Assessment of Rapid-Blood-Culture-Identification Result Interpretation and Antibiotic Prescribing Practices.

Rapid pathogen identification can alter antibiotic prescribing practices if interpreted correctly. Microbiology reporting can be difficult to understand, and new technology has made it more challenging. Nebraska Medicine recently implemented the BioFire FilmArray blood culture identification panel (BCID) coupled with stewardship-based education on interpretation. Physician BCID result interpretation and prescribing were assessed via an electronic survey, with a response rate of 40.8% (156/382 surveys). Seven questions required respondents to interpret BCID results, identify the most likely pathogen, and then choose therapy based on the results. The tallied correct responses resulted in a knowledge score. General linear models evaluated the effect of role, specialty, and utilization of the BCID interpretation guide on the mean knowledge score. The specialties of the respondents included 55.7% internal medicine, 19.7% family medicine, and 24.6% other. Roles included 41.1% residents, 5.0% fellows, and 53.9% faculty. Most reported that they reviewed antimicrobial susceptibility results (89.4%) and adjusted therapy accordingly (81.6%), while only 60% stated that they adjusted therapy based on BCID results. The correct response rates ranged from 52 to 86% for the interpretation questions. The most common errors included misinterpretation of Enterobacteriaceae and Staphylococcus genus results. Neither role nor specialty was associated with total knowledge score in multivariate analysis (P = 0.13 and 0.47, respectively). In conclusion, physician interpretation of BCID results is suboptimal and can result in ineffective treatment or missed opportunity to narrow therapy. With the implementation of new technology, improved reporting practices of BCID results with clinical decision support tools providing interpretation guidance available at the point of care is recommended.

An alternative database approach for management of SNOMED CT and improved patient data queries.

OBJECTIVE: SNOMED CT is the international lingua franca of terminologies for human health. Based in Description Logics (DL), the terminology enables data queries that incorporate inferences between data elements, as well as, those relationships that are explicitly stated. However, the ontologic and polyhierarchical nature of the SNOMED CT concept model make it difficult to implement in its entirety within electronic health record systems that largely employ object oriented or relational database architectures. The result is a reduction of data richness, limitations of query capability and increased systems overhead. The hypothesis of this research was that a graph database (graph DB) architecture using SNOMED CT as the basis for the data model and subsequently modeling patient data upon the semantic core of SNOMED CT could exploit the full value of the terminology to enrich and support advanced data querying capability of patient data sets. METHODS: The hypothesis was tested by instantiating a graph DB with the fully classified SNOMED CT concept model. The graph DB instance was tested for integrity by calculating the transitive closure table for the SNOMED CT hierarchy and comparing the results with transitive closure tables created using current, validated methods. The graph DB was then populated with 461,171 anonymized patient record fragments and over 2.1 million associated SNOMED CT clinical findings. Queries, including concept negation and disjunction, were then run against the graph database and an enterprise Oracle relational database (RDBMS) of the same patient data sets. The graph DB was then populated with laboratory data encoded using LOINC, as well as, medication data encoded with RxNorm and complex queries performed using LOINC, RxNorm and SNOMED CT to identify uniquely described patient populations. RESULTS: A graph database instance was successfully created for two international releases of SNOMED CT and two US SNOMED CT editions. Transitive closure tables and descriptive statistics generated using the graph database were identical to those using validated methods. Patient queries produced identical patient count results to the Oracle RDBMS with comparable times. Database queries involving defining attributes of SNOMED CT concepts were possible with the graph DB. The same queries could not be directly performed with the Oracle RDBMS representation of the patient data and required the creation and use of external terminology services. Further, queries of undefined depth were successful in identifying unknown relationships between patient cohorts. CONCLUSION: The results of this study supported the hypothesis that a patient database built upon and around the semantic model of SNOMED CT was possible. The model supported queries that leveraged all aspects of the SNOMED CT logical model to produce clinically relevant query results. Logical disjunction and negation queries were possible using the data model, as well as, queries that extended beyond the structural IS_A hierarchy of SNOMED CT to include queries that employed defining attribute-values of SNOMED CT concepts as search parameters. As medical terminologies, such as SNOMED CT, continue to expand, they will become more complex and model consistency will be more difficult to assure. Simultaneously, consumers of data will increasingly demand improvements to query functionality to accommodate additional granularity of clinical concepts without sacrificing speed. This new line of research provides an alternative approach to instantiating and querying patient data represented using advanced computable clinical terminologies.

Factors Associated With Receipt of Molecular Testing and its Impact on Time to Initial Systemic Therapy in Metastatic Non-Small Cell Lung Cancer.

BACKGROUND: Despite recommendations for molecular testing irrespective of patient characteristics, differences exist in receipt of molecular testing for oncogenic drivers amongst metastatic non-small cell lung cancer (mNSCLC) patients. Exploration into these differences and their effects on treatment is needed to identify opportunities for improvement. PATIENTS AND METHODS: We conducted a retrospective cohort study of adult patients diagnosed with mNSCLC between 2011 and 2018 using PCORnet's Rapid Cycle Research Project dataset (n = 3600). Log-binomial, Cox proportional hazards (PH), and time-varying Cox regression models were used to ascertain whether molecular testing was received, and time from diagnosis to molecular testing and/or initial systemic treatment in the context of patient age, sex, race/ethnicity, and multiple comorbidities status. RESULTS: The majority of patients in this cohort were ≤ 65 years of age (median [25th, 75th]: 64 [57, 71]), male (54.3%), non-Hispanic white individuals (81.6%), with > 2 comorbidities in addition to mNSCLC (54.1%). About half the cohort received molecular testing (49.9%). Patients who received molecular testing had a 59% higher probability of initial systemic treatment than patients who were yet to receive testing. Multiple comorbidity status was positively associated with receipt of molecular testing (RR, 1.27; 95% CI 1.08, 1.49). CONCLUSION: Receipt of molecular testing in academic centers was associated with earlier initiation of systemic treatment. This finding underscores the need to increase molecular testing rates amongst mNSCLC patients during a clinically relevant period. Further studies to validate these findings in community centers are warranted.

Enhancing the identification of rheumatoid arthritis-associated interstitial lung disease through text mining of chest computerized tomography reports.

OBJECTIVES: Algorithms have been developed to identify rheumatoid arthritis-interstitial lung disease (RA-ILD) in administrative data with positive predictive values (PPVs) between 70 and 80%. We hypothesized that including ILD-related terms identified within chest computed tomography (CT) reports through text mining would improve the PPV of these algorithms in this cross-sectional study. METHODS: We identified a derivation cohort of possible RA-ILD cases (n = 114) using electronic health record data from a large academic medical center and performed medical record review to validate diagnoses (reference standard). ILD-related terms (e.g., ground glass, honeycomb) were identified in chest CT reports by natural language processing. Administrative algorithms including diagnostic and procedural codes as well as specialty were applied to the cohort both with and without the requirement for ILD-related terms from CT reports. We subsequently analyzed similar algorithms in an external validation cohort of 536 participants with RA. RESULTS: The addition of ILD-related terms to RA-ILD administrative algorithms increased the PPV in both the derivation (improvement ranging from 3.6 to 11.7%) and validation cohorts (improvement 6.0 to 21.1%). This increase was greatest for less stringent algorithms. Administrative algorithms including ILD-related terms from CT reports exceeded a PPV of 90% (maximum 94.6% derivation cohort). Increases in PPV were accompanied by a decline in sensitivity (validation cohort -3.9 to -19.5%). CONCLUSIONS: The addition of ILD-related terms identified by text mining from chest CT reports led to improvements in the PPV of RA-ILD algorithms. With high PPVs, use of these algorithms in large data sets could facilitate epidemiologic and comparative effectiveness research in RA-ILD.

Risk of malignancy in patients with chronic kidney disease.

BACKGROUND: Fifteen percent of US adults have chronic kidney disease (CKD). The effect of CKD on the development of different malignancies is unknown. Understanding the effect of CKD on the risk of development of cancer could have important implications for screening and early detection of cancer in these patients. METHODS: Adult CKD patients [estimated GFR (eGFR) <60ml/min/1.73m2] between January 2001 and December 2020 were identified in this single institution study. Patients were divided into four stages of CKD by eGFR. The incidence of cancer and time to development of the first cancer were identified. Multivariable models were used to compare the overall cancer incidence while considering death as a competing risk event and adjusting for relevant covariates (sex, race, diabetes, hypertension, CAD, smoking or not, BMI, and CKD stages). Separate multivariable models of the incidence of cancers were conducted in each age group. Multivariable Cox models were used to fit the overall death adjusting for relevant covariates. Patients were censored at the conclusion of the study period (December 31, 2020). Statistical analysis was performed with SAS software (version 9.4). RESULTS: Of the 13,750 patients with a diagnosis of CKD in this cohort, 2,758 (20.1%) developed a malignancy. The median time to development of cancer following a diagnosis of CKD was 8.5 years. Factors associated with the risk of developing cancer in CKD patients included increasing age, male sex and worsening chronic kidney disease, while diabetes was associated with a lower risk of malignancy. On multivariate analysis, the factors associated with increased mortality in patients who developed cancer included increasing age, diabetes and lower eGFR. CONCLUSION: CKD is an increased risk factor for the development of various malignancies. Age appropriate cancer screening should be aggressively pursued in those with progressive CKD.

Assessment of a Program for SARS-CoV-2 Screening and Environmental Monitoring in an Urban Public School District.

Importance: Scalable programs for school-based SARS-CoV-2 testing and surveillance are needed to guide in-person learning practices and inform risk assessments in kindergarten through 12th grade settings. Objectives: To characterize SARS-CoV-2 infections in staff and students in an urban public school setting and evaluate test-based strategies to support ongoing risk assessment and mitigation for kindergarten through 12th grade in-person learning. Design, Setting, and Participants: This pilot quality improvement program engaged 3 schools in Omaha, Nebraska, for weekly saliva polymerase chain reaction testing of staff and students participating in in-person learning over a 5-week period from November 9 to December 11, 2020. Wastewater, air, and surface samples were collected weekly and tested for SARS-CoV-2 RNA to evaluate surrogacy for case detection and interrogate transmission risk of in-building activities. Main Outcomes and Measures: SARS-CoV-2 detection in saliva and environmental samples and risk factors for SARS-CoV-2 infection. Results: A total of 2885 supervised, self-collected saliva samples were tested from 458 asymptomatic staff members (mean [SD] age, 42.9 [12.4] years; 303 women [66.2%]; 25 Black or African American [5.5%], 83 Hispanic [18.1%], 312 White [68.1%], and 35 other or not provided [7.6%]) and 315 students (mean age, 14.2 [0.7] years; 151 female students [48%]; 20 Black or African American [6.3%], 201 Hispanic [63.8%], 75 White [23.8%], and 19 other race or not provided [6.0%]). A total of 46 cases of SARS-CoV-2 (22 students and 24 staff members) were detected, representing an increase in cumulative case detection rates from 1.2% (12 of 1000) to 7.0% (70 of 1000) among students and from 2.1% (21 of 1000) to 5.3% (53 of 1000) among staff compared with conventional reporting mechanisms during the pilot period. SARS-CoV-2 RNA was detected in wastewater samples from all pilot schools as well as in air samples collected from 2 choir rooms. Sequencing of 21 viral genomes in saliva specimens demonstrated minimal clustering associated with 1 school. Geographical analysis of SARS-CoV-2 cases reported district-wide demonstrated higher community risk in zip codes proximal to the pilot schools. Conclusions and Relevance: In this study of staff and students in 3 urban public schools in Omaha, Nebraska, weekly screening of asymptomatic staff and students by saliva polymerase chain reaction testing was associated with increased SARS-CoV-2 case detection, exceeding infection rates reported at the county level. Experiences differed among schools, and virus sequencing and geographical analyses suggested a dynamic interplay of school-based and community-derived transmission risk. Collectively, these findings provide insight into the performance and community value of test-based SARS-CoV-2 screening and surveillance strategies in the kindergarten through 12th grade educational setting.

Exploration of PCORnet Data Resources for Assessing Use of Molecular-Guided Cancer Treatment.

PURPOSE: Examine the ability of PCORnet data resources to investigate molecular-guided cancer treatment. PATIENTS AND METHODS: Patients (N = 86,154) had single primary solid tumors (diagnosed 2013-2017) from hospital oncology registries linked to the PCORnet Common Data Model (CDM) at 11 medical institutions. Molecular and anatomic test procedures and oral and infused therapies were identified with Current Procedural Terminology (CPT) and Healthcare Common Procedure Coding System (HCPCS) codes, RxNorm Concept Unique Identifier, and National Drug Codes from CDM tables. Chart review (2 institutions, n = 213) for advanced colorectal cancer and Medicare claims linkages (7 institutions, n = 1,731) for breast cancer explored options for increasing electronic data capture. RESULTS: Molecular testing prevalence detected via analyte-specific molecular CPT/HCPCS codes was 5.5% (n = 4,784); for the nonspecific anatomic pathology codes, for which only some testing is performed to guide therapy selection, it was an additional 44.8% (n = 38,610). Molecular-guided therapy prevalence was 5% (n = 4,289). Testing and treatment were most common with stage IV disease and varied across cancer types and study institutions (testing, 0%-10.4%; treatment, 0.8%-8.4%). Therapy-concordant test results were found in charts for all 36 treated patients with colorectal cancer at the 2 institutions, 3 (8.3%) of whom received treatment outside the institution. Breast cancer Medicare claims linkage increased rates of identified testing from 62.7%-98.9% and treatment from 3.9%-8.2%. CONCLUSION: Although a minority of patients received molecular-guided therapies, the majority had testing that could guide cancer treatment. Claims data extended electronic data capture for therapies and test orders but often was uninformative for types of test ordered. Test results continue to require text data curation from narrative pathology reports.

A Survey of LOINC Code Selection Practices Among Participants of the College of American Pathologists Coagulation (CGL) and Cardiac Markers (CRT) Proficiency Testing Programs.

CONTEXT.­: Biomedical terminologies such as Logical Observation Identifiers, Names, and Codes (LOINC) were developed to enable interoperability of health care data between disparate health information systems to improve patient outcomes, public health, and research activities. OBJECTIVE.­: To ascertain the utilization rate and accuracy of LOINC terminology mapping to 10 commonly ordered tests by participants of the College of American Pathologists (CAP) Proficiency Testing program. DESIGN.­: Questionnaires were sent to 1916 US and Canadian laboratories participating in the 2018 CAP coagulation (CGL) and/or cardiac markers (CRT) surveys requesting information on practice setting, instrument(s) and test method(s), and LOINC code selection and usage in the laboratory and electronic health records. RESULTS.­: Ninety of 1916 CGL and/or CRT participants (4.7%) responded to the questionnaire. Of the 275 LOINC codes reported, 54 (19.6%) were incorrect: 2 codes (5934-2 and 12345-1) (0.7%) did not exist in the LOINC database and the highest error rates were observed in the property (27 of 275, 9.8%), system (27 of 275, 9.8%), and component (22 of 275, 8.0%) LOINC axes. Errors in LOINC code selection included selection of the incorrect component (eg, activated clotting time instead of activated partial thromboplastin time); selection of panels that can never be used to obtain an individual analyte (eg, prothrombin time panel instead of international normalized ratio); and selection of an incorrect specimen type. CONCLUSIONS.­: These findings of real-world LOINC code implementation across a spectrum of laboratory settings should raise concern about the reliability and utility of using LOINC for clinical research or to aggregate data.

Sixty-five thousand shades of gray: importance of color in surgical pathology diagnoses.

Digital whole slide imaging (WSI) is a diagnostic modality that has gained acceptance as a tool for use in some areas of surgical pathology such as remote consultations. Accurate control of color representation of digitally rendered images of histologic sections is considered an important parameter of WSI. Currently, professional societies, physicians, and other stakeholders are in the process of establishing clinical guidelines outlining the use of these devices, which include color integrity and color calibration of scanners and viewing devices. Although color is a component of surgical pathology diagnoses, it was posited that pathologists could accurately diagnose surgical specimens without color. To test this hypothesis, 5 pathologists were presented breast biopsy specimens from 20 patients consisting of 22 separate tissue specimens and WSI of 158 hematoxylin and eosin-stained slides imaged at ×20. No special stains were included. The pathologists reviewed each case using a 16-bit grayscale monitor and rendered a diagnosis for each case. Diagnoses were compared to the original light microscopy diagnoses and scored for concordance. A 92.7% concordance was observed. Discordant diagnoses represented well-known areas of diagnostic disagreement in breast pathology as well as known limitations of WSI. The research demonstrated that surgical pathologists did not rely primarily on color to render accurate diagnoses of breast biopsy cases but rather used architectural features of tissue and cellular morphology to reach a diagnostic conclusion. This research did not suggest that color is an unimportant factor in pathology diagnosis, but its importance may be overstated.

Visual memory effects on intraoperator study design: determining a minimum time gap between case reviews to reduce recall bias.

OBJECTIVES: The objective of this research was to determine test intervals between intraoperator case reviews to minimize the impact of recall. METHODS: Three pathologists were presented with a group of 120 slides and subsequently challenged with a study set of 120 slides after 2-week and 4-week intervals. The challenge set consisted of 60 slides seen during the initial review and 60 slides previously unseen within the study. Pathologists rendered a diagnosis for each slide and indicated whether they recalled seeing the slide previously (yes/no). RESULTS: Two weeks after having been shown 60 cases from a challenge set of 120 cases, the pathologists correctly remembered 26, 22, and 24 cases or 40% overall. After 4 weeks, the pathologists correctly recalled 31% of cases previously seen. CONCLUSIONS: Pathologists were capable of recalling from memory cases seen previously at 2 and 4 weeks. Recall rates may be sufficiently high to affect intraobserver study design.

Whole slide imaging diagnostic concordance with light microscopy for breast needle biopsies.

This study investigated the diagnostic accuracy of whole slide imaging (WSI) in breast needle biopsy diagnosis in comparison with standard light microscopy (LM). The study examined the effects of image capture magnification and computer monitor quality on diagnostic concordance of WSI and LM. Four pathologists rendered diagnoses using WSI to examine 85 breast biopsies (92 parts; 786 slides) consisting of benign and malignant cases. Each WSI case was evaluated using images captured at either ×20 or ×40 magnifications and viewed using a Digital Imaging and Communication in Medicine (DICOM) grade, color-calibrated monitor or a standard, desktop liquid-crystal display (LCD) monitor. For each combination, the WSI result was compared with the original, LM diagnosis. The overall concordance rate observed between WSI and LM was 97.1% (95% confidence intervals [CI]: 94.3%-98.5%). After a washout period, all cases were reviewed a second time by each pathologist after using LM, and the second LM diagnosis was compared with the WSI diagnosis rendered by the same pathologist. Intraobserver concordance between WSI and LM was 95.4% (95% CI: 92.2%-97.4%). The second LM diagnoses were also compared with the original LM diagnoses, and the observed interobserver LM concordance rate was 97.3% (95% CI: 93.1%-99.0%). The study data demonstrated that breast needle biopsy diagnoses rendered by WSI were equivalent to diagnoses rendered by LM. No diagnostic differences were detected between the underlying viewing system parameters of monitor quality and image capture resolution. The results of this study demonstrated that WSI can be effectively used in subspecialty diagnostic cases where a minimum amount of tissue is available.

Concordance between whole-slide imaging and light microscopy for routine surgical pathology.

The use of high-resolution digital images of histopathology slides as a routine diagnostic tool for surgical pathology was investigated. The study purpose was to determine the diagnostic concordance between pathologic interpretations using whole-slide imaging and standard light microscopy. Two hundred fifty-one consecutive surgical pathology cases (312 parts, 1085 slides) from a single pathology service were included in the study after cases had been signed out and reports generated. A broad array of diagnostic challenges and tissue sources were represented, including 52 neoplastic cases. All cases were digitized at ×20 and presented to 2 pathologists for diagnosis using whole-slide imaging as the sole diagnostic tool. Diagnoses rendered by the whole-slide imaging pathologists were compared with the original light microscopy diagnoses. Overall concordance between whole-slide imaging and light microscopy as determined by a third pathologist and jury panel was 96.5% (95% confidence interval, 94.8%-98.3%). Concordance between whole-slide imaging pathologists was 97.7% (95% confidence interval, 94.7%-99.2%). Five cases were discordant between the whole-slide imaging diagnosis and the original light microscopy diagnosis, of which 2 were clinically significant. Discordance resulted from interpretive criteria or diagnostic error. The whole-slide imaging modality did not contribute to diagnostic differences. Problems encountered by the whole-slide imaging pathologists primarily involved the inability to clearly visualize nuclear detail or microscopic organisms. Technical difficulties associated with image scanning required at least 1 slide be rescanned in 13% of the cases. Technical and operational issues associated with whole-slide imaging scanning devices used in this study were found to be the most significant obstacle to the use of whole-slide imaging in general surgical pathology.