AIMC Topic: Quality of Health Care

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Machine learning meets maternal health: Uncovering spatial blind spots in antenatal care quality in Bangladesh.

PloS one
BACKGROUND: High-quality antenatal care (ANC) is defined as four or more antenatal visits with at least one to a medically trained provider, measurement of weight and blood pressure, testing of blood and urine, and receipt of information on potential...

Variation in the efficiency of English general practices and associated factors: A cross-sectional study of 5069 general practices.

The European journal of general practice
BACKGROUND: Healthcare demand in English general practice exceeds supply, necessitating practice efficiency. To our knowledge, no study has explored factors associated with practice efficiency in England using a quality-adjusted output.

Applying machine learning to predict quality ANC determinants in Bangladesh: a BDHS-2022 cross-sectional study.

Scientific reports
Quality antenatal care (ANC) is critical for maternal and neonatal health. Despite improvements in healthcare, disparities in ANC access and quality persist, particularly in underserved areas of Bangladesh. This study aimed to identify the key determ...

Identifying key influencers of patient satisfaction using an explainable machine learning approach.

Scientific reports
Patient satisfaction is a crucial measure of healthcare quality, influencing both health outcomes and care experiences. This study aims to identify the factors influencing patient satisfaction in healthcare facilities using machine learning algorithm...

Perceived Quality of Service in Primary Health Care Based on Google Maps Reviews Before, During, and After the COVID-19 Pandemic: Sentiment Analysis.

Journal of medical Internet research
BACKGROUND: The COVID-19 pandemic caused many changes in primary health care systems in Europe. The fast adoption of telemedicine, the shift of health care resources to COVID-19-related tasks, and the tendency of patients to cancel their nonurgent ap...

Using Machine Learning to Match Clients and Therapy Providers: Evaluating Clinical Quality and Cost of Care.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
OBJECTIVES: Matching clients in need of mental healthcare with providers who will deliver high quality treatment presents a substantial challenge. Machine learning models hold potential for predicting the best pairings from a multitude of data points...

The AI Efficiency Paradox: Reclaiming Quality Patient Care in an Era of Optimization.

Journal of medical systems
We examine how artificial intelligence (AI) integration in healthcare may create an "efficiency paradox" where technologies designed to reduce workload can instead generate new layers of inefficiency. We argue that AI implementation strategies priori...

Assessing Patient-Reported Satisfaction With Care and Documentation Time in Primary Care Through AI-Driven Automatic Clinical Note Generation: Protocol for a Proof-of-Concept Study.

JMIR research protocols
BACKGROUND: Relisten is an artificial intelligence (AI)-based software developed by Recog Analytics that improves patient care by facilitating more natural interactions between health care professionals and patients. This tool extracts relevant infor...

Health Care Quality and Patient Safety in the Era of Artificial Intelligence.

The Medical clinics of North America
The integration of digital health technologies is revolutionizing health care quality and patient safety by shifting from reactive to proactive care models. Advances in electronic health records, clinical decision support systems, data analytics, art...