Background

Cancer impacts individuals' life goals. Recent cancer care guidelines recommend discussing life goals as part of patient-provider communication. The goal of this study was to understand patients' attitudes toward goal sharing with their cancer care providers.

Patients and methods

Semi-structured questionnaires were conducted via email with cancer patients and survivors (n = 39) on an online social network called Smart Patients. Participants answered open-ended questions about their life goals. They then completed a survey regarding their attitudes toward goal sharing with healthcare providers. The study team used an integrated inductive-deductive qualitative analysis to identify conceptual themes.

Results

Participants listed goals related to improving physical activity, control, enjoyment/leisure, and inner strength while reducing pain, anxiety, fear of recurrence, and uncertainty. Most of these goals were life goals rather than goals specifically related to medical care. Across all goals, there was a focus on returning to normality. Our findings show that 87% of participants expect their cancer specialist to discuss their treatment preferences and goals regularly with them. However, participants were reluctant to share their goals with their providers. Respondents felt that their providers did not have an interest in their life goals or time to address them in addition to their medical treatment.

Conclusion

Even though cancer patient-provider communication guidelines advocate for discussions around life goals, participants in this study expressed reluctance to share life goals with providers. Further efforts to align expectations of patients and providers may facilitate adherence to cancer communication guidelines about life goals.

Implications for cancer survivors

Cancer survivors should be aware that discussing life goals is part of recommended communication with their cancer care teams.

Objective

The study sought to evaluate if peer input on outpatient cases impacted diagnostic confidence.

Materials and methods

This randomized trial of a peer input intervention occurred among 28 clinicians with case-level randomization. Encounters with diagnostic uncertainty were entered onto a digital platform to collect input from ≥5 clinicians. The primary outcome was diagnostic confidence. We used mixed-effects logistic regression analyses to assess for intervention impact on diagnostic confidence.

Results

Among the 509 cases (255 control; 254 intervention), the intervention did not impact confidence (odds ratio [OR], 1.46; 95% confidence interval [CI], 0.999-2.12), but after adjusting for clinician and case traits, the intervention was associated with higher confidence (OR, 1.53; 95% CI, 1.01-2.32). The intervention impact was greater in cases with high uncertainty (OR, 3.23; 95% CI, 1.09- 9.52).

Conclusions

Peer input increased diagnostic confidence primarily in high-uncertainty cases, consistent with findings that clinicians desire input primarily in cases with continued uncertainty.

BACKGROUND:Diagnostic error in ambulatory care, a frequent cause of preventable harm, may be mitigated using the collective intelligence of multiple clinicians. The National Academy of Medicine has identified enhanced clinician collaboration and digital tools as a means to improve the diagnostic process. OBJECTIVE:This study aims to assess the efficacy of a collective intelligence output to improve diagnostic confidence and accuracy in ambulatory care cases (from primary care and urgent care clinic visits) with diagnostic uncertainty. METHODS:This is a pragmatic randomized controlled trial of using collective intelligence in cases with diagnostic uncertainty from clinicians at primary care and urgent care clinics in 2 health care systems in San Francisco. Real-life cases, identified for having an element of diagnostic uncertainty, will be entered into a collective intelligence digital platform to acquire collective intelligence from at least 5 clinician contributors on the platform. Cases will be randomized to an intervention group (where clinicians will view the collective intelligence output) or control (where clinicians will not view the collective intelligence output). Clinicians will complete a postvisit questionnaire that assesses their diagnostic confidence for each case; in the intervention cases, clinicians will complete the questionnaire after reviewing the collective intelligence output for the case. Using logistic regression accounting for clinician clustering, we will compare the primary outcome of diagnostic confidence and the secondary outcome of time with diagnosis (the time it takes for a clinician to reach a diagnosis), for intervention versus control cases. We will also assess the usability and satisfaction with the digital tool using measures adapted from the Technology Acceptance Model and Net Promoter Score. RESULTS:We have recruited 32 out of our recruitment goal of 33 participants. This study is funded until May 2020 and is approved by the University of California San Francisco Institutional Review Board until January 2020. We have completed data collection as of June 2019 and will complete our proposed analysis by December 2019. CONCLUSIONS:This study will determine if the use of a digital platform for collective intelligence is acceptable, useful, and efficacious in improving diagnostic confidence and accuracy in outpatient cases with diagnostic uncertainty. If shown to be valuable in improving clinicians' diagnostic process, this type of digital tool may be one of the first innovations used for reducing diagnostic errors in outpatient care. The findings of this study may provide a path forward for improving the diagnostic process. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID):DERR1-10.2196/13151.

Introduction

In order to address health disparities, it is important to understand how vulnerable individuals seek information. This study used an adapted version of the Health Information National Trends Survey (HINTS) administered in English, Spanish, and Chinese to describe the behaviors and preferences of a diverse group of vulnerable urban residents.

Methods

We administered a modified HINTS survey in English, Spanish, and Chinese and used purposive sampling to ensure 50% were non-English speakers evenly divided between Spanish and Chinese speakers, and 50% of English-speakers identified as Black. We used multivariable logistic regression to determine characteristics associated with sources used for health information and preferences for delivery of health information.

Results

Among 1027survey respondents (514 English, 256 Spanish, 260 Chinese), 55% had adequate health literacy, and 50% reported household income <$20,000, but 77% reported owning a smartphone. A plurality sought health information on the Internet (39%) or from a health care provider (36%). In multivariable analyses, smartphone ownership predicted higher odds of seeking health information on the Internet [odds ratio, (OR) 2.98; 95% confidence interval (CI), 1.81-4.91]. Participants most preferred email (41%) and brochures (40%) for delivery of health information, but non-English survey respondents were less likely to prefer email: Spanish (OR, 0.30; 95% CI, 0.11-0.83) and Chinese (OR, 0.25; 95% CI, 0.09-0.71). Smartphone ownership predicted an email preference (OR, 2.19; 95% CI, 1.43-3.36).

Conclusions

Among vulnerable populations, smartphone ownership and language preferences impact preferences for seeking and receiving health information. These preferences need to be considered in designing health messages.

Introduction

In order to address health disparities, it is important to understand how vulnerable individuals seek information. This study used an adapted version of the Health Information National Trends Survey (HINTS) administered in English, Spanish, and Chinese to describe the behaviors and preferences of a diverse group of vulnerable urban residents.

Methods

We administered a modified HINTS survey in English, Spanish, and Chinese and used purposive sampling to ensure 50% were non-English speakers evenly divided between Spanish and Chinese speakers, and 50% of English-speakers identified as Black. We used multivariable logistic regression to determine characteristics associated with sources used for health information and preferences for delivery of health information.

Results

Among 1027survey respondents (514 English, 256 Spanish, 260 Chinese), 55% had adequate health literacy, and 50% reported household income <$20,000, but 77% reported owning a smartphone. A plurality sought health information on the Internet (39%) or from a health care provider (36%). In multivariable analyses, smartphone ownership predicted higher odds of seeking health information on the Internet [odds ratio, (OR) 2.98; 95% confidence interval (CI), 1.81-4.91]. Participants most preferred email (41%) and brochures (40%) for delivery of health information, but non-English survey respondents were less likely to prefer email: Spanish (OR, 0.30; 95% CI, 0.11-0.83) and Chinese (OR, 0.25; 95% CI, 0.09-0.71). Smartphone ownership predicted an email preference (OR, 2.19; 95% CI, 1.43-3.36).

Conclusions

Among vulnerable populations, smartphone ownership and language preferences impact preferences for seeking and receiving health information. These preferences need to be considered in designing health messages.

Background

The COVID-19 pandemic and efforts to mitigate transmission resulted in sudden and widespread socioeconomic disruptions including school and child care closures, unemployment and underemployment, and housing precarity. Understanding the extent to which these disruptions may have contributed to adverse health outcomes is critical for establishing policy priorities that can mitigate further harm.

Methods

We explored the associations between pandemic-related child care, employment, and housing disruptions with depressive symptoms, self-rated health, and food security status among a sample of economically disadvantaged and racially diverse female caregivers of young children (n=464). Data were derived from the Assessing California Communities' Experiences with Safety Net Supports (ACCESS) study, which conducted survey-based interviews with California caregivers with low-income from August 2020 - May 2021. We implemented a series of multivariable Poisson regressions with robust standard errors to assess the potency of each exposure, independently and within the context of one another.

Results

Most caregivers experienced disruptions to child care (70%) and employment (63%); few experienced major housing disruptions (8%). Women that experienced child care and housing disruptions had greater depressive symptoms, lower self-rated health, and greater food insecurity, although the relationships for housing and depressive symptoms were modified by the timing of participants' interviews. Employment disruptions were not associated with any of the examined adverse health outcomes.

Conclusion

In the wake of socioeconomic stressors brought about by the COVID-19 pandemic, attending to structural deficits in the child care system and increasing housing supports may be critical for protecting the health of caregivers.

Background

Diagnostic error in ambulatory care, a frequent cause of preventable harm, may be mitigated using the collective intelligence of multiple clinicians. The National Academy of Medicine has identified enhanced clinician collaboration and digital tools as a means to improve the diagnostic process.

Objective

This study aims to assess the efficacy of a collective intelligence output to improve diagnostic confidence and accuracy in ambulatory care cases (from primary care and urgent care clinic visits) with diagnostic uncertainty.

Methods

This is a pragmatic randomized controlled trial of using collective intelligence in cases with diagnostic uncertainty from clinicians at primary care and urgent care clinics in 2 health care systems in San Francisco. Real-life cases, identified for having an element of diagnostic uncertainty, will be entered into a collective intelligence digital platform to acquire collective intelligence from at least 5 clinician contributors on the platform. Cases will be randomized to an intervention group (where clinicians will view the collective intelligence output) or control (where clinicians will not view the collective intelligence output). Clinicians will complete a postvisit questionnaire that assesses their diagnostic confidence for each case; in the intervention cases, clinicians will complete the questionnaire after reviewing the collective intelligence output for the case. Using logistic regression accounting for clinician clustering, we will compare the primary outcome of diagnostic confidence and the secondary outcome of time with diagnosis (the time it takes for a clinician to reach a diagnosis), for intervention versus control cases. We will also assess the usability and satisfaction with the digital tool using measures adapted from the Technology Acceptance Model and Net Promoter Score.

Results

We have recruited 32 out of our recruitment goal of 33 participants. This study is funded until May 2020 and is approved by the University of California San Francisco Institutional Review Board until January 2020. We have completed data collection as of June 2019 and will complete our proposed analysis by December 2019.

Conclusions

This study will determine if the use of a digital platform for collective intelligence is acceptable, useful, and efficacious in improving diagnostic confidence and accuracy in outpatient cases with diagnostic uncertainty. If shown to be valuable in improving clinicians' diagnostic process, this type of digital tool may be one of the first innovations used for reducing diagnostic errors in outpatient care. The findings of this study may provide a path forward for improving the diagnostic process.

International registered report identifier (irrid)

DERR1-10.2196/13151.

Background

Patient portals are becoming ubiquitous. Previous research has documented substantial barriers, especially among vulnerable patient subgroups such as those with lower socioeconomic status or limited health literacy (LHL). We tested the effectiveness of delivering online, video-based portal training to patients in a safety net setting.

Methods

We created an online video curriculum about accessing the San Francisco Health Network portal, and then randomized 93 English-speaking patients with 1+ chronic diseases to receive 1) an in-person tutorial with a research assistant, or 2) a link to view the videos on their own. We also examined a third, nonrandomized usual care comparison group. The primary outcome was portal log-in (yes/no) 3 to 6 months post-training, assessed via the electronic health record. Secondary outcomes were self-reported attitudes and skills collected via baseline and follow-up surveys.

Results

Mean age was 54 years, 51% had LHL, 60% were nonwhite, 52% were female, 45% reported fair/poor health, and 76% reported daily Internet use. At followup, 21% logged into the portal, with no differences by arm (P = .41), but this was higher than the overall clinic rate of 9% (P < .01) during the same time period. We found significant prepost improvements in self-rated portal skills (P = .03) and eHealth literacy (P < .01). Those with LHL were less likely to log in post-training (P < .01).

Conclusions

Both modalities of online training were comparable, and neither mode enabled a majority of vulnerable patients to use portals, especially those with LHL. This suggests that portal training will need to be more intensive or portals need improved usability to meaningfully increase use among diverse patients.

Objective

With the rapid rise in the adoption of patient portals, many patients are gaining access to their personal health information online for the first time. The objective of this study was to examine specific usability barriers to patient portal engagement among a diverse group of patients and caregivers.

Materials and methods

We conducted interviews using performance testing and think-aloud methods with 23 patients and 2 caregivers as they first attempted to use features of a newly launched patient portal.

Results

In navigating the portal, participants experienced basic computer barriers (eg, difficulty using a mouse), routine computer barriers (eg, mistyping, navigation issues), reading/writing barriers, and medical content barriers. Compared to participants with adequate health literacy, participants with limited health literacy required 2 additional minutes to complete each task and were more likely to experience each type of navigational barrier. They also experienced more inaccuracies in interpreting a test result and finding a treatment plan within an after-visit summary.

Discussion

When using a patient portal for the first time, participants with limited health literacy completed fewer tasks unassisted, had a higher prevalence of encountering barriers, took longer to complete tasks, and had more problems accurately interpreting medical information.

Conclusion

Our findings suggest a strong need for tailored and accessible training and support to assist all vulnerable patients and/or caregivers with portal registration and use. Measuring the health literacy of a patient population might serve as a strong proxy for identifying patients who need the most support in using health technologies.