Meet Inspiring Speakers and Experts at our 3000+ Global Conference Series Events with over 1000+ Conferences, 1000+ Symposiums
and 1000+ Workshops on Medical, Pharma, Engineering, Science, Technology and Business.

Explore and learn more about Conference Series : World's leading Event Organizer

Back

Manhal Mohammad Ali

Manhal Mohammad Ali

University of Manchester, UK

Title: Hospital Heterogeneity: What Determines The Quality Of Care?

Biography

Biography: Manhal Mohammad Ali

Abstract

A feature of health care systems, for instance, the NHS is the presence of heterogeneity in health care quality across hospitals. This study seeks to understand what internal and external hospital based factors are responsible for explaining variations in quality of care measured using the processes of care in the case of stroke. We used NHS trust data from National Sentinel Stroke Audit from 2004 to 2010. The data were merged with other administrative data sets to capture hospital’s characteristics. We employed a new class of panel regression tree estimators from the machine learning literature to study the data. A reason behind the choice of the method is the intuitive interpretability of the results. The non-parametric method has the capability to reveal potential interactions among the variables, which could offer valuable information about the processes driving variations in quality across NHS hospitals. The study found complex interactions or complementarities amongst the hospitals organizational, structural and regional level factors in determining quality with organizational factors for stroke care to be the most important predictors. The main results from the tree method are robust to alternative specifications and methods for instance, linear and fixed effect models which control for fixed effects. Cross validations and in sample statistics were carried out to assess the sample predictive performances and fit the data. The findings shed new light on previous research determinants of healthcare quality by identifying critical interactions. The findings helped us to improve and inform policy decisions for quality improvement by identifying the factors that drive quality.