Accepted for/Published in: JMIR Mental Health
Date Submitted: May 16, 2019
Open Peer Review Period: May 16, 2019 - Jun 26, 2019
Date Accepted: Jul 8, 2019
(closed for review but you can still tweet)
Reimbursement of Apps for Mental Health: Current Practices and Potential Pathways
ABSTRACT
Background:
While apps and other digital and mobile health (mHealth) tools are helping improve the mental health of Americans, there is not a single channel through which they can all be reimbursed.
Objective:
To shed light on the state of app reimbursement, we have documented ways in which apps can be reimbursed and surveyed stakeholders to understand current reimbursement practices.
Methods:
Individuals from over a dozen stakeholder organizations in digital behavioral and mental health, care delivery, and managed care were interviewed. A review of Current Procedural Terminology (CPT) and Healthcare Common Procedure Coding System (HCSPCS) codes was conducted to determine potential means for reimbursement.
Results:
Interviews and the review of codes revealed that potential channels for app reimbursement include direct payments by employers, healthcare providers, patients, and insurers. Insurers are additionally paying for apps using channels originally designed for devices, drugs, and laboratory tests, as well as via value-based payments and CPT and HCSPCS codes. However, in many cases, it is possible to achieve the requirements of a CPT or HCSPCS code only if an app is used in conjunction with human time and services.
Conclusions:
Currently, many apps face significant barriers to reimbursement. CPT codes are not a viable means of providing compensation for the use of all apps, particularly those involving little physician work. As an alternative, apps have sought clearance from FDA for prescription use as digital therapeutics; a reimbursement mechanism with unproven sustainability. There is a need for simpler reimbursement mechanisms to cover standalone app treatment interventions.
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.