scholarly journals A Proposed Electronic Health Record Content Structure Based on Clinical Organizations Survey

2014 ◽  
Vol 15 (13) ◽  
pp. 5233-5246 ◽  
Author(s):  
Dr. Ayman E. Khedr ◽  
Fahad Kamal Alsheref

Computer systems and communication technologies made a strong and influential presence in the different fields of medicine. The cornerstone of a functional medical information system is the Electronic Health Records (EHR) management system. Several electronic health records systems were implemented in different states with different clinical data structures that prevent data exchange between systems even in the same state. This leads to the important barrier in implementing EHR system which is the lack of standards of EHR clinical data structure. In this paper we made a survey on several in international and Egyptian medical organization for implementing electronic health record systems for finding the best electronic health record clinical data structure that contains all patient’s medical data. We proposed an electronic health record system with a standard clinical data structure based on the international and Egyptian medical organization survey and with avoiding the limitations in the other electronic health record that exists in the survey.

2019 ◽  
Vol 1 (2) ◽  
pp. 57-61
Author(s):  
Sangeetha R ◽  
Harshini B ◽  
Shanmugapriya A ◽  
Rajagopal T.K.P.

This paper deals with the Electronic Health Records for storing information of the patient which consist of the medical reports. Electronic Health Records (EHRs) are entirely controlled by Hospitals instead of patients, which complicates seeking medical advices from different hospitals. In the existing system of storing details of the patients are very dependent on the servers of the organization. In the proposed all the information of the patient are stored in the blockchain by using the Metamask and these details are stored in the block chain as a blocks of data. Each block consists of the data which is encrypted data. Electronic Health Record (EHR) systems record health-related information on an individual so that it can be consulted by clinicians or staff for patient care. The data is encrypted by the algorithm known as SHA-256 which is used to encrypt all the data of the patients into a single line 256 bit encrypted text which will be stored in the block at etherscan. These records for not only useful for the consultation but also for creation of historic family health information tree that keeps track of genetic health issues and diseases it can also be used for any health service with the authorization from both the patient and medical organization.


2020 ◽  
pp. 614-628
Author(s):  
Juan C. Lavariega ◽  
Roberto Garza ◽  
Lorena G Gómez ◽  
Victor J. Lara-Diaz ◽  
Manuel J. Silva-Cavazos

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.


2012 ◽  
Vol 03 (01) ◽  
pp. 80-93
Author(s):  
A.B. McCoy ◽  
A. Wright ◽  
D.F. Sittig ◽  
A. Laxmisan

Summary Objective: Clinical summarization, the process by which relevant patient information is electronically summarized and presented at the point of care, is of increasing importance given the increasing volume of clinical data in electronic health record systems (EHRs). There is a paucity of research on electronic clinical summarization, including the capabilities of currently available EHR systems. Methods: We compared different aspects of general clinical summary screens used in twelve different EHR systems using a previously described conceptual model: AORTIS (Aggregation, Organization, Reduction, Interpretation and Synthesis). Results: We found a wide variation in the EHRs’ summarization capabilities: all systems were capable of simple aggregation and organization of limited clinical content, but only one demonstrated an ability to synthesize information from the data. Conclusion: Improvement of the clinical summary screen functionality for currently available EHRs is necessary. Further research should identify strategies and methods for creating easy to use, well-designed clinical summary screens that aggregate, organize and reduce all pertinent patient information as well as provide clinical interpretations and synthesis as required.


2020 ◽  
pp. 249-264
Author(s):  
Juan C. Lavariega ◽  
Roberto Garza ◽  
Lorena G Gómez ◽  
Victor J. Lara-Diaz ◽  
Manuel J. Silva-Cavazos

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.


Author(s):  
Juan C. Lavariega ◽  
Roberto Garza ◽  
Lorena G Gómez ◽  
Victor J. Lara-Diaz ◽  
Manuel J. Silva-Cavazos

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.


2020 ◽  
Author(s):  
Tamadur Shudayfat ◽  
Çağdaş Akyürek ◽  
Noha Al-Shdayfat ◽  
Hatem Alsaqqa

BACKGROUND Acceptance of Electronic Health Record systems is considered an essential factor for an effective implementation among the Healthcare providers. In an attempt to understand the healthcare providers’ perceptions on the Electronic Health Record systems implementation and evaluate the factors influencing healthcare providers’ acceptance of Electronic Health Records, the current research examines the effects of individual (user) context factors, and organizational context factors, using Technology Acceptance Model. OBJECTIVE The current research examines the effects of individual (user) context factors, and organizational context factors, using Technology Acceptance Model. METHODS A quantitative cross-sectional survey design was used, in which 319 healthcare providers from five public hospital participated in the present study. Data was collected using a self-administered questionnaire, which was based on the Technology Acceptance Model. RESULTS Jordanian healthcare providers demonstrated positive perceptions of the usefulness and ease of use of Electronic Health Record systems, and subsequently, they accepted the technology. The results indicated that they had a significant effect on the perceived usefulness and perceived ease of use of Electronic Health Record, which in turn was related to positive attitudes towards Electronic Health Record systems as well as the intention to use them. CONCLUSIONS User attributes, organizational competency, management support and training and education are essential variables in predicting healthcare provider’s acceptance toward Electronic Health records. These findings should be considered by healthcare organizations administration to introduce effective system to other healthcare organizations.


2012 ◽  
Vol 8 (4) ◽  
pp. 219-223 ◽  
Author(s):  
Xinglei Shen ◽  
Adam P. Dicker ◽  
Laura Doyle ◽  
Timothy N. Showalter ◽  
Amy S. Harrison ◽  
...  

Most large academic radiation oncology practices have incorporated electronic health record systems into practice and plan to meet meaningful use requirements. Further work should focus on needs of smaller practices, and specific guidelines may improve widespread adoption.


2020 ◽  
Vol 17 (4) ◽  
pp. 402-404
Author(s):  
Jill Schnall ◽  
LingJiao Zhang ◽  
Jinbo Chen

For utilizing electronic health records to help design and conduct clinical trials, an essential first step is to select eligible patients from electronic health records, that is, electronic health record phenotyping. We present two novel statistical methods that can be used in the context of electronic health record phenotyping. One mitigates the requirement for gold-standard control patients in developing phenotyping algorithms, and the other effectively corrects for bias in downstream analysis introduced by study samples contaminated by ineligible subjects.


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