Why measuring quality of mental health care is still an unmet challenge and how to meet it

ChatGPT is not ready yet for use in providing mental health assessment and interventions

Background

Psychiatry is a specialized field of medicine that focuses on the diagnosis, treatment, and prevention of mental health disorders. With advancements in technology and the rise of artificial intelligence (AI), there has been a growing interest in exploring the potential of AI language models systems, such as Chat Generative Pre-training Transformer (ChatGPT), to assist in the field of psychiatry.

Objective

Our study aimed to evaluates the effectiveness, reliability and safeness of ChatGPT in assisting patients with mental health problems, and to assess its potential as a collaborative tool for mental health professionals through a simulated interaction with three distinct imaginary patients.

Methods

Three imaginary patient scenarios (cases A, B, and C) were created, representing different mental health problems. All three patients present with, and seek to eliminate, the same chief complaint (i.e., difficulty falling asleep and waking up frequently during the night in the last 2°weeks). ChatGPT was engaged as a virtual psychiatric assistant to provide responses and treatment recommendations.

Results

In case A, the recommendations were relatively appropriate (albeit non-specific), and could potentially be beneficial for both users and clinicians. However, as complexity of clinical cases increased (cases B and C), the information and recommendations generated by ChatGPT became inappropriate, even dangerous; and the limitations of the program became more glaring. The main strengths of ChatGPT lie in its ability to provide quick responses to user queries and to simulate empathy. One notable limitation is ChatGPT inability to interact with users to collect further information relevant to the diagnosis and management of a patient's clinical condition. Another serious limitation is ChatGPT inability to use critical thinking and clinical judgment to drive patient's management.

Conclusion

As for July 2023, ChatGPT failed to give the simple medical advice given certain clinical scenarios. This supports that the quality of ChatGPT-generated content is still far from being a guide for users and professionals to provide accurate mental health information. It remains, therefore, premature to conclude on the usefulness and safety of ChatGPT in mental health practice.

Assessing and Improving the Quality in Mental Health Services

Background: The mental health of the population consists of the three essential pillars of quality of life, economy, and society. Mental health services take care of the prevention and treatment of mental disorders and through them maintain, improve, and restore the mental health of the population. The purpose of this study is to describe the methodology for qualitative and quantitative evaluation and improvement of the mental health service system. Methods: This is a narrative review study that searches the literature to provide criteria, indicators, and methodology for evaluating and improving the quality of mental health services and the related qualitative and quantitative indicators. The bibliography was searched in popular databases PubMed, Google Scholar, CINAHL, using the keywords “mental”, “health”, “quality”, “indicators”, alone or in combinations thereof. Results: Important quality indicators of mental health services have been collected and presented, and modified where appropriate. The definition of each indicator is presented here, alongside its method of calculation and importance. Each indicator belongs to one of the eight dimensions of quality assessment: (1) Suitability of services, (2) Accessibility of patients to services, (3) Acceptance of services by patients, (4) Ability of healthcare professionals to provide services, (5) Efficiency of health professionals and providers, (6) Continuity of service over time (ensuring therapeutic continuity), (7) Efficiency of health professionals and services, (8) Safety (for patients and for health professionals). Discussion/Conclusions: Accessibility and acceptability of service indicators are important for the attractiveness of services related to their use by the population. Profitability indicators are important economic indicators that affect the viability and sustainability of services, factors that are now taken into account in any health policy. All of the indicators mentioned are related to public health, affecting the quality of life, morbidity, mortality, and life expectancy, directly or indirectly. The systematic measurement and monitoring of indicators and the measurement and quantification of quality through them, are the basis for evidence-based health policy for improvement of the quality of mental health services.