Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You and Your Team.

Learn More →

Big Data and what it means for evaluating integrated care programmes

Big Data and what it means for evaluating integrated care programmes PurposeBig Data is likely to have significant implications for the way in which services are planned, organised or delivered as well as the way in which we evaluate them. The increase in data availability creates particular challenges for evaluators in the field of integrated care and the purpose of this paper is to set out how we may usefully reframe these challenges in the longer term.Design/methodology/approachUsing the characteristics of Big Data as defined in the literature, the paper develops a narrative around the data and research design challenges and how they influence evaluation studies in the field of care integration.FindingsBig Data will have significant implications for how we conduct integrated care evaluations. In particular, dynamic modelling and study designs capable of accommodating new epistemic foundations for the phenomena of social organisations, such as emergence and feedback loops, are likely to be most helpful. Big Data also generates opportunities for exploratory data analysis approaches, as opposed to static model development and testing. Evaluators may find research designs useful that champion realist approaches or single-n designs.Originality/valueThis paper reflects on the emerging literature and changing practice of data generation and data use in health care. It draws on organisational theory and outlines implications of Big Data for evaluating care integration initiatives. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Integrated Care Emerald Publishing

Big Data and what it means for evaluating integrated care programmes

Journal of Integrated Care , Volume 27 (3): 10 – Jun 20, 2019

Loading next page...
 
/lp/emerald-publishing/big-data-and-what-it-means-for-evaluating-integrated-care-programmes-CCHExWZA0L
Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
1476-9018
DOI
10.1108/JICA-05-2019-0017
Publisher site
See Article on Publisher Site

Abstract

PurposeBig Data is likely to have significant implications for the way in which services are planned, organised or delivered as well as the way in which we evaluate them. The increase in data availability creates particular challenges for evaluators in the field of integrated care and the purpose of this paper is to set out how we may usefully reframe these challenges in the longer term.Design/methodology/approachUsing the characteristics of Big Data as defined in the literature, the paper develops a narrative around the data and research design challenges and how they influence evaluation studies in the field of care integration.FindingsBig Data will have significant implications for how we conduct integrated care evaluations. In particular, dynamic modelling and study designs capable of accommodating new epistemic foundations for the phenomena of social organisations, such as emergence and feedback loops, are likely to be most helpful. Big Data also generates opportunities for exploratory data analysis approaches, as opposed to static model development and testing. Evaluators may find research designs useful that champion realist approaches or single-n designs.Originality/valueThis paper reflects on the emerging literature and changing practice of data generation and data use in health care. It draws on organisational theory and outlines implications of Big Data for evaluating care integration initiatives.

Journal

Journal of Integrated CareEmerald Publishing

Published: Jun 20, 2019

References