A clinician's perspective on laboratory utilization management

Minimizing unnecessary proBNP blood tests: an evaluation of a pop-up form implementation in general practice

OBJECTIVE

To evaluate the impact of a compulsory pop-up form on the ordering pattern of proBNP blood tests by general practitioners in the Capital Region of Denmark.

DESIGN

A follow-up study comparing the average number of proBNP tests ordered before and after the implementation of an intervention.

SETTING AND SUBJECTS

From 2016 to 2021, the average number of proBNP tests increased by over 300%. In March 2022, a compulsory pop-up form was introduced in the electronic request system (WebReq), requiring general practitioners to select one of three indications for ordering proBNP, as recommended by the Danish Society of Cardiology. The study included 528 general practitioners in the Capital Region of Denmark, with data available from January 2020 to 2023, encompassing 83,576 proBNP results from 56,645 patients.

MAIN OUTCOME MEASURE

The average number of proBNP tests ordered per month and the median level of proBNP before and after the intervention.

RESULTS

Following the intervention, the average number of proBNP tests per month decreased by 60% over a 22-month follow-up period. The highest reduction was seen among general practitioners who previously ordered the most tests (≥3 per 1000 biochemical tests). In this group, the median proBNP level increased from 12.1 pmol/L before the intervention to 13.5 pmol/L after the intervention (p < 0.0001).

CONCLUSIONS

This study demonstrates a significant decrease in the number of proBNP requests from general practitioners in the Capital Region of Denmark after the introduction of a pop-up form in the requisition system containing the current guidelines.

Retrospective analysis of serologic test requests in the diagnosis of viral hepatitis: Inappropriate test requests and cost

The rational laboratory use and implementation of test ordering procedures aim to reduce unnecessary test requests. This study aimed to determine the financial burden caused by inappropriate serological test requests for viral hepatitis and to investigate physicians' reasons for making unnecessary test requests. We performed a retrospective evaluation of inappropriate requests for hepatitis serology testing and the financial burden they caused at a tertiary care hospital over a 1-year period. The study found 2183 (3.84%) inappropriate test requests, costing $3309.00. Of these, 357 were same-day repeat requests and 1826 were requests not following diagnostic algorithms. In the logistic regression analysis of the factors affecting unnecessary test requests, a statistically significant difference was found between whether the unit was internal or surgical, whether the request came from inpatient services or outpatient clinics, and the professional titles (P < .05). Both types of inappropriate requests were more common among male physicians (P < .05). The highest rates of inappropriate test requesting were in physical therapy and rehabilitation, pediatrics, and adult emergency units. To identify the reasons behind unnecessary test requests, 135 physicians from 23 different departments participated in the survey. The main reasons for requesting tests were identified as protecting against malpractice and fears of misdiagnosis or overlooking a diagnosis. It has been observed that physicians often order tests routinely, without being fully familiar with standard test ordering procedures based on diagnostic algorithms, and lacking knowledge about rational laboratory use. The cost of tests is mostly unknown to clinicians. The study concludes that there are laboratory tests that incur much higher costs. When this assessment is applied to the entire laboratory, it becomes clear how significant a financial burden, unnecessary workload, and loss of time this situation can cause. Identifying the presence of unnecessary test requests is the first step in preventing them. Appropriate measures include highlighting these issues, providing necessary information, and offering in-service training.

Factors affecting hospital services overutilization and reductive strategies in Iran: a qualitative study to explore experts' views

OBJECTIVES

This study aimed to investigate the viewpoints of the main stakeholders of the Iranian healthcare system about the overutilization of hospital services and strategies to eliminate or reduce it in Iran.

METHODS

This is a qualitative study and thematic data analysis using face-to-face semi-structured interviews and Focus Group Discussions (FGDs). We conducted eight interviewers and two FGDs with hospital stakeholders including faculty members, insurance organizations' authorities, experienced hospital administrative staff, hospital managers, and health-care providers.

RESULTS

The factors leading to the overutilization of hospital services were categorized into four main themes including site of service, quality, supplier push, and demand pull. Strategies for eliminating or reducing the overutilization of hospital services are also identified based on the influential factors.

CONCLUSION

Addressing overutilization of hospital services in the health system and adherence to policies for reducing or eliminating overutilization is a way to make preventive strategies to overcome overutilization. Developing a national plan to integrate utilization management into health system programs is a strategy to combat overutilization in various levels of the health system including hospital setting.

Current state of laboratory test utilization practices in the clinical laboratory

Appropriate laboratory test utilization is of growing interest in the face of rising healthcare costs and documented evidence of over- and under-utilization. Building from published literature, laboratory organizations have recently published guidelines for establishing laboratory utilization management programs. However, systematic reviews and meta-analyses have consistently struggled to define rigorous evidence-based best practice recommendations due to the paucity of published data or the heterogeneity of available data. We sought to gain information about utilization practices and programs currently in use and which factors contribute to their success by distributing a survey among laboratory professionals. The survey received seventy-four eligible respondents. We observed a wide range in the duration of laboratory utilization programs and the number of stewardship initiatives. In addition, there was great variety in the utilization practices used and the tests or processes targeted by programs. There was similarity in how initiatives are evaluated and who is involved with utilization programs. Finally, respondents often credited a multidisciplinary committee, support from leadership, and strong IT support/data access as important factors for their program's perceived success. Many of these factors agree with previously published literature.

A randomized controlled study of biochemical tests in primary care: interventions can reduce the number of tests but usage does not become more appropriate

OBJECTIVES

The use of laboratory tests increases worldwide, and to some extent their use is likely to be inappropriate. Although primary care is responsible for a substantial proportion of requests, this sector is less extensively investigated than hospitals.

METHODS

We tested the effect of six combinations of four interventions applied to 313 primary care clinics, using vitamin D as model test (253,762 vitamin D results). We evaluated the changes in test numbers in the six intervention groups compared to the control group, and whether interventions resulted in more homogenous test use within groups or affected the distribution of test results. All interventions included information on vitamin D testing guidelines. Four groups were exposed to a non-interruptive alert in the ordering IT-system and in two groups this was supplemented by an interruptive alert. Half of the groups received monthly feedback reports.

RESULTS

Application of alerts, irrespective of the combination with feedback reports, resulted in significantly reduced test numbers (maximum -46%). Guidelines either alone or combined with feedback reports did not cause significant difference from the control group. The within-group requesting pattern changed significantly for only two of the groups. The distribution of low and normal vitamin D results within groups showed no signs of more appropriate use of the test in any of the groups.

CONCLUSIONS

Some of the interventions reduced the number of tests, but there were no indications of improved adherence to the guidelines. The interventions may have led to under-utilization of the test and thus should be used with care.

Factors Associated With Increased Laboratory Use in the Pediatric Cardiac Intensive Care Unit

BACKGROUND

Laboratory testing is frequently used to guide postoperative management and contributes to hospital resource utilization; however, there is little evidence identifying patient or clinical factors to inform the appropriate frequency of laboratory testing in the pediatric cardiac intensive care unit.

OBJECTIVES

To examine the factors associated with increased laboratory utilization following pediatric congenital heart surgery.

METHODS

For each patient, the total number of tests and types of laboratory tests were recorded. Patients whose number of tests was greater than the 90th percentile were categorized as increased laboratory use.

RESULTS

A sample of 250 unique patients and 909 nursing shifts were obtained for patient- and shift-level analyses. The top 10% of patients identified as the high laboratory utilization group (>128 laboratory tests). High-use group reported significantly younger patients and longer bypass time (P < .001). Patients in the highest Risk Adjustment for Congenital Heart Surgery 1 risk category were 34.7 times more likely to be in high laboratory utilization group (P = .006), independent of age at time of surgery and time on bypass (receiver operating characteristic curve = 0.855). At the shift level, time on bypass (P = .002), age younger than 30 days at surgery (P < .001), 3 to 5 years' registered nurse experience (P < .001), staff precepting (P = .03), and weekday shift status (P = .03) were all independently associated with high laboratory utilization.

CONCLUSIONS

There are multiple factors associated with increased laboratory utilization. Recognition of specific patient and nursing factors can be used to impact patient management.

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

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.

Overuse of diagnostic testing in healthcare: a systematic review

BACKGROUND

Overuse of diagnostic testing substantially contributes to healthcare expenses and potentially exposes patients to unnecessary harm. Our objective was to systematically identify and examine studies that assessed the prevalence of diagnostic testing overuse across healthcare settings to estimate the overall prevalence of low-value diagnostic overtesting.

METHODS

PubMed, Web of Science and Embase were searched from inception until 18 February 2020 to identify articles published in the English language that examined the prevalence of diagnostic testing overuse using database data. Each of the assessments was categorised as using a patient-indication lens, a patient-population lens or a service lens.

RESULTS

118 assessments of diagnostic testing overuse, extracted from 35 studies, were included in this study. Most included assessments used a patient-indication lens (n=67, 57%), followed by the service lens (n=27, 23%) and patient-population lens (n=24, 20%). Prevalence estimates of diagnostic testing overuse ranged from 0.09% to 97.5% (median prevalence of assessments using a patient-indication lens: 11.0%, patient-population lens: 2.0% and service lens: 30.7%). The majority of assessments (n=85) reported overuse of diagnostic testing to be below 25%. Overuse of diagnostic imaging tests was most often assessed (n=96). Among the 33 assessments reporting high levels of overuse (≥25%), preoperative testing (n=7) and imaging for uncomplicated low back pain (n=6) were most frequently examined. For assessments of similar diagnostic tests, major variation in the prevalence of overuse was observed. Differences in the definitions of low-value tests used, their operationalisation and assessment methods likely contributed to this observed variation.

CONCLUSION

Our findings suggest that substantial overuse of diagnostic testing is present with wide variation in overuse. Preoperative testing and imaging for non-specific low back pain are the most frequently identified low-value diagnostic tests. Uniform definitions and assessments are required in order to obtain a more comprehensive understanding of the magnitude of diagnostic testing overuse.

The impact of interventions applied in primary care to optimize the use of laboratory tests: a systematic review

Laboratory tests are important tools in primary care, but their use is sometimes inappropriate. The aim of this review is to give an overview of interventions applied in primary care to optimize the use of laboratory tests. A search for studies was made in the MEDLINE and EMBASE databases. We also extracted studies from two previous reviews published in 2015. Studies were included if they described application of an intervention aiming to optimize the use of laboratory tests. We also evaluated the overall risk of bias of the studies. We included 24 studies. The interventions were categorized as: education, feedback reports and computerized physician order entry (CPOE) strategies. Most of the studies were classified as medium or high risk of bias while only three studies were evaluated as low risk of bias. The majority of the studies aimed at reducing the number of tests, while four studies investigated interventions aiming to increase the use of specific tests. Despite the studies being heterogeneous, we made results comparable by transforming the results into weighted relative changes in number of tests when necessary. Education changed the number of tests consistently, and these results were supported by the low risk of bias of the papers. Feedback reports have mainly been applied in combination with education, while when used alone the effect was minimal. The use of CPOE strategies seem to produce a marked change in the number of test requests, however the studies were of medium or high risk of bias.

A deep learning solution to recommend laboratory reduction strategies in ICU

OBJECTIVE

To build a machine-learning model that predicts laboratory test results and provides a promising lab test reduction strategy, using spatial-temporal correlations.

MATERIALS AND METHODS

We developed a global prediction model to treat laboratory testing as a series of decisions by considering contextual information over time and across modalities. We validated our method using a critical care database (MIMIC III), which includes 4,570,709 observations of 12 standard laboratory tests, among 38,773 critical care patients. Our deep-learning model made real-time laboratory reduction recommendations and predicted the properties of lab tests, including values, normal/abnormal (whether labs were within the normal range) and transition (normal to abnormal or abnormal to normal from the latest lab test). We reported area under the receiver operating characteristic curve (AUC) for predicting normal/abnormal, evaluated accuracy and absolute bias on prediction vs. observation against lab test reduction proportion. We compared our model against baseline models and analyzed the impact of variations on the recommended reduction strategy.

RESULTS

Our best model offered a 20.26 % reduction in the number of laboratory tests. By applying the recommended reduction policy on the hold-out dataset (7755 patients), our model predicted normality/abnormality of laboratory tests with a 98.27 % accuracy (AUC, 0.9885; sensitivity, 97.84 %; specificity, 98.80 %; PPV, 99.01 %; NPV, 97.39 %) on 20.26 % reduced lab tests, and recommended 98.10 % of transitions to be checked. Our model performed better than the greedy models, and the recommended reduction strategy was robust.

DISCUSSION

Strong spatial and temporal correlations between laboratory tests can be used to optimize policies for reducing laboratory tests throughout the hospital course. Our method allows for iterative predictions and provides a superior solution for the dynamic decision-making laboratory reduction problem.

CONCLUSION

This work demonstrates a machine-learning model that assists physicians in determining which laboratory tests may be omitted.

Neonatal Umbilical Arterial Catheter Removal Is Accompanied by a Marked Decline in Phlebotomy Blood Loss

BACKGROUND

Umbilical arterial catheters (UACs) are frequently used in critically ill neonates. UAC are convenient, reliable, and allow for caregiver convenience in performing painless arterial blood sampling. We hypothesized that UAC removal in extremely low birth weight (ELBW) neonates will result in significantly less phlebotomy blood loss (PBL) after correcting for severity of illness.

STUDY DESIGN AND METHODS

PBL was measured at a single center in 99 ELBW infants who survived to day 28. Individual infant's paired daily PBL for the two 24-h periods before and after UAC removal were compared using the paired t test. Daily PBL up to 7 days before and 7 days after UAC removal were compared using a logistic regression with mixed model analysis for repeated measures. Cumulative 28-day phlebotomy loss was evaluated by multiple linear regression analysis.

RESULTS

PBL 24 h before and after UAC removal were 1.7 mL (95% CI 1.5-1.9) and 0.9 mL (95% CI 0.8-1.0; p < 0.0001), respectively. Cumulative 28-day PBL increased by 2.2 mL (±0.7) per day that a UAC was present with or without correction for severity of illness (p < 0.001).

CONCLUSION

UAC removal is independently associated with a marked decline in PBL. We speculate the ease and convenience of UAC blood sampling lead to more frequent blood testing and greater PBL.

Factors leading to overutilisation of hospital pathology testing: the junior doctor's perspective

Objective Pathology overutilisation is a significant issue affecting the quality and cost of health care. Because junior medical officers (JMOs) order most pathology tests in the hospital setting, the aim of the present study was to identify the main reasons for hospital pathology overutilisation from the perspective of the JMO. Methods A qualitative method, using focus group methodology, was undertaken. Sixteen JMOs from two hospitals participated in three focus groups. Data were analysed using thematic analysis. Results Three major themes contributed to overutilisation: the real and perceived expectations of senior colleagues, the level of JMO clinical experience and strategies to manage JMO workload around clinical systems. Within these themes, 12 subthemes were identified. Conclusions Overutilisation of hospital pathology testing occurs when there are high social costs to JMOs for underordering, with little cost for overordering. Interventions should restore this balance through reframing overutilisation as both a costly and potentially harmful activity, promoting a supportive culture with regular senior guidance, and addressing clinical systems in which missed tests create an excessive workload. What is known about the topic? Mean overutilisation rates of pathology testing are reported to be as high as 44%. Although numerous studies have reported successful efforts to decrease hospital pathology overutilisation, no primary research was identified that examined the JMO perspective on this subject. What does this paper add? Clinical need is not the primary factor guiding the pathology-ordering decisions of junior practitioners; rather, medical team culture, limited JMO experience and systems factors have a significant role. What are the implications for practitioners? The social and behavioural determinants of pathology ordering must be considered to achieve appropriate pathology test utilisation. These include senior medical officer engagement, the guidance of JMOs and clinical workflows.

Prevalence and Predictability of Low-Yield Inpatient Laboratory Diagnostic Tests

IMPORTANCE

Laboratory testing is an important target for high-value care initiatives, constituting the highest volume of medical procedures. Prior studies have found that up to half of all inpatient laboratory tests may be medically unnecessary, but a systematic method to identify these unnecessary tests in individual cases is lacking.

OBJECTIVE

To systematically identify low-yield inpatient laboratory testing through personalized predictions.

DESIGN, SETTING, AND PARTICIPANTS

In this retrospective diagnostic study with multivariable prediction models, 116 637 inpatients treated at Stanford University Hospital from January 1, 2008, to December 31, 2017, a total of 60 929 inpatients treated at University of Michigan from January 1, 2015, to December 31, 2018, and 13 940 inpatients treated at the University of California, San Francisco from January 1 to December 31, 2018, were assessed.

MAIN OUTCOMES AND MEASURES

Diagnostic accuracy measures, including sensitivity, specificity, negative predictive values (NPVs), positive predictive values (PPVs), and area under the receiver operating characteristic curve (AUROC), of machine learning models when predicting whether inpatient laboratory tests yield a normal result as defined by local laboratory reference ranges.

RESULTS

In the recent data sets (July 1, 2014, to June 30, 2017) from Stanford University Hospital (including 22 664 female inpatients with a mean [SD] age of 58.8 [19.0] years and 22 016 male inpatients with a mean [SD] age of 59.0 [18.1] years), among the top 20 highest-volume tests, 792 397 were repeats of orders within 24 hours, including tests that are physiologically unlikely to yield new information that quickly (eg, white blood cell differential, glycated hemoglobin, and serum albumin level). The best-performing machine learning models predicted normal results with an AUROC of 0.90 or greater for 12 stand-alone laboratory tests (eg, sodium AUROC, 0.92 [95% CI, 0.91-0.93]; sensitivity, 98%; specificity, 35%; PPV, 66%; NPV, 93%; lactate dehydrogenase AUROC, 0.93 [95% CI, 0.93-0.94]; sensitivity, 96%; specificity, 65%; PPV, 71%; NPV, 95%; and troponin I AUROC, 0.92 [95% CI, 0.91-0.93]; sensitivity, 88%; specificity, 79%; PPV, 67%; NPV, 93%) and 10 common laboratory test components (eg, hemoglobin AUROC, 0.94 [95% CI, 0.92-0.95]; sensitivity, 99%; specificity, 17%; PPV, 90%; NPV, 81%; creatinine AUROC, 0.96 [95% CI, 0.96-0.97]; sensitivity, 93%; specificity, 83%; PPV, 79%; NPV, 94%; and urea nitrogen AUROC, 0.95 [95% CI, 0.94, 0.96]; sensitivity, 87%; specificity, 89%; PPV, 77%; NPV 94%).

CONCLUSIONS AND RELEVANCE

The findings suggest that low-yield diagnostic testing is common and can be systematically identified through data-driven methods and patient context-aware predictions. Implementing machine learning models appear to be able to quantify the level of uncertainty and expected information gained from diagnostic tests explicitly, with the potential to encourage useful testing and discourage low-value testing that incurs direct costs and indirect harms.

Effectiveness of Practices to Support Appropriate Laboratory Test Utilization: A Laboratory Medicine Best Practices Systematic Review and Meta-Analysis

Objectives

To evaluate the effectiveness of practices used to support appropriate clinical laboratory test utilization.

Methods

This review followed the Centers for Disease Control and Prevention (CDC) Laboratory Medicine Best Practices A6 cycle method. Eligible studies assessed one of the following practices for effect on outcomes relating to over- or underutilization: computerized provider order entry (CPOE), clinical decision support systems/tools (CDSS/CDST), education, feedback, test review, reflex testing, laboratory test utilization (LTU) teams, and any combination of these practices. Eligible outcomes included intermediate, systems outcomes (eg, number of tests ordered/performed and cost of tests), as well as patient-related outcomes (eg, length of hospital stay, readmission rates, morbidity, and mortality).

Results

Eighty-three studies met inclusion criteria. Fifty-one of these studies could be meta-analyzed. Strength of evidence ratings for each practice ranged from high to insufficient.

Conclusion

Practice recommendations are made for CPOE (specifically, modifications to existing CPOE), reflex testing, and combined practices. No recommendation for or against could be made for CDSS/CDST, education, feedback, test review, and LTU. Findings from this review serve to inform guidance for future studies.

Health Informatics Tools to Improve Utilization of Laboratory Tests

Herein, we discuss improper test utilization practices and their implications on delivery of health care, as well as providing a brief explanation of the means to reduce such practices by improvement of personnel factors, particularly involving physicians. The article also elaborates on ways to mitigate improperly utilized test practices using appropriate health informatics technologies to their maximum possible capacities.

Blood Transfusion Therapy

Transfusion of red blood cells (RBCs) is a balance between providing benefit for patients while avoiding risks of transfusion. Randomized, controlled trials of restrictive RBC transfusion practices have shown equivalent patient outcomes compared with liberal transfusion practices, and meta-analyses have shown improved in-hospital mortality, reduced cardiac events, and reduced bacterial infections. This body of level 1 evidence has led to substantial, improved blood utilization and reduction of inappropriate blood transfusions with implementation of clinical decision support via electronic medical records, along with accompanying educational initiatives.

Appropriateness of diagnostics tests

The evolution of the concept of 'appropriateness', in the three past decades, from 'no harm' and 'no waste' to 'medical decision-making' and 'determining outcomes' highlights two main points: its foundation is evidence-based medicine, and it is a quality of every phase of the total testing process, not only for the selection of tests. Nevertheless, appropriateness in Laboratory Hematology, as well as in Laboratory Medicine, is an elusive concept: 'Appropriateness' interplays with 'patient's safety', 'healthcare costs', 'clinical decision-making', and 'effectiveness', and the criteria for appropriateness, mainly adherence to clinical guidelines, are often not evidence-based and not always consensus-based. Moreover, practising appropriateness is a complex issue because of the ambiguity of the criteria and targets, the never-ending work of implementing guidelines and their audit, and the uniqueness of the clinical situation of the individual patient. Authors agree on some practical rules: establishing a multidisciplinary and multiprofessional team, choosing carefully clinical targets, finding or building evidences, sharing guidelines with clinicians, choosing adequate tools for changing, working hard on implementation, identifying the 'right' laboratory methods and processes, checking progress indefinitely, providing information, interpretations, and consultations, and promoting feedback and audits. The success depends on the 'right' combination of educational, operative, and reinforcing interventions. Competences in organization, in implementation science, and in interpersonal relationship management are essential as well as knowledge and experience in Hematology, not only in Laboratory Hematology.

Effect of high-potency statins on HbA1c in patients with or without diabetes mellitus

Background

The increased risk of new-onset diabetes with statin use, including high-potency statins, is well known. However, the effects of high-potency statins on HbA1c are unclear. A retrospective cohort study was conducted to examine the effect of high-potency statins on HbA1c in patients with or without diabetes. The study enrolled new statin users identified via the electronic healthcare database of the general hospital in Japan.

Methods

Following identification of all individuals (n = 4,672) who had been prescribed a lipid lowering drug at least once between January 1, 2010 and July 31, 2014, new statin users were selected (n = 1,136). Patients were excluded if they had been prescribed treatment with a statin within the preceding 6-month period. HbA1c levels before and during high-potency statin treatment were compared using the dependent t-test. In addition, the hazard ratio for the incidence of diabetes with high-potency statin treatment was estimated, using low-potency statins as a reference.

Results

In patients with diabetes (n = 153), mean HbA1c (%) levels significantly increased by 0.4 % after high-potency statin use (7.57 ± 1.58; p = 0.0002) compared to baseline (7.18 ± 1.37). Similarly, HbA1c (%) levels significantly increased from 5.78 ± 0.38 to 5.92 ± 0.45 (p < 0.0001) after high-potency statin use in patients without diabetes (n = 165). Furthermore, a trend toward an increase in HbA1c was found for all of the high-potency statins irrespective of a history of diabetes.

Conclusions

The use of high-potency statins may increase HbA1c levels in patients with or without diabetes.

Is there a "magic" hemoglobin number? Clinical decision support promoting restrictive blood transfusion practices

Blood transfusion has been identified as one of the most frequently performed therapeutic procedures, with a significant percentage of transfusions identified to be inappropriate. Recent key clinical trials in adults have provided Level 1 evidence to support restrictive red blood cell (RBC) transfusion practices. However, some advocates have attempted to identify a "correct" Hb threshold for RBC transfusion; whereas others assert that management of anemia, including transfusion decisions, must take into account clinical patient variables, rather than simply one diagnostic laboratory test. The heterogeneity of guidelines for blood transfusion by a number of medical societies reflects this controversy. Clinical decision support (CDS) uses a Hb threshold number in a smart Best Practices Alert (BPA) upon physician order, to trigger a concurrent utilization self-review for whether blood transfusion therapy is appropriate. This review summarizes Level 1 evidence in seven key clinical trials in adults that support restrictive transfusion practices, along strategies made possible by CDS that have demonstrated value in improving blood utilization by promoting restrictive transfusion practices.

Promoting improved utilization of laboratory testing through changes in an electronic medical record: experience at an academic medical center

This case study over time describes five years of experience with interventions to improve laboratory test utilization at an academic medical center. The high-frequency laboratory tests showing the biggest declines in order volume post intervention were serum albumin (36%) and erythrocyte sedimentation rate (17%). Introduction of restrictions for 170 high-cost send-out tests resulted in a 23% decline in order volume. Targeted interventions reduced mis-orders involving several “look-alike” tests: 1,25-dihydroxyvitamin D, 25-hydroxyvitamin D; manganese, magnesium; beta-2-glycoprotein, beta-2-microglobulin. Lastly, targeted alerts reduced duplicate orders of germline genetic testing and orders of hepatitis B surface antigen within 2 weeks of hepatitis B vaccination.

The next chapter in patient blood management: real-time clinical decision support

OBJECTIVES

Blood transfusion was identified by the American Medical Association as one of the top five most frequently overused therapies. Utilization review has been required by accreditation agencies, but retrospective review has been ineffective due to labor-intense resources applied to only a sampling of transfusion events. Electronic medical records have allowed clinical decision support (CDS) to occur via a best practices alert at the critical decision point concurrently with physician order entry.

METHODS

We review emerging strategies for improving blood utilization.

RESULTS

Implementation of CDS at our institution decreased the percentage of transfusions in patients with a hemoglobin level of more than 8 g/dL from 60% to less than 30%. Annual RBC transfusions were reduced by 24%, despite concurrent increases in patient discharge volumes and case mix complexity. This resulted in acquisition costs savings (direct blood product purchase costs) of $6.4 million over 4 years.

CONCLUSIONS

We have been able to significantly reduce inappropriate blood transfusions and related costs through an educational initiative coupled with real-time CDS. In deriving increased value out of health care, CDS can be applied to a number of overuse measures in laboratory testing, radiology, and therapy such as antibiotics, as outlined by the American Board of Internal Medicine's Choosing Wisely campaign.