Journal:Laboratory demand management strategies: An overview - Revision history

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	This research received no external funding.		This research received no external funding.

	==Conflicts of interest===		===Conflicts of interest===
	The authors declare no conflict of interest.		The authors declare no conflict of interest.

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	\|website = [https://www.mdpi.com/2075-4418/11/7/1141/htm https://www.mdpi.com/2075-4418/11/7/1141/htm]		\|website = [https://www.mdpi.com/2075-4418/11/7/1141/htm https://www.mdpi.com/2075-4418/11/7/1141/htm]
	\|download = [https://www.mdpi.com/2075-4418/11/7/1141/pdf https://www.mdpi.com/2075-4418/11/7/1141/pdf] (PDF)		\|download = [https://www.mdpi.com/2075-4418/11/7/1141/pdf https://www.mdpi.com/2075-4418/11/7/1141/pdf] (PDF)
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	In conclusion, the implementation of DM tools of laboratory specialists in collaboration with clinicians is increasing, and the incorporation of AI solutions is emerging in recent years. We believe that these solutions will help us to overcome technical barriers, a lack of harmonization, and other challenges.		In conclusion, the implementation of DM tools of laboratory specialists in collaboration with clinicians is increasing, and the incorporation of AI solutions is emerging in recent years. We believe that these solutions will help us to overcome technical barriers, a lack of harmonization, and other challenges.

			==Acknowledgements==
			===Author contributions===
			Conceptualization, C.M. and J.C.; writing—original draft preparation, C.M.; writing—review and editing, C.M., E.H.-B., T.K.F., M.H.K., H.O. and J.C.; visualization, C.M.; supervision, J.C.; project administration, C.M. All authors have read and agreed to the published version of the manuscript.

			===Funding===
			This research received no external funding.

			==Conflicts of interest===
			The authors declare no conflict of interest.

	==References==		==References==

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	==Discussion and conclusions==		==Discussion and conclusions==
			There is broad approval that laboratory DM approaches are useful for appropriate test utilization, and several tools are already in use.<ref name=":24">{{Cite journal \|last=Ibarz \|first=Mercedes \|last2=Cadamuro \|first2=Janne \|last3=Sumarac \|first3=Zorica \|last4=Guimaraes \|first4=Joao Tiago \|last5=Kovalevskaya \|first5=Svetlana \|last6=Nybo \|first6=Mads \|last7=Cornes \|first7=Michael P. \|last8=Vermeersch \|first8=Pieter \|last9=Simundic \|first9=Ana-Maria \|last10=Lippi \|first10=Giuseppe \|date=2021-02-23 \|title=Clinicians’ and laboratory medicine specialists’ views on laboratory demand management: a survey in nine European countries \|url=https://www.degruyter.com/document/doi/10.1515/dx-2019-0081/html \|journal=Diagnosis \|language=en \|volume=8 \|issue=1 \|pages=111–119 \|doi=10.1515/dx-2019-0081 \|issn=2194-802X}}</ref> However, there are still a number of challenges. Due to different outcome criteria and settings, results may not be generalizable or comparable, which is why DM approaches have to be adapted to local settings. Therefore, harmonization strategies would be desirable. However, a survey conducted by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Working Group on Harmonization of the total testing process (WG-H) among national society members of the EFLM revealed that existing harmonization activities are not coordinated. MRIs are one example mentioned, for which the EFLM WG-H wants to start initiatives to produce official documents in European countries.<ref>{{Cite journal \|last=Ceriotti \|first=Ferruccio \|last2=Barhanovic \|first2=Najdana Gligorovic \|last3=Kostovska \|first3=Irena \|last4=Kotaska \|first4=Karel \|last5=Perich Alsina \|first5=Maria Carmen \|date=2016-01-01 \|title=Harmonisation of the laboratory testing process: need for a coordinated approach \|url=https://www.degruyter.com/document/doi/10.1515/cclm-2016-0244/html \|journal=Clinical Chemistry and Laboratory Medicine (CCLM) \|volume=54 \|issue=12 \|pages=e361–e363 \|doi=10.1515/cclm-2016-0244 \|issn=1437-4331}}</ref> In addition, the third EFLM Strategic Conference under the chair of EFLM president Ana-Maria Simundic was planned to focus on DM only and to generate several task-and-finish groups that would lead the profession in this direction. Sadly, this conference had to be postponed due to the COVID-19 pandemic. We believe that the topics of harmonization as well as DM are recognized by laboratory specialists and that progress will be made over the coming decade.

			As mentioned above, another challenge is that inappropriate orders remain.<ref name=":2" /> One possibility for achieving appropriate test selection may be to conduct a health technology assessment prior to test implementation. Landaas ''et al.''<ref>{{Cite journal \|last=Landaas \|first=Erik J. \|last2=Eckel \|first2=Ashley M. \|last3=Wright \|first3=Jonathan L. \|last4=Baird \|first4=Geoffrey S. \|last5=Hansen \|first5=Ryan N. \|last6=Sullivan \|first6=Sean D. \|date=2020-01-01 \|title=Application of Health Technology Assessment (HTA) to Evaluate New Laboratory Tests in a Health System: A Case Study of Bladder Cancer Testing \|url=http://journals.sagepub.com/doi/10.1177/2374289520968225 \|journal=Academic Pathology \|language=en \|volume=7 \|pages=237428952096822 \|doi=10.1177/2374289520968225 \|issn=2374-2895 \|pmc=PMC7656863 \|pmid=33225061}}</ref> describe an approach whereby the Laboratory Formulary Committee, comprising different medicine professionals, and the Smart Innovation staff of the local hospital analyzed a new molecular bladder cancer test according to a locally implemented health technology assessment program. In conclusion, the committee currently does not support system-wide use, but decided to start a small pilot study. The results thereof indicate that the test could have benefits for selected patients.

			However, these evidence-based assessments and further recommendations proposed for successful implementation, like the selection of quality indicators for monitoring and improvement as well as the ensuring of regular updates, are time-consuming.<ref name=":25">{{Cite journal \|last=Cadamuro \|first=Janne \|last2=Ibarz \|first2=Mercedes \|last3=Cornes \|first3=Michael \|last4=Nybo \|first4=Mads \|last5=Haschke-Becher \|first5=Elisabeth \|last6=von Meyer \|first6=Alexander \|last7=Lippi \|first7=Giuseppe \|last8=Simundic \|first8=Ana-Maria \|date=2019-03-26 \|title=Managing inappropriate utilization of laboratory resources \|url=https://pubmed.ncbi.nlm.nih.gov/30096052 \|journal=Diagnosis (Berlin, Germany) \|volume=6 \|issue=1 \|pages=5–13 \|doi=10.1515/dx-2018-0029 \|issn=2194-802X \|pmid=30096052}}</ref> We believe that AI solutions are the next logical step, aiding in the development as well as improvement of DM strategies, as they could help to manage large data sets. The synopsis of results from laboratory medicine, diagnostic imaging, and pathology is necessary for the purpose of integrated diagnostics. Furthermore, the patient’s history, comorbidities, symptoms, and treatments have to be taken into account for correct interpretation.<ref>{{Cite journal \|last=Lippi \|first=Giuseppe \|last2=Plebani \|first2=Mario \|date=2020-02-15 \|title=Integrated diagnostics: the future of laboratory medicine? \|url=https://pubmed.ncbi.nlm.nih.gov/31839719 \|journal=Biochemia Medica \|volume=30 \|issue=1 \|pages=010501 \|doi=10.11613/BM.2020.010501 \|issn=1846-7482 \|pmc=6904966 \|pmid=31839719}}</ref> Currently, few published articles deal with the issue of applying AI algorithms to laboratory test selection. Islam ''et al.''<ref>{{Cite journal \|last=Islam \|first=Md Mohaimenul \|last2=Yang \|first2=Hsuan-Chia \|last3=Poly \|first3=Tahmina Nasrin \|last4=Li \|first4=Yu-Chuan Jack \|date=2020-11-18 \|title=Development of an Artificial Intelligence-Based Automated Recommendation System for Clinical Laboratory Tests: Retrospective Analysis of the National Health Insurance Database \|url=https://pubmed.ncbi.nlm.nih.gov/33206057 \|journal=JMIR medical informatics \|volume=8 \|issue=11 \|pages=e24163 \|doi=10.2196/24163 \|issn=2291-9694 \|pmc=7710445 \|pmid=33206057}}</ref><ref name=":26">{{Cite journal \|last=Islam \|first=Md. Mohaimenul \|last2=Poly \|first2=Tahmina Nasrin \|last3=Yang \|first3=Hsuan-Chia \|last4=Li \|first4=Yu-Chuan (Jack) \|date=2021-05-29 \|title=Deep into Laboratory: An Artificial Intelligence Approach to Recommend Laboratory Tests \|url=https://www.mdpi.com/2075-4418/11/6/990 \|journal=Diagnostics \|language=en \|volume=11 \|issue=6 \|pages=990 \|doi=10.3390/diagnostics11060990 \|issn=2075-4418 \|pmc=PMC8227070 \|pmid=34072571}}</ref> have published two such studies, one of which in this issue, where they developed a deep learning algorithm based on retrospective patient data to predict appropriate laboratory tests. Xu ''et al.''<ref>{{Cite journal \|last=Xu \|first=Song \|last2=Hom \|first2=Jason \|last3=Balasubramanian \|first3=Santhosh \|last4=Schroeder \|first4=Lee F. \|last5=Najafi \|first5=Nader \|last6=Roy \|first6=Shivaal \|last7=Chen \|first7=Jonathan H. \|date=2019-09-11 \|title=Prevalence and Predictability of Low-Yield Inpatient Laboratory Diagnostic Tests \|url=https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2749559 \|journal=JAMA Network Open \|language=en \|volume=2 \|issue=9 \|pages=e1910967 \|doi=10.1001/jamanetworkopen.2019.10967 \|issn=2574-3805 \|pmc=PMC6739729 \|pmid=31509205}}</ref> aimed to identify superfluous tests in existing lab orders by estimating normal test results within a retrospective dataset. [[Machine learning]] (ML) models may also be used to identify prognostic factors. Tseng ''et al.''<ref>{{Cite journal \|last=Tseng \|first=Yi-Ju \|last2=Wang \|first2=Hsin-Yao \|last3=Lin \|first3=Ting-Wei \|last4=Lu \|first4=Jang-Jih \|last5=Hsieh \|first5=Chia-Hsun \|last6=Liao \|first6=Chun-Ta \|date=2020-08-03 \|title=Development of a Machine Learning Model for Survival Risk Stratification of Patients With Advanced Oral Cancer \|url=https://pubmed.ncbi.nlm.nih.gov/32821921 \|journal=JAMA network open \|volume=3 \|issue=8 \|pages=e2011768 \|doi=10.1001/jamanetworkopen.2020.11768 \|issn=2574-3805 \|pmc=7442932 \|pmid=32821921}}</ref> incorporated clinical, pathological, and cancer-related gene features of patients with advanced oral cancer and found that only 6 of 44 genes analyzed are necessary for further prognostic risk stratification. Therefore, costs and resources for molecular analysis could be reduced with targeted requests. The MRIs mentioned above are implemented as pre-defined alerts. Concerning this challenge, Baron ''et al.''<ref>{{Cite journal \|last=Baron \|first=Jason M \|last2=Huang \|first2=Richard \|last3=McEvoy \|first3=Dustin \|last4=Dighe \|first4=Anand S \|date=2021-01-01 \|title=Use of machine learning to predict clinical decision support compliance, reduce alert burden, and evaluate duplicate laboratory test ordering alerts \|url=https://doi.org/10.1093/jamiaopen/ooab006 \|journal=JAMIA Open \|volume=4 \|issue=ooab006 \|doi=10.1093/jamiaopen/ooab006 \|issn=2574-2531 \|pmc=PMC7935497 \|pmid=33709062}}</ref> mention an approach where logistic regression models may be used to predict whether alerts will be accepted or overruled. The aim is to reduce the alert burden for the ordering clinician by showing only alerts that have a high probability of being accepted. However, not all questions can be solved with AI. For example, using serum tumor markers alone for cancer screening may currently not be recommended even if data were retrospectively evaluated using various ML models.<ref>{{Cite journal \|last=Wang \|first=Hsin-Yao \|last2=Hsieh \|first2=Chia-Hsun \|last3=Wen \|first3=Chiao-Ni \|last4=Wen \|first4=Ying-Hao \|last5=Chen \|first5=Chun-Hsien \|last6=Lu \|first6=Jang-Jih \|date=2016-06-29 \|editor-last=Tan \|editor-first=Min-Han \|title=Cancers Screening in an Asymptomatic Population by Using Multiple Tumour Markers \|url=https://dx.plos.org/10.1371/journal.pone.0158285 \|journal=PLOS ONE \|language=en \|volume=11 \|issue=6 \|pages=e0158285 \|doi=10.1371/journal.pone.0158285 \|issn=1932-6203 \|pmc=PMC4927114 \|pmid=27355357}}</ref>

			Furthermore, it has to be acknowledged that AI is only a tool of assistance.<ref name=":26" /> A combination of computerized and physician-guided processes may be better than each one on their own. Wang ''et al.''<ref>{{Cite journal \|last=Wang D.; Khosla, A.; Gargeya, R. et al. \|year=2016 \|title=Deep Learning for Identifying Metastatic Breast Cancer \|url=https://arxiv.org/abs/1606.05718v1 \|journal=arXiv \|arxiv=1606.05718v1}}</ref> proved this theory when evaluating the efficiency of a deep learning system and experienced pathologists in detecting breast cancer cells. AUROC values were 0.925 for the former and 0.966 for the latter, but 0.995 when combined. Therefore, AI solutions may complement the recommended collaborations with clinicians for successful implementation.<ref name=":25" /> Intensifying collaborations should be a feasible task, since a survey indicates that interest from both professions exists.<ref name=":24" /> An advantage of complementary AI solutions would be that these systems, fed with unfiltered patient data, are capable of finding completely new diagnostic strategies that humans have not yet thought of. For example, Lien ''et al.''<ref>{{Cite journal \|last=Lien \|first=Frank \|last2=Wang \|first2=Hsin-Yao \|last3=Lu \|first3=Jang-Jih \|last4=Wen \|first4=Ying-Hao \|last5=Chiueh \|first5=Tzong-Shi \|date=2021-03-01 \|title=Predicting 2-Day Mortality of Thrombocytopenic Patients Based on Clinical Laboratory Data Using Machine Learning \|url=https://pubmed.ncbi.nlm.nih.gov/33027237 \|journal=Medical Care \|volume=59 \|issue=3 \|pages=245–250 \|doi=10.1097/MLR.0000000000001421 \|issn=1537-1948 \|pmc=7993911 \|pmid=33027237}}</ref> compared different ML models concerning the prediction of the two-day mortality of thrombocytopenic patients on the basis of hematological tests only.

			In conclusion, the implementation of DM tools of laboratory specialists in collaboration with clinicians is increasing, and the incorporation of AI solutions is emerging in recent years. We believe that these solutions will help us to overcome technical barriers, a lack of harmonization, and other challenges.

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	===Revision of laboratory ordering forms and profiles===		===Revision of laboratory ordering forms and profiles===
	The position where tests are placed in the order entry system may affect the number of placed orders.<ref name=":10" /> Furthermore, laboratory ordering profiles (LOPs), which are used to order a bundle of defined analytes with one click in the CPOE system, seem to be a source of overutilization; studies show that the number of orders drops after removing tests from such LOPs. An example provided by Michael Cornes describes a reduction of GGT orders of 82% after the test aiming to assess liver function was removed from the LOP.<ref name=":7" /> Keppel ''et al.''<ref>{{Cite journal \|last=Keppel \|first=Martin H. \|last2=Kolbitsch \|first2=Tobias \|last3=Hoppe \|first3=Uta C. \|last4=Auer \|first4=Simon \|last5=Felder \|first5=Thomas K. \|last6=Oberkofler \|first6=Hannes \|last7=Mrazek \|first7=Cornelia \|last8=Haschke-Becher \|first8=Elisabeth \|last9=Cadamuro \|first9=Janne \|date=2020-08-27 \|title=The clinically effective use of cardiac markers by restructuring laboratory profiles at Cardiology wards \|url=https://pubmed.ncbi.nlm.nih.gov/32305953 \|journal=Clinical Chemistry and Laboratory Medicine \|volume=58 \|issue=9 \|pages=1565–1571 \|doi=10.1515/cclm-2019-1229 \|issn=1437-4331 \|pmid=32305953}}</ref> retrospectively evaluated a DM strategy implemented to reduce unnecessary testing of the cardiac markers high-sensitive troponin T (hsTropT) and NT-proBNP. This intervention was conducted in collaboration with clinicians at three wards of the department of Cardiology, Clinic of Internal Medicine II, University Hospital Salzburg. The implementation started in one ward with an educational approach (see the later subsection on "Education"). Later, both cardiac markers were removed from all LOPs of the three wards, along with the distribution of information about the correct use of hsTropT and NT-proBNP in the form of guidelines and oral presentations. Despite the opportunity to order both tests without restrictions in the CPOE system separate from the LOP, monthly orders decreased by 66.1% and 75.8% for hsTropT and NT-proBNP, respectively, on all three wards. These results indicate that LOPs may indeed be a source of overutilization since they are often not used correctly (e.g., for specific indications) but merely for convenience purposes. Regarding patient safety, length of patient stay and 30-day all-cause re-admission rate were evaluated as surrogate markers, without adverse outcomes.		The position where tests are placed in the order entry system may affect the number of placed orders.<ref name=":10" /> Furthermore, laboratory ordering profiles (LOPs), which are used to order a bundle of defined analytes with one click in the CPOE system, seem to be a source of overutilization; studies show that the number of orders drops after removing tests from such LOPs. An example provided by Michael Cornes describes a reduction of GGT orders of 82% after the test aiming to assess liver function was removed from the LOP.<ref name=":7" /> Keppel ''et al.''<ref>{{Cite journal \|last=Keppel \|first=Martin H. \|last2=Kolbitsch \|first2=Tobias \|last3=Hoppe \|first3=Uta C. \|last4=Auer \|first4=Simon \|last5=Felder \|first5=Thomas K. \|last6=Oberkofler \|first6=Hannes \|last7=Mrazek \|first7=Cornelia \|last8=Haschke-Becher \|first8=Elisabeth \|last9=Cadamuro \|first9=Janne \|date=2020-08-27 \|title=The clinically effective use of cardiac markers by restructuring laboratory profiles at Cardiology wards \|url=https://pubmed.ncbi.nlm.nih.gov/32305953 \|journal=Clinical Chemistry and Laboratory Medicine \|volume=58 \|issue=9 \|pages=1565–1571 \|doi=10.1515/cclm-2019-1229 \|issn=1437-4331 \|pmid=32305953}}</ref> retrospectively evaluated a DM strategy implemented to reduce unnecessary testing of the cardiac markers high-sensitive troponin T (hsTropT) and NT-proBNP. This intervention was conducted in collaboration with clinicians at three wards of the department of Cardiology, Clinic of Internal Medicine II, University Hospital Salzburg. The implementation started in one ward with an educational approach (see the later subsection on "Education"). Later, both cardiac markers were removed from all LOPs of the three wards, along with the distribution of information about the correct use of hsTropT and NT-proBNP in the form of guidelines and oral presentations. Despite the opportunity to order both tests without restrictions in the CPOE system separate from the LOP, monthly orders decreased by 66.1% and 75.8% for hsTropT and NT-proBNP, respectively, on all three wards. These results indicate that LOPs may indeed be a source of overutilization since they are often not used correctly (e.g., for specific indications) but merely for convenience purposes. Regarding patient safety, length of patient stay and 30-day all-cause re-admission rate were evaluated as surrogate markers, without adverse outcomes.

			Similarly, Larochelle ''et al.''<ref name=":4" /> removed cardiac markers from LOPs. While CK and CK-MB were entirely removed, troponin remained in two LOPs for evaluation of new symptoms, suggesting ACS. As indicated above, this DM strategy was implemented in a multifaceted approach. Altogether, the percentage of patients per month with guideline-concordant ordering of cardiac markers for ACS increased from 57.1% to 95.5%. Annually, ordered tests decreased by 16%, 87%, and 95% for troponin, CK, and CK-MB, respectively.

			Along with educational sessions, audits, and feedback, Bartlett ''et al.''<ref name=":2" /> introduced a panel for CRP and ESR testing. CRP was preselected, and an explanation referred to the recommended indications for these tests. Overall, ESR as well as combined ESR/CRP testing were reduced by 33% and 25%, respectively, while the mean number of CRP tests remained unchanged. However, further examination of patients’ charts revealed that inappropriate ESR orders remained after the intervention.

			Other studies focus on LOPs for specific indications or diagnoses. Delvaux ''et al.''<ref>{{Cite journal \|last=Delvaux \|first=Nicolas \|last2=Piessens \|first2=Veerle \|last3=Burghgraeve \|first3=Tine De \|last4=Mamouris \|first4=Pavlos \|last5=Vaes \|first5=Bert \|last6=Stichele \|first6=Robert Vander \|last7=Cloetens \|first7=Hanne \|last8=Thomas \|first8=Josse \|last9=Ramaekers \|first9=Dirk \|last10=Sutter \|first10=An De \|last11=Aertgeerts \|first11=Bert \|date=2020-11-04 \|title=Clinical decision support improves the appropriateness of laboratory test ordering in primary care without increasing diagnostic error: the ELMO cluster randomized trial \|url=https://pubmed.ncbi.nlm.nih.gov/33148311 \|journal=Implementation science: IS \|volume=15 \|issue=1 \|pages=100 \|doi=10.1186/s13012-020-01059-y \|issn=1748-5908 \|pmc=7640389 \|pmid=33148311}}</ref> conducted a randomized controlled trial among general physicians (GPs). LOPs were created for 17 selected indications, based on available guidelines. In the intervention group, GPs received suggested analyses through the CPOE system after selecting an indication, and modifications were allowed before submitting the request. The control group also stated the indication of their orders but did not receive suggestions for test ordering. In the intervention group, the proportion of appropriate tests significantly increased by 0.21 for all tests. In the intervention arm, only 24 tests were ordered per panel, compared to 31 tests in the control arm. The evaluation of potentially delayed diagnoses revealed no difference between the groups. This is an example of how laboratory specialists may aid in test requesting and of how physicians are willing to accept their expert opinion.

			Whiting ''et al.''<ref name=":1" /> aimed to standardize blood tests and introduced the possibility for primary care physicians to order “test groups” for monitoring patients with chronic diseases. Compared to previous habits, full blood counts (FBCs) and liver function tests (LFTs) were not required in this indication. The implementation comprised several PDSA cycles, educational sessions, and regular meetings for discussion and feedback. Requests per 1,000 patients significantly decreased by 14% and 22% for hemoglobin assessing FBC and bilirubin assessing LFT, respectively. Sodium, which was not affected by the DM strategy, and ALT values ≥ 120IU/L, which were assessed to identify alterations in possible significant pathology, did not show significant changes. Therefore, the authors concluded that the measures may not lead to more missed diagnoses.

			In conclusion, LOPs should be revised to suggest appropriate tests for specific indications or diagnoses<ref>{{Cite journal \|last=Smellie \|first=W. S. A. \|last2=Association for Clinical Biochemistry’s Clinical Practice Section \|date=2012-03-20 \|title=Time to harmonise common laboratory test profiles \|url=https://pubmed.ncbi.nlm.nih.gov/22434088 \|journal=BMJ (Clinical research ed.) \|volume=344 \|pages=e1169 \|doi=10.1136/bmj.e1169 \|issn=1756-1833 \|pmid=22434088}}</ref> rather than for unspecific “routine” panels.

			===Removal of outdated tests===
			Apart from giving an alert for inappropriate orders, tests may also be entirely removed from the order entry system. One example within the publication of Mrazek ''et al.''<ref name=":7" />, provided by Ana-Maria Simundic, refers to a stepwise elimination process of CK-MB isoform. According to an expert consensus document, CK-MB isoform may not be necessary in the case of high sensitive troponin assay availability.<ref>{{Cite journal \|last=Thygesen \|first=Kristian \|last2=Alpert \|first2=Joseph S \|last3=Jaffe \|first3=Allan S \|last4=Chaitman \|first4=Bernard R \|last5=Bax \|first5=Jeroen J \|last6=Morrow \|first6=David A \|last7=White \|first7=Harvey D \|last8=ESC Scientific Document Group \|last9=Thygesen \|first9=Kristian \|last10=Alpert \|first10=Joseph S \|last11=Jaffe \|first11=Allan S \|date=2019-01-14 \|title=Fourth universal definition of myocardial infarction (2018) \|url=https://academic.oup.com/eurheartj/article/40/3/237/5079081 \|journal=European Heart Journal \|language=en \|volume=40 \|issue=3 \|pages=237–269 \|doi=10.1093/eurheartj/ehy462 \|issn=0195-668X}}</ref>

			===Display costs===
			Some studies evaluated the effect of displaying costs during the order entry process. Horn ''et al.''<ref>{{Cite journal \|last=Horn \|first=Daniel M. \|last2=Koplan \|first2=Kate E. \|last3=Senese \|first3=Margaret D. \|last4=Orav \|first4=E. John \|last5=Sequist \|first5=Thomas D. \|date=2014-05 \|title=The Impact of Cost Displays on Primary Care Physician Laboratory Test Ordering \|url=http://link.springer.com/10.1007/s11606-013-2672-1 \|journal=Journal of General Internal Medicine \|language=en \|volume=29 \|issue=5 \|pages=708–714 \|doi=10.1007/s11606-013-2672-1 \|issn=0884-8734 \|pmc=PMC4000348 \|pmid=24257964}}</ref> selected 27 laboratory tests, which yielded overall high costs due to the high price of a single analysis or to frequent ordering. Through the intervention period, the costs were displayed to primary care physicians of a group practice (“intervention physicians”), while physicians of other group practices, who received no information about prices, served as a control. In addition, the intervention physicians were informed about the aim of the project via e-mail. The results showed that for five of the twenty-seven tests, the display of cost information was associated with a statistically significant reduction in monthly laboratory ordering rates.

			Similarly, Feldman ''et al.''<ref>{{Cite journal \|last=Feldman \|first=Leonard S. \|last2=Shihab \|first2=Hasan M. \|last3=Thiemann \|first3=David \|last4=Yeh \|first4=Hsin-Chieh \|last5=Ardolino \|first5=Margaret \|last6=Mandell \|first6=Steven \|last7=Brotman \|first7=Daniel J. \|date=2013-05-27 \|title=Impact of Providing Fee Data on Laboratory Test Ordering: A Controlled Clinical Trial \|url=http://archinte.jamanetwork.com/article.aspx?doi=10.1001/jamainternmed.2013.232 \|journal=JAMA Internal Medicine \|language=en \|volume=173 \|issue=10 \|pages=903–908 \|doi=10.1001/jamainternmed.2013.232 \|issn=2168-6106}}</ref> focused on laboratory tests that were either frequently ordered or expensive. Different from the above-mentioned study, this intervention was conducted in a tertiary care hospital, and 61 laboratory tests were randomized, with the costs displayed (“active” arm) or not (control arm). The ordering physicians were not actively informed about why fees were displayed. This intervention resulted in a 9.1% reduction of orders in the active arm, while the orders of control tests increased by 5.1%.

			Silvestri ''et al.''<ref>{{Cite journal \|last=Silvestri \|first=Mark T. \|last2=Xu \|first2=Xiao \|last3=Long \|first3=Theodore \|last4=Bongiovanni \|first4=Tasce \|last5=Bernstein \|first5=Steven L. \|last6=Chaudhry \|first6=Sarwat I. \|last7=Silvestri \|first7=Julia I. \|last8=Stolar \|first8=Marilyn \|last9=Greene \|first9=Erich J. \|last10=Dziura \|first10=James D. \|last11=Gross \|first11=Cary P. \|date=2018-08 \|title=Impact of Cost Display on Ordering Patterns for Hospital Laboratory and Imaging Services \|url=http://link.springer.com/10.1007/s11606-018-4495-6 \|journal=Journal of General Internal Medicine \|language=en \|volume=33 \|issue=8 \|pages=1268–1275 \|doi=10.1007/s11606-018-4495-6 \|issn=0884-8734 \|pmc=PMC6082197 \|pmid=29845468}}</ref> conducted a similar study in an academic health system comprising three hospitals. The evaluation of laboratory orders before and after the implementation of cost display for 1,032 laboratory tests revealed decreased likelihoods for patients with orders during the encounter. Even if tests were ordered, the proportion of requests on a given hospital day as well as the number of tests ordered in one day decreased. In addition, in-hospital mortality, which was assessed for patient safety, did not increase in the post-intervention period.

	==References==		==References==

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	==Introduction==		==Introduction==
	[[Laboratory]] tests are fundamental for medical diagnosis, prognosis, and treatment decisions<ref>{{Cite journal \|last=Whiting \|first=Penny \|last2=Toerien \|first2=Merran \|last3=de Salis \|first3=Isabel \|last4=Sterne \|first4=Jonathan A.C. \|last5=Dieppe \|first5=Paul \|last6=Egger \|first6=Matthias \|last7=Fahey \|first7=Tom \|date=2007-10 \|title=A review identifies and classifies reasons for ordering diagnostic tests \|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435607000820 \|journal=Journal of Clinical Epidemiology \|language=en \|volume=60 \|issue=10 \|pages=981–989 \|doi=10.1016/j.jclinepi.2007.01.012}}</ref> and are being ordered in rising numbers each year due to increased availability, mostly based on technological advances.<ref>{{Cite journal \|last=Fryer \|first=Anthony A \|last2=Hanna \|first2=Fahmy W \|date=2009-11 \|title=Managing demand for pathology tests: financial imperative or duty of care? \|url=http://journals.sagepub.com/doi/10.1258/acb.2009.009186 \|journal=Annals of Clinical Biochemistry: International Journal of Laboratory Medicine \|language=en \|volume=46 \|issue=6 \|pages=435–437 \|doi=10.1258/acb.2009.009186 \|issn=0004-5632}}</ref> However, due to this fact that laboratory orders increase along with convenient availability, it seems that a certain amount of laboratory tests are ordered inappropriately.<ref>{{Cite journal \|last=Blumberg \|first=Gari \|last2=Kitai \|first2=Eliezer \|last3=Vinker \|first3=Shlomo \|last4=Golan-Cohen \|first4=Avivit \|date=2019-06-01 \|title=Changing electronic formats is associated with changes in number of laboratory tests ordered \|url=https://pubmed.ncbi.nlm.nih.gov/31211550 \|journal=The American Journal of Managed Care \|volume=25 \|issue=6 \|pages=e179–e181 \|issn=1936-2692 \|pmid=31211550}}</ref><ref name=":7">{{Cite journal \|last=Mrazek \|first=Cornelia \|last2=Simundic \|first2=Ana-Maria \|last3=Salinas \|first3=Maria \|last4=von Meyer \|first4=Alexander \|last5=Cornes \|first5=Michael \|last6=Bauçà \|first6=Josep Miquel \|last7=Nybo \|first7=Mads \|last8=Lippi \|first8=Giuseppe \|last9=Haschke-Becher \|first9=Elisabeth \|last10=Keppel \|first10=Martin H. \|last11=Oberkofler \|first11=Hannes \|date=2020-06 \|title=Inappropriate use of laboratory tests: How availability triggers demand – Examples across Europe \|url=https://linkinghub.elsevier.com/retrieve/pii/S0009898120300723 \|journal=Clinica Chimica Acta \|language=en \|volume=505 \|pages=100–107 \|doi=10.1016/j.cca.2020.02.017}}</ref> On the one hand, inappropriate orders may present as overutilization, where tests with doubtful contribution to further patient management are ordered; on the other hand, there may be underutilization, when required tests are not being ordered.<ref name=":0">{{Cite journal \|last=Zhi \|first=Ming \|last2=Ding \|first2=Eric L. \|last3=Theisen-Toupal \|first3=Jesse \|last4=Whelan \|first4=Julia \|last5=Arnaout \|first5=Ramy \|date=2013-11-15 \|editor-last=Szecsi \|editor-first=Pal Bela \|title=The Landscape of Inappropriate Laboratory Testing: A 15-Year Meta-Analysis \|url=https://dx.plos.org/10.1371/journal.pone.0078962 \|journal=PLoS ONE \|language=en \|volume=8 \|issue=11 \|pages=e78962 \|doi=10.1371/journal.pone.0078962 \|issn=1932-6203 \|pmc=PMC3829815 \|pmid=24260139}}</ref> Even if studies estimating over- or underuse are rarely comparable due to differences in study design, it seems that the extent is not negligible. In a systematic review, Zhi ''et al.''<ref name=":0" /> estimated an overall mean rate of overutilization of 20.6%. Subgroup analysis revealed a higher mean rate, around 44%, for inappropriate initial testing. However, single studies state that up to 70% of ordered tests may be of doubtful importance for patient management.<ref>{{Cite journal \|last=Cadamuro \|first=Janne \|last2=Gaksch \|first2=Martin \|last3=Wiedemann \|first3=Helmut \|last4=Lippi \|first4=Giuseppe \|last5=von Meyer \|first5=Alexander \|last6=Pertersmann \|first6=Astrid \|last7=Auer \|first7=Simon \|last8=Mrazek \|first8=Cornelia \|last9=Kipman \|first9=Ulrike \|last10=Felder \|first10=Thomas K. \|last11=Oberkofler \|first11=Hannes \|date=2018-04 \|title=Are laboratory tests always needed? Frequency and causes of laboratory overuse in a hospital setting \|url=https://linkinghub.elsevier.com/retrieve/pii/S0009912017312274 \|journal=Clinical Biochemistry \|language=en \|volume=54 \|pages=85–91 \|doi=10.1016/j.clinbiochem.2018.01.024}}</ref><ref>{{Cite journal \|last=Miyakis \|first=S. \|last2=Karamanof \|first2=G. \|last3=Liontos \|first3=M. \|last4=Mountokalakis \|first4=T. D \|date=2006-12-01 \|title=Factors contributing to inappropriate ordering of tests in an academic medical department and the effect of an educational feedback strategy \|url=https://pmj.bmj.com/lookup/doi/10.1136/pgmj.2006.049551 \|journal=Postgraduate Medical Journal \|language=en \|volume=82 \|issue=974 \|pages=823–829 \|doi=10.1136/pgmj.2006.049551 \|issn=0032-5473 \|pmc=PMC2653931 \|pmid=17148707}}</ref> A workup of closed malpractice claims conducted by Gandhi ''et al.''<ref>{{Cite journal \|last=Gandhi \|first=Tejal K. \|last2=Kachalia \|first2=Allen \|last3=Thomas \|first3=Eric J. \|last4=Puopolo \|first4=Ann Louise \|last5=Yoon \|first5=Catherine \|last6=Brennan \|first6=Troyen A. \|last7=Studdert \|first7=David M. \|date=2006-10-03 \|title=Missed and Delayed Diagnoses in the Ambulatory Setting: A Study of Closed Malpractice Claims \|url=http://annals.org/article.aspx?doi=10.7326/0003-4819-145-7-200610030-00006 \|journal=Annals of Internal Medicine \|language=en \|volume=145 \|issue=7 \|pages=488–96 \|doi=10.7326/0003-4819-145-7-200610030-00006 \|issn=0003-4819}}</ref>, as well as Kachalia ''et al.''<ref>{{Cite journal \|last=Kachalia \|first=Allen \|last2=Gandhi \|first2=Tejal K. \|last3=Puopolo \|first3=Ann Louise \|last4=Yoon \|first4=Catherine \|last5=Thomas \|first5=Eric J. \|last6=Griffey \|first6=Richard \|last7=Brennan \|first7=Troyen A. \|last8=Studdert \|first8=David M. \|date=2007-02 \|title=Missed and delayed diagnoses in the emergency department: a study of closed malpractice claims from 4 liability insurers \|url=https://pubmed.ncbi.nlm.nih.gov/16997424 \|journal=Annals of Emergency Medicine \|volume=49 \|issue=2 \|pages=196–205 \|doi=10.1016/j.annemergmed.2006.06.035 \|issn=1097-6760 \|pmid=16997424}}</ref>, revealed that failure to order the appropriate diagnostic or laboratory test contributed to missed or delayed diagnoses in 55% and 58% of cases in an ambulatory setting and the emergency department, respectively. Zhi ''et al.''<ref name=":0" /> state the overall mean rate of underutilization is 44.8%.		[[Laboratory]] tests are fundamental for medical diagnosis, prognosis, and treatment decisions<ref>{{Cite journal \|last=Whiting \|first=Penny \|last2=Toerien \|first2=Merran \|last3=de Salis \|first3=Isabel \|last4=Sterne \|first4=Jonathan A.C. \|last5=Dieppe \|first5=Paul \|last6=Egger \|first6=Matthias \|last7=Fahey \|first7=Tom \|date=2007-10 \|title=A review identifies and classifies reasons for ordering diagnostic tests \|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435607000820 \|journal=Journal of Clinical Epidemiology \|language=en \|volume=60 \|issue=10 \|pages=981–989 \|doi=10.1016/j.jclinepi.2007.01.012}}</ref> and are being ordered in rising numbers each year due to increased availability, mostly based on technological advances.<ref>{{Cite journal \|last=Fryer \|first=Anthony A \|last2=Hanna \|first2=Fahmy W \|date=2009-11 \|title=Managing demand for pathology tests: financial imperative or duty of care? \|url=http://journals.sagepub.com/doi/10.1258/acb.2009.009186 \|journal=Annals of Clinical Biochemistry: International Journal of Laboratory Medicine \|language=en \|volume=46 \|issue=6 \|pages=435–437 \|doi=10.1258/acb.2009.009186 \|issn=0004-5632}}</ref> However, due to this fact that laboratory orders increase along with convenient availability, it seems that a certain amount of laboratory tests are ordered inappropriately.<ref name=":10">{{Cite journal \|last=Blumberg \|first=Gari \|last2=Kitai \|first2=Eliezer \|last3=Vinker \|first3=Shlomo \|last4=Golan-Cohen \|first4=Avivit \|date=2019-06-01 \|title=Changing electronic formats is associated with changes in number of laboratory tests ordered \|url=https://pubmed.ncbi.nlm.nih.gov/31211550 \|journal=The American Journal of Managed Care \|volume=25 \|issue=6 \|pages=e179–e181 \|issn=1936-2692 \|pmid=31211550}}</ref><ref name=":7">{{Cite journal \|last=Mrazek \|first=Cornelia \|last2=Simundic \|first2=Ana-Maria \|last3=Salinas \|first3=Maria \|last4=von Meyer \|first4=Alexander \|last5=Cornes \|first5=Michael \|last6=Bauçà \|first6=Josep Miquel \|last7=Nybo \|first7=Mads \|last8=Lippi \|first8=Giuseppe \|last9=Haschke-Becher \|first9=Elisabeth \|last10=Keppel \|first10=Martin H. \|last11=Oberkofler \|first11=Hannes \|date=2020-06 \|title=Inappropriate use of laboratory tests: How availability triggers demand – Examples across Europe \|url=https://linkinghub.elsevier.com/retrieve/pii/S0009898120300723 \|journal=Clinica Chimica Acta \|language=en \|volume=505 \|pages=100–107 \|doi=10.1016/j.cca.2020.02.017}}</ref> On the one hand, inappropriate orders may present as overutilization, where tests with doubtful contribution to further patient management are ordered; on the other hand, there may be underutilization, when required tests are not being ordered.<ref name=":0">{{Cite journal \|last=Zhi \|first=Ming \|last2=Ding \|first2=Eric L. \|last3=Theisen-Toupal \|first3=Jesse \|last4=Whelan \|first4=Julia \|last5=Arnaout \|first5=Ramy \|date=2013-11-15 \|editor-last=Szecsi \|editor-first=Pal Bela \|title=The Landscape of Inappropriate Laboratory Testing: A 15-Year Meta-Analysis \|url=https://dx.plos.org/10.1371/journal.pone.0078962 \|journal=PLoS ONE \|language=en \|volume=8 \|issue=11 \|pages=e78962 \|doi=10.1371/journal.pone.0078962 \|issn=1932-6203 \|pmc=PMC3829815 \|pmid=24260139}}</ref> Even if studies estimating over- or underuse are rarely comparable due to differences in study design, it seems that the extent is not negligible. In a systematic review, Zhi ''et al.''<ref name=":0" /> estimated an overall mean rate of overutilization of 20.6%. Subgroup analysis revealed a higher mean rate, around 44%, for inappropriate initial testing. However, single studies state that up to 70% of ordered tests may be of doubtful importance for patient management.<ref>{{Cite journal \|last=Cadamuro \|first=Janne \|last2=Gaksch \|first2=Martin \|last3=Wiedemann \|first3=Helmut \|last4=Lippi \|first4=Giuseppe \|last5=von Meyer \|first5=Alexander \|last6=Pertersmann \|first6=Astrid \|last7=Auer \|first7=Simon \|last8=Mrazek \|first8=Cornelia \|last9=Kipman \|first9=Ulrike \|last10=Felder \|first10=Thomas K. \|last11=Oberkofler \|first11=Hannes \|date=2018-04 \|title=Are laboratory tests always needed? Frequency and causes of laboratory overuse in a hospital setting \|url=https://linkinghub.elsevier.com/retrieve/pii/S0009912017312274 \|journal=Clinical Biochemistry \|language=en \|volume=54 \|pages=85–91 \|doi=10.1016/j.clinbiochem.2018.01.024}}</ref><ref>{{Cite journal \|last=Miyakis \|first=S. \|last2=Karamanof \|first2=G. \|last3=Liontos \|first3=M. \|last4=Mountokalakis \|first4=T. D \|date=2006-12-01 \|title=Factors contributing to inappropriate ordering of tests in an academic medical department and the effect of an educational feedback strategy \|url=https://pmj.bmj.com/lookup/doi/10.1136/pgmj.2006.049551 \|journal=Postgraduate Medical Journal \|language=en \|volume=82 \|issue=974 \|pages=823–829 \|doi=10.1136/pgmj.2006.049551 \|issn=0032-5473 \|pmc=PMC2653931 \|pmid=17148707}}</ref> A workup of closed malpractice claims conducted by Gandhi ''et al.''<ref>{{Cite journal \|last=Gandhi \|first=Tejal K. \|last2=Kachalia \|first2=Allen \|last3=Thomas \|first3=Eric J. \|last4=Puopolo \|first4=Ann Louise \|last5=Yoon \|first5=Catherine \|last6=Brennan \|first6=Troyen A. \|last7=Studdert \|first7=David M. \|date=2006-10-03 \|title=Missed and Delayed Diagnoses in the Ambulatory Setting: A Study of Closed Malpractice Claims \|url=http://annals.org/article.aspx?doi=10.7326/0003-4819-145-7-200610030-00006 \|journal=Annals of Internal Medicine \|language=en \|volume=145 \|issue=7 \|pages=488–96 \|doi=10.7326/0003-4819-145-7-200610030-00006 \|issn=0003-4819}}</ref>, as well as Kachalia ''et al.''<ref>{{Cite journal \|last=Kachalia \|first=Allen \|last2=Gandhi \|first2=Tejal K. \|last3=Puopolo \|first3=Ann Louise \|last4=Yoon \|first4=Catherine \|last5=Thomas \|first5=Eric J. \|last6=Griffey \|first6=Richard \|last7=Brennan \|first7=Troyen A. \|last8=Studdert \|first8=David M. \|date=2007-02 \|title=Missed and delayed diagnoses in the emergency department: a study of closed malpractice claims from 4 liability insurers \|url=https://pubmed.ncbi.nlm.nih.gov/16997424 \|journal=Annals of Emergency Medicine \|volume=49 \|issue=2 \|pages=196–205 \|doi=10.1016/j.annemergmed.2006.06.035 \|issn=1097-6760 \|pmid=16997424}}</ref>, revealed that failure to order the appropriate diagnostic or laboratory test contributed to missed or delayed diagnoses in 55% and 58% of cases in an ambulatory setting and the emergency department, respectively. Zhi ''et al.''<ref name=":0" /> state the overall mean rate of underutilization is 44.8%.

	Along with Sarkar ''et al.''<ref>{{Cite journal \|last=Sarkar \|first=Mayukh K. \|last2=Botz \|first2=Chad M. \|last3=Laposata \|first3=Michael \|date=2017-03-01 \|title=An assessment of overutilization and underutilization of laboratory tests by expert physicians in the evaluation of patients for bleeding and thrombotic disorders in clinical context and in real time \|url=https://pubmed.ncbi.nlm.nih.gov/29536907 \|journal=Diagnosis (Berlin, Germany) \|volume=4 \|issue=1 \|pages=21–26 \|doi=10.1515/dx-2016-0042 \|issn=2194-802X \|pmid=29536907}}</ref>, who support the high proportions of errors in test selection by evaluating orders for coagulation disorders in real time, inappropriate ordering may be considered a substantial threat to patient safety. Overutilization may lead to unnecessary follow-up investigations or treatments, increased workload and costs, and increased patient anxiety, while underutilization may result in missed or delayed diagnoses.<ref name=":0" /><ref>{{Cite journal \|last=Cornes \|first=Michael \|date=2017-06-15 \|title=Case report of unexplained hypocalcaemia in a slightly haemolysed sample \|url=http://www.biochemia-medica.com/en/journal/27/2/10.11613/BM.2017.046 \|journal=Biochemia Medica \|language=en \|volume=27 \|issue=2 \|pages=426–429 \|doi=10.11613/BM.2017.046 \|issn=1330-0962 \|pmc=PMC5493164 \|pmid=28694734}}</ref><ref name=":1">{{Cite journal \|last=Whiting \|first=Darunee \|last2=Croker \|first2=Richard \|last3=Watson \|first3=Jessica \|last4=Brogan \|first4=Andy \|last5=Walker \|first5=Alex J \|last6=Lewis \|first6=Tom \|date=2019-03 \|title=Optimising laboratory monitoring of chronic conditions in primary care: a quality improvement framework \|url=https://qir.bmj.com/lookup/doi/10.1136/bmjoq-2018-000349 \|journal=BMJ Open Quality \|language=en \|volume=8 \|issue=1 \|pages=e000349 \|doi=10.1136/bmjoq-2018-000349 \|issn=2399-6641 \|pmc=PMC6440689 \|pmid=30997410}}</ref> Lack of knowledge, insecurity, pure habit, patient pressure, or fear of lawsuits are possible causes for inappropriate testing.<ref>{{Cite journal \|last=Vrijsen \|first=B.E.L. \|last2=Naaktgeboren \|first2=C.A. \|last3=Vos \|first3=L.M. \|last4=van Solinge \|first4=W.W. \|last5=Kaasjager \|first5=H.A.H. \|last6=ten Berg \|first6=M.J. \|date=2020-03 \|title=Inappropriate laboratory testing in internal medicine inpatients: Prevalence, causes and interventions \|url=https://linkinghub.elsevier.com/retrieve/pii/S2049080120300157 \|journal=Annals of Medicine and Surgery \|language=en \|volume=51 \|pages=48–53 \|doi=10.1016/j.amsu.2020.02.002 \|pmc=PMC7021522 \|pmid=32082564}}</ref><ref name=":2">{{Cite journal \|last=Bartlett \|first=Kristen J \|last2=Vo \|first2=Ann P \|last3=Rueckert \|first3=Justin \|last4=Wojewoda \|first4=Christina \|last5=Steckel \|first5=Elizabeth H \|last6=Stinnett-Donnelly \|first6=Justin \|last7=Repp \|first7=Allen B \|date=2020-02 \|title=Promoting appropriate utilisation of laboratory tests for inflammation at an academic medical centre \|url=https://qir.bmj.com/lookup/doi/10.1136/bmjoq-2019-000788 \|journal=BMJ Open Quality \|language=en \|volume=9 \|issue=1 \|pages=e000788 \|doi=10.1136/bmjoq-2019-000788 \|issn=2399-6641 \|pmc=PMC7047503 \|pmid=32098777}}</ref><ref>{{Cite journal \|last=Morgan \|first=Simon \|last2=Morgan \|first2=Andy \|last3=Kerr \|first3=Rohan \|last4=Tapley \|first4=Amanda \|last5=Magin \|first5=Parker \|date=2016-09 \|title=Test ordering by GP trainees: Effects of an educational intervention on attitudes and intended practice \|url=https://pubmed.ncbi.nlm.nih.gov/27629671 \|journal=Canadian Family Physician Medecin De Famille Canadien \|volume=62 \|issue=9 \|pages=733–741 \|issn=1715-5258 \|pmc=5023346 \|pmid=27629671}}</ref> The lack of knowledge is reflected by various studies, which observed inappropriate orders despite available guidelines or recommendations on the implementation of [[demand management]] (DM) tools.<ref name=":1" /><ref name=":2" /><ref name=":3">{{Cite journal \|last=Juskewitch \|first=Justin E. \|last2=Norgan \|first2=Andrew P. \|last3=Johnson \|first3=Ryan D. \|last4=Trivedi \|first4=Vipul A. \|last5=Hanson \|first5=Curtis A. \|last6=Block \|first6=Darci R. \|date=2019-04 \|title=Impact of an electronic decision support rule on ESR/CRP co-ordering rates in a community health system and projected impact in the tertiary care setting and a commercially insured population \|url=https://linkinghub.elsevier.com/retrieve/pii/S0009912018311652 \|journal=Clinical Biochemistry \|language=en \|volume=66 \|pages=13–20 \|doi=10.1016/j.clinbiochem.2019.01.009}}</ref><ref name=":4">{{Cite journal \|last=Larochelle \|first=Marc R. \|last2=Knight \|first2=Amy M. \|last3=Pantle \|first3=Hardin \|last4=Riedel \|first4=Stefan \|last5=Trost \|first5=Jeffrey C. \|date=2014-11 \|title=Reducing Excess Cardiac Biomarker Testing at an Academic Medical Center \|url=http://link.springer.com/10.1007/s11606-014-2919-5 \|journal=Journal of General Internal Medicine \|language=en \|volume=29 \|issue=11 \|pages=1468–1474 \|doi=10.1007/s11606-014-2919-5 \|issn=0884-8734 \|pmc=PMC4238205 \|pmid=24973056}}</ref><ref name=":5">{{Cite journal \|last=Taher \|first=Jennifer \|last2=Beriault \|first2=Daniel R. \|last3=Yip \|first3=Drake \|last4=Tahir \|first4=Shafqat \|last5=Hicks \|first5=Lisa K. \|last6=Gilmour \|first6=Julie A. \|date=2020-07 \|title=Reducing free thyroid hormone testing through multiple Plan-Do-Study-Act cycles \|url=https://linkinghub.elsevier.com/retrieve/pii/S0009912020303106 \|journal=Clinical Biochemistry \|language=en \|volume=81 \|pages=41–46 \|doi=10.1016/j.clinbiochem.2020.05.004}}</ref>		Along with Sarkar ''et al.''<ref>{{Cite journal \|last=Sarkar \|first=Mayukh K. \|last2=Botz \|first2=Chad M. \|last3=Laposata \|first3=Michael \|date=2017-03-01 \|title=An assessment of overutilization and underutilization of laboratory tests by expert physicians in the evaluation of patients for bleeding and thrombotic disorders in clinical context and in real time \|url=https://pubmed.ncbi.nlm.nih.gov/29536907 \|journal=Diagnosis (Berlin, Germany) \|volume=4 \|issue=1 \|pages=21–26 \|doi=10.1515/dx-2016-0042 \|issn=2194-802X \|pmid=29536907}}</ref>, who support the high proportions of errors in test selection by evaluating orders for coagulation disorders in real time, inappropriate ordering may be considered a substantial threat to patient safety. Overutilization may lead to unnecessary follow-up investigations or treatments, increased workload and costs, and increased patient anxiety, while underutilization may result in missed or delayed diagnoses.<ref name=":0" /><ref>{{Cite journal \|last=Cornes \|first=Michael \|date=2017-06-15 \|title=Case report of unexplained hypocalcaemia in a slightly haemolysed sample \|url=http://www.biochemia-medica.com/en/journal/27/2/10.11613/BM.2017.046 \|journal=Biochemia Medica \|language=en \|volume=27 \|issue=2 \|pages=426–429 \|doi=10.11613/BM.2017.046 \|issn=1330-0962 \|pmc=PMC5493164 \|pmid=28694734}}</ref><ref name=":1">{{Cite journal \|last=Whiting \|first=Darunee \|last2=Croker \|first2=Richard \|last3=Watson \|first3=Jessica \|last4=Brogan \|first4=Andy \|last5=Walker \|first5=Alex J \|last6=Lewis \|first6=Tom \|date=2019-03 \|title=Optimising laboratory monitoring of chronic conditions in primary care: a quality improvement framework \|url=https://qir.bmj.com/lookup/doi/10.1136/bmjoq-2018-000349 \|journal=BMJ Open Quality \|language=en \|volume=8 \|issue=1 \|pages=e000349 \|doi=10.1136/bmjoq-2018-000349 \|issn=2399-6641 \|pmc=PMC6440689 \|pmid=30997410}}</ref> Lack of knowledge, insecurity, pure habit, patient pressure, or fear of lawsuits are possible causes for inappropriate testing.<ref>{{Cite journal \|last=Vrijsen \|first=B.E.L. \|last2=Naaktgeboren \|first2=C.A. \|last3=Vos \|first3=L.M. \|last4=van Solinge \|first4=W.W. \|last5=Kaasjager \|first5=H.A.H. \|last6=ten Berg \|first6=M.J. \|date=2020-03 \|title=Inappropriate laboratory testing in internal medicine inpatients: Prevalence, causes and interventions \|url=https://linkinghub.elsevier.com/retrieve/pii/S2049080120300157 \|journal=Annals of Medicine and Surgery \|language=en \|volume=51 \|pages=48–53 \|doi=10.1016/j.amsu.2020.02.002 \|pmc=PMC7021522 \|pmid=32082564}}</ref><ref name=":2">{{Cite journal \|last=Bartlett \|first=Kristen J \|last2=Vo \|first2=Ann P \|last3=Rueckert \|first3=Justin \|last4=Wojewoda \|first4=Christina \|last5=Steckel \|first5=Elizabeth H \|last6=Stinnett-Donnelly \|first6=Justin \|last7=Repp \|first7=Allen B \|date=2020-02 \|title=Promoting appropriate utilisation of laboratory tests for inflammation at an academic medical centre \|url=https://qir.bmj.com/lookup/doi/10.1136/bmjoq-2019-000788 \|journal=BMJ Open Quality \|language=en \|volume=9 \|issue=1 \|pages=e000788 \|doi=10.1136/bmjoq-2019-000788 \|issn=2399-6641 \|pmc=PMC7047503 \|pmid=32098777}}</ref><ref>{{Cite journal \|last=Morgan \|first=Simon \|last2=Morgan \|first2=Andy \|last3=Kerr \|first3=Rohan \|last4=Tapley \|first4=Amanda \|last5=Magin \|first5=Parker \|date=2016-09 \|title=Test ordering by GP trainees: Effects of an educational intervention on attitudes and intended practice \|url=https://pubmed.ncbi.nlm.nih.gov/27629671 \|journal=Canadian Family Physician Medecin De Famille Canadien \|volume=62 \|issue=9 \|pages=733–741 \|issn=1715-5258 \|pmc=5023346 \|pmid=27629671}}</ref> The lack of knowledge is reflected by various studies, which observed inappropriate orders despite available guidelines or recommendations on the implementation of [[demand management]] (DM) tools.<ref name=":1" /><ref name=":2" /><ref name=":3">{{Cite journal \|last=Juskewitch \|first=Justin E. \|last2=Norgan \|first2=Andrew P. \|last3=Johnson \|first3=Ryan D. \|last4=Trivedi \|first4=Vipul A. \|last5=Hanson \|first5=Curtis A. \|last6=Block \|first6=Darci R. \|date=2019-04 \|title=Impact of an electronic decision support rule on ESR/CRP co-ordering rates in a community health system and projected impact in the tertiary care setting and a commercially insured population \|url=https://linkinghub.elsevier.com/retrieve/pii/S0009912018311652 \|journal=Clinical Biochemistry \|language=en \|volume=66 \|pages=13–20 \|doi=10.1016/j.clinbiochem.2019.01.009}}</ref><ref name=":4">{{Cite journal \|last=Larochelle \|first=Marc R. \|last2=Knight \|first2=Amy M. \|last3=Pantle \|first3=Hardin \|last4=Riedel \|first4=Stefan \|last5=Trost \|first5=Jeffrey C. \|date=2014-11 \|title=Reducing Excess Cardiac Biomarker Testing at an Academic Medical Center \|url=http://link.springer.com/10.1007/s11606-014-2919-5 \|journal=Journal of General Internal Medicine \|language=en \|volume=29 \|issue=11 \|pages=1468–1474 \|doi=10.1007/s11606-014-2919-5 \|issn=0884-8734 \|pmc=PMC4238205 \|pmid=24973056}}</ref><ref name=":5">{{Cite journal \|last=Taher \|first=Jennifer \|last2=Beriault \|first2=Daniel R. \|last3=Yip \|first3=Drake \|last4=Tahir \|first4=Shafqat \|last5=Hicks \|first5=Lisa K. \|last6=Gilmour \|first6=Julie A. \|date=2020-07 \|title=Reducing free thyroid hormone testing through multiple Plan-Do-Study-Act cycles \|url=https://linkinghub.elsevier.com/retrieve/pii/S0009912020303106 \|journal=Clinical Biochemistry \|language=en \|volume=81 \|pages=41–46 \|doi=10.1016/j.clinbiochem.2020.05.004}}</ref>
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	===Revision of laboratory ordering forms and profiles===		===Revision of laboratory ordering forms and profiles===
			The position where tests are placed in the order entry system may affect the number of placed orders.<ref name=":10" /> Furthermore, laboratory ordering profiles (LOPs), which are used to order a bundle of defined analytes with one click in the CPOE system, seem to be a source of overutilization; studies show that the number of orders drops after removing tests from such LOPs. An example provided by Michael Cornes describes a reduction of GGT orders of 82% after the test aiming to assess liver function was removed from the LOP.<ref name=":7" /> Keppel ''et al.''<ref>{{Cite journal \|last=Keppel \|first=Martin H. \|last2=Kolbitsch \|first2=Tobias \|last3=Hoppe \|first3=Uta C. \|last4=Auer \|first4=Simon \|last5=Felder \|first5=Thomas K. \|last6=Oberkofler \|first6=Hannes \|last7=Mrazek \|first7=Cornelia \|last8=Haschke-Becher \|first8=Elisabeth \|last9=Cadamuro \|first9=Janne \|date=2020-08-27 \|title=The clinically effective use of cardiac markers by restructuring laboratory profiles at Cardiology wards \|url=https://pubmed.ncbi.nlm.nih.gov/32305953 \|journal=Clinical Chemistry and Laboratory Medicine \|volume=58 \|issue=9 \|pages=1565–1571 \|doi=10.1515/cclm-2019-1229 \|issn=1437-4331 \|pmid=32305953}}</ref> retrospectively evaluated a DM strategy implemented to reduce unnecessary testing of the cardiac markers high-sensitive troponin T (hsTropT) and NT-proBNP. This intervention was conducted in collaboration with clinicians at three wards of the department of Cardiology, Clinic of Internal Medicine II, University Hospital Salzburg. The implementation started in one ward with an educational approach (see the later subsection on "Education"). Later, both cardiac markers were removed from all LOPs of the three wards, along with the distribution of information about the correct use of hsTropT and NT-proBNP in the form of guidelines and oral presentations. Despite the opportunity to order both tests without restrictions in the CPOE system separate from the LOP, monthly orders decreased by 66.1% and 75.8% for hsTropT and NT-proBNP, respectively, on all three wards. These results indicate that LOPs may indeed be a source of overutilization since they are often not used correctly (e.g., for specific indications) but merely for convenience purposes. Regarding patient safety, length of patient stay and 30-day all-cause re-admission rate were evaluated as surrogate markers, without adverse outcomes.

	==References==		==References==

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← Older revision		Revision as of 20:20, 28 October 2021
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	MRIs, which may also be implemented in the form of alerts at the stage of order entry, are discussed in the subsection about minimum retesting intervals.		MRIs, which may also be implemented in the form of alerts at the stage of order entry, are discussed in the subsection about minimum retesting intervals.

	===Hold back orders in the laboratory information system (LIS)===		===Hold back orders in the laboratory information system===
			Informing the ordering provider through alerts at the stage of order entry would be the preferred solution; however, it may not always be possible to reject inappropriate orders in the CPOE system due to technical issues. In these cases, orders may be screened for appropriateness upon arrival in the [[laboratory information system]] (LIS).

			Cadamuro ''et al.'' [23] selected the analysis of anti-PF4/heparin antibodies (HIT-Ab) as the objective for a so-called gatekeeping strategy. This test is used in cases of suspected heparin-induced thrombocytopenia (HIT), type II. However, before ordering the HIT-Ab test, pretest probability may be assessed with the 4T-score. [24] The four questions of this scoring system were incorporated into the CPOE system, and the appropriate answers had to be selected from a drop-down menu as a mandatory part of the HIT-Ab ordering process. Subsequently, the score was calculated automatically within the LIS, and depending on the result, the LIS rejected or submitted the order for testing. In the case of rejection, the ordering physician was informed of the probability of a positive HIT-Ab test being <2% and the possibility to overrule the laboratory’s decision. This intervention resulted in a reduction of HIT-Ab testing of about 50%, without jeopardizing patient safety.

			Mrazek ''et al.'' [4], who aimed to collect cases indicating a relationship between availability and number of ordered tests, described an example, provided by Maria Salinas, where the LIS held back orders, in which at least four tumor markers (TMs) were requested concomitantly. The laboratory specialist then decided upon the appropriateness of the order in synopsis with the patient’s medical record. Samples of inappropriate orders are stored until the order necessity is clarified with the general practitioner. Three years after implementation of this DM strategy, annual requests containing four or five TMs declined by 66%.

			MRIs, which may be considered as a subset of holding back orders, are discussed in the following section.

			===Minimum retesting intervals===
			Minimum retesting intervals (MRIs) are defined as “the minimum time before a test should be repeated, based on the properties of the test and the clinical situation in which it is used.” [25] Recommendations for MRIs are freely available, for example, from the collaboration of the Royal College of Pathologists, the Association for Clinical Biochemistry and Laboratory Medicine, and the Institute of Biomedical Science. [25] MRIs may be implemented in the LIS, dependent on available technical possibilities. Salinas ''et al.'' [26] implemented an MRI in the form of a comment on the laboratory report. In case a ferritin test was re-ordered within three days of the last order for inpatients and three months for outpatients, the LIS rejected the request and stated an explanation in the comment, including the previous ferritin value. The results showed that 3.9% and 12% of requested ferritin were not measured in inpatients and outpatients, respectively.

			A similar approach was used by Mrazek ''et al.'' [27], who implemented an MRI of 60 days for hemoglobin A1c (HbA1c) at one site of a University Hospital (Landeskrankenhaus [LKH]). Inappropriate orders were automatically rejected by the LIS, and an automatically generated comment explained the inappropriateness, stated the date as well as the result of the last HbA1c test and advised calling the laboratory if the analysis was needed in a special situation. This resulted in a decline of HbA1c measurements by 15.8%. After the implementation of the MRI, only 1.1% of ordered HbA1c were measured within 60 days, compared to 15% before the intervention. At another site, the Landesklinik St. Veit (STV), the MRI was implemented by educational measures only (see the later subsection on "Education").

			One drawback of rejecting tests in the LIS is that unnecessary blood collections may be performed for cancelled tests. Therefore, it would be favorable if the requesting physician is at least alerted in the course of order entry. Waldron ''et al.'' [28] implemented an MRI of 48 hours for CRP testing. The ordering provider was alerted, but as blocking the order was not possible at the stage of order entry, the LIS rejected the test and provided an accompanying comment on the report. Requests within the MRI were only possible through direct consultation of a consultant microbiologist. Over one year, CRP requests dropped by 7.0%, and analyzed CRP tests decreased by 12.3%. The results of Larochelle ''et al.'' [17], who implemented a duplicate order pop-up warning for troponin re-orders within six hours as part of a multifaceted approach, are discussed in the next subsection.

			Different outcomes are reported with regard to the reactions to the alert. As was previously mentioned, Lippi ''et al.'' [21] introduced pop-up alerts with the possibility to override the rule for biological implausibility as well as MRIs for 15 different tests at two University Hospital wards. In the observational period of six months, 22% of the orders generated an alert and 77% of these tests were cancelled. Lapić ''et al.'' [29] implemented an MRI for inpatients at a university hospital for 53 tests. The pop-up alert gave information about the inappropriateness, referred to the date as well as the status of the previous test request, and included the possibility to override the warning. In the observational period of one year, 106,780 orders, which accounted for 14.8% of all requests, violated the defined MRIs. The percentage of ignored alerts depended on the tests, but for high-volume tests—including complete blood count, CRP, alanine-aminotransferase (ALT), gamma-glutamyltransferase (GGT), and total bilirubin, which together accounted for 65% of alerts—the alert was ignored in > 85% of cases. Therefore, outcomes may depend on the clinical setting and may not be generalizable.

			Moyer ''et al.'' [30] implemented MRIs for ionized calcium (iCa), magnesium (Mg), and N-terminal pro brain natriuretic peptide (NT-proBNP) for intensive care unit inpatients. The alert at the stage of order entry did not only depend on the MRI, but also on the previous results for iCa and Mg. The iCa alert was triggered if iCa was re-ordered within 24 hours and the previous iCa result was within the reference range. The pop-up alert informed the user about the date and result of the previous order, provided information about clinical situations in which iCa might still be indicated, and left the choice to cancel the request or to continue with the order to the user. In the latter case, an indication for the re-order had to be provided. Comparison of 90-day periods before and after the implementation of this DM strategy revealed a decrease in test numbers of between 28% for NT-proBNP and 48% for iCa. In a six-month period after the implementation, 6,110 alerts were triggered, with the majority for Mg (5,160). Overall, alerts were dismissed in 66% of the cases, again, with the majority for Mg testing (88%). iCa and NT-proBNP were re-ordered only in 5% and 7% of cases, respectively. Regarding patient safety, the authors examined the [[International Statistical Classification of Diseases and Related Health Problems\|International Classification of Diseases Ninth Revision]] (ICD-9) codes, which may be associated with electrolyte disturbances. Despite the decline in electrolyte measurements, no increase of ICD-9 codes was observed.

			Riley ''et al.'' [31] aimed to avoid duplicate genetic testing, as this is generally indicated only once in a patient’s lifetime. If the order has already been performed, the ordering provider was informed about the date of the previous result. Repeated analyses could be ordered by phone only. Evaluation after the intervention revealed that 82% of repeated orders were justified because the previous order yielded no result due to errors in the testing process. The authors mention that they have adjusted the programming according to these results, but this was not included in the study.

			===Revision of laboratory ordering forms and profiles===

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