NDLI: Patient-reported outcomes in a large community-based pain medicine practice: evaluation for use in phenotype modeling

Content Provider	Springer Nature : BioMed Central
Author	Juckett, David A. Davis, Fred N. Gostine, Mark Reed, Philip Risko, Rebecca
Abstract	Background An academic, community medicine partnership was established to build a phenotype-to-outcome model targeting chronic pain. This model will be used to drive clinical decision support for pain medicine in the community setting. The first step in this effort is an examination of the electronic health records (EHR) from clinics that treat chronic pain. The biopsychosocial components provided by both patients and care providers must be of sufficient scope to populate the spectrum of patient types, treatment modalities, and possible outcomes. Methods The patient health records from a large Midwest pain medicine practice (Michigan Pain Consultants, PC) contains physician notes, administrative codes, and patient-reported outcomes (PRO) on over 30,000 patients during the study period spanning 2010 to mid-2014. The PRO consists of a regularly administered Pain Health Assessment (PHA), a biopsychosocial, demographic, and symptomology questionnaire containing 163 items, which is completed approximately every six months with a compliance rate of over 95 %. The biopsychosocial items (74 items with Likert scales of 0–10) were examined by exploratory factor analysis and descriptive statistics to determine the number of independent constructs available for phenotypes and outcomes. Pain outcomes were examined both in the aggregate and the mean of longitudinal changes in each patient. Results Exploratory factor analysis of the intake PHA revealed 15 orthogonal factors representing pain levels; physical, social, and emotional functions; the effects of pain on these functions; vitality and health; and measures of outcomes and satisfaction. Seven items were independent of the factors, offering unique information. As an exemplar of outcomes from the follow-up PHAs, patients reported approximately 60 % relief in their pain. When examined in the aggregate, patients showed both a decrease in pain levels and an increase in coping skills with an increased number of visits. When examined individually, 80-85 % of patients presenting with the highest pain levels reported improvement by approximately two points on an 11-point pain scale. Conclusions We conclude that the data available in a community practice can be a rich source of biopsychosocial information relevant to the phenotypes of chronic pain. It is anticipated that phenotype linkages to best treatments and outcomes can be constructed from this set of records.
Related Links	https://bmcmedinformdecismak.biomedcentral.com/counter/pdf/10.1186/s12911-015-0164-4.pdf
Ending Page	14
Page Count	14
Starting Page	1
File Format	HTM / HTML
ISSN	14726947
DOI	10.1186/s12911-015-0164-4
Journal	BMC Medical Informatics and Decision Making
Issue Number	1
Volume Number	15
Language	English
Publisher	BioMed Central
Publisher Date	2015-05-28
Access Restriction	Open
Subject Keyword	Health Informatics Information Systems and Communication Service Management of Computing and Information Systems Chronic pain Patient-reported outcomes Factor analysis Pain severity
Content Type	Text
Resource Type	Article
Subject	Health Informatics Computer Science Applications Health Policy
Journal Impact Factor	3.3/2023
5-Year Journal Impact Factor	3.9/2023

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Patient-reported outcomes in a large community-based pain medicine practice: evaluation for use in phenotype modeling

Common patient-reported outcomes across ICHOM Standard Sets: the potential contribution of PROMIS®

Exploratory application of machine learning methods on patient reported data in the development of supervised models for predicting outcomes

WeChat assisted electronic symptom measurement for patients with adenomyosis

Patient-centered medicine and patient-oriented research: improving health outcomes for individual patients

Patient question set proliferation: scope and informatics challenges of patient question set management in a large multispecialty practice with case examples pertaining to tobacco use, menopause, and Urology and Orthopedics specialties

The Computer-based Health Evaluation Software (CHES): a software for electronic patient-reported outcome monitoring

Mobile applications for pain management: an app analysis for clinical usage

Improving patient-provider communication about chronic pain: development and feasibility testing of a shared decision-making tool

Patient-reported outcomes in a large community-based pain medicine practice: evaluation for use in phenotype modeling

Similar Documents

Patient-reported outcomes in a large community-based pain medicine practice: evaluation for use in phenotype modeling

Common patient-reported outcomes across ICHOM Standard Sets: the potential contribution of PROMIS®

Exploratory application of machine learning methods on patient reported data in the development of supervised models for predicting outcomes

WeChat assisted electronic symptom measurement for patients with adenomyosis

Patient-centered medicine and patient-oriented research: improving health outcomes for individual patients

Patient question set proliferation: scope and informatics challenges of patient question set management in a large multispecialty practice with case examples pertaining to tobacco use, menopause, and Urology and Orthopedics specialties

The Computer-based Health Evaluation Software (CHES): a software for electronic patient-reported outcome monitoring

Mobile applications for pain management: an app analysis for clinical usage

Improving patient-provider communication about chronic pain: development and feasibility testing of a shared decision-making tool

Patient-reported outcomes in a large community-based pain medicine practice: evaluation for use in phenotype modeling