The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
Improving quality through effective implementation of information technology in healthcare
Abstract
OBJECTIVE: To describe an implementation of one information technology system (electronic medical record, EMR) in one hospital, the perceived impact, the factors thought to help and hinder implementation and the success of the system and compare this with theories of effective IT implementation. To draw on previous research, empirical data from this study is used to develop IT implementation theory. DESIGN: Qualitative case study, replicating the methods and questions of a previously published USA EMR implementation study using semi-structured interviews and documentation. SETTING: Large Swedish teaching hospital shortly after a merger of two hospital sites. PARTICIPANTS: Thirty senior clinicians, managers, project team members, doctors and nurses. RESULTS: The Swedish implementation was achieved within a year and for under half the budget, with a generally popular EMR which was thought to save time and improve the quality of patient care. Evidence from this study and findings from the more problematic USA implementation case suggests that key factors for cost effective implementation and operation were features of the system itself, the implementation process and the conditions under which the implementation was carried out. CONCLUSION: There is empirical support for the IT implementation theory developed in this study, which provides a sound basis for future research and successful implementation. Successful implementation of an EMR is likely with an intuitive system, requiring little training, already well developed for clinical work but allowing flexibility for development, where clinicians are involved in selection and in modification for their department needs and where a realistic timetable is made using an assessment of the change-capability of the organization. Once a system decision is made, the implementation should be driven by top and departmental leaders assisted by competent project teams involving information technology specialists and users. Corrections for unforeseen eventualities will be needed, especially with less developed systems, requiring regular reviews of progress and modifications to systems and timetables to respond to user needs.
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“Existing literature on the benefits of electronic records is largely U.S or primary care based [18–34] and reports ‘potential’ rather than actual benefits; with a large proportion of this evidence reporting the potential for electronic records to improve patient safety [19, 21, 23, 27–30].”
From Exploring the implementation of an electronic record into a maternity unit: a qualitative study using Normalisation Process Theory (2017) · cites this paper as [19]
In the citing paper
“In accordance with existing literature, evidence of actual benefits reported in our study were limited to a number of ‘clinically orientated’ benefits surrounding improved information availability, accessibility and legibility [19, 23, 31–34].”
From Exploring the implementation of an electronic record into a maternity unit: a qualitative study using Normalisation Process Theory (2017) · cites this paper as [19]
Citations
Cites
(1984) · Cited by 81,983
Physicians’ Use Of Electronic Medical Records: Barriers And Solutions
Miller, R. H., & Sim, I. (2004) · Health Affairs · doi:10.1377/hlthaff.23.2.116 · Cited by 869
Costs and benefits of health information technology.
Shekelle, P. G., Morton, S. C., & Keeler, E. B. (2006) · doi:10.23970/ahrqepcerta132 · Cited by 501 · cited 5×
“These may be classified in terms of features of the EMR system [1, 5– 13], the implementation process [6, 8, 11, 14 – 16], or of the leadership [11, 14 – 16], resources [ 1 , 5, 6, 8, 14, 15, 17] and the recipient organization’s culture [15, 18 –20].”
BackgroundInfluentialDeveloping and Testing a Model to Predict Outcomes of Organizational Change
Gustafson, D. H., Sainfort, F., Eichler, M., Adams, L., Bisognano, M. A., & Steudel, H. J. (2003) · Health Services Research · doi:10.1111/1475-6773.00143 · Cited by 298
Kaiser Permanente's experience of implementing an electronic medical record: a qualitative study
Scott, J. T., Rundall, T. G., Vogt, T. M., & Hsu, J. (2005) · BMJ · doi:10.1136/bmj.38638.497477.68 · Cited by 266
Self-citationHendy, J., Reeves, B. C., Fulop, N., Hutchings, A., & Masseria, C. (2005) · BMJ · doi:10.1136/bmj.331.7512.331 · Cited by 195
Information technologies: when will they make it into physicians' black bags?
Audet, A., Doty, M. M., Peugh, J., Shamasdin, J., Zapert, K., & Schoenbaum, S. C. (2004) · PubMed · Cited by 151
Technology. Health information community networks
Duhl, L. J. (2000) · Public Health Reports · doi:10.1093/phr/115.2.271 · Cited by 148
(1997) · Health Information Management Journal · doi:10.1177/183335839702700321 · Cited by 144
Electronic Medical Records: Are Physicians Ready?
Dansky, K. H., Gamm, L. D., Vasey, J. J., & Barsukiewicz, C. K. (1999) · Journal of Healthcare Management · doi:10.1097/00115514-199911000-00007 · Cited by 118
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A Holistic Framework to Improve the Uptake and Impact of eHealth Technologies
van Gemert-Pijnen, J. E., Nijland, N., van Limburg, M., Ossebaard, H. C., Kelders, S. M., Eysenbach, G., & Seydel, E. R. (2011) · Journal of Medical Internet Research · doi:10.2196/jmir.1672 · Cited by 1,126
Cresswell, K., & Sheikh, A. (2013) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2012.10.007 · Cited by 690
LUDWICK, D., & DOUCETTE, J. (2009) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2008.06.005 · Cited by 668
Gagnon, M.-P., Desmartis, M., Labrecque, M., Car, J., Pagliari, C., Pluye, P., Frémont, P., Gagnon, J., Tremblay, N., & Légaré, F. (2012) · Journal of Medical Systems · doi:10.1007/s10916-010-9473-4 · Cited by 637
GREENHALGH, T., POTTS, H. W. W., WONG, G., BARK, P., & SWINGLEHURST, D. (2009) · The Milbank Quarterly · doi:10.1111/j.1468-0009.2009.00578.x · Cited by 541
Metadata
- Authors
- Ovretveit, J., Scott, T., Rundall, T. G., Shortell, S. M., & Brommels, M.
- Affiliations
- University of St Andrews (GB)
- University of California, Berkeley (US)
- University of Helsinki (FI)
- Venue
- International Journal for Quality in Health Care
- Publisher
- Oxford University Press (OUP)
- Published
- 2007-08-01
- Volume
- 19
- Issue
- 5
- Pages
- 259-266
- ISSN
- 1353-4505 (ISSN-L)
- 1464-3677
- OpenAlex
- W2167472681
- Cited by
- 204
- References
- 19
- Citations by year
- 2026: 1 · 2025: 7 · 2024: 12 · 2023: 3 · 2022: 8 · 2021: 9 · 2020: 5 · 2019: 11 · 2018: 10 · 2017: 15 · 2016: 10 · 2015: 11 · 2014: 18 · 2013: 12 · 2012: 14
- FWCI
- 22.80
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal for Quality in Health Care (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Social Sciences › Business, Management and Accounting › Management Information Systems › Information Systems Theories and Implementation
- Social Sciences › Business, Management and Accounting › Management Information Systems › ERP Systems Implementation and Impact
- Keywords
- electronic health records, health information technology implementation, hospital mergers, cost-effective implementation, quality of care, implementation barriers and facilitators, project teams
- MeSH terms
- Attitude of Health Personnel, Cost-Benefit Analysis, Health Facility Merger, Health Plan Implementation, Hospital Information Systems, Humans, Interviews as Topic, Medical Staff, Hospital, Organizational Innovation, Quality Assurance, Health Care, Sweden, Program Evaluation, Medical Records Systems, Computerized, Program Development, Organizational Case Studies
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