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In March 2020, days after New York shut down to mitigate the spread of COVID-19, we developed a cross-sectional, participant-administered electronic survey to explore how New Yorkers were impacted by and were responding to the ongoing crisis. A critical component of the survey was to assess how credible and trustworthy respondents found various information sources. To advertise and distribute the survey, we embedded an invitation to participate using a popup on the GetHealthyHeights.org website. GetHealthyHeights was designed using community-based participatory research for the medically-underserved, urban, and largely Latinx community of Washington Heights-Inwood, New York City. We received 321 responses from April through July 2020. Participant ages ranged from 25 to 87, and 25% were Latinx. Results showed that the choice of and trust in different COVID-19 information sources were observed to be significantly different across demographic variables, including gender, age, race, and chronic health conditions. In the domains of trust and information source credibility, designers should account for perspectives of diverse subgroups., (©2018 AMIA - All rights reserved.)

Women at high risk for breast cancer may benefit from enhanced screening and risk-reduction strategies. However, limited time during clinical encounters is one barrier to routine breast cancer risk assessment. We evaluated if electronic health record (EHR) data downloaded using Fast Healthcare Interoperability Resources (FHIR) is sufficient for breast cancer risk calculation in our decision support tools, RealRisks and BNAV. We accessed EHR data using FHIR for six patient advocates, and downloaded and parsed XML documents. We searched for relevant clinical variables, and evaluated if data was sufficient to calculate risk using validated models (Gail, Breast Cancer Screening Consortium [BCSC], BRCAPRO). While only one advocate had sufficient EHR data to calculate risk using the BCSC model only, we identified variables including age, race/ethnicity, mammographic density, and prior breast biopsy in most advocates. EHR data from FHIR could be incorporated into automated breast cancer risk calculation in clinical decision support tools., (©2021 AMIA - All rights reserved.)

The United States Preventive Services Taskforce recommends that primary care providers screen patients for an increased risk of carrying a BRCA1 or BRCA2 mutation and refer those who meet family history criteria to genetic counseling. Such screening requires detailed and accurate family history data, which often goes uncollected during a primary care visit due to time constraints, competing priorities, and lack of awareness on behalf of both patients and providers. In order to address these barriers and promote appropriate genetic counseling referral, we developed a user-centered framework that collects and communicates relevant data in order to prepare patients and their primary care providers for an informed discussion on genetic counseling referral. This paper describes this framework and the underlining data schema that makes it possible.

Genetic testing is a method to assess hereditary cancer risk. However, it is under-utilized and various methods of family history intake have been evaluated in previous studies. The six-point-scale (SPS) is a validated family history screener that is used to determine eligibility for BRCA genetic counseling. We automated the calculation of the SPS score using structured family history data along with free text from the electronic health record (EHR) to detect detailed family history information of breast cancer. We extracted data for all women aged 35 to 74 who had screening mammography at Columbia University Medical Center (CUMC) from January 2015 to May 2017 (N=37,596). After we calculated SPS scores using structured and free-text EHR data, we compared the results with SPS score calculated from a baseline survey conducted for a prospective study called Know Your Risks: Assessment at Screening (KYRAS). Among 1,202 patients with EHR structured family history data, we found 1.43% had an SPS score of 6 higher which meets criteria for genetic counseling referral, while 12.05% of the survey respondents had SPS score of 6 or higher. Results show there is a need for more efficient methods to identify patients eligible for genetic counseling through EHR analysis.

Chemoprevention with antiestrogens could decrease the incidence of invasive breast cancer but uptake has been low among high-risk women in the United States. We have designed a web-based patient-facing decision aid, called RealRisks, to inform high-risk women about the risks and benefits of chemoprevention and facilitate shared decision-making with their primary care provider. We conducted two rounds of usability testing to determine how subjects engaged with and understood the information in RealRisks. A total of 7 English-speaking and 4 Spanish-speaking subjects completed testing. Using surveys, think-aloud protocols, and subject recordings, we identified several themes relating to the usability of RealRisks, specifically in the content, ease of use, and navigability of the application. By conducting studies in two languages with a diverse multi-ethnic population, we were able to implement interface changes to make RealRisks accessible to users with varying health literacy and acculturation.

The purpose of this study was to identify barriers and facilitators to patient-provider communication when discussing breast cancer risk to aid in the development of decision support tools. Four patient focus groups (N=34) and eight provider focus groups (N=10) took place in Northern Manhattan. A qualitative analysis was conducted using Atlas.ti software. The coding yielded 62.3%-94.5% agreement. The results showed that 1) barriers are time constraints, lack of knowledge, low health literacy, and language barriers, and 2) facilitators are information needs, desire for personalization, and autonomy when communicating risk in patient-provider encounters. These results will inform the development of a patient-centered decision aid (RealRisks) and a provider-facing breast cancer risk navigation (BNAV) tool, which are designed to facilitate patient-provider risk communication and shared decision-making about breast cancer prevention strategies, such as chemoprevention.