A1  - Lewkowicz, Daniel
A1  - Böttinger, Erwin
A1  - Siegel, Martin
T1  - Economic evaluation of digital therapeutic care apps for unsupervised treatment of low back pain
T2  - JMIR mhealth and uhealth
N2  - Background: 
Digital therapeutic care (DTC) programs are unsupervised app-based treatments that provide video exercises and educational material to patients with nonspecific low back pain during episodes of pain and functional disability. German statutory health insurance can reimburse DTC programs since 2019, but evidence on efficacy and reasonable pricing remains scarce. This paper presents a probabilistic sensitivity analysis (PSA) to evaluate the efficacy and cost-utility of a DTC app against treatment as usual (TAU) in Germany. 

Objective: 
The aim of this study was to perform a PSA in the form of a Monte Carlo simulation based on the deterministic base case analysis to account for model assumptions and parameter uncertainty. We also intend to explore to what extent the results in this probabilistic analysis differ from the results in the base case analysis and to what extent a shortage of outcome data concerning quality-of-life (QoL) metrics impacts the overall results. 

Methods: 
The PSA builds upon a state-transition Markov chain with a 4-week cycle length over a model time horizon of 3 years from a recently published deterministic cost-utility analysis. A Monte Carlo simulation with 10,000 iterations and a cohort size of 10,000 was employed to evaluate the cost-utility from a societal perspective. Quality-adjusted life years (QALYs) were derived from Veterans RAND 6-Dimension (VR-6D) and Short-Form 6-Dimension (SF-6D) single utility scores. Finally, we also simulated reducing the price for a 3-month app prescription to analyze at which price threshold DTC would result in being the dominant strategy over TAU in Germany. 

Results: 
The Monte Carlo simulation yielded on average a euro135.97 (a currency exchange rate of EUR euro1=US $1.069 is applicable) incremental cost and 0.004 incremental QALYs per person and year for the unsupervised DTC app strategy compared to in-person physiotherapy in Germany. The corresponding incremental cost-utility ratio (ICUR) amounts to an additional euro34,315.19 per additional QALY. DTC yielded more QALYs in 54.96% of the iterations. DTC dominates TAU in 24.04% of the iterations for QALYs. Reducing the app price in the simulation from currently euro239.96 to euro164.61 for a 3-month prescription could yield a negative ICUR and thus make DTC the dominant strategy, even though the estimated probability of DTC being more effective than TAU is only 54.96%.

Conclusions:
Decision-makers should be cautious when considering the reimbursement of DTC apps since no significant treatment effect was found, and the probability of cost-effectiveness remains below 60% even for an infinite willingness-to-pay threshold. More app-based studies involving the utilization of QoL outcome parameters are urgently needed to account for the low and limited precision of the available QoL input parameters, which are crucial to making profound recommendations concerning the cost-utility of novel apps.
KW  - cost-utility analysis
KW  - cost
KW  - probabilistic sensitivity analysis
KW  - Monte Carlo simulation
KW  - low back pain
KW  - pain
KW  - economic
KW  - cost-effectiveness
KW  - Markov model
KW  - digital therapy
KW  - digital health app
KW  - mHealth
KW  - mobile health
KW  - health app
KW  - mobile app
KW  - orthopedic
KW  - QUALY
KW  - DALY
KW  - quality-adjusted life years
KW  - disability-adjusted life years
KW  - time horizon
KW  - veteran
KW  - statistics
Y1  - 2023
UR  - https://publishup.uni-potsdam.de/frontdoor/index/index/docId/64295
SN  - 2291-5222
VL  - 11
PB  - JMIR Publications
CY  - Toronto
ER  -