scholarly journals How Nurses Identify Hospitalized Patients on Their Personal Notes: Findings From Analyzing ‘Brains’ Headers with Multiple Raters

2018 ◽  
Vol 7 (1) ◽  
pp. 205-209 ◽  
Author(s):  
Ritesh Sarkhel ◽  
Jacob J. Socha ◽  
Austin Mount-Campbell ◽  
Susan Moffatt-Bruce ◽  
Simon Fernandez ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Registered Nurses ◽  
Hospital Setting ◽  
Future Research ◽  
Learning Approaches ◽  
Health Records ◽  
Web Based ◽  
Gender And Age ◽  
Primary Finding ◽  
Electronic Health

The overarching objective of this research is to reduce the burden of documentation in electronic health records by registered nurses in hospitals. Registered nurses have consistently reported that e-documentation is a concern with the introduction of electronic health records. As a result, many nurses use handwritten notes in order to avoid using electronic health records to access information about patients. At the top of these notes are patient identifiers. By identifying aspects of good and suboptimal headers, we can begin to form a model of how to effectively support identifying patients during assessments and care activities. The primary finding is that nurses use room number as the primary patient identifier in the hospital setting, not the patient’s last name. In addition, the last name, gender, and age are sufficiently important identifiers that they are frequently recorded at the top of handwritten notes. Clearly distinguishable field labels and values are helpful in quickly scanning the identifier for identifying information. A web based annotator was designed as a first step towards machine learning approaches to recognize handwritten or printed data on paper sheets in future research.

Research and application of artificial intelligence based on electronic health record data from patients with cancer: a systematic review (Preprint)

2021 ◽  
Author(s):  
Xinyu Yang ◽  
Dongmei Mu ◽  
Hao Peng ◽  
Hua Li ◽  
Ying Wang ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Electronic Health Records ◽  
Ensemble Methods ◽  
Future Research ◽  
Electronic Health Record Data ◽  
Health Records ◽  
Patients With Cancer ◽  
Cancer Management ◽  
Treatment And Prevention ◽  
Electronic Health

BACKGROUND With the accumulation of electronic health records data and the development of artificial intelligence, patients with cancer urgently need new evidence of more personalized clinical and demographic characteristics and more sophisticated treatment and prevention strategies. However, no research has systematically analyzed the application and significance of electronic health records and artificial intelligence in cancer care. OBJECTIVE In this study, we reviewed the literature on the application of AI based on EHR data from patients with cancer, hoping to provide reference for subsequent researchers, and help accelerate the application of EHR data and AI technology in the field of cancer, so as to help patients get more scientific and accurate treatment. METHODS Three databases were systematically searched to retrieve potentially relevant articles published from January 2009 to October 2020. A combination of terms related to "electronic health records", "artificial intelligence" and "cancer" was used to search for these publications. RESULTS Of the 1034 articles considered, 148 met the inclusion criteria. The review has shown that ensemble methods and deep learning were on the rise. It presented the representative literatures on the subfield of cancer diagnosis, treatment and care. In addition, the vast majority of studies in this area were based on private institutional databases, resulting in poor portability of the proposed methodology process. CONCLUSIONS The use of new methods and electronic health records data sharing and fusion were recommended for future research. With the help of specialists, artificial intelligence and the mining of massive electronic medical records could provide great opportunities for improving cancer management.

A Web-Based Application to Exchange Electronic Health Records and Medical Images in Ophthalmology

2009 ◽  
pp. 152-164
Author(s):  
Isabel de la Torre Díez
Keyword(s):  
Electronic Health Records ◽  
Medical Images ◽  
Universal Access ◽  
Diabetic Patients ◽  
Health Records ◽  
Web Based ◽  
Clinical Document ◽  
Extensible Markup ◽  
Electronic Health ◽  
Web Based System

This chapter describes a Web -based application to store and exchange Electronic Health Records (EHR) and medical images in Ophthalmology: TeleOftalWeb 3.2. The Web -based system has been built on Java Servlet and Java Server Pages (JSP) technologies. Its architecture is a typical three-layered with two databases. The user and authentication information is stored in a relational database: MySQL 5.0. The patient records and fundus images are achieved in an Extensible Markup Language (XML) native database: dbXML 2.0. The application uses XML-based technologies and Health Level Seven/Clinical Document Architecture (HL7/CDA) specifications. The EHR standardization is carried out. The main application object is the universal access to the diabetic patients EHR by physicians wherever they are.

scholarly journals Understanding optimisation processes of electronic health records (EHRs) in select leading hospitals: a qualitative study

2018 ◽  
Vol 25 (2) ◽  
pp. 109-125 ◽  
Author(s):  
Mark Chun Moon ◽  
Rebecca Hills ◽  
George Demiris
Keyword(s):  
United States ◽  
Qualitative Study ◽  
Electronic Health Records ◽  
Hospital Setting ◽  
The United States ◽  
Theory Approach ◽  
Health Records ◽  
High Performing ◽  
Advisory Groups ◽  
Electronic Health

BackgroundLittle is known about optimisation of electronic health records (EHRs) systems in the hospital setting while adoption of EHR systems continues in the United States.ObjectiveTo understand optimisation processes of EHR systems undertaken in leading healthcare organisations in the United States.MethodsInformed by a grounded theory approach, a qualitative study was undertaken that involved 11 in-depth interviews and a focus group with the EHR experts from the high performing healthcare organisations across the United States.ResultsThe study describes EHR optimisation processes characterised by prioritising exponentially increasing requests with predominant focus on improving efficiency of EHR, building optimisation teams or advisory groups and standardisation. The study discusses 16 types of optimisation that interdependently produced 16 results along with identifying 11 barriers and 20 facilitators to optimisation.ConclusionsThe study describes overall experiences of optimising EHRs in select high performing healthcare organisations in the US. The findings highlight the importance of optimising the EHR after, and even before, go-live and dedicating resources exclusively for optimisation.

Performance Evaluation of a Web-Based System to Exchange Electronic Health Records Using Queueing Model (M/M/1)

2010 ◽  
Vol 36 (2) ◽  
pp. 915-924 ◽  
Author(s):  
Isabel de la Torre ◽  
Francisco Javier Díaz ◽  
Míriam Antón ◽  
Mario Martínez ◽  
José Fernando Díez ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Electronic Health Records ◽  
Queueing Model ◽  
Health Records ◽  
Web Based ◽  
Electronic Health ◽  
Web Based System

Impact of electronic health records on the patient experience in a hospital setting

2014 ◽  
Vol 9 (10) ◽  
pp. 627-633 ◽  
Author(s):  
Christopher W. Migdal ◽  
Aram A. Namavar ◽  
Virgie N. Mosley ◽  
Nasim Afsar-manesh
Keyword(s):  
Electronic Health Records ◽  
Patient Experience ◽  
Hospital Setting ◽  
Health Records ◽  
Electronic Health

scholarly journals Towards a Stakeholder-Oriented Blockchain-Based Architecture for Electronic Health Records: Design Science Research Study

10.2196/13585 ◽  
2019 ◽  
Vol 21 (10) ◽  
pp. e13585 ◽  
Author(s):  
Jan Heinrich Beinke ◽  
Christian Fitte ◽  
Frank Teuteberg
Keyword(s):  
Electronic Health Records ◽  
Data Security ◽  
Design Science ◽  
Science Research ◽  
Design Science Research ◽  
Future Research ◽  
Health Records ◽  
Blockchain Technology ◽  
Recommendations For Action ◽  
Electronic Health

Background Data security issues still constitute the main reason for the sluggish dissemination of electronic health records (EHRs). Given that blockchain technology offers the possibility to verify transactions through a decentralized network, it may serve as a solution to secure health-related data. Therefore, we have identified stakeholder-specific requirements and propose a blockchain-based architecture for EHRs, while referring to the already existing scientific discussions on the potential of blockchain for use in EHRs. Objective This study aimed to introduce blockchain technology for EHRs, based on identifying stakeholders and systematically eliciting their requirements, and to discuss the key benefits (KBs) and key challenges (KCs) of blockchain technology in the context of EHRs. Methods The blockchain-based architecture was developed in the framework of the design science research paradigm. The requirements were identified using a structured literature review and interviews with nine health care experts. Subsequently, the proposed architecture was evaluated using 4 workshops with 15 participants. Results We identified three major EHR stakeholder groups and 34 respective requirements. On this basis, we developed a five-layer architecture. The subsequent evaluation of the artifact was followed by the discussion of 12 KBs and 12 KCs of a blockchain-based architecture for EHRs. To address the KCs, we derived five recommendations for action for science and practice. Conclusions Our findings indicate that blockchain technology offers considerable potential to advance EHRs. Improvements to currently available EHR solutions are expected, for instance, in the areas of data security, traceability, and automation by smart contracts. Future research could examine the patient’s acceptance of blockchain-based EHRs and cost-benefit analyses.

scholarly journals Towards a Stakeholder-Oriented Blockchain-Based Architecture for Electronic Health Records: Design Science Research Study (Preprint)

2019 ◽  
Author(s):  
Jan Heinrich Beinke ◽  
Christian Fitte ◽  
Frank Teuteberg
Keyword(s):  
Electronic Health Records ◽  
Data Security ◽  
Design Science ◽  
Science Research ◽  
Design Science Research ◽  
Future Research ◽  
Health Records ◽  
Blockchain Technology ◽  
Recommendations For Action ◽  
Electronic Health

BACKGROUND Data security issues still constitute the main reason for the sluggish dissemination of electronic health records (EHRs). Given that blockchain technology offers the possibility to verify transactions through a decentralized network, it may serve as a solution to secure health-related data. Therefore, we have identified stakeholder-specific requirements and propose a blockchain-based architecture for EHRs, while referring to the already existing scientific discussions on the potential of blockchain for use in EHRs. OBJECTIVE This study aimed to introduce blockchain technology for EHRs, based on identifying stakeholders and systematically eliciting their requirements, and to discuss the key benefits (KBs) and key challenges (KCs) of blockchain technology in the context of EHRs. METHODS The blockchain-based architecture was developed in the framework of the design science research paradigm. The requirements were identified using a structured literature review and interviews with nine health care experts. Subsequently, the proposed architecture was evaluated using 4 workshops with 15 participants. RESULTS We identified three major EHR stakeholder groups and 34 respective requirements. On this basis, we developed a five-layer architecture. The subsequent evaluation of the artifact was followed by the discussion of 12 KBs and 12 KCs of a blockchain-based architecture for EHRs. To address the KCs, we derived five recommendations for action for science and practice. CONCLUSIONS Our findings indicate that blockchain technology offers considerable potential to advance EHRs. Improvements to currently available EHR solutions are expected, for instance, in the areas of data security, traceability, and automation by smart contracts. Future research could examine the patient’s acceptance of blockchain-based EHRs and cost-benefit analyses.

scholarly journals Evaluating the Use of Electronic Health Records for Type 2 Diabetes Surveillance in 2 California Counties, 2010-2014

2017 ◽  
Vol 132 (4) ◽  
pp. 463-470 ◽  
Author(s):  
Maxwell J. Richardson ◽  
Stephen K. Van Den Eeden ◽  
Eric Roberts ◽  
Assiamira Ferrara ◽  
Susan Paulukonis ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Clinical Diagnosis ◽  
Family Income ◽  
Census Data ◽  
Diabetes Prevalence ◽  
Future Research ◽  
Test Results ◽  
Health Records ◽  
Hba1c Test ◽  
Electronic Health

Objectives: Electronic health records (EHRs) and electronic laboratory records (ELRs) are increasingly seen as a rich source of data for performing public health surveillance activities and monitoring community health status. Their potential for surveillance of chronic illness, however, may be underused. Our objectives were to (1) evaluate the use of EHRs and ELRs for diabetes surveillance in 2 California counties and (2) examine disparities in diabetes prevalence by geography, income, and race/ethnicity. Methods: We obtained data on a clinical diagnosis of diabetes and hemoglobin A1c (HbA1c) test results for adult members of Kaiser Permanente Northern California living in Contra Costa County or Solano County at any time during 2010-2014. We evaluated the validity of using HbA1c test results to determine diabetes prevalence, using clinical diagnoses as a gold standard. We estimated disparities in diabetes prevalence by combining HbA1c test results with US Census data on income, race, and ethnicity. Results: When compared with a clinical diagnosis of diabetes, data on a patient’s 5-year maximum HbA1c value ≥6.5% yielded the best combination of sensitivity (87.4%) and specificity (99.2%). The prevalence of 5-year maximum HbA1c ≥6.5% decreased with increasing median family income and increased with greater proportions of residents who were either non-Hispanic black or Hispanic. Conclusions: Timely diabetes surveillance data from ELRs can be used to document disparities, target interventions, and evaluate changes in population health. ELR data may be easier to access than a patient’s entire EHR, but outcome metric validation with diabetes diagnoses would need to be ongoing. Future research should validate ELR and EHR data across multiple providers.

Sign in / Sign up

Export Citation Format

Share Document