Statistical methods to harmonize electronic health record data across healthcare systems: case study and lessons learned

Bioinformatics · 2026-02-28

MOTIVATION: Although common data models for electronic health record (EHR) data can facilitate multi-site data organization and querying, the same medical event may still be coded differently between healthcare systems. In this paper, we present statistical methods to identify and mitigate coding discrepancies using summary-level data, and demonstrate these methods using data from two FDA Sentinel data partners: Kaiser Permanente Washington and Kaiser Permanente Northwest. RESULTS: We first characterize differences in coding patterns, then compute a code mapping matrix to harmonize data between systems. Our findings reveal significant heterogeneity in coded EHR data, even after adopting a common data model with the same coding system, highlighting the importance of data harmonization before downstream analyses. Our study also demonstrates the effectiveness of the data harmonization approaches, which provide a foundational data quality step to promote semantic interoperability, enhance data integration, and improve the integrity of study conclusions. AVAILABILITY AND IMPLEMENTATION: Computation prototypes, including R/Python codes and examples, are included in Section 7, available as supplementary data at Bioinformatics online and will be posted on GitHub upon publication.

A Systematic Process for Assessing Fitness‐for‐Purpose of Health Outcomes for Computable Phenotyping With Electronic Health Record Data

Pharmacoepidemiology and Drug Safety · 2026-03-01

PURPOSE: Information from electronic health records (EHRs) may be incorporated into computable phenotype algorithms in efforts to overcome inaccuracies of algorithms based on administrative claims data alone. However, such efforts can be resource-intensive and unsuccessful. Assessing the feasibility of computable phenotyping for a health outcome of interest (HOI) before proceeding is therefore recommended. METHODS: We developed a systematic fitness-for-purpose (FFP) assessment process to implement concepts outlined in a previously described general framework for computable phenotyping incorporating EHR data. Our process includes verifying the HOI is well-defined, reviewing clinical information about the HOI, identifying existing algorithms and their performance, evaluating HOI clinical and data complexity, and determining an overall FFP conclusion and recommendation. We applied this process to 10 HOIs lacking high-performing claims-based algorithms, selecting HOIs of public health importance that varied in clinical and data complexity, including neutropenia, pericardial effusion, and drug-induced liver injury. RESULTS: HOIs assessed as having moderate (vs. easy) overall difficulty had characteristics such as the need for natural language processing, integration of multiple laboratory test results, or longitudinal EHR data. HOIs assessed as having high difficulty required using data from multiple EHR sources, ruling out many other potential causes, or relying on low-sensitivity diagnostic tests. Input from experts in EHR data and clinical care was crucial. CONCLUSION: EHR data have the potential to enhance the accuracy of defining certain HOIs for research and surveillance compared to administrative claims data. The process and tools we created will support others in assessing FFP of HOIs for computable phenotyping.

Estimating Risk Differences Using Large Healthcare Data Networks for Medical Product Post‐Market Safety Outcomes in a Distributed Data Setting and Allowing for Active Post‐Market Surveillance

Statistics in Medicine · 2026-02-27

Risk differences allow decision makers to easily estimate the excess safety risk associated with a medical product relative to the potential benefits. However, in post-market observational surveillance studies that actively monitor (e.g., sequentially over time) for safety risk of new medical products, available methods target a relative measure (e.g., odds ratio and relative risk), which can be especially unstable in the rare event setting. These studies are typically conducted within distributed healthcare networks (e.g., Food and Drug Administration [FDA] Sentinel and Centers for Disease Control [CDC] Vaccine Safety Datalink) with patient-level data protected behind firewalls, but sharing of aggregate, deidentified data for centralized analyses. We propose an inverse probability of treatment weighting (IPTW) method that uses site-specific propensity scores to estimate site-specific risk differences that are combined to create an overall stratified risk difference estimate. This method is tailored to the rare event setting and requires minimal data sharing. The stratified IPTW approach is then extended to the active post-market surveillance setting by incorporating group sequential monitoring boundaries using a novel permutation approach. A simulation study is conducted to evaluate the performance of the new methods relative to two centralized analysis approaches, and the methods are applied to a safety surveillance study comparing the risk of febrile seizure between two vaccines using FDA Sentinel Data from three healthcare organizations.

Abstract DP373: Patient-Reported Quality of Life and Symptom Associations in Pediatric Familial Cerebral Cavernous Malformation

Stroke · 2026-01-29

Background: Familial cerebral cavernous malformation (fCCM) is an autosomal dominant neurovascular disorder characterized by multiple lesions that increase risk of intracranial hemorrhage (ICH), seizures, and headaches. The impact of these symptoms on physical, mental, and social quality of life (QoL) in children with fCCM is unknown. We aimed to assess QoL domains and their associations with clinical symptoms and functional status at baseline and longitudinally in pediatric fCCM. Methods: Patient-Reported Outcomes Measurement Information System (PROMIS) surveys were completed by children or parent proxy for 66 pediatric fCCM participants (ages 5–17) enrolled in the Brain Vascular Malformation Consortium CCM study (2019–2025). Domain scores were converted to T-scores standardized to a U.S. pediatric reference population (mean=50, SD=10); higher scores reflect worse QoL. One-sample t-tests compared domain scores to population norms. Multivariable regression assessed associations between baseline PROMIS scores and prior ICH, seizures, headaches, or modified Rankin Scale (mRS) scores, adjusting for age, sex, and respondent type. Longitudinal analyses evaluated whether new symptom onset was associated with changes in PROMIS scores over time. Results: Among 66 participants (mean age 11.6±4.5), <50% reported prior ICH, seizures, or headaches; 93.3% had mRS scores of 0–1. PROMIS scores in anxiety (45.59 [95% CI: 42.51–48.67], p=0.006), depression (43.89 [41.63–46.14], p<0.001), fatigue (41.7 [39.03–44.37], p<0.001), and pain (43.29 [40.84–45.74], p<0.001) were significantly better than population norms. No significant baseline symptom-domain associations were observed, though moderate effect sizes were noted for prior ICH and worse fatigue (+3.83), mobility (+3.01), and sleep disturbance (+4.34); and for prior headache and fatigue (+3.64). Longitudinally, new headache onset was associated with increasing fatigue (+5.59 [0.046–11.13], p=0.048), with trends for worsening anxiety, pain, and sleep. Higher mRS scores correlated with worse pain (p=0.001), mobility (p=0.004), and sleep (p=0.011). Conclusions: PROMIS surveys captured QoL variation in pediatric fCCM, with moderate symptom-domain associations and significant correlations with mRS scores. Longitudinal changes in PROMIS scores tracked evolving symptom burden, particularly with new onset headaches and fatigue. Larger studies are needed to confirm PROMIS validity and refine its clinical utility in pediatric fCCM.

Transport infrastructure development and travel behaviour change: summary of research and future directions

Transportation Planning and Technology · 2026-03-30

Prevalencia de tuberculosis latente en pacientes con artritis reumatoide y su relación con característica sociodemográficas y clínicas

Global Rheumatology · 2025-09-30

Objetivo: El objetivo de este estudio fue determinar la prevalencia de tuberculosis latente (ITBL) y su relación con características sociodemográficas y clínicas en pacientes con artritis reumatoide (AR). Metodología: Estudio transversal analítico, que incluyo 538 pacientes atendidos en un centro de excelencia colombiano especializado en AR. A los pacientes se les realizó la prueba cutánea de la tuberculina (TST). Los umbrales de esta prueba se definieron de acuerdo con las recomendaciones de los CDC. Se estratificó el análisis por sexo, tipo de tratamiento (terapia convencional y biológica) y LTBI negativo y positivo (grupos diagnósticos). Resultados: Se estimó una prevalencia de TST positiva de 12,1% (65/538; IC 95% 9,6%-15,1%) en AR. Se encontró una prevalencia de 14,8% (12/81; IC 95% 8,7%-24,1%) en hombres y 11,6% (53/457; IC 95% 9,0%-14,9%) en mujeres. Las edades de los pacientes oscilaban entre 19 y 92 años (media, 57 años; DE, 12,0), la proporción mujer-hombre era de 5,6, y la mediana de tiempo transcurrido desde el diagnóstico de AR era de 17,3 años (IQR, 8,8-17,8). La prevalencia de LTBI no se asoció significativamente con las características sociodemográficas y clínicas de los pacientes con AR, excepto el tiempo transcurrido desde el diagnóstico de AR, que mostró una débil evidencia de asociación (p=0,034; r=0,1). Conclusiones: Este estudio es una de las primeras aproximaciones en Colombia para estimar la prevalencia de LTBI en pacientes con artritis reumatoide. La prevalencia de LTBI se asoció débilmente con el tiempo desde el diagnóstico de AR.

129 Words and the Weight of Worlds

SSRN Electronic Journal · 2025-01-01

Vascular Organoids Derived from Capillary malformation-induced Pluripotent Stem Cells Exhibit Disease-Relevant Phenotypes

Stem Cell Reviews and Reports · 2025-09-25 · 1 citations

Capillary malformation (CM) is a congenital vascular anomaly that affects the skin, mucosa, eye, and brain. A major obstacle to mechanistic and drug screening studies for CM has been the lack of preclinical models. In this study, we established vascular organoids (VOs) generated through the self-assembly of vascular lineages of endothelial cells and smooth muscle cells differentiated from CM-induced pluripotent stem cells (iPSC). Within these VOs induced endothelial cells and smooth muscle cells organized into juxtapositions to form vascular branches. CM patient iPSC-derived VOs showed a higher density of endothelial and smooth muscle cell populations and greater vascular branch lengths as compared with VOs derived from iPSCs generated from healthy skin biopsies. Overall, this study represents the first disease-relevant VO model of CM, providing a valuable platform for future mechanistic studies and drug screening.

NASA Innovative Advanced Concepts (NIAC) Program

2025-07-16 · 3 citations

The NASA Innovative Advanced Concepts (NIAC) Program nurtures visionary ideas that could transform future aerospace missions with the creation of breakthroughs — radically better or entirely new aerospace concepts — while engaging America's innovators and entrepreneurs as partners in the journey. NIAC is unique within NASA. It is a program that values both technical acumen and imagination, inspired by curiosity and the quest for knowledge. We encourage innovators to be creative and attempt great leaps forward in aerospace. NIAC studies explore innovative, technically credible, advanced concepts that could one day “Change the Possible” in aerospace. NIAC is open to all categories of U.S. organizations. Non-U.S. organizations may partner in, or lead, NIAC studies on a no-exchange-of-funds basis, and subject to NASA’s policy on foreign participation. NIAC supports innovative research through multiple phases of study, all competitively awarded. Phase I studies are nine-month efforts to explore the overall viability of visionary concepts. Phase II studies further develop the most promising Phase I concepts for up to two years, addressing key challenges and developing a technology roadmap for eventual implementation. Phase III studies further advance, for up to two years, those technologies which uniquely require NIAC support to facilitate transition into other NASA, government, or commercial programs. A NIAC concept must be relevant to NASA’s Vision and Mission, innovative, of high potential impact, credible and reasonable, and examined in a reference mission. The reference mission is a key feature of NIAC studies, facilitating concept assessment in a space or aeronautics mission context to demonstrate that it would be worth further development. This paper provides an update to NIAC’s history and current role including process, additional summary statistics about its selections, status of outreach, and examples of some visionary and credible studies and impacts.

The Integration of ICT in Healthcare: A Mixed-Methods Assessment of Its Effectiveness and Limitations

Journal of Innovations · 2025-07-02

From the implementation of simple staffing systems and basic technologies in the late 20th century to today’s sophisticated patient tracking platforms and AI-driven data analytics, Information and Communication Technology (ICT) has played a pivotal role in transforming healthcare globally. This report examines the effectiveness of ICT in healthcare, focusing particularly on integrated patient portals and mobile health applications. Drawing on industry research and supported by data collected through surveys and interviews with teenagers, adults, seniors, and healthcare professionals, the findings confirm that ICT has significantly improved access to patient records and enhanced communication between patients and healthcare providers. However, ICT is not without flaws. Several participants expressed concerns regarding patient portals, particularly their poor user interfaces (UI), insufficient privacy protections, high costs, and the automated delivery of test results without adequate context or follow-up. Ultimately, the findings highlight both the promise of ICT in modern healthcare and the key challenges that must be addressed to optimize its future implementation.