Development and validation of a pragmatic natural language processing approach to identifying falls in older adults in the emergency department

BACKGROUND: Falls among older adults are both a common reason for presentation to the emergency department, and a major source of morbidity and mortality. It is critical to identify fall patients quickly and reliably during, and immediately after, emergency department encounters in order to deliver appropriate care and referrals. Unfortunately, falls are difficult to identify without manual chart review, a time intensive process infeasible for many applications including surveillance and quality reporting. Here we describe a pragmatic NLP approach to automating fall identification. METHODS: In this single center retrospective review, 500 emergency department provider notes from older adult patients (age 65 and older) were randomly selected for analysis. A simple, rules-based NLP algorithm for fall identification was developed and evaluated on a development set of 1084 notes, then compared with identification by consensus of trained abstractors blinded to NLP results. RESULTS: The NLP pipeline demonstrated a recall (sensitivity) of 95.8%, specificity of 97.4%, precision of 92.0%, and F1 score of 0.939 for identifying fall events within emergency physician visit notes, as compared to gold standard manual abstraction by human coders. CONCLUSIONS: Our pragmatic NLP algorithm was able to identify falls in ED notes with excellent precision and recall, comparable to that of more labor-intensive manual abstraction. This finding offers promise not just for improving research methods, but as a potential for identifying patients for targeted interventions, quality measure development and epidemiologic surveillance

Pertuzumab, trastuzumab, and chemotherapy in HER2-positive gastric/gastroesophageal junction cancer: end-of-study analysis of the JACOB phase III randomized clinical trial

Cáncer gástrico; Metastásico; PertuzumabCàncer gàstric; Metastàtic; PertuzumabGastric cancers; Metastatic; PertuzumabBackground Dual-targeted anti-HER2 therapy significantly improves outcomes in HER2-positive breast cancer and could be beneficial in other HER2-positive cancers. JACOB’s end-of study analyses aimed to evaluate the long-term efficacy and safety of pertuzumab plus trastuzumab and chemotherapy for previously untreated HER2-positive metastatic gastric or gastroesophageal junction cancer. Methods Eligible patients were randomized 1:1 to pertuzumab/placebo plus trastuzumab and chemotherapy every 3 weeks. Primary endpoint: overall survival (OS). Secondary endpoints included progression-free survival (PFS), objective response rate (ORR), duration of response (DoR), and safety. Results The intention-to-treat population comprised 388 patients in the pertuzumab arm and 392 in the placebo arm. The safety population comprised 385 and 388 patients, respectively. Median follow-up was ≥ 44.4 months. Median OS was increased by 3.9 months (hazard ratio 0.85 [95% confidence intervals, 0.72–0.99]) and median PFS by 1.3 months (hazard ratio 0.73 [95% confidence intervals, 0.62–0.85]) in the pertuzumab vs. the placebo arm. ORR was numerically higher (57.0% vs. 48.6%) and median DoR 1.8 months longer with pertuzumab treatment. There was a trend for more favorable hazard ratios in certain subgroups related to HER2 amplification/overexpression. Safety was comparable between arms, except for serious and grade 3–5 adverse events, and any-grade diarrhea, which were more frequent with pertuzumab. Conclusions JACOB did not meet its primary endpoint. Nonetheless, the study continues to demonstrate some, albeit limited, evidence of treatment activity and an acceptable safety profile for pertuzumab plus trastuzumab and chemotherapy in previously untreated HER2-positive metastatic gastric or gastroesophageal junction cancer after long-term follow-up.This study was sponsored by F. Hoffmann-La Roche Ltd. The sponsor, F. Hoffmann-La Roche Ltd, contributed to the design of this study. Data collected by the investigators were analyzed by statisticians at F. Hoffmann-La Roche Ltd. Authors employed by the study sponsor contributed to the conduct of the study, collection, management, analysis, and interpretation of the data, and preparation, review, and approval of the manuscript, as well as the decision to submit the manuscript for publication

Health-related quality-of-life analysis from KEYNOTE-590: pembrolizumab plus chemotherapy versus chemotherapy for advanced esophageal cancer

Chemotherapy; Esophageal cancer; Health-related quality of lifeQuimioteràpia; Càncer d'esòfag; Qualitat de vida relacionada amb la salutQuimioterapia; Cáncer de esófago; Calidad de vida relacionada con la saludBackground In the KEYNOTE-590 study, first-line pembrolizumab plus chemotherapy provided statistically significant improvement in overall survival, progression-free survival, and objective response rate compared with chemotherapy, with a manageable safety profile in patients with advanced esophageal cancer. Prespecified health-related quality-of-life (HRQoL) outcomes are reported. Materials and Methods Change from baseline to week 18 in the EORTC Quality of Life Questionnaire Core 30 (QLQ-C30) global health status/QoL (GHS/QoL) and QLQ–Esophageal cancer module (OES18) dysphagia, pain, and reflux scales were evaluated. Results The HRQoL analysis included 730 patients who received treatment and completed ≥1 HRQoL assessment. Least squares mean (LSM) change from baseline to week 18 was similar between treatment groups for QLQ-C30 GHS/QoL and physical functioning and QLQ-OES18 reflux scales. The QLQ-OES18 dysphagia (LSM difference, −5.54; 95% CI, −10.93 to −0.16) and pain (LSM difference, −2.94; 95% CI, −5.86 to −0.02) scales favored pembrolizumab plus chemotherapy over placebo plus chemotherapy. Median time to confirmed deterioration (TTD) was similar between treatment groups for QLQ-C30 GHS/QoL and physical functioning and QLQ-OES18 dysphagia and reflux scales. Compared with chemotherapy, pembrolizumab plus chemotherapy prolonged median TTD, as seen on the QLQ-OES18 pain scale (HR, 0.69; 95% CI, 0.51 to 0.95). Conclusion The use of pembrolizumab plus chemotherapy maintained HRQoL at week 18 relative to baseline and was comparable with placebo plus chemotherapy. These HRQoL results together with published reports of efficacy, support the use of pembrolizumab plus chemotherapy as first-line therapy for advanced/metastatic esophageal cancer. ClinicalTrials.gov ID NCT03189719Funding for this research was provided by Merck Sharp & Dohme LLC, a subsidiary of Merck & Co., Inc., Rahway, NJ, USA

Academic Detailing as a Health Information Technology Implementation Method: Supporting the Design and Implementation of an Emergency Department-Based Clinical Decision Support Tool to Prevent Future Falls

BACKGROUND: Clinical decision support (CDS) tools that incorporate machine learning-derived content have the potential to transform clinical care by augmenting clinicians\u27 expertise. To realize this potential, such tools must be designed to fit the dynamic work systems of the clinicians who use them. We propose the use of academic detailing-personal visits to clinicians by an expert in a specific health IT tool-as a method for both ensuring the correct understanding of that tool and its evidence base and identifying factors influencing the tool\u27s implementation. OBJECTIVE: This study aimed to assess academic detailing as a method for simultaneously ensuring the correct understanding of an emergency department-based CDS tool to prevent future falls and identifying factors impacting clinicians\u27 use of the tool through an analysis of the resultant qualitative data. METHODS: Previously, our team designed a CDS tool to identify patients aged 65 years and older who are at the highest risk of future falls and prompt an interruptive alert to clinicians, suggesting the patient be referred to a mobility and falls clinic for an evidence-based preventative intervention. We conducted 10-minute academic detailing interviews (n=16) with resident emergency medicine physicians and advanced practice providers who had encountered our CDS tool in practice. We conducted an inductive, team-based content analysis to identify factors that influenced clinicians\u27 use of the CDS tool. RESULTS: The following categories of factors that impacted clinicians\u27 use of the CDS were identified: (1) aspects of the CDS tool\u27s design (2) clinicians\u27 understanding (or misunderstanding) of the CDS or referral process, (3) the busy nature of the emergency department environment, (4) clinicians\u27 perceptions of the patient and their associated fall risk, and (5) the opacity of the referral process. Additionally, clinician education was done to address any misconceptions about the CDS tool or referral process, for example, demonstrating how simple it is to place a referral via the CDS and clarifying which clinic the referral goes to. CONCLUSIONS: Our study demonstrates the use of academic detailing for supporting the implementation of health information technologies, allowing us to identify factors that impacted clinicians\u27 use of the CDS while concurrently educating clinicians to ensure the correct understanding of the CDS tool and intervention. Thus, academic detailing can inform both real-time adjustments of a tool\u27s implementation, for example, refinement of the language used to introduce the tool, and larger scale redesign of the CDS tool to better fit the dynamic work environment of clinicians

Effectiveness of an Emergency Department-Based Machine Learning Clinical Decision Support Tool to Prevent Outpatient Falls Among Older Adults: Protocol for a Quasi-Experimental Study

Background Emergency department (ED) providers are important collaborators in preventing falls for older adults because they are often the first health care providers to see a patient after a fall and because at-home falls are often preceded by previous ED visits. Previous work has shown that ED referrals to falls interventions can reduce the risk of an at-home fall by 38%. Screening patients at risk for a fall can be time-consuming and difficult to implement in the ED setting. Machine learning (ML) and clinical decision support (CDS) offer the potential of automating the screening process. However, it remains unclear whether automation of screening and referrals can reduce the risk of future falls among older patients. Objective The goal of this paper is to describe a research protocol for evaluating the effectiveness of an automated screening and referral intervention. These findings will inform ongoing discussions about the use of ML and artificial intelligence to augment medical decision-making. Methods To assess the effectiveness of our program for patients receiving the falls risk intervention, our primary analysis will be to obtain referral completion rates at 3 different EDs. We will use a quasi-experimental design known as a sharp regression discontinuity with regard to intent-to-treat, since the intervention is administered to patients whose risk score falls above a threshold. A conditional logistic regression model will be built to describe 6-month fall risk at each site as a function of the intervention, patient demographics, and risk score. The odds ratio of a return visit for a fall and the 95% CI will be estimated by comparing those identified as high risk by the ML-based CDS (ML-CDS) and those who were not but had a similar risk profile. Results The ML-CDS tool under study has been implemented at 2 of the 3 EDs in our study. As of April 2023, a total of 1326 patient encounters have been flagged for providers, and 339 unique patients have been referred to the mobility and falls clinic. To date, 15% (45/339) of patients have scheduled an appointment with the clinic. Conclusions This study seeks to quantify the impact of an ML-CDS intervention on patient behavior and outcomes. Our end-to-end data set allows for a more meaningful analysis of patient outcomes than other studies focused on interim outcomes, and our multisite implementation plan will demonstrate applicability to a broad population and the possibility to adapt the intervention to other EDs and achieve similar results. Our statistical methodology, regression discontinuity design, allows for causal inference from observational data and a staggered implementation strategy allows for the identification of secular trends that could affect causal associations and allow mitigation as necessary. Trial Registration ClinicalTrials.gov NCT05810064; https://www.clinicaltrials.gov/study/NCT05810064 International Registered Report Identifier (IRRID) DERR1-10.2196/4812

A Comparison of Homogenization vs. Enzymatic Lysis for Microbiome Profiling in Clinical Endoscopic Biopsy Tissue Samples

Identification of the human microbiome has proven to be of utmost importance with the emerging role of bacteria in various physiological and pathological processes. High throughput sequencing strategies have evolved to assess the composition of the microbiome. To identify possible bias that may exist in the processing of tissue for whole genome sequencing (WGS), it is important to evaluate the extraction method on the overall microbial content and composition. Here we compare two different methods of extraction, homogenization vs. enzymatic lysis, on gastric, esophageal and colorectal biopsies and survey the microbial content and composition using WGS and quantitative PCR (qPCR). We examined total bacterial content using universal 16S rDNA qPCR as well as the abundance of three phyla (Actinobacter, Firmicutes, Bacteroidetes) and one genus (Fusobacterium). We found minimal differences between the two extraction methods in the overall community structure. Furthermore, based on our qPCR analysis, neither method demonstrated preferential extraction of any particular clade of bacteria, nor significantly altered the detection of Gram-positive or Gram-negative organisms. However, although the overall microbial composition remained very similar and the most prevalent bacteria could be detected effectively using either method, the precise community structure and microbial abundances between the two methods were different, primarily due to variations in detection of low abundance genus. We also demonstrate that the homogenization extraction method provides higher microbial DNA content and higher read counts from human tissue biopsy samples of the gastrointestinal tract

Evaluating the Usability of an Emergency Department After Visit Summary: Staged Heuristic Evaluation

BACKGROUND: Heuristic evaluations, while commonly used, may inadequately capture the severity of identified usability issues. In the domain of health care, usability issues can pose different levels of risk to patients. Incorporating diverse expertise (eg, clinical and patient) in the heuristic evaluation process can help assess and address potential negative impacts on patient safety that may otherwise go unnoticed. One document that should be highly usable for patients-with the potential to prevent adverse outcomes-is the after visit summary (AVS). The AVS is the document given to a patient upon discharge from the emergency department (ED), which contains instructions on how to manage symptoms, medications, and follow-up care. OBJECTIVE: This study aims to assess a multistage method for integrating diverse expertise (ie, clinical, an older adult care partner, and health IT) with human factors engineering (HFE) expertise in the usability evaluation of the patient-facing ED AVS. METHODS: We conducted a three-staged heuristic evaluation of an ED AVS using heuristics developed for use in evaluating patient-facing documentation. In stage 1, HFE experts reviewed the AVS to identify usability issues. In stage 2, 6 experts of varying expertise (ie, emergency medicine physicians, ED nurses, geriatricians, transitional care nurses, and an older adult care partner) rated each previously identified usability issue on its potential impact on patient comprehension and patient safety. Finally, in stage 3, an IT expert reviewed each usability issue to identify the likelihood of successfully addressing the issue. RESULTS: In stage 1, we identified 60 usability issues that violated a total of 108 heuristics. In stage 2, 18 additional usability issues that violated 27 heuristics were identified by the study experts. Impact ratings ranged from all experts rating the issue as no impact to 5 out of 6 experts rating the issue as having a large negative impact. On average, the older adult care partner representative rated usability issues as being more significant more of the time. In stage 3, 31 usability issues were rated by an IT professional as impossible to address, 21 as maybe, and 24 as can be addressed. CONCLUSIONS: Integrating diverse expertise when evaluating usability is important when patient safety is at stake. The non-HFE experts, included in stage 2 of our evaluation, identified 23% (18/78) of all the usability issues and, depending on their expertise, rated those issues as having differing impacts on patient comprehension and safety. Our findings suggest that, to conduct a comprehensive heuristic evaluation, expertise from all the contexts in which the AVS is used must be considered. Combining those findings with ratings from an IT expert, usability issues can be strategically addressed through redesign. Thus, a 3-staged heuristic evaluation method offers a framework for integrating context-specific expertise efficiently, while providing practical insights to guide human-centered design

Development and Preliminary Clinical Activity of PD-1-Guided CTLA-4 Blocking Bispecific DART Molecule.

Combination immunotherapy with antibodies directed against PD-1 and CTLA-4 shows improved clinical benefit across cancer indications compared to single agents, albeit with increased toxicity. Leveraging the observation that PD-1 and CTLA-4 are co-expressed by tumor-infiltrating lymphocytes, an investigational PD-1 x CTLA-4 bispecific DART molecule, MGD019, is engineered to maximize checkpoint blockade in the tumor microenvironment via enhanced CTLA-4 blockade in a PD-1-binding-dependent manner

T cell-inflamed gene expression profile and PD-L1 expression and pembrolizumab efficacy in advanced esophageal cancer

Aim: Investigate the relationship between response to pembrolizumab and expression of the 18-gene T cell-inflamed gene expression profile (TcellinfGEP) or PD-L1 combined positive score (CPS) in esophageal cancer. Materials & methods: This analysis included heavily pretreated patients with advanced/metastatic esophageal/gastroesophageal junction adenocarcinoma or squamous cell carcinoma who received pembrolizumab in the single-arm, phase II study KEYNOTE-180. PD-L1 CPS was evaluated with PD-L1 IHC 22C3 pharmDx. Results: In patients with squamous cell carcinoma, trends toward enrichment for responders were observed for patients with PD-L1 CPS ≥10 tumors. In patients with adenocarcinoma, a trend was observed for TcellinfGEP but not for PD-L1. Conclusion: TcellinfGEP and PD-L1 CPS may enrich for responders to pembrolizumab in patients with esophageal cancer. Clinical Trial Registration: NCT02559687 (ClinicalTrials.gov