Population Segmentation Based on Healthcare Needs: Validation of a Brief Clinician-Administered Tool.

BACKGROUND: As populations age with increasingly complex chronic conditions, segmenting populations into clinically meaningful categories of healthcare and related service needs can provide healthcare planners with crucial information to optimally meet needs. However, while conventional approaches typically involve electronic medical records (EMRs), such records do not always capture information reliably or accurately. OBJECTIVE: We describe the inter-rater reliability and predictive validity of a clinician-administered tool, the Simple Segmentation Tool (SST) for categorizing older individuals into one of six Global Impression (GI) segments and eight complicating factors (CFs) indicative of healthcare and related social needs. DESIGN: Observational study ( ClinicalTrials.gov , number NCT02663037). PARTICIPANTS: Patients aged 55 years and above. MAIN MEASURES: Emergency department (ED) subjects (between May and June 2016) had baseline SST assessment by two physicians and a nurse concurrently seeing the same individual. General medical (GM) ward subjects (February 2017) had a SST assessment by their principal physician. Adverse events (ED visits, hospitalizations, and mortality over 90 days from baseline) were determined by a blinded reviewer. Inter-rater reliability was measured using Cohen's kappa. Predictive validity was evaluated using Cox hazard ratios based on time to first adverse event. KEY RESULTS: Cohen's kappa between physician-physician, service physician-nurse, and physician-nurse pairs for GI were 0.60, 0.71, and 0.68, respectively. Cox analyses demonstrated significant predictive validity of GI and CFs for adverse outcomes. CONCLUSIONS: With modest training, clinicians can complete a brief instrument to segment their patient into clinically meaningful categories of healthcare and related service needs. This approach can complement and overcome current limitations of EMR-based instruments, particularly with respect to whole-patient care. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02663037.

Autoimmune Switch From Graves' Disease to Hashimoto's Thyroiditis With Coexisting Sjogren's Syndrome: A Case of Polyautoimmunity in a Young Woman.

Autoimmune thyroid disease (AITD) encompasses a spectrum of conditions ranging from Graves' disease (GD) to Hashimoto's thyroiditis (HT). These conditions often coexist with other autoimmune diseases (AIDs). This case describes a young woman in her 20s who transitioned from GD to HT during her first pregnancy, while having another coexisting AID, Sjogren's syndrome (SS). AITD and SS are recognized as the most common polyautoimmune diseases, sharing many common pathophysiological characteristics such as the presence of lymphocytic infiltrates, similar expressions of the human leukocyte antigen molecules, and predisposing environmental factors. This case underscores the importance for physicians to be vigilant regarding the possibility of changing antibodies in AITD and the potential for concurrent AIDs in a single individual. It highlights the need for screening such patients for comprehensive management.

Impact of an End-User-Designed Education Bundle for Electronic Health Records System Education of House Officers.

Introduction The benefits of Electronic Health Records (EHR) use in clinical care are well documented. However, without proper education and training on EHR systems, clinicians may face challenges in utilizing these technological tools effectively. Suboptimal usage of EHR systems can affect productivity. This study assesses the effectiveness of an end-user-designed education bundle as a supplement to existing training in EHR training for house officers. Additionally, it evaluates the effectiveness of using non-conventional teaching modalities (i.e., short TikTok-style videos) to see how effective and accepted it was in comparison to traditional educational material. Methods A single-armed pre-post-study design consisting of 36 house officers was employed to evaluate the effectiveness of the intervention bundle. The bundle consists of a series of EHR tips and tricks as identified by experienced senior medical officers. The three components of the bundle are a handbook with consolidated tips and tricks, a long-form lecture video, and a series of TikTok-style videos. Distribution was done through healthcare collaborative platforms such as TigerConnect™ (Los Angeles, USA) and email. Results Participants found that the inclusion of our supplementary education bundle results in more effective training for EHR usage, with mean effectiveness with and without the educational bundle being 7.77 and 6.44, respectively (p < 0.001). There were also significant improvements in ease of finding information (7.67 vs 7.14, p = 0.016), performing general functions (7.50 vs 6.89, p = 0.0050), and overall efficiency (7.39 vs 6.92, p = 0.022). We also found TikTok-style videos were non-inferior to more traditional forms of education such as a handbook and traditional long-form lecture videos (p = 0.250). Conclusion An end-user-driven education bundle focusing on high-yield, advanced functions may be useful in enhancing the overall EHR system experience for junior doctors. Of note, TikTok-style videos may be no less effective than traditional methods of EHR teaching.