Feasibility and Performance of Continuous Glucose Monitoring to Guide Computerized Insulin Infusion Therapy in Cardiovascular Intensive Care Unit.

BACKGROUND: We evaluated the feasibility of real-time continuous glucose monitoring (CGM) for titrating continuous intravenous insulin infusion (CII) to manage hyperglycemia in postoperative individuals in the cardiovascular intensive care unit and assessed their accuracy, nursing acceptance, and postoperative individual satisfaction. METHODS: Dexcom G6 CGM devices were applied to 59 postsurgical patients with hyperglycemia receiving CII. A hybrid approach combining CGM with periodic point-of-care blood glucose (POC-BG) tests with two phases (initial-ongoing) of validation was used to determine CGM accuracy. Mean and median absolute relative differences and Clarke Error Grid were plotted to evaluate the CGM accuracy. Surveys of nurses and patients on the use of CGMs experience were conducted and results were analyzed. RESULTS: In this cohort (mean age 64, 32% female, 32% with diabetes) with 864 paired POC-BG and CGM values analyzed, mean and median absolute relative difference between POC-BG and CGM values were 13.2% and 9.8%, respectively. 99.7% of paired CGM and POC-BG were in Zones A and B of the Clarke Error Grid. Responses from nurses reported CGMs being very or quite convenient (n = 28; 93%) and it was favored over POC-BG testing (n = 28; 93%). Majority of patients (n = 42; 93%) reported their care process using CGM as being good or very good. CONCLUSION: This pilot study demonstrates the feasibility, accuracy, and nursing convenience of adopting CGM via a hybrid approach for insulin titration in postoperative settings. These findings provide robust rationale for larger confirmatory studies to evaluate the benefit of CGM in postoperative care to improve workflow, enhance health outcomes, and cost-effectiveness.

A Generalizable Decision-Making Framework for Selecting Onsite versus Send-out Clinical Laboratory Testing.

BACKGROUND: Laboratory networks provide services through onsite testing or through specimen transport to higher-tier laboratories. This decision is based on the interplay of testing characteristics, treatment characteristics, and epidemiological characteristics. OBJECTIVES: Our objective was to develop a generalizable model using the threshold approach to medical decision making to inform test placement decisions. METHODS: We developed a decision model to compare the incremental utility of onsite versus send-out testing for clinical purposes. We then performed Monte Carlo simulations to identify the settings under which each strategy would be preferred. Tuberculosis was modeled as an exemplar. RESULTS: The most important determinants of the decision to test onsite versus send-out were the clinical utility lost due to send-out testing delays and the accuracy decrement with onsite testing. When the sensitivity decrements of onsite testing were minimal, onsite testing tended to be preferred when send-out delays reduced clinical utility by >20%. By contrast, when onsite testing incurred large reductions in sensitivity, onsite testing tended to be preferred when utility lost due to delays was >50%. The relative cost of onsite versus send-out testing affected these thresholds, particularly when testing costs were >10% of treatment costs. CONCLUSIONS: Decision makers can select onsite versus send-out testing in an evidence-based fashion using estimates of the percentage of clinical utility lost due to send-out delays and the relative accuracy of onsite versus send-out testing. This model is designed to be generalizable to a wide variety of use cases. HIGHLIGHTS: The design of laboratory networks, including the decision to place diagnostic instruments at the point-of-care or at higher tiers as accessed through specimen transport, can be informed using the threshold approach to medical decision making.The most important determinants of the decision to test onsite versus send-out were the clinical utility lost due to send-out testing delays and the accuracy decrement with onsite testing.The threshold approach to medical decision making can be used to compare point-of-care testing accuracy decrements with the lost utility of treatment due to send-out testing delays.The relative cost of onsite versus send-out testing affected these thresholds, particularly when testing costs were >10% of treatment costs.

Yellow fever in Ghana: Predicting emergence and ecology from historical outbreaks.

Understanding the epidemiology and ecology of yellow fever in endemic regions is critical for preventing future outbreaks. Ghana is a high-risk country for yellow fever. In this study we estimate the epidemiology, ecological cycles, and areas at risk for yellow fever in Ghana based on historical outbreaks. We identify 2371 cases and 887 deaths (case fatality rate 37.4%) from yellow fever reported in Ghana from 1910 to 2022. Since implementation of routine childhood vaccination in 1992, the estimated mean annual number of cases decreased by 81% and the geographic distribution of yellow fever cases also changed. While there have been multiple large historical outbreaks of yellow fever in Ghana from the urban cycle, recent outbreaks have originated among unvaccinated nomadic groups in rural areas with the sylvatic/savanna cycles. Using machine learning and an ecological niche modeling framework, we predict areas in Ghana that are similar to where prior yellow fever outbreaks have originated based on temperature, precipitation, landcover, elevation, and human population density. We find differences in predictions depending on the ecological cycles of outbreaks. Ultimately, these findings and methods could be used to inform further subnational risk assessments for yellow fever in Ghana and other high-risk countries.

Providing specimen transport through an online marketplace in the Northern region of Ghana.

Background: Integrated diagnostic networks, which are themselves dependent on robust specimen transport solutions, are fundamental to effective healthcare systems. Objective: This study aimed to pilot an online marketplace for the transport of specimens throughout a laboratory network in Ghana. Methods: Independent drivers were matched with health facilities that required specimen transport using a suite of mobile applications and web portals developed for this study. This marketplace was piloted with seven drivers, two laboratories, and five health facilities in Ghana's Northern region from March 2019 to October 2019. Results: During the pilot, 182 deliveries were completed for 691 patients, including 4118 laboratory tests for antenatal care, disease surveillance, and clinical testing. Testing included 34 tests for communicable and non-communicable diseases. All but two specimens (laboratory cancellations) were successfully delivered and tested. The median time from request to encrypted emailing of results was 19.7 h, while that for a drop-off request was 0.9 h. In the midwife registry, the median time from patient visit to result recording was 1 day, compared to 4 days in the same months in 2018, and the number of mothers without documented testing decreased from 41 to 3. Similarly, the proportion of tuberculosis specimen deliveries from Buipe Polyclinic to Tamale Zonal Laboratory taking over 1 day fell from 62% at baseline to 3% during the pilot. Conclusion: An online marketplace successfully orchestrated the delivery of laboratory specimens under a variety of clinical circumstances, reducing overall turn-around time without diminution of the overall specimen delivery process. What this study adds: This study established the efficacy of an online marketplace to orchestrate timely and high-quality delivery of specimens within a laboratory network.

Retrospective analysis of serum free light chain reference intervals and risk for monoclonal gammopathy suggests different limits than those in international guidelines.

OBJECTIVES: Recent reference interval studies of the serum free light chain (FLC) test using contemporary instruments display divergence with the diagnostic range generally adopted as the international standard. In this study, we perform a retrospective reference interval analysis with risk predictions for monoclonal gammopathy. METHODS: Retrospective laboratory and clinical data for 8,986 patients were included in the study. Reference intervals were generated against a set of inclusion/exclusion criteria for two time periods representing the use of different instruments. The presence of monoclonal gammopathy was established from diagnostic test interpretations and EHR diagnosis codes in the patient problem lists and medical history. RESULTS: The 95% FLC ratio reference intervals were 0.76-2.38 for SPAPLUS®, and 0.68-1.82 for Optilite® instruments. These intervals varied considerably from the current diagnostic range of 0.26-1.65 and mapped approximately to the FLC ratios beyond which risk of monoclonal gammopathy substantially increased. CONCLUSIONS: These findings corroborate recent reference interval studies and support recommendations for independent re-evaluation of intervals by institutions as well as an update of international guidelines.

An assessment of the laboratory network in Ghana: A national-level ATLAS survey (2019-2020).

Background: Integrated health systems with strong laboratory networks are critical in improving public health. The current study assessed the laboratory network in Ghana and its functionality using the Assessment Tool for Laboratory Services (ATLAS). Intervention: A national-level laboratory network survey was conducted among stakeholders of the Ghanaian laboratory network in Accra. Face-to-face interviews were conducted from December 2019 to January 2020, with follow-up phone interviews between June and July 2020. Also, we reviewed supporting documents provided by stakeholders for supplementary information and transcribed these to identify themes. Where possible, we completed the Laboratory Network scorecard using data obtained from the ATLAS. Lessons learnt: The Laboratory Network (LABNET) scorecard assessment was a valuable addition to the ATLAS survey as it quantified the functionality of the laboratory network and its overall advancement toward achieving International Health Regulations (2005) and Global Health Security Agenda targets. Two significant challenges indicated by respondents were laboratory financing and delayed implementation of the Ghana National Health Laboratory Policy. Recommendations: Stakeholders recommended a review of the country's funding landscape, such as funding laboratory services from the country's internally generated funds. Also, they recommended laboratory policy implementation to ensure adequate laboratory workforce and standards.

Rational design of an essential diagnostics network to support Universal Health Coverage: a modeling analysis.

BACKGROUND: Diagnostic investigations, including pathology and laboratory medicine (PALM) and radiology, have been largely absent from international strategies such as the Sustainable Development Goals. Further, there is little international guidance on which health system tiers different diagnostics should be placed, a critical step in developing a country-level diagnostics network. We describe a modeling strategy to produce tier-specific diagnostic recommendations based on disease burden, current treatment pathways, and existing infrastructure in a country. METHODS: The relational model assumes that diagnostics should be available at the lowest tier where patients might receive medical management. Using Ghana as an exemplar, the 20 diseases forecasted by 2030 and 2040 to cause the greatest burden in low- and middle-income countries were mapped to three generalized tiers in the Ghanaian health system (Primary, Secondary, and Tertiary care) for three levels of each disease (triage, uncomplicated, and complicated). The lowest tier at which a diagnostic could potentially be placed was restricted by existing infrastructure, though placement still required there be a medical justification for the diagnostic at that tier. RESULTS: The model recommended 111 unique diagnostic investigations with 17 at Primary tier, an additional 45 at Secondary tier and a further 49 at Tertiary tier. Estimated capital costs were $8,330 at Primary tier and between $571,000 to $777,000 at Secondary tier. Twenty-eight different laboratory tests were recommended as send-outs from Primary to Secondary tier, and twelve as send-outs to Tertiary tier. CONCLUSIONS: This model provides a transparent framework within which countries can customize diagnostic planning to local disease priorities, health system patient treatment pathways, and infrastructural limitations to best support Universal Health Coverage.

Implementation of INHERET, an Online Family History and Cancer Risk Interpretation Program for Primary Care and Specialty Clinics.

BACKGROUND: Individuals at increased risk for cancer are ascertained at low rates of 1% to 12% in primary care (PC). Underserved populations experience disparities of ascertainment, but data are lacking. INHERET is an online personal and family history tool to facilitate the identification of individuals who are eligible, according to guidelines, to be counseled on germline genetic testing and risk management. PATIENTS AND METHODS: INHERET data entry uses cancer genetics clinic questionnaires and algorithms that process patient data through NCCN Clinical Practice Guidelines in Oncology and best practice guidelines. The tool was tested in silico on simulated and retrospective patients and prospectively in a pilot implementation trial. Patients in cancer genetics and in PC clinics were invited to participate via email or a card. Informed consent was completed online. RESULTS: INHERET aimed to integrate patient data by algorithms based on professional and best practice guidelines to elicit succinct, actionable recommendations that providers can use without affecting clinic workflow or encounter length. INHERET requires a 4th-grade reading level, has simple navigation, and produces data lists and pedigree graphs. Prospective implementation testing revealed understandability of 90% to 100%, ease of use of 85%, and completion rates of 85% to 100%. Physicians using INHERET reported no added time to their encounters when patients were identified for counseling. In a specialty genetics clinic, INHERET's data were input, on average, within 72 hours compared with 4 to 6 weeks through standard care, and the queue for scheduling patients decreased from 400 to fewer than 15 in <6 months. CONCLUSIONS: INHERET was found to be accessible for all education and age levels, except patients aged >70 years, who encountered more technical difficulties. INHERET aided providers in conveying high-risk status to patients and eliciting appropriate referrals, and, in a specialty clinic, it produced improved workflows and shortened queues.

Predicting Direct-Specimen SARS-CoV-2 Assay Performance Using Residual Patient Samples.

BACKGROUND: Diagnostic sensitivities of point-of-care SARS-CoV-2 assays depend on specimen type and population-specific viral loads. Evaluation of these assays require "direct" specimens from paired-swab studies rather than more accessible residual specimens in viral transport media (VTM). METHODS: Residual VTM and limit-of-detection studies were conducted on Abbott ID NOW™ COVID-19, Quidel Sofia 2™ SARS Antigen FIA, and DiaSorin Simplexa™ COVID-19 Direct assays, with cycle threshold (CT) adjustments to approximate direct-specimen testing based on gene-target doubling each PCR cycle. Logistic regression was used to model assay performance by specimen CT. These models were applied to CT distributions of symptomatic and asymptomatic populations presenting to emergency services to predict the percentage of specimens that would be detected by each assay. A 96-sample paired-swab study was conducted to confirm model results. RESULTS: When using direct nasopharyngeal samples and fit with either VTM or limit-of-detection data, percent positivities for ID NOW (symptomatic 94.9%/97.4%; asymptomatic 88.4.0%/89.6%) and Simplexa (symptomatic 97.8%/97.2%; asymptomatic 91.1%/90.8%) were predicted to be similar. Likewise, percent positivities for ID NOW with direct nasal specimens (symptomatic 77.8%; asymptomatic 64.5%) and, fit with VTM data, Sofia 2 with direct nasopharyngeal specimens (symptomatic 76.6%, asymptomatic 60.3%) were similar. The paired-swab study comparing direct nasopharyngeal specimens on ID NOW and nasopharyngeal VTM specimens on Simplexa showed 99% concordance. CONCLUSIONS: Assay performance can be modeled as dependent on viral load, fit using laboratory bench study results, and adjusted to account for direct-specimen testing. When using nasopharyngeal specimens, direct testing on Abbott ID NOW and VTM testing on DiaSorin Simplexa have similar performance.

Availability of essential diagnostics in ten low-income and middle-income countries: results from national health facility surveys.

BACKGROUND: Pathology and laboratory medicine diagnostics and diagnostic imaging are crucial to achieving universal health coverage. We analysed Service Provision Assessments (SPAs) from ten low-income and middle-income countries to benchmark diagnostic availability. METHODS: Diagnostic availabilities were determined for Bangladesh, Haiti, Malawi, Namibia, Nepal, Kenya, Rwanda, Senegal, Tanzania, and Uganda, with multiple timepoints for Haiti, Kenya, Senegal, and Tanzania. A smaller set of diagnostics were included in the analysis for primary care facilities compared with those expected at hospitals, with 16 evaluated in total. Surveys spanned 2004-18, including 8512 surveyed facilities. Country-specific facility types were mapped to basic primary care, advanced primary care, or hospital tiers. We calculated percentages of facilities offering each diagnostic, accounting for facility weights, stratifying by tier, and for some analyses, region. The tier-level estimate of diagnostic availability was defined as the median of all diagnostic-specific availabilities at each tier, and country-level estimates were the median of all diagnostic-specific availabilities of each of the tiers. Associations of country-level diagnostic availability with country income as well as (within-country) region-level availability with region-specific population densities were determined by multivariable linear regression, controlling for appropriate covariates including tier. FINDINGS: Median availability of diagnostics was 19·1% in basic primary care facilities, 49·2% in advanced primary care facilities, and 68·4% in hospitals. Availability varied considerably between diagnostics, ranging from 1·2% (ultrasound) to 76·7% (malaria) in primary care (basic and advanced) and from 6·1% (CT scan) to 91·6% (malaria) in hospitals. Availability also varied between countries, from 14·9% (Bangladesh) to 89·6% (Namibia). Availability correlated positively with log(income) at both primary care tiers but not the hospital tier, and positively with region-specific population density at the basic primary care tier only. INTERPRETATION: Major gaps in diagnostic availability exist in many low-income and middle-income countries, particularly in primary care facilities. These results can serve as a benchmark to gauge progress towards implementing guidelines such as the WHO Essential Diagnostics List and Priority Medical Devices initiatives. FUNDING: Bill & Melinda Gates Foundation.

Evaluating urban-rural access to pathology and laboratory medicine services in Tanzania.

Placement of pathology and laboratory medicine (PALM) services requires balancing efficiency (maximizing test volume) with equitable urban-rural access. We compared the association between population density (proxy for efficiency) and travel time to the closest facility (proxy for equitable access) across levels of Tanzania's public sector health system. We linked geospatial data for Tanzania from multiple sources. Data on facility locations and other geographic measures were collected from government and non-governmental databases. We classified facilities assuming increasing PALM availability by tier: (1) dispensaries, (2) health centres, (3) district hospitals and (4) regional/referral hospitals. We used the AccessMod 5 algorithm to estimate travel time to the closest facility for each tier across Tanzania with 500-m resolution. District-level average population density and travel time to the closest facility were calculated and presented using medians and interquartile ranges. Spatial correlations between these variables were estimated using the global Moran's I and bivariate Local Indicator of Spatial Autocorrelation, specifying a queen's neighbourhood matrix. Spatial analysis was restricted to 171 contiguous districts. The study included 5406 dispensaries, 675 health centres, 186 district hospitals and 37 regional/referral hospitals. District-level travel times were shortest for Tier 1 (median: [IQR]: 45.4 min [30.0-74.7]) and longest for Tier 4 facilities (160.2 min [107.3-260.0]). There was a weak spatial autocorrelation across tiers (Tier 1: -0.289, Tier 2: -0.292, Tier 3: -0.271 and Tier 4: -0.258) and few districts were classified as significant spatial outliers. Across tiers, geographic patterns of populated districts surrounded by neighbours with short travel time and sparsely populated districts surrounded by neighbours with long travel time were observed. Similar spatial correlation measures across health system levels suggest that Tanzania's health system reflects equitable urban-rural access to different PALM services. Longer travel times to hospital-based care could be ameliorated by shifting specialized diagnostics to more accessible lower tiers.

Availability and Prices of WHO Essential Diagnostics in Laboratories in West Africa: A Landscape Survey of Diagnostic Testing in Northern Ghana.

BACKGROUND: We determined the availability and pricing of laboratory testing in the Northern Region of Ghana to identify current gaps with respect to the WHO's Essential Diagnostics List (EDL). METHODS: A representative sample of facilities offering diagnostic testing within the Northern Region was geographically mapped and evaluated, with random sampling stratified by population density. Data were collected on testing menus, volumes, turn-around times, and out-of-pocket test prices. A total of 27 health centers and 39 clinical laboratories were surveyed between June and August 2019. RESULTS: Health centers offered a median of 2 of 20 tests recommended by the WHO for facilities without laboratories. The most common tests offered included point-of-care tests for malaria, HIV, and pregnancy. Clinical laboratories offered a median of 11 of 72 tests on the EDL. These facilities most commonly provided testing for malaria, HIV, pregnancy, HBsAg, urinalysis, HCV Ab, syphilis, glucose, and CBC. Urban laboratories had a total of 36 EDL tests available while rural laboratories had 12. Test prices were higher in private compared to public laboratories. National Health Insurance reimbursements were lower than out-of-pocket prices (38%), and when controlling for test price, test availability was negatively associated with this gap in reimbursement. CONCLUSIONS: Availability of diagnostic testing in Ghana's Northern Region is severely limited compared to the WHO's EDL. The disparity is pronounced in rural facilities. Reimbursement rates should be reset to more closely match out-of-pocket test prices in order to achieve the Universal Health Coverage target of the Sustainable Development Goals.

Differences in Performance Characteristics Among Four High-Throughput Assays for the Detection of Antibodies Against SARS-CoV-2 Using a Common Set of Patient Samples.

OBJECTIVES: Serologic testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has experienced a changing landscape of available assays coupled with uncertainty surrounding performance characteristics. Studies are needed to directly compare multiple commercially available assays. METHODS: Residual serum samples were identified based on SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR) testing, clinical test results, and collection dates. Serum samples were analyzed using assays from four different manufacturers: DiaSorin anti-SARS-CoV-2 S1/S2 IgG, EUROIMMUN anti-SARS-CoV-2 IgG ELISA, Roche Elecsys anti-SARS-CoV-2, and Siemens SARS-CoV-2 Total antibody assays. RESULTS: Samples from SARS-CoV-2 RT-PCR-positive patients became increasingly positive as time from symptom onset increased. For patients with latest sample 14 or more days after symptom onset, sensitivities reached 93.1% to 96.6%, 98.3%, and 96.6% for EUROIMMUN, Roche, and Siemens assays, respectively, which were superior to the DiaSorin assay at 87.7%. The specificity of Roche and Siemens assays was 100% and superior to DiaSorin and EUROIMMUN assays, which ranged from 96.1% to 97.0% and 86.3% to 96.4%, respectively. CONCLUSIONS: Laboratories should be aware of the advantages and limitations of serology testing options for SARS-CoV-2. The specificity and sensitivity achieved by the Roche and Siemens assays would be acceptable for testing in lower-prevalence regions and have the potential of orthogonal testing advantages if used in combination.

Socioeconomic characteristics associated with the introduction of new vaccines and full childhood vaccination in Ghana, 2014.

BACKGROUND: Childhood vaccination in Ghana has historically been high, but the impact of recently introduced vaccines on coverage is unknown. We calculate vaccine coverage of Ghanaian children- contrasting newly introduced vaccines and those long available - and describe associations between sociodemographic indicators and full vaccination. METHODS: Data from the 2014 Ghana Demographic and Health Survey was used to calculate full vaccination, defined as receipt of one dose bacillus Calmette-Guérin (BCG); two doses of rotavirus vaccine; 3 doses of pentavalent vaccine, oral polio vaccine (OPV), and pneumococcal conjugate vaccine (PCV); and one dose of measles-rubella vaccine and yellow fever vaccine, among children age 12-24 months. Logistic regression with survey procedures was used to estimate odds ratios for socioeconomic factors' association with full vaccination. RESULTS: The sample comprised a total of 1107 children 12-24 months. Full vaccination coverage was 70.8%. Vaccination coverage was higher for vaccines administered at younger ages (e.g., birth dose of BCG was 97.0%) than at older ages (e.g., yellow fever at 9 months was 88.2%). Newly introduced vaccines had lower coverage: at 10 weeks, pentavalent 2 was 95.4%, versus 91.2% for PCV 2 and 88.8% for rotavirus 2. Living outside of Greater Accra, home delivery, younger maternal age, urban residence, and more than one child under five in the home were all associated with decreased odds of full vaccination in the adjusted analysis whereas sex of the child, wealth, religion, and maternal education were not associated with full vaccination status. CONCLUSION: Ghana has high overall vaccination rates although disparities in full vaccination by sociodemographic status exist. As vaccine recommendations are revised, it will be important to insure equitable access to vaccination for all children regardless of demographic and socioeconomic background.

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.