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The COVID-19 pandemic prompted widespread closures of primary and secondary schools. Routine testing of asymptomatic students and staff members, as part of a comprehensive mitigation program, can help schools open safely. “Pooling in a pod” is a public health surveillance strategy whereby testing cohorts (pods) are based on social relationships and physical proximity. Pooled testing provides a single laboratory test result for the entire pod, rather than a separate result for each person in the pod. During the 2020-2021 school year, an independent preschool–grade 12 school in Washington, DC, used pooling in a pod for weekly on-site point-of-care testing of all staff members and students. Staff members and older students self-collected anterior nares samples, and trained staff members collected samples from younger students. Overall, 12 885 samples were tested in 1737 pools for 863 students and 264 staff members from November 30, 2020, through April 30, 2021. The average pool size was 7.4 people. The average time from sample collection to pool test result was 40 minutes. The direct testing cost per person per week was $24.24, including swabs. During the study period, 4 surveillance test pools received positive test results for COVID-19. A post-launch survey found most parents (90.3%), students (93.4%), and staff members (98.8%) were willing to participate in pooled testing with confirmatory tests for pool members who received a positive test result. The proportion of students in remote learning decreased by 62.2% for students in grades 6-12 ( P < .001) and by 92.4% for students in preschool to grade 5 after program initiation ( P < .001). Pooling in a pod is a feasible, cost-effective surveillance strategy that may facilitate safe, sustainable, in-person schooling during a pandemic.

Background and objectives Outpatient parenteral antimicrobial therapy (OPAT) for infections has been in use for nearly 40 years, and although it has been found safe and efficacious, its use has been studied primarily among otherwise healthy patients. We aimed to develop and evaluate an OPAT program for patients with cancer, particularly solid tumors. Methods We implemented multiple quality improvement interventions between June 2018 and January 2020. We retrospectively and prospectively collected data on demographics, the completeness of infectious diseases (ID) physician consultation notes, rates of laboratory test result monitoring, ID clinic follow-up, and 30-day outcomes, including unplanned OPAT-related readmissions, OPAT-related emergency center visits, and deaths. Results Completeness of ID provider notes improved from a baseline of 77 to 100% (p p p p = .027). Thirty-day unplanned OPAT-related readmission, ID clinic follow-up, 30-day emergency center visit, and death rates improved without reaching statistical significance. Conclusions Sustained efforts, multiple interventions, and multidisciplinary engagement can improve laboratory test result monitoring among solid tumor patients discharged with OPAT. Although demonstrating a decrease in unplanned readmissions through institution of a formal OPAT program among patients with solid malignancies may be more difficult compared with the general population, the program may still result in improved safety.

Objectives For the correct interpretation of test results, it is important to be aware of drug-laboratory test interactions (DLTIs). If DLTIs are not taken into account by clinicians, erroneous interpretation of test results may lead to a delayed or incorrect diagnosis, unnecessary diagnostic testing or therapy with possible harm for patients. A DLTI alert accompanying a laboratory test result could be a solution. The aim of this study was to test a multicentre proof of concept of an electronic clinical decision support system (CDSS) for real-time monitoring of DLTIs. Methods CDSS was implemented in three Dutch hospitals. So-called ‘clinical rules’ were programmed to alert medical specialists for possible DLTIs based on laboratory test results outside the reference range in combination with prescribed drugs. A selection of interactions from the DLTI database of the Dutch society of clinical chemistry and laboratory medicine were integrated in 43 clinical rules, including 24 tests and 25 drugs. During the period of one month all generated DTLI alerts were registered in the laboratory information system. Results Approximately 65 DLTI alerts per day were detected in each hospital. Most DLTI alerts were generated in patients from the internal medicine and intensive care departments. The most frequently reported DLTI alerts were potassium-proton pump inhibitors (16%), potassium-beta blockers (11%) and creatine kinase-statins (11%). Conclusions This study shows that it is possible to alert for potential DLTIs in real-time with a CDSS. The CDSS was successfully implemented in three hospitals. Further research must reveal its usefulness in clinical practice.

Clinical decision-making relies heavily on making a correct diagnosis. Clinicians have a responsibility to understand the full spectrum of the diagnostic information conveyed by a physical exam finding, laboratory test result, or imaging. Many laboratory tests, such as troponin and B-type natriuretic peptide (BNP), are continuous tests with many possible results. Yet, there is a tendency to dichotomize tests into positive and negative, and use sensitivity and specificity to describe the test characteristics. This approach can lead to waste of important diagnostic information and substandard clinical decision-making. The aim of this paper is to demonstrate the role of ROC curves in developing a more comprehensive understanding of diagnostic information portrayed by continuous tests to augment clinical decision-making. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11606-019-05125-0) contains supplementary material, which is available to authorized users.

INTRODUCTION Clinicians and healthcare professionals rely heavily on health-associated standards, such as reference intervals (RIs), for appropriate laboratory test result interpretation. RIs are commonly partitioned into discrete age/sex bins based on statistical and/or clinical significance. In pediatric hematology, such partitioning does not adequately represent complex variation in analyte concentrations throughout maturation. The objective of this study was to establish continuous RIs for common hematological parameters in the healthy pediatric Canadian Laboratory Initiative on Pediatric Reference Intervals (CALIPER) cohort. METHODS Data from healthy CALIPER children and adolescents (6 months

Objective To identify factors predicting laboratory-positive coronavirus disease (COVID-19) in pediatric patients with acute respiratory symptoms. Study design We conducted a cross-sectional analysis of a prospective cohort study. Methods Data from 1,849 individuals were analyzed. COVID-19 was confirmed (reverse transcription-quantitative polymerase chain reaction) in 15.9% and factors predicting a positive test result were evaluated through prevalence odds ratios (OR) and 95% confidence intervals (CI). Results Increasing age, personal history of obesity, and household contact with a case were associated, in multiple regression model, with increased odds of a positive test result. Young patients residing in areas with higher population-sizes were less likely to be laboratory-confirmed, as wells as those with severe respiratory symptoms. Conclusions Early identification and isolation of children and teenagers with sug-gestive symptoms of COVID-19 is important to limit viral spread. We identified several factors predicting the laboratory test result. Our findings are relevant from a public health policy perspective, particularly after the restart of in-person academic activities., Highlights • Children and teenagers play an important role in the spread of viral pathogens, including SARS-COV-2. • In this manuscript we identified factors associated with the odds of positive COVID-19 test results among children and teenager with acute respiratory symptoms. • Early identification and isolation of underaged individuals with COVID-19 may reduce the related disease burden. • Our findings may be highly relevant, from a public health policy perspective, after the restart of in-person academic activities all around the globe.

Background Diagnostics utility of the obtained laboratory test results strictly depends on their possible interpretation in the context of distinguishing of both the health and disease state as well as the desired effects of therapeutic interventions. For this purpose, it is necessary to compare the obtained results to the reference intervals. Current recommendations obligate each laboratory to determine its own reference intervals for each of examined parameters. Many laboratories are unable to define and implement their own reference intervals because it is an expensive and time-consuming procedure when using a best known - direct method. This problem is particularly evident in hard-to-access populations, such as pediatric and geriatric. An alternative solution designed to determine reference intervals is using indirect methods, which are based on the results of studies performed for diagnostic purposes in outpatients and inpatients and archived in digital medical databases, which may be subjected to statistical analysis. Methods The search for peer-reviewed articles was conducted in PubMed and Scopus databases. Variations of terms: Biological Variation, Reference Interval, Clinical Decision Limits, Laboratory Information System, Medical Laboratory, Direct Method, Indirect Method were used with different combinations of logical operators to ensure exhaustive search results. The original and review publications and recommendations best suited to the presented topic were selected from among the results of searches based on the previous list of terms from the period 2001 - 2019. Results This work presents and critically analyses the currently existing guidelines related to determining and applying reference intervals in medical diagnostic laboratories, as well as to identify both the associated problems and difficulties and perspectives concerning the ways of their establishment and implementation. Conclusions It is crucial to remember that interpretation of a laboratory test result is a process of comparison and it usefulness depends mainly on the adopted reference system or decision limits. The process of establishing reference intervals and decision limits is complex and the choice of appropriate method depends of the many biological and technical factors connected with populations and laboratory equipment differences. The knowledge of advantages and limitations of the reference interval and decision limits allows for significant enhancement of the accuracy in daily clinical practice.

Objective Emergency department (ED) patients with psychiatric chief complaints undergo medical screening to rule out underlying or comorbid medical illnesses prior to transfer to a psychiatric facility. This systematic review attempts to determine the clinical utility of protocolized laboratory screening for the streamlined medical clearance of ED psychiatric patients by determining the clinical significance of individual laboratory results. Methods We searched PubMed, Embase, and Scopus using the search terms "emergency department, psychiatry, diagnostic tests, laboratories, studies, testing, screening, and clearance" up to June 2017 for studies on adult psychiatric patients. This systematic review follows the recommendations of Meta-analysis of Observational Studies in Epidemiology (MOOSE) statement. The quality of each study was rated according to the Newcastle-Ottawa quality assessment scale. Results Four independent reviewers identified 2,847 publications. We extracted data from three studies (n = 629 patients). Included studies defined an abnormal test result as any laboratory result that falls out of the normal range. A laboratory test result was deemed as "clinically significant" only when patient disposition or treatment plan was changed because of that test result. Across the three studies the prevalence of clinically significant results were low (0.0%-0.4%). Conclusions The prevalence of clinically significant laboratory test results were low, suggesting that according to the available literature, routine laboratory testing does not significantly change patient disposition. Due to the paucity of available research on this subject, we could not determine the clinical utility of protocolized laboratory screening tests for medical clearance of psychiatric patients in the ED. Future research on the utility of routine laboratory testing is important in a move toward shared decision making and patient-centered health care.

Appropriate handling of ‘critical’ laboratory test result values is an essential component of timely, quality patient care. While interinstitutional variability exists,1 critical values have historically been defined as potentially ‘life-threatening’ if not attended to quickly,2 necessitating prompt notification of a responsible clinician. Given patient safety implications, timely communication of results to a provider is a common regulatory element, including: (1) Joint Commission patient safety goals,3 (2) Clinical Laboratory Improvement Amendments4 and (3) the International Organization for Standardization.5 Inpatient values comprise a significant proportion of notifications,6 and among inpatients, oncology inpatients typically constitute a substantial volume.7 After laboratory result generation, contacting a responsible clinician can be complicated by multiple barriers. Previous approaches to improve this process include using call centres, automatic pager notifications and automatic personal digital assistant (PDA) telephone notifications.8–11 In our hospital, the inpatient haematology/oncology/stem cell transplantation (H/O) service had an overall notification success rate substantially lower than the hospital average as an effect of the large volume of critical results that typically returned in a short time period at certain times of day, leading to a multidisciplinary initiative to improve the notification process. In our free-standing 360-bed paediatric hospital, ‘overall’ successful critical result notification must: (1) be acknowledged by a licenced individual provider (LIP) and (2) meet criteria for ‘timely’ notification, indicating that both outgoing notification from the laboratory/call centre and LIP acknowledgement occur within 30 min of result generation. H/O inpatients account for 15%–20% of all inpatient critical values but had a significantly lower overall successful notification rate than the hospital average. Timely outgoing notification occurred >90%, but timely LIP acknowledgement was

A reference interval (RI)10 is a standard component of reporting a laboratory result and is important to transform a numerical value into clinically meaningful information. An RI is intended to inform the clinical care provider that laboratory values within the interval indicate a nondiseased condition. The most common approach is to base an RI on the central 95% of laboratory test values observed for a reference population that is free of diseases that influence that laboratory test result. Because many diseases are asymptomatic, it becomes difficult to qualify people for a nondiseased condition, thus biasing the selection of reference individuals. Furthermore, information on the full complement of disease conditions that influence a laboratory test may be unknown. Thus, RIs may be influenced by inappropriately selected reference populations. Another limitation in determining an RI is obtaining an adequate sample of a reference population to make an estimate of the central 95% of results with suitable uncertainty to be meaningful for interpreting a test result. The sample size requirement becomes even larger when partitioning by sex, age, ethnicity, menstrual cycle, and other parameters is necessary for meaningful RIs. CLSI Guideline EP28-A3c describes consensus approaches and some limitations for establishing and verifying RIs. However, some of the approaches in this guideline are statistically underpowered such that uncertainties in the RIs may not be appreciated. A particularly challenging situation is the requirement for laboratories to establish an RI for a laboratory developed measurement procedure (MP) or to verify the RIs proposed by the manufacturer of an in vitro diagnostic (IVD) MP. Identifying a suitable reference population for either requirement can be very challenging. Evolution in laboratory practice is needed to enable appropriate RIs to be adopted by laboratories. We asked experts with different perspectives to address issues we all face in establishing or …

Background A wealth of clinical information is buried in free text of electronic health records (EHR), and converting clinical information to machine-understandable form is crucial for the secondary use of EHRs. Laboratory test results, as one of the most important types of clinical information, are written in various styles in free text of EHRs. This has brought great difficulties for data integration and utilization of EHRs. Therefore, developing technology to normalize different expressions of laboratory test results in free text is indispensable for the secondary use of EHRs. Methods In this study, we developed a knowledge-based method named LATTE (transforming lab test results), which could transform various expressions of laboratory test results into a normalized and machine-understandable format. We first identified the analyte of a laboratory test result with a dictionary-based method and then designed a series of rules to detect information associated with the analyte, including its specimen, measured value, unit of measure, conclusive phrase and sampling factor. We determined whether a test result is normal or abnormal by understanding the meaning of conclusive phrases or by comparing its measured value with an appropriate normal range. Finally, we converted various expressions of laboratory test results, either in numeric or textual form, into a normalized form as “specimen-analyte-abnormality”. With this method, a laboratory test with the same type of abnormality would have the same representation, regardless of the way that it is mentioned in free text. Results LATTE was developed and optimized on a training set including 8894 laboratory test results from 756 EHRs, and evaluated on a test set including 3740 laboratory test results from 210 EHRs. Compared to experts’ annotations, LATTE achieved a precision of 0.936, a recall of 0.897 and an F1 score of 0.916 on the training set, and a precision of 0.892, a recall of 0.843 and an F1 score of 0.867 on the test set. For 223 laboratory tests with at least two different expression forms in the test set, LATTE transformed 85.7% (2870/3350) of laboratory test results into a normalized form. Besides, LATTE achieved F1 scores above 0.8 for EHRs from 18 of 21 different hospital departments, indicating its generalization capabilities in normalizing laboratory test results. Conclusion In conclusion, LATTE is an effective method for normalizing various expressions of laboratory test results in free text of EHRs. LATTE will facilitate EHR-based applications such as cohort querying, patient clustering and machine learning. Availability LATTE is freely available for download on GitHub ( https://github.com/denglizong/LATTE ).

Background Interpreting hematology analytes in children is challenging due to the extensive changes in hematopoiesis that accompany physiological development and lead to pronounced sex- and age-specific dynamics. Continuous percentile charts from birth to adulthood allow accurate consideration of these dynamics. However, the ethical and practical challenges unique to pediatric reference intervals have restricted the creation of such percentile charts, and limitations in current approaches to laboratory test result displays restrict their use when guiding clinical decisions. Methods We employed an improved data-driven approach to create percentile charts from laboratory data collected during patient care in 10 German centers (9,576,910 samples from 358,292 patients, 412,905–1,278,987 samples per analyte). We demonstrate visualization of hematology test results using percentile charts and z-scores (www.pedref.org/hematology) and assess the potential of percentiles and z-scores to support diagnosis of different hematological diseases. Results We created percentile charts for hemoglobin, hematocrit, red cell indices, red cell count, red cell distribution width, white cell count and platelet count in girls and boys from birth to 18 years of age. Comparison of pediatricians evaluating complex clinical scenarios using percentile charts versus conventional/tabular representations shows that percentile charts can enhance physician assessment in selected example cases. Age-specific percentiles and z-scores, compared with absolute test results, improve the identification of children with blood count abnormalities and the discrimination between different hematological diseases. Conclusions The provided reference intervals enable precise assessment of pediatric hematology test results. Representation of test results using percentiles and z-scores facilitates their interpretation and demonstrates the potential of digital approaches to improve clinical decision-making.

OBJECTIVE Point-of-care testing (POCT) is a commonly used technology that hastens the time to laboratory results in emergency departments (ED). We evaluated an ED-based POCT program on ED length of stay (LOS) and time to care, coupled with qualitative interviews of local ED stakeholders. METHODS We conducted a mixed-methods study (2012-2016) to examine the impact of POCT in a single, community ED. The quantiative analysis involved an observational before-after study comparing time to laboratory test result (POC troponin or POC chemistry) and ED LOS after implementation of POCT, using a propensity-weighted interrupted time series analysis (ITSA). A complementary qualitative analysis involved five semistructured interviews with staff using grounded theory on the benefits and challenges to ED POCT. RESULTS A total of 47,399 ED visits were included in the study (24,705 in the preintervention period and 22,694 in the postintervention period). After POCT implementation, overall laboratory testing increased marginally from 61% to 62%. Central laboratory troponin and chemistry declined by > 50% and was replaced by POCT. Prior to POCT implementation, time to troponin and chemistry had declined steadily due to other improvements in laboratory efficiency. After POCT implementation, there was an immediate 20-minute further decline (p

OBJECTIVES Laboratory tests are usually requested for monitoring during outpatient parenteral antimicrobial therapy (OPAT), but these recommendations are not always followed. The purpose of this study was to determine whether rehospitalization during the OPAT course is associated with the availability of these test results to the treating physician. METHODS Electronic health records (EHRs) from all patients in the Cleveland Clinic OPAT registry with start dates from 1 January to 28 February 2011 were reviewed in a retrospective cohort study. Comprehensive data on patient and OPAT characteristics were obtained for the first OPAT course per patient. Availability of laboratory test results was defined as documentation of results of at least one recommended test in the health system's EHR. Proportions of patients rehospitalized were compared for OPAT courses with test results available and non-available. Adjustments were made for patient age, hospital length of stay, anticipated OPAT duration, OPAT site and Charlson comorbidity index score. RESULTS Four hundred patients received OPAT during the study period; 60% at home, 36% in skilled nursing facilities or long-term acute care facilities and 4% in other settings. Recommended monitoring laboratory test results were available to infectious disease physicians in 291 (73%) OPAT episodes. There were 82 patient readmissions (21%) while on OPAT. In a multivariable logistic regression model, non-availability of recommended test results was independently associated with readmissions while on OPAT (adjusted OR 2.53; 95% CI 1.36-4.73). CONCLUSIONS Non-availability of recommended test results to treating physicians for patients on OPAT is associated with increased readmissions during OPAT.

A diagnosis of multiple myeloma (MM) is difficult to make on the basis of any single laboratory test result. Accurate diagnosis of MM generally results from a number of costly and invasive laboratory tests and medical procedures. The aim of this work is to find a new, highly specific and sensitive method for MM diagnosis. Serum samples were tested in groups representing MM (n = 54) and non-MM (n = 108). These included a subgroup of 17 plasma cell dyscrasias, a subgroup of 17 reactive plasmacytosis, 5 B cell lymphomas, and 7 other tumors with osseus metastasis, as well as 62 healthy donors as controls. Bioinformatic calculations associated with MM were performed. The decision algorithm, with a panel of three biomarkers, correctly identified 24 of 24 (100%) MM samples and 46 of 49 (93.88%) non-MM samples in the training set. During the masked test for the discriminatory model, 26 of 30 MM patients (sensitivity, 86.67%) were precisely recognized, and all 34 normal donors were successfully classified; patients with reactive plasmacytosis were also correctly classified into the non-MM group, and 11 of the other patients were incorrectly classified as MM. The results suggested that proteomic fingerprint technology combining magnetic beads with MALDI-TOF-MS has the potential for identifying individuals with MM. The biomarker classification model was suitable for preliminary assessment of MM and could potentially serve as a useful tool for MM diagnosis and differentiation diagnosis.

Introduction: Laboratory information is generated when a meaning is given to certain data. This is usually achieved by comparing a laboratory test result with the reference range/decisional limit (RL), and by providing consultation for the interpretation of data, advice, and follow-up testing. Aim: In this paper, we investigate factors affecting the conversion of data into useful information with regard to biochemical markers of myocardial damage (CK-MB mass, myoglobin, and troponins), in view of their importance in detecting myocardial necrosis. Our aim was to report results obtained in order to verify the consensus between laboratories with reference to interpretative comments and the reference ranges/decisional limits added to clinical reports. Methods: A questionnaire and simulated medical reports on three different patients were distributed to participants (94 laboratories) in the 2001 cycle of the External Quality Assessment (EQA). Moreover, we analysed 113 medical reports sent by laboratories during the most recent EQA cycle 2002, and checked the number of different RLs used, both independent and within the diagnostic system used. We also compared each laboratory result of a control sample, obtained in the 2002 cycle, with declared RL in order to verify the clinical significance of results (‘‘normal’’ or ‘‘pathological’’) for troponin I and CK-MB. Results: Our findings show that few laboratories regularly add interpretative comments to medical reports. On the contrary, they cooperate with clinicians who require consultation, advice, and information for the appropriate use of biochemical markers. There is a general consensus among participants regarding probable syndromes suggested by the interpretation of the same result and most laboratories also agree on further investigations to be carried out for several diseases. Concerning RL, the data demonstrate that numerous different RLs are used to report the results of the biochemical markers evaluated, both when considered independent of the diagnostic system used and within the diagnostic system used. Discussion and conclusions: The biochemist does not have the opportunity to verify the efficacy of the interpretation that he/she provided. An audit of this activity is therefore required to allow the laboratory to monitor its own performance and to assure good practice. The evaluation of interpretative comments, through specific surveys, should be a prime objective of EQA organisers. Well-designed EQA programs can, moreover, support laboratories in establishing appropriate RL and in verifying the clinical significance of their results with respect to that of other laboratories. Our survey on interpretative comments and the analysis of the RLs further demonstrate how laboratory medicine can contribute to the objective evaluation of the patients’ health status. D 2003 Elsevier Science B.V. All rights reserved.

In 1978, Casscells et al1 published a small but important study showing that the majority of physicians, house officers, and students overestimated the positive predictive value (PPV) of a laboratory test result using prevalence and false positive rate. Today, interpretation of diagnostic tests is even more critical with the increasing use of medical technology in health care. Accordingly, we replicated the study by Casscells et al1 by asking a convenience sample of physicians, house officers, and students the same question: “If a test to detect a disease whose prevalence is 1/1000 has a false positive rate of 5%, what is the chance that a person found to have a positive result actually has the disease, assuming you know nothing about the person’s symptoms or signs?”

A recent American Medical Association report highlighted failures in communication of abnormal test results as an important but understudied facet of improving safety in ambulatory care.1 Because many outpatient test results are not life-threatening and don’t require verbal communication, health information technology (IT) has potential to reliably transmit result information in the fragmented outpatient setting. Thus, few will disagree that communication of abnormal test results is an obvious context where advantages of health IT will be observed. In this issue of JGIM, Callen et al. report the results of a timely systematic review of 19 studies that documented quantitative evidence of test results not followed up in ambulatory settings.2 They found wide variation in abnormal results lacking follow-up: 7 % to 62 % for laboratory, and 1 % to 36 % for imaging tests. Although evidence of the effectiveness of electronic test management systems was limited, there was a general trend towards improved follow-up in electronic systems. In another article in this issue, El-Kareh et al. discuss the results of a randomized controlled trial that put electronic communication to the test. The authors studied the effectiveness of sending microbiology test result alerts via a secure, internal e-mail system to clinicians when results were finalized post-discharge.3 They found better documented evidence of appropriate follow-up within 3 days in the intervention group (28 % vs. 13 % in controls). Neither group’s laboratory follow-up rate was particularly encouraging. On the bright side, both studies used distinctly different research approaches to reach similar conclusions, i.e., application of information and communication technologies, such as electronic health records (EHRs) with alerting capability, can increase the likelihood of appropriate test result follow-up. In paper-based systems, evaluating evidence of follow-up is itself challenging. On the other hand, both articles remind us that using EHR-based technology by itself does not entirely solve the problem of failure to follow up test results. Callen et al., as well as others, have made a strong case for addressing these failures based on safety implications. Additionally, Stage 2 meaningful EHR use (slated for implementation in 2014) includes laboratory test result reporting criteria. Time is now ripe for novel approaches to understand and improve this complex problem. The use of technology in the complex healthcare system must take into context the social environment where technology is embedded. For example, Callen et al. found lack of clear policies and procedures in relation to test result follow-up. We previously identified ambiguity of responsibility for test result follow-up to be a key factor in failure to follow up abnormal results.4 Several EHRs now use asynchronous alert notifications to transmit results, but providers often receive many other types of notifications in their electronic in-box. We found that primary care providers (PCPs) receive a mean of 57 alerts a day in an integrated delivery system’s EHR, all with new information they need to process and/or act upon.5 Important information about abnormal results might get buried among other alerts. To help understand the complexities involved with electronic communication of test results and facilitate progress in developing multifaceted solutions, a “sociotechnical” approach is needed. In our work, we use an eight-dimension sociotechnical model to study both problems and solutions related to safe and effective EHR implementation and use.6 In the sections below, we illustrate the usefulness of this model by discussing each of its eight dimensions, as applied to issues raised by the two studies. We also take the liberty of making several recommendations that might be useful to reduce failures in test result follow-up in EHR-based systems. Hardware/Software: To maintain superiority over paper, EHRs must be configured to ensure that results are reported to the correct provider in a timely fashion. Thus, all test orders should be placed via a Computer-based Provider Order Entry (CPOE) system. Orders should be transmitted in a coded format to the entity performing the test, and the transmission should occur via a two-way system-to-system interface that can send orders and receive results. Otherwise, results might not make it back into the EHR in a form that allows clinical decision support interventions (e.g., alert for abnormal creatinine will not fire while entering an order for metformin). Clinical Content: Results should be stored as structured/coded data to facilitate reporting and tracking of results. This feature enabled El-Kareh and colleagues to extract results from the EHR, and can facilitate result-tracking functions. Institutions must also define standardized result categories and definitions (e.g., critical, normal, etc.) to facilitate prioritization and reporting. For instance, certain levels of abnormalities can be flagged in the EHR for more immediate action based on urgency. Care should be taken to avoid flagging borderline or clinically insignificant results as urgent. User Interface: A poor user interface can lead providers to miss critical information. EHRs should have result review screens that ensure that all critical information is displayed on one screen (i.e., no scrolling is required) and all columns are sufficiently wide to allow users to see all pertinent information. In addition, users should be able to sort, or filter, results by date, type, patient, or urgency.7 Personnel: Providers should be trained to process their alerts in a timely manner and document follow-up and communication of results to patients in the EHR. Poor documentation is widely prevalent and might be one reason to explain the low follow-up rates reported in El-Kareh et al.’s study. Workflow/Communication: Institutions must avoid partial use of EHRs for test result management (i.e., results or notes, but not both, available electronically8), because this leads to a higher risk of test result follow-up failures. Workflows related to certain high-risk areas (tests ordered by residents, part-time physicians, emergency deparment physicians; send-out tests; and post-discharge results) must be well-defined. This process should include creation of back-up procedures (including use of surrogates) and fail-safe escalation systems to safeguard against results “falling through the cracks”. To what extent this was done, if at all, in the El-Kareh study is unclear, and thus a seemingly straightforward technological intervention might not have reached its full potential. Additionally, practices must create robust processes to send both normal and abnormal test results to patients. In the Veterans’ Health Administration (VA), providers can generate letters though EHR templates, which are then sent to patients through centralized mailing facilities. Many institutions use web-based portals to make results accessible to patients, and some directly notify patients bypassing provider review. Whether the latter approach reduces follow-up failures is unclear.9 Internal Organizational Policies, Procedures, Culture and Environment: Responsibility for test result follow-up is an under-recognized and underemphasized contributory factor in follow-up failures. Responsibility should always be clear, and can be delegated to someone as long as that procedure is clear to both parties. It is unclear how physicians in the El-Kareh study perceived their test result follow-up responsibilities; many that did not answer the survey or follow up appropriately might have attributed this responsibility to someone else (e.g., inpatient physician thought that the PCP was responsible post-discharge). We also recommend that all institutions/clinics should have an annually updated, written policy on all aspects of test result management (e.g., provider notification, patient notification, follow-up responsibilities).10 This document should define processes and procedures for test result communication, including which results are critical and need verbal communication. Institutions should also maintain updated contact information for all providers and patients. Some of the e-mail alerts sent by the investigators might not have reached the study physicians. External Rules and Regulations: In 2009, the VA released a policy directive requiring communication of all test results to patients within 14 calendar days after the test result is available to the ordering practitioner. To the best of our knowledge, there are no other federal or state policies giving guidance on definitions and measurement of timeliness of test result follow-up. Measurement and Monitoring: The VA is now instituting a measurement system for test results follow-up, and we encourage other institutions to do the same. Logs of test result values, alerts, and provider acknowledgment of alert receipt (results review) could be used for this purpose. However, acknowledgment of a test result receipt does not guarantee that the follow-up action has taken place;4 alternative measurement systems should be in place to monitor test result follow-up.

Objectives To describe the management of and satisfaction with laboratory testing, and desirability of laboratory health information technology in the nursing home setting. Design Cross-sectional study using an Internet-based survey. Participants and Setting National sample of 426 nurse practitioners and 308 physicians who practice in the nursing home setting. Measurements Systems and processes available for ordering and reviewing laboratory tests, laboratory test result management satisfaction, self-reported delays in laboratory test result review, and desirability of computerized laboratory test result management features in the nursing home setting. Results A total of 96 participants (48 physicians and 48 nurse practitioners) completed the survey, for an overall response rate of 13.1% (96/734). Of the survey participants, 77.1% had worked in the nursing home setting for more than 5 years. Over half of clinicians (52.1%) reported 3 or more recent delays in receiving laboratory test results. Only 43.8% were satisfied with their laboratory test results management. Satisfaction was associated with keeping a list of laboratory orders and availability of computerized laboratory test order entry. In the nursing home, 35.4% of participants reported the ability to electronically review laboratory test results, 12.5% and 10.4% respectively had computerized ordering of chemistry/hematology and microbiology/pathology tests. The following 3 features were rated most desirable in a computerized laboratory test result management system: showing abnormal results first, warning if a test result was missed, and allowing electronic acknowledgment of test results. Conclusion Delays in receiving laboratory test results and dissatisfaction with the management of laboratory test result information are commonly reported among physicians and nurse practitioners working in nursing homes. Test result management satisfaction was associated with computerized order entry and keeping track of ordered laboratory tests, suggesting that implementation of certain health information technology could potentially improve quality of care.

This article introduces the use of information theoretic concepts such as entropy, S, for the evaluation of laboratory test results, and it offers a new measure of information, 1 – S, which tells us just how far toward certainty a laboratory test result can predict a binary outcome. The derived method is applied to the serum markers troponin I and prostate-specific antigen and to histologic grading of HER-2/neu staining, to cytologic diagnosis of cervical specimens, and to the measurement of tumor thickness in malignant melanoma. Not only do the graphic results provide insight for these tests, they also validate prior conclusions. Thus, this information theoretic approach shows promise for evaluating and understanding laboratory test results. Most would agree that the major purpose for laboratory tests is to provide information about the presence or absence of disease or other critical medical outcomes for patients. Yet, to my knowledge, there is no widely accepted, formal measure for the amount of information that laboratory tests provide. When evaluating new laboratory tests, pathologists resort to a variety of concepts and statistics evolved from probability theory, including sensitivity, specificity, positive predictive value, negative predictive value, efficiency, and likelihood ratios; however, none of these carries the name of information. Pathologists, nevertheless, are attentive to the field of “informatics,” which seems to deal with computer hardware, software, various algorithmic approaches to problem solving, patient databases, and graphics; but to my knowledge, the field of informatics offers no commonly used measure of the information that laboratory tests provide. For such a measure, one must turn to the field of information theory, which evolved from probability theory and from statistical mechanics, and that came to be recognized as

Background Many medical errors occur during the laboratory testing process, including lost test results. Patient inquiry concerning results often represents the final safety net for locating lost results. This qualitative study sought to identify, from a patient perspective, specific preferences and factors that influence the process of communicating normal (negative) laboratory test results to patients. Methods We conducted 30-minute guided interviews with 20 adult patients. Patients were recruited from two practice-based research networks in Colorado that were participating in a medical errors study. A semi-structured interview elicited the participant's experience with and preference for laboratory test result notification. Quantitative descriptive statistics were generated for demographic and preference data. Qualitative results were analyzed by a team of experienced qualitative researchers using multiple styles of qualitative analyses, including a template approach and an editing approach. Results Ninety percent of participants wanted to be notified of all tests results. Important issues related to notification included privacy, responsive and interactive feedback, convenience, timeliness, and provision of details. Telephone notification was preferred, followed by regular mail. Electronic notification was perceived as uncomfortable because it was not secure. While 65% preferred being notified by a provider, participants acknowledge that this may be impractical; thus, they wanted to be notified by someone knowledgeable enough to answer questions. Participants do not normally discuss their preferences for test result notification with their providers. Conclusion Privacy, responsive and interactive feedback, convenience, and timeliness with detailed information may be critical for patient satisfaction and for improving patient safety, and are features that may be incorporated into emerging communication channels.

Using the capabilities of the HELP medical information system at LDS Hospital, a Computerized Laboratory Alerting System (CLAS) was developed. CLAS monitors and alerts for the presence of life-threatening conditions in hospitalized patients which are indicated by laboratory test results. Alerts are posted on computer terminals on the hospital's nursing divisions, where they are reviewed and acknowledged by hospital staff so that appropriate treatment can be rapidly instituted. CLAS was evaluated to determine its effectiveness in relaying alerts to the clinical staff, and improvements were made to develop an effective user interface. Initial average alert response times on nursing divisions ranged from 5.1 to 58.2 hr. The average alert response time dropped to 3.6 hr when alert review was integrated with laboratory result review, and to 0.1 hr after installation of a flashing light to notify hospital staff of the presence of new alerts.

The function of the clinical pharmacokinetic service (CPS) in University Hospital is described. A methodological procedure was developed for routine interpretation of specified drug serum levels. Work lists that identify analytical procedures to be included for clinical pharmacokinetic evaluation are prepared daily. The results of all analyses of serum drug levels are evaluated by a pharmacist who is trained in clinical pharmacokinetics. Patient variables that influence serum levels of drugs are mathematically manipulated by program logic. Projections of expected drug levels as a result of dosing regimens are made and compared to measured laboratory results. Iterative programming that modifies projections on the basis of actual measurements is employed to determine individual drug dosing regimens that provide therapeutic/nontoxic serum levels of drugs. The drug/test interference system, which accesses the CPS data base, provides information concerning the potential physiologic, therapeutic, or toxic effect of drugs on biochemical substances. The system allows display of data concerning each drug before it is administered. Information concerning the date and time of initiation and termination of drug therapy allows for a warning comment to be attached automatically to the appropriate laboratory test result if interference is indicated.

Perkal's discriminating function may be used for differential diagnosis by taking many clinical characteristics, i.e. medical history, physical examination and laboratory test results. In this paper, Perkal's function is applied to the differential diagnosis of two types of diabtes. This original mathematical method may be used for the differential diagnosis of many other morbid conditions by processing a large amount of clinical data with a digital computer.

The determination of frequency value (percentile limits) and the classification of the different variation factors allow us to define more and more homogeneous subpopulations as we use these factors for sorting. Using as our study population those persons coming to the Centre for Preventive Medicine, we were able to: (a) Describe and measure the significance and importance of physiological variations or of variations attributed to age—the latter largely related only to excessive weight, which it seems to us is often the case. (b) Establish a classification for variation factors; the recapitulatory table should be useful to clinical chemists in helping physicians interpret a laboratory test result that falls within the zone of incertitude. (c) Suggest a preliminary group of reference values for healthy subjects, to be used in interpreting a laboratory test in this way.