ArticleJournal of pain research2019
A narrative review of data collection and analysis guidelines for comparative effectiveness research in chronic pain using patient-reported outcomes and electronic health records.
Article in Journal of pain research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed.
- Hierarchical Clustering Applied to Chronic Pain Drawings Identifies Undiagnosed Fibromyalgia: Implications for Busy Clinical Practice.The journal of pain · 2024Observational
- Utilizing a learning health system to capture real-world patient data: Application of the reliable change index to evaluate and improve the outcome of a pain rehabilitation program.Pain practice : the official journal of World Institute of Pain · 2024Article
- Using Natural Language Processing and Machine Learning to Identify Opioids in Electronic Health Record Data.Journal of pain research · 2023Article
- CHOIRBM: An R package for exploratory data analysis and interactive visualization of pain patient body map data.PLoS computational biology · 2022Article
- Whole Body Pain Distribution and Risk Factors for Widespread Pain Among Patients Presenting with Abdominal Pain: A Retrospective Cohort Study.Pain and therapy · 2022Article
- Determining chronic pain data elements as a first step towards improving quality of care and research in chronic pain.Acta bio-medica : Atenei Parmensis · 2021Article
- A Narrative Review on Perioperative Pain Management Strategies in Enhanced Recovery Pathways-The Past, Present and Future.Journal of clinical medicine · 2021Review
- Article
- Telemedicine for Chronic Pain in the COVID-19 Era and Beyond.Pain medicine (Malden, Mass.) · 2020Review
- Information and communication technology for increasing healthy ageing in people with non-communicable diseases: identifying challenges and further areas for development.Aging clinical and experimental research · 2019Article
- Development and validation of the Collaborative Health Outcomes Information Registry body map.Pain reportsArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chronic pain is a widespread and complex set of conditions that are often difficult and expensive to treat. Comparative effectiveness research (CER) is an evolving research method that is useful in determining which treatments are most effective for medical conditions such as chronic pain. An underutilized mechanism for conducting CER in pain medicine involves combining patient-reported outcomes (PROs) with electronic health records (EHRs). Patient-reported pain and mental and physical health outcomes are increasingly collected during clinic visits, and these data can be linked to EHR data that are relevant to the treatment of a patient's pain, such as diagnoses, medications ordered, and medical comorbidities. When aggregated, this information forms a data repository that can be used for high-quality CER. This review provides a blueprint for conducting CER using PROs combined with EHRs. As an example, the University of Pittsburgh's patient outcomes repository for treatment is described. This system includes PROs collected via the Collaborative Health Outcomes Information Registry software and cross-linked data from the University of Pittsburgh Medical Center EHR. The requirements, best practice guidelines, statistical considerations, and caveats for performing CER with this type of data repository are also discussed.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.