Managing protected health information in distributed research network environments: automated review to facilitate collaboration

BMC Medical Informatics and Decision Making

Research Article

Sandhyasree Padmanabhan¹  Paul Hitz²  Roy Pardee³  Amy Butani⁴  Christine E Bredfeldt⁵ 

[1] C-V Sight, Shrewsbury, MA, USA;Essentia Institute of Rural Health, Duluth, MN, USA;Group Health Research Institute, Seattle, WA, USA;HealthPartners Institute for Education and Research, Bloomington, MN, USA;Mid-Atlantic Permanente Research Institute, Kaiser Permanente in the Mid-Atlantic States, Rockville, MD, USA;

关键词: HIPAA;    Protected health information;    Distributed research;    De-identification;   

DOI  :  10.1186/1472-6947-13-39

 received in 2012-12-07, accepted in 2013-03-14,  发布年份 2013

来源: Springer

【 摘 要 】

BackgroundMulti-site health sciences research is becoming more common, as it enables investigation of rare outcomes and diseases and new healthcare innovations. Multi-site research usually involves the transfer of large amounts of research data between collaborators, which increases the potential for accidental disclosures of protected health information (PHI). Standard protocols for preventing release of PHI are extremely vulnerable to human error, particularly when the shared data sets are large.MethodsTo address this problem, we developed an automated program (SAS macro) to identify possible PHI in research data before it is transferred between research sites. The macro reviews all data in a designated directory to identify suspicious variable names and data patterns. The macro looks for variables that may contain personal identifiers such as medical record numbers and social security numbers. In addition, the macro identifies dates and numbers that may identify people who belong to small groups, who may be identifiable even in the absences of traditional identifiers.ResultsEvaluation of the macro on 100 sample research data sets indicated a recall of 0.98 and precision of 0.81.ConclusionsWhen implemented consistently, the macro has the potential to streamline the PHI review process and significantly reduce accidental PHI disclosures.

【 授权许可】

CC BY   
© Bredfeldt et al.; licensee BioMed Central Ltd. 2013