The Clinical Information and Management System for Stroke (CIMSS)

An effective electronic infrastructure for capture and feedback of evidence based prospective observational data that describe these interlinked components could allow a better understanding of these complex relationships. Improved understanding of how stroke services function, and evaluation of the impact of proposed improvements to the stroke pathway would offer a number of benefits to patients, healthcare professionals and commissioners.

The overarching aim of CIMSS is to simplify, improve and support the collection of evidence based quality stroke data across the region through development of an electronic infrastructure. In order to achieve this we have a number of objectives:

• Definition of an evidence based dataset comprising four components of stroke care (process, care structure, case-mix and patient outcomes)
• Testing of this preliminary dataset for feasibility and acceptability in three study sites (research phase)
• Examination of existing voluntary and mandatory data requirements in Trusts across the region
• Development of a ‘data dictionary’ from which existing metrics and the CIMSS dataset may be derived
• A bespoke IT solution and implementation strategy for individual Trusts based on preferences (identified through Conjoint Analysis in partnership with the TRiPLaB CLAHRC theme)
• Prospective electronic capture of process, case-mix and outcomes data in participating sites during 2012

• What we collect – data fields are collected at ward level as part of the routine care of the stroke patient. Our aim is that data is captured once and re-used, and that data is recorded by the members of the team responsible for creating it.
• How we collect it – we are exploring novel data entry solutions such as hand held devices or tablet PCs. Bespoke IT and implementation strategies are informed by members of the stroke teams within Trusts rather than a prescriptive or ‘one size fits all’ approach.
• How we report it – reporting of data back to the stroke teams in an accessible format (e.g. a clinical dashboard) could help with service improvements. In addition, routine collection of patient reported outcomes could help to inform individual treatment and rehabilitation goals. At a population level, such data could be fed back to commissioners, or collated for broader comparisons.

Teale EA and Young JB. A review of stroke outcome measures valid and reliable for administration by postal survey. Reviews in Clinical Gerontology 2010;20(4), 338-353. https://doi.org/10.1017/S0959259810000213

Munyombwe T, Teale EA, West R, Hill K, Tu YK, Young J. Impact of early disability on six month physical function after stroke: a latent profile analysis. Age and Ageing 2012 41, 84.

Teale EA, Forster A, Munyombwe T, Young JB. A systematic review of case-mix adjustment models for stroke. Clinical Rehabilitation 2012; 26(9):771 – 786. https://doi.org/10.1177/0269215511433068

Teale E, Young J, Sleigh I. “A point of care electronic stroke data collection system” British Journal of Health Care Management 2013;19(1):10-15.

Teale E, Young J, Dennis M, Sheldon T. Predicting patient-reported stroke outcomes: a validation of the six simple variable prognostic model. Cerebrovascular Diseases Extra 2013;3(1):97-102.

Teale EA, Munyombwe TM, Young JB. The scaling properties of the Subjective Index of Physical and Social Outcome following stroke in a study population unselected by age. Archives of Physical Medicine and Rehabilitation 2013;94:2448-55.

Investigators

Young J, Keen J, Forster A, Bamford J, McDermid J.

01/10/2008 – 30/09/2013

National Institute for Health and Care Research (NIHR)

For further information contact Anne Forster

This summary presents independent research funded by the National Institute for Health and Care Research. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care.