Cancer patients’ understanding of longitudinal EORTC QLQ-C30 scores presented as bar charts

Loth, F; Holzner, Bernhard; Sztankay, Monika; Bliem, Harald R.; Raoufi, S.; Rumpold, Gerhard; Giesinger, Johannes

doi:10.1016/j.pec.2016.08.004

Cited by 7 publications

(29 citation statements)

References 20 publications

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“…For example, McNair et al found accuracy rates ranging from 85% to 98% across six formats in a sample of 192 patients. Others found similar percentages . Interpretation in our study seemed to be most accurate when using a bar chart compared to a line graph, although it should be said that one particular figure using a line graph (ie aggregated PROMs scores over time with results of two treatment options) was also accurately interpreted.…”

Section: Discussionsupporting

confidence: 42%

“…Others found similar percentages. 23,43,44 Interpretation in our study seemed to be most accurate when using a bar chart compared to a line graph, although it should be said that one particular figure using a line graph (ie aggregated PROMs scores over time with results of two treatment options) was also accurately interpreted. Therefore, it seems to depend partly on the type of information presented, which format was associated with better comprehension.…”

Section: Discussion Of Findingsmentioning

confidence: 67%

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Using PROMs during routine medical consultations: The perspectives of people with Parkinson’s disease and their health professionals

Damman

Verbiest

Vonk

et al. 2019

Health Expectations

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BackgroundThe use of patient‐reported outcomes measures (PROMs), such as quality of life or symptoms like pain or fatigue, is increasingly embraced within patient‐centred care and shared decision making.ObjectivesTo investigate: (a) how patients and health professionals think about using PROMs during routine medical consultations; (b) for which purpose(s), patients and health professionals want to use PROMs during those consultations; and (c) how patients interpret PROMs information presented in various formats. People with Parkinson's disease and their health professionals served as case example.MethodsWe performed semi‐structured interviews with patients (N = 13) and professionals (N = 7 neurologists; N = 7 physiotherapists). We also used a survey in which patients (N = 115) were shown six figures displaying different information types. Presentation formats of this information varied (line/bar graphs). Interpretation by patients, perceived usefulness of information, attitude towards using information during routine medical consultations and (hypothetical) decisions were assessed.FindingsPatients and professionals were generally positive about using PROMs during medical consultations. Professionals stressed the opportunity to monitor changes in individual PROMs over time. Patients were primarily positive about aggregated PROMs to make treatment decisions. This information was also most often interpreted correctly, especially when presented through a line graph (90.1% correct). Professionals thought patients should take the initiative in discussing PROMs, whereas patients thought professionals should do so.Conclusion/DiscussionWhen used in routine medical consultations, PROMs seem to have potential to support shared decision making and facilitate patient‐professional communication. However, training seems needed for both patients and professionals to facilitate actual discussion and proper interpretation.

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Section: Discussionsupporting

confidence: 42%

Section: Discussion Of Findingsmentioning

confidence: 67%

Using PROMs during routine medical consultations: The perspectives of people with Parkinson’s disease and their health professionals

Damman

Verbiest

Vonk

et al. 2019

Health Expectations

View full text Add to dashboard Cite

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“…Development of thresholds for PRO measures has been recommended in the literature because the interpretation of scores on abstract metrics has been identified as one of the major barriers to the use of PRO measures in daily clinical practice [30]. The TCIs for the EORTC CAT Core can be integrated into software used for routine PRO monitoring to improve graphical presentation of PRO results (e.g., use of color-coding or reference lines [31,32]). In addition, TCIs make PRO scores more actionable and support the linking of PRO results to clinical decision-making [33,34].…”

Section: Discussionmentioning

confidence: 99%

Thresholds for clinical importance were defined for the European Organisation for Research and Treatment of Cancer Computer Adaptive Testing Core—an adaptive measure of core quality of life domains in oncology clinical practice and research

Giesinger

Loth

Aaronson

et al. 2020

Journal of Clinical Epidemiology

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The aim of this article was to establish thresholds for clinical importance (TCIs) for the European Organisation for Research and Treatment of Cancer (EORTC) Computer Adaptive Testing (CAT) Core measure, the new adaptive version of the EORTC QLQ-C30. Study Design and Setting: For our diagnostic study, we recruited cancer patients with mixed diagnoses and treatments from six European countries. Patients completed the EORTC CAT Core and a questionnaire with anchor items assessing criteria for clinical importance (limitations in everyday life, need for help/care, and worries by the patient/family/partner) for each EORTC CAT Core domain. We used a binary variable summarizing the anchor items for determining TCIs and for calculating the area under the curve (AUC) in receiving operator characteristic analysis as a measure of diagnostic accuracy. Results: Using data from 498 cancer patients (mean age 60.4 years, 55.2% women), we established TCIs for the 14 domains of the EORTC CAT Core. Median AUC across domains was 0.93 (range 0.84e0.94). Median sensitivity and specificity of the TCIs were 0.91 (range 0.80e0.96) and 0.77 (range 0.66e0.84), respectively. TCIs and AUCs were largely consistent across patient groups. Conclusion: We have generated TCIs for the 14 functional health and symptom domains of the EORTC CAT Core. The EORTC CAT Core showed high diagnostic accuracy in identifying clinically important symptoms and functional impairments.

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“…Of 18 studies that met our inclusion criteria (Figure 1), 9 used mixed methods, [43][44][45][46][47][48][49][50][51] 7 used quantitative descriptive methods, [52][53][54][55][56][57][58] 1 used qualitative methods, 59 and 1 used a quantitative randomized controlled design 60 (Table 1). Ten of 18 studies met all MMAT criteria (Supplementary Table S2).…”

Section: Resultsmentioning

confidence: 99%

“…Study participants included patients (n ¼ 9), 43,45,46,48,49,51,54,56,58 providers (n ¼ 4), 44,50,55,60 or both (n ¼ 5) 47,52,53,57,59 (Table 1). Sample sizes were 10 to 548 patients and 3 to 233 providers.…”

Section: Study and Symptom Characteristicsmentioning

confidence: 99%

Information visualizations of symptom information for patients and providers: a systematic review

Lor

Koleck

Bakken

2018

Journal of the American Medical Informatics Association

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Objective To systematically synthesize the literature on information visualizations of symptoms included as National Institute of Nursing Research common data elements and designed for use by patients and/or healthcare providers. Methods We searched CINAHL, Engineering Village, PsycINFO, PubMed, ACM Digital Library, and IEEE Explore Digital Library to identify peer-reviewed studies published between 2007 and 2017. We evaluated the studies using the Mixed Methods Appraisal Tool (MMAT) and a visualization quality score, and organized evaluation findings according to the Health Information Technology Usability Evaluation Model. Results Eighteen studies met inclusion criteria. Ten of these addressed all MMAT items; 13 addressed all visualization quality items. Symptom visualizations focused on pain, fatigue, and sleep and were represented as graphs (n = 14), icons (n = 4), and virtual body maps (n = 2). Studies evaluated perceived ease of use (n = 13), perceived usefulness (n = 12), efficiency (n = 9), effectiveness (n = 5), preference (n = 6), and intent to use (n = 3). Few studies reported race/ethnicity or education level. Conclusion The small number of studies for each type of information visualization limit generalizable conclusions about optimal visualization approaches. User-centered participatory approaches for information visualization design and more sophisticated evaluation designs are needed to assess which visualization elements work best for which populations in which contexts.

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Cancer patients’ understanding of longitudinal EORTC QLQ-C30 scores presented as bar charts

Abstract: Knowledge about patients' understanding of graphically displayed QOL results contributes to creation of optimal evidence-based feedback on the patients' present QOL and its trajectory.

Cited by 7 publications

References 20 publications

Using PROMs during routine medical consultations: The perspectives of people with Parkinson’s disease and their health professionals

Using PROMs during routine medical consultations: The perspectives of people with Parkinson’s disease and their health professionals

Thresholds for clinical importance were defined for the European Organisation for Research and Treatment of Cancer Computer Adaptive Testing Core—an adaptive measure of core quality of life domains in oncology clinical practice and research

Information visualizations of symptom information for patients and providers: a systematic review

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