Quantification of Patient-Reported Pain Locations: Development of an Automated Measurement Method.
Patient-reported pain locations are critical for comprehensive pain assessment. Our study aim was to introduce an automated process for measuring the location and distribution of pain collected during a routine outpatient clinic visit. In a cross-sectional study, 116 adults with sickle cell disease–...
| Publicado en: | CIN: Computers, Informatics, Nursing Vol. 41; no. 5; pp. 346 - 356 |
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| Autores principales: | , , , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Lippincott Williams & Wilkins
May2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=163611556&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 163611556 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15382931 KXN jtl: CIN: Computers, Informatics, Nursing issn: 15382931 maglogo: N pubinfo: dt: May2023 vid: 41 iid: 5 pid: 433 pub: Lippincott Williams & Wilkins place: Baltimore, Maryland artinfo: ui: 163611556 163611556 163611556 10.1097/CIN.0000000000000875 163611556 ppf: 346 ppct: 10 formats: tig: atl: Quantification of Patient-Reported Pain Locations: Development of an Automated Measurement Method. aug: au: Abudawood, Khulud Yoon, Saunjoo L. Garg, Rishabh Yao, Yingwei Molokie, Robert E. Wilkie, Diana J. affil: Author Affiliations: College of Nursing, King Saud bin Abdulaziz University for Health Sciences (Dr Abudawood), Jeddah, Saudi Arabia sug: subj: Patient-Reported Outcomes Pain Measurement Illinois Automation Methods Program Development Human Outpatients Secondary Analysis Adult Anemia, Sickle Cell Body Surface Area Algorithms Illinois Drawing Image Processing, Computer Assisted Male Female Adult: 19-44 years Male Female ab: Patient-reported pain locations are critical for comprehensive pain assessment. Our study aim was to introduce an automated process for measuring the location and distribution of pain collected during a routine outpatient clinic visit. In a cross-sectional study, 116 adults with sickle cell disease–associated pain completed PAIN Report ItⓇ. This computer-based instrument includes a two-dimensional, digital body outline on which patients mark their pain location. Using the ImageJ software, we calculated the percentage of the body surface area marked as painful and summarized data with descriptive statistics and a pain frequency map. The painful body areas most frequently marked were the left leg-front (73%), right leg-front (72%), upper back (72%), and lower back (70%). The frequency of pain marks in each of the 48 body segments ranged from 3 to 79 (mean, 33.2 ± 21.9). The mean percentage of painful body surface area per segment was 10.8% ± 7.5% (ranging from 1.3% to 33.1%). Patient-reported pain locations can be easily analyzed from digital drawings using an algorithm created via the free ImageJ software. This method may enhance comprehensive pain assessment, facilitating research and personalized care over time for patients with various pain conditions. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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