Why Can AI Make So Much Impact in Long-Term Mental Healthcare?
In long-term care, administrative pressure has become structural. Recent research by Berenschot1 shows that healthcare professionals in long-term care (including mental healthcare) spend an average of 34% of their working time on administrative tasks. In contrast, professionals themselves consider 23% to be acceptable. At the same time, nearly 80% describe the administrative workload as burdensome.
A key driver of this increased workload is not just the time spent on administrative tasks. It is the growing complexity of information. Patient records often contain years of observations, conversation notes, treatment evaluations, multidisciplinary reports, risk assessments, and legal documentation. Healthcare professionals are expected to continuously maintain an overview of it all, even when temporarily taking over clients, returning from leave, or working across teams.
That is exactly why AI can make such a major impact in this field of healthcare. AI is uniquely good at creating an overview within (textual) complexity. It can help healthcare professionals instantly search through large dossiers, generate structured summaries, identify relevant signals, and surface the right patient information directly inside the EHR. Not to replace professionals, but to help them navigate growing amounts of information faster, reduce administrative pressure, and create more time and mental space for patient care.
Massive patient records and the nature of behavioral healthcare
In long-term mental healthcare, documentation is inherently narrative and longitudinal, requiring detailed tracking of patient history, clinical reasoning, and treatment progression over time. Sociotherapists write daily reports. Psychologists contribute to treatment evaluations. Psychiatrists review patient history and prescribe medication. Teams collaborate on treatment plans and structured summaries. Over time, patient records become massive.
Moreover, all information could be relevant. A small observation from weeks ago can suddenly become important when there is a conflict between cliënts in a group setting. A behavioral pattern hidden in daily reports may help prevent escalation. A treatment adjustment written by another discipline can completely change clinical interpretation.
AI for a quick overview
For healthcare professionals, it is often a challenge to find the right information at the right moment. Especially with large patient files, they spend more time searching, summarizing, and documenting than they would like. Therefore, the biggest strength of AI in long-term mental healthcare is not simply automation. It is creating an overview. AI can process and structure enormous amounts of information in seconds. That means healthcare professionals no longer need to manually search through hundreds of pages to understand what matters most. Imagine:
Starting your shift with a concise summary of the past week
Instantly identifying important behavioral signals or risk patterns
Automatically generating structured six-month patient summaries
Quickly understanding a patient before temporarily joining another team
Translating complex treatment information into understandable language for patients
This is where AI creates immediate value: not by replacing clinical expertise, but by helping professionals access relevant context faster. In many countries, including the Netherlands, this is becoming increasingly important as the mental healthcare sector faces growing workforce shortages. According to recent labour market projections, the Dutch mental healthcare sector is expected to face a shortage of more than 20,000 FTEs by 20342.
Delphyr: a secure intelligence layer in your EHR
Delphyr sits quietly within the daily workflow of mental health care professionals, like an extra layer on top of the EHR. During a shift, it helps surface what matters most: a clear summary of a patient’s recent weeks, key behavioral signals hidden in notes, or a structured overview of a long and complex dossier.
Safe and compliant
Because Delphyr is fully integrated into existing EHR systems, patient data never needs to leave the healthcare environment. This “AI layer” approach is intentional; it allows healthcare professionals to benefit from AI-driven insights without changing the systems they already trust and rely on.
Delphyr is built from inside healthcare, founded by an anesthetist who understands the realities of clinical work. The platform is developed with strict attention to GDPR requirements, European AI Act principles, and healthcare standards such as ISO 27001 and NEN 7510, with MDR certification in progress. In addition, Delphyr uses its own medically trained language model and collaborates with European cloud providers to ensure data sovereignty.
Sources
Berenschot. (2026, February 2). Administratieve druk in langdurige zorg blijft structureel hoog. ICT&health. https://www.icthealth.nl/nieuws/administratieve-druk-in-langdurige-zorg-blijft-structureel-hoog/
Arbeidsmarkt Zorg en Welzijn (AZW). (2025). Nieuwe prognose arbeidsmarkt van de geestelijke gezondheidszorg [PDF]. Nieuwe prognose arbeidsmarkt van de geestelijke gezondheidszorg (PDF)