ChartWalk: Navigating large collections of text notes in electronic health records for clinical chart review.

Before seeing a patient for the first time, healthcare workers will typically conduct a comprehensive clinical chart review of the patient's electronic health record (EHR). Within the diverse documentation pieces included there, text notes are among the most important and thoroughly perused segments for this task; and yet they are among the least supported medium in terms of content navigation and overview. In this work, we delve deeper into the task of clinical chart review from a data visualization perspective and propose a hybrid graphics+text approach via ChartWalk, an interactive tool to support the review of text notes in EHRs. We report on our iterative design process grounded in input provided by a diverse range of healthcare professionals, with steps including: (a) initial requirements distilled from interviews and the literature, (b) an interim evaluation to validate design decisions, and (c) a task-based qualitative evaluation of our final design. We contribute lessons learned to better support the design of tools not only for clinical chart reviews but also other healthcare-related tasks around medical text analysis.

PhenoPad: Building AI enabled note-taking interfaces for patient encounters.

Current clinical note-taking approaches cannot capture the entirety of information available from patient encounters and detract from patient-clinician interactions. By surveying healthcare providers' current note-taking practices and attitudes toward new clinical technologies, we developed a patient-centered paradigm for clinical note-taking that makes use of hybrid tablet/keyboard devices and artificial intelligence (AI) technologies. PhenoPad is an intelligent clinical note-taking interface that captures free-form notes and standard phenotypic information via a variety of modalities, including speech and natural language processing techniques, handwriting recognition, and more. The output is unobtrusively presented on mobile devices to clinicians for real-time validation and can be automatically transformed into digital formats that would be compatible with integration into electronic health record systems. Semi-structured interviews and trials in clinical settings rendered positive feedback from both clinicians and patients, demonstrating that AI-enabled clinical note-taking under our design improves ease and breadth of information captured during clinical visits without compromising patient-clinician interactions. We open source a proof-of-concept implementation that can lay the foundation for broader clinical use cases.

A Cross-Sectional Study of Nemaline Myopathy.

OBJECTIVE: Nemaline myopathy (NM) is a rare neuromuscular condition with clinical and genetic heterogeneity. To establish disease natural history, we performed a cross-sectional study of NM, complemented by longitudinal assessment and exploration of pilot outcome measures. METHODS: Fifty-seven individuals with NM were recruited at 2 family workshops, including 16 examined at both time points. Participants were evaluated by clinical history and physical examination. Functional outcome measures included the Motor Function Measure (MFM), pulmonary function tests (PFTs), myometry, goniometry, and bulbar assessments. RESULTS: The most common clinical classification was typical congenital (54%), whereas 42% had more severe presentations. Fifty-eight percent of individuals needed mechanical support, with 26% requiring wheelchair, tracheostomy, and feeding tube. The MFM scale was performed in 44 of 57 participants and showed reduced scores in most with little floor/ceiling effect. Of the 27 individuals completing PFTs, abnormal values were observed in 65%. Last, bulbar function was abnormal in all patients examined, as determined with a novel outcome measure. Genotypes included mutations in ACTA1 (18), NEB (20), and TPM2 (2). Seventeen individuals were genetically unresolved. Patients with pathogenic ACTA1 and NEB variants were largely similar in clinical phenotype. Patients without genetic resolution had more severe disease. CONCLUSION: We present a comprehensive cross-sectional study of NM. Our data identify significant disabilities and support a relatively stable disease course. We identify a need for further diagnostic investigation for the genetically unresolved group. MFM, PFTs, and the slurp test were identified as promising outcome measures for future clinical trials.

Doccurate: A Curation-Based Approach for Clinical Text Visualization.

Before seeing a patient, physicians seek to obtain an overview of the patient's medical history. Text plays a major role in this activity since it represents the bulk of the clinical documentation, but reviewing it quickly becomes onerous when patient charts grow too large. Text visualization methods have been widely explored to manage this large scale through visual summaries that rely on information retrieval algorithms to structure text and make it amenable to visualization. However, the integration with such automated approaches comes with a number of limitations, including significant error rates and the need for healthcare providers to fine-tune algorithms without expert knowledge of their inner mechanics. In addition, several of these approaches obscure or substitute the original clinical text and therefore fail to leverage qualitative and rhetorical flavours of the clinical notes. These drawbacks have limited the adoption of text visualization and other summarization technologies in clinical practice. In this work we present Doccurate, a novel system embodying a curation-based approach for the visualization of large clinical text datasets. Our approach offers automation auditing and customizability to physicians while also preserving and extensively linking to the original text. We discuss findings of a formal qualitative evaluation conducted with 6 domain experts, shedding light onto physicians' information needs, perceived strengths and limitations of automated tools, and the importance of customization while balancing efficiency. We also present use case scenarios to showcase Doccurate's envisioned usage in practice.