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Massachusetts Institute of Technology

Understanding Clinical Pain Management and Patient Experiences of Pain from Electronic Health Records

Abstract

dc:description.abstract

Opioid prescription practices in clinical settings are frequently variable and subjective. Improper usage of prescription opioids is in turn a massive public health issue in the United States. However, lack of pain medication can also lead to patients being unable to perform daily activities due to unmitigated pain. In this thesis, we find that data on opioid prescriptions and self-reported pain reveal differences in how patients of different demographics report pain and in how providers choose to prescribe opioids. We analyze data from two distinct populations, the MIMIC III ICU dataset and records from general medical services at Brigham and Women’s Hospital (BWH). This work is undertaken in collaboration with providers at BWH in Boston. To help quantify and standardize patients’ experiences of pain, we may consider the concept of functional pain — i.e., if the patient is in too much pain to perform basic activities such as turning or walking. This gives rise to the clinical Functional Pain Scale (FPS), which we will endeavor to use retrospectively with clinical notes. We identify and isolate relevant notes and annotate them for relevant spans, and assign an overall functional pain score to each note based on BWH guidelines. Natural Language Processing (NLP) models are then trained to identify these spans and to predict the assigned functional pain score. Through this work, we hope to improve pain management practices, and more broadly, the patient experience.

Degree

thesis:*
Name thesis:degree_name
Master
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2021

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Vaughn, Julie R.
Advisor dc:contributor.advisor
  • Szolovits, Peter

Rights

dc:rights
Statement dc:rights
  • In Copyright - Educational Use Permitted
  • Copyright MIT

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/140086
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/140086

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
related terms
citation

Vaughn, Julie R.. Understanding Clinical Pain Management and Patient Experiences of Pain from Electronic Health Records. Massachusetts Institute of Technology, 2021. https://hdl.handle.net/1721.1/140086