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Jeff Behrens and Isaac Kohane. Hermann, Julie (Julie Lynn) Harvard University--MIT Division of Health Sciences and Technology. Harvard University--MIT Division of Health Sciences and Technology 2012-01-12T19:30:05Z 2012-01-12T19:30:05Z 2011 2011 http://hdl.handle.net/1721.1/68467 769907237 Thesis (S.M.)--Harvard-MIT Division of Health Sciences and Technology, 2011. Cataloged from PDF version of thesis. Includes bibliographical references (p. 96-98). Understanding the true incidence and prevalence of a disease has tremendous value for the biopharmaceutical industry, particularly for orphan diseases that affect a minority of the population (in the US, the definition of orphan disease is a disorder that must affect less than 200,000 people, or 1 in 1,500). However, incidence and prevalence data for orphan diseases in scientific literature is poorly studied, inconsistent, numbers range widely and articles often contain poorly supported citations. Additionally, once a treatment is available and disease awareness increases, there may be an increase in reported disease prevalence, as patients proactively seek treatment from their healthcare providers. The goal of this research is to investigate the incidence of X-linked Hypohidrotic Ectodermal Dysplasia (XLHED) and provide a framework for investigators to study the incidence and prevalence of other rare diseases. Specific research objectives include: 1) Develop a clinical phenotype to identify XLHED patients in medical records and/or claims data 2) Analyze patient registry data to identify characteristics that are unique to XLHED and distinguish XLHED from other ectodermal dysplasias 3) Develop a robust search algorithm to accurately identify XLHED patients in claims databases By performing a thorough literature review, and an analysis of the National Foundation for Ectodermal Dysplasias (NFED) patient registry, I was able to meet the first two research objectives. After analyzing the medical record and claims data at two major academic medical centers, we were only able to identify 25 total patients, 19 of whom had associated claims data, to include in our patient cohort. Since this number was too small of a base from which to develop an identification algorithm as originally planned, I instead analyzed descriptive statistics of their claims data in order to better understand how these patients flow through the healthcare system, and what identification criteria might be valuable for an investigator studying a larger patient population in the future. Further studies using different combinations of claims and/or narrative data to more accurately identify HED patients and therefore increase the sample size of future analyses are recommended to continue this epidemiological research and provide new insights into the diagnosis and treatment patterns of XLHED. by Julie Hermann. S.M. 98 p. eng Massachusetts Institute of Technology M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 Harvard University--MIT Division of Health Sciences and Technology. Quantifying the patient population of ultra-orphan diseases: a case study in X-Linked Hypohidrotic Ectodermal Dysplasia Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="f428a83f-5da2-400a-8104-ad8739d8805f"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Quantifying the patient population of ultra-orphan diseases: a case study in X-Linked Hypohidrotic Ectodermal Dysplasia</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2011</PublicationDate> <Authors> <Author> <DisplayName>Hermann, Julie (Julie Lynn)</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Harvard University--MIT Division of Health Sciences and Technology.</Keyword> <Abstract>Understanding the true incidence and prevalence of a disease has tremendous value for the biopharmaceutical industry, particularly for orphan diseases that affect a minority of the population (in the US, the definition of orphan disease is a disorder that must affect less than 200,000 people, or 1 in 1,500). However, incidence and prevalence data for orphan diseases in scientific literature is poorly studied, inconsistent, numbers range widely and articles often contain poorly supported citations. Additionally, once a treatment is available and disease awareness increases, there may be an increase in reported disease prevalence, as patients proactively seek treatment from their healthcare providers. The goal of this research is to investigate the incidence of X-linked Hypohidrotic Ectodermal Dysplasia (XLHED) and provide a framework for investigators to study the incidence and prevalence of other rare diseases. Specific research objectives include: 1) Develop a clinical phenotype to identify XLHED patients in medical records and/or claims data 2) Analyze patient registry data to identify characteristics that are unique to XLHED and distinguish XLHED from other ectodermal dysplasias 3) Develop a robust search algorithm to accurately identify XLHED patients in claims databases By performing a thorough literature review, and an analysis of the National Foundation for Ectodermal Dysplasias (NFED) patient registry, I was able to meet the first two research objectives. After analyzing the medical record and claims data at two major academic medical centers, we were only able to identify 25 total patients, 19 of whom had associated claims data, to include in our patient cohort. Since this number was too small of a base from which to develop an identification algorithm as originally planned, I instead analyzed descriptive statistics of their claims data in order to better understand how these patients flow through the healthcare system, and what identification criteria might be valuable for an investigator studying a larger patient population in the future. Further studies using different combinations of claims and/or narrative data to more accurately identify HED patients and therefore increase the sample size of future analyses are recommended to continue this epidemiological research and provide new insights into the diagnosis and treatment patterns of XLHED.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>