Identifying heart failure in patients with chronic obstructive lung disease through the Canadian Primary Care Sentinel Surveillance Network in British Columbia: a case derivation study.

BACKGROUND: Heart failure (HF) poses a substantial global health burden, particularly in patients with chronic obstructive pulmonary disease (COPD). The objective of this study was to validate an electronic medical record-based definition of HF in patients with COPD in primary care practices in the province of British Columbia, Canada. METHODS: We conducted a cross-sectional retrospective chart review from Sept. 1, 2018, to Dec. 31, 2018, for a cohort of patients from primary care practices in BC whose physicians were recruited through the BC node of the Canadian Primary Care Sentinel Surveillance Network. Heart failure case definitions were developed by combining diagnostic codes, medication information and laboratory values available in primary care electronic medical records. These were compared with HF diagnoses identified through detailed chart review as the gold standard. Sensitivity, specificity, negative (NPV) and positive predictive values (PPV) were calculated for each definition. RESULTS: Charts of 311 patients with COPD were reviewed, of whom 72 (23.2%) had HF. Five categories of definitions were constructed, all of which had appropriate sensitivity, specificity and NPV. The optimal case definition consisted of 1 HF billing code or a specific combination of medications for HF. This definition had an excellent specificity (93.3%, 95% confidence interval [CI] 89.4%-96.1%), sensitivity (90.3%, 95% CI 81.0%-96.0%), PPV (80.2%, 95% CI 69.9%-88.3%) and NPV (97.0%, 95% CI 93.8%-98.8%). INTERPRETATION: This comprehensive case definition improves upon previous primary care HF definitions to include medication codes and laboratory data, along with previously used billing codes. A case definition for HF was derived and validated and can be used with data from electronic medical records to identify HF in patients with COPD in primary care accurately.

No lab is an island: universal coding of laboratory test names.

The local laboratory with a local client-base, that never needs to exchange information with any outside entity, is a dying breed. As marketing channels, animal movement, and reporting requirements become increasingly national and international, the need to communicate about laboratory tests and results grows. Local and proprietary names of laboratory tests often fail to communicate enough detail to distinguish between similar tests. To avoid a lengthy description of each test, laboratories need the ability to assign codes that, although not sufficiently user-friendly for day-to-day use, contain enough information to translate between laboratories and even languages. The Logical Observation Identifiers Names and Codes (LOINC) standard provides such a universal coding system. Each test-each atomic observation-is evaluated on 6 attributes that establish its uniqueness at the level of clinical-or epidemiologic-significance. The analyte detected, analyte property, specimen, and result scale combine with the method of analysis and timing (for challenge and metabolic type tests) to define a unique LOINC code. Equipping laboratory results with such universal identifiers creates a world of opportunity for cross-institutional data exchange, aggregation, and analysis, and presents possibilities for data mining and artificial intelligence on a national and international scale. A few challenges, relatively unique to regulatory veterinary test protocols, require special handling.

Correlation between Pretreatment Hematologic Parameters and Cervical Cancer Patients Undergoing Hysterectomy: a Retrospective Study.

BACKGROUND: The objective of this study is to investigate the correlation of mean platelet volume (MPV), MPV/ platelet count, and monocyte to lymphocyte ratio (MLR) between cervical cancer patients and healthy people and to evaluate the value of those parameters in early diagnosis of cervical cancer. METHODS: The study population included 137 cervical cancer patients undergoing hysterectomy and 113 healthy controls. The clinical features (age, pathology type, tumor staging, and tumor size) were collected from the hospital information system. The hematology parameters (white blood cell, red blood cell, hemoglobin, platelet count, neutrophil, lymphocyte, monocyte, mean platelet volume, platelet distribution width) are obtained in the laboratory information system. RESULTS: We found that the monocyte count and MLR value are higher in the cervical cancer group. The MPV and MPV/platelet are lower in the cervical cancer group. The receiver operating characteristic (ROC) analysis shows that MPV+MLR can generate a moderate specificity with 71.68%, sensitivity with 65.69%, and AUC with 0.718 to distinguish cervical cancer and healthy people. CONCLUSIONS: MPV/platelet and MLR may be helpful for the early diagnosis of cervical cancer. A larger clinical data analysis is necessary to evaluate the diagnostic value of hematologic parameters in cervical cancer.

Relevance or performance: potential savings associated with verification of prior results before performing microbiology analysis.

OBJECTIVE: In an era of rising healthcare expenditures, it is critical to find ways to decrease cost. The objective of this study is to evaluate the number of repeated tests and the associated cost savings in a university-affiliated hospital. METHODS: The following 7 microbiology analysis were assessed for nonrepeat testing: HCV antibody, HBV core antibody, CMV IgG, rubella IgG, Treponema pallidum antibodies, Clostridioides difficile toxin detection, and vancomycin-resistant enterococci PCR. Presence of a prior positive result leads to the cancellation of subsequent orders. RESULTS: Percentages of not repeated test ranged from 0.1% to 21.4%. Rubella IgG had the highest proportion of unnecessary repeat testing. Total cost savings were estimated at $33,627 for 2016. CONCLUSION: Unnecessary repeated microbiologic test can account for a non-negligible part of total volume test. Use of an automated software to detect unnecessary repeated microbiologic test through laboratory information system can generate important savings.

Diagnostic Utility of Complement Serology for Atypical Hemolytic Uremic Syndrome.

OBJECTIVE: To investigate the clinical utility of a 9-analyte complement serology panel (COMS) covering complement function (CH50 and AH50), components (C3, C4), factor B (CFB), factor H, and activation markers (C4d, Bb, and soluble membrane attack complex) for the diagnosis of atypical hemolytic uremic syndrome (aHUS). METHODS: Physician orders for COMS from January 19, 2015, through November 4, 2016, were reviewed. Demographic characteristics, patient diagnosis, and laboratory parameters were recorded. RESULTS: There were 177 COMS orders for 147 patients. The median patient age was 44.9 years (range, 0.9-88.0 years). Common reasons for ordering COMS included monitoring and diagnosis of C3 glomerulopathy and renal dysfunction and differentiation of aHUS from other thrombotic microangiopathies (TMAs). Forty-four patients had COMS ordered for TMAs: 8 had aHUS and all had 1 or more abnormalities within the alternative pathway of complement. Although the sensitivity of this finding for the diagnosis of aHUS is 100%, the specificity is only 28%, with a positive likelihood ratio of 1.39. Patients with aHUS had lower CH50, C3, and CFB than did those with secondary non-aHUS TMA (all P<.01). A combined CFB of 20.9 mg/dL or less and CH50 of 56% or less led to sensitivity of 75% with increased specificity of 88.9% and a diagnostic odds ratio of 24. CONCLUSION: A COMS abnormality should not be interpreted in isolation. In conjunction with clinical presentation, a decrease in both CFB and CH50 may be an important clue to support the diagnosis of aHUS.

Ganglionic Antibody Level as a Predictor of Severity of Autonomic Failure.

OBJECTIVE: To assess antibody level as a test of autonomic failure (AF) associated with ganglionic nicotinic acetylcholine receptor antibody (AChR-Ab) autoimmunity. PATIENTS AND METHODS: We searched the Mayo Clinic laboratory database of 926 ganglionic AChR-Ab-seropositive patients seen at our institution between October 1, 1997, and April 1, 2015, for initial level of 0.05 nmol/L or higher and contemporaneous autonomic reflex screen (standardized evaluation of adrenergic, cardiovagal, and sudomotor functions) from which Composite Autonomic Scoring Scale (CASS) scores could be calculated. RESULTS: Of 289 patients who met inclusion criteria, 163 (56.4%) were women, median age was 54 years (range, 10-87 years), median antibody level was 0.11 nmol/L (range, 0.05-22.10 nmol/L), and median CASS total score was 2.0 (range, 0-10). Using receiver operating characteristic curve analysis, a level above 0.40 nmol/L predicted severe AF (CASS score, ≥7) with 92% specificity and 56% sensitivity. For at least moderate AF (CASS score ≥4 and anhidrosis ≥25%), a level of at least 0.20 nmol/L had 80% specificity and 59% sensitivity. Levels below 0.20 nmol/L were not predictive of the presence or absence of AF. For predicting orthostatic hypotension, ganglionic AChR-Ab level had excellent specificity above 0.4 nmol/L but lacked sensitivity. Autoantibodies to additional targets were present in 61 patients (21.1%). CONCLUSION: Ganglionic AChR-Ab level of at least 0.40 nmol/L is a moderately sensitive and highly specific marker for severe AF, as is a level of at least 0.20 nmol/L for moderate AF if CASS score is coupled with anhidrosis of 25% or more, among patients with suspected ganglionic AChR-Ab autoimmune autonomic ganglionopathy. Antibody levels of less than 0.20 nmol/L have little clinical importance in the absence of clinical AF.

A laboratory information management system for the analysis of tritium (3H) in environmental waters.

Accurate and precise measurements of low levels of tritium (3H) in environmental waters are difficult to attain due to complex steps of sample preparation, electrolytic enrichment, liquid scintillation decay counting, and extensive data processing. We present a Microsoft Access™ relational database application, TRIMS (Tritium Information Management System) to assist with sample and data processing of tritium analysis by managing the processes from sample registration and analysis to reporting and archiving. A complete uncertainty propagation algorithm ensures tritium results are reported with robust uncertainty metrics. TRIMS will help to increase laboratory productivity and improve the accuracy and precision of 3H assays. The software supports several enrichment protocols and LSC counter types. TRIMS is available for download at no cost from the IAEA at www.iaea.org/water.

Changing the electronic request form proves to be an effective tool for optimizing laboratory test utilization in the emergency department.

OBJECTIVES: Appropriate laboratory utilization more often than not needs to be initiated by the laboratory. This study was performed to analyze the impact on test ordering patterns in the emergency department obtained by omitting certain tests from the electronic tick box request form. The tests could still be ordered by writing the full name of the test or by a phone call. METHODS: Erythrocyte sedimentation rate (ESR), fibrinogen, aspartate aminotransferase (AST), calcium and lipase were omitted from the electronic request form and could subsequently be ordered either by phone or a typed-in request. A reflex testing protocol was elaborated for reduction of creatine kinase (CK) and CK-MB analyses. All interventions were introduced with prior consultation with clinical staff and according to current guidelines. The reduction of test orders and costs in the post-intervention period was assessed. All data were retrieved retrospectively from the laboratory information system (LIS). RESULTS: Disappearance from the tick box request form resulted in a significant decrease in the number of requests for targeted tests in the post-intervention year, mostly affecting AST and fibrinogen (83% and 79% reduction of ordering, respectively), followed by a 58% reduction in calcium orders, and 54% and 43% reductions in ESR and lipase requests, respectively. A substantial reduction in CK requests was also observed, while CK-MB requests almost disappeared. Annual cost savings that emerged from all implemented interventions were estimated to be 19,445€. CONCLUSION: Significant reduction in ordering of selected tests was achieved simply by limiting their availability in hospital computerized order entry (COE) system. The present data suggest that removal of laboratory tests from the electronic request form can be an effective tool for changing physicians' test ordering behavior.

The Effects of Computerized Clinical Decision Support Systems on Laboratory Test Ordering: A Systematic Review.

CONTEXT: - Inappropriate laboratory test ordering has been shown to be as high as 30%. This can have an important impact on quality of care and costs because of downstream consequences such as additional diagnostics, repeat testing, imaging, prescriptions, surgeries, or hospital stays. OBJECTIVE: - To evaluate the effect of computerized clinical decision support systems on appropriateness of laboratory test ordering. DATA SOURCES: - We used MEDLINE, Embase, CINAHL, MEDLINE In-Process and Other Non-Indexed Citations, Clinicaltrials.gov, Cochrane Library, and Inspec through December 2015. Investigators independently screened articles to identify randomized trials that assessed a computerized clinical decision support system aimed at improving laboratory test ordering by providing patient-specific information, delivered in the form of an on-screen management option, reminder, or suggestion through a computerized physician order entry using a rule-based or algorithm-based system relying on an evidence-based knowledge resource. Investigators extracted data from 30 papers about study design, various study characteristics, study setting, various intervention characteristics, involvement of the software developers in the evaluation of the computerized clinical decision support system, outcome types, and various outcome characteristics. CONCLUSIONS: - Because of heterogeneity of systems and settings, pooled estimates of effect could not be made. Data showed that computerized clinical decision support systems had little or no effect on clinical outcomes but some effect on compliance. Computerized clinical decision support systems targeted at laboratory test ordering for multiple conditions appear to be more effective than those targeted at a single condition.

OPENING THE DOOR TO THE LARGE SCALE USE OF CLINICAL LAB MEASURES FOR ASSOCIATION TESTING: EXPLORING DIFFERENT METHODS FOR DEFINING PHENOTYPES.

The past decade has seen exponential growth in the numbers of sequenced and genotyped individuals and a corresponding increase in our ability of collect and catalogue phenotypic data for use in the clinic. We now face the challenge of integrating these diverse data in new ways new that can provide useful diagnostics and precise medical interventions for individual patients. One of the first steps in this process is to accurately map the phenotypic consequences of the genetic variation in human populations. The most common approach for this is the genome wide association study (GWAS). While this technique is relatively simple to implement for a given phenotype, the choice of how to define a phenotype is critical. It is becoming increasingly common for each individual in a GWAS cohort to have a large profile of quantitative measures. The standard approach is to test for associations with one measure at a time; however, there are many justifiable ways to define a set of phenotypes, and the genetic associations that are revealed will vary based on these definitions. Some phenotypes may only show a significant genetic association signal when considered together, such as through principle components analysis (PCA). Combining correlated measures may increase the power to detect association by reducing the noise present in individual variables and reduce the multiple hypothesis testing burden. Here we show that PCA and k-means clustering are two complimentary methods for identifying novel genotype-phenotype relationships within a set of quantitative human traits derived from the Geisinger Health System electronic health record (EHR). Using a diverse set of approaches for defining phenotype may yield more insights into the genetic architecture of complex traits and the findings presented here highlight a clear need for further investigation into other methods for defining the most relevant phenotypes in a set of variables. As the data of EHR continue to grow, addressing these issues will become increasingly important in our efforts to use genomic data effectively in medicine.

Failure to review STAT clinical laboratory requests and its economical impact.

BACKGROUND: Failure to follow-up laboratory test results has been described as one of the major processes contributing to unsafe patient care. Currently, most of the laboratories do not know with certainty not only their rate of missed (or unreviewed) requests but the economical cost and impact that this issue implies. The aim of our study was to measure that rate and calculate the resulting costs. MATERIAL AND METHODS: In January 2015, we checked in our Laboratory Information Management System (LIMS) for every emergency request from 1(st) July 2011 to 30(th) June 2014, if they had been reviewed by any allowed user or not. 319,064 requests were ordered during that period of time. Results were expressed as "ordered requests", "missed requests" and its percentage. Additionally, total cost of missed requests was calculated in euros (€). "Non-productive days" were theorised (as the days producing requests that were not reviewed) based on these results. RESULTS: 7924 requests (2.5%) were never reviewed by clinicians. This represented a total cost of 203,039 € and 27 "non-productive" days in three years. Significant differences between inpatients, outpatients and emergency department as well as different emergencies units were found after application of statistical analysis. CONCLUSIONS: In terms of resources, never reviewed or missed requests appear to be a not negligible problem for the clinical laboratory management. Electronic result delivery, with electronic endorsement to indicate follow-up of requests along with better systems of electronic requesting should be investigated as a way of improving patient outcomes and save unnecessary expenses.

Altering a computerized laboratory test order form rationalizes ordering of laboratory tests in primary care physicians.

BACKGROUND: To reduce physicians' inappropriate laboratory requests for their patients, administrators have used methods such as modifying a laboratory request order form with an agreed requesting protocol for the most common diagnoses in primary health care. OBJECTIVE: To study the effects of removing the erythrocyte sedimentation rate (ESR) and aspartate transaminase (AST) which are considered of limited clinical value for primary care clinical decision-making from a computerized laboratory test order form. These tests were removed to another new view from the electronic laboratory menu where the physicians, instead of just ticking the desired test from the list, had to do 4-8s extra work by writing down the abbreviation to order the test. METHODS: An observational controlled prospective study based on a before-after design was performed by removing AST and ES from the laboratory test order form of the computerized laboratory system for all primary care in the city of Helsinki, Finland. The numbers of annual and monthly use of AST and ESR and their controls, alanine transaminase (ALT) and C-reactive protein (CRP) ordered by General practitioners (GPs) was recorded over an eight-year period: four years before and a four years after the removal of AST and ES. RESULTS: Removing AST and ESR from the computerized laboratory test order form decreased their use by up to 90%, whereas the use of the control tests increased throughout the follow-up period. The variation in use of these removed tests also decreased. CONCLUSION: Removing a laboratory test from a computerized laboratory test order form may significantly reduce GPs' use of the laboratory test. Further studies are needed, however, to ensure the safety of this type of intervention.

INTEGRATING CLINICAL LABORATORY MEASURES AND ICD-9 CODE DIAGNOSES IN PHENOME-WIDE ASSOCIATION STUDIES.

Electronic health records (EHR) provide a comprehensive resource for discovery, allowing unprecedented exploration of the impact of genetic architecture on health and disease. The data of EHRs also allow for exploration of the complex interactions between health measures across health and disease. The discoveries arising from EHR based research provide important information for the identification of genetic variation for clinical decision-making. Due to the breadth of information collected within the EHR, a challenge for discovery using EHR based data is the development of high-throughput tools that expose important areas of further research, from genetic variants to phenotypes. Phenome-Wide Association studies (PheWAS) provide a way to explore the association between genetic variants and comprehensive phenotypic measurements, generating new hypotheses and also exposing the complex relationships between genetic architecture and outcomes, including pleiotropy. EHR based PheWAS have mainly evaluated associations with case/control status from International Classification of Disease, Ninth Edition (ICD-9) codes. While these studies have highlighted discovery through PheWAS, the rich resource of clinical lab measures collected within the EHR can be better utilized for high-throughput PheWAS analyses and discovery. To better use these resources and enrich PheWAS association results we have developed a sound methodology for extracting a wide range of clinical lab measures from EHR data. We have extracted a first set of 21 clinical lab measures from the de-identified EHR of participants of the Geisinger MyCodeTM biorepository, and calculated the median of these lab measures for 12,039 subjects. Next we evaluated the association between these 21 clinical lab median values and 635,525 genetic variants, performing a genome-wide association study (GWAS) for each of 21 clinical lab measures. We then calculated the association between SNPs from these GWAS passing our Bonferroni defined p-value cutoff and 165 ICD-9 codes. Through the GWAS we found a series of results replicating known associations, and also some potentially novel associations with less studied clinical lab measures. We found the majority of the PheWAS ICD-9 diagnoses highly related to the clinical lab measures associated with same SNPs. Moving forward, we will be evaluating further phenotypes and expanding the methodology for successful extraction of clinical lab measurements for research and PheWAS use. These developments are important for expanding the PheWAS approach for improved EHR based discovery.

Is routine hospital episode data sufficient for identifying individuals with chronic kidney disease? A comparison study with laboratory data.

Internationally, investment in the availability of routine health care data for improving health, health surveillance and health care is increasing. We assessed the validity of hospital episode data for identifying individuals with chronic kidney disease compared to biochemistry data in a large population-based cohort, the Grampian Laboratory Outcomes, Morbidity and Mortality Study-II (n = 70,435). Grampian Laboratory Outcomes, Morbidity and Mortality Study-II links hospital episode data to biochemistry data for all adults in a health region with impaired kidney function and random samples of individuals with normal and unmeasured kidney function in 2003. We compared identification of individuals with chronic kidney disease by hospital episode data (based on International Classification of Diseases-10 codes) to the reference standard of biochemistry data (at least two estimated glomerular filtration rates <60 mL/min/1.73 m(2) at least 90 days apart). Hospital episode data, compared to biochemistry data, identified a lower prevalence of chronic kidney disease and had low sensitivity (<10%) but high specificity (>97%). Using routine health care data from multiple sources offers the best opportunity to identify individuals with chronic kidney disease.

[The JLAC Coding System for Clinical Laboratory Tests].

Clinical laboratory data are essential for the diagnosis of and therapy for patients in hospital. In addition to such direct clinical use in hospitals, the collected personal clinical laboratory data have been recognized as very important for the life-long health care of individual patients. Furthermore, the data derived from a large number of patients are utilized for epidemiological studies and safety evaluation of new drugs. For the above-mentioned secondary use, laboratory data which are obtained at different times and in different facilities must be comparable. Recently, a huge amount of medical information has been accumulated and utilized as "big data" for the development of national healthcare and life science industries. Under these circumstances, the JLAC, a coding system of laboratory tests developed and maintained by JSLM, is attracting increasing attention for the spatial and temporal comparison of laboratory test data.

Advances In Infection Surveillance and Clinical Decision Support With Fuzzy Sets and Fuzzy Logic.

By the use of extended intelligent information technology tools for fully automated healthcare-associated infection (HAI) surveillance, clinicians can be informed and alerted about the emergence of infection-related conditions in their patients. Moni--a system for monitoring nosocomial infections in intensive care units for adult and neonatal patients--employs knowledge bases that were written with extensive use of fuzzy sets and fuzzy logic, allowing the inherent un-sharpness of clinical terms and the inherent uncertainty of clinical conclusions to be a part of Moni's output. Thus, linguistic as well as propositional uncertainty became a part of Moni, which can now report retrospectively on HAIs according to traditional crisp HAI surveillance definitions, as well as support clinical bedside work by more complex crisp and fuzzy alerts and reminders. This improved approach can bridge the gap between classical retrospective surveillance of HAIs and ongoing prospective clinical-decision-oriented HAI support.