Ethical issues in electronic health records: A general overview

Ozair, Fouzia F; Jamshed, Nayer; Sharma, Amit Kumar; Aggarwal, Praveen

doi:10.4103/2229-3485.153997

Cited by 148 publications

(75 citation statements)

References 7 publications

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“…Much attention should be paid to the ethical issues that might arise 67. Security breaches threaten patient privacy when confidential health information is made available to others without the consent of the individual 67. Strict privacy and security policies, supportive technology, and routine random audits are possible solutions 67.…”

Section: Discussionmentioning

confidence: 99%

Chinese health care system and clinical epidemiology

Sun¹,

Gregersen²,

Yuan³

2017

CLEP

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China has gone through a comprehensive health care insurance reform since 2003 and achieved universal health insurance coverage in 2011. The new health care insurance system provides China with a huge opportunity for the development of health care and medical research when its rich medical resources are fully unfolded. In this study, we review the Chinese health care system and its implication for medical research, especially within clinical epidemiology. First, we briefly review the population register system, the distribution of the urban and rural population in China, and the development of the Chinese health care system after 1949. In the following sections, we describe the current Chinese health care delivery system and the current health insurance system. We then focus on the construction of the Chinese health information system as well as several existing registers and research projects on health data. Finally, we discuss the opportunities and challenges of the health care system in regard to clinical epidemiology research. China now has three main insurance schemes. The Urban Employee Basic Medical Insurance (UEBMI) covers urban employees and retired employees. The Urban Residence Basic Medical Insurance (URBMI) covers urban residents, including children, students, elderly people without previous employment, and unemployed people. The New Rural Cooperative Medical Scheme (NRCMS) covers rural residents. The Chinese Government has made efforts to build up health information data, including electronic medical records. The establishment of universal health care insurance with linkage to medical records will provide potentially huge research opportunities in the future. However, constructing a complete register system at a nationwide level is challenging. In the future, China will demand increased capacity of researchers and data managers, in particular within clinical epidemiology, to explore the rich resources.

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Section: Discussionmentioning

confidence: 99%

Chinese health care system and clinical epidemiology

Sun¹,

Gregersen²,

Yuan³

2017

CLEP

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“…Namely, physicians tend to use badly formatted shorthand and non-widespread acronyms ('transport pt to OT tid via W/C' for 'transport patient to occupational therapy three times a day via wheel chair'), while labelled records are scarce (ranging in the hundreds for a given task and with very few annotated samples). A reason for this scarcity is that data access is difficult due to ethical concerns [18][19][20]. Other reason is that, even with data access granted, medical text needs to be annotated by field expert (e.g.…”

Section: Introductionmentioning

confidence: 99%

Named entity recognition in electronic health records using transfer learning bootstrapped Neural Networks

et al. 2020

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Neural networks (NNs) have become the state of the art in many machine learning applications, such as image, sound [1] and natural language processing [2,3]. However, the success of NNs remains dependent on the availability of large labelled datasets, such as in the case of electronic health records (EHRs). With scarce data, NNs are unlikely to be able to extract this hidden information with practical accuracy. In this study, we develop an approach that solves these problems for named entity recognition, obtaining 94.6 F1 score in I2B2 2009 Medical Extraction Challenge [6], 4.3 above the architecture that won the competition. To achieve this, we bootstrap our NN models through transfer learning by pretraining word embeddings on a secondary task performed on a large pool of unannotated EHRs and using the output embeddings as a foundation of a range of NN architectures. Beyond the official I2B2 challenge, we further achieve 82.4 F1 on extracting relationships between medical terms using attention-based seq2seq models bootstrapped in the same manner.

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“…An electronic health record is defined as "a record of a patient's medical details (including history, physical examinations, investigations and treatment) in a digital format" (Ozair, Jamshed, Sharma, & Aggarwal, 2015, p. 73). Many benefits of EHR have been discussed in the literature, including a reduction in lost records, ease of access, better decision-making by clinicians, and a reduction in expense compared with traditional paper files (Fontenot, 2013;Ozair et al, 2015). Fontenot (2013) provided a brief history of medical record keeping, which began with Hippocrates in the 5th century BC, mainly for the purpose of tracking illnesses and their inherent causes.…”

mentioning

confidence: 99%

“…As technology advances, paper files have caused many issues that digital records can now solve, such as illegible handwriting, poor organizational systems, and file security (Fontenot, 2013;Richards, 2009). The need for a set standard of documentation and increased efficiency with the maintenance of records is imperative as the mental health profession advances (Fontenot, 2013;Ozair et al, 2015;Richards, 2009). With the use of an EHR system, clinicians can access files in their office, see notes from previous sessions, and maintain up-to-date diagnoses without having to sort through an unwieldy paper file.…”

mentioning

confidence: 99%

“…Also, the initial investment of financial and human resources to train staff and implement software can be significant and timeconsuming. Finally, a possible impediment could arise when all clinicians do not have a role in the transition process, given that problems can occur when staff members lack a feeling of ownership in the EHR system (Ozair et al, 2015). Other than the disadvantages listed above, there are few documented complications with a transition to digital records.…”

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confidence: 99%

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Clinicians’ Experiences of Transition to Electronic Health Records

Magruder

Adams

Pohto

et al. 2018

J of College Counseling

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Electronic health records (EHR) are becoming a part of college counseling centers. The purpose of this study was to explore the experiences of clinicians (N = 5) who recently underwent the transition from paper files to an EHR system. A grounded theory methodology was used to analyze the interview data, and a member check was conducted to verify the accuracy of the results. Finally, the authors discuss implications for clinicians and offer suggestions to assist with the transition to an EHR system based on the data collected.

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Ethical issues in electronic health records: A general overview

Cited by 148 publications

References 7 publications

Chinese health care system and clinical epidemiology

Chinese health care system and clinical epidemiology

Named entity recognition in electronic health records using transfer learning bootstrapped Neural Networks

Clinicians’ Experiences of Transition to Electronic Health Records

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