scholarly journals Health Literacy and Shared Decision-making: Exploring the Relationship to Enable Meaningful Patient Engagement in Healthcare

Author(s):  
Danielle M. Muscat ◽  
Heather L. Shepherd ◽  
Don Nutbeam ◽  
Lyndal Trevena ◽  
Kirsten J. McCaffery
2019 ◽  
Vol 102 (2) ◽  
pp. 360-366 ◽  
Author(s):  
Hsiu-Nien Shen ◽  
Chia-Chen Lin ◽  
Tammy Hoffmann ◽  
Chia-Yin Tsai ◽  
Wen-Hsuan Hou ◽  
...  

2018 ◽  
Vol 45 (3) ◽  
pp. 156-160 ◽  
Author(s):  
Rosalind J McDougall

Artificial intelligence (AI) is increasingly being developed for use in medicine, including for diagnosis and in treatment decision making. The use of AI in medical treatment raises many ethical issues that are yet to be explored in depth by bioethicists. In this paper, I focus specifically on the relationship between the ethical ideal of shared decision making and AI systems that generate treatment recommendations, using the example of IBM’s Watson for Oncology. I argue that use of this type of system creates both important risks and significant opportunities for promoting shared decision making. If value judgements are fixed and covert in AI systems, then we risk a shift back to more paternalistic medical care. However, if designed and used in an ethically informed way, AI could offer a potentially powerful way of supporting shared decision making. It could be used to incorporate explicit value reflection, promoting patient autonomy. In the context of medical treatment, we need value-flexible AI that can both respond to the values and treatment goals of individual patients and support clinicians to engage in shared decision making.


2020 ◽  
Vol 203 ◽  
pp. e817-e818
Author(s):  
Kerry Kilbridge ◽  
William Martin-Doyle* ◽  
Christopher Filson ◽  
Quoc-Dien Trinh ◽  
Sierra Williams ◽  
...  

2020 ◽  
Author(s):  
Richard Huan Xu ◽  
Ling-Ming Zhou ◽  
Eliza Lai-Yi Wong ◽  
Dong Wang

BACKGROUND Although previous studies have shown that a high level of health literacy can improve patients’ ability to engage in health-related shared decision-making (SDM) and improve their quality of life, few studies have investigated the role of eHealth literacy in improving patient satisfaction with SDM (SSDM) and well-being. OBJECTIVE This study aims to assess the relationship between patients’ eHealth literacy and their socioeconomic determinants and to investigate the association between patients’ eHealth literacy and their SSDM and well-being. METHODS The data used in this study were obtained from a multicenter cross-sectional survey in China. The eHealth Literacy Scale (eHEALS) and Investigating Choice Experiments Capability Measure for Adults were used to measure patients’ eHealth literacy and capability well-being, respectively. The SSDM was assessed by using a self-administered questionnaire. The Kruskal-Wallis one-way analysis of variance and Wilcoxon signed-rank test were used to compare the differences in the eHEALS, SSDM, and Investigating Choice Experiments Capability Measure for Adults scores of patients with varying background characteristics. Ordinary least square regression models were used to assess the relationship among eHealth literacy, SSDM, and well-being adjusted by patients’ background characteristics. RESULTS A total of 569 patients completed the questionnaire. Patients who were male, were highly educated, were childless, were fully employed, were without chronic conditions, and indicated no depressive disorder reported a higher mean score on the eHEALS. Younger patients (SSDM<sub>≥61 years</sub>=88.6 vs SSDM<sub>16-30 years</sub>=84.2) tended to show higher SSDM. Patients who were rural residents and were well paid were more likely to report good capability well-being. Patients who had a higher SSDM and better capability well-being reported a significantly higher level of eHealth literacy than those who had lower SSDM and poorer capability well-being. The regression models showed a positive relationship between eHealth literacy and both SSDM (<i>β</i>=.22; <i>P</i>&lt;.001) and well-being (<i>β</i>=.26; <i>P</i>&lt;.001) after adjusting for patients’ demographic, socioeconomic status, lifestyle, and health status variables. CONCLUSIONS This study showed that patients with a high level of eHealth literacy are more likely to experience optimal SDM and improved capability well-being. However, patients’ depressive status may alter the relationship between eHealth literacy and SSDM. CLINICALTRIAL


2017 ◽  
pp. 351-368
Author(s):  
Geri Lynn Baumblatt

In this chapter the author describes the challenges of engaging and communicating with patients and how technology can improve communication, elicit honest patient disclosure, and create more productive conversation and help patients engage and partner in their care. The author will also discuss how research with multimedia programs reveals it can help reduce anxiety, improve knowledge, help low health literacy audiences, and contribute to improved outcomes. This chapter will also examine how multimedia decision aid programs can help patients understand their options and complex risk information, while helping them consider their values and preferences so they can truly engage in shared decision making.


2019 ◽  
Vol 37 (7_suppl) ◽  
pp. 84-84 ◽  
Author(s):  
William Martin-Doyle ◽  
Christopher Paul Filson ◽  
Susan Regan ◽  
Quoc-Dien Trinh ◽  
Sierra Williams ◽  
...  

84 Background: ASCO, AUA, ASTRO and SUO endorse shared decision making for men with localized PCa. We explored treatment decisions among providers and their AA patients (pts) in a prospective cohort study at Grady Memorial Hospital and the Atlanta Veterans Administration Hospital. Methods: Following their visit, 18 providers documented the PCa treatment options they had discussed with 124 newly diagnosed, early-stage, African American PCa pts. At a subsequent visit, prior to choosing their cancer treatment, pts were asked to name the options they had discussed with their provider. Demographics were collected. Health literacy was measured using the Rapid Estimate of Adult Literacy in Medicine (REALM). Numeracy, comprehension of common PCa terms, and anatomic knowledge were assessed using published methods (Kilbridge K, et al. J Clin Oncol 27:2015-2021, 2009). Chi-square, t-tests and multivariate logistic regression were used to identify variables associated with correct understanding of treatment choices. Results: Just 23.4% of pts correctly understood their treatment options. In univariate analysis, only health literacy was statistically significantly associated with comprehension of PCa treatment options (p < 0.05). In a multivariate logistic model adjusting for age, education, income, numeracy, comprehension of common PCa terms, and anatomic knowledge; health literacy remained the only significant predictor of pts’ comprehension of their treatment choices (OR 3.8, 95% CI 1.2-11.9, p = 0.021). Even among the 49 pts with the highest level of health literacy, only 34.7% correctly understood their cancer treatment options (compared to 16.0% among low literacy patients). Conclusions: Successful shared decision making requires pts to understand their treatment choices. Information presented by healthcare providers may be overwhelming for newly diagnosed pts, particularly those with lower health literacy. Our study suggests that even pts with the highest level of health literacy may need additional support to understand their PCa treatment options.


2014 ◽  
Vol 41 (7) ◽  
pp. 1290-1297 ◽  
Author(s):  
Jennifer L. Barton ◽  
Laura Trupin ◽  
Chris Tonner ◽  
John Imboden ◽  
Patricia Katz ◽  
...  

Objective.Treat-to-target guidelines promote shared decision making (SDM) in rheumatoid arthritis (RA). Also, because of high cost and potential toxicity of therapies, SDM is central to patient safety. Our objective was to examine patterns of perceived communication around decision making in 2 cohorts of adults with RA.Methods.Data were derived from patients enrolled in 1 of 2 longitudinal, observational cohorts [University of California, San Francisco (UCSF) RA Cohort and RA Panel Cohort]. Subjects completed a telephone interview in their preferred language that included a measure of patient-provider communication, including items about decision making. Measures of trust in physician, education, and language proficiency were also asked. Logistic regression was performed to identify correlates of suboptimal SDM communication. Analyses were performed on each sample separately.Results.Of 509 patients across 2 cohorts, 30% and 32% reported suboptimal SDM communication. Low trust in physician was independently associated with suboptimal SDM communication in both cohorts. Older age and limited English proficiency were independently associated with suboptimal SDM in the UCSF RA Cohort, as was limited health literacy in the RA Panel Cohort.Conclusion.This study of over 500 adults with RA from 2 demographically distinct cohorts found that nearly one-third of subjects report suboptimal SDM communication with their clinicians, regardless of cohort. Lower trust in physician was independently associated with suboptimal SDM communication in both cohorts, as was limited English language proficiency and older age in the UCSF RA Cohort and limited health literacy in the RA Panel Cohort. These findings underscore the need to examine the influence of SDM on health outcomes in RA.


2001 ◽  
Vol 19 (7) ◽  
pp. 684-691 ◽  
Author(s):  
Simon P. Kim ◽  
Sara J. Knight ◽  
Cecilia Tomori ◽  
Kathleen M. Colella ◽  
Richard A. Schoor ◽  
...  

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