Leveraging Existing Datasets to Advance Family Caregiving Research: Opportunities to Measure What Matters.

More than 17.7 million people in the U.S. care for older adults. Analyzing population datasets can increase our understanding of the needs of family caregivers of older adults. We reviewed 14 U.S. population-based datasets (2003-2023) including older adults' and caregivers' data to assess inclusion and measurement of 8 caregiving science domains, with a focus on whether measures were validated and/or unique variables were used. Challenges exist related to survey design, sampling, and measurement. Findings highlight the need for consistent data collection by researchers, state, tribal, local, and federal programs, for improved utility of population-based datasets for caregiving and aging research.

The case for open science: rare diseases.

The premise of Open Science is that research and medical management will progress faster if data and knowledge are openly shared. The value of Open Science is nowhere more important and appreciated than in the rare disease (RD) community. Research into RDs has been limited by insufficient patient data and resources, a paucity of trained disease experts, and lack of therapeutics, leading to long delays in diagnosis and treatment. These issues can be ameliorated by following the principles and practices of sharing that are intrinsic to Open Science. Here, we describe how the RD community has adopted the core pillars of Open Science, adding new initiatives to promote care and research for RD patients and, ultimately, for all of medicine. We also present recommendations that can advance Open Science more globally.

An update on the use of health information technology in newborn screening.

Newborn screening (NBS) has high-stakes health implications and requires rapid and effective communication between many people and organizations. Multiple NBS stakeholders worked together to create national guidance for reporting NBS results with HL7 (Health Level 7) messages that contain LOINC (Logical Observation Identifiers Names and Codes) and SNOMED-CT (Systematized Nomenclature of Medicine-Clinical Terms) codes, report quantitative test results, and use standardized computer-readable UCUM units of measure. This guidance (a LOINC panel and an example annotated HL7 message) enables standard HL7 v2.5.1 laboratory messages to carry the information required for reporting NBS results. Other efforts include HL7 implementation guides for reporting point-of-care (POC) NBS results as well as standardizing follow-up of patients diagnosed with conditions identified through NBS. If the guidance is used nationally, regional and national registries can aggregate results from state programs to facilitate research and quality assurance and help ensure continuity of operations following a disaster situation.