Use of a data warehouse at an academic medical center for clinical pathology quality improvement, education, and research

Working with the Electronic Health Record and Laboratory Information System to Maximize Ordering and Reporting of Molecular Microbiology Results

Molecular microbiology assays have a higher cost of testing compared to traditional methods and need to be utilized appropriately. Results from these assays may also require interpretation and appropriate follow-up. Electronic tools available in the electronic health record and laboratory information system can be deployed both preanalytically and postanalytically to influence ordering behaviors and positively impact diagnostic stewardship. Next generation technologies, such as machine learning and artificial intelligence, have the potential to expand upon the capabilities currently available and warrant additional study and development but also require regulation around their use in health care.

Implementation of automatic data extraction from an enterprise database warehouse (EDW) for validating pediatric VTE decision rule: a prospective observational study in a critical care population

Multiple clinical risk prediction tools for hospital acquired venous thromboembolism (HA-VTE) have been developed. The objectives of this study were to develop and assess the feasibility of data extraction from Electronic Medical Records (EMR) from an enterprise database warehouse (EDW) and to test the validity of a previously developed Pediatric Clot Decision Rule (PCDR). This single-center prospective observational cohort study was conducted between March 2016 and March 2017 and included eligible patients admitted to the intensive care units. Risk score was calculated using the PCDR tool. Sensitivity, specificity, positive and negative predicted value (PPV and NPV) were calculated based on a cut-point of 3. A total of 2822 children were eligible for analysis and 5.1% (95% CI 4.2-6.2) children had a PCDR score of 3. Children with PCDR score of ≥ 3 had a 3 times higher odd of developing VTE compared to those with scores < 3 (OR 3.1; 95% CI 1.93-4.80; p < 0.001). The model performance showed that at the cutoff point of ≥ 3, both the specificity and sensitivity of the PCDR in predicting VTE was 69% and NPV of 98%. We successfully demonstrated using our EDW to populate a research database using an automatic data import. A PCDR score of ≥ 3 was associated with VTE. Collaboration through large registries will be useful in informing practices and guidelines for rare disorders such as pediatric VTE.

An integration approach of multi-source heterogeneous fuzzy spatiotemporal data based on RDF

With the growing importance of the fuzzy spatiotemporal data in information application, there is an increasing need for researching on the integration method of multi-source heterogeneous fuzzy spatiotemporal data. In this paper, we first propose a fuzzy spatiotemporal RDF graph model based on RDF (Resource Description Framework) that proposed by the World Wide Web Consortium (W3C) to represent data in triples (subject, predicate, object). Secondly, we analyze and classify the related heterogeneous problems of multi-source heterogeneous fuzzy spatiotemporal data, and use the fuzzy spatiotemporal RDF graph model to define the corresponding rules to solve these heterogeneous problems. In addition, based on the characteristics of RDF triples, we analyze the heterogeneous problem of multi-source heterogeneous fuzzy spatiotemporal data integration in RDF triples, and provide the integration methods FRDFG in this paper. Finally, we report our experiments results to validate our approach and show its significant superiority.

Natural language processing algorithms for mapping clinical text fragments onto ontology concepts: a systematic review and recommendations for future studies

BACKGROUND

Free-text descriptions in electronic health records (EHRs) can be of interest for clinical research and care optimization. However, free text cannot be readily interpreted by a computer and, therefore, has limited value. Natural Language Processing (NLP) algorithms can make free text machine-interpretable by attaching ontology concepts to it. However, implementations of NLP algorithms are not evaluated consistently. Therefore, the objective of this study was to review the current methods used for developing and evaluating NLP algorithms that map clinical text fragments onto ontology concepts. To standardize the evaluation of algorithms and reduce heterogeneity between studies, we propose a list of recommendations.

METHODS

Two reviewers examined publications indexed by Scopus, IEEE, MEDLINE, EMBASE, the ACM Digital Library, and the ACL Anthology. Publications reporting on NLP for mapping clinical text from EHRs to ontology concepts were included. Year, country, setting, objective, evaluation and validation methods, NLP algorithms, terminology systems, dataset size and language, performance measures, reference standard, generalizability, operational use, and source code availability were extracted. The studies' objectives were categorized by way of induction. These results were used to define recommendations.

RESULTS

Two thousand three hundred fifty five unique studies were identified. Two hundred fifty six studies reported on the development of NLP algorithms for mapping free text to ontology concepts. Seventy-seven described development and evaluation. Twenty-two studies did not perform a validation on unseen data and 68 studies did not perform external validation. Of 23 studies that claimed that their algorithm was generalizable, 5 tested this by external validation. A list of sixteen recommendations regarding the usage of NLP systems and algorithms, usage of data, evaluation and validation, presentation of results, and generalizability of results was developed.

CONCLUSION

We found many heterogeneous approaches to the reporting on the development and evaluation of NLP algorithms that map clinical text to ontology concepts. Over one-fourth of the identified publications did not perform an evaluation. In addition, over one-fourth of the included studies did not perform a validation, and 88% did not perform external validation. We believe that our recommendations, alongside an existing reporting standard, will increase the reproducibility and reusability of future studies and NLP algorithms in medicine.

Prospective Study of Use of Edmonton Symptom Assessment Scale Versus Routine Symptom Management During Weekly Radiation Treatment Visits

PURPOSE:

During radiotherapy (RT), patient symptoms are evaluated and managed weekly during physician on-treatment visits (OTVs). The Edmonton Symptom Assessment Scale (ESAS) is a 9-symptom validated self-assessment tool for reporting common symptoms in patients with cancer. We hypothesized that implementation and physician review of ESAS during weekly OTVs may result in betterment of symptom severity during RT for certain modifiable domains.

METHODS:

As an institutional quality improvement project, patients were partitioned into 2 groups: (1) 85 patients completing weekly ESAS (preintervention) but blinded to their providers who gave routine symptom management and (2) 170 completing weekly ESAS (postintervention group) reviewed by providers during weekly OTVs with possible intervention. To determine the independent association with symptom severity of the intervention, multivariate logistic regression was performed. At study conclusion, provider assessments of ESAS utility were also collected.

RESULTS:

Compared with the preintervention group, stable or improved symptom severity was seen in the postintervention group for pain (70.7% v 85.6%; P = .005) and anxiety (79.3% v 92.9%; P = .002). The postintervention group had decreased association (on multivariate analysis) with worsening severity of pain (OR, 0.13; P < .001), nausea (OR, 0.25; P = .023), loss of appetite (OR, 0.30; P = .024), and anxiety (OR, 0.19; P = .005). Most physicians (87.5%) and nurses (75%) found ESAS review useful in symptom management.

CONCLUSION:

Incorporation of ESAS for OTVs was associated with stable or improved symptom severity where therapeutic intervention is more readily available, such as counseling, pain medication, anti-emetics, appetite stimulants, and anti-anxiolytics. The incorporation of validated patient-reported symptom-scoring tools may improve provider management.

Building a Semantic Health Data Warehouse in the Context of Clinical Trials: Development and Usability Study

Background

The huge amount of clinical, administrative, and demographic data recorded and maintained by hospitals can be consistently aggregated into health data warehouses with a uniform data model. In 2017, Rouen University Hospital (RUH) initiated the design of a semantic health data warehouse enabling both semantic description and retrieval of health information.

Objective

This study aimed to present a proof of concept of this semantic health data warehouse, based on the data of 250,000 patients from RUH, and to assess its ability to assist health professionals in prescreening eligible patients in a clinical trials context.

Methods

The semantic health data warehouse relies on 3 distinct semantic layers: (1) a terminology and ontology portal, (2) a semantic annotator, and (3) a semantic search engine and NoSQL (not only structured query language) layer to enhance data access performances. The system adopts an entity-centered vision that provides generic search capabilities able to express data requirements in terms of the whole set of interconnected conceptual entities that compose health information.

Results

We assessed the ability of the system to assist the search for 95 inclusion and exclusion criteria originating from 5 randomly chosen clinical trials from RUH. The system succeeded in fully automating 39% (29/74) of the criteria and was efficiently used as a prescreening tool for 73% (54/74) of them. Furthermore, the targeted sources of information and the search engine–related or data-related limitations that could explain the results for each criterion were also observed.

Conclusions

The entity-centered vision contrasts with the usual patient-centered vision adopted by existing systems. It enables more genericity in the information retrieval process. It also allows to fully exploit the semantic description of health information. Despite their semantic annotation, searching within clinical narratives remained the major challenge of the system. A finer annotation of the clinical texts and the addition of specific functionalities would significantly improve the results. The semantic aspect of the system combined with its generic entity-centered vision enables the processing of a large range of clinical questions. However, an important part of health information remains in clinical narratives, and we are currently investigating novel approaches (deep learning) to enhance the semantic annotation of those unstructured data.

Technology-Enabled Outreach to Patients Taking High-Risk Medications Reduces a Quality Gap in Completion of Clinical Laboratory Testing

Clinical laboratory quality improvement (QI) efforts can include population test utilization. The authors used a health care organization's Medical Data Warehouse (MDW) to characterize a gap in guideline-concordant laboratory testing recommended for safe use of antirheumatic agents, then tested the effectiveness of laboratory-led, technology-enabled outreach to patients at reducing this gap. Data linkages available through the Kaiser Permanente Colorado MDW and electronic health record were used to identify ambulatory adults taking antirheumatic agents who were due/overdue for alanine aminotransferase (ALT), aspartate aminotransferase (AST), complete blood count (CBC), or serum creatinine (SCr) testing. Outreach was implemented using an interactive voice response system to send patients text or phone call reminders. Interrupted time series analysis was used to estimate reminder effectiveness. Rates of guideline-concordant testing and testing timeliness in baseline vs. intervention periods were determined using generalized linear models for repeated measures. Results revealed a decrease in percentage of 3763 patients taking antirheumatic agents due/overdue for testing at any given time: baseline 24.3% vs. intervention 17.5% (P < 0.001). Among 3205 patients taking conventional antirheumatic agents, concordance for all ALT testing was baseline 52.8% vs. intervention 65.4% (P < 0.001) among patients chronically using these agents and baseline 20.6% vs. intervention 26.1% (P < 0.001) among patients newly starting these agents. The 95^th percentiles for days to ALT testing were baseline 149 vs. intervention 117 among chronic users and baseline 134 vs. intervention 92 among new starts. AST, CBC, and SCr findings were similar. Technology-enabled outreach reminding patients to obtain laboratory testing improves health care system outcomes.

Identifying Preanalytic and Postanalytic Laboratory Quality Gaps Using a Data Warehouse and Structured Multidisciplinary Process

CONTEXT.—

The laboratory total testing process includes preanalytic, analytic, and postanalytic phases, but most laboratory quality improvement efforts address the analytic phase. Expanding quality improvement to preanalytic and postanalytic phases via use of medical data warehouses, repositories that include clinical, utilization, and administrative data, can improve patient care by ensuring appropriate test utilization. Cross-department, multidisciplinary collaboration to address gaps and improve patient and system outcomes is beneficial.

OBJECTIVE.—

To demonstrate medical data warehouse utility for characterizing laboratory-associated quality gaps amenable to preanalytic or postanalytic interventions.

DESIGN.—

A multidisciplinary team identified quality gaps. Medical data warehouse data were queried to characterize gaps. Organizational leaders were interviewed about quality improvement priorities. A decision aid with elements including national guidelines, local and national importance, and measurable outcomes was completed for each gap.

RESULTS.—

Gaps identified included (1) test ordering; (2) diagnosis, detection, and documentation, and (3) high-risk medication monitoring. After examination of medical data warehouse data including enrollment, diagnoses, laboratory, pharmacy, and procedures for baseline performance, high-risk medication monitoring was selected, specifically alanine aminotransferase, aspartate aminotransferase, complete blood count, and creatinine testing among patients receiving disease-modifying antirheumatic drugs. The test utilization gap was in monitoring timeliness (eg, >60% of patients had a monitoring gap exceeding the guideline recommended frequency). Other contributors to selecting this gap were organizational enthusiasm, regulatory labeling, and feasibility of a significant laboratory role in addressing the gap.

CONCLUSIONS.—

A multidisciplinary process facilitated identification and selection of a laboratory medicine quality gap. Medical data warehouse data were instrumental in characterizing gaps.

Prevalence and Clinical Utility of "Incidental" Critical Values Resulting From Critical Care Laboratory Testing

OBJECTIVE

Panels of clinical laboratory testing may generate "incidental" critical values from unordered parameters. Existing regulations do not clearly delineate guidelines for handling incidental critical values. The objective of this study was to examine the patterns and clinical utility of incidental critical values at 2 critical care laboratories within an academic medical center.

METHODS

In this retrospective study, the electronic health record and laboratory information system were reviewed for incidental critical results obtained from blood gas analyzer analysis of whole blood specimens between November 2010 and August 2014.

RESULTS

Within the retrospective time period, 9,092 incidental critical results were documented, of which only 11.8% were added to the "parent" order following clinical notification. Incidental critical results frequently occurred in patients who had recent critical values for the same parameter.

CONCLUSION

In this study, at an academic medical center, incidental critical values associated with blood gas analyzers were added on at a low rate and often provided redundant information. Relative to the manual effort involved in care providers' notification and documentation of results, incidental critical values appear to have low clinical utility.

Use of a Rapid Ethylene Glycol Assay: a 4-Year Retrospective Study at an Academic Medical Center

Ethylene glycol (EG) is a common cause of toxic ingestions. Gas chromatography (GC)-based laboratory assays are the gold standard for diagnosing EG intoxication. However, GC requires specialized instrumentation and technical expertise that limits feasibility for many clinical laboratories. The objective of this retrospective study was to determine the utility of incorporating a rapid EG assay for management of cases with suspected EG poisoning. The University of Iowa Hospitals and Clinics core clinical laboratory adapted a veterinary EG assay (Catachem, Inc.) for the Roche Diagnostics cobas 8000 c502 analyzer and incorporated this assay in an osmolal gap-based algorithm for potential toxic alcohol/glycol ingestions. The main limitation is that high concentrations of propylene glycol (PG), while readily identifiable by reaction rate kinetics, can interfere with EG measurement. The clinical laboratory had the ability to perform GC for EG and PG, if needed. A total of 222 rapid EG and 24 EG/PG GC analyses were documented in 106 patient encounters. Of ten confirmed EG ingestions, eight cases were managed entirely with the rapid EG assay. PG interference was evident in 25 samples, leading to 8 GC analyses to rule out the presence of EG. Chart review of cases with negative rapid EG assay results showed no evidence of false negatives. The results of this study highlight the use of incorporating a rapid EG assay for the diagnosis and management of suspected EG toxicity by decreasing the reliance on GC. Future improvements would involve rapid EG assays that completely avoid interference by PG.

Predicting changes in hemoglobin S after simple transfusion using complete blood counts

BACKGROUND

Hemoglobin S percentages are used in the management of patients who have sickle cell disease. However, hemoglobin S measurements often are not routinely or rapidly performed. Rapid and accurate methods to estimate hemoglobin S levels after simple transfusion may improve the care of patients with sickle cell disease.

STUDY DESIGN AND METHODS

A comprehensive review of the electronic medical record identified 24 stable patients with sickle cell disease who received simple red blood cell transfusions and had hemoglobin S measurements before and after the transfusion that were less than 72 hours apart. Examination of these patients identified 62 separate transfusions that met our criteria. Three simple equations that utilized complete blood count values and readily available information from the medical record were used to predict the post-transfusion hemoglobin S level after transfusion (Equation 1: predicted post-transfusion hemoglobin = pre-transfusion hemoglobin S × [pre-transfusion hemoglobin/post-transfusion hemoglobin]; Equation 2: predicted post-transfusion hemoglobin S = pre-transfusion hemoglobin S × [pre-transfusion hematocrit/post-transfusion hematocrit]; and Equation 3: predicted post-transfusion hemoglobin S = pre-transfusion hemoglobin S × total pre-transfusion hemoglobin/[total pre-transfusion hemoglobin + (red blood cell volume × 20)]).

RESULTS

The predicted hemoglobin S values for all three equations showed a highly significant correlation with the measured post-hemoglobin S value. The coefficient of determination (R² ) for Equations 1, 2, and 3 was 0.95, 0.92, and 0.97, respectively. Predicting the post-transfusion hemoglobin S value using estimates of the patient's total hemoglobin and the transfused hemoglobin (Equation 3) was the most precise.

CONCLUSION

Reductions in hemoglobin S values in patients with sickle cell disease who receive simple red blood cell transfusions can be reliably predicted using complete blood cell measurements and simple arithmetic equations.

The Georges Pompidou University Hospital Clinical Data Warehouse: A 8-years follow-up experience

BACKGROUND

When developed jointly with clinical information systems, clinical data warehouses (CDWs) facilitate the reuse of healthcare data and leverage clinical research.

OBJECTIVE

To describe both data access and use for clinical research, epidemiology and health service research of the "Hôpital Européen Georges Pompidou" (HEGP) CDW.

METHODS

The CDW has been developed since 2008 using an i2b2 platform. It was made available to health professionals and researchers in October 2010. Procedures to access data have been implemented and different access levels have been distinguished according to the nature of queries.

RESULTS

As of July 2016, the CDW contained the consolidated data of over 860,000 patients followed since the opening of the HEGP hospital in July 2000. These data correspond to more than 122 million clinical item values, 124 million biological item values, and 3.7 million free text reports. The ethics committee of the hospital evaluates all CDW projects that generate secondary data marts. Characteristics of the 74 research projects validated between January 2011 and December 2015 are described.

CONCLUSION

The use of HEGP CDWs is a key facilitator for clinical research studies. It required however important methodological and organizational support efforts from a biomedical informatics department.

Using Focused Laboratory Management and Quality Improvement Projects to Enhance Resident Training and Foster Scholarship

Training in patient safety, quality, and management is widely recognized as an important element of graduate medical education. These concepts have been intertwined in pathology graduate medical education for many years, although training programs face challenges in creating explicit learning opportunities in these fields. Tangibly involving pathology residents in management and quality improvement projects has the potential to teach and reinforce key concepts and further fulfill Accreditation Council for Graduate Medical Education goals for pursuing projects related to patient safety and quality improvement. In this report, we present our experience at a pathology residency program (University of Iowa) in engaging pathology residents in projects related to practical issues of laboratory management, process improvement, and informatics. In this program, at least 1 management/quality improvement project, typically performed during a clinical chemistry/management rotation, was required and ideally resulted in a journal publication. The residency program also initiated a monthly management/informatics series for pathology externs, residents, and fellows that covers a wide range of topics. Since 2010, all pathology residents at the University of Iowa have completed at least 1 management/quality improvement project. Many of the projects involved aspects of laboratory test utilization, with some projects focused on other areas such as human resources, informatics, or process improvement. Since 2012, 31 peer-reviewed journal articles involving effort from 26 residents have been published. Multiple projects resulted in changes in ongoing practice, particularly within the hospital electronic health record. Focused management/quality improvement projects involving pathology residents can result in both meaningful quality improvement and scholarly output.

Measurement, Standards, and Peer Benchmarking: One Hospital's Journey

Peer-to-peer benchmarking is an important component of rapid-cycle performance improvement in patient safety and quality-improvement efforts. Institutions should carefully examine critical success factors before engagement in peer-to-peer benchmarking in order to maximize growth and change opportunities. Solutions for Patient Safety has proven to be a high-yield engagement for Children's Hospital of Pittsburgh of University of Pittsburgh Medical Center, with measureable improvement in both organizational process and culture.