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Predicting the impact of new health technologies on average length of stay: Development of a prediction framework

Published online by Cambridge University Press:  25 October 2005

Sue Simpson
Affiliation:
The University of Birmingham
Claire Packer
Affiliation:
The University of Birmingham
Andrew Stevens
Affiliation:
The University of Birmingham
James Raftery
Affiliation:
The University of Birmingham

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.

Type
GENERAL ESSAYS
Copyright
© 2005 Cambridge University Press

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References

Health Management Information Consortium database. Available at: www.hsmc.bham.ac.uk/library/. Accessed December 24, 2004.
Aranki SF, Shaw DP, Adams DH, et al. 1996 Predictors of atrial fibrillation after coronary artery surgery. Current trends and impact on hospital resources. Circulation. 94: 390397.Google Scholar
Bates DW, Spell N, Cullen DJ, et al. 1997 The costs of adverse drug events in hospitalized patients. JAMA. 277: 307311.Google Scholar
Bloom BS, de Pouvourville N, Libert S, Fendrick AM. 2000 Surgeon predictions on growth of minimal invasive therapy: The difficulty of estimating technologic diffusion. Health Policy. 54: 201207.Google Scholar
Chrischilles E, Delgado DJ, Stolshek BS, et al. 2002 Impact of age and colony-stimulating factor use on hospital length of stay for febrile neutropenia in CHOP-treated non-Hodgkin's lymphoma. Cancer Control. 9: 203211.Google Scholar
Classen DC, Pestotnik SL, Evans RS, Lloyd JF, Burke JP. 1997 Adverse drug events in hospitalized patients. Excess length of stay, extra costs, and attributable mortality. JAMA. 277: 301306.Google Scholar
Combier E, Levacher S, Letoumelin P, et al. 1999 Cost-effectiveness analysis of the terlipressin-glycerin trinitrate combination in the pre-hospital management of acute gastro-intestinal haemorrhage in cirrhotic patients. Intensive Care Med. 25: 364370.Google Scholar
Creed F, Tomenson P, Anthony P, Tramner M. 1997 Predicting length of stay in psychiatry. Psychol Med. 27: 961966.Google Scholar
Department of Health. 2004. Hospital episode statistics. Available at: www.dh.gov.uk/publicationsandstatistics/statistics/hospital-episodestatistics/fs/en. Accessed December 24
Fleszler F, Friedenberg F, Krevsky B, Friedel D, Braitman LE. 2003 Abdominal computed tomography prolongs length of stay and is frequently unnecessary in the evaluation of acute pancreatitis. Am J Med Sci. 325: 251255.Google Scholar
Foster C, Murphy M, Nicholas JJ, Pignone M, 2004: Bazian Ltd. Cardiovascular disorders: Primary prevention. In: Clinical evidence, vol 11. London: BMJ Publishing Group; 163196.
Gelijns A, Rosenberg N. 1994 The dynamics of technological change in medicine. Health Aff. 13: 28.Google Scholar
Grady KL, Haller KB, Grusk BB, Corliss JW. 1990 Predictors of hospital length of stay after heart transplantation. J Heart Transplant. 9: 9296.Google Scholar
Lee-Lewandrowski E, Corboy D, Lewandrowski K, et al. 2003 Implementation of a point-of-care satellite laboratory in the emergency department of an academic medical center: Impact on test turnaround time and patient emergency department length of stay. Arch Pathol Lab Med. 127: 456460.Google Scholar
Lichtenberg FR. 1996 Do (more and better) drugs keep people out of hospitals? Health Econ. 86: 384388.Google Scholar
Lindqvist R, Moller TR, Stenbeck M, Diderichsen F. 2002 Do changes in surgical procedures for breast cancer have consequences for hospital mean length of stay? A study of women operated on for breast cancer in Sweden, 1980–95. Int J Technol Assess Health Care. 18: 566575.Google Scholar
Lukish JR, Eichelberger MR, Newman KD, et al. 2001 The use of a bioactive skin substitute decreases length of stay for pediatric burn patients. J Pediatr Surg. 36: 11181121.Google Scholar
Milligan M. 2003 Curtain down on period drama. Health Serv J. 113: 27.Google Scholar
Mohr P, Mueller C, Neumann P, et al. 2001. The impact of medical technology on future health care costs. Maryland: Project Hope Center for Health Affairs;
Morgan M, Beech R. 1990 Variations in length of stay and rates of day case surgery: Implications for the efficiency of surgical management. J Epidemiol Community Health. 44: 90105.Google Scholar
National Institute for Clinical Excellence. Interventional procedure overview—minimally invasive two-incision surgery for total hip replacement. Available at: www.nice.org.uk/pdf/ip/240overview.pdf. Accessed September 20, 2004.
O'Connor H, Broadbent JAM, Magos AL, McPherson K. 1997 Medical Research Council randomised trial of endometrial resection versus hysterectomy in management of menorrhagia. Lancet. 349: 897901.Google Scholar
Roberts R, Zalenski RJ, Mensah EK, Rydman RJ. 1997 Costs of an emergency department-based accelerated diagnostic protocol vs hospitalization in patients with chest pain: A randomized controlled trial. JAMA. 278: 16701676.Google Scholar
Rowsell M, Bello M, Hemingway DM. 2000 Circumferential mucosectomy (stapled haemorrhoidectomy) versus conventional haemorrhoidectomy: Randomised controlled trial. Lancet. 355: 779781.Google Scholar
Sloan FA, Valvona J. 1986 Why has hospital length of stay declined? An evaluation of alternative theories. Soc Sci Med. 22: 6373.Google Scholar
Stempel DA, Yancey SW. 1999 Addition of salmeterol decreases hospitalization, length of stay and does not add to direct costs of asthma care. J Allergy Clin Immunol. 103: S60.Google Scholar
Stoskopf C, Horn SD. 1992 Predicting length of stay for patients with psychosis. Health Serv Res. 26: 743766.Google Scholar
Willke RJ, Glick HA, Li JZ, Rittenhouse BE. 2002 Effects of linezolid on hospital length of stay compared with vancomycin in treatment of methicillin-resistant Staphylococcus infections. An application of multivariate survival analysis. Int J Technol Assess Health Care. 18: 540554.Google Scholar
Xiao J, Douglas D, Lee AH, Vemuri SR. 1997 A Delphi evaluation of the factors influencing length of stay in Australian hospitals. Int J Health Plann Manage. 12: 207218.Google Scholar