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BMC Medical Informatics and Decision Making
Published in: BMC Medical Informatics and Decision Making 1/2017

Open Access 01-12-2017 | Research article

The effect of a test ordering software intervention on the prescription of unnecessary laboratory tests - a randomized controlled trial

Authors: Carlos Manuel Silva Martins, Andreia Sofia da Costa Teixeira, Luís Filipe Ribeiro de Azevedo, Luísa Maria Barbosa Sá, Paulo Alexandre Azevedo Pereira Santos, Maria Luciana Gomes Domingues do Couto, Altamiro Manuel Rodrigues da Costa Pereira, Alberto Augusto Oliveira Pinto Hespanhol, Cristina Maria Nogueira da Costa Santos

Published in: BMC Medical Informatics and Decision Making | Issue 1/2017

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Abstract

Background

The way software for electronic health records and laboratory tests ordering systems are designed may influence physicians’ prescription. A randomised controlled trial was performed to measure the impact of a diagnostic and laboratory tests ordering system software modification.

Methods

Participants were family physicians working and prescribing diagnostic and laboratory tests.
The intervention group had a modified software with a basic shortcut menu changes, where some tests were withdrawn or added, and with the implementation of an evidence-based decision support based on United States Preventive Services Task Force (USPSTF) recommendations. This intervention group was compared with usual software (control group).
The outcomes were the number of tests prescribed from those: withdrawn from the basic menu; added to the basic menu; marked with green dots (USPSTF’s grade A and B); and marked with red dots (USPSTF’s grade D).

Results

Comparing the monthly average number of tests prescribed before and after the software modification, from those tests that were withdrawn from the basic menu, the control group prescribed 33.8 tests per 100 consultations before and 30.8 after (p = 0075); the intervention group prescribed 31.3 before and 13.9 after (p < 0001). Comparing the tests prescribed between both groups during the intervention, from those tests that were withdrawn from the basic menu, the intervention group prescribed a monthly average of 14.0 vs. 29.3 tests per 100 consultations in the control group (p < 0.001). From those tests that are USPSTF’s grade A and B, intervention group prescribed 66.8 vs. 74.1 tests per 100 consultations in the control group (p = 0.070). From those tests categorised as USPSTF grade D, the intervention group prescribed an average of 9.8 vs. 11.8 tests per 100 consultations in the control group (p = 0.003).

Conclusions

Removing unnecessary tests from a quick shortcut menu of the diagnosis and laboratory tests ordering system had a significant impact and reduced unnecessary prescription of tests.
The fact that it was not possible to perform the randomization at the family physicians’ level, but only of the computer servers is a limitation of our study. Future research should assess the impact of different tests ordering systems during longer periods.

Trial registration

ISRCTN45427977, May 1st 2014 (retrospectively registered).
Literature
1.
Glasziou P, Moynihan R, Richards T, Godlee F. Too much medicine; too little care. BMJ. 2013;347:f4247.CrossRefPubMed
2.
Moynihan R, Doust J, Henry D. Preventing overdiagnosis: how to stop harming the healthy. BMJ. 2012;344:e3502.CrossRefPubMed
3.
4.
Raposo VL. Electronic health records: Is it a risk worth taking in healthcare delivery? GMS Health Technol Assess. 2015;11:Doc02.PubMedPubMedCentral
5.
Ben-Assuli O. Electronic health records, adoption, quality of care, legal and privacy issues and their implementation in emergency departments. Health Policy Amst Neth. 2015;119(3):287–97.CrossRef
6.
Ben-Assuli O, Leshno M. Assessing electronic health record systems in emergency departments: using a decision analytic Bayesian model. Health Informatics J. 2016;22(3):712–29.CrossRefPubMed
7.
Boonstra A, Broekhuis M. Barriers to the acceptance of electronic medical records by physicians from systematic review to taxonomy and interventions. BMC Health Serv Res. 2010;10:231.CrossRefPubMedPubMedCentral
8.
Roukema J, Los RK, Bleeker SE, van Ginneken AM, van der Lei J, Moll HA. Paper versus computer: feasibility of an electronic medical record in general pediatrics. Pediatrics. 2006;117(1):15–21.CrossRefPubMed
9.
Bowman S. Impact of electronic health record systems on information integrity: quality and safety implications. Perspect Health Inf Manag AHIMA Am Health Inf Manag Assoc. 2013;10:1c.
10.
Nguyen L, Bellucci E, Nguyen LT. Electronic health records implementation: an evaluation of information system impact and contingency factors. Int J Med Inform. 2014;83(11):779–96.CrossRefPubMed
11.
Moen A, Hackl WO, Hofdijk J, Van Gemert-Pijnen L, Ammenwerth E, Nykänen P, et al. eHealth in Europe - Status and Challenges. Yearb Med Inform. 2013;8(1):59–63.PubMed
12.
Olsson S, Lymberis A, Whitehouse D. European Commission activities in eHealth. Int J Circumpolar Health. 2004;63(4):310–6.CrossRefPubMed
13.
Iakovidis I, Purcarea O. eHealth in Europe: from Vision to Reality. Stud Health Technol Inform. 2008;134:163–8.PubMed
14.
Martins C, Azevedo LF, Ribeiro O, Sá L, Santos P, Couto L, et al. A Population-Based Nationwide Cross-Sectional Study on Preventive Health Services Utilization in Portugal—What Services (and Frequencies) Are Deemed Necessary by Patients? Sun Q, editor. PLoS ONE. 2013;8(11), e81256.CrossRefPubMedPubMedCentral
15.
van Bokhoven MA, Pleunis-van Empel MCH, Koch H, Grol RPTM, Dinant G-J, van der Weijden T. Why do patients want to have their blood tested? A qualitative study of patient expectations in general practice. BMC Fam Pract. 2006;7:75.CrossRefPubMedPubMedCentral
16.
van der Weijden T, van Bokhoven MA, Dinant G-J, van Hasselt CM, Grol RPTM. Understanding laboratory testing in diagnostic uncertainty: a qualitative study in general practice. Br J Gen Pract J R Coll Gen Pract. 2002;52(485):974–80.
17.
van Bokhoven MA, Koch H, Dinant G-J, Bindels PJ, Grol RP, van der Weijden T. Exploring the black box of change in improving test-ordering routines. Fam Pract. 2008;25(3):139–45.CrossRefPubMed
18.
Verstappen WHJM, ter Riet G, Dubois WI, Winkens R, Grol RPTM, van der Weijden T. Variation in test ordering behaviour of GPs: professional or context-related factors? Fam Pract. 2004;21(4):387–95.CrossRefPubMed
19.
Main C, Moxham T, Wyatt JC, Kay J, Anderson R, Stein K. Computerised decision support systems in order communication for diagnostic, screening or monitoring test ordering: systematic reviews of the effects and cost-effectiveness of systems. Health Technol Assess Winch Engl. 2010;14(48):1–227.
20.
Costa-Pereira A, Giest S, Dumortier J, Artmann J. eHealth Strategies - Country Brief. Portugal: European Commission; 2010.
21.
22.
Martins C, Azevedo LF, Santos C, Sá L, Santos P, Couto M, et al. Preventive health services implemented by family physicians in Portugal-a cross-sectional study based on two clinical scenarios. BMJ Open. 2014;4(5), e005162.CrossRefPubMedPubMedCentral
23.
Administração Regional de Saúde do Norte, IP. Action plan 2010-2012 of the Western Oporto grouping of health centers. 2010.
24.
da Saúde M. National Plan for Prevention and Control of Oncological Diseases 2007/2010. 2007.
25.
Zaat JO, van Eijk JT, Bonte HA. Laboratory test form design influences test ordering by general practitioners in The Netherlands. Med Care. 1992;30(3):189–98.CrossRefPubMed
26.
Barth JH, Balen AH, Jennings A. Appropriate design of biochemistry request cards can promote the use of protocols and reduce unnecessary investigations. Ann Clin Biochem. 2001;38(Pt 6):714–6.CrossRefPubMed
27.
Metadata
Title
The effect of a test ordering software intervention on the prescription of unnecessary laboratory tests - a randomized controlled trial
Authors
Carlos Manuel Silva Martins
Andreia Sofia da Costa Teixeira
Luís Filipe Ribeiro de Azevedo
Luísa Maria Barbosa Sá
Paulo Alexandre Azevedo Pereira Santos
Maria Luciana Gomes Domingues do Couto
Altamiro Manuel Rodrigues da Costa Pereira
Alberto Augusto Oliveira Pinto Hespanhol
Cristina Maria Nogueira da Costa Santos
Publication date
01-12-2017
Publisher
BioMed Central
Published in
BMC Medical Informatics and Decision Making / Issue 1/2017
Electronic ISSN: 1472-6947
DOI
https://doi.org/10.1186/s12911-017-0416-6

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