Predicting the impact of new health technologies on average length of stay: development of a prediction framework
Simpson, Sue, Packer, Claire, Stevens, Andrew and Raftery, James (2005) Predicting the impact of new health technologies on average length of stay: development of a prediction framework. International Journal of Technology Assessment in Health Care, 21, (4), 487-491. (doi:10.1017/S0266462305050671).
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Description/Abstract
Objectives: The aim of this study was to develop a framework to predict the impact of new health technologies on average length of hospital stay.
Methods: A literature search of EMBASE, MEDLINE, Web of Science, and the Health Management Information Consortium databases was conducted to identify papers that discuss the impact of new technology on length of stay or report the impact with a proposed mechanism of impact of specific technologies on length of stay. The mechanisms of impact were categorized into those relating to patients, the technology, or the organization of health care and clinical practice.
Results: New health technologies have a variable impact on length of stay. Technologies that lead to an increase in the proportion of sicker patients or increase the average age of patients remaining in the hospital lead to an increase in individual and average length of stay. Technologies that do not affect or improve the inpatient case mix, or reduce adverse effects and complications, or speed up the diagnostic or treatment process should lead to a reduction in individual length of stay and, if applied to all patients with the condition, will reduce average length of stay.
Conclusions: The prediction framework we have developed will ensure that the characteristics of a new technology that may influence length of stay can be consistently taken into consideration by assessment agencies. It is recognized that the influence of technology on length of stay will change as a technology diffuses and that length of stay is highly sensitive to changes in admission policies and organization of care.
| Item Type: | Article |
|---|---|
| Related URLs: | |
| Keywords: | forecasting, length of stay, health-care technology |
| Subjects: | R Medicine > R Medicine (General) |
| Divisions: | University Structure - Pre August 2011 > School of Medicine > Community Clinical Sciences |
| Item ID: | 24504 |
| Date Deposited: | 31 Mar 2006 |
| Last Modified: | 01 Jun 2011 04:05 |
| Contributors: | Simpson, Sue (Author) Packer, Claire (Author) Stevens, Andrew (Author) Raftery, James (Author) |
| Date: | 2005 |
| Status: | Published |
| Contact Email Address: | raftery@soton.ac.uk |
| URI: | http://eprints.soton.ac.uk/id/eprint/24504 |
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