Protected Health Information De-Identification on Visual and Textual Features using Transfer Learning

2020 ◽  
Author(s):  
Munipalle Sai Nikhila ◽  
Vinay Kornapalli ◽  
Pradeep Singh
Keyword(s):  
Health Information ◽  
Transfer Learning ◽  
Protected Health Information ◽  
Textual Features

scholarly journals Filtered BERT: Similarity Filter-Based Augmentation with Bidirectional Transfer Learning for Protected Health Information Prediction in Clinical Documents

2021 ◽  
Vol 11 (8) ◽  
pp. 3668
Author(s):  
Min Kang ◽  
Kye Hwa Lee ◽  
Youngho Lee
Keyword(s):  
Health Information ◽  
Transfer Learning ◽  
Data Augmentation ◽  
Protected Health Information ◽  
Limited Data ◽  
Secondary Use ◽  
Data Environment

For the secondary use of clinical documents, it is necessary to de-identify protected health information (PHI) in documents. However, the difficulty lies in the fact that there are few publicly annotated PHI documents. To solve this problem, in this study, we propose a filtered bidirectional encoder representation from transformers (BERT)-based method that predicts a masked word and validates the word again through a similarity filter to construct augmented sentences. The proposed method effectively performs data augmentation. The results show that the augmentation method based on filtered BERT improved the performance of the model. This suggests that our method can effectively improve the performance of the model in the limited data environment.

scholarly journals A DICOM dataset for evaluation of medical image de-identification

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Michael Rutherford ◽  
Seong K. Mun ◽  
Betty Levine ◽  
William Bennett ◽  
Kirk Smith ◽  
...  
Keyword(s):  
Health Information ◽  
National Cancer Institute ◽  
Medical Image ◽  
Cancer Imaging ◽  
Protected Health Information ◽  
Dicom Standard ◽  
Clinical Imaging ◽  
X Ray ◽  
Evaluation Dataset ◽  
Data Elements

AbstractWe developed a DICOM dataset that can be used to evaluate the performance of de-identification algorithms. DICOM objects (a total of 1,693 CT, MRI, PET, and digital X-ray images) were selected from datasets published in the Cancer Imaging Archive (TCIA). Synthetic Protected Health Information (PHI) was generated and inserted into selected DICOM Attributes to mimic typical clinical imaging exams. The DICOM Standard and TCIA curation audit logs guided the insertion of synthetic PHI into standard and non-standard DICOM data elements. A TCIA curation team tested the utility of the evaluation dataset. With this publication, the evaluation dataset (containing synthetic PHI) and de-identified evaluation dataset (the result of TCIA curation) are released on TCIA in advance of a competition, sponsored by the National Cancer Institute (NCI), for algorithmic de-identification of medical image datasets. The competition will use a much larger evaluation dataset constructed in the same manner. This paper describes the creation of the evaluation datasets and guidelines for their use.

scholarly journals Robust Security for Health Information by ECC with Signature Hash Function in WBAN

2018 ◽  
Vol 11 (1) ◽  
pp. 256
Author(s):  
G. Sridevi Devasena ◽  
S. Kanmani
Keyword(s):  
Health Information ◽  
Key Management ◽  
Hash Function ◽  
Data Communication ◽  
Public Key Cryptography ◽  
Protected Health Information ◽  
Body Area ◽  
Efficient Data ◽  
Body Parameters ◽  
Secure Transmission

<p>Wireless Body Area Networks (WBANs) are fundamental technology in health care that permits the information of a patient’s essential body parameters to be gathered by the sensors. However, the safety and concealment defense of the gathered information is a key uncertain problem. A Hybrid Key Management (HKM) scheme [13] is worked based on Public Key Cryptography (PKC)-authentication scheme. This scheme uses a oneway hash function to construct a Merkle Tree. The PKC method increase the computational complexity and lacking scalability. Additionally, it increases expensive computation, communication costs and delay. To overcome this problem, Robust Security for Protected Health Information by ECC with signature Hash Function in WBAN (RSP) is proposed. The system employs hash-chain based key signature technique to achieve efficient, secure transmission from sensor to user in WBAN. Moreover, Elliptical Curve Cryptography algorithm is used to verifies the authenticate sensor. In addition, it describes the experimental results of the proposed system demonstrate the efficient data communication in a network.</p>

Maturing an Information Technology Privacy Program

2020 ◽  
pp. 125-143
Author(s):  
Mike Gregory ◽  
Cynthia Roberts
Keyword(s):  
Information Technology ◽  
Health Insurance ◽  
Health Information ◽  
Maturity Model ◽  
Protected Health Information ◽  
Healthcare Organizations ◽  
Privacy And Security ◽  
Security Standards ◽  
Financial Transactions ◽  
Administrative Simplification

The Health Insurance Portability and Accountability Act of 1996 (HIPAA) was initially enacted as an administrative simplification to standardize electronic transmission of common administrative and financial transactions. The program also calls for implementation specifications regarding privacy and security standards to protect the confidentiality and integrity of individually identifiable health information or protected health information. The Affordable Care Act further expanded many of the protective provisions set forth by HIPAA. Since its implementation, healthcare organizations around the nation have invested billions of dollars and have cycled through numerous program attempts aimed at meeting these standards. This chapter reviews the process taken by one organization to review the privacy policy in place utilizing a maturity model, identify deficiencies, and lead change in order to heighten the maturity of the system. The authors conclude with reflection related to effectiveness of the process as well as implications for practice.

Security

2011 ◽  
pp. 228-273
Author(s):  
Roy Rada
Keyword(s):  
United States ◽  
Health Information ◽  
The United States ◽  
Protected Health Information ◽  
Security Measures ◽  
Privacy And Security ◽  
Privacy Rule ◽  
Global Concern ◽  
Covered Entity ◽  
Security Rule

Privacy and security of health information is a global concern. However, this chapter will focus on approaches to security in the United States. In particular, the federal regulation of security in the form of the Security Rule will be studied. The HIPAA Security Rule details the system and administrative requirements that a covered entity must meet in order to assure that health information is safe from people without authorization for its access. By contrast, the Privacy Rule describes the requirements that govern the circumstances under which protected health information must be used or disclosed with and without patient involvement and when a patient may have access to his or her protected health information. The implementation of reasonable and appropriate security measures supports compliance with the Privacy Rule.

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