Inappropriate use of laboratory tests: How availability triggers demand – Examples across Europe

Mrazek, Cornelia; Šimundić, Ana-Maria; Salinas, María; Meyer, Alexander; Cornes, Michael; Bauçà, Josep Miquel; Nybo, Mads; Lippi, Giuseppe; Haschke-Becher, Elisabeth; Keppel, Martin H.; Oberkofler, Hannes; Felder, Thomas K.; Cadamuro, Janne

doi:10.1016/j.cca.2020.02.017

Cited by 28 publications

(12 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…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.…”

Section: Possible Strategies To Avoid Inappropriate Test Utilizationmentioning

confidence: 99%

“…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 [ 4 ]. Keppel et al [ 32 ] retrospectively evaluated a DM strategy implemented to reduce unnecessary testing of the cardiac markers high-sensitive troponin T (hsTropT) and NT-proBNP.…”

Section: Possible Strategies To Avoid Inappropriate Test Utilizationmentioning

confidence: 99%

“…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 [ 4 ], 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 [ 35 ].…”

Section: Possible Strategies To Avoid Inappropriate Test Utilizationmentioning

confidence: 99%

“…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 ].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Laboratory Demand Management Strategies—An Overview

et al. 2021

Self Cite

View full text Add to dashboard Cite

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 as well as clinicians that demand management 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 demand management strategies that may be adopted to local settings. We believe that artificial intelligence may help to further improve these available tools.

show abstract

Section: Possible Strategies To Avoid Inappropriate Test Utilizationmentioning

confidence: 99%

Section: Possible Strategies To Avoid Inappropriate Test Utilizationmentioning

confidence: 99%

Section: Possible Strategies To Avoid Inappropriate Test Utilizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Laboratory Demand Management Strategies—An Overview

et al. 2021

Self Cite

View full text Add to dashboard Cite

show abstract

“…Inadequate knowledge of laboratory tests, availability of higher numbers of new tests, fear of diagnostic errors, and lack of education have been found to be associated with inappropriate laboratory testing [12,13]. Several factors also increased the rate of inappropriate laboratory testing, such as increasing patient satisfaction, fear of liability, and fee-for-service billing [10,14]. Existing strategies to reduce inappropriate tests and improve the efficiency of ordering clinical laboratory tests include feedback and reminder [15,16], clinical decision support tools [17], education [18], cost display [19], practice guidelines [20], and condition-specific algorithms [21].…”

Section: Introductionmentioning

confidence: 99%

Deep into Laboratory: An Artificial Intelligence Approach to Recommend Laboratory Tests

et al. 2021

View full text Add to dashboard Cite

Laboratory tests are performed to make effective clinical decisions. However, inappropriate laboratory test ordering hampers patient care and increases financial burden for healthcare. An automated laboratory test recommendation system can provide rapid and appropriate test selection, potentially improving the workflow to help physicians spend more time treating patients. The main objective of this study was to develop a deep learning-based automated system to recommend appropriate laboratory tests. A retrospective data collection was performed at the National Health Insurance database between 1 January 2013, and 31 December 2013. We included all prescriptions that had at least one laboratory test. A total of 1,463,837 prescriptions from 530,050 unique patients was included in our study. Of these patients, 296,541 were women (55.95%), the range of age was between 1 and 107 years. The deep learning (DL) model achieved a higher area under the receiver operating characteristics curve (AUROC micro = 0.98, and AUROC macro = 0.94). The findings of this study show that the DL model can accurately and efficiently identify laboratory tests. This model can be integrated into existing workflows to reduce under- and over-utilization problems.

show abstract

Influenza molecular diagnostic testing in a 1000-bed academic Italian hospital during the 2018–19 influenza season

Valent

Malacarne

Licata

et al. 2020

J Public Health (Berl.)

View full text Add to dashboard Cite

Aim The aims of this study were to examine the requests for influenza molecular tests processed by the Virology Laboratory of the University Hospital of Udine during the 2018-19 influenza season and to assess the test results and to estimate costs. Subjects and methods We analyzed various administrative databases of the hospital health information system, which can be deterministically linked at the individual level through an anonymous stochastic key. Requests for influenza molecular tests from November 1, 2018, to April 15, 2019, and test results were described by week and, for hospitalized patients, hospital ward. Previous vaccination status of tested patients, outcomes and estimated test costs were assessed. Results In the 2018-19 influenza season, 979 influenza A and B virologic tests were processed by the laboratory, corresponding to 758 patients. Requests had more than doubled compared with the previous influenza season. Rapid real-time PCR tests, routinely available at the University Hospital of Udine since January 2019, represented 17% of requests. Six hundred forty-eight patients were hospitalized. Medical wards requested the test after a median of 1 day after admission, whereas requests were delayed for surgical and oncologic patients. The number of tests, proportion of positivity and consumption of rapid tests varied by medical specialty. Overall consumption of oseltamivir was similar to that of the previous influenza season. Conclusions This analysis, benefiting from the availability of integrated health administrative databases, provided useful information to support public health decision-making and managing the supply and demand for diagnostic tests.

show abstract

Inappropriate use of laboratory tests: How availability triggers demand – Examples across Europe

Cited by 28 publications

References 38 publications

Laboratory Demand Management Strategies—An Overview

Laboratory Demand Management Strategies—An Overview

Deep into Laboratory: An Artificial Intelligence Approach to Recommend Laboratory Tests

Influenza molecular diagnostic testing in a 1000-bed academic Italian hospital during the 2018–19 influenza season

Contact Info

Product

Resources

About