Ula Hwang, Natalia Sifnugel, Inessa Cohen, Ling Han, Katy Araujo, Luann M Bianco, Cynthia A Brandt, Sandra Capelli, Christopher R Carpenter, Daniel S Cruz, Scott M Dresden, Ivy L Fishman, Katrina Gipson, S Nicole Hastings, William W Hung, Raymond Kang, Mechelle Lockhart, Daniella Meeker, Ugochi Ohuabunwa, Sierra Ottilie-Kovelman, Caitlin Partridge, Timothy F Platts-Mills, Jacqueline Sandoval, Zachary Taylor, Debra F Tomasino, Camille P Vaughan
{"title":"老年急诊应用研究标准化研究（GEARSS）：一项老年急诊科患者的观察性研究。","authors":"Ula Hwang, Natalia Sifnugel, Inessa Cohen, Ling Han, Katy Araujo, Luann M Bianco, Cynthia A Brandt, Sandra Capelli, Christopher R Carpenter, Daniel S Cruz, Scott M Dresden, Ivy L Fishman, Katrina Gipson, S Nicole Hastings, William W Hung, Raymond Kang, Mechelle Lockhart, Daniella Meeker, Ugochi Ohuabunwa, Sierra Ottilie-Kovelman, Caitlin Partridge, Timothy F Platts-Mills, Jacqueline Sandoval, Zachary Taylor, Debra F Tomasino, Camille P Vaughan","doi":"10.1111/acem.70101","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>Multicenter research of geriatric emergency department (GED) care remains limited. Our objectives were to: 1. Prospectively collect data prioritized by the Geriatric Emergency care Applied Research (GEAR) network, a transdisciplinary taskforce for GED care, and create a multicenter GED research repository of prospective and electronic health record (EHR) data, 2. Assess concordance between prospective and EHR data.</p><p><strong>Methods: </strong>The GEAR Standardization Study (GEARSS) is a multicenter, prospective study of older emergency department (ED) patients (65+) focusing on the 4Ms of age-friendly care (mobility, medication safety, mentation, what matters) and elder mistreatment. Demographic and clinical data were collected via interviews by trained research assistants (RA) on Days 0, 4, 30, and 90 and linked to EHR. Prevalence of chronic comorbidities and incident delirium were measured and reported using descriptive statistics. Prospective and EHR data concordance was assessed with Cohen's Kappa.</p><p><strong>Results: </strong>999 participants were recruited from 5 EDs (3/25/2021-6/30/2022) across 3 institutions: Grady Health System, Northwestern Memorial Hospital, and Yale New Haven Health. The cohort was 57.0% female, 55.2% White, 39.1% Black, and 3.4% Hispanic, and the mean age was 75.1 years. For rheumatologic disease, peptic ulcer disease, diabetes, renal disease, and cancer, prevalence differed between prospective and EHR data by > 10%. About two-thirds of participants were at risk for falls. Concordance between prospective and EHR data was good for ethnicity (K = 0.73); excellent for sex (K = 1.00), age (K = 1.00), and race (K = 0.98); fair for disposition (K = 0.53); slight for ED observation status (K = 0.33) and dementia diagnosis (K = 0.24); poor for delirium presence (K = 0.07).</p><p><strong>Conclusion: </strong>In GEARSS, demographic variables aligned strongly between prospective and EHR data, while diagnosis, disposition, and mentation factors did not. This multicenter data source provides preliminary findings for common geriatric syndromes and conditions. Choice of measures using these data should be driven by GED research questions.</p>","PeriodicalId":7105,"journal":{"name":"Academic Emergency Medicine","volume":" ","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12266642/pdf/","citationCount":"0","resultStr":"{\"title\":\"The Geriatric Emergency Care Applied Research Standardization Study (GEARSS): An Observational Study of Older Emergency Department Patients.\",\"authors\":\"Ula Hwang, Natalia Sifnugel, Inessa Cohen, Ling Han, Katy Araujo, Luann M Bianco, Cynthia A Brandt, Sandra Capelli, Christopher R Carpenter, Daniel S Cruz, Scott M Dresden, Ivy L Fishman, Katrina Gipson, S Nicole Hastings, William W Hung, Raymond Kang, Mechelle Lockhart, Daniella Meeker, Ugochi Ohuabunwa, Sierra Ottilie-Kovelman, Caitlin Partridge, Timothy F Platts-Mills, Jacqueline Sandoval, Zachary Taylor, Debra F Tomasino, Camille P Vaughan\",\"doi\":\"10.1111/acem.70101\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objectives: </strong>Multicenter research of geriatric emergency department (GED) care remains limited. Our objectives were to: 1. Prospectively collect data prioritized by the Geriatric Emergency care Applied Research (GEAR) network, a transdisciplinary taskforce for GED care, and create a multicenter GED research repository of prospective and electronic health record (EHR) data, 2. Assess concordance between prospective and EHR data.</p><p><strong>Methods: </strong>The GEAR Standardization Study (GEARSS) is a multicenter, prospective study of older emergency department (ED) patients (65+) focusing on the 4Ms of age-friendly care (mobility, medication safety, mentation, what matters) and elder mistreatment. Demographic and clinical data were collected via interviews by trained research assistants (RA) on Days 0, 4, 30, and 90 and linked to EHR. Prevalence of chronic comorbidities and incident delirium were measured and reported using descriptive statistics. Prospective and EHR data concordance was assessed with Cohen's Kappa.</p><p><strong>Results: </strong>999 participants were recruited from 5 EDs (3/25/2021-6/30/2022) across 3 institutions: Grady Health System, Northwestern Memorial Hospital, and Yale New Haven Health. The cohort was 57.0% female, 55.2% White, 39.1% Black, and 3.4% Hispanic, and the mean age was 75.1 years. For rheumatologic disease, peptic ulcer disease, diabetes, renal disease, and cancer, prevalence differed between prospective and EHR data by > 10%. About two-thirds of participants were at risk for falls. Concordance between prospective and EHR data was good for ethnicity (K = 0.73); excellent for sex (K = 1.00), age (K = 1.00), and race (K = 0.98); fair for disposition (K = 0.53); slight for ED observation status (K = 0.33) and dementia diagnosis (K = 0.24); poor for delirium presence (K = 0.07).</p><p><strong>Conclusion: </strong>In GEARSS, demographic variables aligned strongly between prospective and EHR data, while diagnosis, disposition, and mentation factors did not. This multicenter data source provides preliminary findings for common geriatric syndromes and conditions. 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The Geriatric Emergency Care Applied Research Standardization Study (GEARSS): An Observational Study of Older Emergency Department Patients.
Objectives: Multicenter research of geriatric emergency department (GED) care remains limited. Our objectives were to: 1. Prospectively collect data prioritized by the Geriatric Emergency care Applied Research (GEAR) network, a transdisciplinary taskforce for GED care, and create a multicenter GED research repository of prospective and electronic health record (EHR) data, 2. Assess concordance between prospective and EHR data.
Methods: The GEAR Standardization Study (GEARSS) is a multicenter, prospective study of older emergency department (ED) patients (65+) focusing on the 4Ms of age-friendly care (mobility, medication safety, mentation, what matters) and elder mistreatment. Demographic and clinical data were collected via interviews by trained research assistants (RA) on Days 0, 4, 30, and 90 and linked to EHR. Prevalence of chronic comorbidities and incident delirium were measured and reported using descriptive statistics. Prospective and EHR data concordance was assessed with Cohen's Kappa.
Results: 999 participants were recruited from 5 EDs (3/25/2021-6/30/2022) across 3 institutions: Grady Health System, Northwestern Memorial Hospital, and Yale New Haven Health. The cohort was 57.0% female, 55.2% White, 39.1% Black, and 3.4% Hispanic, and the mean age was 75.1 years. For rheumatologic disease, peptic ulcer disease, diabetes, renal disease, and cancer, prevalence differed between prospective and EHR data by > 10%. About two-thirds of participants were at risk for falls. Concordance between prospective and EHR data was good for ethnicity (K = 0.73); excellent for sex (K = 1.00), age (K = 1.00), and race (K = 0.98); fair for disposition (K = 0.53); slight for ED observation status (K = 0.33) and dementia diagnosis (K = 0.24); poor for delirium presence (K = 0.07).
Conclusion: In GEARSS, demographic variables aligned strongly between prospective and EHR data, while diagnosis, disposition, and mentation factors did not. This multicenter data source provides preliminary findings for common geriatric syndromes and conditions. Choice of measures using these data should be driven by GED research questions.
期刊介绍：
Academic Emergency Medicine (AEM) is the official monthly publication of the Society for Academic Emergency Medicine (SAEM) and publishes information relevant to the practice, educational advancements, and investigation of emergency medicine. It is the second-largest peer-reviewed scientific journal in the specialty of emergency medicine.
The goal of AEM is to advance the science, education, and clinical practice of emergency medicine, to serve as a voice for the academic emergency medicine community, and to promote SAEM''s goals and objectives. Members and non-members worldwide depend on this journal for translational medicine relevant to emergency medicine, as well as for clinical news, case studies and more.
Each issue contains information relevant to the research, educational advancements, and practice in emergency medicine. Subject matter is diverse, including preclinical studies, clinical topics, health policy, and educational methods. The research of SAEM members contributes significantly to the scientific content and development of the journal.
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