Results 41 to 50 of about 1,599,078 (384)

Measurement of clinical documentation burden among physicians and nurses using electronic health records: a scoping review

J. Am. Medical Informatics Assoc., 2021
Background   Objective Electronic health records (EHRs) are linked with documentation burden resulting in clinician burnout. While clear classifications and validated measures of burnout exist, documentation burden remains ill-defined and inconsistently ...
Amanda J. Moy, Jessica M. Schwartz, Ruijun Chen, S. Sadri, E. Lucas, K. Cato, S. Rossetti   +6 more
semanticscholar   +1 more source

Electronic Health Records and Support For Primary Care Teamwork [PDF]

, 2015
This study examined primary care practices' experiences using electronic health records (EHRs) as they strive to function as teams in patientcentered medical homes (PCMHs). We identify how EHRs facilitate and pose challenges to teamwork and how practices
Ann S. O, Dori A. Cross, Kevin Draper, Rebecca Gourevitch, Sarah Hudson Scholle   +4 more
core   +2 more sources

The Requirements and Challenges in Using Personal Health Record

مدیریت اطلاعات سلامت, 2019
Patients apply the Personal Health Record (PHR) to access and use their record information and other medical resources. This study aimed to explain the concept, requirements, and challenges of PHR.
Mohammad Hosein Hayavi-Haghighi, Zari Rahmatpasand-Fatideh, Mohammad Dehghani   +2 more
doaj   +1 more source

Factors of quality of care and their association with smartphone based PHR adoption in South Korean hospitals

BMC Medical Informatics and Decision Making, 2021
Background Healthcare organizations have begun to adopt personal health records (PHR) systems to engage patients, but little is known about factors associated with the adoption of PHR systems at an organizational level.
Byung Kwan Choi, Young-Taek Park, Hyeoun-Ae Park, Chris Lane, Emmanuel C. Jo, Sunghong Kang   +5 more
doaj   +1 more source

Linked electronic health records for research on a nationwide cohort of more than 54 million people in England: data resource

British medical journal, 2021
Objective To describe a novel England-wide electronic health record (EHR) resource enabling whole population research on covid-19 and cardiovascular disease while ensuring data security and privacy and maintaining public trust.
A. Wood, R. Denholm, S. Hollings, J. Cooper, Samantha Ip, V. Walker, Spiros C. Denaxas, A. Akbari, A. Banerjee, W. Whiteley, A. Lai, J. Sterne, C. Sudlow, A. Douiri, Abdul Qadr Akinoso-Imran, Adrian Jonas, A. Shah, A. Handy, Alun H Davies, A. Kurdi, A. Hansell, A. Docherty, A. Pherwani, A. Dashtban, B. Bray, Ben. Cairns, B. Goldacre, Ben Humberstone, B. Mateen, B. Doble, Brian Roberts, Carole Morris, C. Dale, C. Rogers, C. Wolfe, Christopher Tomlinson, C. Lawson, Clea du Toit, C. Berry, Craig Smith, Daniel O'Connell, D. Harris, David Brind, D. Cromwell, David Hughes, David Moreno Martos, Debbie Ringham, Deborah Lawler, Deborah Lowe, Elena Nikiphorou, Eloise Withnell, E. di Angelantonio, E. Morris, E. Birney, Fabian Falck, F. Torabi, F. Greaves, F. Falter, F. Zaccardi, F. Kee, G. Davies, G. Nicholson, G. Curry, Haoting Zhang, H. Hemingway, H. Wilde, H. Abbasizanjani, Honghan Wu, H. Tang, Huan Wang, I. Mordi, J. MacArthur, J. Lyons, Jennifer Beveridge, Jessica K. Barrett, Jianhua Wu, J. Thygesen, J. Danesh, J. Dennis, Jon Boyle, J. Halcox, K. Khunti, K. Cheema, K. Brown, Ken Li, K. Kavanagh, L. North, L. Pasea, L. Ellins, L. Pierotti, L. Wright, Lydia Martin, L. Morrice, M. Mamas, M. Bennie, M. Barber, M. MacLeod, Massimo Caputo, M. Buch, M. Mizani, M. Katsoulis, M. Gravenor, M. Inouye, M. Skrypak, M. Gerstung, M. Pirmohamed, M. Glickman, N. Herz, N. Davies, N. Hall, Nilesh J Samani, O. Seminog, P. Lorgelly, P. Machado, Qiuju Li, R. Denholm, R. Goldacre, R. Carragher, R. Sofat, R. Takhar, R. Lyons, R. Priedon, R. Griffiths, R. Payne, R. Kolamunnage-Dona, S. Salim, S. Padmanabhan, S. Onida, S. Kent, S. Bacon, Sinduja Manohar, S. Babu-Narayan, Spencer J Keene, Susheel Varma, T. Lawrence, Tianxiao Wang, T. Wilkinson, T. Norris, T. Palmer, V. Nafilyan   +139 more
semanticscholar   +1 more source

Predicting diabetes-related hospitalizations based on electronic health records [PDF]

, 2019
OBJECTIVE: To derive a predictive model to identify patients likely to be hospitalized during the following year due to complications attributed to Type II diabetes. METHODS: A variety of supervised machine learning classification methods were tested and
Brisimi, Theodora S., Dai, Wuyang, Paschalidis, Ioannis Ch., Wang, Taiyao, Xu, Tingting   +4 more
core   +1 more source

Protocol for the development of a CONSORT extension for RCTs using cohorts and routinely collected health data

Research Integrity and Peer Review, 2018
Background Randomized controlled trials (RCTs) are often complex and expensive to perform. Less than one third achieve planned recruitment targets, follow-up can be labor-intensive, and many have limited real-world generalizability.
Linda Kwakkenbos, Edmund Juszczak, Lars G Hemkens, Margaret Sampson, Ole Fröbert, Clare Relton, Chris Gale, Merrick Zwarenstein, Sinéad M Langan, David Moher, Isabelle Boutron, Philippe Ravaud, Marion K Campbell, Kimberly A Mc Cord, Tjeerd P van Staa, Lehana Thabane, Rudolf Uher, Helena M Verkooijen, Eric I Benchimol, David Erlinge, Maureen Sauvé, David Torgerson, Brett D Thombs   +22 more
doaj   +1 more source

Adoption of Electronic Health Records: A Roadmap for India [PDF]

Healthcare Informatics Research, 2016
ObjectivesThe objective of the study was to create a roadmap for the adoption of Electronic Health Record (EHR) in India based an analysis of the strategies of other countries and national scenarios of ICT use in India.MethodsThe strategies for adoption ...
Sunil Kumar Srivastava
doaj   +1 more source

Deep representation learning of electronic health records to unlock patient stratification at scale [PDF]

npj Digital Medicine, 2020
Deriving disease subtypes from electronic health records (EHRs) can guide next-generation personalized medicine. However, challenges in summarizing and representing patient data prevent widespread practice of scalable EHR-based stratification analysis ...
I. Landi, B. Glicksberg, Hao-Chih Lee, S. Cherng, Giulia Landi, M. Danieletto, J. Dudley, Cesare Furlanello, Riccardo Miotto   +8 more
semanticscholar   +1 more source

Synergistic drug combinations from electronic health records and gene expression. [PDF]

, 2016
ObjectiveUsing electronic health records (EHRs) and biomolecular data, we sought to discover drug pairs with synergistic repurposing potential. EHRs provide real-world treatment and outcome patterns, while complementary biomolecular data, including ...
Chen, William, Daugherty, Aaron C, Desai, Manisha, Farrington, Carl, Gomez, Scarlett L, Hastie, Trevor, Kenkare, Pragati, Kurian, Allison W, Lim, Michael, Low, Yen S, Mathur, Maya, Radin, Andrew A, Schroeder, Elizabeth A, Seto, Tina, Shah, Nigam H, Sirota, Marina, Sledge, George W, Thompson, Caroline A, Weber, Susan, Yu, Peter P   +19 more
core   +2 more sources