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Tejani AS, Bialecki B, O’Donnell K, Sippel Schmidt T, Kohli MD, Alkasab T. Standardizing imaging findings representation: harnessing Common Data Elements semantics and Fast Healthcare Interoperability Resources structures. J Am Med Inform Assoc 2024; 31:1735-1742. [PMID: 38900188 PMCID: PMC11258419 DOI: 10.1093/jamia/ocae134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Revised: 05/22/2024] [Accepted: 05/24/2024] [Indexed: 06/21/2024] Open
Abstract
OBJECTIVES Designing a framework representing radiology results in a standards-based data structure using joint Radiological Society of North America/American College of Radiology Common Data Elements (CDEs) as the semantic labels on standard structures. This allows radiologist-created report data to integrate with artificial intelligence-generated results for use throughout downstream systems. MATERIALS AND METHODS We developed a framework modeling radiology findings as Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) observations using CDE set/element identifiers as standardized semantic labels. This framework deploys CDE identifiers to specify radiology findings and attributes, providing consistent labels for radiology report concepts-diagnoses, recommendations, tabular/quantitative data-with built-in integration with RadLex, SNOMED CT, LOINC, and other ontologies. Observation structures fit within larger HL7 FHIR DiagnosticReport resources, providing output including both nuanced text and structured data. RESULTS Labeling radiology findings as discrete data for interchange between systems requires two components: structure and semantics. CDE definitions provide semantic identifiers for findings and their component values. The FHIR observation resource specifies a structure for associating identifiers with radiology findings in the context of reports, with CDE-encoded observations referring to definitions for CDE identifiers in a central repository. The discussion includes an example of encoding pulmonary nodules on a chest CT as CDE-labeled observations, demonstrating the application of this framework to exchange findings throughout the imaging workflow, making imaging data available to downstream clinical systems. DISCUSSION CDE-labeled observations establish a lingua franca for encoding, exchanging, and consuming radiology data at the level of individual findings, facilitating use throughout healthcare systems. IMPORTANCE CDE-labeled FHIR observation objects can increase the value of radiology results by facilitating their use throughout patient care.
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Affiliation(s)
- Ali S Tejani
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX 75390, United States
| | - Brian Bialecki
- Informatics, American College of Radiology, Reston, VA 20191, United States
| | - Kevin O’Donnell
- Connectivity, Standards, & Interoperability, Canon Medical Research United States Inc, Vernon Hills, IL 60061, United States
| | - Teri Sippel Schmidt
- Biomedical Informatics and Data Sciences Department, Johns Hopkins School of Medicine, Baltimore, MD 21205, United States
| | - Marc D Kohli
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143, United States
| | - Tarik Alkasab
- Department of Radiology, Massachusetts General Hospital, Boston, MA 02114, United States
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Sikora A, Keats K, Murphy DJ, Devlin JW, Smith SE, Murray B, Buckley MS, Rowe S, Coppiano L, Kamaleswaran R. A common data model for the standardization of intensive care unit medication features. JAMIA Open 2024; 7:ooae033. [PMID: 38699649 PMCID: PMC11064096 DOI: 10.1093/jamiaopen/ooae033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 02/12/2024] [Accepted: 04/09/2024] [Indexed: 05/05/2024] Open
Abstract
Objective Common data models provide a standard means of describing data for artificial intelligence (AI) applications, but this process has never been undertaken for medications used in the intensive care unit (ICU). We sought to develop a common data model (CDM) for ICU medications to standardize the medication features needed to support future ICU AI efforts. Materials and Methods A 9-member, multi-professional team of ICU clinicians and AI experts conducted a 5-round modified Delphi process employing conference calls, web-based communication, and electronic surveys to define the most important medication features for AI efforts. Candidate ICU medication features were generated through group discussion and then independently scored by each team member based on relevance to ICU clinical decision-making and feasibility for collection and coding. A key consideration was to ensure the final ontology both distinguished unique medications and met Findable, Accessible, Interoperable, and Reusable (FAIR) guiding principles. Results Using a list of 889 ICU medications, the team initially generated 106 different medication features, and 71 were ranked as being core features for the CDM. Through this process, 106 medication features were assigned to 2 key feature domains: drug product-related (n = 43) and clinical practice-related (n = 63). Each feature included a standardized definition and suggested response values housed in the electronic data library. This CDM for ICU medications is available online. Conclusion The CDM for ICU medications represents an important first step for the research community focused on exploring how AI can improve patient outcomes and will require ongoing engagement and refinement.
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Affiliation(s)
- Andrea Sikora
- Department of Clinical and Administrative Pharmacy, University of Georgia College of Pharmacy, Augusta, GA 30912, United States
| | - Kelli Keats
- Department of Pharmacy, Augusta University Medical Center, Augusta, GA 30912, United States
| | - David J Murphy
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Emory University, Atlanta, GA 30322, United States
| | - John W Devlin
- Northeastern University School of Pharmacy, Boston, MA 02115, United States
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, MA 02115, United States
| | - Susan E Smith
- Department of Clinical and Administrative Pharmacy, University of Georgia College of Pharmacy, Athens, GA 30601, United States
| | - Brian Murray
- Department of Pharmacy, University of North Carolina Medical Center, Chapel Hill, NC 27514, United States
| | - Mitchell S Buckley
- Department of Pharmacy, Banner University Medical Center Phoenix, Phoenix, AZ 85032, United States
| | - Sandra Rowe
- Department of Pharmacy, Oregon Health and Science University, Portland, OR 97239, United States
| | - Lindsey Coppiano
- Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA 30322, United States
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30322, United States
| | - Rishikesan Kamaleswaran
- Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA 30322, United States
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30322, United States
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Levites Strekalova YA, Nelson JD, Weber HM, Wang X, Midence SM. Application of the Delphi method to the development of common data elements for social drivers of health: A systematic scoping review. Transl Behav Med 2024; 14:426-433. [PMID: 38718172 PMCID: PMC11208287 DOI: 10.1093/tbm/ibae020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/28/2024] Open
Abstract
Collaborative data science requires standardized, harmonized, interoperable, and ethically sourced data. Developing an agreed-upon set of elements requires capturing different perspectives on the importance and feasibility of the data elements through a consensus development approach. This study reports on the systematic scoping review of literature that examined the inclusion of diverse stakeholder groups and sources of social drivers of health variables in consensus-based common data element (CDE) sets. This systematic scoping review included sources from PubMed, Embase, CINAHL, WoS MEDLINE, and PsycINFO databases. Extracted data included the stakeholder groups engaged in the Delphi process, sources of CDE sets, and inclusion of social drivers data across 11 individual and 6 social domains. Of the 384 studies matching the search string, 22 were included in the final review. All studies involved experts with healthcare expertise directly relevant to the developed CDE set, and only six (27%) studies engaged health consumers. Literature reviews and expert input were the most frequent sources of CDE sets. Seven studies (32%) did not report the inclusion of any demographic variables in the CDE sets, and each demographic SDoH domain was included in at least one study with age and sex assigned at birth included in all studies, and social driver domains included only in four studies (18%). The Delphi technique engages diverse expert groups around the development of SDoH data elements. Future studies can benefit by involving health consumers as experts.
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Affiliation(s)
- Yulia A Levites Strekalova
- Department of Health Services Research, Management, and Policy, College of Public Health and Health Professions, University of Florida, 1225 Center Drive, Gainesville, FL 32610, USA
- Clinical and Translational Science Institute, University of Florida, 2004 Mowry Road, Gainesville, FL 32610, USA
| | - July D Nelson
- Department of Health Services Research, Management, and Policy, College of Public Health and Health Professions, University of Florida, 1225 Center Drive, Gainesville, FL 32610, USA
| | - Haley M Weber
- Department of Health Services Research, Management, and Policy, College of Public Health and Health Professions, University of Florida, 1225 Center Drive, Gainesville, FL 32610, USA
| | - Xiangren Wang
- Department of Health Services Research, Management, and Policy, College of Public Health and Health Professions, University of Florida, 1225 Center Drive, Gainesville, FL 32610, USA
| | - Sara M Midence
- Department of Health Services Research, Management, and Policy, College of Public Health and Health Professions, University of Florida, 1225 Center Drive, Gainesville, FL 32610, USA
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Kortz TB, Mediratta RP, Smith AM, Nielsen KR, Agulnik A, Gordon Rivera S, Reeves H, O’Brien NF, Lee JH, Abbas Q, Attebery JE, Bacha T, Bhutta EG, Biewen CJ, Camacho-Cruz J, Coronado Muñoz A, deAlmeida ML, Domeryo Owusu L, Fonseca Y, Hooli S, Wynkoop H, Leimanis-Laurens M, Nicholaus Mally D, McCarthy AM, Mutekanga A, Pineda C, Remy KE, Sanders SC, Tabor E, Teixeira Rodrigues A, Yuee Wang JQ, Kissoon N, Takwoingi Y, Wiens MO, Bhutta A. Etiology of hospital mortality in children living in low- and middle-income countries: a systematic review and meta-analysis. Front Pediatr 2024; 12:1397232. [PMID: 38910960 PMCID: PMC11190367 DOI: 10.3389/fped.2024.1397232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Accepted: 05/20/2024] [Indexed: 06/25/2024] Open
Abstract
In 2019, 80% of the 7.4 million global child deaths occurred in low- and middle-income countries (LMICs). Global and regional estimates of cause of hospital death and admission in LMIC children are needed to guide global and local priority setting and resource allocation but are currently lacking. The study objective was to estimate global and regional prevalence for common causes of pediatric hospital mortality and admission in LMICs. We performed a systematic review and meta-analysis to identify LMIC observational studies published January 1, 2005-February 26, 2021. Eligible studies included: a general pediatric admission population, a cause of admission or death, and total admissions. We excluded studies with data before 2,000 or without a full text. Two authors independently screened and extracted data. We performed methodological assessment using domains adapted from the Quality in Prognosis Studies tool. Data were pooled using random-effects models where possible. We reported prevalence as a proportion of cause of death or admission per 1,000 admissions with 95% confidence intervals (95% CI). Our search identified 29,637 texts. After duplicate removal and screening, we analyzed 253 studies representing 21.8 million pediatric hospitalizations in 59 LMICs. All-cause pediatric hospital mortality was 4.1% [95% CI 3.4%-4.7%]. The most common causes of mortality (deaths/1,000 admissions) were infectious [12 (95% CI 9-14)]; respiratory [9 (95% CI 5-13)]; and gastrointestinal [9 (95% CI 6-11)]. Common causes of admission (cases/1,000 admissions) were respiratory [255 (95% CI 231-280)]; infectious [214 (95% CI 193-234)]; and gastrointestinal [166 (95% CI 143-190)]. We observed regional variation in estimates. Pediatric hospital mortality remains high in LMICs. Global child health efforts must include measures to reduce hospital mortality including basic emergency and critical care services tailored to the local disease burden. Resources are urgently needed to promote equity in child health research, support researchers, and collect high-quality data in LMICs to further guide priority setting and resource allocation.
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Affiliation(s)
- Teresa B. Kortz
- Department of Pediatrics, University of California, San Francisco, San Francisco, CA, United States
- Institute for Global Health Sciences, University of California, San Francisco, San Francisco, CA, United States
| | - Rishi P. Mediratta
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, United States
| | - Audrey M. Smith
- Department of Medicine, Miller School of Medicine, Miami, FL, United States
| | - Katie R. Nielsen
- Department of Pediatrics and Department of Global Health, University of Washington, Seattle, WA, United States
| | - Asya Agulnik
- Department of Global Pediatric Medicine, St. Jude Children’s Research Hospital, Memphis, TN, United States
| | - Stephanie Gordon Rivera
- Institute for Global Health Sciences, University of California, San Francisco, San Francisco, CA, United States
| | - Hailey Reeves
- Faculty of Medicine & Dentistry, University of Alberta, Edmonton, AB, Canada
| | - Nicole F. O’Brien
- Department of Pediatrics, Ohio State University/Nationwide Children’s Hospital, Columbus, OH, United States
| | - Jan Hau Lee
- Children's Intensive Care Unit, Department of Paediatric Subspecialties, KK Women's and Children's Hospital, Singapore, Singapore
- Paediatrics Academic Clinical Programme, Duke-NUS Medical School, Singapore, Singapore
| | - Qalab Abbas
- Department of Pediatrics and Child Health, Section of Pediatric Critical Care Medicine, Aga Khan University, Karachi, Pakistan
| | - Jonah E. Attebery
- Department of Pediatrics, University of Colorado, Aurora, CO, United States
- Barrow Global Health, Barrow Neurological Institute, Phoenix, AZ, United States
| | - Tigist Bacha
- Department of Pediatric and Child Health, Saint Paul Hospital Medical College, Addis Ababa, Ethiopia
| | - Emaan G. Bhutta
- Mailman School of Public Health, Columbia University, New York, NY, United States
| | - Carter J. Biewen
- Department of Pediatrics, University of California, San Francisco, San Francisco, CA, United States
| | - Jhon Camacho-Cruz
- Department of Pediatrics, Universidad Nacional de Colombia, Fundación Universitaria de Ciencias de la Salud (FUCS), Sociedad de Cirugía de Bogota-Hospital San José, Fundación Universitaria Sanitas, Clínica Reina Sofia Pediátrica y Mujer Colsanitas, Red Colaborativa Pediátrica de Latinoamérica (LARed Network), Bogotá D.C.,Colombia
| | - Alvaro Coronado Muñoz
- Pediatric Critical Care Division, Department of Pediatrics, Children’s Hospital at Montefiore, New York, NY, United States
| | - Mary L. deAlmeida
- Department of Pediatrics, Emory University, Atlanta, GA, United States
| | - Larko Domeryo Owusu
- Pediatric Emergency Unit, Child Health Directorate, Komfo Anokye Teaching Hospital, Kumasi, Ghana
| | - Yudy Fonseca
- Department of Pediatrics, University of Maryland Medical Center, Baltimore, MD, United States
| | - Shubhada Hooli
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, United States
| | - Hunter Wynkoop
- Department of Pediatrics, Ohio State University/Nationwide Children’s Hospital, Columbus, OH, United States
| | - Mara Leimanis-Laurens
- Department of Pediatrics and Human Development, Michigan State University, East Lansing and Helen DeVos Children’s Hospital, Grand Rapids, MI, United States
| | - Deogratius Nicholaus Mally
- Pediatric Intensive Care Unit, Pediatrics and Child Health, Muhimbili University of Health and Allied Sciences (MUHAS), Dar es Salaam, Tanzania
| | - Amanda M. McCarthy
- Department of Pediatrics, University of Texas M.D. Anderson Cancer Center, Houston, TX, United States
| | - Andrew Mutekanga
- Department of Medicine, Mbarara University of Science and Technology, Mbarara, Uganda
| | - Carol Pineda
- Department of Pediatrics, Baystate Medical Center, University of Massachusetts Chan Medical School, Springfield, MA, United States
| | - Kenneth E. Remy
- Department of Pediatrics, Rainbow Babies and Children’s Hospital, and Department of Internal Medicine, University Hospitals of Cleveland, Cleveland, OH, United States
| | - Sara C. Sanders
- Department of Pediatrics, Connecticut Children’s and University of Connecticut, Hartford, CT, United States
| | - Erica Tabor
- Department of Biology, Pennsylvania State University, University Park, PA, United States
| | | | - Justin Qi Yuee Wang
- Paediatric Intensive Care Unit, Royal Brompton Hospital, London, United Kingdom
| | - Niranjan Kissoon
- Department of Pediatrics and Emergency Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Yemisi Takwoingi
- Institute of Applied Health Research, University of Birmingham, Edgbaston and NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, United Kingdom
| | - Matthew O. Wiens
- Department of Anesthesiology, Pharmacology and Therapeutics, University of British Columbia, Vancouver, BC, Canada
- Walimu, Kampala, Uganda
| | - Adnan Bhutta
- Department of Pediatrics, Indiana University School of Medicine and Riley Children’s Health, Indianapolis, IN, United States
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Nematollahi S, Dieterich K, Filges I, De Vries JIP, Van Bosse H, Natera de Benito D, Hall JG, Sawatzky B, Bedard T, Sanchez VC, Navalon-Martinez C, Pan T, Hilton C, Dahan-Oliel N. Éléments de données communs pour l'arthrogrypose multiple congénitale: Un cadre international. Dev Med Child Neurol 2024. [PMID: 38590274 DOI: 10.1111/dmcn.15915] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/10/2024]
Abstract
RésuméObjectifAfin de faciliter les études multisites et la recherche clinique d'envergure internationale, cette étude a pour but d'identifier des éléments de données communs (EDCs) normalisés et fondés sur un consensus pour l'arthrogrypose multiple congénitale (AMC).MéthodeUne étude à méthodes mixtes comprenant plusieurs groupes de discussion et trois séries d'enquêtes Delphi modifiées pour parvenir à un consensus ont été menées.RésultatsDans l'ensemble, 45 experts cliniques ainsi qu'adultes ayant une expérience vécue (dont 12 membres d'un consortium d'AMC) ont participé à cette étude à travers 11 pays en Amérique du Nord, Europe et Australie. Les EDCs comprennent 321 éléments de données et 19 mesures standardisées dans divers domaines, du développement du fœtus à l'âge adulte. Les éléments de données relatifs aux traits phénotypiques de l'AMC ont été cartographiés conformément à l'ontologie du phénotype humain (HPO). Une structure de gouvernance universelle, des protocoles de fonctionnement et des plans de développement durable ont été identifiés comme les principaux facilitateurs considérant que la capacité limitée de partage des données et la nécessité d'une infrastructure informatique fédérée étaient les principaux obstacles.InterprétationUne collecte de données systématiques sur l'AMC à l'aide d'EDCs permettra d'étudier sur les voies étiologiques, décrire le profil épidémiologique, et établir des corrélations génotype‐phénotype de manière standardisée. Les EDCs proposés faciliteront les collaborations internationales multidisciplinaires en améliorant à grande échelle les études multicentriques, les possibilités de partage des données, ainsi que le transfert et la diffusion des connaissances.
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Affiliation(s)
- Shahrzad Nematollahi
- École de physiothérapie et d'ergothérapie, Université de McGill, Montréal, QC, Canada
- Département de recherche clinique, Hôpitaux Shriners pour enfants du Canada, Montréal, Canada
| | - Klaus Dieterich
- Inserm U1209, Institut des Biosciences Avancées, CHU Grenoble Alpes, Centre de référence de l'arthrogrypose et des maladies neuromusculaires, Université Grenoble Alpes, Grenoble, France
| | - Isabel Filges
- Génétique médicale, Institut de génétique médicale et de pathologie et Département de recherche clinique, Hôpital universitaire de Bâle et Université de Bâle, Bâle, Suisse
| | - Johanna I P De Vries
- Obstétrique et gynécologie, Amsterdam Movement Sciences, Amsterdam Centre médical universitaire, Centre médical de la Vrije Universiteit, Amsterdam, Pays-Bas
| | - Harold Van Bosse
- Département de chirurgie orthopédique, Hôpital pour enfants Cardinal Glennon/SSM Santé, Université de St. Louis University, St. Louis, MO, États-Unis
| | - Daniel Natera de Benito
- Unité neuromusculaire, Hôpital Sant Joan de Déu, Barcelone, Espagne
- Recherche appliquée en maladies neuromusculaires, Institut de Recerca Sant Joan de Déu, Barcelone, Espagne
| | - Judith G Hall
- Département de génétique médicale et de pédiatrie, Université de la Colombie-Britannique et BC hôpital pour enfants, Vancouver, Canada
| | - Bonita Sawatzky
- Département d'orthopédie, Université de la Colombie-Britannique, Vancouver, Canada
| | - Tanya Bedard
- Génétique clinique, Système de surveillance des anomalies congénitales de l'Alberta, Calgary, Alberta, Canada
| | | | | | - Tony Pan
- Département d'informatique biomédicale, Université Emory, Atlanta, GA, États-Unis
- Département d'ingénierie et de la science des données, Institut de technologie de Géorgie, Atlanta, GA, États-Unis
| | - Coleman Hilton
- Département d'Ingénierie et d'analyse des données, Shriners Children's, Siège social, Tampa, FL, États-Unis
| | - Noémi Dahan-Oliel
- École de physiothérapie et d'ergothérapie, Université de McGill, Montréal, QC, Canada
- Département de recherche clinique, Hôpitaux Shriners pour enfants du Canada, Montréal, Canada
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Nematollahi S, Dieterich K, Filges I, De Vries JIP, Van Bosse H, Natera de Benito D, Hall JG, Sawatzky B, Bedard T, Sanchez VC, Navalon-Martinez C, Pan T, Hilton C, Dahan-Oliel N. Elementos de datos comunes para la artrogriposis múltiple congénita: Un marco internacional. Dev Med Child Neurol 2024. [PMID: 38581247 DOI: 10.1111/dmcn.15914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/08/2024]
Abstract
ResumenObjetivoPara facilitar los estudios multicéntricos y la investigación clínica internacional, este estudio pretende identificar de forma consensuada los elementos de datos estandarizados para la artrogriposis múltiple congénita (AMC).MétodoEstudio de métodos mixtos de grupos de discusión y tres rondas de encuestas Delphi modificadas para llegar a un consenso utilizando dos escalas de clasificación por niveles.ResultadosEn total, 45 expertos clínicos y adultos con experiencia vivida (incluidos 12 miembros de un consorcio de AMC) participaron en este estudio procedentes de 11 países: Norteamérica, Europa y Australia. Los CDEs incluyen 321 elementos de datos y 19 medidas estandarizadas en varios dominios desde el desarrollo fetal hasta la edad adulta. Los elementos de datos relativos a los rasgos fenotípicos del CDEs se mapearon de acuerdo con la Ontología de Fenotipos Humanos. Se identificaron como principales facilitadores la estructura de gobernanza universal, protocolos operados de forma local y los planes de sostenibilidad, mientras que los principales obstáculos observados son la capacidad limitada para compartir datos y la necesidad de una infraestructura informática federada.InterpretaciónLa recopilación de datos sistemáticos sobre la AMC mediante CDEs permitirá investigar las vías etiológicas, describir el perfil epidemiológico y establecer correlaciones genotipo‐fenotipo de forma estandarizada. Los CDEs propuestos facilitarán las colaboraciones multidisciplinares internacionales mejorando los estudios a gran escala y las oportunidades para compartir datos, translación de conocimiento y difusión.
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Affiliation(s)
- Shahrzad Nematollahi
- Escuela de Fisioterapia y Terapia Ocupacional, Universidad McGill, Montreal, Canadá
- Departamento de Investigación Clínica, Hospitales Shriners para Niños, Montreal, Canadá
| | - Klaus Dieterich
- Université Grenoble Alpes, Inserm U1209, Instituto de Biociencias Avanzadas, CHU Grenoble Alpes, Centro de Referencia de Artrogriposis y Neuromuscular, Grenoble, Francia
| | - Isabel Filges
- Genética Médica, Instituto de Genética Médica y Patología y Departamento de Investigación Clínica, Hospital Universitario de Basilea y Universidad de Basilea, Basilea, Suiza
| | - Johanna I P De Vries
- Obstetricia y Ginecología, Amsterdam Movement Sciences, Amsterdam, University Medical Center, Vrije Universiteit Medical Center, Amsterdam, the Países Bajos
| | - Harold Van Bosse
- Departamento de Cirugía Ortopédica, Cardinal Glennon Children's Hospital/SSM Health/St. Louis University, St. Louis, MO, EE.UU
| | - Daniel Natera de Benito
- Unidad Neuromuscular, Hospital Sant Joan de Déu, Barcelona, España
- Investigación Aplicada en Enfermedades Neuromusculares, Institut de Recerca Sant Joan de Déu, Barcelona, España
| | - Judith G Hall
- Departamento de Genética Médica y Pediatría, Universidad de Columbia Británica y BC Children's Hospital, Vancouver, Columbia Británica, Canadá
| | - Bonita Sawatzky
- Departamento de Ortopedia, Universidad de British Columbia, Vancouver, British Columbia Columbia, Canadá
| | - Tanya Bedard
- Sistema de Vigilancia de Anomalías Congénitas de Alberta, Genética Clínica, Alberta Children's Hospital, Alberta Health Services, Calgary, Alberta, Canadá
| | | | | | - Tony Pan
- Departamento de Informática Biomédica, Universidad de Emory, Atlanta, GA, EE.UU
- Instituto de Ingeniería y Ciencia de Datos, Instituto de Tecnología de Georgia, Atlanta, GA, EE.UU
| | | | - Noémi Dahan-Oliel
- Escuela de Fisioterapia y Terapia Ocupacional, Universidad McGill, Montreal, Canadá
- Departamento de Investigación Clínica, Hospitales Shriners para Niños, Montreal, Canadá
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7
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Nematollahi S, Dieterich K, Filges I, De Vries JIP, Van Bosse H, Benito DND, Hall JG, Sawatzky B, Bedard T, Sanchez VC, Navalon-Martinez C, Pan T, Hilton C, Dahan-Oliel N. Common data elements for arthrogryposis multiplex congenita: An international framework. Dev Med Child Neurol 2024. [PMID: 38491830 DOI: 10.1111/dmcn.15898] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2023] [Revised: 02/05/2024] [Accepted: 02/09/2024] [Indexed: 03/18/2024]
Abstract
AIM To facilitate multisite studies and international clinical research, this study aimed to identify consensus-based, standardized common data elements (CDEs) for arthrogryposis multiplex congenita (AMC). METHOD A mixed-methods study comprising of several focus group discussions and three rounds of modified Delphi surveys to achieve consensus using two tiered-rating scales were conducted. RESULTS Overall, 45 clinical experts and adults with lived experience (including 12 members of an AMC consortium) participated in this study from 11 countries in North America, Europe, and Australia. The CDEs include 321 data elements and 19 standardized measures across various domains from fetal development to adulthood. Data elements pertaining to AMC phenotypic traits were mapped according to the Human Phenotype Ontology. A universal governance structure, local operating protocols, and sustainability plans were identified as the main facilitators, whereas limited capacity for data sharing and the need for a federated informatics infrastructure were the main barriers. INTERPRETATION Collection of systematic data on AMC using CDEs will allow investigations on etiological pathways, describe epidemiological profile, and establish genotype-phenotype correlations in a standardized manner. The proposed CDEs will facilitate international multidisciplinary collaborations by improving large-scale studies and opportunities for data sharing, knowledge translation, and dissemination.
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Affiliation(s)
- Shahrzad Nematollahi
- School of Physical and Occupational Therapy, McGill University, Montreal, Canada
- Department of Clinical Research, Shriners Hospitals for Children, Montreal, Canada
| | - Klaus Dieterich
- Université Grenoble Alpes, Inserm U1209, Institute of Advanced Biosciences, CHU Grenoble Alpes, Arthrogryposis and Neuromuscular Reference Center, Grenoble, France
| | - Isabel Filges
- Medical Genetics, Institute of Medical Genetics and Pathology and Department of Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Johanna I P De Vries
- Obstetrics and Gynecology, Amsterdam Movement Sciences, Amsterdam University Medical Center, Vrije Universiteit Medical Center, Amsterdam, the Netherlands
| | - Harold Van Bosse
- Department of Orthopaedic Surgery, Cardinal Glennon Children's Hospital/SSM Health/St. Louis University, St. Louis, MO, USA
| | - Daniel Natera-De Benito
- Neuromuscular Unit, Hospital Sant Joan de Déu, Barcelona, Spain
- Applied Research in Neuromuscular Diseases, Institut de Recerca Sant Joan de Déu, Barcelona, Spain
| | - Judith G Hall
- Department of Medical Genetics and Pediatrics, University of British Columbia and BC Children's Hospital, Vancouver, British Columbia, Canada
| | - Bonita Sawatzky
- Department of Orthopaedics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Tanya Bedard
- Alberta Congenital Anomalies Surveillance System, Clinical Genetics, Alberta Children's Hospital, Alberta Health Services, Calgary, Alberta, Canada
| | | | | | - Tony Pan
- Department of Biomedical Informatics, Emory University, Atlanta, GA, USA
- Institute for Data Engineering and Science, Georgia Institute of Technology, Atlanta, GA, USA
| | | | - Noémi Dahan-Oliel
- School of Physical and Occupational Therapy, McGill University, Montreal, Canada
- Department of Clinical Research, Shriners Hospitals for Children, Montreal, Canada
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8
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Radack T, Meade M, Woods B. Techniques for Improving Electronic Survey Response Rate. Clin Spine Surg 2023; 36:476-477. [PMID: 37941116 DOI: 10.1097/bsd.0000000000001548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 10/03/2023] [Indexed: 11/10/2023]
Abstract
Electronic surveys are readily utilized for the conduction of orthopedic research and are commonly plagued by decreased response rates as compared with more conventional telephone and paper surveys. Given the rise of electronic survey usage and technological implementation into medical research, this paper aims to summarize factors both intrinsic and extrinsic which can increase survey completion in the clinical setting.
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Affiliation(s)
- Tyler Radack
- Rothman Institute at Thomas Jefferson University, Philadelphia, PA
| | - Matthew Meade
- Division of Orthopaedic Surgery, Jefferson Health, Stratford, NJ
| | - Barrett Woods
- Rothman Institute at Thomas Jefferson University, Philadelphia, PA
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9
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Asdo A, Mawji A, Agaba C, Komugisha C, Novakowski SK, Pillay Y, Kamau S, Wiens MO, Akech S, Tagoola A, Kissoon N, Ansermino JM, Dunsmuir D. Repeatability of Pulse Oximetry Measurements in Children During Triage in 2 Ugandan Hospitals. GLOBAL HEALTH, SCIENCE AND PRACTICE 2023; 11:e2200544. [PMID: 37640488 PMCID: PMC10461707 DOI: 10.9745/ghsp-d-22-00544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 07/31/2023] [Indexed: 08/31/2023]
Abstract
BACKGROUND In low- and middle-income countries, health workers use pulse oximeters for intermittent spot measurements of oxygen saturation (SpO2). However, the accuracy and reliability of pulse oximeters for spot measurements have not been determined. We evaluated the repeatability of spot measurements and the ideal observation time to guide recommendations during spot check measurements. METHODS Two 1-minute measurements were taken for the 3,903 subjects enrolled in the study conducted April 2020-January 2022 in Uganda, collecting 1 Hz SpO2 and signal quality index (SQI) data. The repeatability between the 2 measurements was assessed using an intraclass correlation coefficient (ICC), calculated using a median of all seconds of non-zero SpO2 values for each recording (any quality, Q1) and again with a quality filter only using seconds with SQI 90% or higher (good quality, Q2). The ICC was also recalculated for both conditions of Q1 and Q2 using the initial 5 seconds, then the initial 10 seconds, and continuing with 5-second increments up to the full 60 seconds. Lastly, the whole minute ICC was calculated with good quality (Q2), including only records where both measurements had a mean SQI of more than 70% (Q3). RESULTS The repeatability ICC with condition Q1 was 0.591 (95% confidence interval [CI]=0.570, 0.611). Using only the first 5 seconds of each measurement reduced the repeatability to 0.200 (95% CI=0.169, 0.230). Filtering with Q2, the whole-minute ICC was 0.855 (95% CI=0.847, 0.864). The ICC did not improve beyond the first 35 seconds. For Q3, the repeatability rose to 0.908 (95% CI=0.901, 0.914). CONCLUSIONS Training guidelines must emphasize the importance of signal quality and duration of measurement, targeting a minimum of 35 seconds of adequate-quality, stable data. In addition, the design of new devices should incorporate user prompts and force quality checks to encourage more accurate pulse oximetry measurements.
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Affiliation(s)
- Ahmad Asdo
- Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Vancouver, Canada
- Institute for Global Health at BC Children’s and Women’s Hospital, Vancouver, Canada
| | - Alishah Mawji
- Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Vancouver, Canada
- Institute for Global Health at BC Children’s and Women’s Hospital, Vancouver, Canada
| | - Collins Agaba
- World Alliance for Lung and Intensive Care Medicine in Uganda, Kampala, Uganda
| | - Clare Komugisha
- World Alliance for Lung and Intensive Care Medicine in Uganda, Kampala, Uganda
| | - Stefanie K. Novakowski
- Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Vancouver, Canada
- Institute for Global Health at BC Children’s and Women’s Hospital, Vancouver, Canada
| | - Yashodani Pillay
- Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Vancouver, Canada
- Institute for Global Health at BC Children’s and Women’s Hospital, Vancouver, Canada
| | - Stephen Kamau
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya
| | - Matthew O. Wiens
- Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Vancouver, Canada
- Institute for Global Health at BC Children’s and Women’s Hospital, Vancouver, Canada
- World Alliance for Lung and Intensive Care Medicine in Uganda, Kampala, Uganda
| | - Samuel Akech
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya
| | - Abner Tagoola
- Department of Pediatrics, Jinja Regional Referral Hospital, Jinja, Uganda
| | - Niranjan Kissoon
- Institute for Global Health at BC Children’s and Women’s Hospital, Vancouver, Canada
- Department of Pediatrics, University of British Columbia, Vancouver, Canada
| | - J. Mark Ansermino
- Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Vancouver, Canada
- Institute for Global Health at BC Children’s and Women’s Hospital, Vancouver, Canada
| | - Dustin Dunsmuir
- Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Vancouver, Canada
- Institute for Global Health at BC Children’s and Women’s Hospital, Vancouver, Canada
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10
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Gleason JL, Tamburro R, Signore C. Promoting Data Harmonization of COVID-19 Research in Pregnant and Pediatric Populations. JAMA 2023; 330:497-498. [PMID: 37471096 DOI: 10.1001/jama.2023.10835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/21/2023]
Abstract
This Viewpoint investigates the use of common data elements to promote data harmonization in COVID-19–related studies of pediatric and pregnant populations.
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Affiliation(s)
- Jessica L Gleason
- Epidemiology Branch, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland
| | - Robert Tamburro
- Division of Extramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland
| | - Caroline Signore
- Division of Extramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland
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11
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Ranjit S, Kissoon N, Argent A, Inwald D, Ventura AMC, Jaborinsky R, Sankar J, de Souza DC, Natraj R, De Oliveira CF, Samransamruajkit R, Jayashree M, Schlapbach LJ. Haemodynamic support for paediatric septic shock: a global perspective. THE LANCET. CHILD & ADOLESCENT HEALTH 2023; 7:588-598. [PMID: 37354910 DOI: 10.1016/s2352-4642(23)00103-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Revised: 04/19/2023] [Accepted: 04/19/2023] [Indexed: 06/26/2023]
Abstract
Septic shock is a leading cause of hospitalisation, morbidity, and mortality for children worldwide. In 2020, the paediatric Surviving Sepsis Campaign (SSC) issued evidence-based recommendations for clinicians caring for children with septic shock and sepsis-associated organ dysfunction based on the evidence available at the time. There are now more trials from multiple settings, including low-income and middle-income countries (LMICs), addressing optimal fluid choice and amount, selection and timing of vasoactive infusions, and optimal monitoring and therapeutic endpoints. In response to developments in adult critical care to trial personalised haemodynamic management algorithms, it is timely to critically reassess the current state of applying SSC guidelines in LMIC settings. In this Viewpoint, we briefly outline the challenges to improve sepsis care in LMICs and then discuss three key concepts that are relevant to management of children with septic shock around the world, especially in LMICs. These concepts include uncertainties surrounding the early recognition of paediatric septic shock, choices for initial haemodynamic support, and titration of ongoing resuscitation to therapeutic endpoints. Specifically, given the evolving understanding of clinical phenotypes, we focus on the controversies surrounding the concepts of early fluid resuscitation and vasoactive agent use, including insights gained from experience in LMICs and high-income countries. We outline the key components of sepsis management that are both globally relevant and translatable to low-resource settings, with a view to open the conversation to the large variety of treatment pathways, especially in LMICs. We emphasise the role of simple and easily available monitoring tools to apply the SSC guidelines and to tailor individualised support to the patient's cardiovascular physiology.
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Affiliation(s)
- Suchitra Ranjit
- Paediatric Intensive Care Unit, Apollo Children's Hospital, Chennai, India.
| | | | - Andrew Argent
- Department of Paediatrics and Child Health, University of Cape Town, Red Cross War Memorial Children's Hospital, Cape Town, South Africa
| | - David Inwald
- Addenbrooke's Hospital, University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Andréa Maria Cordeiro Ventura
- Department of Pediatrics, Pediatric Intensive Care Unit, Hospital Universitário da Universidade de Sao Paulo, São Paulo, Brazil
| | - Roberto Jaborinsky
- Northeastern National University, Corrientes, Argentina; Latin American Society of Pediatric Intensive Care (LARed Network), Montevideo, Uruguay; SLACIP Sociedad Latinoamericana de Cuidados Intensivos Pediátricos, Monterrey, Mexico
| | - Jhuma Sankar
- Division of Pediatric Pulmonology and Critical Care, Department of Pediatrics, AIIMS, New Delhi, India
| | - Daniela Carla de Souza
- Department of Pediatrics, Pediatric Intensive Care Unit, Hospital Universitário da Universidade de Sao Paulo, São Paulo, Brazil; Latin American Sepsis Institute, São Paulo, Brazil
| | - Rajeswari Natraj
- Department of Paediatric Intensive Care, Apollo Children's Hospitals, Chennai, India
| | | | - Rujipat Samransamruajkit
- Division of Pediatric Critical Care, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Muralidharan Jayashree
- Pediatric Emergency and Intensive Care, Advanced Pediatrics Centre, PGIMER, Chandigarh, India
| | - Luregn J Schlapbach
- Child Health Research Centre, The University of Queensland, Brisbane, QLD, Australia; Department of Intensive Care and Neonatology and Children's Research Center, University Children's Hospital Zurich, University of Zurich, Zurich, Switzerland
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12
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Harmonization and standardization of data for a pan-European cohort on SARS- CoV-2 pandemic. NPJ Digit Med 2022; 5:75. [PMID: 35701537 PMCID: PMC9198067 DOI: 10.1038/s41746-022-00620-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 05/19/2022] [Indexed: 11/12/2022] Open
Abstract
The European project ORCHESTRA intends to create a new pan-European cohort to rapidly advance the knowledge of the effects and treatment of COVID-19. Establishing processes that facilitate the merging of heterogeneous clusters of retrospective data was an essential challenge. In addition, data from new ORCHESTRA prospective studies have to be compatible with earlier collected information to be efficiently combined. In this article, we describe how we utilized and contributed to existing standard terminologies to create consistent semantic representation of over 2500 COVID-19-related variables taken from three ORCHESTRA studies. The goal is to enable the semantic interoperability of data within the existing project studies and to create a common basis of standardized elements available for the design of new COVID-19 studies. We also identified 743 variables that were commonly used in two of the three prospective ORCHESTRA studies and can therefore be directly combined for analysis purposes. Additionally, we actively contributed to global interoperability by submitting new concept requests to the terminology Standards Development Organizations.
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13
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Mawji A, Li E, Dunsmuir D, Komugisha C, Novakowski SK, Wiens MO, Vesuvius TA, Kissoon N, Ansermino JM. Smart triage: Development of a rapid pediatric triage algorithm for use in low-and-middle income countries. Front Pediatr 2022; 10:976870. [PMID: 36483471 PMCID: PMC9723221 DOI: 10.3389/fped.2022.976870] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Accepted: 11/01/2022] [Indexed: 11/23/2022] Open
Abstract
INTRODUCTION Early and accurate recognition of children at risk of progressing to critical illness could contribute to improved patient outcomes and resource allocation. In resource limited settings digital triage tools can support decision making and improve healthcare delivery. We developed a model for rapid identification of critically ill children at triage. METHODS This was a prospective cohort study of acutely ill children presenting at Jinja Regional Referral Hospital in Eastern Uganda. Variables collected in the emergency department informed the development of a logistic model based on hospital admission using bootstrap stepwise regression. Low and high-risk thresholds for 90% minimum sensitivity and specificity, respectively generated three risk level categories. Performance was assessed using receiver operating characteristic curve analysis on a held-out test set generated by an 80:20 split with 10-fold cross validation. A risk stratification table informed clinical interpretation. RESULTS The model derivation cohort included 1,612 participants, with an admission rate of approximately 23%. The majority of admitted patients were under five years old and presenting with sepsis, malaria, or pneumonia. A 9-predictor triage model was derived: logit (p) = -32.888 + (0.252, square root of age) + (0.016, heart rate) + (0.819, temperature) + (-0.022, mid-upper arm circumference) + (0.048 transformed oxygen saturation) + (1.793, parent concern) + (1.012, difficulty breathing) + (1.814, oedema) + (1.506, pallor). The model afforded good discrimination, calibration, and risk stratification at the selected thresholds of 8% and 40%. CONCLUSION In a low income, pediatric population, we developed a nine variable triage model with high sensitivity and specificity to predict who should be admitted. The triage model can be integrated into any digital platform and used with minimal training to guide rapid identification of critically ill children at first contact. External validation and clinical implementation are in progress.
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Affiliation(s)
- Alishah Mawji
- Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Vancouver, BC, Canada.,Centre for International Child Health, BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - Edmond Li
- Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Vancouver, BC, Canada
| | - Dustin Dunsmuir
- Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Vancouver, BC, Canada.,Centre for International Child Health, BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | | | - Stefanie K Novakowski
- Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Vancouver, BC, Canada.,Centre for International Child Health, BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - Matthew O Wiens
- Centre for International Child Health, BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | | | - Niranjan Kissoon
- Department of Pediatrics, University of British Columbia, Vancouver, BC, Canada
| | - J Mark Ansermino
- Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Vancouver, BC, Canada.,Centre for International Child Health, BC Children's Hospital Research Institute, Vancouver, BC, Canada
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14
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Li ECK, Grays S, Tagoola A, Komugisha C, Nabweteme AM, Ansermino JM, Mitton C, Kissoon N, Khowaja AR. Cost-effectiveness analysis protocol of the Smart Triage program: A point-of-care digital triage platform for pediatric sepsis in Eastern Uganda. PLoS One 2021; 16:e0260044. [PMID: 34788338 PMCID: PMC8598020 DOI: 10.1371/journal.pone.0260044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 11/01/2021] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND Sepsis is a clinical syndrome characterized by organ dysfunction due to presumed or proven infection. Severe cases can have case fatality ratio 25% or higher in low-middle income countries, but early diagnosis and timely treatment have a proven benefit. The Smart Triage program in Jinja Regional Referral Hospital in Uganda will provide expedited sepsis treatment in children through a data-driven electronic patient triage system. To complement the ongoing Smart Triage interventional trial, we propose methods for a concurrent cost-effectiveness analysis of the Smart Triage platform. METHODS We will use a decision-analytic model taking a societal perspective, combining government and out-of-pocket costs, as patients bear a sizeable portion of healthcare costs in Uganda due to the lack of universal health coverage. Previously published secondary data will be used to link healthcare utilization with costs and intermediate outcomes with mortality. We will model uncertainty via probabilistic sensitivity analysis and present findings at various willingness-to-pay thresholds using a cost-effectiveness acceptability curve. DISCUSSION Our proposed analysis represents a first step in evaluating the cost-effectiveness of an innovative digital triage platform designed to improve clinical outcomes in pediatric sepsis through expediting care in low-resource settings. Our use of a decision analytic model to link secondary costing data, incorporate post-discharge healthcare utilization, and model clinical endpoints is also novel in the pediatric sepsis triage literature for low-middle income countries. Our analysis, together with subsequent analyses modelling budget impact and scale up, will inform future modifications to the Smart Triage platform, as well as motivate scale-up to the district and national levels. TRIAL REGISTRATION Trial registration of parent clinical trial: NCT04304235, https://clinicaltrials.gov/ct2/show/NCT04304235. Registered 11 March 2020.
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Affiliation(s)
- Edmond C. K. Li
- School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
| | - Sela Grays
- Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada
| | | | | | | | - J. Mark Ansermino
- Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Craig Mitton
- School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
- Centre for Clinical Epidemiology and Evaluation, Vancouver Coastal Health, Vancouver, Canada
| | - Niranjan Kissoon
- Department of Pediatrics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Asif R. Khowaja
- Faculty of Applied Health Sciences, Brock University, St. Catharines, Canada
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15
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Chandna A, Osborn J, Bassat Q, Bell D, Burza S, D'Acremont V, Fernandez-Carballo BL, Kain KC, Mayxay M, Wiens M, Dittrich S. Anticipating the future: prognostic tools as a complementary strategy to improve care for patients with febrile illnesses in resource-limited settings. BMJ Glob Health 2021; 6:bmjgh-2021-006057. [PMID: 34330761 PMCID: PMC8327814 DOI: 10.1136/bmjgh-2021-006057] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Accepted: 06/25/2021] [Indexed: 12/17/2022] Open
Abstract
In low-income and middle-income countries, most patients with febrile illnesses present to peripheral levels of the health system where diagnostic capacity is very limited. In these contexts, accurate risk stratification can be particularly impactful, helping to guide allocation of scarce resources to ensure timely and tailored care. However, reporting of prognostic research is often imprecise and few prognostic tests or algorithms are translated into clinical practice. Here, we review the often-conflated concepts of prognosis and diagnosis, with a focus on patients with febrile illnesses. Drawing on a recent global stakeholder consultation, we apply these concepts to propose three use-cases for prognostic tools in the management of febrile illnesses in resource-limited settings: (1) guiding referrals from the community to higher-level care; (2) informing resource allocation for patients admitted to hospital and (3) identifying patients who may benefit from closer follow-up post-hospital discharge. We explore the practical implications for new technologies and reflect on the challenges and knowledge gaps that must be addressed before this approach could be incorporated into routine care settings. Our intention is that these use-cases, alongside other recent initiatives, will help to promote a harmonised yet contextualised approach for prognostic research in febrile illness. We argue that this is especially important given the heterogeneous settings in which care is often provided for patients with febrile illnesses living in low-income and middle-income countries.
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Affiliation(s)
- Arjun Chandna
- Cambodia Oxford Medical Research Unit, Angkor Hospital for Children, Siem Reap, Cambodia .,Centre for Tropical Medicine & Global Health, University of Oxford, Oxford, UK
| | - Jennifer Osborn
- Foundation for Innovative New Diagnostics, Geneva, Switzerland
| | - Quique Bassat
- ISGlobal, Hospital Clínic, Universitat de Barcelona, Barcelona, Spain.,Centro de Investigação em Saúde de Manhiça (CISM), Maputo, Mozambique.,ICREA, Pg. Lluís Companys 23, Barcelona, Spain.,Pediatrics Department, Hospital Sant Joan de Dé, Universitat de Barcelona, Esplugues, Barcelona, Spain.,Consorcio de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - David Bell
- Independent Consultant, Issaquah, Washington, USA
| | | | - Valérie D'Acremont
- Centre for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland.,Swiss Tropical and Public Health Institute, Basel, Switzerland
| | | | - Kevin C Kain
- Department of Medicine, University Health Network, Toronto, Ontario, Canada
| | - Mayfong Mayxay
- Centre for Tropical Medicine & Global Health, University of Oxford, Oxford, UK.,Microbiology Department, Lao-Oxford-Mahosot Hospital-Wellcome Trust Research Unit, Vientiane, Lao People's Democratic Republic.,Institute of Research and Education Development (IRED), University of Health Sciences, Vientiane, Lao People's Democratic Republic
| | - Matthew Wiens
- Center for International Child Health, BC Children's Hospital, Vancouver, British Columbia, Canada.,Mbarara University of Science and Technology, Mbarara, Uganda.,Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada.,Walimu, Kampala, Uganda
| | - Sabine Dittrich
- Centre for Tropical Medicine & Global Health, University of Oxford, Oxford, UK.,Foundation for Innovative New Diagnostics, Geneva, Switzerland
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