scholarly journals The Effect of Perceived Expected Satisfaction with Electronic Health Records Availability on Expected Satisfaction with Electronic Health Records Portability in a Multi-Stakeholder Environment

10.28945/3434 ◽  
2016 ◽  
Vol 11 ◽  
pp. 031-053
Author(s):  
Karoly Bozan ◽  
Pratim Datta
Keyword(s):  
Electronic Health Records ◽  
Data Sharing ◽  
International Classification Of Diseases ◽  
Optimal Care ◽  
Health Records ◽  
Patient Health ◽  
Classification Of Diseases ◽  
Electronic Health ◽  
Using Data ◽  
Multi Stakeholder

A central premise for the creation of Electronic Health Records (EHR) is ensuring the portability of patient health records across various clinical, insurance, and regulatory entities. From portability standards such as International Classification of Diseases (ICD) to data sharing across institutions, a lack of portability of health data can jeopardize optimal care and reduce meaningful use. This research empirically investigates the relationship between health records availability and portability. Using data collected from 168 medical providers and patients, we confirm the positive relationship between user perceptions of expected satisfaction with EHR availability and the expected satisfaction with portability. Our findings contribute to more informed practice by understanding how ensuring the availability of patient data by virtue of enhanced data sharing standards, device independence, and better EHR data integration can subsequently drive perceptions of portability across a multitude of stakeholders.

scholarly journals Validation of International Classification of Diseases coding for bone metastases in electronic health records using technology-enabled abstraction

2015 ◽  
pp. 441 ◽  
Author(s):  
Alexander Liede ◽  
Rohini Khorana Hernandez ◽  
Maayan Roth ◽  
Geoffrey Calkins ◽  
Leonardo Nicacio ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Bone Metastases ◽  
International Classification Of Diseases ◽  
International Classification ◽  
Health Records ◽  
Classification Of Diseases ◽  
Electronic Health

Documentation of Child Maltreatment in Electronic Health Records

2017 ◽  
Vol 57 (9) ◽  
pp. 1041-1052 ◽  
Author(s):  
Canan Karatekin ◽  
Brandon Almy ◽  
Susan Marshall Mason ◽  
Iris Borowsky ◽  
Andrew Barnes
Keyword(s):  
Child Maltreatment ◽  
Electronic Health Records ◽  
International Classification Of Diseases ◽  
International Classification ◽  
Self Report ◽  
Protective Services ◽  
Health Records ◽  
Classification Of Diseases ◽  
Electronic Health

International Classification of Diseases codes for child maltreatment can aid surveillance and research, but the extent to which they are used is not well established. We documented prevalence of the use of maltreatment-related codes, examined demographic characteristics of youth assigned these codes, and compared results with previous studies. Data were extracted from electronic health records of 0- to 21-year-olds assigned 1 of 15 maltreatment-related International Classification of Diseases, Ninth Revision, codes who had encounters in a large medical system over a 4-year period. Only 0.02% of approximately 2.5 million youth had a maltreatment-related code, replicating other studies. Results provide a dramatic contrast to much higher rates based on self-report or informant-report and referrals to Child Protective Services. Lack of documentation of maltreatment in electronic health records can lead to missed chances at early intervention, inadequate coordination of health care, insufficient allocation of resources to addressing problems related to maltreatment, and flawed public health data.

scholarly journals The Postencounter Form System: Viewpoint on Efficient Data Collection Within Electronic Health Records (Preprint)

2019 ◽  
Author(s):  
Philip Held ◽  
Randy A Boley ◽  
Walter G Faig ◽  
John A O'Toole ◽  
Imran Desai ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Medical Center ◽  
Health Records ◽  
Clinical Notes ◽  
The Road ◽  
Clinical Encounters ◽  
Efficient Data ◽  
Data Points ◽  
Electronic Health ◽  
Using Data

UNSTRUCTURED Electronic health records (EHRs) offer opportunities for research and improvements in patient care. However, challenges exist in using data from EHRs due to the volume of information existing within clinical notes, which can be labor intensive and costly to transform into usable data with existing strategies. This case report details the collaborative development and implementation of the postencounter form (PEF) system into the EHR at the Road Home Program at Rush University Medical Center in Chicago, IL to address these concerns with limited burden to clinical workflows. The PEF system proved to be an effective tool with over 98% of all clinical encounters including a completed PEF within 5 months of implementation. In addition, the system has generated over 325,188 unique, readily-accessible data points in under 4 years of use. The PEF system has since been deployed to other settings demonstrating that the system may have broader clinical utility.

Early prediction of clinical deterioration using data-driven machine learning modeling of electronic health records

2021 ◽  
Author(s):  
Victor M. Ruiz ◽  
Michael P. Goldsmith ◽  
Lingyun Shi ◽  
Allan F. Simpao ◽  
Jorge A. Gálvez ◽  
...  
Keyword(s):  
Machine Learning ◽  
Electronic Health Records ◽  
Clinical Deterioration ◽  
Data Driven ◽  
Early Prediction ◽  
Health Records ◽  
Electronic Health ◽  
Using Data

Development and validation of various phenotyping algorithms for Diabetes Mellitus using data from electronic health records

2017 ◽  
Vol 152 ◽  
pp. 53-70 ◽  
Author(s):  
Santiago Esteban ◽  
Manuel Rodríguez Tablado ◽  
Francisco E. Peper ◽  
Yamila S. Mahumud ◽  
Ricardo I. Ricci ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Electronic Health Records ◽  
Health Records ◽  
Electronic Health ◽  
Using Data ◽  
Development And Validation

EEMI - An Electronic Health Record for Pediatricians

2020 ◽  
pp. 614-628
Author(s):  
Juan C. Lavariega ◽  
Roberto Garza ◽  
Lorena G Gómez ◽  
Victor J. Lara-Diaz ◽  
Manuel J. Silva-Cavazos
Keyword(s):  
Electronic Health Records ◽  
Electronic Health Record ◽  
Data Sharing ◽  
Medical Records ◽  
Data Exchange ◽  
Data Representation ◽  
Health Record ◽  
Health Records ◽  
Health Area ◽  
Electronic Health

The use of paper health records and handwritten prescriptions are prone to preset errors of misunderstanding instructions or interpretations that derive in affecting patients' health. Electronic Health Records (EHR) systems are useful tools that among other functions can assists physicians' tasks such as finding recommended medicines, their contraindications, and dosage for a given diagnosis, filling prescriptions and support data sharing with other systems. This paper presents EEMI, a Children EHR focused on assisting pediatricians in their daily office practice. EEMI functionality keeps the relationships among diagnosis, treatment, and medications. EEMI also calculates dosages and automatically creates prescriptions which can be personalized by the physician. The system also validates patient allergies. This paper also presents the current use of EHRs in Mexico, the Mexican Norm (NOM-024-SSA3-2010), standards for the development of electronic medical records and its relationships with other standards for data exchange and data representation in the health area.

scholarly journals Identifying clinically important COPD sub-types using data-driven approaches in primary care population based electronic health records

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Maria Pikoula ◽  
Jennifer Kathleen Quint ◽  
Francis Nissen ◽  
Harry Hemingway ◽  
Liam Smeeth ◽  
...  
Keyword(s):  
Primary Care ◽  
Electronic Health Records ◽  
Population Based ◽  
Data Driven ◽  
Health Records ◽  
Primary Care Population ◽  
Electronic Health ◽  
Using Data

scholarly journals Business analysis for a sustainable, multi-stakeholder ecosystem for leveraging the Electronic Health Records for Clinical Research (EHR4CR) platform in Europe

2017 ◽  
Vol 97 ◽  
pp. 341-352 ◽  
Author(s):  
Danielle Dupont ◽  
Ariel Beresniak ◽  
Mats Sundgren ◽  
Andreas Schmidt ◽  
John Ainsworth ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Clinical Research ◽  
Health Records ◽  
Business Analysis ◽  
Electronic Health ◽  
Multi Stakeholder
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