How Do Mental Health App Generate Value? A GUIDE

ByDr. Mega Boo Boo
Generating Value with Mental Health Apps — GIVEMEA Study Guide
GIVEMEA Study Guide · Digital Health & mHealth Policy

Generating Value with Mental Health Apps

Adam C. Powell, John B. Torous, Joseph Firth & Kenneth R. Kaufman · BJPsych Open 6, e16, 1–5 · 2020

Secondary Research / Narrative Review International Team (USA · UK · AUS) Open Access · CC-BY 4.0 Focus: USA Reimbursement
250k+Health Apps Available
300+Anxiety Apps (iOS USA)
$300Cost/Employee/Year
21Reviews in Meta-Review
39References Cited
Central Argument
Mental health apps generate value across multiple stakeholders — patients, providers, and health plans — but are currently reimbursed through channels designed for other purposes. A new app-specific reimbursement channel, analogous to those used for drugs, devices, and laboratory tests, is needed to unlock their full potential.

Research Question

How are mental health apps currently generating value and being reimbursed across the world — particularly in the USA — and what reforms to reimbursement mechanisms are needed to enable apps to fulfil their potential in mental healthcare?

The Value Framework

The authors apply Porter’s (2010) definition: value in healthcare = outcomes ÷ cost. Apps generate value differently depending on how and for whom they are used. Patients benefit through improved mental health quality, increased care access, and reduced costs. Providers gain through increased demand, reduced operating costs, and better patient engagement. Health plans benefit from substitution savings and early intervention preventing higher-acuity episodes. Crucially, the paper notes that the majority of health apps have not yet demonstrated value — economic outcomes data remain sparse and methodologically limited.

The Reimbursement Problem

Apps do not fit neatly into existing reimbursement frameworks. CPT codes are built around physician time and practice expenses — but many apps operate autonomously, with minimal clinician involvement. When apps are billed as devices via HCPCS codes (e.g. E1399, T1505), those codes were never designed for software. Direct-to-consumer models require patients to pay out-of-pocket, limiting access and adoption. The closure of the Lantern mental health app in 2018 — linked to the difficulties of direct-to-consumer markets — illustrates the sustainability risk of operating without reliable reimbursement pathways.

Apps Are Not Replacing Care — They Are Extending It

The paper’s most important clinical framing: initial enthusiasm led to speculation that apps could fully substitute for in-person care. Increasing evidence suggests that a more effective and realistic role is to augment and extend clinical care rather than replace it. Apps exist along a spectrum from full care substitutes (used independently by patients) to backstage infrastructure (supporting administrative and care management functions behind the scenes). In the future, the distinction between “care delivered by an app” and “care not delivered by an app” will likely disappear entirely — apps will be viewed as foundational infrastructure, much as websites are today.

Reimbursement Channels for Mental Health Apps in the USA

Channel Mechanism Best Suited For Key Limitation for Apps
CPT Codes Physician work + practice expenses + malpractice, adjusted geographically via GPCI Apps tightly integrated with physician services (e.g. administrative tools) Inappropriate for autonomous apps with minimal physician involvement; no CPT code exists for autonomous treatment
Device-Like (HCPCS) Codes E1399 (miscellaneous DME) and T1505 (electronic medication compliance) Apps billed as durable medical equipment or compliance tools Codes not designed for software; requires FDA approval pathway for prescription apps
Drug-Like Prescription digital therapeutics reimbursed like pharmaceuticals Prescription-only apps with FDA clearance Prescribing authority required — excludes psychologists, social workers in many states
Lab-Like Reimbursement for data generated by apps (e.g. monitoring codes 99453, 99454, 99457) Apps monitoring physiological parameters remotely Existing codes are for physiological (not behavioural) monitoring; unsuitable for mental health measurement-based care
Bundled / Capitated App costs absorbed within a lump-sum payment to a provider Apps used to reduce overall cost of an episode of care One-off; non-transparent; does not create visible incentives for app development investment
Direct Payment Out-of-pocket by patient, or employer/provider paying app vendor directly Consumer wellness apps not requiring clinical evidence Limits access; unsustainable business model (e.g. Lantern closure 2018)

■ Reimbursement & Finance   ■ Digital Health & Technology   ■ Risks & Barriers   ■ Policy & Regulation

Reimbursement & Finance

CPT Code
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CPT Code
Current Procedural Terminology code — the primary US system for reimbursing healthcare provider services. Values are set based on physician work, malpractice, and practice expenses, then adjusted by the Geographic Practice Cost Index. CPT is poorly suited to autonomous apps where physician input is minimal.
HCPCS Codes
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HCPCS Codes
Healthcare Common Procedure Coding System — used to bill for supplies, devices, and non-physician services. Mental health apps are being reimbursed under codes E1399 (miscellaneous durable medical equipment) and T1505 (electronic medication compliance devices), even though these codes were never designed for software.
Bundled / Capitated Payment
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Bundled / Capitated Payment
A fixed lump sum paid by a health plan to a provider to cover a defined episode of care or a population of patients. App costs may be absorbed within this payment. While flexible, these arrangements are one-off and non-transparent — making it hard for developers to predict or plan around the financial opportunity.
Value in Healthcare
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Value in Healthcare
Defined by Porter (2010) as outcomes divided by cost. Powell et al. apply this framework to mental health apps: value depends on both the outcomes delivered (to patients, providers, and health plans) and the costs incurred. Most apps have not yet demonstrated value because rigorous outcomes and cost-effectiveness data remain scarce.
Direct-to-Consumer (DTC)
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Direct-to-Consumer
A model in which patients pay out-of-pocket for apps without any insurer or employer reimbursement. It is the simplest to implement and requires no clinical evidence — but it limits access to those who can afford to pay, and the Lantern app’s 2018 closure illustrates its sustainability risks.

Digital Health & Technology

mHealth
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mHealth
Mobile health — the use of mobile devices (primarily smartphones) to support healthcare delivery. In the context of this paper, mHealth encompasses the full spectrum of mental health apps, from wellness and screening tools to prescription digital therapeutics and care management software.
Digital Therapeutics
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Digital Therapeutics
App-based interventions that deliver evidence-based therapeutic content as a standalone or adjunct treatment. In contrast to general wellness apps, digital therapeutics may seek FDA clearance and pursue prescription-based reimbursement, positioning them more analogously to pharmaceutical products.
Measurement-Based Care
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Measurement-Based Care
A clinical practice in which validated symptom rating scales are administered regularly and used to guide treatment decisions. Apps can facilitate measurement-based care by enabling patients to complete assessments between appointments. However, existing CPT monitoring codes (99453, 99454, 99457) cover physiological — not behavioural — parameters, creating a reimbursement gap.
FHIR & SMART
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FHIR & SMART
Fast Healthcare Interoperability Resources (FHIR) and SMART on FHIR are US federal government-backed informatics standards enabling apps to securely exchange data with electronic health records. Powell et al. identify these as providing a clear technical pathway for apps to become integrated into clinical workflows — solving fragmentation if adopted widely.
IntelliCare
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IntelliCare
A suite of evidence-based mental health apps developed at Northwestern University, designed for treatment of depression and anxiety. Cited by Powell et al. as a counter-example to the majority of commercial apps that do not follow evidence-based guidelines — illustrating that quality apps exist, but are the exception rather than the rule in app stores.

Risks & Barriers

Privacy Risk
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Privacy Risk
Research reviewed in the paper (Huckvale et al. 2019) found that many mental health apps for depression and smoking cessation have problematic data sharing and privacy practices. The combination of sensitive health data and weak privacy standards is a significant patient safety concern — and a barrier to clinician recommendation.
Prescribing Authority Gap
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Prescribing Authority Gap
Mental health services are frequently delivered by professionals who lack prescribing authority — including social workers and psychologists in many US states. Prescription-based reimbursement channels for apps are therefore a structural barrier to patient access, since these clinicians cannot legally prescribe FDA-regulated apps.
Evidence Gap
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Evidence Gap
Despite widespread use, most mental health apps have not demonstrated clinical effectiveness or cost-effectiveness. A meta-review of 21 reviews found insufficient evidence on cost-effectiveness for young people; studies of top-funded digital health companies found mental health apps had only examined feasibility, not clinical outcomes. This gap makes it difficult to justify or mandate reimbursement.

Policy & Regulation

FDA Regulatory Discretion
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FDA Regulatory Discretion
The FDA’s policy of choosing not to actively regulate certain categories of mobile medical apps that pose low risk, including many wellness-oriented apps that claim not to be medical devices. This creates a two-tier ecosystem: most mental health apps are unregulated; a smaller number seek formal FDA clearance as medical devices or digital therapeutics.
NHS Apps Library
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NHS Apps Library
A curated catalogue of vetted health apps published by NHS England. Apps listed are free, paid by patients, or available free with a GP prescription/referral. The library also provides a liability disclaimer: any adverse effects are the developer’s — not the recommending clinician’s — responsibility. Powell et al. hold this up as a model the USA could emulate.
Care Fragmentation
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Care Fragmentation
The disconnection between app-based and in-person care that occurs when apps have little or no integration into the traditional clinical workflow. Many current apps increase fragmentation by operating as siloed tools without sharing data with providers. FHIR/SMART standards and tighter clinical integration are proposed as solutions.

Study Design at a Glance

This is a secondary research / narrative review paper — not a systematic review, meta-analysis, or primary data collection study. An international team of four authors (based in the USA, Australia, and the UK) collaborated to synthesise existing literature and policy documents on mental health app use and reimbursement. The paper covers three distinct content areas: current and future use of apps, the value delivered by apps, and reimbursement pathways (with primary focus on the USA).

Research Approach

  • Secondary research: synthesis of published literature, industry reports, government documents, and policy frameworks
  • No primary data collection; no formal search protocol or PRISMA flow reported (distinguishes this from a systematic review)
  • International perspective contributed by team members with experience in Australia (Firth), UK (Firth/Kaufman), and USA (Powell, Torous, Kaufman)
  • Conclusions developed collaboratively by all four authors based on their combined findings

Sources and Evidence Used

  • Industry reports (app store counts, download statistics)
  • Academic literature: systematic reviews, meta-reviews, and primary studies on app effectiveness, privacy, and economics
  • Regulatory documents: FDA guidance, AMA CPT codebooks, CMS coding guidance
  • Policy documents: NHS Apps Library, Mental Health Commission of Canada toolkit, Australian healthdirect
  • Company and news sources: Lantern closure, CVS Health digital initiatives

Strengths

  • Rare international comparative lens: places US reimbursement challenges alongside NHS and Australian models
  • Synthesises both clinical and economic dimensions of app value — rare for a single paper
  • Practical policy recommendations (HCPCS-based app-specific codes) are specific and actionable
  • Open Access publication maximises policy and practitioner reach

Limitations

  • Not a systematic review — search strategy, inclusion/exclusion criteria, and risk of bias assessment are absent
  • Significant conflicts of interest: lead author Powell holds stock in multiple health insurance and hospital corporations and sits on advisory boards of app-related companies
  • Written in 2019/2020 — the regulatory and reimbursement landscape for digital therapeutics has evolved substantially since publication
  • The paper acknowledges that most apps have not demonstrated value, which somewhat undermines the urgency of its reimbursement reform argument
  • Future use predictions are speculative and not empirically derived

Key references cited in Powell et al. (2020) and why they matter to the paper’s argument.

Ref 16

Porter ME (2010) — What Is Value in Health Care?

NEJM 363:2477–81
Conceptual Foundation
Provides the foundational value equation (outcomes ÷ cost) that Powell et al. use to evaluate what mental health apps actually deliver. Without this framework, the paper’s multi-stakeholder analysis of app value would lack a theoretical anchor. Porter’s definition is the lens through which every reimbursement argument is assessed.
Ref 3

Powell, Bowman & Harbin (2019) — Reimbursement of Apps for Mental Health

JMIR Mental Health 6:e14724
Predecessor Paper
The predecessor work by the same lead author that provided the detailed taxonomy of US reimbursement channels illustrated in Figure 1 of this paper. Powell et al. 2020 build directly on this earlier JMIR paper, which is cited as the source for the CPT/device/drug/lab/bundled channel framework. Understanding this predecessor is key to understanding Figure 1.
Ref 12

Huckvale, Torous & Larsen (2019) — Assessment of Data Sharing & Privacy Practices

JAMA Network Open 2:e192542
Safety Evidence Risk Finding
Empirically documented that many mental health apps (for depression and smoking cessation) have problematic data-sharing practices. This finding is crucial to the paper’s argument: reimbursement reform must go hand in hand with quality and privacy standards, not simply open the floodgates to all apps.
Ref 22

Safavi et al. (2019) — Top-Funded Digital Health Companies

Health Affairs 38:115–23
Evidence Gap
Reviewed the studies supported by top-funded digital health companies and found that those in mental health and depression had only examined feasibility — not clinical effectiveness. This is a striking finding that Powell et al. use to support their argument that the evidence base for app value is still underdeveloped, even among well-resourced companies.
Ref 14

Bhugra et al. — WPA-Lancet Psychiatry Commission on the Future of Psychiatry

Lancet Psychiatry 2017; 4:775–818
Clinical Framework
A major international commission that shaped thinking on the role of digital tools in psychiatry’s future. Powell et al. cite it to support the key claim that apps are most effective when augmenting clinical care rather than replacing it — grounding their argument in expert consensus rather than speculation.
Ref 6

BinDhim et al. (2014) — Depression Screening via a Smartphone App

J Am Med Inform Assoc 2014; 22:29–34
Access Example
One of the earliest demonstrations of app-based mental health screening at scale — offering PHQ-9 depression screening to over 8,000 people across 66 countries and linking those with elevated scores to local help. Powell et al. cite this as evidence that apps can extend care reach to populations who might not otherwise seek help.

Click an answer to reveal feedback. Each question locks after answering.

Question 1 of 5
According to Powell et al., how do most mental health apps currently generate value for health plans?
✓ Correct. Health plans benefit from two main sources of app-generated value: substitution savings (apps replacing more expensive care modalities) and prevention savings (early identification and intervention reducing the likelihood of higher-acuity, higher-cost episodes). Neither of these has yet been robustly proven in the literature, but they represent the primary theoretical value proposition for payers.
Not quite. The paper describes health plan value as coming from substitution savings and prevention of higher-acuity situations — not from complete care replacement, data licensing, or government mandates. The authors also note that the evidence base for these savings remains limited.
Question 2 of 5
Why are existing CPT remote monitoring codes (99453, 99454, 99457) unsuitable for reimbursing mental health measurement-based care delivered via apps?
✓ Correct. CPT codes 99453, 99454, and 99457 were designed to reimburse remote monitoring of physiological parameters — think blood pressure cuffs or glucose monitors. They do not map onto the behavioural and psychological data generated by mental health apps, creating a structural gap in the coding system for measurement-based psychiatric care.
The issue is not about FDA clearance, provider type restrictions, or data collection modality. The paper specifically notes that these codes are designed for physiological monitoring and are therefore “unsuitable for use in implementing measurement-based care in the context of behavioural health.”
Question 3 of 5
What does Powell et al. identify as the core structural problem with reimbursing autonomous mental health apps through prescription-based channels?
✓ Correct. Prescription-based reimbursement requires that a clinician with prescribing authority authorise the app. But a large proportion of mental health services are delivered by social workers, psychologists, and counsellors — many of whom lack prescribing authority in their state. This effectively excludes a significant segment of the mental health workforce from facilitating access to reimbursed apps.
The core structural problem Powell et al. identify is about prescribing authority — not cost, IP rights, or legal impossibility. FDA approval is actually achievable for software (several apps have obtained it), but the prescribing authority gap remains a practical barrier to access regardless of regulatory status.
Question 4 of 5
What approach does the paper recommend for the future reimbursement of autonomous mental health apps in the USA?
✓ Correct. The paper’s central policy recommendation is to develop a standardised series of HCPCS codes specifically for app-related procedures — creating a dedicated reimbursement channel that does not require tying app value to physician time. This would parallel the channels used for devices (durable medical equipment), drugs (pharmacy benefit), and lab tests, and would reduce reliance on bespoke, one-off contracts.
The paper recommends a new HCPCS-based app-specific channel — not a blanket app store mandate, an expansion of CPT 96127, or universal FDA drug approval. The existing CPT 96127 only covers brief assessments conducted without physician administration, not autonomous treatment; and drug approval would create the same prescribing authority barriers the authors are trying to reduce.
Question 5 of 5
The paper cites the closure of the Lantern mental health app in 2018. What does this case illustrate?
✓ Correct. The Lantern app’s CEO attributed its closure to the company’s decision to pursue direct-to-consumer markets. Powell et al. use this as a concrete cautionary example: out-of-pocket payment may be the simplest reimbursement model to implement, but it is also the most financially fragile — and its failure has real consequences for patients who depended on the product.
The Lantern case specifically illustrates the financial fragility of direct-to-consumer models — not efficacy comparisons, regulatory requirements, or venture capital reliability. The company’s own leadership cited the DTC market decision as the reason for closure, making it a pointed example of what happens without stable reimbursement infrastructure.
— / 5 Quiz Score
Core Thesis
Mental health apps generate real but largely unproven value — and are being squeezed into reimbursement channels designed for something else. A purpose-built payment mechanism, modelled on existing device and drug channels but decoupled from physician time, is the structural reform needed to enable apps to fulfil their role in mental healthcare.
  • 💰

    Reimbursement Shapes Development

    When reimbursement pathways are opaque or one-off, developers cannot predict or plan for financial returns — and some will choose not to invest. The absence of clear reimbursement is not just a funding problem; it is an innovation suppressor. Transparent, standardised payment channels create the market signals that drive quality app development.

  • 🔗

    The Future Is Augmentation, Not Replacement

    The paper firmly rejects the idea that apps will or should replace in-person mental healthcare. The more evidence-supported model is integration: apps extend clinician reach, support measurement-based care, reduce administrative burden, and engage patients between appointments. In the long term, the app/no-app distinction will disappear — digital tools will simply be part of healthcare infrastructure.

  • ⚠️

    Most Apps Have Not Proved Their Value

    Despite the scale of the market (250,000+ health apps), the evidence base for mental health app effectiveness and cost-effectiveness is strikingly thin. Studies of top-funded companies show feasibility work only — not clinical outcomes. The paper argues for reimbursement reform while acknowledging this gap, implicitly relying on the logic that investment will generate the evidence needed rather than demanding evidence first.

  • 🔐

    Quality and Privacy Must Come Alongside Access

    Expanding reimbursement without addressing quality standards and privacy risks would be counterproductive. Research shows most commercial mental health apps do not follow evidence-based guidelines, and many have problematic data-sharing practices. The NHS Apps Library model — curated, vetted, with explicit liability disclaimers for recommending clinicians — points toward a framework that could address these concerns in parallel with reimbursement reform.

  • ⚖️

    The Prescribing Authority Gap Is an Equity Issue

    Reimbursement systems requiring prescribing authority systematically exclude the majority of the mental health workforce from facilitating app access. Social workers and psychologists see many of the most vulnerable patients — those with limited insurance, those in underserved areas. Designing reimbursement systems around physician prescription requirements recreates the access barriers that apps are meant to solve.

  • 🌍

    International Models Offer Practical Blueprints

    The NHS Apps Library (UK) and Canada’s Mental Health Commission toolkit demonstrate that app reimbursement reform is achievable — not merely theoretical. The UK’s bulk-buy arrangements and curated library with liability protections for recommending clinicians are concrete mechanisms the authors present as models for US policymakers. International comparison is one of this paper’s strongest contributions.

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