Rethinking Human Abstraction as the Gold Standard.

@PedsDataCommons discusses automated approaches for data extraction from electronic health records.

Making sense of artificial intelligence and large language models-including ChatGPT-in pediatric hematology/oncology.

ChatGPT and other artificial intelligence (AI) systems have captivated the attention of healthcare providers and researchers for their potential to improve care processes and outcomes. While these technologies hold promise to automate processes, increase efficiency, and reduce cognitive burden, their use also carries risks. In this commentary, we review basic concepts of AI, outline some of the capabilities and limitations of currently available tools, discuss current and future applications in pediatric hematology/oncology, and provide an evaluation and implementation framework that can be used by pediatric hematologist/oncologists considering the use of AI in clinical practice.

Extracting Electronic Health Record Neuroblastoma Treatment Data With High Fidelity Using the REDCap Clinical Data Interoperability Services Module.

Purpose: Although the International Neuroblastoma Risk Group Data Commons (INRGdc) has enabled seminal large cohort studies, the research is limited by the lack of real-world, electronic health record (EHR) treatment data. To address this limitation, we evaluated the feasibility of extracting treatment data directly from EHRs using the REDCap Clinical Data Interoperability Services (CDIS) module for future submission to the INRGdc.

Methods: Patients enrolled on the Children's Oncology Group neuroblastoma biology study ANBL00B1 (ClinicalTrials.

Targeted Enrollment in Pediatric Oncology Trials: A Vision for Just-in-Time Matching.

@PedsDataCommons shares vision for automated clinical trials matching in pediatric oncology.

An open-source platform for pediatric cancer data exploration: a report from Data for the Common Good.

Objective: The Pediatric Cancer Data Commons (PCDC)-a project of Data for the Common Good-houses clinical pediatric oncology data and utilizes the open-source Gen3 platform. To meet the needs of end users, the PCDC development team expanded the out-of-box functionality and developed additional custom features that should be useful to any group developing similar data commons.

Materials And Methods: Modifications of the PCDC data portal software were implemented to facilitate desired functionality.

Accelerating pediatric Hodgkin lymphoma research: the Hodgkin Lymphoma Data Collaboration (NODAL).

Data commons have proven to be an indispensable avenue for advancing pediatric cancer research by serving as unified information technology platforms that, when coupled with data standards, facilitate data sharing. The Pediatric Cancer Data Commons, the flagship project of Data for the Common Good (D4CG), collaborates with disease-based consortia to facilitate development of clinical data standards, harmonization and pooling of clinical data from disparate sources, establishment of governance structure, and sharing of clinical data. In the interest of international collaboration, researchers developed the Hodgkin Lymphoma Data Collaboration and forged a relationship with the Pediatric Cancer Data Commons to establish a data commons for pediatric Hodgkin lymphoma.

Automated Matching of Patients to Clinical Trials: A Patient-Centric Natural Language Processing Approach for Pediatric Leukemia.

Purpose: Matching patients to clinical trials is cumbersome and costly. Attempts have been made to automate the matching process; however, most have used a trial-centric approach, which focuses on a single trial. In this study, we developed a patient-centric matching tool that matches patient-specific demographic and clinical information with free-text clinical trial inclusion and exclusion criteria extracted using natural language processing to return a list of relevant clinical trials ordered by the patient's likelihood of eligibility.

Data standards in pediatric oncology: Past, present, and future.

In this commentary, we highlight the central role that data standards play in facilitating data-driven efforts to advance research in pediatric oncology. We discuss the current state of data standards for pediatric oncology and propose five steps to achieve an improved future state with benefits for clinicians, researchers, and patients.

Creating a data commons: The INternational Soft Tissue SaRcoma ConsorTium (INSTRuCT).

In this article, we will discuss the genesis, evolution, and progress of the INternational Soft Tissue SaRcoma ConsorTium (INSTRuCT), which aims to foster international research and collaboration focused on pediatric soft tissue sarcoma. We will begin by highlighting the current state of clinical research for pediatric soft tissue sarcomas, including rhabdomyosarcoma and non-rhabdomyosarcoma soft tissue sarcoma. We will then explore challenges and research priorities, describe the development of INSTRuCT, and discuss how the consortium aims to address key research priorities.

Management Practices for Asparaginase-associated Coagulopathy: A Survey of Pediatric Oncologists.

Background: Coagulopathy and thrombosis are well-described complications of asparaginase therapy. However, treatment practices in pediatric hematology/oncology (PHO) patients vary widely as evidence-based guidelines for clinical management of these complications in this population are lacking.

Objective: The objective of this study was to assess management practices of asparaginase-related coagulopathy by pediatric hematologist/oncologist attending physicians.

Drug labeling changes and pediatric hematology/oncology prescribing: Measuring the impact of U.S. legislation.

Background/aims: The Pediatric Research Equity Act and Best Pharmaceuticals for Children Act are intended to promote the conduct of clinical trials that generate pediatric-specific evidence about drug safety and efficacy. This study assesses the quality of evidence generated through Pediatric Research Equity Act-mandated and Best Pharmaceuticals for Children Act-incentivized clinical trials of hematology/oncology drugs and characterizes subsequent changes in pediatric drug utilization rates.

Methods: Trial characteristics (blinding, randomization, and comparator group) were determined for clinical trials that supported pediatric label changes.

PANCYTOPENIA SECONDARY TO AUTOIMMUNE VITAMIN B DEFICIENCY IN GRAVES DISEASE.

Objective: To describe a case of Graves disease (GD) and coexistent pancytopenia associated with autoimmune vitamin B deficiency. While thyrotoxicosis and antithyroid drugs can cause pancytopenia, other autoimmune conditions such as vitamin B deficiency can occur, leading to severe anemia and pancytopenia.

Methods: A 19-year-old female with GD treated with methimazole presented with thyrotoxicosis and evidence of pancytopenia.

Mobile Point-of-Care Medical Photography: Legal Considerations for Health Care Providers.

Medical photographs have been used for decades to document clinical findings. The ease with which medical photographs can be captured and integrated into the electronic health record (EHR) has increased as digital cameras obviated the need for the film development process. Today, cameras integrated into smartphones allow for high-resolution images to be instantly uploaded and integrated into the EHR.

Development of a Taxonomy for Medication-Related Patient Safety Events Related to Health Information Technology in Pediatrics.

Background: Although electronic health records (EHRs) are designed to improve patient safety, they have been associated with serious patient harm. An agreed-upon and standard taxonomy for classifying health information technology (HIT) related patient safety events does not exist.

Objectives: We aimed to develop and evaluate a taxonomy for medication-related patient safety events associated with HIT and validate it using a set of events involving pediatric patients.

Computer-based simulation to reduce EHR-related chemotherapy ordering errors.

Background: The electronic health record (EHR) is a contributor to serious patient harm occurring within a sociotechnical system. Chemotherapy ordering is a high-risk task due to the complex nature of ordering workflows and potential detrimental effects if wrong chemotherapeutic doses are administered. Many chemotherapy ordering errors cannot be mitigated through systems-based changes due to the limited extent to which individual institutions are able to customize proprietary EHR software.

Clinical evaluation and diagnostic yield following evaluation of abnormal pulse detected using Apple Watch.

Objective: The study sought to characterize the evaluation of patients who present following detection of an abnormal pulse using Apple Watch.

Materials And Methods: We conducted a retrospective review of patients evaluated for abnormal pulse detected using Apple Watch over a 4-month period.

Results: Among 264 included patients, clinical documentation for 41 (15.

Implementation of Artificial Intelligence-Based Clinical Decision Support to Reduce Hospital Readmissions at a Regional Hospital.

Background: Hospital readmissions are a key quality metric, which has been tied to reimbursement. One strategy to reduce readmissions is to direct resources to patients at the highest risk of readmission. This strategy necessitates a robust predictive model coupled with effective, patient-centered interventions.

What's in a name? A comparison of attitudes towards artificial intelligence (AI) versus augmented human intelligence (AHI).

Background: "Artificial intelligence" (AI) is often referred to as "augmented human intelligence" (AHI). The latter term implies that computers support-rather than replace-human decision-making. It is unclear whether the terminology used affects attitudes and perceptions in practice.

Cerebral sinovenous thrombosis in pediatric hemolytic uremic syndrome.

Hemolytic uremic syndrome (HUS) may result in thrombotic central nervous system complications. We present a child with diarrhea-associated HUS who developed new-onset focal seizures secondary to cerebral sinovenous thrombosis (CSVT). Her CSVT was treated with low-molecular-weight heparin.

Patients' Experiences and Attitudes of Using a Secure Mobile Phone App for Medical Photography: Qualitative Survey Study.

Background: Point-of-care clinical photography using mobile devices is coming of age as a new standard of care for clinical documentation. High-quality cameras in modern smartphones facilitate faithful reproduction of clinical findings in photographs; however, clinical photographs captured on mobile devices are often taken using the native camera app on the device and transmitted using relatively insecure methods (eg, SMS text message and email) that do not preserve images as part of the electronic medical records. Native camera apps lack robust security features and direct integration with electronic health records (EHRs), which may limit patient acceptability and usefulness to clinicians.

A lesson in implementation: A pre-post study of providers' experience with artificial intelligence-based clinical decision support.

Background: To explore attitudes about artificial intelligence (AI) among staff who utilized AI-based clinical decision support (CDS).

Methods: A survey was designed to assess staff attitudes about AI-based CDS tools. The survey was anonymously and voluntarily completed by clinical staff in three primary care outpatient clinics before and after implementation of an AI-based CDS system aimed to improve glycemic control in patients with diabetes as part of a quality improvement project.