Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Simultaneous trend analysis for evaluating outcomes in patient-centred health monitoring services

Conley, Edward Clarke, Owens, David R., Luzio, Stephen L., Subramanian, Mahesh, Ali, Ali Shaikh, Hardisty, Alex and Rana, Omer Farooq ORCID: https://orcid.org/0000-0003-3597-2646 2008. Simultaneous trend analysis for evaluating outcomes in patient-centred health monitoring services. Health Care Management Science 11 (2) , pp. 152-166. 10.1007/s10729-008-9061-z

Full text not available from this repository.

Abstract

The research aim underpinning the Healthcare@Home (HH) information system described here was to enable ‘near real time’ risk analysis for disease early detection and prevention. To this end, we are implementing a family of prototype web services to ‘push’ or ‘pull’ individual’s health-related data via an system of clinical hubs, mobile communication devices and/or dedicated home-based network computers. We are examining more efficient methods for ethical use of such data in timeline-based (i.e. ‘longitudinal’) data analysis systems. A consistent data collation infrastructure is being created for use along the ‘patient path’—accessible wherever patients happen to be. This ‘patient-centred’ infrastructure can be applied in the evaluation of disease progression risk (in the light of clinical understanding of disease processes). In this paper we describe the requirements for making multi-data trend management ‘scale-up’, together with some requirements of an ‘end-to-end’ functioning data collection system. A Service-Oriented Architecture (SOA) approach is used to maximise benefits from (1) clinical evidence and (2) computational models of disease progression that can be made available elsewhere on the SOA. We discuss the implications of this so-called ‘closed loop’ approach for improving healthcare intervention outcomes, patient safety, decision support, objective measurement of service quality and in providing inputs for quantitative healthcare (predictive) modelling.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Uncontrolled Keywords: Web services - Time series analysis routines - Scalability - Chronic disease management - Portal technologies - Risk monitoring - Service-oriented architecture
Publisher: Springer Verlag
ISSN: 1386-9620
Last Modified: 18 Oct 2022 13:31
URI: https://orca.cardiff.ac.uk/id/eprint/14228

Citation Data

Cited 21 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item