RESEARCH/Original article
Mobile app self-care versus in-office care for stress reduction: a cost minimization analysis
Journal of Telemedicine and Telecare 2014, Vol. 20(8) 431–435 ! The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/1357633X14555616 jtt.sagepub.com
David D Luxton1,2, Ryan N Hansen3 and Katherine Stanfill1
Summary We calculated the cost of providing stress reduction care with a mobile phone app (Breathe2Relax) in comparison with normal in-person care, the standard method for managing stress in military and civilian populations. We conducted a cost-minimization analysis. The total cost to the military healthcare system of treating 1000 patients with the app was $106,397. Treating 1000 patients with in-office care cost $68,820. Treatment using the app became less expensive than in-office treatment at approximately 1600 users. From the perspective of the civilian healthcare system, treatment using the app became less expensive than in-office treatment at approximately 1500 users. An online tool was used to obtain data about the number of app downloads and usage sessions. A total of 47,000 users had accessed the app for 10–30 min sessions in the 2.5 years since the release of the app. Assuming that all 47,000 users were military beneficiaries, the savings to the military healthcare system would be $2.7 million; if the 47,000 users were civilian, the savings to the civilian healthcare system would be $2.9 million. Because of the large number of potential users, the total societal savings resulting from self-care using the app may be considerable. Accepted: 29 August 2014
Introduction Health care applications (‘‘apps’’) on smartphones and tablet computers provide a convenient way of detecting and monitoring health conditions, as well as a means of providing education and self-care. However, there is little published data about the usability, clinical efficacy and economic benefit of self-help services that can be accessed via mobile devices. On the other hand, there is significant interest from health care organisations in understanding the costs and benefits of these technologies in order to make decisions about implementation. The development of mobile health apps is one function of the National Center for Telehealth and Technology (part of the US Department of Defense). The goal is to improve psychological health and traumatic brain injury conditions for the military community. Mobile health apps which are developed for the military are also made freely available to the public. One of these apps, Breathe2Relax (B2R), provides instruction on diaphragmatic breathing. Diaphragmatic breathing, also called relaxation breathing, deep breathing or breathing retraining is often taught alongside other stress reduction skills, such as progressive muscle relaxation, meditation or biofeedback.1 Diaphragmatic breathing is used as a component of several behavioural health therapies, including Mindfulness Based Cognitive Therapy, Mindfulness Based Stress
Reduction, Cognitive Behavioral Therapy,2 as well as other treatments such as Acceptance and Commitment Therapy and Dialectical Behavioral Therapy.3 As part of a larger treatment regimen, diaphragmatic breathing has been shown to be effective in the treatment of a wide range of physical and psychosomatic disorders such as fibromyalgia and chronic pain, as well as with non-clinical populations in reducing stress.4 The B2R app provides instruction on diaphragmatic breathing similar to that provided in-person. The app uses graphics, animation, narration and videos to teach diaphragmatic breathing skills. It allows users to learn and practice this skill on their own, or as part of a stress management programme supervised by a healthcare professional. The app allows users to record their stress level on a visual analogue scale displayed on the screen. It also provides detailed information about the effects of stress on 1 National Center for Telehealth and Technology, Defense Centers of Excellence for Psychological Health and Traumatic Brain Injury, Tacoma, USA 2 Department of Psychiatry and Behavioral Sciences, School of Medicine, University of Washington, Seattle, USA 3 School of Pharmacy, University of Washington, Seattle, USA
Corresponding author: Dr David D Luxton, National Center for Telehealth and Technology, 9933 West Hayes Street, Joint Base Lewis-McChord WA 98431, USA. Email: [email protected]
Downloaded from jtt.sagepub.com at Bobst Library, New York University on April 28, 2015
432
Journal of Telemedicine and Telecare 20(8)
the body and it includes a ‘‘virtual body scanner’’ animation that shows how each part of the body reacts to stress. The aim of the present study was to calculate the cost of providing stress reduction care with the B2R app in comparison with normal office care, the standard method for managing stress in military and civilian populations.
Methods We conducted a cost-minimization analysis, comparing the cost of training 1000 patients using the B2R app with in-person training conducted by health care professionals. A cost-minimization analysis assumes that the interventions are equally effective.5,6 Although the clinical effectiveness of the B2R app has not been evaluated, it has a satisfactory theoretical basis, especially regarding its training content. For the present analysis, use of the app was assumed to be equivalent to in-person instruction of relaxation breathing. Costs were determined from the perspective of the provider (the US military health system, MHS). Because the B2R app can be used by people who are not MHS beneficiaries, we also conducted the cost-minimization analysis from the perspective of the civilian healthcare system.
In-person training – military The total cost of conventional, in-person training for 1000 military patients was based on the average cost of MHSpurchased care plus the cost of the patient’s time. Costs incurred by patients that were not reimbursed by the government were not included. Fixed costs such as infrastructure and equipment were not included. The Current Procedural Terminology (CPT) code used to value the cost of MHS-purchased care was code number 90804, ‘‘Individual psychotherapy, insight oriented, behavior modifying and/or supportive, in an office or outpatient facility, approximately 20 to 30 minutes face-to-face with the patient’’. In 2011, the average cost of MHS-purchased care for this code was $58.82 per patient. The cost of 30 min of patient time was based on 2011 regular military compensation estimates.7 We used the most common ranks for enlisted military personnel (E3– E5)8 with four years of service, giving a rate of $20 per hour (i.e. $10.00 per half hour).
App training – military The total cost of training 1000 military patients via the app was based on the development cost of the app plus the cost of the patients’ time. Costs incurred by patients that were not reimbursed by the government were not included. Fixed costs such as infrastructure and equipment were not included. The development of the app required five staff. The range of personnel costs is shown in Table 1; the upper
Table 1. Cost ($) of developing and deploying the Breathe2Relax app.
Hourly rate Project leader Project manager Psychologist Graphic designer Developer Subtotal Total
iOS
Android
Hours Cost
Hours Cost
49.43–64.26 6 70.44–93.63 32 41.53–64.26 127 44.73–59.47 148 54.11–71.92 483
385 2996 8161 8801 34,737 55,080
n/a 48 n/a n/a 512
n/a 4494 n/a n/a 36,823 41,317 96,397
personnel cost value was used. The cost of developing and deploying the Apple iOS and Android versions of B2R are shown in Table 1. It takes approximately 30 min to conduct one full training and practice cycle (initial session) of B2R use. The same cost of patient time was assumed, $10.00 per half hour.
In-person training – civilian The total cost of conventional, in-person training for 1000 patients was based on the average cost of the same CPT code (90804) for civilian patients covered by health insurance plans in the US (See Table 2.). We used a commercial insurance database (Truven Health Analytics Marketscan Commercial Claims and Encounters Database), which contains inpatient, outpatient and pharmacy claims. In 2011, the average cost for the 90804 CPT code was $62.80 per patient. The development cost of the B2R app was assumed to be the same. Since the civilian healthcare system does not pay for the patient’s time, this was not included.
App training – civilian The total cost of training 1000 civilian patients via the app was based on the development cost of the app (See Table 2.). The cost of the patients’ time was not included.
App usage data An online tool (Flurry Analytics) was used to determine the number of downloads and details of the usage sessions.9 The tool grouped session times into categories; we chose the category 15–30 min of use. We collected data regarding app usage from 2011.
Cost minimization analysis We built a cost model using a spreadsheet (Excel, Microsoft) to compare the cost and savings associated with treating patients using the B2R app versus in-office care over a one-year period. The model outputs included per session cost components, app development costs,
Downloaded from jtt.sagepub.com at Bobst Library, New York University on April 28, 2015
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Table 2. Total costs for 1000 patients (in 2011 dollars). Since the evaluation was for a single year (2011), discounting was not applied. Breathe2Relax (n ¼ 1000) 2a. Cost to the military healthcare system Cost of 1000 sessions (CPT code) 0 Cost of patient time 10,000 (30 min per session) Cost of app 96,397 Total 106,397 2b. Cost to the civilian healthcare system Cost of 1000 sessions (CPT code) 0 Cost of patient time N/A (30 min per session) Cost of app 96,397 Total 96,397
In-office (n ¼ 1000) 58,820 10,000 n/a 68,820 62,800 N/A n/a 62,800
the savings to the MHS since release of the app (approximately 2.5 years) would be $2.7 million; if the 47,000 users were civilian, the savings to the civilian healthcare system would be $2.9 million. That is, the savings would be approximately $1 million per annum assuming that people (whether military or civilian) used the app instead of in-person equivalent care.
Sensitivity analysis A one-way sensitivity analysis revealed that the care reimbursement cost and B2R app development cost were the most influential variables from both the MHS and civilian perspectives.
Discussion
One-way and probabilistic (Monte Carlo) sensitivity analyses were performed to ascertain parameter and model uncertainty, and the reliability of the results based on the input assumptions. These analyses involved varying each model input individually based on either the ends of its 95% confidence interval or by 10% when measures of parameter variance were not available.
In the present study we used a simple economic model for analysis, which included the development costs of the app. The economic advantages of using the app versus in-office care began at approximately 1600 users. Because the B2R app has been used by far more people, the present analysis suggests that it is economically beneficial to both the military and civilian healthcare systems. Mobile health apps may also be used within a stepped care framework. Stepped care is a model of healthcare delivery in which simpler and less expensive (but effective) treatments are provided first, and more complex and expensive care is reserved for people who do not benefit from first-line treatment.10 Thus mobile health apps could be used to help people manage symptoms on their own so that limited healthcare resources can be more efficiently allocated. Overall, well-designed mobile health apps have the potential to reduce costs, and improve efficiency while maintaining quality care.
Results
Limitations
The cost to the military healthcare system of treating 1000 patients using the app was $106,397, of which 91% was the cost of app development, see Table 2a. Treating 1000 patients with in-office care cost $68,820. Thus, treatment using the app cost $37,500 more than conventional treatment, an increase of about 50%. However, application development was a fixed cost, which remained constant as the number of patients treated increased. Treatment using the app became less expensive than in-office treatment at approximately 1600 users (Figure 1). The cost to the civilian healthcare system of treating 1000 patients using the app was simply the cost of the app development, $96,397, see Table 2b. This was a fixed cost. Treatment using the app became less expensive than inoffice treatment at approximately 1500 users (Figure 2). By July 2013 there had been 298,000 app users. Of that total, 47,000 users had accessed the app for 10–30 min sessions, 242,800 had used it for less than 10 min sessions, and 8200 users had accessed the app for longer sessions. Assuming that the 47,000 users were MHS beneficiaries,
The present study had several limitations. First, the costminimization analysis was theoretical and has not been tested prospectively. It is not known whether people who used the B2R app would have otherwise used equivalent in-person care. Moreover, although B2R was an app developed for the military community, we were unable to ascertain from the Flurry Analytics data whether the users of the B2R app were MHS beneficiaries or not. The overall cost savings in both the military and civilian analyses should thus be viewed as potential savings. In addition, there are no available data on the effectiveness of the B2R app for training users in diaphragmatic breathing techniques or as a treatment. Therefore, a limiting factor to this analysis is our knowledge of the ability of the app to adequately replace an in-person training session. Nonetheless, the analysis suggests substantial economic advantages of B2R for both military and civilian users. The complex trajectory of health conditions can incur direct and indirect costs that are difficult to capture.
patient time cost offsets and total costs. Scenario analyses were performed to determine the optimum treatment cohort size by varying the size of the cohorts treated with each intervention.
Sensitivity analyses
Downloaded from jtt.sagepub.com at Bobst Library, New York University on April 28, 2015
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Journal of Telemedicine and Telecare 20(8)
Figure 1. Cost of in-office training and B2R training from the perspective of the military healthcare system.
Figure 2. Cost of in-office training and B2R training from the perspective of the civilian health system.
Co-occurring medical and psychiatric conditions, as well as the potential discovery of new conditions once treatment has been initiated, can add to the complexity of estimating treatment costs.11 Patient compliance, treatment satisfaction, ease of treatment delivery, as well as comfort with technology are also important factors that may influence treatment effectiveness and costs. Other client population characteristics may also be germane to economic analysis, such as cultural subgroups, geographical location (e.g. rural vs. urban regions), and other accessibility variables (e.g. economic status, infrastructure access). These matters should be considered in future economic evaluations of mobile health apps.
Conclusion The present study suggests that a self-help app can provide substantial cost-savings in relation to in-office care, for both the military and civilian healthcare systems. There is potentially a large number of users, so the total savings may be considerable. Moreover, there is an economic benefit to society when affordable self-care options are made widely available to the public. While many health and wellness apps are available, there is little information about their clinical effectiveness. Further research is needed, that includes clinical validation of mobile health apps as well as economic evaluations of them.
Downloaded from jtt.sagepub.com at Bobst Library, New York University on April 28, 2015
Luxton et al.
435
Acknowledgements We thank Matthew Higgins and Ying Zhang who assisted with cost data capture and Colonel Vincent Mysliwiec who assisted with testing the app. The views expressed are those of the authors and do not reflect the official policy or position of the Department of Defense of the US Government.
References 1. Barrows KA, Jacobs BP. Mind-body medicine. An introduction and review of the literature. Med Clin North Am 2002;86:11–31. 2. Hofmann SG, Sawyer AT, Witt AA, Oh D. The effect of mindfulness-based therapy on anxiety and depression: a meta-analytic review. J Consult Clin Psychol 2010;78:169–83. 3. Kahl KG, Winter L, Schweiger U. The third wave of cognitive behavioural therapies: what is new and what is effective? Curr Opin Psychiatry 2012;25:522–8. 4. Grossman P, Niemann L, Schmidt S, Walach H. Mindfulness-based stress reduction and health benefits. A meta-analysis. J Psychosom Res 2004;57:35–43. 5. Petitti DB. Meta-Analysis, Decision Analysis and CostEffectiveness Analysis: methods for quantitative synthesis in medicine. 2nd edn. New York: Oxford University Press, 2000.
6. Gold MR, Siegel JE, Russell LB, Weinstein MC. CostEffectiveness in Health and Medicine. New York: Oxford University Press, 1996. 7. Office of the Secretary of Defense. Regular Military Compensation Calculator. See http://militarypay.defense. gov/mpcalcs/Calculators/RMC.aspx (last checked 26 August 2014). 8. Office of the Deputy Under Secretary of Defense (Military Community and Family Policy) 2012. 2011 Demographics: profile of the military community. See http://www.military onesource.mil/12038/MOS/Reports/2011_Demographics_ Report.pdf (last checked 26 August 2014). 9. Flurry Inc. See http://www.flurry.com/flurry-analytics.html (last checked 26 August 2014). 10. Bower P, Gilbody S. Stepped care in psychological therapies: access, effectiveness and efficiency. Narrative literature review. Br J Psychiatry 2005;186:11–7. 11. Luxton DD. Considerations for planning and evaluating economic analyses of telemental health. Psychol Serv 2013;10:276–82.
Downloaded from jtt.sagepub.com at Bobst Library, New York University on April 28, 2015
Mobile app self-care versus in-office care for stress reduction: a cost minimization analysis
Journal of Telemedicine and Telecare 2014, Vol. 20(8) 431–435 ! The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/1357633X14555616 jtt.sagepub.com
David D Luxton1,2, Ryan N Hansen3 and Katherine Stanfill1
Summary We calculated the cost of providing stress reduction care with a mobile phone app (Breathe2Relax) in comparison with normal in-person care, the standard method for managing stress in military and civilian populations. We conducted a cost-minimization analysis. The total cost to the military healthcare system of treating 1000 patients with the app was $106,397. Treating 1000 patients with in-office care cost $68,820. Treatment using the app became less expensive than in-office treatment at approximately 1600 users. From the perspective of the civilian healthcare system, treatment using the app became less expensive than in-office treatment at approximately 1500 users. An online tool was used to obtain data about the number of app downloads and usage sessions. A total of 47,000 users had accessed the app for 10–30 min sessions in the 2.5 years since the release of the app. Assuming that all 47,000 users were military beneficiaries, the savings to the military healthcare system would be $2.7 million; if the 47,000 users were civilian, the savings to the civilian healthcare system would be $2.9 million. Because of the large number of potential users, the total societal savings resulting from self-care using the app may be considerable. Accepted: 29 August 2014
Introduction Health care applications (‘‘apps’’) on smartphones and tablet computers provide a convenient way of detecting and monitoring health conditions, as well as a means of providing education and self-care. However, there is little published data about the usability, clinical efficacy and economic benefit of self-help services that can be accessed via mobile devices. On the other hand, there is significant interest from health care organisations in understanding the costs and benefits of these technologies in order to make decisions about implementation. The development of mobile health apps is one function of the National Center for Telehealth and Technology (part of the US Department of Defense). The goal is to improve psychological health and traumatic brain injury conditions for the military community. Mobile health apps which are developed for the military are also made freely available to the public. One of these apps, Breathe2Relax (B2R), provides instruction on diaphragmatic breathing. Diaphragmatic breathing, also called relaxation breathing, deep breathing or breathing retraining is often taught alongside other stress reduction skills, such as progressive muscle relaxation, meditation or biofeedback.1 Diaphragmatic breathing is used as a component of several behavioural health therapies, including Mindfulness Based Cognitive Therapy, Mindfulness Based Stress
Reduction, Cognitive Behavioral Therapy,2 as well as other treatments such as Acceptance and Commitment Therapy and Dialectical Behavioral Therapy.3 As part of a larger treatment regimen, diaphragmatic breathing has been shown to be effective in the treatment of a wide range of physical and psychosomatic disorders such as fibromyalgia and chronic pain, as well as with non-clinical populations in reducing stress.4 The B2R app provides instruction on diaphragmatic breathing similar to that provided in-person. The app uses graphics, animation, narration and videos to teach diaphragmatic breathing skills. It allows users to learn and practice this skill on their own, or as part of a stress management programme supervised by a healthcare professional. The app allows users to record their stress level on a visual analogue scale displayed on the screen. It also provides detailed information about the effects of stress on 1 National Center for Telehealth and Technology, Defense Centers of Excellence for Psychological Health and Traumatic Brain Injury, Tacoma, USA 2 Department of Psychiatry and Behavioral Sciences, School of Medicine, University of Washington, Seattle, USA 3 School of Pharmacy, University of Washington, Seattle, USA
Corresponding author: Dr David D Luxton, National Center for Telehealth and Technology, 9933 West Hayes Street, Joint Base Lewis-McChord WA 98431, USA. Email: [email protected]
Downloaded from jtt.sagepub.com at Bobst Library, New York University on April 28, 2015
432
Journal of Telemedicine and Telecare 20(8)
the body and it includes a ‘‘virtual body scanner’’ animation that shows how each part of the body reacts to stress. The aim of the present study was to calculate the cost of providing stress reduction care with the B2R app in comparison with normal office care, the standard method for managing stress in military and civilian populations.
Methods We conducted a cost-minimization analysis, comparing the cost of training 1000 patients using the B2R app with in-person training conducted by health care professionals. A cost-minimization analysis assumes that the interventions are equally effective.5,6 Although the clinical effectiveness of the B2R app has not been evaluated, it has a satisfactory theoretical basis, especially regarding its training content. For the present analysis, use of the app was assumed to be equivalent to in-person instruction of relaxation breathing. Costs were determined from the perspective of the provider (the US military health system, MHS). Because the B2R app can be used by people who are not MHS beneficiaries, we also conducted the cost-minimization analysis from the perspective of the civilian healthcare system.
In-person training – military The total cost of conventional, in-person training for 1000 military patients was based on the average cost of MHSpurchased care plus the cost of the patient’s time. Costs incurred by patients that were not reimbursed by the government were not included. Fixed costs such as infrastructure and equipment were not included. The Current Procedural Terminology (CPT) code used to value the cost of MHS-purchased care was code number 90804, ‘‘Individual psychotherapy, insight oriented, behavior modifying and/or supportive, in an office or outpatient facility, approximately 20 to 30 minutes face-to-face with the patient’’. In 2011, the average cost of MHS-purchased care for this code was $58.82 per patient. The cost of 30 min of patient time was based on 2011 regular military compensation estimates.7 We used the most common ranks for enlisted military personnel (E3– E5)8 with four years of service, giving a rate of $20 per hour (i.e. $10.00 per half hour).
App training – military The total cost of training 1000 military patients via the app was based on the development cost of the app plus the cost of the patients’ time. Costs incurred by patients that were not reimbursed by the government were not included. Fixed costs such as infrastructure and equipment were not included. The development of the app required five staff. The range of personnel costs is shown in Table 1; the upper
Table 1. Cost ($) of developing and deploying the Breathe2Relax app.
Hourly rate Project leader Project manager Psychologist Graphic designer Developer Subtotal Total
iOS
Android
Hours Cost
Hours Cost
49.43–64.26 6 70.44–93.63 32 41.53–64.26 127 44.73–59.47 148 54.11–71.92 483
385 2996 8161 8801 34,737 55,080
n/a 48 n/a n/a 512
n/a 4494 n/a n/a 36,823 41,317 96,397
personnel cost value was used. The cost of developing and deploying the Apple iOS and Android versions of B2R are shown in Table 1. It takes approximately 30 min to conduct one full training and practice cycle (initial session) of B2R use. The same cost of patient time was assumed, $10.00 per half hour.
In-person training – civilian The total cost of conventional, in-person training for 1000 patients was based on the average cost of the same CPT code (90804) for civilian patients covered by health insurance plans in the US (See Table 2.). We used a commercial insurance database (Truven Health Analytics Marketscan Commercial Claims and Encounters Database), which contains inpatient, outpatient and pharmacy claims. In 2011, the average cost for the 90804 CPT code was $62.80 per patient. The development cost of the B2R app was assumed to be the same. Since the civilian healthcare system does not pay for the patient’s time, this was not included.
App training – civilian The total cost of training 1000 civilian patients via the app was based on the development cost of the app (See Table 2.). The cost of the patients’ time was not included.
App usage data An online tool (Flurry Analytics) was used to determine the number of downloads and details of the usage sessions.9 The tool grouped session times into categories; we chose the category 15–30 min of use. We collected data regarding app usage from 2011.
Cost minimization analysis We built a cost model using a spreadsheet (Excel, Microsoft) to compare the cost and savings associated with treating patients using the B2R app versus in-office care over a one-year period. The model outputs included per session cost components, app development costs,
Downloaded from jtt.sagepub.com at Bobst Library, New York University on April 28, 2015
Luxton et al.
433
Table 2. Total costs for 1000 patients (in 2011 dollars). Since the evaluation was for a single year (2011), discounting was not applied. Breathe2Relax (n ¼ 1000) 2a. Cost to the military healthcare system Cost of 1000 sessions (CPT code) 0 Cost of patient time 10,000 (30 min per session) Cost of app 96,397 Total 106,397 2b. Cost to the civilian healthcare system Cost of 1000 sessions (CPT code) 0 Cost of patient time N/A (30 min per session) Cost of app 96,397 Total 96,397
In-office (n ¼ 1000) 58,820 10,000 n/a 68,820 62,800 N/A n/a 62,800
the savings to the MHS since release of the app (approximately 2.5 years) would be $2.7 million; if the 47,000 users were civilian, the savings to the civilian healthcare system would be $2.9 million. That is, the savings would be approximately $1 million per annum assuming that people (whether military or civilian) used the app instead of in-person equivalent care.
Sensitivity analysis A one-way sensitivity analysis revealed that the care reimbursement cost and B2R app development cost were the most influential variables from both the MHS and civilian perspectives.
Discussion
One-way and probabilistic (Monte Carlo) sensitivity analyses were performed to ascertain parameter and model uncertainty, and the reliability of the results based on the input assumptions. These analyses involved varying each model input individually based on either the ends of its 95% confidence interval or by 10% when measures of parameter variance were not available.
In the present study we used a simple economic model for analysis, which included the development costs of the app. The economic advantages of using the app versus in-office care began at approximately 1600 users. Because the B2R app has been used by far more people, the present analysis suggests that it is economically beneficial to both the military and civilian healthcare systems. Mobile health apps may also be used within a stepped care framework. Stepped care is a model of healthcare delivery in which simpler and less expensive (but effective) treatments are provided first, and more complex and expensive care is reserved for people who do not benefit from first-line treatment.10 Thus mobile health apps could be used to help people manage symptoms on their own so that limited healthcare resources can be more efficiently allocated. Overall, well-designed mobile health apps have the potential to reduce costs, and improve efficiency while maintaining quality care.
Results
Limitations
The cost to the military healthcare system of treating 1000 patients using the app was $106,397, of which 91% was the cost of app development, see Table 2a. Treating 1000 patients with in-office care cost $68,820. Thus, treatment using the app cost $37,500 more than conventional treatment, an increase of about 50%. However, application development was a fixed cost, which remained constant as the number of patients treated increased. Treatment using the app became less expensive than in-office treatment at approximately 1600 users (Figure 1). The cost to the civilian healthcare system of treating 1000 patients using the app was simply the cost of the app development, $96,397, see Table 2b. This was a fixed cost. Treatment using the app became less expensive than inoffice treatment at approximately 1500 users (Figure 2). By July 2013 there had been 298,000 app users. Of that total, 47,000 users had accessed the app for 10–30 min sessions, 242,800 had used it for less than 10 min sessions, and 8200 users had accessed the app for longer sessions. Assuming that the 47,000 users were MHS beneficiaries,
The present study had several limitations. First, the costminimization analysis was theoretical and has not been tested prospectively. It is not known whether people who used the B2R app would have otherwise used equivalent in-person care. Moreover, although B2R was an app developed for the military community, we were unable to ascertain from the Flurry Analytics data whether the users of the B2R app were MHS beneficiaries or not. The overall cost savings in both the military and civilian analyses should thus be viewed as potential savings. In addition, there are no available data on the effectiveness of the B2R app for training users in diaphragmatic breathing techniques or as a treatment. Therefore, a limiting factor to this analysis is our knowledge of the ability of the app to adequately replace an in-person training session. Nonetheless, the analysis suggests substantial economic advantages of B2R for both military and civilian users. The complex trajectory of health conditions can incur direct and indirect costs that are difficult to capture.
patient time cost offsets and total costs. Scenario analyses were performed to determine the optimum treatment cohort size by varying the size of the cohorts treated with each intervention.
Sensitivity analyses
Downloaded from jtt.sagepub.com at Bobst Library, New York University on April 28, 2015
434
Journal of Telemedicine and Telecare 20(8)
Figure 1. Cost of in-office training and B2R training from the perspective of the military healthcare system.
Figure 2. Cost of in-office training and B2R training from the perspective of the civilian health system.
Co-occurring medical and psychiatric conditions, as well as the potential discovery of new conditions once treatment has been initiated, can add to the complexity of estimating treatment costs.11 Patient compliance, treatment satisfaction, ease of treatment delivery, as well as comfort with technology are also important factors that may influence treatment effectiveness and costs. Other client population characteristics may also be germane to economic analysis, such as cultural subgroups, geographical location (e.g. rural vs. urban regions), and other accessibility variables (e.g. economic status, infrastructure access). These matters should be considered in future economic evaluations of mobile health apps.
Conclusion The present study suggests that a self-help app can provide substantial cost-savings in relation to in-office care, for both the military and civilian healthcare systems. There is potentially a large number of users, so the total savings may be considerable. Moreover, there is an economic benefit to society when affordable self-care options are made widely available to the public. While many health and wellness apps are available, there is little information about their clinical effectiveness. Further research is needed, that includes clinical validation of mobile health apps as well as economic evaluations of them.
Downloaded from jtt.sagepub.com at Bobst Library, New York University on April 28, 2015
Luxton et al.
435
Acknowledgements We thank Matthew Higgins and Ying Zhang who assisted with cost data capture and Colonel Vincent Mysliwiec who assisted with testing the app. The views expressed are those of the authors and do not reflect the official policy or position of the Department of Defense of the US Government.
References 1. Barrows KA, Jacobs BP. Mind-body medicine. An introduction and review of the literature. Med Clin North Am 2002;86:11–31. 2. Hofmann SG, Sawyer AT, Witt AA, Oh D. The effect of mindfulness-based therapy on anxiety and depression: a meta-analytic review. J Consult Clin Psychol 2010;78:169–83. 3. Kahl KG, Winter L, Schweiger U. The third wave of cognitive behavioural therapies: what is new and what is effective? Curr Opin Psychiatry 2012;25:522–8. 4. Grossman P, Niemann L, Schmidt S, Walach H. Mindfulness-based stress reduction and health benefits. A meta-analysis. J Psychosom Res 2004;57:35–43. 5. Petitti DB. Meta-Analysis, Decision Analysis and CostEffectiveness Analysis: methods for quantitative synthesis in medicine. 2nd edn. New York: Oxford University Press, 2000.
6. Gold MR, Siegel JE, Russell LB, Weinstein MC. CostEffectiveness in Health and Medicine. New York: Oxford University Press, 1996. 7. Office of the Secretary of Defense. Regular Military Compensation Calculator. See http://militarypay.defense. gov/mpcalcs/Calculators/RMC.aspx (last checked 26 August 2014). 8. Office of the Deputy Under Secretary of Defense (Military Community and Family Policy) 2012. 2011 Demographics: profile of the military community. See http://www.military onesource.mil/12038/MOS/Reports/2011_Demographics_ Report.pdf (last checked 26 August 2014). 9. Flurry Inc. See http://www.flurry.com/flurry-analytics.html (last checked 26 August 2014). 10. Bower P, Gilbody S. Stepped care in psychological therapies: access, effectiveness and efficiency. Narrative literature review. Br J Psychiatry 2005;186:11–7. 11. Luxton DD. Considerations for planning and evaluating economic analyses of telemental health. Psychol Serv 2013;10:276–82.
Downloaded from jtt.sagepub.com at Bobst Library, New York University on April 28, 2015
