Clinical decision support improves the appropriateness of laboratory test ordering in primary care without increasing diagnostic error: the ELMO cluster randomized trial

Nicolas Delvaux, Veerle Piessens, Tine De Burghgraeve, Pavlos Mamouris, Bert Vaes, Robert Vander Stichele, Hanne Cloetens, Josse Thomas, Dirk Ramaekers, An De Sutter, Bert Aertgeerts, Nicolas Delvaux, Veerle Piessens, Tine De Burghgraeve, Pavlos Mamouris, Bert Vaes, Robert Vander Stichele, Hanne Cloetens, Josse Thomas, Dirk Ramaekers, An De Sutter, Bert Aertgeerts

Abstract

Background: Inappropriate laboratory test ordering poses an important burden for healthcare. Clinical decision support systems (CDSS) have been cited as promising tools to improve laboratory test ordering behavior. The objectives of this study were to evaluate the effects of an intervention that integrated a clinical decision support service into a computerized physician order entry (CPOE) on the appropriateness and volume of laboratory test ordering, and on diagnostic error in primary care.

Methods: This study was a pragmatic, cluster randomized, open-label, controlled clinical trial.

Setting: Two hundred eighty general practitioners (GPs) from 72 primary care practices in Belgium.

Patients: Patients aged ≥ 18 years with a laboratory test order for at least one of 17 indications: cardiovascular disease management, hypertension, check-up, chronic kidney disease (CKD), thyroid disease, type 2 diabetes mellitus, fatigue, anemia, liver disease, gout, suspicion of acute coronary syndrome (ACS), suspicion of lung embolism, rheumatoid arthritis, sexually transmitted infections (STI), acute diarrhea, chronic diarrhea, and follow-up of medication.

Interventions: The CDSS was integrated into a computerized physician order entry (CPOE) in the form of evidence-based order sets that suggested appropriate tests based on the indication provided by the general physician.

Measurements: The primary outcome of the ELMO study was the proportion of appropriate tests over the total number of ordered tests and inappropriately not-requested tests. Secondary outcomes of the ELMO study included diagnostic error, test volume, and cascade activities.

Results: CDSS increased the proportion of appropriate tests by 0.21 (95% CI 0.16-0.26, p < 0.0001) for all tests included in the study. GPs in the CDSS arm ordered 7 (7.15 (95% CI 3.37-10.93, p = 0.0002)) tests fewer per panel. CDSS did not increase diagnostic error. The absolute difference in proportions was a decrease of 0.66% (95% CI 1.4% decrease-0.05% increase) in possible diagnostic error.

Conclusions: A CDSS in the form of order sets, integrated within the CPOE improved appropriateness and decreased volume of laboratory test ordering without increasing diagnostic error.

Trial registration: ClinicalTrials.gov Identifier: NCT02950142 , registered on October 25, 2016.

Conflict of interest statement

None of the authors report any competing interests.

Figures

Fig. 1
Fig. 1
Flow of patient recruitment. CDSS, clinical decision support system; ID, identifier

References

    1. Health Industry Distributors Association (HIDA) 2019 US Laboratory Market Report. 2019.
    1. Washington DC: Health Care Cost Institute . 2017 Health Care Cost and Utilization Report. 2019.
    1. O’Sullivan JW, Stevens S, Hobbs FDR, Salisbury C, Little P, Goldacre B, et al. Temporal trends in use of tests in UK primary care, 2000-15: retrospective analysis of 250 million tests. BMJ. 2018;363:k4666. doi: 10.1136/bmj.k4666.
    1. Zhi M, Ding EL, Theisen-Toupal J, Whelan J, Arnaout R. The landscape of inappropriate laboratory testing: a 15-year meta-analysis. PLoS One. 2013;8:e78962. doi: 10.1371/journal.pone.0078962.
    1. van Walraven C, Naylor CD. Do we know what inappropriate laboratory utilization is? A systematic review of laboratory clinical audits. JAMA. 1998;280:550–558. doi: 10.1001/jama.280.6.550.
    1. Lippi G, Bovo C, Ciaccio M. Inappropriateness in laboratory medicine: an elephant in the room? Ann Transl Med. 2017;5:82. doi: 10.21037/atm.2017.02.04.
    1. Houben PHH, van der Weijden T, Winkens RAG, Grol RPTM. Cascade effects of laboratory testing are found to be rare in low disease probability situations: prospective cohort study. J Clin Epidemiol. 2010;63:452–458. doi: 10.1016/j.jclinepi.2009.08.004.
    1. Morgan DJ, Brownlee S, Leppin AL, Kressin N, Dhruva SS, Levin L, et al. Setting a research agenda for medical overuse. BMJ. 2015;351:h4534. doi: 10.1136/bmj.h4534.
    1. Epner PL, Gans JE, Graber ML. When diagnostic testing leads to harm: a new outcomes-based approach for laboratory medicine. BMJ Qual Saf. 2013;22:ii6–ii10. doi: 10.1136/bmjqs-2012-001621.
    1. Hickner J, Thompson PJ, Wilkinson T, Epner P, Shaheen M, Pollock AM, et al. Primary care physicians’ challenges in ordering clinical laboratory tests and interpreting results. J Am Board Fam Med. 2014;27:268–274. doi: 10.3122/jabfm.2014.02.130104.
    1. Vrijsen BEL, Naaktgeboren CA, Vos LM, van Solinge WW, Kaasjager HAH, ten Berg MJ. Inappropriate laboratory testing in internal medicine inpatients: prevalence, causes and interventions. Ann Med Surg. 2020;51:48–53. doi: 10.1016/j.amsu.2020.02.002.
    1. Roman BR, Yang A, Masciale J, Korenstein D. Association of attitudes regarding overuse of inpatient laboratory testing with health care provider type. JAMA Intern Med. 2017;177:1205–1207. doi: 10.1001/jamainternmed.2017.1634.
    1. Hoffman JR, Kanzaria HK. Intolerance of error and culture of blame drive medical excess. BMJ. 2014;349. 10.1136/bmj.g5702.
    1. Cadogan SL, Browne JP, Bradley CP, Cahill MR. The effectiveness of interventions to improve laboratory requesting patterns among primary care physicians: a systematic review. Implement Sci. 2015;10:167. doi: 10.1186/s13012-015-0356-4.
    1. Maillet É, Paré G, Currie LM, Raymond L, Ortiz de Guinea A, Trudel M-C, et al. Laboratory testing in primary care: a systematic review of health IT impacts. Int J Med Inform. 2018;116:52–69. doi: 10.1016/j.ijmedinf.2018.05.009.
    1. Rubinstein M, Hirsch R, Bandyopadhyay K, Madison B, Taylor T, Ranne A, et al. Effectiveness of practices to support appropriate laboratory test utilization: a laboratory medicine best practices systematic review and meta-analysis. Am J Clin Pathol. 2018;149:197–221. doi: 10.1093/ajcp/aqx147.
    1. Bright TJ, Wong A, Dhurjati R, Bristow E, Bastian L, Coeytaux RR, et al. Effect of clinical decision-support systems: a systematic review. Ann Intern Med. 2012;157:29–43. doi: 10.7326/0003-4819-157-1-201207030-00450.
    1. Delvaux N, Van Thienen K, Heselmans A, de Velde SV, Ramaekers D, Aertgeerts B. The effects of computerized clinical decision support systems on laboratory test ordering: a systematic review. Arch Pathol Lab Med. 2017;141:585–595. doi: 10.5858/arpa.2016-0115-RA.
    1. van Wyk JT, van Wijk MA, Sturkenboom MC, Mosseveld M, Moorman PW, van der Lei J. Electronic alerts versus on-demand decision support to improve dyslipidemia treatment: a cluster randomized controlled trial. Circulation. 2008;117:371–378. doi: 10.1161/CIRCULATIONAHA.107.697201.
    1. Sequist TD, Gandhi TK, Karson AS, Fiskio JM, Bugbee D, Sperling M, et al. A randomized trial of electronic clinical reminders to improve quality of care for diabetes and coronary artery disease. J Am Med Inform Assoc. 2005;12:431–437. doi: 10.1197/jamia.M1788.
    1. Zera CA, Bates DW, Stuebe AM, Ecker JL, Seely EW. Diabetes screening reminder for women with prior gestational diabetes: a randomized controlled trial. Obstet Gynecol. 2015;126:109–114. doi: 10.1097/AOG.0000000000000883.
    1. van Wijk MAM, van der Lei J, Mosseveld M, Bohnen AM, van Bemmel JH. Assessment of decision support for blood test ordering in primary care. A randomized trial. Ann Intern Med. 2001;134:274–281. doi: 10.7326/0003-4819-134-4-200102200-00010.
    1. Feldstein AC, Smith DH, Perrin N, Yang X, Rix M, Raebel MA, et al. Improved therapeutic monitoring with several interventions: a randomized trial. Arch Intern Med. 2006;166:1848–1854. doi: 10.1001/archinte.166.17.1848.
    1. Smith DH, Feldstein AC, Perrin NA, Yang X, Rix MM, Raebel MA, et al. Improving laboratory monitoring of medications: an economic analysis alongside a clinical trial. Am J Managed Care. 2009;15:281–289.
    1. Delvaux N, De Sutter A, Van de Velde S, Ramaekers D, Fieuws S, Aertgeerts B. Electronic Laboratory Medicine ordering with evidence-based Order sets in primary care (ELMO study): protocol for a cluster randomised trial. Implement Sci. 2017;12:147. doi: 10.1186/s13012-017-0685-6.
    1. De Sutter A, Van den Bruel A, Devriese S, Mambourg F, Van Gaever V, Verstraete A, et al. Laboratorium testen in de huisartsgeneeskunde. Federaal Kenniscentrum voor de Gezondheidszorg (KCE) 2007.
    1. Avonts M, Cloetens H, Leyns C, Delvaux N, Dekker N, Demulder A, et al. Aanbeveling voor goede medisch praktijkvoering: Aanvraag van laboratoriumtests door huisartsen. Huisarts Nu. 2011. pp. S1–S55.
    1. Leysen P, Avonts M, Cloetens H, Delvaux N, Koeck P, Saegeman V, et al. Richtlijn voor goed medische praktijkvoering: Aanvraag van laboratoriumtests door huisartsen - deel 2. Domus Medica vzw: Antwerpen; 2012.
    1. Delvaux N, Aertgeerts B, van Bussel JC, Goderis G, Vaes B, Vermandere M. Health data for research through a nationwide privacy-proof system in Belgium: design and implementation. JMIR Med Inform. 2018;6:e11428. doi: 10.2196/11428.
    1. Bindraban RS, van Beneden M, Kramer MHH, van Solinge WW, van de Ven PM, Naaktgeboren CA, et al. Association of a multifaceted intervention with ordering of unnecessary laboratory tests among caregivers in internal medicine departments. JAMA Netw Open. 2019;2:e197577. doi: 10.1001/jamanetworkopen.2019.7577.
    1. Krogsbøll LT, Jørgensen KJ, Gøtzsche PC. General health checks in adults for reducing morbidity and mortality from disease. Cochrane Database Syst Rev. 2019. doi: 10.1002/14651858.CD009009.pub3. Cited 14 Aug 2019.
    1. European IVD Market Statistics Report 2017 . Belgium: MedTech Europe. 2017.
    1. Gandhi TK, Kachalia A, Thomas EJ, Puopolo AL, Yoon C, Brennan TA, et al. Missed and delayed diagnoses in the ambulatory setting: a study of closed malpractice claims. Ann Intern Med. 2006;145:488–496. doi: 10.7326/0003-4819-145-7-200610030-00006.
    1. McDonald KM, Matesic B, Contopoulos-Ioannidis DG, Lonhart J, Schmidt E, Pineda N, et al. Patient safety strategies targeted at diagnostic errors. Ann Intern Med. 2013;158:381–389. doi: 10.7326/0003-4819-158-5-201303051-00004.
    1. Elwenspoek MMC, Patel R, Watson JC, Whiting P. Are guidelines for monitoring chronic disease in primary care evidence based? BMJ. 2019;365. 10.1136/bmj.l2319.
    1. Callahan A, Shah NH, Chen JH. Research and reporting considerations for observational studies using electronic health record data. Ann Intern Med. 2020;172:S79–S84. doi: 10.7326/M19-0873.
    1. Van de Velde S, Roshanov P, Kortteisto T, Kunnamo I, Aertgeerts B, Vandvik PO, et al. Tailoring implementation strategies for evidence-based recommendations using computerised clinical decision support systems: protocol for the development of the GUIDES tools. Implement Sci. 2016;11:29. doi: 10.1186/s13012-016-0393-7.
    1. Devaraj S, Sharma SK, Fausto DJ, Viernes S, Kharrazi H. Barriers and facilitators to clinical decision support systems adoption: a systematic review. J Bus Adm Res. 2014;3:36. doi: 10.5430/jbar.v3n2p36.
    1. Powers BW, Jain SH, Shrank WH. De-adopting low-value care: evidence, eminence, and economics. JAMA. 2020. 10.1001/jama.2020.17534.

Source: PubMed

3
Se inscrever