ObjectiveWomen of low socioeconomic status (SES) diagnosed with early stage breast cancer experience decision-making, treatment and outcome disparities. Evidence suggests that decision aids can benefit underserved patients, when tailored to their needs. Our aim was to develop and test the usability, acceptability and accessibility of a pictorial encounter decision aid targeted at women of low SES diagnosed with early stage breast cancer.DesignCommunity-based participatory research (CBPR) using think-aloud protocols (phases 1 and 2) and semistructured interviews (phase 3).SettingUnderserved community settings (eg, knitting groups, bingo halls, senior centres) and breast clinics.ParticipantsIn phase 1, we recruited a convenience sample of clinicians and academics. In phase 2, we targeted women over 40 years of age, of low SES, regardless of breast cancer history, and in phase 3, women of low SES, recently diagnosed with breast cancer.InterventionThe pictorial encounter decision aid was derived from an evidence-based table comparing treatment options for breast cancer (http://www.optiongrid.org).Outcome measuresWe assessed the usability, acceptability and accessibility of the pictorial decision aid prototypes using the think-aloud protocol and semistructured interviews.ResultsAfter initial testing of the first prototype with 18 academics and health professionals, new versions were developed and tested with 53 lay individuals in community settings. Usability was high. In response to feedback indicating that the use of cartoon characters was considered insensitive, a picture-only version was developed and tested with 23 lay people in phase 2, and 10 target users in phase 3.Conclusions and relevanceUsing CBPR methods and iterative user testing cycles improved usability and accessibility, and led to the development of the Picture Option Grid, entirely guided by multiple stakeholder feedback. All women of low SES recently diagnosed with early stage breast cancer found the Picture Option Grid usable, acceptable and accessible.
IMPORTANCE Early discussion of end-of-life (EOL) care preferences improves clinical outcomes and goal-concordant care. However, most EOL discussions occur approximately 1 month before death, despite most patients desiring information earlier.OBJECTIVE To describe successful navigation and missed opportunities for EOL discussions (eg, advance care planning, palliative care, discontinuation of disease-directed treatment, hospice care, and after-death wishes) between oncologists and outpatients with advanced cancer. DESIGN, SETTING, AND PARTICIPANTSThis study is a secondary qualitative analysis of outpatient visits audio-recorded between November 2010 and September 2014 for the Studying Communication in Oncologist-Patient Encounters randomized clinical trial. The study was conducted at 2 US academic medical centers. Participants included medical, gynecological, and radiation oncologists and patients with stage IV malignant neoplasm, whom oncologists characterized as being ones whom they "…would not be surprised if they were admitted to an intensive care unit or died within one year." Data were analyzed between January 2018 and August 2020. EXPOSURES The parent study randomized participants to oncologist-and patient-directed interventions to facilitate discussion of emotions. Encounters were sampled across preintervention and postintervention periods and all 4 treatment conditions. MAIN OUTCOMES AND MEASURES Secondary qualitative analysis was done of patient-oncologist dyads with 3 consecutive visits for EOL discussions, and a random sample of 7 to 8 dyads from 4 trial groups was analyzed for missed opportunities. RESULTS The full sample included 141 patients (54 women [38.3%]) and 39 oncologists (8 women [19.5%]) (mean [SD] age for both patients and oncologists, 56.3 [10.0] years). Of 423 encounters, only 21 (5%) included EOL discussions. Oncologists reevaluated treatment options in response to patients' concerns, honored patients as experts on their goals, or used anticipatory guidance to frame treatment reevaluation. In the random sample of 31 dyads and 93 encounters, 35 (38%) included at least 1 missed opportunity. Oncologists responded inadequately to patient concerns over disease progression or dying, used optimistic future talk to address patient concerns, or expressed concern over treatment discontinuation. Only 4 of 23 oncologists (17.4%) had both an EOL discussion and a missed opportunity. CONCLUSIONS AND RELEVANCEOpportunities for EOL discussions were rarely realized, whereas missed opportunities were more common, a trend that mirrored oncologists' treatment style. There (continued) Key Points Question How do oncologists successfully navigate and miss opportunities for discussions about end of life (EOL), including advance care planning, palliative care, discontinuation Author affiliations and article information are listed at the end of this article.
Background We calculated the performance of National Cancer Institute (NCI)/National Comprehensive Cancer Network (NCCN) cancer centers’ end‐of‐life (EOL) quality metrics among minority and white decedents to explore center‐attributable sources of EOL disparities. Methods We conducted a retrospective cohort study of Medicare beneficiaries with poor‐prognosis cancers who died between April 1, 2016 and December 31, 2016 and had any inpatient services in the last 6 months of life. We attributed patients’ EOL treatment to the center at which they received the preponderance of EOL inpatient services and calculated eight risk‐adjusted metrics of EOL quality (hospice admission ≤3 days before death; chemotherapy last 14 days of life; ≥2 emergency department (ED) visits; intensive care unit (ICU) admission; or life‐sustaining treatment last 30 days; hospice referral; palliative care; advance care planning last 6 months). We compared performance between patients across and within centers. Results Among 126,434 patients, 10,119 received treatment at one of 54 NCI/NCCN centers. In aggregate, performance was worse among minorities for ED visits (10.3% vs 7.4%, P < .01), ICU admissions (32.9% vs 30.4%, P = .03), no hospice referral (39.5% vs 37.0%, P = .03), and life‐sustaining treatment (19.4% vs 16.2%, P < .01). Despite high within‐center correlation for minority and white metrics (0.61‐0.79; P < .01), five metrics demonstrated worse performance as the concentration of minorities increased: ED visits (P = .03), ICU admission (P < .01), no hospice referral (P < .01), and life‐sustaining treatments (P < .01). Conclusion EOL quality metrics vary across NCI/NCCN centers. Within center, care was similar for minority and white patients. Minority‐serving centers had worse performance on many metrics.
Although biomarkers significantly improved prediction of 30-day readmission or mortality in our derivation cohort, the external validation of the biomarker panel was poor. Biomarkers perform poorly, much like other efforts to improve prediction of readmission, suggesting there are many other factors yet to be explored to improve prediction of readmission.
BackgroundWomen of low socioeconomic status (SES) diagnosed with early stage breast cancer are less likely to be involved in treatment decisions. They tend to report higher decisional regret and poorer communication. Evidence suggests that well-designed encounter decision aids (DAs) could improve outcomes and potentially reduce healthcare disparities. Our goal was to evaluate the acceptability and feasibility of encounter decision aids (Option Grid, Comic Option Grid, and Picture Option Grid) adapted for a low-SES and low-literacy population.MethodsWe used a multi-phase, mixed-methods approach. In phase 1, we conducted a focus group with rural community stakeholders. In phase 2, we developed and administered a web-based questionnaire with patients of low and high SES. In phase 3, we interviewed patients of low SES and relevant healthcare professionals.ResultsData from phase 1 (n = 5) highlighted the importance of addressing treatment costs for patients. Data from phase 2 (n = 268) and phase 3 (n = 15) indicated that using both visual displays and numbers are helpful for understanding statistical information. Data from all three phases suggested that using plain language and simple images (Picture Option Grid) was most acceptable and feasible. The Comic Option Grid was deemed least acceptable.ConclusionOption Grid and Picture Option Grid appeared acceptable and feasible in facilitating patient involvement and improving perceived understanding among patients of high and low SES. Picture Option Grid was considered most acceptable, accessible and feasible in the clinic visit. However, given the small sample sizes used, those findings need to be interpreted with caution. Further research is needed to determine the impact of pictorial and text-based encounter decision aids in underserved patients and across socioeconomic strata.
BackgroundCurrent preoperative models use clinical risk factors alone in estimating risk of in‐hospital mortality following cardiac surgery. However, novel biomarkers now exist to potentially improve preoperative prediction models. An assessment of Galectin‐3, N‐terminal pro b‐type natriuretic peptide (NT‐ProBNP), and soluble ST2 to improve the predictive ability of an existing prediction model of in‐hospital mortality may improve our capacity to risk‐stratify patients before surgery.Methods and ResultsWe measured preoperative biomarkers in the NNECDSG (Northern New England Cardiovascular Disease Study Group), a prospective cohort of 1554 patients undergoing coronary artery bypass graft surgery. Exposures of interest were preoperative levels of galectin‐3, NT‐ProBNP, and ST2. In‐hospital mortality and adverse events occurring after coronary artery bypass graft were the outcomes. After adjustment, NT‐ProBNP and ST2 showed a statistically significant association with both their median and third tercile categories with NT‐ProBNP odds ratios of 2.89 (95% confidence interval [CI]: 1.04–8.05) and 5.43 (95% CI: 1.21–24.44) and ST2 odds ratios of 3.96 (95% CI: 1.60–9.82) and 3.21 (95% CI: 1.17–8.80), respectively. The model receiver operating characteristic score of the base prediction model (0.80 [95% CI: 0.72–0.89]) varied significantly from the new multi‐marker model (0.85 [95% CI: 0.79–0.91]). Compared with the Northern New England (NNE) model alone, the full prediction model with biomarkers NT‐proBNP and ST2 shows significant improvement in model classification of in‐hospital mortality.ConclusionsThis study demonstrates a significant improvement of preoperative prediction of in‐hospital mortality in patients undergoing coronary artery bypass graft and suggests that biomarkers can be used to identify patients at higher risk.
Preoperative ST2 levels are associated with postoperative AKI risk and can be used to identify patients at higher risk of developing AKI after cardiac surgery.
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