Umberto Tachinardi

Objective: To develop and externally validate prediction models for next‐year falls in Parkinson's disease (PD), and to evaluate the incremental value of imaging and fluid biomarkers. Methods: We developed models in Parkinson's Progression Markers Initiative (PPMI) to predict next‐year falls with external validation in University of Pennsylvania (UPenn) cohorts. We evaluated incident falls among visits without current or prior falls and recurrent falls among visits with current falls. We calculated area under the receiver operating characteristic curve (AUROC), area under the precision‐recall curve (AUPRC), and development‐derived risk strata. Results: The incident model, comprising Movement Disorder Society–Unified Parkinson's Disease Rating Scale Part III, Montreal Cognitive Assessment, and Geriatric Depression Scale (GDS), was developed in 773 visit‐pairs and validated in 589 visit‐pairs. AUROC was 0.704 (95% confidence interval [CI] = 0.653–0.750) in PPMI and 0.630 (95% CI = 0.564–0.687) in UPenn. Incident fall risk increased from 7.1 to 18.5% across low‐ to high‐risk groups in UPenn. The recurrent model, comprising Hoehn and Yahr (H&Y), GDS, and Symbol Digit Modalities Test, was developed in 302 visit‐pairs and validated in 137 visit‐pairs. AUROC was 0.683 (95% CI = 0.623–0.753) in PPMI and 0.641 (95% CI = 0.538–0.732) in UPenn. Recurrent fall rates increased from 22.2 to 65.0% across low‐ to high‐risk groups in UPenn. Exploratory biomarker augmentation modestly improved discrimination beyond clinical models in PPMI, but not in external validation, where estimates were imprecise. Interpretation: Clinical measures may identify next‐year fall risk in PD with moderate discrimination, although performance attenuated in external validation. Exploratory biomarkers provided modest incremental value in development but not in external validation. ANN NEUROL 2026

Purpose: Visual analytics is a nascent and underexplored area in the medical education literature that can assist in synthesizing large volumes of data and information to provide actionable insight. This scoping review aims to identify: 1) the characteristics of the studies that have applied visual analytics in medical education, 2) how visual analytics are being used to support medical education efforts. Method: This study followed the Joanna Briggs Institute (JBI) scoping review guidelines to search four databases in mid-April 2026: PubMed, IEEE Xplore, Scopus, ACM Digital, along with Google Scholar. Key search terms included “medical education” and “visual analytics”; papers that did not implement visual analytics systems in the medical education context were excluded. Variables of the eligible papers were extracted and further analyzed in terms of study characteristics (publication year, study location, primary focus & level of trainees assessed) and application of visual analytics (type of visualization, framework guidance, hardware/software, evaluation technique). Results: Of the 39 eligible papers from 584 screened, 20 (51.3%) were published in the United States. Using visual analytics for learner competency assessment and quality improvement of training programs were the primary focuses. For trainees, nearly all papers focused on assessing residents and medical students. More than 28 (71.8%) studies utilized an interactive tool/dashboard and/or applied an evaluation technique. Only 14 (35.9%) involved a framework-guided design of the visualization. Conclusions: This review highlights that while visual analytics is maturing in medical education, systemic application requires adopting framework-guided visualization design, expertise-matched tools, and goal-oriented evaluation. Future research should prioritize interoperable frameworks for knowledge sharing, controlled field studies assessing impacts on learner competencies, and patient outcomes, and "cross-continuum" dashboards spanning pre-medical through faculty levels. These strategies allow educators and learners to make sense of complex educational data through visual analytics dashboards, ultimately enhancing assessment and patient care quality.

INTRODUCTION It is well known that global excitement for Artificial Intelligence (AI) has reached an all-time high in healthcare, offering transformative opportunities across clinical decisions, diagnostics, operations, and administrative functions.() Intensive care units (ICUs) are especially well-positioned to benefit from AI, as patients are continuously monitored, producing a rich, multimodal stream of data that makes […] INTRODUCTION It is well known that global excitement for Artificial Intelligence (AI) has reached an all-time high in healthcare, offering transformative opportunities across clinical decisions, diagnostics, operations, and administrative functions.() Intensive care units (ICUs) are especially well-positioned to benefit from AI, as patients are continuously monitored, producing a rich, multimodal stream of data that makes […]

Background: The role of the Chief Research Informatics Officer (CRIO) is emerging in academic health centers to address the challenges clinical researchers face in the increasingly digitalized, data-intensive healthcare system. Most current CRIOs are the first officers in their institutions to hold that role. To date there is very little published information about this role and the individuals who serve it. Objective: To increase our understanding of the CRIO role, the leaders who serve it, and the factors associated with their success in their organizations. Methods: The Clinical Research Informatics Working Group of the American Medical Informatics Association (AMIA) conducted a national survey of CRIOs in the United States and convened an expert panel of CRIOs to discuss their experience during the 2016 AMIA Annual Symposium. Results: CRIOs come from diverse academic backgrounds. Most have advance training and extensive experience in biomedical informatics but the majority have been CRIOs for less than three years. CRIOs identify funding, data governance, and advancing data analytics as their major challenges. Conclusion: CRIOs play an important role in helping shape the future of clinical research, innovation, and data analytics in healthcare in their organizations. They share many of the same challenges and see the same opportunities for the future of the field. Better understanding the background and experience of current CRIOs can help define and develop the role in other organizations and enhance their influence in the field of research informatics. Citation: Sanchez-Pinto LN, Mosa ASM, Fultz-Hollis K, Tachinardi U, Barnett WK, Embi PJ. The Emerging Role of the Chief Research Informatics Officer in Academic Health Centers. Appl Clin Inform 2017; 8: 845–853 https://doi.org/10.4338/ACI-2017-04-RA-0062 ^* For the Clinical Research Informatics Working Group of the American Medical Informatics Association. Clinical Relevance Statement The role of the Chief Research Informatics Officer (CRIO) is emerging in academic health centers to address the challenges clinical researchers face in the increasingly digitalized, data-intensive healthcare system. To date there has been very little published information about this role and the individuals who serve it. Better understanding the background and experience of current CRIOs can help define and develop the role in other organizations and enhance their influence in the future of research informatics. Human Subjects Protections The study was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects, and was reviewed by the University of Missouri-Columbia and The University of Chicago Institutional Review Boards.

Since the inception of the Clinical and Translational Science Award (CTSA) program in 2006, leaders in education across CTSA sites have been developing and updating core competencies for Clinical and Translational Science (CTS) trainees. By 2009, 14 competency domains, including biomedical informatics, had been identified and published. Since that time, the evolution of the CTSA program, changes in the practice of CTS, the rapid adoption of electronic health records (EHRs), the growth of biomedical informatics, the explosion of big data, and the realization that some of the competencies had proven to be difficult to apply in practice have made it clear that the competencies should be updated. This paper describes the process undertaken and puts forth a new set of competencies that has been recently endorsed by the Clinical Research Informatics Workgroup of AMIA. In addition to providing context and background for the current version of the competencies, we hope this will serve as a model for revision of competencies over time.

New vocabularies are rapidly evolving in the literature relative to the practice of clinical medicine and translational research. To provide integrated access to new terms, we developed a mobile and desktop online reference-Marshfield Dictionary of Clinical and Translational Science (MD-CTS). It is the first public resource that comprehensively integrates Wiktionary (word definition), BioPortal (ontology), Wiki (image reference), and Medline abstract (word usage) information. MD-CTS is accessible at http://spellchecker.mfldclin.edu/. The website provides a broadened capacity for the wider clinical and translational science community to keep pace with newly emerging scientific vocabulary. An initial evaluation using 63 randomly selected biomedical words suggests that online references generally provided better coverage (73%-95%) than paper-based dictionaries (57-71%).

Objective The completion of sequencing the human genome in 2003 has spurred the production and collection of genetic data at ever increasing rates. G

Advances in health information technology and biomedical informatics have laid the groundwork for significant improvements in healthcare and biomedical research. For instance, Electronic Health Records can help improve the delivery of evidence-based care, enhance quality, and contribute to discoveries and evidence generation. Despite this promise, there are many challenges to achieving the vision and missions of our healthcare and research enterprises. Given the challenges inherent in doing so, institutions are increasingly moving to establish dedicated leadership and governance models charged with designing, deploying and leveraging various information resources to advance research and advanced care activities at AHCs. Some institutions have even created a new leadership position to oversee such activities, such as the Chief Research Information Officer. This panel will include research informatics leaders discussing their experiences from the proverbial trenches as they work to operationalize such cross-mission governance models. Panelists will start by providing an overview their respective positions and environments, discuss their experiences, and share lessons learned through their work at the intersection of clinical and translational research informatics and Health IT.

Image storage and retrieval make medical image departments unique in terms of information systems. The PACS concept was developed as a solution for integrating medical image systems. On the other hand, hospital information systems (HIS) were oriented towards text-based data. Today many hospitals suffer from the lack of integration between both systems. In the authors' institution this question was addressed a few years ago and the authors have decided to develop a fresh HIS with PACS embedded capabilities. To approach this problem, a small-scale prototype is under implementation at InCor's Nuclear Cardiology Department. Here, the authors highlight the importance of using open systems and conceptual modeling to make PACS and HIS integration not only feasible but also rewarding.

Traditional paper-based Medical Records, and even most of their digital counterparts, represent historical patient information. On the other hand new generations of Point-of-Care devices can be connected to standard networks and deliver streams of real time data through an Intranet, or even the Internet. Vital signs provided by IP-based devices can then be viewed at remote stations. Merging both worlds, real time and historical, in the pursuit of a comprehensive EPR is the main challenge of the present project. The basic infra-structure is composed of three main components: an existing Web-based EPR viewing station1 (Web-EPR); a fully integrated HIS/PACS system1; and a monitoring network (Siemens Infinity Network 2). Communication between the components was obtained by developing interfaces based on both HL7 and Siemens protocols the later only for waveforms. For the graphical display a web-browser-based application of the streamed signals was developed and integrated into the existing Web-EPR. This addition expanded the Web-EPR capabilities providing means to include real time signals and calculated parameters on the set of information already available. Some extra features of this project include: one-way SMS messaging of the parameters, interactive WAP access and a DICOM compliant storage of signal waveforms.