Risk analysis and user satisfaction after implementation of computerized physician order entry in Dutch hospitals
- 423 Downloads
Background Computerized physician order entry (CPOE) in hospitals is widely considered to be important for patient safety, but implementation is lagging behind and user satisfaction is often low. Risk analysis methods may improve the implementation process and thus user satisfaction. Objective The aim of our study was to determine the association of performing risk analysis with user satisfaction after implementation of CPOE. Setting All hospitals in the Netherlands. Method A cross-sectional study using a questionnaire was performed. All Dutch hospital pharmacies were asked about the extent of implementation of CPOE in the hospitals they served, the performance of (retrospective or prospective) risk analysis and the satisfaction with CPOE of doctors, nurses and pharmacists. Only hospitals that had implemented inpatient CPOE on at least 70 % of the wards were included in the primary analysis. Main outcome measure The primary outcome measure was the proportion of hospital pharmacists with a satisfaction level of 4 or 5 (i.e. ‘satisfied’). The secondary outcome measure was the proportion of medical doctors and nurses with a satisfaction level of 4 or 5 (i.e. satisfied). The main determinant was the performance of a formal method of prospective or retrospective risk analysis. Results The questionnaire was sent to all 79 Dutch hospital pharmacies. Questionnaires were returned by 70 hospital pharmacies, serving 72 separate hospitals. In 40 hospitals the CPOE was implemented on at least 70 % of the wards. The association of risk analysis with the proportion of satisfied users was determined within this group of 40 hospitals. For hospital pharmacists we found that the performance of risk analysis showed a statistically non-significant trend towards an association with satisfaction [OR 3.3 (95 % CI 0.8–14.1)]. For medical doctors the performance of risk analysis was associated with satisfaction [OR 10.0 (95 % CI 1.8–56.0)]. Also a statistically non-significant trend towards an association with satisfaction was found for nurses [OR 4.5 (95 % CI 0.8–24.7)]. Conclusion Although not statistically significant, the user satisfaction with CPOE seems to be associated with the performance of risk analysis during the implementation of CPOE. This suggests that the CPOE implementation process can be optimized by performing risk analysis before and/or after implementation.
KeywordsCPOE FMEA Implementation RCA Risk analysis User satisfaction The Netherlands
We would like to express our gratitude to the Dutch Hospital Pharmacists who cooperated in this study. Also, we would like to thank Lisette Hoekstra and Fleur Kos (students) for performing the pilot of this study.
No funding was received for this study.
Conflicts of interest
All authors declared that they have no competing interests: no support from any organization for the submitted work; no financial relationships with any organization that might have an interest in the submitted work in the previous five years; no other relationships or activities that could appear to have influenced the submitted work.
- 5.Garnica MP. CPOE: an essential tool for evidence-based practice. JNP. 2011;36:12–5.Google Scholar
- 6.Hagland M. CPOE and patient safety. Healthcare inform. 2011;28:76–8.Google Scholar
- 14.IOM. Health IT and patient safety: building safer systems for better care. Washington DC: The National Academies Press; 2012.Google Scholar
- 16.Niazkhani Z, Pirnejad H, van der Sijs H, Aarts J. Evaluating the medication process in the context of CPOE use: the significance of working around the system. J Am Med Inform Assoc. 2011;80:490–506.Google Scholar
- 18.Niazkhani Z, Pirnejad H, van der Sijs H, de Bont A, Aarts J. Computerized provider order entry system—does it support the inter-professional medication process? Lessons from a Dutch academic hospital. Methods Inform Med. 2010;49:20–7.Google Scholar
- 24.Ozdas A, Miller RA. In: Geissbuhler A, Haux R, Kulikowski C, editors. IMIA Yearbook of Medical Informatics 2007. Methods Inf Med 2007;46(1):128–37.Google Scholar
- 29.Williams E, Talley R. The use of failure mode effect and criticality analysis in a medication error subcommittee. Hospital pharmacy 1994; 29:331–2, 34–6, 39.Google Scholar
- 32.DeRosier J, Stalhandske E, Bagian JP, Nudell T. Using health care failure mode and effect analysis: the VA National Center for Patient Safety’s prospective risk analysis system. Jt Comm J Qual Improv. 2002;28(248–67):09.Google Scholar
- 35.Franklin BD, Shebl NA, Barber N. Failure mode and effects analysis: too little for too much? BMJ Qual Saf (Published Online First: March 23, 2012) doi: 10.1136/bmjqs-2011-000723.
- 36.Giesen D, Meertens V, Vis R, Beukenhorst D. Vragenlijstontwikkeling (questionnaire development). The Hague, The Netherlands: Dutch Statistics 2010.Google Scholar
- 40.Percarpio KB, Watts BV, Weeks WB. The effectiveness of root cause analysis: what does the literature tell us? Jt Comm J Qual Pat Saf. 2008;34:391–8.Google Scholar