scholarly journals Improving data sharing between acute hospitals in England: an overview of health record system distribution and retrospective observational analysis of inter-hospital transitions of care

BMJ Open ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. e031637
Author(s):  
Leigh R Warren ◽  
Jonathan Clarke ◽  
Sonal Arora ◽  
Ara Darzi
Keyword(s):  
Spatial Distribution ◽  
Data Sharing ◽  
Acute Hospital ◽  
Transitions Of Care ◽  
Secondary Outcome ◽  
Health Record ◽  
Hospital Data ◽  
Record System ◽  
Frequency Of Use ◽  
Electronic Health

ObjectivesTo determine the frequency of use and spatial distribution of health record systems in the English National Health Service (NHS). To quantify transitions of care between acute hospital trusts and health record systems to guide improvements to data sharing and interoperability.DesignRetrospective observational study using Hospital Episode Statistics.SettingAcute hospital trusts in the NHS in England.ParticipantsAll adult patients resident in England that had one or more inpatient, outpatient or accident and emergency encounters at acute NHS hospital trusts between April 2017 and April 2018.Primary and secondary outcome measuresFrequency of use and spatial distribution of health record systems. Frequency and spatial distribution of transitions of care between hospital trusts and health record systems.Results21 286 873 patients were involved in 121 351 837 encounters at 152 included trusts. 117 (77.0%) hospital trusts were using electronic health records (EHR). There was limited regional alignment of EHR systems. On 11 017 767 (9.1%) occasions, patients attended a hospital using a different health record system to their previous hospital attendance. 15 736 863 (73.9%) patients had two or more encounters with the included trusts and 3 931 255 (25.0%) of those attended two or more trusts. Over half (53.6%) of these patients had encounters shared between just 20 pairs of hospitals. Only two of these pairs of trusts used the same EHR system.ConclusionsEach year, millions of patients in England attend two or more different hospital trusts. Most of the pairs of trusts that commonly share patients do not use the same record systems. This research highlights significant barriers to inter-hospital data sharing and interoperability. Findings from this study can be used to improve electronic health record system coordination and develop targeted approaches to improve interoperability. The methods used in this study could be used in other healthcare systems that face the same interoperability challenges.

scholarly journals Decentralized Electronic Health Record System

2020 ◽  
Vol 15 (1) ◽  
pp. 77-80
Author(s):  
Ajaya Mandal ◽  
Prakriti Dumaru ◽  
Sagar Bhandari ◽  
Shreeti Shrestha ◽  
Subarna Shakya
Keyword(s):  
Electronic Health Record ◽  
Data Sharing ◽  
Medical Records ◽  
Data Privacy ◽  
Electronic Health Record System ◽  
Health Record ◽  
Smart Contracts ◽  
Record System ◽  
Block Chain ◽  
Electronic Health

 With a view to overcome the shortcomings of traditional Electronic Health Record (EHR) system so as to assure the interoperability by providing open access to sensitive health data, while still preserving personal data privacy, anonymity and avoiding data misuse, Decentralized Electronic Health Record System was developed. The aforementioned issue concerning traditional EHR system can be addressed by implication of emerging technology of the era namely Block chain, together with Inter Planetary File System (IPFS) which enables data sharing in decentralized and transactional fashion, thereby maintaining delicate balance between privacy and accessibility of electronic health records. A block chain based EHR system has been built for secure, efficient and interoperable access to medical records by both patients and doctors while preserving privacy of the sensitive patient’s information. Patients can easily and comprehensively access to their medical records across providers and treatment sites using unique properties of block chain and decentralized storage. A separate portal for both the patients and doctors has been built enabling the smart contracts to handle further interaction between doctors and patients. So, in this system, it is demonstrated how principles of decentralization and block chain architectures could contribute to EHR system using Ethereum smart contracts and IPFS to orchestrate a suitable system governing the medical record access while providing patients with comprehensive record review along with consideration for audit ability and data sharing.

Why Do Physicians Reject the Electronic Health Record: A Theoretical Perspective? (Preprint)

2018 ◽  
Author(s):  
Weam Alfayez ◽  
Arwa Alumran ◽  
Dr Saja A. Al-Rayes
Keyword(s):  
Information Technology ◽  
Electronic Health Record ◽  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Health Record ◽  
Record System ◽  
Factors Influencing ◽  
Tam Model ◽  
Electronic Health ◽  
Acceptance Model

BACKGROUND Many theories/ models adopted from behavioral sciences literature or developed within the field of information technologies could help in understanding the technology acceptance, usage, and effective adoption. OBJECTIVE The main aim of this paper is to review the different theories/ models that can help in understanding information technology/system acceptance and use, and to choose the most appropriate theoretical framework that could be applied to understand the factors influencing physicians’ use of the Electronic Health Record system (EHR) at King Fahd Military Medical Complex (KFMMC) in Dhahran city, Saudi Arabia. METHODS The theories/ models were reviewed using scientific databases. The inclusion criteria were if the theories/ models used to explain individual behaviors toward accepting and using of information technology including the once conducted within the healthcare. RESULTS The review showed that there were five theories/ models were used within information technology studies to understand the technology acceptance and used. There were Theory of Reasoned Action, Theory of Planned Behaviour, Innovation Diffusion Theory, Unified theory of acceptance and use of technology, and Technology Acceptance Model. Each has different explanatory power of technology use. The most appropriate theoretical framework to understand the reason behind physician use of the EHR at KFMMC would be the Technology Acceptance Model (TAM). TAM model could explain up to 75% of the variation in the behavioral intention (acceptance), and up to 62% of the variation in the actual use. It is the gold standard for assessing the usage of health technologies and systems. In fact, the TAM model is one of the core models used to explore the physician’s perceptions of the Electronic Health Record system adoption. CONCLUSIONS This review showed that there are different theories available in the literature can be used to justify the reason behind electronic health record acceptance. TAM is one of the effective, simplest models used to understand the factors influencing physicians to use the EHR-system. Further studies need to apply the TAM model to check its ability in explaining the reason behind EHR within different hospitals in Saudi Arabia

scholarly journals Developing Clinical Decision Support within a Commercial Electronic Health Record System to Improve Antimicrobial Prescribing in the Neonatal ICU

2014 ◽  
Vol 05 (02) ◽  
pp. 368-387 ◽  
Author(s):  
K. Cato ◽  
B. Sheehan ◽  
S. Patel ◽  
J. Duchon ◽  
P. DeLaMora ◽  
...  
Keyword(s):  
Decision Support ◽  
Electronic Health Record ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Electronic Health Record System ◽  
Health Record ◽  
Record System ◽  
Antimicrobial Prescribing ◽  
Neonatal Icu ◽  
Electronic Health

SummaryObjective: To develop and implement a clinical decision support (CDS) tool to improve antibiotic prescribing in neonatal intensive care units (NICUs) and to evaluate user acceptance of the CDS tool.Methods: Following sociotechnical analysis of NICU prescribing processes, a CDS tool for empiric and targeted antimicrobial therapy for healthcare-associated infections (HAIs) was developed and incorporated into a commercial electronic health record (EHR) in two NICUs. User logs were reviewed and NICU prescribers were surveyed for their perceptions of the CDS tool.Results: The CDS tool aggregated selected laboratory results, including culture results, to make treatment recommendations for common clinical scenarios. From July 2010 to May 2012, 1,303 CDS activations for 452 patients occurred representing 22% of patients prescribed antibiotics during this period. While NICU clinicians viewed two culture results per tool activation, prescribing recommendations were viewed during only 15% of activations. Most (63%) survey respondents were aware of the CDS tool, but fewer (37%) used it during their most recent NICU rotation. Respondents considered the most useful features to be summarized culture results (43%) and antibiotic recommendations (48%).Discussion: During the study period, the CDS tool functionality was hindered by EHR upgrades, implementation of a new laboratory information system, and changes to antimicrobial testing methodologies. Loss of functionality may have reduced viewing antibiotic recommendations. In contrast, viewing culture results was frequently performed, likely because this feature was perceived as useful and functionality was preserved.Conclusion: To improve CDS tool visibility and usefulness, we recommend early user and information technology team involvement which would facilitate use and mitigate implementation challenges.Citation: Hum RS, Cato K, Sheehan B, Patel S, Duchon J, DeLaMora P, Ferng YH, Graham P, Vawdrey DK, Perlman J, Larson E, Saiman L. Developing clinical decision support within a commercial electronic health record system to improve antimicrobial prescribing in the neonatal ICU. Appl Clin Inf 2014; 5: 368–387 http://dx.doi.org/10.4338/ACI-2013-09-RA-0069

Implementation and evaluation of Stanford Health Care store-and-forward teledermatology consultation workflow built within an existing electronic health record system

2018 ◽  
Vol 26 (3) ◽  
pp. 125-131 ◽  
Author(s):  
Grace E Kim ◽  
Olga K Afanasiev ◽  
Chris O’Dell ◽  
Christopher Sharp ◽  
Justin M Ko
Keyword(s):  
Health Care ◽  
Electronic Health Record ◽  
Primary Care Physicians ◽  
Health Record ◽  
Record System ◽  
Privacy Concerns ◽  
Successful Model ◽  
Dermatology Clinic ◽  
Electronic Health ◽  
Store And Forward

Introduction Teledermatology services that function separately from patients’ primary electronic health record (EHR) can lead to fragmented care, poor provider communication, privacy concerns and billing challenges. This study addresses these challenges by developing PhotoCareMD, a store-and-forward (SAF) teledermatology consultation workflow built entirely within an existing Epic-based EHR. Methods Thirty-six primary care physicians (PCPs) from eight outpatient clinics submitted 215 electronic consults (eConsults) for 211 patients to a Stanford Health Care dermatologist via PhotoCareMD. Comparisons were made with in-person referrals for this same dermatologist prior to initiation of PhotoCareMD. Results Compared to traditional in-person dermatology clinic visits, eConsults decreased the time to diagnosis and treatment from 23 days to 16 hours. The majority (73%) of eConsults were resolved electronically. In-person referrals from PhotoCareMD (27%) had a 50% lower cancellation rate compared with traditional referrals (11% versus 22%). The average in-person visit and documentation was 25 minutes compared with 8 minutes for an eConsult. PhotoCareMD saved 13 additional clinic hours to be made available to the dermatologist over the course of the pilot. At four patients per hour, this opens 52 dermatology clinic slots. Over 96% of patients had a favourable experience and 95% felt this service saved them time. Among PCPs, 100% would recommend PhotoCareMD to their colleagues and 95% said PhotoCareMD was a helpful educational tool. Discussion An internal SAF teledermatology workflow can be effectively implemented to increase access to and quality of dermatologic care. Our workflow can serve as a successful model for other hospitals and specialties.

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