Picture This: Presenting Longitudinal Patient-Reported Outcome Research Study Results to Patients

and PRO Data Presentation Stakeholder Advisory Board

Research output: Contribution to journalArticle

Abstract

Background. Patient-reported outcome (PRO) results from clinical trials and research studies can inform patient-clinician decision making. However, data presentation issues specific to PROs, such as scaling directionality (higher scores may represent better or worse outcomes) and scoring strategies (normed v. nonnormed scores), can make the interpretation of PRO scores uniquely challenging. Objective. To identify the association of PRO score directionality, score norming, and other factors on a) how accurately PRO scores are interpreted and b) how clearly they are rated by patients, clinicians, and PRO researchers. Methods. We electronically surveyed adult cancer patients/survivors, oncology clinicians, and PRO researchers and conducted one-on-one cognitive interviews with patients/survivors and clinicians. Participants were randomized to 1 of 3 line graph formats showing longitudinal change: higher scores indicating “better,” “more” (better for function, worse for symptoms), or “normed” to a population average. Quantitative data evaluated interpretation accuracy and clarity. Online survey comments and cognitive interviews were analyzed qualitatively. Results. The Internet sample included 629 patients, 139 clinicians, and 249 researchers; 10 patients and 5 clinicians completed cognitive interviews. “Normed” line graphs were less accurately interpreted than “more” (odds ratio [OR] = 0.76; P = 0.04). “Better” line graphs were more accurately interpreted than both “more” (OR = 1.43; P = 0.01) and “normed” (OR = 1.88; P = 0.04). “Better” line graphs were more likely to be rated clear than “more” (OR = 1.51; P = 0.05). Qualitative data informed interpretation of these findings. Limitations. The survey relied on the online platforms used for distribution and consequent snowball sampling. We do not have information regarding participants’ numeracy/graph literacy. Conclusions. For communicating PROs as line graphs in patient educational materials and decision aids, these results support using graphs, with higher scores consistently indicating better outcomes.

Original languageEnglish (US)
JournalMedical Decision Making
DOIs
StateAccepted/In press - Jan 1 2018

Fingerprint

Outcome Assessment (Health Care)
Odds Ratio
Research Personnel
Interviews
Survivors
Decision Support Techniques
Patient Reported Outcome Measures
Internet
Decision Making
Clinical Trials
Research
Population
Neoplasms
Surveys and Questionnaires

Keywords

  • clinical trials
  • comparative effectiveness research
  • graphic communication
  • knowledge translation
  • patient-reported outcomes

ASJC Scopus subject areas

  • Health Policy

Cite this

Picture This : Presenting Longitudinal Patient-Reported Outcome Research Study Results to Patients. / and PRO Data Presentation Stakeholder Advisory Board.

In: Medical Decision Making, 01.01.2018.

Research output: Contribution to journalArticle

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title = "Picture This: Presenting Longitudinal Patient-Reported Outcome Research Study Results to Patients",
abstract = "Background. Patient-reported outcome (PRO) results from clinical trials and research studies can inform patient-clinician decision making. However, data presentation issues specific to PROs, such as scaling directionality (higher scores may represent better or worse outcomes) and scoring strategies (normed v. nonnormed scores), can make the interpretation of PRO scores uniquely challenging. Objective. To identify the association of PRO score directionality, score norming, and other factors on a) how accurately PRO scores are interpreted and b) how clearly they are rated by patients, clinicians, and PRO researchers. Methods. We electronically surveyed adult cancer patients/survivors, oncology clinicians, and PRO researchers and conducted one-on-one cognitive interviews with patients/survivors and clinicians. Participants were randomized to 1 of 3 line graph formats showing longitudinal change: higher scores indicating “better,” “more” (better for function, worse for symptoms), or “normed” to a population average. Quantitative data evaluated interpretation accuracy and clarity. Online survey comments and cognitive interviews were analyzed qualitatively. Results. The Internet sample included 629 patients, 139 clinicians, and 249 researchers; 10 patients and 5 clinicians completed cognitive interviews. “Normed” line graphs were less accurately interpreted than “more” (odds ratio [OR] = 0.76; P = 0.04). “Better” line graphs were more accurately interpreted than both “more” (OR = 1.43; P = 0.01) and “normed” (OR = 1.88; P = 0.04). “Better” line graphs were more likely to be rated clear than “more” (OR = 1.51; P = 0.05). Qualitative data informed interpretation of these findings. Limitations. The survey relied on the online platforms used for distribution and consequent snowball sampling. We do not have information regarding participants’ numeracy/graph literacy. Conclusions. For communicating PROs as line graphs in patient educational materials and decision aids, these results support using graphs, with higher scores consistently indicating better outcomes.",
keywords = "clinical trials, comparative effectiveness research, graphic communication, knowledge translation, patient-reported outcomes",
author = "{and PRO Data Presentation Stakeholder Advisory Board} and Elliott Tolbert and Michael Brundage and Elissa Bantug and Blackford, {Amanda L.} and Katherine Smith and Claire Snyder",
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AB - Background. Patient-reported outcome (PRO) results from clinical trials and research studies can inform patient-clinician decision making. However, data presentation issues specific to PROs, such as scaling directionality (higher scores may represent better or worse outcomes) and scoring strategies (normed v. nonnormed scores), can make the interpretation of PRO scores uniquely challenging. Objective. To identify the association of PRO score directionality, score norming, and other factors on a) how accurately PRO scores are interpreted and b) how clearly they are rated by patients, clinicians, and PRO researchers. Methods. We electronically surveyed adult cancer patients/survivors, oncology clinicians, and PRO researchers and conducted one-on-one cognitive interviews with patients/survivors and clinicians. Participants were randomized to 1 of 3 line graph formats showing longitudinal change: higher scores indicating “better,” “more” (better for function, worse for symptoms), or “normed” to a population average. Quantitative data evaluated interpretation accuracy and clarity. Online survey comments and cognitive interviews were analyzed qualitatively. Results. The Internet sample included 629 patients, 139 clinicians, and 249 researchers; 10 patients and 5 clinicians completed cognitive interviews. “Normed” line graphs were less accurately interpreted than “more” (odds ratio [OR] = 0.76; P = 0.04). “Better” line graphs were more accurately interpreted than both “more” (OR = 1.43; P = 0.01) and “normed” (OR = 1.88; P = 0.04). “Better” line graphs were more likely to be rated clear than “more” (OR = 1.51; P = 0.05). Qualitative data informed interpretation of these findings. Limitations. The survey relied on the online platforms used for distribution and consequent snowball sampling. We do not have information regarding participants’ numeracy/graph literacy. Conclusions. For communicating PROs as line graphs in patient educational materials and decision aids, these results support using graphs, with higher scores consistently indicating better outcomes.

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