Laboratory Test Ordering in Inpatient Hospitals: A Scoping Review on the Effects and Features of Clinical Decision Support Systems


 Background: Studies have revealed inappropriate laboratory testing as a source of waste. This review was aimed to evaluate the effects and features of CDSSs on physicians' appropriate laboratory test ordering in inpatient hospitals.Method: Medline through PubMed, SCOPUS, Web of Science, and Cochrane were queried without any time period restriction. The outcomes were categorized based on test-related, physician-related, and patient-related. The primary outcome measures were the number and cost of laboratory test ordered.Result: Sixteen studies met the inclusion criteria. Most studies were conducted based on a quasi-experimental design. The results showed improvement in laboratory test-related outcomes (e.g. proportion and cost of tests) and also physician-related outcomes (e.g. guideline adherence and orders cancellation). Patient-related outcomes (e.g. length of stay and mortality rate) were not well investigated in the included studies. Also, the evidence about applying CDSS as a decision aid for interpreting laboratory results was rare.Conclusion: CDSSs increase appropriate test ordering in hospitals through eliminating redundant test orders and enhancing evidence-based practice. Appropriate testing and cost saving were both affected by the CDSSs. However the evidence is limited about the effects of laboratory test CDSSs on patient-related outcomes.


Background
Laboratory tests results have an important impact on patients care, as they affect many of physicians' decisions including admission, drug orders, and discharge as well as motoring and managing the vast majority of diseases. However, studies indicate that diagnostic tests are being used inappropriately as a meta-analysis result showed that almost 20% of laboratory tests are over-utilized and 45% are under-utilized [1]. A study has indicated that only 1-5% of chemistry tests and 1-3% of hematology tests have led to an action; action in this study meant any alternation from what would have been done without the test result [2]. Moreover, in one study about 70% of residents reported that they are ordering unnecessary daily laboratory tests [3].
Inappropriate test ordering can increase risk of false positive results and medical errors [4]. Overutilization can potentially cause patient discomfort including phlebotomy-induced anemia [5]. Underutilization can also result in delayed or missed diagnosis. Studies found that a vast majority of claims both in outpatients and emergency department belongs to missed diagnosis which resulted in death or serious harm to patients [6,7]. Overcrowded diagnostic services, increased length of stay (LOS), and waste of valuable healthcare resources are amongst other consequences of inappropriate testing [8][9][10].
Conversely it imposes a lot of costs to healthcare as 3% of health care expenditures in the USA belong to laboratory testing [11][12][13].
Information technology [IT] has provided some solutions to decrease inappropriate laboratory tests ordering. Some of these technologies are electronic medical record (EMR) [14], electronic health record (EHR) [15], computerized physician order entry (CPOE) [16], and clinical decision support systems (CDSS) [17]. Among all technologies CDSS has more potential to support physicians when deciding about ordering a test or interpreting the results. However, studies have shown inconsistent results about the impact of CDSSs on physicians' performance and patients outcomes [18,19]. Thus there is a need for a scoping review on the effects of CDSSs on ordering appropriate laboratory tests.
Studies evaluating the impact of CDSSs on diagnostic testing showed no improvement in clinical outcome but small positive improvement on physicians behavior regarding diagnostic test ordering [20,21]. There are two similar systematic reviews focusing on laboratory test ordering speci cally. The rst is Maillet et al. (2018) study [22] which addressed the IT impact on laboratory tests ordering process in primary healthcare. This study did not focus on the effectiveness of CDSSs rather it focused on all speci c IT interventions. It also included the studies conducted in primary healthcare. The second systematic review by Delvaux et al. (2017) [23] included the studies conducted in diverse healthcare settings (i.e. primary healthcare, hospital outpatient, and hospital inpatient). They found that CDSSs had little or no effect on clinical outcomes but some effects on physician compliance rate. Including all studies conducted in inpatient hospitals aiming at improving laboratory testing process as the primary objective, without considering study designs, might produce different results. Thus, the goal of current study was to conduct a scoping review on the effects and features of CDSSs on physicians' appropriate laboratory tests ordering in inpatient hospitals.

Research question
Do CCDSSs improve practitioners' appropriate laboratory test ordering in hospitals?

Search Strategy And Study Selection
A search strategy was developed using keywords, MeSH terms, and major subject headings to identify published papers in the literature and adaptations were made for each database. Four databases were queried: Medline (through PubMed), SCOPUS, Web of Science, and Cochrane. We considered studies published till 21 January 2020 without any time limitation. The search strategy consisted of a combination keywords and Mesh terms related to clinical laboratory services (laboratory test utilization), CDSSs, and hospitals. The search strategy is presented as supplementary (supplementary A). the identi ed papers were also searched to include any other paper missed during the electronic searches. Authors resolved disagreements through discussion and consensus, and any remaining disagreements were resolved by another author (EN).

Inclusion criteria
Type of studies A variety of evaluation study designs were included: randomized controlled trials (RCTs), non-randomized controlled clinical trials (CCTs), prospective observational studies, before-after, and interrupted time series (ITS).

Type of population
The study populations in the included studies were laboratory tests, physicians ordering laboratory tests, or the patients for whom laboratory tests were ordered.

Types of interventions
Studies using CDSSs as an intervention to improve laboratory test ordering as the primary aim were included. In current study a CDSS is considered as a health Information Technology system designed for providing assistance to physicians and other healthcare providers with decision-making tasks. CDSSs can ease access to data required to make decisions, provide reminders and alarms while a patient encounter, assist in recognizing a diagnosis and in entering appropriate orders, and alert healthcare providers when new patterns in patient data are observed [22,24]. In studies with multifaceted interventions, the effects of CDSS intervention were considered independently and in cases which it was not possible to separate the CDSS impact, studies were excluded.

Type of outcomes
Outcome measures include: diagnostic yield and diagnostic detection rate, the number and cost of laboratory test ordered, laboratory turnaround time (TAT), STAT tests, guideline adherence for laboratory test ordering, physicians knowledge and attitude toward laboratory testing, patients outcome (e.g. patients safety, readmissions, death, length of stay and disposition). These outcomes were categorized based on test-related, physician-related, and patient-related groups. Test-related outcomes were proportion of tests, cost of tests, test intervals, number of STAT request, and laboratory TATs. Physician-related outcomes include diagnostic yield and diagnostic detection rate, adherence or order cancellation after the reminders (or overriding the reminders), and physicians knowledge and attitude. Patient-related outcomes were patients' complications, patients' disposition, length of stay (LOS), and mortality rate.

Exclusion criteria
Exclusion criteria were studies published in any language rather than English, conducted in outpatient or primary care settings, used interventions rather than CDSS, conducted in an unreal clinical environment or based on a scenario (in a simulated setting i.e. for test of a system). Moreover, all retrospective studies were excluded.

Quality Assessment
One study was RCT [28], one case-control [39], and the others (n = 14) were quasi experimental studies (appendix B). Most of the included studies (n = 11, 68.7%) were of intermediate quality, the remaining were of good quality. The main limitations of the included studies were not being blinded (93.7% had not blinded assessors) and lack of a clear speci ed description of inclusion and exclusion criteria (43.7%). The results are presented as a supplementary (supplementary B).
Quality assessments of the CDSSs are presented in Table 2. Almost all CDSSs were integrated with CPOEs (93.7%), providing real-time feedback (93.7%) without any recommended action (100%). Most CDSS classi cations of the studies (43.7%) are in C category which required the ordering clinician to justify why they were overriding the provided decision support recommendation (see Table 2 legend). Four studies (25%) were integrated with and automated through EHR. Eight studies (50%) reported that they tested CDS before implementation. Only two studies (12.5%) reported user training about the intervention; in other cases the provided educations were about the targeted tests indication or similar things. Other characteristics, barriers, and facilitators affecting implementation of CDSS were: role of order sets, "adjustment" period, stakeholder and champion leaders engagement, appropriate environment, ease of repeating targeted tests, testing options constrains, paradoxical prompting generated by CDSS, and daily orders which would not trigger the audits.  *Intervention Classi cation: "A" interventions provided information only; "B" interventions presented information on appropriateness or guidelines speci cally often as a pop-up or alert. Some of these interventions also recommended alternative interventions, but did not include any barrier for the clinician to order th were similar to "B" interventions, but required the ordering clinician to justify with free text why they were overriding the decision support recommendation tha "soft stop"). "D" interventions included a "hard stop," meaning the intervention prevented the clinician from ordering a test contrary to the CDS determination o discussion with or permission obtained from another clinician or pathologist.

** Not Mentioned
CDSS interventions were mostly in the form of a reminder about duplicate tests in a speci c timeframe, rule-bases providing knowledge about when it is appropriate to order the speci ed test, or prede ned appropriateness criteria physicians had to determine before ordering the tests. These interventions support physicians' informed decision-making in the rst step of testing process when they are deciding about ordering a test.

Data Extraction
We designed a form to extract data from each of the included studies. For each study the following data were extracted: study design, sample size, intervention description, and results. One author (SZ) extracted data which were subsequently reviewed and con rmed by another reviewer (EN).
A narrative synthesis was used to describe and compare the designs and the results of included studies. We categorized studies based on different features of CDSSs, outcome category, and effects of CDSSs. The effect of interventions were reported based on statistically signi cant positive, positive without statistical argument, no effect (not statistically signi cant), negative without statistical argument, or statistically signi cant negative [27]. Meta-analysis was not performed due to the variety of outcomes and results.

Results
Study selection (Fig. 1) The literature search identi ed 2784 records, as well as two additional papers [28,29] identi ed through other sources (snowball-search), 739 of which were duplicates. The papers were screened for eligibility by title and abstract, resulting in 74 potential papers for the full-text review. During the full-text reviewing 58 papers were excluded. Finally, 16 studies were deemed eligible for inclusion. Most of the included studies were conducted in the United States (n = 12, 75%); and one was conducted in each of the following countries: Canada [30], United Kingdom [31], Italy [32], and France [33].   The included studies had mostly investigated laboratory test-related outcomes. Generally, CDSS interventions showed positive effects on all outcomes.

Laboratory Test-related Outcomes
Appropriate testing and cost saving were both affected by the CDSSs and it is consistent with a similar systematic review on outpatient setting [22]. It is also consistent with a narrative review by Bindraban et al. [48] which showed nearly all interventions in educational, CPOE, and audit and feedback category caused reduction in test order volume. Roshanov et al. systematic review [20] also indicated that those systems aimed at reducing test ordering rate had positive impact. However the results are inconsistent with Delvaux and colleague systematic review. They found that CDSSs designed to change laboratory testing behavior for diabetes, HIV, and anticoagulation had little or no in uence on clinical outcome. Our study included studies aimed at improving laboratory testing process as the primary aim. However most studies included by Delvaux et al., as mentioned in Introduction section, had different objective for instance computer-aided dosing and further they evaluated its impact on diagnostic testing. Thus it seems CDSSs speci cally designed to affect laboratory tests are more in uential. Eaton et al. [36] showed that CDSSs might be effective for some tests and ineffective for some others. There was only one study [42] that found a negative impact in magnesium ordering attributed to CDSS. The CDSS was supposed to regulate magnesium ordering; they developed a CDSS in a way that three tests (i.e. magnesium, calcium, and phosphorus) could be ordered from one user interface of CPOE. This may have caused an unintentional prompt to order these tests together without original plan. Decreasing cost of tests was approved in several studies [28,30,32,34,37,38,41]. But it is important to mention that quality of the studies were fair and results were not analyzed statistically. Thus the conclusion about cost reduction sounds di cult.
Even it is stated that the reported cost reduction is an underestimation of true cost savings since they only assessed consumables costs, and associated resources (i.e. equipment, personnel, test tubes, etc.) should be included in the calculation.

Physician-related Outcomes
Physician-related outcomes were reported in three included studies [28,31,33]. In these studies compliance was measured based on the proportion of

Patient-related Outcomes
The results also indicated that the evidence pertaining to the effects of CDSSs on patient-related outcomes is limited. Overall, CDSSs may make little or no difference to patient outcomes including patient complications, patient disposition, or mortality rate [28,34,39,41]. For instance in Bates et al. [28], study three of the eight urinalysis cancelled tests displayed a few red blood cells, while the previous specimen had been negative. It is inferred from these ndings that cancelling the orders due to a CDSS suggestion, probably lead to no adverse event to patients. Bridges et al. [34] study showed that patients with duplicate tests had higher mortality rate than those without duplicate tests; they also had a worse disposition after discharge, indicating those with redundant tests were generally sicker. Thus, less mortality rate cannot be only attributed to CDSS effect and needs more investigation. Patient experience like decreased phlebotomy and other possible improved outcomes like decreased risk for false-positive test results should be investigated in future studies.

Discussion
Generally, the studies were mostly of moderate methodological quality with only one RCT out of the 16 included studies, and most studies being conducted after 2015. The majority of included studies were addressing the CDSSs effect on laboratory test-related outcomes. The results showed improvement in laboratory test-related and physician-related outcomes. Patient-related outcomes were not well investigated in the included studies.
Most studies were conducted after 2015 suggesting a new research agenda in health information technology. It also indicates that attentions to resource utilization for appropriate utilizing laboratory tests have been increased recently. It might also be attributed to limited resources as well as increased cost of healthcare. Healthcare resource utilization and costs by different diseases shows a high economic burden highlighting need for taking some actions for decreasing costs [45][46][47]. The results of this review showed that CDSSs have the ability to improve laboratory tests utilization in some cases including hepatitis B virus, Clostridium Di cile, magnesium, B-Type natriuric peptide, TFT, ESR, and heparin-induced thrombocytopenia tests.

Strengths And Limitations
A comprehensive search strategy, without any time period restriction, was performed to nd the maximum number of relevant studies. To avoid missing any important ndings, a variety of interventional study designs were included. We assessed the effects of CDSSs not only on proportion of test orders and associated costs but also on physician-related and patient-related clinical outcomes.
A limitation of this review is that due to exclusion of non-English language papers and conference proceedings, some relevant studies might have been missed. Another limitation is the exclusive focus on studies on reducing unnecessary testing as the main outcome. Most studies conducted in this eld were performed using a quasi-experimental design making the conclusion about the impacts di cult due to possible biases.

Implication
Applying a clinical algorithm and hard stop alerts for preventing speci ed tests would result in more reduction in tests volume. CDSSs should be evaluated for speci c laboratory tests to make sure only effective alerts would be displayed [36]. Nonetheless, allowing overrides may be effective for clinicians' acceptance of the system. Nonintrusive alerts should be evaluated to make sure only effective alerts continue to be displayed so as to prevent rising alert fatigue [36]. Alert fatigue causes both important and non-important alerts to be overridden by clinicians. Thus, considering a balance between system exibility and hard-stop alerts is important in designing a CDSS. It is suggested that the intervention must be sustainable through providing awareness to the changes, which will bring about better compliance. Impact on physician-related outcomes can be promoted over time, since physicians possibly experience an "adjustment" period at the beginning of the intervention so they need time to become familiar with the intervention [34]. Although physicians' attitude and requirements are important factors contributing in more acceptances and perceived usefulness of CDSS, less attention has been paid to them. It has been shown that simple static rules had higher compliance rates than complicated dynamic rules [31]. CDSSs design should not allow two or more tests to be ordered from a single interface, because it may contribute in unintentional prompt to order those tests together and increase tests ordering.

Future Research Directions
Since most studies were conducted after 2015, indicating a new research agenda, there is a need for more studies investigating effective information technology-based approaches to manage health resources utilization. Moreover, considering the majority of the studies were performed using a quasiexperimental design, there is an essential need for further studies with more robust study designs. Also, to make sure about the effects of CDSSs on test interval, STAT tests, and TAT, further studies are needed. According to the lack of evidence on potential negative effects resulting from the cancellation of the tests based on CDSS recommendations, future research should evaluate these effects, especially potential harm to patients. Although some physicians need guidance when interpreting some tests [49,50]  Availability of data and material All data are available in the submission.

Competing interest
The authors declare that there are no con icts of interest

Funding
No funding is received for this research.
Authors' contribution EN and ZM directed the study. SZ MS contributed in reading the articles for relevance and disagreements were solved by EN. SZ extracted the information of the included studies. SZ and EN have drafted the manuscript. All the authors have read and approve the manuscript. Figure 1