JMIR Publications

ABSTRACT

Background:

Digital therapeutic care (DTC) apps provide a new effective and scalable approach for people with non-specific low back pain (LBP). DTC apps are also driven by personalized decision support interventions that support the user in self-managing LBP and may induce prolonged behavior change to reduce the frequency and intensity of pain episodes. However, these therapeutic apps come along with high attrition rates, and the initial prescription cost is higher than face-to-face physiotherapy. In Germany, DTC apps are now being reimbursed by statutory health insurance, but price targets and cost-driving factors for the formation of the reimbursement rate are still unexplored.

Objective:

The objective was to evaluate the cost-effectiveness of DTC apps compared to treatment-as-usual (TAU) in Germany. Secondly, we aimed to explore under which circumstances the reimbursement rate could be modified to consider value-based pricing.

Methods:

We developed a state-transition Markov model based on a best-practice analysis of prior LBP-related decision-analytic models and evaluated the cost-utility of DTC apps compared to TAU in Germany. Based on a three-year time horizon, we simulated the incremental cost and quality-adjusted life years (QALY) for people with non-acute LBP from the societal perspective. In the deterministic sensitivity and scenario analyses, we focused on diverging attrition rates and app cost to assess our model's robustness and conditions for changing the reimbursement rate.

Results:

Our base case results indicate that the DTC strategy led to an incremental cost of 121.59€ but also generated additional 0.0221 QALYs compared to the TAU strategy estimating an incremental cost-effectiveness ratio (ICER) of 5,486€ per QALY. The sensitivity analysis revealed that the reimbursement rate and the capability of DTC to prevent reoccurring LBP episodes have a significant impact on the ICER. At the same time, the other parameters remain unaffected and thus support the robustness of our model. In the scenario analysis, the different model time horizons and attrition rates strongly influence the economic outcome. Reducing the cost of the app to 99€ per three months or decreasing the app’s attrition rate make DTC significantly less costly with more generated QALY and thus the dominant strategy over TAU.

Conclusions:

The current reimbursement rate for DTC apps in the statutory health insurance can be considered a cost-effective measure compared to TAU. The apps' attrition rate and effect on the patient’s prolonged behavior change essentially influence the settlement of an appropriate reimbursement rate. Future value-based pricing targets should focus on additional outcome parameters besides pain intensity and functional disability by including attrition rates and the app’s long-term effect on the quality of life.