I have built small tools that compress a repetitive task into a few minutes of machine-assisted execution. The result is satisfying. A piece of software can often serve another user at low marginal cost, even though compute, support, security, and maintenance never become literally free.
Psychotherapy has a different production structure. Much of it requires trained attention delivered over time. German digital health applications (Digitale Gesundheitsanwendungen, or DiGA) can be prescribed and reimbursed through their own regulatory path, while access to psychotherapy depends on workforce, regional planning, indication, and available appointments. The two routes are easy to place in one rhetorical comparison and difficult to compare like for like.
William Baumol’s cost-disease model clarifies one pressure in that comparison. It does not decide the policy.
The Seduction of Leverage
The phrase vibe coding describes one version of software development with a language model: describe desired behaviour, let the model draft code, run it, and iterate in natural language. It can lower the barrier to a prototype. It does not remove requirements, domain knowledge, testing, security, or the need to understand a system whose failure matters.
The attraction is leverage. Some software outputs can scale much faster than the labour that produced their first version. That changes which projects feel economically and culturally exciting. It does not follow that every activity should be reorganised to exhibit the same curve.
What Therapy Requires—and What Can Change
A psychotherapy session commonly involves sustained attention between a clinician and a patient. A meta-analysis by Flückiger and colleagues found a robust association between therapeutic alliance and adult psychotherapy outcomes across the included studies [[1]]. Association does not make alliance the sole mechanism of every therapy, establish that techniques are interchangeable, or prove that all care must be one-to-one.
Individual, group, digital, and blended therapies are different interventions with different evidence, risks, and capacity profiles. Technology can change administration, monitoring, exercises, communication, and sometimes delivery. It does not make clinician time and an app the same product. How much a service design changes capacity and outcomes is an empirical question, not a fixed biological ceiling.
What Baumol’s Model Actually Says
Baumol and Bowen’s 1966 example was the performing arts [[2]]. A string quartet still needs four performers for the duration of that quartet. If productivity and wages grow faster elsewhere, a labour-intensive performance experiences relative cost pressure even when its own quality has not declined.
The model predicts a tendency under assumptions about productivity and labour markets. It does not say that costs literally rise without bound, that every component of healthcare is technologically fixed, or that one software advance causes one therapy fee decision. Baumol later applied the argument to labour-intensive services including healthcare and education [[3]].
Psychotherapy contains labour-intensive components, so the analogy is useful. It is not exact. Treatment modalities, administration, training, regulation, regional supply, and clinical need all affect capacity. “Cost disease” is not a diagnosis of laziness and not a complete model of a health system.
There Is an App for That
Germany’s 2019 Digital Healthcare Act created the fast-track framework through which eligible DiGA can enter a federal directory and be prescribed [[4]]. The live BfArM directory is the authoritative place to check a product’s current indication, listing status, and evidence documentation. Counts and prices change; they should be extracted and dated rather than repeated as timeless facts.
Research on the first years of the pathway shows that products may enter permanently or provisionally and that listings can later change [[5]]. That is not evidence that every DiGA is ineffective. Nor does availability establish that a digital product is clinically substitutable for psychotherapy. Suitability depends on the indication, evidence, patient, risks, and intended role in care.
The tempting arithmetic is to divide an app budget by a session fee and report how many therapy sessions the money “could have bought.” I have removed that calculation. A budget does not create trained clinicians, regional seats, appropriate treatment, or appointment time. Comparing financing priorities is legitimate; translating euros mechanically into clinical capacity is not.
Policy Is Not an Equation Output
German fee schedules, needs planning, professional training, crisis services, and DiGA reimbursement have separate institutions and legal mechanisms. A statement by a professional body, an insurer report, and a live product directory may each be accurate within its scope while answering different questions.
Baumol’s model cannot identify the cause of a particular reimbursement or workforce decision. It also cannot show that policy intends to replace therapists with apps. Establishing either claim would require a dated policy record and causal evaluation, not two headline numbers moving in opposite directions.
The narrower inference survives. Care capacity depends partly on trained people whose time remains costly, while digital products can follow a more scalable delivery path. Public policy should evaluate both access and evidence without pretending they are interchangeable units.
The Uncomfortable Part
I enjoy leverage. I also think labour-intensive care should be funded deliberately rather than treated as inefficient merely because its measured productivity does not grow like software. That is my political judgment, not a deduction from Baumol.
The comparison with a string quartet is useful but limited. A performance, a therapy session, and a crisis call all contain time that cannot simply be copied. Their outcomes, labour markets, technologies, and funding rules are different. Some parts can change; some encounters still need someone’s attention.
Evidence-based digital tools can be useful. They should not become an accounting fiction that makes trained human capacity look obsolete. Policy decides whether that capacity is available.
Clinical, BfArM, and health-policy sources checked through 2026-07-11.
References
[1] Flückiger, C., Del Re, A. C., Wampold, B. E., & Horvath, A. O. (2018). The alliance in adult psychotherapy: A meta-analytic synthesis. Psychotherapy, 55(4), 316–340. https://doi.org/10.1037/pst0000172
[2] Baumol, W. J., & Bowen, W. G. (1966). Performing Arts, The Economic Dilemma: A Study of Problems Common to Theater, Opera, Music and Dance. Twentieth Century Fund.
[3] Baumol, W. J. (2012). The Cost Disease: Why Computers Get Cheaper and Health Care Doesn’t. Yale University Press.
[4] Bundesinstitut für Arzneimittel und Medizinprodukte. DiGA-Verzeichnis. https://diga.bfarm.de/de
[5] Goeldner, M., & Gehder, S. (2024). Digital Health Applications (DiGAs) on a Fast Track: Insights From a Data-Driven Analysis of Prescribable Digital Therapeutics in Germany From 2020 to Mid-2024. JMIR mHealth and uHealth, 12, e59013. https://doi.org/10.2196/59013
Changelog
- 2026-07-11: Removed unsupported current fee, budget, product-count, and budget-to-therapy arithmetic; distinguished alliance evidence from a universal therapy mechanism; and bounded Baumol’s relative-cost model away from causal claims about German policy, workforce collapse, or AI.