scholarly journals Extracting Clinical Information from Electronic Medical Records

2018 ◽  
pp. 113-120 ◽  
Author(s):  
Manuel Lamy ◽  
Rúben Pereira ◽  
João C. Ferreira ◽  
José Braga Vasconcelos ◽  
Fernando Melo ◽  
...  
Keyword(s):  
Electronic Medical Records ◽  
Medical Records ◽  
Clinical Information

Informed Consent and Biobanks

2005 ◽  
Vol 33 (1) ◽  
pp. 15-21 ◽  
Author(s):  
Ellen Wright Clayton
Keyword(s):  
Information Technology ◽  
Informed Consent ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Clinical Information ◽  
Information Resources ◽  
Biomedical Science ◽  
Research Setting ◽  
The Past

Biomedical research has always relied on access to human biological materials and clinical information, resources that when combined form biobanks. In the past, it appears that investigators sometimes used these resources with relatively little oversight, and without the consent of the individuals from whom these materials and information were obtained. Several developments in the last ten to fifteen years have converged to place greater emphasis on the role of individual consent in the creation and use of biobanks. The most important by far is the power of information technology, which has transformed our lives in almost every domain. In the research setting, it is now easy to abstract information from electronic medical records. Computers make it possible to analyze enormous datasets and have contributed in essential ways to the dramatic increases in our understanding of genomics and other areas of biomedical science.

scholarly journals Clinician-Dermatopathologist Communication via the Requisition Form in the Era of Electronic Medical Records: A Review of the Literature

2020 ◽  
Vol 4 (1) ◽  
pp. 15-22
Author(s):  
Haley Danielle Heibel ◽  
Clay J. Cockerell
Keyword(s):  
Electronic Medical Records ◽  
Medical Records ◽  
English Language ◽  
Formal Education ◽  
Clinical Information ◽  
Cost Effective ◽  
Work Flow ◽  
Review Of The Literature ◽  
Study Designs ◽  
User Friendly

Background:  There are shortcomings in the quality and accuracy of submitted clinical information on skin biopsy requisition forms (SBRFs).  Most SBRFs are completed via electronic medical records (EMR), and the effect of this on the work flow and the quality of submitted clinical information must be evaluated to identify targets in clinician-dermatopathologist communication for improvement.Objective: This review of the literature explored how SBRFs are currently handled by clinicians in the context of EMR, barriers to effective clinician-dermatopathologist communication, and suggestions for improvement.Methods: A literature search was conducted on Medline, Cinahl, and Scopus including the keywords of dermatology*, dermapatholog*, dermatopathology*, and requisition*.  20 articles were retrieved.  17 articles were included from this search and from cross-referencing articles.Results:  This review reaffirmed the inadequacy of clinical information provided to dermatopathologists.  Standardization of and formal education in completing SBRFs, along with dermatopathologist access to information and images via shared EMR may improve histopathologic interpretation of specimens and allow for cost-effective patient care.Limitations: This review was restricted to the English language.  Previous studies have primarily been retrospective study designs and survey studies.Conclusion: The development of user-friendly standardized SBRFs with validated criteria are necessary.  Clinician awareness of how to appropriately convey information and terminology on the SBRF may significantly improve the work flow of both clinicians and dermatopathologists and patient outcomes.

A Bio-Psycho-Social Review of Usability Methods and their Applications in Healthcare

2011 ◽  
pp. 1874-1899 ◽  
Author(s):  
Morgan Price
Keyword(s):  
Information Systems ◽  
Social Interactions ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Clinical Information ◽  
Hospital Information Systems ◽  
The Other ◽  
Clinical Information Systems ◽  
Complete Understanding

The purpose of this chapter is to provide the reader with an overview of several models and theories from the general HCI literature, highlighting models at three levels of focus: biomechanical interactions, individual-cognitive interactions, and social interactions. This chapter will also explore how these models were or could be applied to the design and evaluation of clinical information systems, such as electronic medical records and hospital information systems. Finally, it will conclude with how an understanding at each level compliments the other two in order to create a more complete understanding of the interactions of information systems in healthcare.

scholarly journals A Hybrid Method to Extract Clinical Information From Chinese Electronic Medical Records

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 70624-70633 ◽  
Author(s):  
Ming Cheng ◽  
Liming Li ◽  
Yafeng Ren ◽  
Yinxia Lou ◽  
Jianbo Gao
Keyword(s):  
Electronic Medical Records ◽  
Hybrid Method ◽  
Medical Records ◽  
Clinical Information

scholarly journals Ongoing Use of SSRIs Does Not Alter Outcome in Hospitalized COVID-19 Patients: A Retrospective Analysis

2021 ◽  
Vol 11 (1) ◽  
pp. 70
Author(s):  
Steven H. Rauchman ◽  
Sherri G. Mendelson ◽  
Courtney Rauchman ◽  
Lora J. Kasselman ◽  
Aaron Pinkhasov ◽  
...  
Keyword(s):  
Electronic Medical Records ◽  
Symptom Severity ◽  
Medical Records ◽  
Logistic Regression Model ◽  
Clinical Information ◽  
Infectious Agents ◽  
Clinical Databases ◽  
Significant Difference ◽  
Ssri Treatment ◽  
Age Category

SARS-CoV-2 continues to have devastating consequences worldwide. Though vaccinations have helped reduce spread, new strains still pose a threat. Therefore, it is imperative to identify treatments that prevent severe COVID-19 infection. Recently, acute use of SSRI antidepressants in COVID+ patients was shown to reduce symptom severity. The aim of this retrospective observational study was to determine whether COVID+ patients already on SSRIs upon hospital admission had reduced mortality compared to COVID+ patients not on chronic SSRI treatment. Electronic medical records of 9044 patients with laboratory-confirmed COVID-19 from six hospitals were queried for demographic and clinical information. Using R, a logistic regression model was run with mortality as the outcome and SSRI status as the exposure. In this sample, no patients admitted on SSRIs had them discontinued. There was no significant difference in the odds of dying between COVID+ patients on chronic SSRIs vs. those not taking SSRIs, after controlling for age category, gender, and race. This study shows the utility of large clinical databases in determining what commonly prescribed drugs might be useful in treating COVID-19. During pandemics due to novel infectious agents, it is critical to evaluate safety and efficacy of drugs that might be repurposed for treatment.

scholarly journals Electronic medical records in humanitarian emergencies – the development of an Ebola clinical information and patient management system

F1000Research ◽  
2016 ◽  
Vol 5 ◽  
pp. 1477
Author(s):  
Kiran Jobanputra ◽  
Jane Greig ◽  
Ganesh Shankar ◽  
Eric Perakslis ◽  
Ronald Kremer ◽  
...  
Keyword(s):  
Electronic Medical Records ◽  
Medical Records ◽  
Social Impact ◽  
Clinical Information ◽  
Shared Vision ◽  
Lessons Learned ◽  
Software Developers ◽  
Humanitarian Emergencies ◽  
Individual Variables ◽  
Clinical Interactions

By November 2015, the West Africa Ebola epidemic had caused 28598 infections and 11299 deaths in the three countries most affected. The outbreak required rapid innovation and adaptation. Médecins sans Frontières (MSF) scaled up its usual 20-30 bed Ebola management centres (EMCs) to 100-300 beds with over 300 workers in some settings. This brought challenges in patient and clinical data management resulting from the difficulties of working safely with high numbers of Ebola patients. We describe a project MSF established with software developers and the Google Social Impact Team to develop context-adapted tools to address the challenges of recording Ebola clinical information. We share the outcomes and key lessons learned in innovating rapidly under pressure in difficult environmental conditions. Information on adoption, maintenance, and data quality was gathered through review of project documentation, discussions with field staff and key project stakeholders, and analysis of tablet data. In March 2015, a full prototype was deployed in Magburaka EMC, Sierra Leone. Inpatient data were captured on 204 clinical interactions with 34 patients from 5 March until 10 April 2015. Data continued to also be recorded on paper charts, creating theoretically identical record “pairs” on paper and tablet. 85 record pairs for 32 patients with 26 data items (temperature and symptoms) per pair were analysed. The average agreement between sources was 85%, ranging from 69% to 95% for individual variables. The time taken to deliver the product was more than that anticipated by MSF (7 months versus 6 weeks). Deployment of the tablet coincided with a dramatic drop in patient numbers and thus had little impact on patient care. We have identified lessons specific to humanitarian-technology collaborative projects and propose a framework for emergency humanitarian innovation. Time and effort is required to bridge differences in organisational culture between the technology and humanitarian worlds. This investment is essential for establishing a shared vision on deliverables, urgency, and ownership of product.

scholarly journals Electronic medical records in humanitarian emergencies – the development of an Ebola clinical information and patient management system

F1000Research ◽  
2017 ◽  
Vol 5 ◽  
pp. 1477 ◽  
Author(s):  
Kiran Jobanputra ◽  
Jane Greig ◽  
Ganesh Shankar ◽  
Eric Perakslis ◽  
Ronald Kremer ◽  
...  
Keyword(s):  
Electronic Medical Records ◽  
Medical Records ◽  
Social Impact ◽  
Clinical Information ◽  
Shared Vision ◽  
Lessons Learned ◽  
Software Developers ◽  
Humanitarian Emergencies ◽  
Clinical Interactions ◽  
Good Agreement

By November 2015, the West Africa Ebola epidemic had caused 28598 infections and 11299 deaths in the three countries most affected. The outbreak required rapid innovation and adaptation. Médecins sans Frontières (MSF) scaled up its usual 20-30 bed Ebola management centres (EMCs) to 100-300 beds with over 300 workers in some settings. This brought challenges in patient and clinical data management resulting from the difficulties of working safely with high numbers of Ebola patients. We describe a project MSF established with software developers and the Google Social Impact Team to develop context-adapted tools to address the challenges of recording Ebola clinical information. We share the outcomes and key lessons learned in innovating rapidly under pressure in difficult environmental conditions. Information on adoption, maintenance, and data quality was gathered through review of project documentation, discussions with field staff and key project stakeholders, and analysis of tablet data. In March 2015, a full prototype was deployed in Magburaka EMC, Sierra Leone. Inpatient data were captured on 204 clinical interactions with 34 patients from 5 March until 10 April 2015. Data continued to also be recorded on paper charts, creating theoretically identical record “pairs” on paper and tablet. 83 record pairs for 33 patients with 22 data items (temperature and symptoms) per pair were analysed. The overall Kappa coefficient for agreement between sources was 0.62, but reduced to 0.59 when rare bleeding symptoms were excluded, indicating moderate to good agreement. The time taken to deliver the product was more than that anticipated by MSF (7 months versus 6 weeks). Deployment of the tablet coincided with a dramatic drop in patient numbers and thus had little impact on patient care. We have identified lessons specific to humanitarian-technology collaborative projects and propose a framework for emergency humanitarian innovation. Time and effort is required to bridge differences in organisational culture between the technology and humanitarian worlds. This investment is essential for establishing a shared vision on deliverables, urgency, and ownership of product.

A Bio-Psycho-Social Review of Usability Methods and their Applications in Healthcare

2010 ◽  
pp. 23-48 ◽  
Author(s):  
Morgan Price
Keyword(s):  
Information Systems ◽  
Social Interactions ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Clinical Information ◽  
Hospital Information Systems ◽  
The Other ◽  
Clinical Information Systems ◽  
Complete Understanding

The purpose of this chapter is to provide the reader with an overview of several models and theories from the general HCI literature, highlighting models at three levels of focus: biomechanical interactions, individual-cognitive interactions, and social interactions. This chapter will also explore how these models were or could be applied to the design and evaluation of clinical information systems, such as electronic medical records and hospital information systems. Finally, it will conclude with how an understanding at each level compliments the other two in order to create a more complete understanding of the interactions of information systems in healthcare.

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