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Managing changing compliance requirements by predicting regulatory evolution

Authors: Jeremy C. Maxwell; Annie I. Antón; Peter P. Swire;

Managing changing compliance requirements by predicting regulatory evolution

Abstract

Over time, laws change to meet evolving social needs. Requirements engineers that develop software for regulated domains, such as healthcare or finance, must adapt their software as laws change to maintain legal compliance. In the United States, regulatory agencies will almost always release a proposed regulation, or rule, and accept comments from the public. The agency then considers these comments when drafting a final rule that will be binding on the regulated domain. Herein, we examine how these proposed rules evolve into final rules, and propose an Adaptability Framework. This framework can aid software engineers in predicting what areas of a proposed rule are most likely to evolve, allowing engineers to begin building towards the more stable sections of the rule. We develop the framework through a formative study using the Health Insurance Portability and Accountability (HIPAA) Security Rule and apply it in a summative study on the Health Information Technology: Initial Set of Standards, Implementation Specifications, and Certification Criteria for Electronic Health Record Technology.

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Average
Top 10%
Top 10%
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