Clinical trend discovery and analysis of Taiwanese health insurance claims data
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.
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| Other Authors: | |
| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2016
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| Online Access: | http://hdl.handle.net/1721.1/105967 |
| _version_ | 1826192513386414080 |
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| author | Pillai, Divya P |
| author2 | Peter Szolovits. |
| author_facet | Peter Szolovits. Pillai, Divya P |
| author_sort | Pillai, Divya P |
| collection | MIT |
| description | Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016. |
| first_indexed | 2024-09-23T09:18:06Z |
| format | Thesis |
| id | mit-1721.1/105967 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T09:18:06Z |
| publishDate | 2016 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1059672019-04-10T21:40:15Z Clinical trend discovery and analysis of Taiwanese health insurance claims data Pillai, Divya P Peter Szolovits. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Cataloged from student-submitted PDF version of thesis. Includes bibliographical references (pages 61-62). Data-driven analysis can improve our understanding of medicine, and data from electronic health records and labs has been used successfully in predictive tasks. Less advanced analysis has been done on health insurance claims data, which can be rich and more structured but large in scale. Taiwan has had nationalized health insurance for twenty years; its National Health Research Institute Database (NHIRD) contains records of insurance claims, including medications, prescriptions, and treatment costs for both inpatient and outpatient visits, spanning sixteen years and a million patients. The NHIRD enables longitudinal studies of a patient's medical progression as well as aggregation and generalization to population-level insights. We conducted preliminary exploration of data trends in aggregate, such as diagnosis code frequency and average treatment cost over time. An infrastructure to perform large-scale queries and handle results was required to effectively use the NHIRD for research applications. After indexing database tables to improve query performance, we created a pipeline in Python to connect to and query the database, analyze data for hypothesis discovery and hypothesis testing, convert Taiwanese codes to international standards, and produce plots and graphs. This pipeline was used to examine drug side effects and comorbidities observed across a population, accounting for demographic variables. We also studied patient-specific longitudinal matrices of medical events, which were highly sparse. We attempted quantitative imputation methods to densify these matrices, but because the data was binary (indicating the presence of an event at a given time), categorical, and irregular, advanced imputation offered limited benefit. Nevertheless, we discovered interesting patterns in cohorts of diabetes patients treated with various classes of drugs. This information can be exploited in computational phenotyping and other learning methods, and combined with other data sources it could increase accuracy of clinical predictive tasks. by Divya P. Pillai. M. Eng. 2016-12-22T15:16:48Z 2016-12-22T15:16:48Z 2016 2016 Thesis http://hdl.handle.net/1721.1/105967 965614668 eng 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 62 pages application/pdf a-ch--- Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Pillai, Divya P Clinical trend discovery and analysis of Taiwanese health insurance claims data |
| title | Clinical trend discovery and analysis of Taiwanese health insurance claims data |
| title_full | Clinical trend discovery and analysis of Taiwanese health insurance claims data |
| title_fullStr | Clinical trend discovery and analysis of Taiwanese health insurance claims data |
| title_full_unstemmed | Clinical trend discovery and analysis of Taiwanese health insurance claims data |
| title_short | Clinical trend discovery and analysis of Taiwanese health insurance claims data |
| title_sort | clinical trend discovery and analysis of taiwanese health insurance claims data |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/105967 |
| work_keys_str_mv | AT pillaidivyap clinicaltrenddiscoveryandanalysisoftaiwanesehealthinsuranceclaimsdata |