Journal:Laboratory demand management strategies: An overview

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Full article title Laboratory demand management strategies: An overview
Journal Diagnostics
Author(s) Mrazek, Cornelia; Haschke-Becher, Elisabeth; Felder, Thomas K.; Keppel, Martin H.; Oberkofler, Hannes; Cadamuro, Janne
Author affiliation(s) Paracelsus Medical University
Primary contact Email: c dot mrazek at salk dot at
Year published 2021
Volume and issue 11(7)
Article # 1141
DOI 10.3390/diagnostics11071141
ISSN 2075-4418
Distribution license Creative Commons Attribution 4.0 International
Website https://www.mdpi.com/2075-4418/11/7/1141/htm
Download https://www.mdpi.com/2075-4418/11/7/1141/pdf (PDF)

Abstract

Inappropriate laboratory test selection in the form of overutilization as well as underutilization, frequently occurs despite available guidelines. There is broad approval among laboratory specialists and clinicians that demand management (DM) strategies are useful tools to avoid this issue. Most of these tools are based on automated algorithms or other types of machine learning. This review summarizes the available DM strategies that may be adopted to local settings. We believe that artificial intelligence (AI) may help to further improve these available tools.

Keywords: appropriate laboratory test ordering overutilization, pre-analytical phase, underutilization

Introduction

Laboratory tests are fundamental for medical diagnosis, prognosis, and treatment decisions[1] and are being ordered in rising numbers each year due to increased availability, mostly based on technological advances.[2] 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.[3][4] 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.[5] 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.[5] 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.[6][7] A workup of closed malpractice claims conducted by Gandhi et al.[8], as well as Kachalia et al.[9], 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.[5] state the overall mean rate of underutilization is 44.8%.

Along with Sarkar et al.[10], 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.[5][11][12] Lack of knowledge, insecurity, pure habit, patient pressure, or fear of lawsuits are possible causes for inappropriate testing.[13][14][15] 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.[12][14][16][17][18]

This review summarizes available DM strategies, which may be implemented into local settings to reduce inappropriate test utilization.

Possible strategies to avoid inappropriate test utilization

DM tools may help to prevent overutilization and underutilization. An attempt to categorize the different DM strategies as appropriate tools to overcome over- and underutilization is depicted in Figure 1.


Fig1 Mrazek Diagnostics21 11-7.png

Figure 1. Categorization of DM strategies: Stratification of whether DM tools prevent overutilization and underutilization. LOP = laboratory ordering profile.

Many studies combine several tools[14][17][19], which has been shown to have an additive effect on the overall outcome.[20] In addition, the collaboration of laboratory specialists and clinicians together with audits, feedback, reminders, and multiple plan-do-study-act (PDSA) cycles will further improve efficiency in terms of a continuous improvement process.[12][14][18][19]

Alerts at the stage of order entry

Alerts appearing in the form of pop-up windows in the clinical physician order entry (CPOE) system may be designed to avoid various causes of overutilization.

Lippi et al.[21] implemented alerts for biological implausibility concerning age (e.g., beta human chorionic gonadotropin in patients < 9 and > 60 years) or gender (e.g., prostatic specific antigen [PSA] in females) at two university hospital wards. In addition, alerts for minimum retesting intervals (MRIs) were implemented (addressed in a further subsection). The alert provides an explanation as to why the order is deemed inappropriate and enables the ordering provider to choose order cancellation or acceptance.

Similarly, Juskewitch et al.[16] implemented an alert, triggered by the concomitant order of erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) in a community health system. Again, the user is informed about the inappropriate request and has the choice to cancel ESR or to proceed with the order. The implementation of this DM strategy resulted in a 42% relative rate reduction of ESR/CRP co-ordering.

Alerts may also help to suggest an alternative test, as Parkhurst et al.[22] showed. The authors reduced genetic testing of methylene tetrahydrofolate reductase (MTHFR) by informing the ordering physician about the latest recommendations of MTHFR testing, including the suggestion of homocysteine as an alternate test. In this study, the choice of overruling or adopting the suggestion was left with the user. Overall, there was a significant decrease of average monthly MTHFR tests from 12.93 per million patients in the year before the intervention to 7.08 per million patients afterwards.

Larochelle et al.[17] aimed to improve ordering of cardiac biomarkers according to guidelines for the diagnosis of acute coronary syndrome (ACS). As part of a multimodal intervention, including education and several changes in the CPOE system (see later subsections), a pop-up alert was introduced, triggered by the order of creatinkinase (CK) and CK-MB isoform (CK-MB), informing the user about the recommended indications for these tests.

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)

References

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Notes

This presentation is faithful to the original, with only a few minor changes to presentation, spelling, and grammar. In some cases important information was missing from the references, and that information was added.