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 BT - Monte Carlo Simulation JF - 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 U6 - https://doi.org/10.2196/44585 SN - 2291-5222 VL - 11 PB - JMIR Publications CY - Toronto ER - TY - JOUR A1 - Lewkowicz, Daniel A1 - Wohlbrandt, Attila M. A1 - Böttinger, Erwin T1 - Digital therapeutic care apps with decision-support interventions for people with low back pain in Germany BT - Cost-effectiveness analysis JF - JMIR mhealth and uhealth N2 - Background: Digital therapeutic care apps provide a new effective and scalable approach for people with nonspecific low back pain (LBP). Digital therapeutic care 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 are associated with high attrition rates, and the initial prescription cost is higher than that of face-to-face physiotherapy. In Germany, digital therapeutic care apps are now being reimbursed by statutory health insurance; however, price targets and cost-driving factors for the formation of the reimbursement rate remain unexplored. Objective: The aim of this study was to evaluate the cost-effectiveness of a digital therapeutic care app compared to treatment as usual (TAU) in Germany. We further 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 a digital therapeutic care app compared to TAU in Germany. Based on a 3-year time horizon, we simulated the incremental cost and quality-adjusted life years (QALYs) for people with nonacute 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. All costs are reported in Euro (euro1=US $1.12). Results: Our base case results indicated that the digital therapeutic care strategy led to an incremental cost of euro121.59, but also generated 0.0221 additional QALYs compared to the TAU strategy, with an estimated incremental cost-effectiveness ratio (ICER) of euro5486 per QALY. The sensitivity analysis revealed that the reimbursement rate and the capability of digital therapeutic care to prevent reoccurring LBP episodes have a significant impact on the ICER. At the same time, the other parameters remained unaffected and thus supported the robustness of our model. In the scenario analysis, the different model time horizons and attrition rates strongly influenced the economic outcome. Reducing the cost of the app to euro99 per 3 months or decreasing the app's attrition rate resulted in digital therapeutic care being significantly less costly with more generated QALYs, and is thus considered to be the dominant strategy over TAU. Conclusions: The current reimbursement rate for a digital therapeutic care app in the statutory health insurance can be considered a cost-effective measure compared to TAU. The app's 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 quality of life. KW - cost-utility analysis KW - low back pain KW - back pain KW - cost-effectiveness KW - Markov model KW - digital therapy KW - digital health app KW - mHealth KW - orthopedic; KW - eHealth KW - mobile health KW - digital health KW - pain management KW - health apps Y1 - 2022 U6 - https://doi.org/10.2196/35042 SN - 2291-5222 VL - 10 IS - 2 PB - JMIR Publications CY - Toronto ER - TY - JOUR A1 - Salzwedel, Annett A1 - Rabe, Sophie A1 - Zahn, Thomas A1 - Neuwirth, Julia A1 - Eichler, Sarah A1 - Haubold, Kathrin A1 - Wachholz, Anne A1 - Reibis, Rona Katharina A1 - Völler, Heinz T1 - Nutzerinteresse an mobilen digitalen Assistenzsystemen zur Förderung körperlicher Aktivität bei Studierenden und Mitarbeitern einer Universität T1 - User Interest in Digital Health Technologies to Enhance Physical Activity in Students and Staff of a University JF - Gesundheitswesen N2 - Hintergrund Einem Großteil der Bevölkerung gelingt es trotz ausreichenden Wissens um die protektiven Effekte nicht, ausreichende körperliche Aktivität in den Alltag zu integrieren. Digitale Assistenzsysteme könnten hierbei unterstützend eingesetzt werden. Dies setzt jedoch das Interesse potentieller Nutzer voraus. Methode In einer Online-Befragung wurden im Juni/Juli 2015 Mitarbeiter und Studierende der Universität Potsdam zum individuellen Ausmaß der sportlichen Aktivität, dem Interesse an elektronischer Trainingsunterstützung und weiteren Parametern befragt. Ergebnis 1217 Studierende und 485 Mitarbeiter (67,3 bzw. 67,5% Frauen, 26±4,9 bzw. 42,7±11,7 Jahre) nahmen an der Studie teil. Die empfohlene sportliche Aktivität (≥3 Tage bzw. 150 min/Woche) wurde von 70,1% der Mitarbeiter und 52,7% der Studierenden nicht erreicht. Innerhalb dieser Gruppen zeigten 53,2% (Studierende) bzw. 44,2% (Mitarbeiter), unabhängig von Alter, Geschlecht, BMI bzw. Bildungsniveau, Interesse an einer elektronischen Trainingsunterstützung. Schlussfolgerung Auch in jüngeren Bevölkerungsgruppen mit hohem Bildungsniveau ist die Mehrzahl der Personen unzureichend körperlich aktiv. Ein Interesse an Trainingsunterstützung besteht in etwa der Hälfte dieser sportlich inaktiven Gruppe. Dies legt den Schluss nahe, dass der personalisierte Einsatz mobiler Assistenzsysteme für die positive Beeinflussung des Lebensstils zunehmend an Bedeutung gewinnen könnte. N2 - Introduction Though health-enhancing effects of physical activity are well documented, the majority of the population is unable to implement present recommendations into daily routine. Mobile health (mHealth) technologies might be able to increase the physical activity level. However, the interest of potential users is a mandatory basis for this. Method We conducted an online-survey from 06-07/2015 by asking students and employees from the University of Potsdam for their activity level, interest in mHealth training support and other relevant parameters. Results 1 217 students and 485 employees (67.3 % and 67.5 % female, 26.0 +/- 4.9 and 42.7 +/- 11.7 years, respectively) participated in the survey. 70.1 % of employees and 52.7 % of students did not follow the recommendation for physical activity (3 times per week). 53.2 % (students) and 44.2 % (employees), independent of age, sex, BMI and level of education or professional qualification, indicated their interest in mHealth technology offering training support. Conclusion Even in a younger population with higher education, most respondents reported an insufficient level of physical activity. About half of them indicated their interest in training support. Therefore, the use of personalized mHealth technology may be of increasing significance for a positive change of lifestyle. KW - physical activity KW - digital health KW - prevention KW - lifestyle KW - mHealth KW - körperliche Aktivität KW - digitale Gesundheit KW - Prävention KW - Lebensstil KW - mobile Assistenzsysteme Y1 - 2018 U6 - https://doi.org/10.1055/s-0043-103951 SN - 0941-3790 SN - 1439-4421 VL - 80 IS - 11 SP - 1023 EP - 1025 PB - Thieme CY - Stuttgart ER -