As healthcare costs continue to rise, many Americans are looking to artificial intelligence to provide cost-reducing solutions. At the 13th annual UNC Business of Healthcare Conference, a panel of experts separated the AI hype from reality in a discussion of the limitations, risks and ethical questions surrounding AI solutions in healthcare.
Public health surveillance systems routinely process massive volumes of data to identify health adverse events affecting the general population. Surveillance and response to foodborne disease suffers from a number of systemic and other delays that hinder early detection and confirmation of emerging contamination situations. In this paper we develop an answer set programming (ASP) application to assist public health officials in detecting an emerging foodborne disease outbreak by integrating and analyzing in near real-time temporally, spatially and symptomatically diverse data. These data can be extracted from a large number of distinct information systems such as surveillance and laboratory reporting systems from health care providers, real-time complaint hotlines from consumers, and inspection reporting systems from regulatory agencies. We encode geographic ontologies in ASP to infer spatial relationships that may not be evident using traditional statistical tools. These technologies and ontologies have been implemented in a new informatics tool, the North Carolina Foodborne Events Data Integration and Analysis Tool (NCFEDA). The application was built to demonstrate the potential of situational awareness—created through real-time data fusion, analytics, visualization, and real-time communication—to reduce latency of response to foodborne disease outbreaks by North Carolina public health personnel.
The long-term upward trend in Hong Kong's housing price and its ever-increasing price-rent ratio has caused extensive concern from investors and researchers. Dynamic Gordon Model ties an asset's worth to the expected value of the future payoff stream accruing to the asset, and it has been widely used in the literature on finance and real estate asset. As far as we know, this model has not been applied to the research on the Hong Kong real estate market. In this paper, we used this model to analyze the quarterly date of Hong Kong housing prices and other economic indicators from 1999 to 2019.
Gentrifying cities increasingly are adopting inclusive and equitable development policies, strategies, tools, and regulatory practices to minimize, if not altogether eliminate, the demographic and economic dislocations that often accompany their growing attractiveness as ideal places to live, work, and play for a creative class of young people and well-resourced retirees who are predominantly white. Creating greater opportunities for historically under-utilized businesses to grow and prosper through enhanced local government contracting and procurement is one mechanism through which gentrifying cities are trying to generate greater equity and shared prosperity.
As the historic 2020 U.S. presidential election draws nearer, voters are taking stock of the impact the COVID-19 pandemic has had on their lives and livelihoods, and demanding that policymakers present their plans for economic recovery. In this Kenan Insight, we look at the major forces reshaping the U.S. economy and offer suggestions for forging an intentional and equitable path forward.
Research from UNC Kenan-Flagler Finance Professor Eric Ghysels attaches explicit costs to a model’s classification errors, in this case concerning pretrial detention decisions, avoiding the one-size-fits-all symmetrical cost function of traditional machine learning.
Our American Growth Project examination of skills in the workforce begins with a discussion of why skills are difficult to measure, then moves to a broad look at two ways to estimate the skill level across our Extended Metropolitan Areas.
While access and quality of healthcare in the U.S. are shaped by several factors—location, work, insurance—a simple change can make a big difference for patients. According to a new study led by the institute-affiliated Center for the Business of Health Faculty Director Brad Staats, delivering mental and physical care at the same location can improve patient experience and care efficiency. This week’s Kenan Insight offers a chance for our experts to explore the findings of this new study.
The COVID-19 pandemic increased economic inequities in a number of ways, including in access to external capital – and while 2020 marked a break-out year for venture-backed firms, the pandemic hit many main street businesses hard. In this Kenan Insight, we explore the forces driving the haves and have-nots in this new economic climate, as well as actionable policy solutions as government support programs wind down.
When the human mind is free to roam, its subjective experience is characterized by a continuously evolving stream of thought. Although there is a technique that captures people’s streams of free thought—free association—its utility for scientific research is undermined by two open questions: (a) How can streams of thought be quantified? (b) Do such streams predict psychological phenomena?
The challenge for public health officials is to detect an emerging foodborne disease outbreak from a large set of simple and isolated, domain-specific events. These events can be extracted from a large number of distinct information systems such as surveillance and laboratory reporting systems from health care providers, real-time complaint hotlines from consumers, and inspection reporting systems from regulatory agencies. In this paper we formalize a foodborne disease outbreak as a complex event and apply an event-driven rule-based engine to the problem of detecting emerging events. We define an evidence set as a set of simple events that are linked symptomatically, spatially and temporally. A weighted metric is used to compute the strength of the evidence set as a basis for response by public health officials.
While the COVID-19 pandemic was devastating for many, research shows its impact was not felt equally. Black Americans experienced disproportionate health and economic ramifications, which compounded the financial, social and psychological strain many felt pre-pandemic, and have contributed to growing inter-generational wealth disparities. In today’s Kenan Insight, our experts explore whether the multi-trillion dollar “Build Back Better” plan proposed by the Biden administration holds the potential to begin closing pervasive gaps in American society.
The coronavirus pandemic has been especially traumatic on our country’s African American working poor. From being disproportionately concentrated in low-wage hospitality and service sector jobs to struggling with caregiving and food insecurity issues due to shuttered daycare facilities and food banks, working-poor African Americans are facing an inequitable share of financial, social and psychological challenges. What can be done to ease the burdens of working-poor African Americans, both during the pandemic and moving forward? In this Kenan Insight, Urban Investment Strategies Center Director and William R. Kenan Jr. Distinguished Professor of Strategy and Entrepreneurship Jim Johnson invokes a little-known federal program, the Southeast Crescent Regional Commission (SCRC), as part of a strategic response to providing a coherent, place-based development plan.
In our previous Kenan Insight, we outlined the major findings in our recent report, Seven Forces Reshaping the Economy. This week, we explore how the COVID-19 pandemic has upended education and childcare, ushering in changes to both that will last far beyond the current crisis.