FreshRSS

🔒
❌ Acerca de FreshRSS
Hay nuevos artículos disponibles. Pincha para refrescar la página.
AnteayerTus fuentes RSS

Trust and confidence of clinical staff and patients is crucial for the successful introduction of artificial intelligence (AI) in mental healthcare

Por: Barrera · A.

Commentary on: Higgins O, Short BL, Chalup SK, et al. Artificial intelligence (AI) and machine learning (ML) based decision support systems in mental health: an integrative review. Int J Ment Health Nurs 2023 [Epub ahead of print 6 Feb 2023]. doi: 10.1111/inm.13114.

Implications for practice and research

  • The introduction of artificial intelligence (AI)-based decision support systems (DSS) in mental healthcare is at a very early stage.

  • For DSS to be relevant and cost-effective, clinicians must participate at all stages of development, from project specification to evaluation.

  • Context

    This integrative review1 investigates the evidence for incorporating AI-based DSS in mental healthcare as a partial solution to an escalating care demand which can lead to staff’s burnout and potentially unfinished or missed care. Rightly, the authors of this review mention wider systemic problems such as under-resourcing and staff shortages. A DSS is an information...

    Design and evaluation of a digital health intervention with proactive follow-up by nurses to improve healthcare and outcomes for patients with breast cancer in Mexico: protocol for a randomised clinical trial

    Introduction

    Nearly 30 000 Mexican women develop breast cancer annually, frequently presenting unmet supportive care needs. In high-income countries, incorporating electronic patient-reported outcomes (ePROs) into cancer care has demonstrated potential for increasing patient-centred care and reducing unmet needs. No such ePRO interventions have been implemented in Mexico. This paper presents the study protocol for designing and evaluating an ePRO digital health application combined with proactive follow-up by nurses.

    Methods and analysis

    We designed a two-component intervention for women receiving breast cancer treatment: a responsive web application for monitoring ePROs and clinical algorithms guiding proactive follow-up by nurses. We will conduct a pilot test of the intervention with 50 patients with breast cancer for 6 weeks to assess feasibility and adjust the application. We will conduct a parallel arm randomised controlled trial assigning 205 patients each to intervention and control in one of Mexico’s largest public oncology hospitals. The intervention will be provided for 6 months, with additional 3 months of post-intervention observation. The control group will receive usual healthcare and a list of breast cancer information sources. Women diagnosed with stages I, II or III breast cancer who initiate chemotherapy and/or radiotherapy will be invited to participate. The primary study outcome will be supportive care needs; secondary outcomes include global quality of life and breast symptoms. Information on the outcomes will be obtained through web-based self-administered questionnaires collected at baseline, 1, 3, 6 and 9 months.

    Ethics and dissemination

    The National Research and Ethics Committees of the Mexican Institute of Social Security approved the study (R-2021-785-059). Participants will sign an informed consent form prior to their inclusion. Findings will be disseminated through a policy brief to the local authorities, a webinar for patients, publications in peer-reviewed journals and presentations at national and international conferences.

    Trial registration number

    NCT05925257.

    ❌