Laboratory Data as a Potential Source of Bias in Healthcare Artificial Intelligence and Machine Learning Models
Artificial intelligence (AI) and machine learning (ML) are anticipated to transform the practice of medicine. As one of the largest sources of digital data in healthcare, laboratory results can strongly influence AI and ML algorithms that require large sets of healthcare data for training. Embedded bias introduced into AI and ML models not only has disastrous consequences for quality of...
Enhancing the Functionalities of Personal Health Record Systems: Empirical Study Based on the HL7 Personal Health Record System Functional Model Release 1
Background: The increasing demand for personal health record (PHR) systems is driven by individuals' desire to actively manage their health care. However, the limited functionality of current PHR systems has affected users' willingness to adopt them, leading to lower-than-expected usage rates. The HL7 (Health Level Seven) PHR System Functional Model (PHR-S FM) was proposed to address this issue, outlining all...
Digitalizing Handwritten Digits of Patients with Parkinson’s Disease Utilizing Consumer Hardware and Open-Source Software
Introduction: Parkinson's disease represents a burdensome condition with complex manifestations. A licensed, standardized paper-based questionnaire is completed by both patients and physicians to monitor the progression and state of the disease. However, integrating the obtained scores into digital systems still poses a challenge. Methods: Paper-based handwriting is intuitive and an efficient mode of human-computer interaction. Accordingly, we transformed a consumer-grade...
Monitoring Variability of Laboratory Results in a Clinical Data Warehouse Using Automatic Dashboard
Hospital laboratory results are a significant data source in Clinical Data Ware-houses (CDW). To ensure comparability across healthcare organizations and for use in research studies, the results need to be interoperable. The LOINC (Logical Observation Identifiers, Names, and Codes) terminology provides a unique identifier for local codes for lab tests, enabling interoperability. However, in real-world, events occur over time and...
Classifier Chains for LOINC Transcoding
Purpose: Mapping clinical observations and medical test results into the standardized vocabulary LOINC is a prerequisite for exchanging clinical data between health information systems and ensuring efficient interoperability. Methods: We present a comparison of three approaches for LOINC transcoding applied to French data collected from real-world settings. These approaches include both a state-of-the-art language model approach and a classifier chains...
Optimizing Integration with the Italian EHR: The Use of LOINC Codes
According to the regulation "Decreto del Presidente del Consiglio dei Ministri" (DPCM) of September 29, 2015, n.178, the Logical Observation Identifiers Names and Codes (LOINC) system is included among the coding systems adopted in the Italian Electronic Health Record (EHR). As part of the Digital Health Solutions in Community Medicine (DHEAL-COM) project, one key goal is to categorize parameters using...
Automated Versus Semi-automated Lab Value Extraction for the VA Cardiac Surgical Quality Improvement Program
Introduction: The Veterans Affairs Surgical Quality Improvement Program (VASQIP) trains surgical quality nurses (SQNs) at each Veterans Affairs (VA) hospital to extract or verify 187 variables from the medical record for all cardiac surgical cases. For ten preoperative laboratory values, VASQIP has a semiautomated (SA) system in which local lab values are automatically extracted, verified by SQNs, and lab values...
Why Terminology Standards Matter for Data-driven Artificial Intelligence in Healthcare
Artificial intelligence (AI) has become invaluable in healthcare for disease diagnosis, treatment planning, and clinical decision-making. AI uses algorithms that emulate the human brain to learn, synthesize, analyze, generalize, and solve problems using natural language processing (NLP), machine learning, deep learning, and large language models. The accuracy and performance of AI algorithms depend on the quality and quantity of data...
Standardizing imaging findings representation: harnessing Common Data Elements semantics and Fast Healthcare Interoperability Resources structures
Objectives: Designing a framework representing radiology results in a standards-based data structure using joint Radiological Society of North America/American College of Radiology Common Data Elements (CDEs) as the semantic labels on standard structures. This allows radiologist-created report data to integrate with artificial intelligence-generated results for use throughout downstream systems. Materials and methods: We developed a framework modeling radiology findings as...
Integrating and Adopting AI in the Radiology Workflow: A Primer for Standards and Integrating the Healthcare Enterprise (IHE) Profiles
The deployment of artificial intelligence (AI) solutions in radiology practice creates new demands on existing imaging workflow. Accommodating custom integrations creates a substantial operational and maintenance burden. These custom integrations also increase the likelihood of unanticipated problems. Standards-based interoperability facilitates AI integration with systems from different vendors into a single environment by enabling seamless exchange between information systems in the...
Report of the HIMSS-SIIM Enterprise Imaging Community Data Standards Evaluation Workgroup: Anatomic Ontology Assessment
Previously, the lack of a standard body part ontology has been identified as a critical deficiency needed to enable enterprise imaging. This whitepaper aims to provide a comprehensive assessment of anatomical ontologies with the aim of facilitating enterprise imaging. It offers an overview of the process undertaken by the Health Information Management Systems Society (HIMSS) and Society for Imaging Informatics...
Creation of Standardized Common Data Elements for Diagnostic Tests in Infectious Disease Studies: Semantic and Syntactic Mapping
Background: It is necessary to harmonize and standardize data variables used in case report forms (CRFs) of clinical studies to facilitate the merging and sharing of the collected patient data across several clinical studies. This is particularly true for clinical studies that focus on infectious diseases. Public health may be highly dependent on the findings of such studies. Hence, there...
The Medical Informatics Initiative at a glance-establishing a health research data infrastructure in Germany
The Medical Informatics Initiative (MII) funded by the Federal Ministry of Education and Research (BMBF) 2016-2027 is successfully laying the foundations for data-based medicine in Germany. As part of this funding, 51 new professorships, 21 junior research groups, and various new degree programs have been established to strengthen teaching, training, and continuing education in the field of medical informatics and...
Critically Evaluating the Role for Postoperative Antibiotics in Patients Undergoing Urethroplasty with Buccal Mucosa Graft: A Claims Database Analysis
Objectives: To compare outcomes among patients undergoing first-time urethroplasty with buccal mucosa graft (BMG) who receive post-operative antibiotics versus those who do not. Methods: A retrospective cohort study was conducted using the TriNetX claims database between 2008-2022. Using CPT, ICD10, and LOINC codes, patients >18 years old undergoing primary urethroplasty with BMG who received an outpatient prescription for antibiotics between...
Analysis of laboratory data transmission between two healthcare institutions using a widely used point-to-point health information exchange platform: a case report
Objective: The objective was to identify information loss that could affect clinical care in laboratory data transmission between 2 health care institutions via a Health Information Exchange platform. Materials and methods: Data transmission results of 9 laboratory tests, including LOINC codes, were compared in the following: between sending and receiving electronic health record (EHR) systems, the individual Health Level Seven...
Functional Analysis of G6PD Variants Associated With Low G6PD Activity in the All of Us Research Program
Glucose-6-phosphate dehydrogenase (G6PD) protects red blood cells against oxidative damage through regeneration of NADPH. Individuals with G6PD polymorphisms (variants) that produce an impaired G6PD enzyme are usually asymptomatic, but at risk of hemolytic anemia from oxidative stressors, including certain drugs and foods. Prevention of G6PD deficiency-related hemolytic anemia is achievable through G6PD genetic testing or whole-genome sequencing (WGS) to identify...
Navigating data standards in public health: A brief report from a data-standards meeting
Data standardisation is not merely a technicality but a fundamental cornerstone in the field of public health. It plays a pivotal role in enabling effective data sharing, pooling, analysis, and interpretation, thereby facilitating informed decision-making during infectious disease outbreaks. Despite its undeniable significance, the journey towards achieving data standardisation has been challenging and slow. Even the term ‘data standardisation’ is...
Establishing the Reportable Interval for Routine Clinical Laboratory Tests: A Data-Driven Strategy Leveraging Retrospective Electronic Medical Record Data
Background: This paper presents a data-driven strategy for establishing the reportable interval in clinical laboratory testing. The reportable interval defines the range of laboratory result values beyond which reporting should be withheld. The lack of clear guidelines and methodology for determining the reportable interval has led to potential errors in reporting and patient risk. Methods: To address this gap, the...
Albumin Levels and Risk of Early Cardiovascular Complications After Ischemic Stroke: A Propensity-Matched Analysis of a Global Federated Health Network
Background: No studies have investigated the association between albumin levels and the risk of early cardiovascular complications in patients with ischemic stroke. Methods: Retrospective analysis with a federated research network (TriNetX) based on electronic medical records (International Classification of Diseases-Tenth Revision-Clinical Modification and logical observation identifiers names and codes) mainly reported between 2000 and 2023, from 80 health care organizations...
The Role of HL7 FHIR in the European Project GATEKEEPER
The European Project GATEKEEPER aims to develop a platform and marketplace to ensure a healthier independent life for the aging population. In this platform the role of HL7 FHIR is to provide a shared logical data model to collect data in heterogeneous living, which can be used by AI Service and the Gatekeeper HL7 FHIR Implementation Guide was created for...