Visual analogies, not graphs, increase patients' comprehension of changes in their health status

 OBJECTIVES Patients increasingly use patient-reported outcomes (PROs) to self-monitor their health status. Visualizing PROs longitudinally (over time) could help patients interpret and contextualize their PROs. The study sought to assess hospitalized patients' objective comprehension (primary outcome) of text-only, non-graph, and graph visualizations that display longitudinal PROs. MATERIALS AND METHODS We conducted a clinical research study in 40 hospitalized patients comparing 4 visualization conditions: (1) text-only, (2) text plus visual analogy, (3) text plus number line, and (4) text plus line graph. Each participant viewed every condition, and we used counterbalancing (systematic randomization) to control for potential order effects. We assessed objective comprehension using the International Organization for Standardization protocol. Secondary outcomes included response times, preferences, risk perceptions, and behavioral intentions. RESULTS Overall, 63% correctly comprehended the text-only condition and 60% comprehended the line graph condition, compared with 83% for the visual analogy and 70% for the number line (P = .05) conditions. Participants comprehended the visual analogy significantly better than the text-only (P = .02) and line graph (P = .02) conditions. Of participants who comprehended at least 1 condition, 14% preferred a condition that they did not comprehend. Low comprehension was associated with worse cognition (P < .001), lower education level (P = .02), and fewer financial resources (P = .03). CONCLUSIONS The results support using visual analogies rather than text to display longitudinal PROs but caution against relying on graphs, which is consistent with the known high prevalence of inadequate graph literacy. The discrepancies between comprehension and preferences suggest factors other than comprehension influence preferences, and that future researchers should assess comprehension rather than preferences to guide presentation decisions.

[1]  Steven K. Feiner,et al.  Engaging hospitalized patients in clinical care: Study protocol for a pragmatic randomized controlled trial. , 2016, Contemporary clinical trials.

[2]  P. Ubel,et al.  Communicating side effect risks in a tamoxifen prophylaxis decision aid: the debiasing influence of pictographs. , 2008, Patient education and counseling.

[3]  Lisa M. Schwartz,et al.  The Role of Numeracy in Understanding the Benefit of Screening Mammography , 1997, Annals of Internal Medicine.

[4]  Hadi Kharrazi,et al.  Measure once, cut twice d adding patient-reported outcome measures to the electronic health record for comparative effectiveness research , 2013 .

[5]  Jessica S. Ancker,et al.  The Practice of Informatics: Design Features of Graphs in Health Risk Communication: A Systematic Review , 2006, J. Am. Medical Informatics Assoc..

[6]  Angela Fagerlin,et al.  Improving understanding of adjuvant therapy options by using simpler risk graphics , 2008, Cancer.

[7]  S. Kripalani,et al.  Validation of a Short, 3-Item Version of the Subjective Numeracy Scale , 2015, Medical decision making : an international journal of the Society for Medical Decision Making.

[8]  T. Marteau,et al.  Perceived effectiveness of stop smoking interventions: impact of presenting evidence using numbers, visual displays, and different timeframes. , 2012, Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco.

[9]  M. Rotondo,et al.  The Cost of Patient-Reported Outcomes in Medicine , 2018 .

[10]  Chris North,et al.  Information Visualization , 2008, Lecture Notes in Computer Science.

[11]  Lisa V. Grossman,et al.  Measuring health status and symptom burden using a web-based mHealth application in patients with heart failure , 2019, European journal of cardiovascular nursing : journal of the Working Group on Cardiovascular Nursing of the European Society of Cardiology.

[12]  Michael Siegrist,et al.  The Effect of Graphical and Numerical Presentation of Hypothetical Prenatal Diagnosis Results on Risk Perception , 2008, Medical decision making : an international journal of the Society for Medical Decision Making.

[13]  M. Feola,et al.  Cognitive impairment in heart failure patients , 2014, Journal of geriatric cardiology : JGC.

[14]  R. Fitzpatrick,et al.  Impact of patient-reported outcome measures on routine practice: a structured review. , 2006, Journal of evaluation in clinical practice.

[15]  N. Devlin,et al.  Getting the Most out of PROMs: Putting Health Outcomes at the Heart of NHS Decision-Making , 2010 .

[16]  Noel T Brewer,et al.  Tables or Bar Graphs? Presenting Test Results in Electronic Medical Records , 2012, Medical decision making : an international journal of the Society for Medical Decision Making.

[17]  Peter Tugwell,et al.  What types of interventions generate inequalities? Evidence from systematic reviews , 2012, Journal of Epidemiology & Community Health.

[18]  D. Burkhoff,et al.  Development and validation of a patient questionnaire to determine New York Heart Association classification. , 2004, Journal of cardiac failure.

[19]  Use of analogy in learning scientific concepts. , 1993 .

[20]  Nicole L. Exe,et al.  Numeracy and Literacy Independently Predict Patients’ Ability to Identify Out-of-Range Test Results , 2014, Journal of medical Internet research.

[21]  E. Sampson,et al.  Dementia in the acute hospital: prospective cohort study of prevalence and mortality , 2009, British Journal of Psychiatry.

[22]  Galina Velikova,et al.  Measuring quality of life in routine oncology practice improves communication and patient well-being: a randomized controlled trial. , 2004, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[23]  E. Bantug,et al.  Picture This: Presenting Longitudinal Patient-Reported Outcome Research Study Results to Patients , 2018, Medical decision making : an international journal of the Society for Medical Decision Making.

[24]  Lisa M. Schwartz,et al.  PSYCHOLOGICAL SCIENCE IN THE PUBLIC INTEREST Helping Doctors and Patients Make Sense of Health Statistics , 2022 .

[25]  Heidrun Schumann,et al.  Visualizing time-oriented data - A systematic view , 2007, Comput. Graph..

[26]  Michael A. Martin,et al.  “It's Like… You Know”: The Use of Analogies and Heuristics in Teaching Introductory Statistical Methods , 2003 .

[27]  Amy P Abernethy,et al.  Review of electronic patient-reported outcomes systems used in cancer clinical care. , 2014, Journal of oncology practice.

[28]  Claire F. Snyder,et al.  What do these scores mean? Presenting patient‐reported outcomes data to patients and clinicians to improve interpretability , 2017, Cancer.

[29]  P. Raghubir,et al.  Is 1/10 > 10/100? The effect of denominator salience on perceptions of base rates of health risk , 2008 .

[30]  P. Ubel,et al.  Measuring Numeracy without a Math Test: Development of the Subjective Numeracy Scale , 2007, Medical decision making : an international journal of the Society for Medical Decision Making.

[31]  David Feeny,et al.  Assessing the use of health-related quality of life measures in the routine clinical care of lung-transplant patients , 2010, Quality of Life Research.

[32]  J. Greenhalgh The applications of PROs in clinical practice: what are they, do they work, and why? , 2009, Quality of Life Research.

[33]  E. Boyko,et al.  Brief questions to identify patients with inadequate health literacy. , 2004, Family medicine.

[34]  N. Tangri,et al.  Cognitive Impairment in Advanced Chronic Kidney Disease: The Canadian Frailty Observation and Interventions Trial , 2016, American Journal of Nephrology.

[35]  G. Guyatt,et al.  The impact of measuring patient-reported outcomes in clinical practice: a systematic review of the literature , 2008, Quality of Life Research.

[36]  Andrew J. May,et al.  A Comparison of Field-Based and Lab-Based Experiments to Evaluate User Experience of Personalised Mobile Devices , 2013, Adv. Hum. Comput. Interact..

[37]  Sunmoo Yoon,et al.  Method for the Development of Data Visualizations for Community Members with Varying Levels of Health Literacy , 2013, AMIA.

[38]  Karen Page,et al.  Screening for mild cognitive impairment in patients with heart failure: Montreal Cognitive Assessment versus Mini Mental State Exam , 2013, European journal of cardiovascular nursing : journal of the Working Group on Cardiovascular Nursing of the European Society of Cardiology.

[39]  E. Bantug,et al.  Engaging stakeholders to improve presentation of patient-reported outcomes data in clinical practice , 2016, Supportive Care in Cancer.

[40]  Alexandre N. Tuch,et al.  The role of visual complexity and prototypicality regarding first impression of websites: Working towards understanding aesthetic judgments , 2012, Int. J. Hum. Comput. Stud..

[41]  J. Gore,et al.  Symptom Presentation in Patients Hospitalized with Acute Heart Failure , 2010, Clinical cardiology.

[42]  Steven K. Feiner,et al.  Leveraging Patient-Reported Outcomes Using Data Visualization , 2018, Applied Clinical Informatics.

[43]  Sunmoo Yoon,et al.  Sometimes more is more: iterative participatory design of infographics for engagement of community members with varying levels of health literacy , 2016, J. Am. Medical Informatics Assoc..

[44]  Suzanne Bakken,et al.  A Systematic Method for Exploring Data Attributes in Preparation for Designing Tailored Infographics of Patient Reported Outcomes , 2018, EGEMS.

[45]  Joanne Greenhalgh,et al.  Implementing patient-reported outcomes assessment in clinical practice: a review of the options and considerations , 2012, Quality of Life Research.

[46]  Edward T. Cokely,et al.  Designing Visual Aids That Promote Risk Literacy: A Systematic Review of Health Research and Evidence-Based Design Heuristics , 2017, Hum. Factors.

[47]  Neil W. Wagle Implementing Patient-Reported Outcome Measures , 2017 .

[48]  M. Brundage,et al.  Added value of health-related quality of life measurement in cancer clinical trials: the experience of the NCIC CTG , 2010, Expert review of pharmacoeconomics & outcomes research.

[49]  G. Lakoff,et al.  Metaphors We Live By , 1980 .

[50]  Maja Brückmann,et al.  Four decades of research in science education : from curriculum development to quality improvement , 2008 .

[51]  K. Meadows,et al.  The effectiveness of the use of patient-based measures of health in routine practice in improving the process and outcomes of patient care: a literature review. , 1999, Journal of evaluation in clinical practice.

[52]  Donald M. Berwick,et al.  Era 3 for Medicine and Health Care. , 2016, JAMA.

[53]  J. Baumhauer Patient-Reported Outcomes - Are They Living Up to Their Potential? , 2017, The New England journal of medicine.

[54]  Claire F. Snyder,et al.  Communicating patient-reported outcome scores using graphic formats: results from a mixed-methods evaluation , 2015, Quality of Life Research.

[55]  Jessica S. Ancker,et al.  Good intentions are not enough: how informatics interventions can worsen inequality , 2018, J. Am. Medical Informatics Assoc..

[56]  Jacqueline A. ter Stege,et al.  Patient-Reported Outcome Measurement in Clinical Dermatological Practice: Relevance and Feasibility of a Web-Based Portal , 2015, Dermatology.

[57]  J. Fries,et al.  The Patient-Reported Outcomes Measurement Information System (PROMIS): Progress of an NIH Roadmap Cooperative Group During its First Two Years , 2007, Medical care.

[58]  Edward T. Cokely,et al.  Effective communication of risks to young adults: using message framing and visual aids to increase condom use and STD screening. , 2011, Journal of experimental psychology. Applied.

[59]  M. Galesic,et al.  Graph Literacy , 2011, Medical decision making : an international journal of the Society for Medical Decision Making.

[60]  P. Ubel,et al.  The impact of the format of graphical presentation on health-related knowledge and treatment choices. , 2008, Patient education and counseling.

[61]  J. Perry,et al.  Is Cognitive Function a Concern in Independent Elderly Adults Discharged Home from the Emergency Department in Canada After a Minor Injury? , 2014, Journal of the American Geriatrics Society.

[62]  J T Hart,et al.  THE INVERSE CARE LAW , 1971 .

[63]  Xingda Qu,et al.  Presenting self-monitoring test results for consumers: the effects of graphical formats and age , 2018, J. Am. Medical Informatics Assoc..

[64]  Melissa D. Begg,et al.  Using Visual Analogies To Teach Introductory Statistical Concepts , 2017 .

[65]  Naoki Sato,et al.  The global health and economic burden of hospitalizations for heart failure: lessons learned from hospitalized heart failure registries. , 2014, Journal of the American College of Cardiology.

[66]  Kilbourn Jp Letter: Cystic fibrosis. , 1974 .

[67]  P. Ubel,et al.  Validation of the Subjective Numeracy Scale: Effects of Low Numeracy on Comprehension of Risk Communications and Utility Elicitations , 2007, Medical decision making : an international journal of the Society for Medical Decision Making.

[68]  George Hripcsak,et al.  Engaging hospitalized patients with personalized health information: a randomized trial of an inpatient portal , 2018, J. Am. Medical Informatics Assoc..

[69]  Roma Maguire,et al.  What is the value of the routine use of patient-reported outcome measures toward improvement of patient outcomes, processes of care, and health service outcomes in cancer care? A systematic review of controlled trials. , 2014, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[70]  K. Wallston,et al.  Short, subjective measures of numeracy and general health literacy in an adult emergency department. , 2011, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[71]  M. Fornage,et al.  Heart Disease and Stroke Statistics—2017 Update: A Report From the American Heart Association , 2017, Circulation.

[72]  Deborah Schrag,et al.  Symptom Monitoring With Patient-Reported Outcomes During Routine Cancer Treatment: A Randomized Controlled Trial. , 2016, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[73]  C. Whitlatch,et al.  Decision-making for persons with cognitive impairment and their family caregivers , 2002, American journal of Alzheimer's disease and other dementias.

[74]  Susan R. Goldman,et al.  The Role of Prior Knowledge in Learning From Analogies in Science Texts , 2010 .

[75]  Jacob Solomon,et al.  Graphics help patients distinguish between urgent and non-urgent deviations in laboratory test results , 2016, J. Am. Medical Informatics Assoc..

[76]  Pete Wegier,et al.  Aiding risk information learning through simulated experience (ARISE): Using simulated outcomes to improve understanding of conditional probabilities in prenatal Down syndrome screening. , 2017, Patient education and counseling.

[77]  Thomas S. Huang,et al.  A multidisciplinary approach to designing and evaluating Electronic Medical Record portal messages that support patient self-care , 2017, J. Biomed. Informatics.

[78]  K. Weinfurt,et al.  Reliability and construct validity of PROMIS® measures for patients with heart failure who undergo heart transplant , 2015, Quality of Life Research.

[79]  Charles G. Martin,et al.  Influence of data display formats on physician investigators' decisions to stop clinical trials: prospective trial with repeated measures , 1999, BMJ.

[80]  Taya Irizarry,et al.  Patient Portals and Patient Engagement: A State of the Science Review , 2015, Journal of medical Internet research.

[81]  Erika A. Waters,et al.  Using the Short Graph Literacy Scale to Predict Precursors of Health Behavior Change , 2019, Medical decision making : an international journal of the Society for Medical Decision Making.

[82]  Bryant T Karras,et al.  Enhancing patient-provider communication with the electronic self-report assessment for cancer: a randomized trial. , 2011, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[83]  R. Duit On the role of analogies and metaphors in learning science. , 1991 .

[84]  Ethan Basch,et al.  Electronic patient‐reported outcome systems in oncology clinical practice , 2012, CA: a cancer journal for clinicians.

[85]  J. Cummings,et al.  The Montreal Cognitive Assessment, MoCA: A Brief Screening Tool For Mild Cognitive Impairment , 2005, Journal of the American Geriatrics Society.

[86]  B. Lapin,et al.  Clinical Utility of Patient-Reported Outcome Measurement Information System Domain Scales: Thresholds for Determining Important Change After Stroke , 2019, Circulation. Cardiovascular quality and outcomes.

[87]  Laura D. Scherer,et al.  Blocks, Ovals, or People? Icon Type Affects Risk Perceptions and Recall of Pictographs , 2014, Medical decision making : an international journal of the Society for Medical Decision Making.

[88]  R. McKelvie,et al.  Cognitive function and self-care management in older patients with heart failure , 2014, European journal of cardiovascular nursing : journal of the Working Group on Cardiovascular Nursing of the European Society of Cardiology.

[89]  N. Aaronson,et al.  Health-related quality-of-life assessments and patient-physician communication: a randomized controlled trial. , 2002, JAMA.

[90]  David W. Bates,et al.  Accelerating Innovation in Health IT. , 2016, The New England journal of medicine.

[91]  Wändi Bruine de Bruin,et al.  Designing Graphs to Communicate Risks: Understanding How the Choice of Graphical Format Influences Decision Making , 2017, Risk analysis : an official publication of the Society for Risk Analysis.