Over 8 million patients experiencing cancer face health-related social needs (HRSN) challenges, such as food, housing, and financial insecurity, that directly impact their health outcomes. While patients may participate in the screening of unmet social needs with their healthcare provider, it is not well understood if patients will self-screen and act on referrals to community services. Therefore, we conducted a mixed-methods study in which we pilot-tested a patient-centered oncology-focused digital social care referral platform, ConnectedNest. We recruited 13 cancer-focused community-based organizations (CBOs) and 41 individuals (e.g., patients, survivors, and caregivers) affected by cancer to participate in the study. Individuals used the application on their phones for 3 months. They completed a social needs assessment and were provided with a personalized list of local CBO programs that could address these unmet needs. Quantitative analyses described participant HRSN and connections to referred programs. User experience surveys were collected over 30 and 60 days to understand their experience. Individuals were also invited to participate in an a semi-structured interview to understand barriers and facilitators for social care referrals. Participants reported needs across 14 categories, with an average of 4.5 HRSN per participants. The top 3 reported needs were physical activity, financial strain, and mental health. Using our social care referral platform, approximately 39% of participants were able to connect with local CBOs. Three topic areas emerged from the participant interviews, highlighting that personal motivation, the participant's role, and the interest in services affected the participant's use of the technology. This study demonstrates the potential for digital social care referral platforms to bridge individuals affected by cancer with vital CBO resources to address HRSNs.

Over 8 million patients experiencing cancer face health-related social needs (HRSN) challenges, such as food, housing, and financial insecurity, that directly impact their health outcomes. While patients may participate in the screening of unmet social needs with their healthcare provider, it is not well understood if patients will self-screen and act on referrals to community services. Therefore, we conducted a mixed-methods study in which we pilot-tested a patient-centered oncology-focused digital social care referral platform, ConnectedNest. We recruited 13 cancer-focused community-based organizations (CBOs) and 41 individuals (e.g., patients, survivors, and caregivers) affected by cancer to participate in the study. Individuals used the application on their phones for 3 months. They completed a social needs assessment and were provided with a personalized list of local CBO programs that could address these unmet needs. Quantitative analyses described participant HRSN and connections to referred programs. User experience surveys were collected over 30 and 60 days to understand their experience. Individuals were also invited to participate in an a semi-structured interview to understand barriers and facilitators for social care referrals. Participants reported needs across 14 categories, with an average of 4.5 HRSN per participants. The top 3 reported needs were physical activity, financial strain, and mental health. Using our social care referral platform, approximately 39% of participants were able to connect with local CBOs. Three topic areas emerged from the participant interviews, highlighting that personal motivation, the participant's role, and the interest in services affected the participant's use of the technology. This study demonstrates the potential for digital social care referral platforms to bridge individuals affected by cancer with vital CBO resources to address HRSNs.

A number of recent papers have investigated the impact of hurricanes on economic growth. However, there is limited understanding of the investment component of local growth after hurricanes. Using hand collected and web-scraped statutory property tax rate data in the U.S., I find that local governments respond to hurricane impact by raising tax rates. I find the hike in tax rates is persistent for 3-4 years after hurricane impact. The response is four times larger for major hurricanes compared to minor hurricanes. However, the increase in tax rates is not expected to be large enough to cause significant out-migration after the average hurricane. I supplement these findings with a novel data set of firm facility-level hurricane impact. I find that firms initially decrease investment in the quarter following hurricane impact and increase it in the final quarters of the second year after impact. Taken together, my paper presents a novel set of stylized facts on government and firm mitigation investment response that can be interpreted in light of recent general equilibrium models with disaster risk.