Abstract
Background:
One driver of increasing health care costs is the use of radiologic imaging procedures. More appropriate use could improve quality and reduce costs.
Purpose:
To review interventions that use the computerized clinical decision-support (CCDS) capabilities of electronic health records to improve appropriate use of diagnostic radiologic test ordering.
Data Sources:
English-language articles in PubMed from 1995 to September 2014 and searches in Web of Science and PubMed of citations related to key articles.
Study Selection:
23 studies, including 3 randomized trials, 7 time-series studies, and 13 pre–post studies that assessed the effect of CCDS on diagnostic radiologic test ordering in adults.
Data Extraction:
2 independent reviewers extracted data on functionality, study outcomes, and context and assessed the quality of included studies.
Data Synthesis:
Thirteen studies provided moderate-level evidence that CCDS improves appropriateness (effect size, −0.49 [95% CI, −0.71 to −0.26]) and reduces use (effect size, −0.13 [CI, −0.23 to −0.04]). Interventions with a “hard stop” that prevents a clinician from overriding the CCDS without outside consultation, as well as interventions in integrated care delivery systems, may be more effective. Harms have rarely been assessed but include decreased ordering of appropriate tests and physician dissatisfaction.
Limitation:
Potential for publication bias, insufficient reporting of harms, and poor description of context and implementation.
Conclusion:
Computerized clinical decision support integrated with the electronic health record can improve appropriate use of diagnostic radiology by a moderate amount and decrease use by a small amount. Before widespread adoption can be recommended, more data are needed on potential harms.
Primary Funding Source:
U.S. Department of Veterans Affairs. (PROSPERO registration number: CRD42014007469)
References
- 1.
Kocher KE ,Meurer WJ ,Fazel R ,Scott PA ,Krumholz HM ,Nallamothu BK . National trends in use of computed tomography in the emergency department. Ann Emerg Med. 2011;58:452-62. [PMID: 21835499] doi:10.1016/j.annemergmed.2011.05.020 CrossrefMedlineGoogle Scholar - 2.
Korley FK ,Pham JC ,Kirsch TD . Use of advanced radiology during visits to U.S. emergency departments for injury-related conditions, 1998-2007. JAMA. 2010;304:1465-71. [PMID: 20924012] doi:10.1001/jama.2010.1408 CrossrefMedlineGoogle Scholar - 3.
Chou R ,Fu R ,Carrino JA ,Deyo RA . Imaging strategies for low-back pain: systematic review and meta-analysis. Lancet. 2009;373:463-72. [PMID: 19200918] doi:10.1016/S0140-6736(09)60172-0 CrossrefMedlineGoogle Scholar - 4.
Moher D ,Liberati A ,Tetzlaff J ,Altman DG ;PRISMA Group . Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med. 2009;151:264-9. [PMID: 19622511] LinkGoogle Scholar - 5.
Chaudhry B ,Wang J ,Wu S ,Maglione M ,Mojica W ,Roth E ,et al . Systematic review: impact of health information technology on quality, efficiency, and costs of medical care. Ann Intern Med. 2006;144:742-52. [PMID: 16702590] LinkGoogle Scholar - 6.
Buntin MB ,Burke MF ,Hoaglin MC ,Blumenthal D . The benefits of health information technology: a review of the recent literature shows predominantly positive results. Health Aff (Millwood). 2011;30:464-71. [PMID: 21383365] doi:10.1377/hlthaff.2011.0178 CrossrefMedlineGoogle Scholar - 7.
Goldzweig CL ,Orshansky G ,Paige NM ,Towfigh AA ,Haggstrom DA ,Miake-Lye I ,et al . Electronic patient portals: evidence on health outcomes, satisfaction, efficiency, and attitudes: a systematic review. Ann Intern Med. 2013;159:677-87. [PMID: 24247673] doi:10.7326/0003-4819-159-10-201311190-00006 LinkGoogle Scholar - 8.
Jones SS ,Rudin RS ,Perry T ,Shekelle PG . Health information technology: an updated systematic review with a focus on meaningful use. Ann Intern Med. 2014;160:48-54. [PMID: 24573664] doi:10.7326/M13-1531 LinkGoogle Scholar - 9.
Georgiou A ,Prgomet M ,Markewycz A ,Adams E ,Westbrook JI . The impact of computerized provider order entry systems on medical-imaging services: a systematic review. J Am Med Inform Assoc. 2011;18:335-40. [PMID: 21385821] doi:10.1136/amiajnl-2010-000043 CrossrefMedlineGoogle Scholar - 10.
Roshanov PS ,Misra S ,Gerstein HC ,Garg AX ,Sebaldt RJ ,Mackay JA ,et al ;CCDSS Systematic Review Team . Computerized clinical decision support systems for chronic disease management: a decision maker–researcher partnership systematic review. Implement Sci. 2011;6:92. [PMID: 21824386] doi:10.1186/1748-5908-6-92 CrossrefMedlineGoogle Scholar - 11.
Fillmore CL ,Bray BE ,Kawamoto K . Systematic review of clinical decision support interventions with potential for inpatient cost reduction. BMC Med Inform Decis Mak. 2013;13:135. [PMID: 24344752] doi:10.1186/1472-6947-13-135 CrossrefMedlineGoogle Scholar - 12.
Borenstein M ,Hedges LV ,Higgins JPT ,Rothstein HR . Chapter 7: Converting among effect sizes.. In: Borenstein M, Hedges LV, Higgins JPT, Rothstein HR, eds. Introduction to Meta-Analysis. Chichester, UK: J Wiley; 2011:45-9. Google Scholar - 13.
Sánchez-Meca J ,Maríen-Martíinez F ,Chacón-Moscoso S . Effect-size indices for dichotomized outcomes in meta-analysis. Psychol Methods. 2003;8:448-67. [PMID: 14664682] CrossrefMedlineGoogle Scholar - 14.
IntHout J ,Ioannidis JP ,Borm GF . The Hartung–Knapp–Sidik–Jonkman method for random effects meta-analysis is straightforward and considerably outperforms the standard DerSimonian–Laird method. BMC Med Res Methodol. 2014;14:25. [PMID: 24548571] doi:10.1186/1471-2288-14-25 CrossrefMedlineGoogle Scholar - 15.
Bates DW ,Kuperman GJ ,Jha A ,Teich JM ,Orav EJ ,Ma'luf N ,et al . Does the computerized display of charges affect inpatient ancillary test utilization? Arch Intern Med. 1997;157:2501-8. [PMID: 9385303] CrossrefMedlineGoogle Scholar - 16.
Tierney WM ,McDonald CJ ,Hui SL ,Martin DK . Computer predictions of abnormal test results. Effects on outpatient testing. JAMA. 1988;259:1194-8. [PMID: 3339821] CrossrefMedlineGoogle Scholar - 17.
Harpole LH ,Khorasani R ,Fiskio J ,Kuperman GJ ,Bates DW . Automated evidence-based critiquing of orders for abdominal radiographs: impact on utilization and appropriateness. J Am Med Inform Assoc. 1997;4:511-21. [PMID: 9391938] CrossrefMedlineGoogle Scholar - 18.
Blackmore CC ,Mecklenburg RS ,Kaplan GS . Effectiveness of clinical decision support in controlling inappropriate imaging. J Am Coll Radiol. 2011;8:19-25. [PMID: 21211760] doi:10.1016/j.jacr.2010.07.009 CrossrefMedlineGoogle Scholar - 19.
Carton M ,Auvert B ,Guerini H ,Boulard JC ,Heautot JF ,Landre MF ,et al . Assessment of radiological referral practice and effect of computer-based guidelines on radiological requests in two emergency departments. Clin Radiol. 2002;57:123-8. [PMID: 11977945] CrossrefMedlineGoogle Scholar - 20. Chin HL, Wallace P. Embedding guidelines into direct physician order entry: simple methods, powerful results. Proceedings of the American Medical Informatics Association Annual Symposium, Washington, DC, 6–10 November 1999. Google Scholar
- 21.
Ip IK ,Schneider L ,Seltzer S ,Smith A ,Dudley J ,Menard A ,et al . Impact of provider-led, technology-enabled radiology management program on imaging. Am J Med. 2013;126:687-92. [PMID: 23786668] doi:10.1016/j.amjmed.2012.11.034 CrossrefMedlineGoogle Scholar - 22.
Raja AS ,Ip IK ,Prevedello LM ,Sodickson AD ,Farkas C ,Zane RD ,et al . Effect of computerized clinical decision support on the use and yield of CT pulmonary angiography in the emergency department. Radiology. 2012;262:468-74. [PMID: 22187633] doi:10.1148/radiol.11110951 CrossrefMedlineGoogle Scholar - 23.
Rosenthal DI ,Weilburg JB ,Schultz T ,Miller JC ,Nixon V ,Dreyer KJ ,et al . Radiology order entry with decision support: initial clinical experience. J Am Coll Radiol. 2006;3:799-806. [PMID: 17412171] CrossrefMedlineGoogle Scholar - 24.
Sistrom CL ,Dang PA ,Weilburg JB ,Dreyer KJ ,Rosenthal DI ,Thrall JH . Effect of computerized order entry with integrated decision support on the growth of outpatient procedure volumes: seven-year time series analysis. Radiology. 2009;251:147-55. [PMID: 19221058] doi:10.1148/radiol.2511081174 CrossrefMedlineGoogle Scholar - 25.
Curry L ,Reed MH . Electronic decision support for diagnostic imaging in a primary care setting. J Am Med Inform Assoc. 2011;18:267-70. [PMID: 21486884] doi:10.1136/amiajnl-2011-000049 CrossrefMedlineGoogle Scholar - 26.
Day F ,Hoang LP ,Ouk S ,Nagda S ,Schriger DL . The impact of a guideline-driven computer charting system on the emergency care of patients with acute low back pain. Proc Annu Symp Comput Appl Med Care. 1995:576-80. [PMID: 8563351] MedlineGoogle Scholar - 27.
Drescher FS ,Chandrika S ,Weir ID ,Weintraub JT ,Berman L ,Lee R ,et al . Effectiveness and acceptability of a computerized decision support system using modified Wells criteria for evaluation of suspected pulmonary embolism. Ann Emerg Med. 2011;57:613-21. [PMID: 21050624] doi:10.1016/j.annemergmed.2010.09.018 CrossrefMedlineGoogle Scholar - 28.
Durand DJ ,Feldman LS ,Lewin JS ,Brotman DJ . Provider cost transparency alone has no impact on inpatient imaging utilization. J Am Coll Radiol. 2013;10:108-13. [PMID: 23273974] doi:10.1016/j.jacr.2012.06.020 CrossrefMedlineGoogle Scholar - 29.
Flamm M ,Fritsch G ,Hysek M ,Klausner S ,Entacher K ,Panisch S ,et al . Quality improvement in preoperative assessment by implementation of an electronic decision support tool. J Am Med Inform Assoc. 2013;20:e91-6. [PMID: 23599223] doi:10.1136/amiajnl-2012-001178 CrossrefMedlineGoogle Scholar - 30.
Gupta A ,Ip IK ,Raja AS ,Andruchow JE ,Sodickson A ,Khorasani R . Effect of clinical decision support on documented guideline adherence for head CT in emergency department patients with mild traumatic brain injury. J Am Med Inform Assoc. 2014;21:e347-51. [PMID: 24534635] doi:10.1136/amiajnl-2013-002536 CrossrefMedlineGoogle Scholar - 31.
Soo Hoo GW .Wu CC ,Vazirani S ,Li Z .Barack BM , Does a clinical decision rule using D-dimer level improve the yield of pulmonary CT angiography? AJR Am J Roentgenol. 2011;196:1059-64. [PMID: 21512071] doi:10.2214/AJR.10.4200 CrossrefMedlineGoogle Scholar - 32.
Ip IK ,Gershanik EF ,Schneider LI ,Raja AS ,Mar W ,Seltzer S ,et al . Impact of IT-enabled intervention on MRI use for back pain. Am J Med. 2014;127:512-8. [PMID: 24513065] doi:10.1016/j.amjmed.2014.01.024 CrossrefMedlineGoogle Scholar - 33.
Sanders DL ,Miller RA . The effects on clinician ordering patterns of a computerized decision support system for neuroradiology imaging studies. Proc AMIA Symp. 2001:583-7. [PMID: 11825254] MedlineGoogle Scholar - 34.
Solberg LI ,Wei F ,Butler JC ,Palattao KJ ,Vinz CA ,Marshall MA . Effects of electronic decision support on high-tech diagnostic imaging orders and patients. Am J Manag Care. 2010;16:102-6. [PMID: 20148614] MedlineGoogle Scholar - 35.
Tierney WM ,Miller ME ,McDonald CJ . The effect on test ordering of informing physicians of the charges for outpatient diagnostic tests. N Engl J Med. 1990;322:1499-504. [PMID: 2186274] CrossrefMedlineGoogle Scholar - 36.
Vartanians VM ,Sistrom CL ,Weilburg JB ,Rosenthal DI ,Thrall JH . Increasing the appropriateness of outpatient imaging: effects of a barrier to ordering low-yield examinations. Radiology. 2010;255:842-9. [PMID: 20501721] doi:10.1148/radiol.10091228 CrossrefMedlineGoogle Scholar - 37.
Raja AS ,Gupta A ,Ip IK ,Mills AM ,Khorasani R . The use of decision support to measure documented adherence to a national imaging quality measure. Acad Radiol. 2014;21:378-83. [PMID: 24507424] doi:10.1016/j.ascra.2013.10.017 CrossrefMedlineGoogle Scholar - 38.
Cohen J . Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Hillsdale, NJ: Lawrence Erlbaum Assoc; 1988. Google Scholar - 39.
Strom BL ,Schinnar R ,Aberra F ,Bilker W ,Hennessy S ,Leonard CE ,et al . Unintended effects of a computerized physician order entry nearly hard-stop alert to prevent a drug interaction: a randomized controlled trial. Arch Intern Med. 2010;170:1578-83. [PMID: 20876410] doi:10.1001/archinternmed.2010.324 CrossrefMedlineGoogle Scholar - 40.
Bowen S ,Johnson K ,Reed MH ,Zhang L ,Curry L . The effect of incorporating guidelines into a computerized order entry system for diagnostic imaging. J Am Coll Radiol. 2011;8:251-8. [PMID: 21458763] doi:10.1016/j.jacr.2010.11.020 CrossrefMedlineGoogle Scholar
Author, Article, and Disclosure Information
Caroline Lubick Goldzweig,
From West Los Angeles Veterans Affairs Medical Center and University of California, Los Angeles, Fielding School of Public Health, Los Angeles, and RAND Corporation, Southern California Evidence-based Practice Center, Santa Monica, California.
Disclaimer: The findings and conclusions in this article are those of the authors, who are responsible for its contents. The findings and conclusions do not necessarily represent the views of the U.S. Department of Veterans Affairs or the U.S. government; therefore, no statement in this article should be construed as an official position of the U.S. Department of Veterans Affairs.
Acknowledgment: The authors thank David Atkins, Charles Anderson, Hardeep Singh, and David Douglas for their input as technical experts or operational partners for this report.
Grant Support: By the Veterans Affairs Quality Enhancement Research Initiative (Veterans Affairs Evidence Synthesis Program Project 05-226).
Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M14-2600.
Corresponding Author: Caroline Lubick Goldzweig, MD, MS, Veterans Affairs West Los Angeles Healthcare Center, 11301 Wilshire Boulevard, 111-G, Los Angeles, CA 90073; e-mail, caroline.
Current Author Addresses: Drs. Goldzweig, Orshansky, Paige, and Shekelle; Ms. Miake-Lye; and Ms. Beroes: Veterans Affairs West Los Angeles Healthcare Center, 11301 Wilshire Boulevard, 111-G, Los Angeles, CA 90073.
Ms. Ewing: RAND Corporation, 1776 Main Street, Santa Monica, CA 90401.
Author Contributions: Conception and design: C.L. Goldzweig, P.G. Shekelle.
Analysis and interpretation of the data: C.L. Goldzweig, G. Orshansky, N.M. Paige, B.A. Ewing, P.G. Shekelle.
Drafting of the article: C.L. Goldzweig, G. Orshansky, N.M. Paige, I.M. Miake-Lye, P.G. Shekelle.
Critical revision of the article for important intellectual content: G. Orshansky, N.M. Paige, I.M. Miake-Lye, C.L. Goldzweig, P.G. Shekelle.
Final approval of the article: C.L. Goldzweig, G. Orshansky, N.M. Paige, I.M. Miake-Lye, J.M. Beroes, B.A. Ewing, P.G. Shekelle.
Statistical expertise: B.A. Ewing.
Obtaining of funding: P.G. Shekelle.
Administrative, technical, or logistic support: I.M. Miake-Lye, J.M. Beroes.
Collection and assembly of data: C.L. Goldzweig, G. Orshansky, N.M. Paige, I.M. Miake-Lye, J.M. Beroes, B.A. Ewing, P.G. Shekelle.
Submit a Comment
Contributors must reveal any conflict of interest. Comments are moderated. Please see our information for authorsregarding comments on an Annals publication.
*All comments submitted after October 1, 2021 and selected for publication will be published online only.