Anonymizing Health Data: Case Studies and Methods to Get You Started

Anonymizing Health Data: Case Studies and Methods to Get You Started

Luk Arbuckle, Khaled El Eman


This sensible e-book will show confirmed tools for anonymizing well-being facts to assist your company proportion significant datasets, with out exposing sufferer identification. major specialists Khaled El Emam and Luk Arbuckle stroll you thru a risk-based technique, utilizing case experiences from their efforts to de-identify 1000s of datasets.

Clinical facts is efficacious for examine and different kinds of analytics, yet making it nameless with no compromising facts caliber is difficult. This e-book demonstrates suggestions for dealing with assorted information forms, in accordance with the authors’ stories with a maternal-child registry, inpatient discharge abstracts, medical health insurance claims, digital scientific checklist databases, and the area exchange heart catastrophe registry, between others.

comprehend varied tools for operating with cross-sectional and longitudinal datasets
examine the danger of adversaries who try to re-identify sufferers in anonymized datasets
decrease the dimensions and complexity of huge datasets with no wasting key info or jeopardizing privacy
Use easy methods to anonymize unstructured free-form textual content data
reduce the hazards inherent in geospatial info, with out omitting severe location-based health and wellbeing information
examine how one can anonymize coding details in healthiness data
examine the problem of anonymously linking similar datasets

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