Skip to main content

Main menu

  • HOME
  • ARTICLES
    • Current Issue
    • Ahead of Print
    • Archives
    • Abstracts In Press
    • Special Issue Archive
    • Subject Collections
  • INFO FOR
    • Authors
    • Reviewers
    • Call For Papers
    • Subscribers
    • Advertisers
  • SUBMIT
    • Manuscript
    • Peer Review
  • ABOUT
    • The JABFM
    • Editorial Board
    • Indexing
    • Editors' Blog
  • CLASSIFIEDS
  • Other Publications
    • abfm

User menu

  • Log out

Search

  • Advanced search
American Board of Family Medicine
  • Other Publications
    • abfm
  • Log out
American Board of Family Medicine

American Board of Family Medicine

Advanced Search

  • HOME
  • ARTICLES
    • Current Issue
    • Ahead of Print
    • Archives
    • Abstracts In Press
    • Special Issue Archive
    • Subject Collections
  • INFO FOR
    • Authors
    • Reviewers
    • Call For Papers
    • Subscribers
    • Advertisers
  • SUBMIT
    • Manuscript
    • Peer Review
  • ABOUT
    • The JABFM
    • Editorial Board
    • Indexing
    • Editors' Blog
  • CLASSIFIEDS
  • JABFM On Twitter
  • JABFM On YouTube
  • JABFM On Facebook
Research ArticleSpecial Communications

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

Pavela G. Bambekova, Winston Liaw, Robert L. Phillips and Andrew Bazemore
The Journal of the American Board of Family Medicine May 2020, 33 (3) 463-467; DOI: https://doi.org/10.3122/jabfm.2020.03.190206
Pavela G. Bambekova
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).
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Winston Liaw
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).
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Robert L. Phillips Jr.
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).
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Andrew Bazemore
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).
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • References
  • Info & Metrics
  • PDF
Loading

Abstract

Clinicians are concerned about their patients' social determinants of health (SDH); yet, they are unsure how to effectively gather patient-level SDH data and intervene without adding to current administrative burdens. Designed properly, clinical registries offer solutions to integrate neighborhood SDH data with clinical data from electronic health records, enabling the understanding of community factors to guide patient care. Federal and state interest in adjusting reimbursements based on SDH further underscores the need for strategies that integrate SDH and clinical data. The Population Health Assessment Engine (PHATE) exemplifies a registry-based SDH data integration solution that adjusts payments, contributes to public health surveillance, organizes care around hot spots (gaps in quality or uncontrolled disease), assesses patient risk, and connects with community organizations. PHATE also permits residency training to meet community health competency milestones by incorporating the PHATE curriculum. These functions enhance value, and their utility in education and care delivery would benefit from further investigation.

  • Electronic Health Records
  • Patient Care
  • Population Health
  • Public Health Surveillance
  • Registries
  • Social Determinants of Health

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].

Figure 1.
  • Download figure
  • Open in new tab
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.

View this table:
  • View inline
  • View popup
Table 1.

How the Population Health Assessment Engine Can Be Used to Improve Health

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 patients—and 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 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 resources—is 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].

View this table:
  • View inline
  • View popup
Table 2.

How the Population Health Assessment Engine Can Be Used to Meet Training Milestones

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.

Acknowledgments

The authors thank Jennifer Rankin (HealthLandscape) for her contributions to the PHATE curriculum and Yan Barnett and Chris Barnett (University of Missouri) for their contributions to the development of PHATE.

Notes

  • This article was externally peer reviewed.

  • 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.

  • 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.

  • To see this article online, please go to: http://jabfm.org/content/33/3/463.full.

  • Received for publication June 7, 2019.
  • Revision received December 19, 2019.
  • Accepted for publication December 21, 2019.

References

  1. 1.↵
    1. Tong ST,
    2. Liaw WR,
    3. Kashiri PL,
    4. et al
    . Clinician experiences on screening for social needs in primary care. J Am Board Fam Med 2018;31:351–63.
    OpenUrlAbstract/FREE Full Text
  2. 2.↵
    1. Phillips RL,
    2. Liaw W,
    3. Crampton P,
    4. et al
    . How other countries use deprivation indices—and why the United States desperately needs one. Health Aff (Millwood) 2016;35:1991–8.
    OpenUrlAbstract/FREE Full Text
  3. 3.↵
    1. Bazemore AW,
    2. Cottrell EK,
    3. Gold R,
    4. et al
    . “Community vital signs”: incorporating geocoded social determinants into electronic records to promote patient and population health. J Am Med Inform Assoc 2016;23:407–12.
    OpenUrlCrossRefPubMed
  4. 4.↵
    1. Tollman SM
    . The Pholela Health Centre—the origins of community-oriented primary health care (COPC). An appreciation of the work of Sidney and Emily Kark. S Afr Med J 1994;84:653–8.
    OpenUrlPubMed
  5. 5.↵
    1. Mullan F,
    2. Phillips RL,
    3. Kinman EL
    . Geographic retrofitting: a method of community definition in community-oriented primary care practices. Fam Med 2004;36:440–6.
    OpenUrlPubMed
  6. 6.↵
    Office of the Assistant Secretary for Planning and Evaluation. Social risk factors and performance under Medicare's value-based purchasing programs. Washington, DC: US Department of Health and Human Services; 2016.
  7. 7.↵
    Community Health Assessment. City of Cincinnati Health Commissioner's Accreditation Lead Team. 2017. Community Health Assessment. Available from: https://www.cincinnati-oh.gov/health/assets/File/EDIT%20THIS%20CHA_12_21_17%20FINAL.pdf.
  8. 8.↵
    1. Lichkus J,
    2. Liaw WR,
    3. Phillips RL
    . Utilizing PHATE: a population health-mapping tool to identify areas of food insecurity. Ann Fam Med 2019;17:372.
    OpenUrlFREE Full Text
PreviousNext
Back to top

In this issue

The Journal of the American Board of Family     Medicine: 33 (3)
The Journal of the American Board of Family Medicine
Vol. 33, Issue 3
May/June 2020
  • Table of Contents
  • Table of Contents (PDF)
  • Cover (PDF)
  • Index by author
  • Back Matter (PDF)
  • Front Matter (PDF)
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on American Board of Family Medicine.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Integrating Community and Clinical Data to Assess Patient Risks with A Population Health Assessment Engine (PHATE)
(Your Name) has sent you a message from American Board of Family Medicine
(Your Name) thought you would like to see the American Board of Family Medicine web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
5 + 14 =
Solve this simple math problem and enter the result. E.g. for 1+3, enter 4.
Citation Tools
Integrating Community and Clinical Data to Assess Patient Risks with A Population Health Assessment Engine (PHATE)
Pavela G. Bambekova, Winston Liaw, Robert L. Phillips, Andrew Bazemore
The Journal of the American Board of Family Medicine May 2020, 33 (3) 463-467; DOI: 10.3122/jabfm.2020.03.190206

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Integrating Community and Clinical Data to Assess Patient Risks with A Population Health Assessment Engine (PHATE)
Pavela G. Bambekova, Winston Liaw, Robert L. Phillips, Andrew Bazemore
The Journal of the American Board of Family Medicine May 2020, 33 (3) 463-467; DOI: 10.3122/jabfm.2020.03.190206
Reddit logo Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • Introduction
    • Using PHATE to Practice Community-Oriented Primary Care
    • A New Paradigm for Care Delivery Built on COPC
    • Preparing the Workforce for a New Paradigm
    • Conclusions
    • Acknowledgments
    • Notes
    • References
  • Figures & Data
  • Info & Metrics
  • References
  • PDF

Related Articles

  • No related articles found.
  • PubMed
  • Google Scholar

Cited By...

  • HOW THE ABFM WILL ADDRESS HEALTH EQUITY
  • Well-Being, New Technologies, and Clinical Evidence for Family Physicians
  • Google Scholar

More in this TOC Section

  • Primary Care Is an Essential Ingredient to a Successful Population Health Improvement Strategy
  • Hepatitis C Update and Expanding the Role of Primary Care
Show more Special Communications

Similar Articles

Keywords

  • Electronic Health Records
  • Patient Care
  • Population Health
  • Public Health Surveillance
  • Registries
  • Social Determinants of Health

Navigate

  • Home
  • Current Issue
  • Past Issues

Authors & Reviewers

  • Info For Authors
  • Info For Reviewers
  • Submit A Manuscript/Review

Other Services

  • Get Email Alerts
  • Classifieds
  • Reprints and Permissions

Other Resources

  • Forms
  • Contact Us
  • ABFM News

© 2023 American Board of Family Medicine

Powered by HighWire