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title{Electronic Health Record (EHR) Software Requirements Compliance with Health Insurance Portability and Accountability Act (HIPPA)}
author{Jeevan Pandey }
date{October 29, 2018}
begin{document}
maketitle
begin{abstract}
Being able to efficiently critique a paper is a necessary skill that every researcher should possess. In this deliverable, I have carefully utilized the three-pass method described in the paper “How to Read a Paper” by S. Keshav to write my critique of a paper. More specifically, I focused on the second pass to make more detailed notes about the figures, tables, and the content clarity of the paper. I also utilized the third pass to get important information related to my critique such as: the study’s contribution to the knowledge, theory, or practice in the field, the research design and methodology used in the study, the study's findings in terms of how they are presented and interpreted, the researcher's conclusions, the content, writing quality, style, and organization of the information in the paper. I have also identified important information related to the paper such as the author's name, publication date and venue, purpose of the study, and the analytical approach or theoretical framework used by the paper. To successfully write my critique, I followed important guidelines from the article titled “Writing a critique or review of a research article" by the University of Calgary. The article is beneficial to anyone who is writing a critique.
end{abstract}
section{Introduction}
The health-care industry relies on Electronic Health Record
(EHR) systems, which are real-time, patient-centered records
that make patient information available instantly and securely
to authorized users textbf{(HealthIT2018EHR)}. EHRs contain information related to a
patient’s medical history, diagnoses, medications, treatment
plans, laboratory and test results, etc., that are accessed by
health-care providers to make decisions about a patient’s care
textbf{HealthIT2018EHR}. Considering the information contained in EHR systems, who gets access to this information is very important in order to protect patient privacy and confidentiality. Hence, the United States congress passed the
Health Insurance Portability and Accountability Act (HIPPA)
in 1996 to protect and handle confidential
health information effectively textbf{California2018EHR}. According to this act, EHR systems need to
comply with all the rules and regulations under HIPPA to
protect patient information. More specifically, the software
requirements for an EHR system need to be in compliance with
the legal obligations outlined in HIPPA §164.312. The legal
obligations outlined in HIPPA §164.312 can be found on textbf{Massey2012Itrust}
To comply with HIPPA regulations, EHR software
companies have compliance teams that make sure that the
software requirements are in compliance with HIPPA
regulations as software engineers are not well-prepared to identify legally compliant software requirements textbf{Massey2012Itrust}. Thus, when working on these EHR software
projects, moving to the next phase of the software development
life cycle is dependent on the approval from the compliance
department which, depending on the complexity of the project,
can be a lengthy process. This wait time is a valuable resource of a
company along with the cost associated with paying employees
in the compliance team that handle the task of matching
software requirements compliance with HIPPA. Thus, there is a need to automate the process of matching EHR software requirements with HIPPA regulations. To identify possible solutions, this research will also explore some popular data mining document similarity algorithms that can help compare these EHR software requirements with the regulations outlined in HIPPA and determine if they are legally compliant for implementation.
section{Background}
There are other studies that have identified the complexity involved in matching EHR software requirements with HIPPA regulations. Massey et al. conducted a study to identify whether EHR software requirements that have met or
exceeded their legal obligations outlined in HIPPA are ready
for legal implementation or not [3]. They examine how
software engineers make this determination using a multi-case
study with three cases [3]. In the first case study, engineering
graduate-level software engineering students assess the
requirements in comparison to obligations outlined in HIPPA
[3]. In the second case study, they use a different set of
participants, and in the third case study, they use a Wideband
Delphi approach to deriving consensus in groups [3]. They then
measure the results against the evaluations of HIPPA
compliance subject matter experts [3]. Their findings indicate
that average graduate-level software engineering students are
ill-prepared to write legally compliant software and that subject
matter experts are an absolute necessity [3].
Studies related to
Wagh et al. have also proposed cosine similarity and
citation based similarity mesures to examine the similarity
between legal documents [4]. They mention the complexity of
the legal domain and emphaisize the importance of retreiving
information from legal documents which is carried out by a
human expert [4]. They use a network based model and
measure network metrix like degree distribution, centrality, and
connected components [4]. According to their findings, citation
based similarity measure is more robust in determining parallel
among cases [4].
Gupta et al. have used a clustering based approach
called similarity index to identify similarity between text
documents [5]. Their alogirthm uses two types of
similarity index and propose a new similarity index. They use
neural networks to calculate metrix like precision, recall,
accuracy, and f-measure [5].
section{Objectives}
section{Methods}
section{Data}
This paper uses data from the ITrust Medical Record
System, an open-source EHR system designed and
implemented by students and faculties at North Carolina State
University. The data contains software requirements from the
ITrust dataset along with the traceability matrix that links the
requirements with their respective HIPPA §164.312
obligations.
section{Execution Plan}
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section{References}
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