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Integrating Community and Clinical Data to Assess Patient Risks with A Population Health Assessment Engine (PHATE)

Introduction Variation in social determinants of health (SDH) contributes to pervasive health disparities. Although aware of their impact, clinicians are uncertain how to ask about the SDH needs of individuals, question the accuracy of patients’ responses, and lack resources to address identified needs. In response, others have proposed using small-area SDH indices in place of or in addition to individual SDH data. These neighborhood indices have been conceptually tested as Community Vital Signs (CVSigns). The Institute of Medicine recommended that neighborhood and clinical data from electronic health records (EHRs) should be integrated in a single or shared platform. The Population Health Assessment Engine (PHATE; pricing information is available at www.primeregistry.org/phate) builds on this recommendation by combining CVSigns and clinical records to define clinical service areas and characterize communities. In the following paragraphs, we describe how PHATE contributes to public health surveillance, helps providers organize care around hot spots, allows for patient risk assessment, and connects practices with community organizations. PHATE’s CVSigns is based on ecological SDH organized as a social deprivation index—a small area index associated with poor health outcomes, disease prevalence, and increased costs. This integration provides a reliable first-pass assessment of patient risks based on where they live. This article was externally peer reviewed. Submitted 7 June 2019; revised 19 December 2019; accepted 21 December 2019. From Long School of Medicine, University of Texas Health San Antonio, San Antonio (PGB); Department of Health Systems and Population Health Sciences, University of Houston College of Medicine (WL); American Board of Family Medicine, Lexington, KY (RLP, AB). Funding: PHATE, and the related curriculum, are funded by the American Board of Family Medicine Foundation as is the scholar program that supported the corresponding author. Conflicting and Competing Interests: Drs. Phillips and Bazemore are employed by the American Board of Family Medicine. Dr. Liaw has received funding from the American Board of Family Medicine. Corresponding author: Pavela G. Bambekova, BS, School of Medicine, University of Texas Health San Antonio, 2722 Prague, San Antonio, TX 78230 (E-mail: Bambekova@ livemail.uthscsa.edu)


Introduction
Variation in social determinants of health (SDH) contributes to pervasive health disparities. Although aware of their impact, clinicians are uncertain how to ask about the SDH needs of individuals, question the accuracy of patients' responses, and lack resources to address identified needs. 1 In response, others have proposed using small-area SDH indices in place of or in addition to individual SDH data. 2 These neighborhood indices have been conceptually tested as Community Vital Signs (CVSigns). 3 The Institute of Medicine recommended that neighborhood and clinical data from electronic health records (EHRs) should be integrated in a single or shared platform. 3 The Population Health Assessment Engine (PHATE; pricing information is available at www.primeregistry.org/phate) builds on this recommendation by combining CVSigns and clinical records to define clinical service areas and characterize communities. In the following paragraphs, we describe how PHATE contributes to public health surveillance, helps providers organize care around hot spots, allows for patient risk assessment, and connects practices with community organizations. PHATE's CVSigns is based on ecological SDH organized as a social deprivation index-a small area index associated with poor health outcomes, disease prevalence, and increased costs. 3 This integration provides a reliable first-pass assessment of patient risks based on where they live.

Using PHATE to Practice Community-Oriented Primary Care
The creation of federally qualified health centers can be traced back to community-oriented primary care (COPC), a model that addresses SDH through community engagement and integration of public health and primary care. 4 In addition to a payment system that rewards volume over value, COPC adoption has historically been limited by technological challenges, including inadequate tools and data to define the service areas of practices, the first step in COPC. 4 The Health Resources and Services Administration Uniform Data Set Mapper (www.udsmapper.org) tool successfully overcame these challenges by using geographic retrofitting to identify service areas for federally qualified health centers. 5 PHATE opens up this technology to front-line clinicians at a time when value-based payment models strive to achieve a balance between efficiency and effectiveness while promoting enhanced population health management and systemic reduction of health care costs for both populations and individuals.

A New Paradigm for Care Delivery Built on COPC
PHATE is a tool that allows clinicians to build on COPC principles and forge new models for how care is delivered. Using data from the American Board of Family Medicine's PRIME Registry, PHATE geocodes patient addresses to define a clinic's service area and a patient's CVSigns, directly addressing the National Academy of Medicine's call for inclusion of SDHs into EHRs. PHATE also uses addresses, diagnoses, and quality measures to geospatially identify hotspots of disease prevalence and poor control ( Figure 1). Through these functions, PHATE transforms care delivery at several levels [Insert Table 1].

Adjusting Payment and Quality Measures
With the ascension of value-based payment, providers may be reluctant to care for patients with social risk factors. In response, efforts are underway to adjust payment and measurement to account for these risks. For example, at the state level, policy makers in Ohio, Massachusetts, and Minnesota are developing approaches to accomplish this goal. At the federal level, a report from the Assistant Secretary for Planning and Evaluation calls for adjustments in payment that reward achievement or improvement in beneficiaries with social risk factors, although the details for how this will be accomplished have yet to be defined. 6 The CVSign within PHATE could support adjustment, as is done in the United Kingdom and New Zealand. 2 PHATE could also adjust quality measures. Minorities have poorer outcomes due to higher levels of medical risk, worse living environments, and greater challenges in adherence and lifestyle; 6 at the same time, providers serving these beneficiaries may have poorer performance due to fewer resources, more challenging clinical workloads, and lower levels of community support. 1 Adjusting payments without adjusting measures would put practices with disadvantaged patients at risk for receiving enhanced resources and having have them taken away for poor quality. 2 PHATE supports measure adjustments within PRIME while also identifying equity gaps that need improvement.

Public Health Surveillance
Federal, state, and local public health departments use clinical data to assist in disease surveillance. These partnerships help generate real-time data and small-area estimates. Currently, public health departments use national surveys, such as the Behavioral Risk Factor Surveillance System, to monitor disease and health behaviors, but unfortunately, the Behavioral Risk Factor Surveillance System is limited by cost, reliance on self-report, and telephone access. Registries with tools like PHATE can provide additional public health data, including diagnosis codes, medications, laboratory values, and SDH information.
Organizing Care around Hot Spots Public health departments are starting to use geographic variation in health care to identify hot spots-clusters of high-need, high-cost patientsand inform targeted interventions. Cincinnati's Community Health Assessment found a 20-year variation in life expectancy across neighborhoods. In response, the Cincinnati Health Department partnered with community organizations to develop strategies for at-risk neighborhoods. 7 Cincinnati pediatricians identified geospatial patterns for hospitalizations, and armed with these data, they reorganized care delivery. Specifically, they received alerts when patients from specific neighborhoods were admitted and deployed comprehensive care teams to address social needs and transitional care support.
By identifying disease and poor-quality clusters, PHATE allows primary care teams to similarly reorganize care to address hot spots.
Assessing Patient Risk PHATE's merger of EHR and neighborhood data allows for the incorporation of geography to improve risk assessment for patients. For example, Lichkus references PHATE's applicability in identifying the geographic distribution of patients who screen positive for food insecurity. 8 PHATE, therefore, allows for a better understanding of neighborhoods with greater risk of food insecurity and other risks in local communities. A good understanding of risks will allow providers and public health officials to investigate why some locations experience a differential burden; it will also encourage collaboration with local organizations to improve access to services.

Connecting with Community Organizations
PHATE coordinates work at patient and community levels, fulfilling the National Academy of Figure 1. Population Health Assessment Engine (PHATE) uses patient addresses, diagnoses, and quality measures to geospatially identify hotspots, or clusters, of disease prevalence or poor disease control. This is a heatmap of individuals not up to date with depression screening, from the PHATE Demo Dataset. Medicine's call to integrate primary care and public health. More specifically, clinics can use PHATE to help public health officials identify high-risk populations and allocate resources. PHATE can also be used as a visualization tool to incentivize third parties like insurance companies to invest in community improvement projects. Aunt Bertha-a free, online national directory of community resourcesis integrated into PHATE, thereby allowing practices to make community connections.

Preparing the Workforce for a New Paradigm
Teaching the next generation of clinicians to succeed in addressing patients' SDH will require training. The Robert Graham Center and HealthLandscape developed a curriculum to help learners understand how to bring together community data, clinical data, and community resources by using PHATE. Relatedly, residencies lack strategies for meeting population health training milestones. PHATE can transform the delivery of care and how trainees learn about population health [Insert Table 2].

Conclusions
PHATE provides an innovative way to integrate neighborhood and EHR data, allowing users to adjust payment, contribute to public health surveillance, organize care around hot spots, assess patient risk, and connect with community organizations. PHATE is a tool that can reduce clinical burden, support intrinsic interest in addressing SDH, and train the next generation of clinicians. Working across various registries and EHRs, PHATE would benefit from further evaluation of its utility for education and clinical care. PHATE can be used as a primary screening tool to identify patients at risk for adverse health outcomes; once identified, patients can be further screened to determine the effect their SDH have on their health outcomes. For example, knowing that a given community has a high crime rate can prompt a physician to ask patients about the level of safety they experience in their homes.
Collaborates with the participants necessary to address important health problems for both individuals and communities. PHATE helps identify community partners like food banks, housing and transportation services, and education resources. Mobilizes team members and links patients with community resources to achieve health promotion and disease prevention.
Community health workers and case managers can connect patients with unmet social needs with community resources through Aunt Bertha.
Lists ways in which community characteristics and resources affect the health of patients and communities.
Clinicians can look at maps of their service areas, which help them have a visual representation of the neighborhood deprivation within the local community.
Recognizes inefficiencies, inequities, variation, and quality gaps in health care delivery.
The hot spotting tool displays, geospatially, clusters of patients with gaps in quality or poor disease control. Integrates practice and community data to improve population health.
Once clusters are identified, PHATE helps clinicians identify risk factors that can account for or address hot spots.
PHATE, Population Health Assessment Engine; SDH, social determinants of health.