Correction to: Designing and implementing smart glass technology for emergency medical services: a sociotechnical perspective.
[This corrects the article DOI: 10.1093/jamiaopen/ooac113.].
Author(s):
DOI: 10.1093/jamiaopen/ooad008
[This corrects the article DOI: 10.1093/jamiaopen/ooac113.].
Author(s):
DOI: 10.1093/jamiaopen/ooad008
Mobile health (mHealth) technologies in low- and middle-income countries (LMICs) have received increased attention for the significant potential benefits they can bring to underserved populations. As smartphones are becoming increasingly accessible, many stakeholders in the mHealth space have begun exploring smartphone applications as a means to impact individuals living within LMICs. With the COVID-19 pandemic straining healthcare systems around the world, many governments in LMICs turned to use smartphone applications [...]
Author(s): Winkie, Mitchell J, Nambudiri, Vinod E
DOI: 10.1093/jamia/ocac146
In the wake of Coronavirus disease 2019 (COVID-19), several nations have sought to implement digital vaccine passports (DVPs) to enable the resumption of international travel. Comprising a minimum dataset for each unique individual, DVPs have the makings of a global electronic health record, broaching key issues involved in building a global digital health ecosystem. Debate simulations offer a safe, interactive space to foster participatory policy discussions for advancing digital health [...]
Author(s): Godinho, Myron Anthony, Liaw, Siaw-Teng, Kanjo, Chipo, Marin, Heimar F, Martins, Henrique, Quintana, Yuri
DOI: 10.1093/jamia/ocac126
Author(s): Quintana, Yuri, Cullen, Theresa A, Holmes, John H, Joshi, Ashish, Novillo-Ortiz, David, Liaw, Siaw-Teng
DOI: 10.1093/jamia/ocad027
We provide a scoping review of Digital Health Interventions (DHIs) that mitigate COVID-19 misinformation and disinformation seeding and spread.
Author(s): Czerniak, Katarzyna, Pillai, Raji, Parmar, Abhi, Ramnath, Kavita, Krocker, Joseph, Myneni, Sahiti
DOI: 10.1093/jamia/ocad005
Patients and families are key partners in diagnosis, but methods to routinely engage them in diagnostic safety are lacking. Policy mandating patient access to electronic health information presents new opportunities. We tested a new online tool ("OurDX") that was codesigned with patients and families, to determine the types and frequencies of potential safety issues identified by patients/families with chronic health conditions and whether their contributions were integrated into the visit [...]
Author(s): Bell, Sigall K, Dong, Zhiyong J, Desroches, Catherine M, Hart, Nicholas, Liu, Stephen, Mahon, Brianna, Ngo, Long H, Thomas, Eric J, Bourgeois, Fabienne
DOI: 10.1093/jamia/ocad003
Convert the Medical Information Mart for Intensive Care (MIMIC)-IV database into Health Level 7 Fast Healthcare Interoperability Resources (FHIR). Additionally, generate and publish an openly available demo of the resources, and create a FHIR Implementation Guide to support and clarify the usage of MIMIC-IV on FHIR.
Author(s): Bennett, Alex M, Ulrich, Hannes, van Damme, Philip, Wiedekopf, Joshua, Johnson, Alistair E W
DOI: 10.1093/jamia/ocad002
Ambient clinical documentation technology uses automatic speech recognition (ASR) and natural language processing (NLP) to turn patient-clinician conversations into clinical documentation. It is a promising approach to reducing clinician burden and improving documentation quality. However, the performance of current-generation ASR remains inadequately validated. In this study, we investigated the impact of non-lexical conversational sounds (NLCS) on ASR performance. NLCS, such as Mm-hm and Uh-uh, are commonly used to convey important [...]
Author(s): Tran, Brian D, Latif, Kareem, Reynolds, Tera L, Park, Jihyun, Elston Lafata, Jennifer, Tai-Seale, Ming, Zheng, Kai
DOI: 10.1093/jamia/ocad001
The onset of COVID-19 and related policy responses made it difficult to study interactive health informatics solutions in clinical study settings. Instrumented log and event data from interactive systems capture temporal details that can be used to generate insights about care continuity during ongoing pandemics.
Author(s): Wachira, Charles, Ogallo, William, Okwako, Sharon, Remy, Sekou Lionel, Bukania, Zipporah, Njeru, Mercy Karimi, Mwangi, Moses, Mokua, Sharon, Omwanda, Wycliffe, Ressler, Daniele, Walcott-Bryant, Aisha
DOI: 10.1093/jamia/ocad004
Extracorporeal membrane oxygenation (ECMO) resource allocation tools are currently lacking. We developed machine learning (ML) models for predicting COVID-19 patients at risk of receiving ECMO to guide patient triage and resource allocation.
Author(s): Xue, Bing, Shah, Neel, Yang, Hanqing, Kannampallil, Thomas, Payne, Philip Richard Orrin, Lu, Chenyang, Said, Ahmed Sameh
DOI: 10.1093/jamia/ocac256