Developing a Social Determinants of Health Common Data ... · •Builds patient-provider...

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Developing a Social Determinants of Health Common Data Model for PRAPARE (Protocol for Responding to and Assessing Patient Assets, Risks,

and Experiences) Session 213, February 14, 2019

Andrew Hamilton, Chief Informatics Officer, AllianceChicago

Rosy Chang Weir, Director of Research, Association of Asian Pacific Community Health Organizations

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Andrew Hamilton, RN, BSN, MS

Rosy Chang Weir, PhD

Have no real or apparent conflicts of interest to report.

Conflict of Interest

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Learning Objectives

• Describe the process for creating a CHC common data model including SDOH data elements

• Discuss how a CHC common data model will be used to improve the representation of under-represented communities in health services research

• Discuss aspects of the proposed data model, including key value-sets related to social and economic risk factor data and how those data elements related to existing/emerging common data models

• Describe the PRAPARE protocol and the importance of standardized collection of SDOH data

• Discuss how the PRAPARE data model relates to other tools utilized to collect social and economic risk factor data

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Bay Area regional Health Inequities Initiative (BARHII). 2008. “Health Inequities in the Bay Area”, accessed November 28, 2012 from http://barhii.org/resources/index.html.

Why Collect Data on Social Determinants of Health (SDH)?

How well

do we

know our

patients?

Are services

addressing

SDH

reimbursed

and/or

sustainable?

Are

community

partnerships

adequate and

integrated?

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What is PRAPARE?

Protocol for Responding to & Assessing Patients’ Assets, Risks & Experiences:

A national standardized patient risk assessment protocoldesigned to engage patients in assessing & addressing social determinants of health (SDH).

PRAPARE = SDH screening tool + implementation/action process

Created by: National Association of Community Health Centers, Association of Asian Pacific Community Health Organizations, Oregon Primary Care Association, Institute for Alternative Futures in partnership with others, including AllianceChicago

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Community Health Centers Today

Largest national network of primary/preventive care

•27+ million patients at 10,400+ sites

• 1 in 12 US residents

• 1 in 6 Medicaid beneficiaries

• 1 in 3 low income, uninsured

• 1 in 3 people in poverty

• 1 in 3 racial/ethnic minority individuals in poverty

• 1.3 million homeless persons

• 965,000+ migrant farmworkers

1400 Health Center Orgs.

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Health Center Model of Care

• Community governance

• Located in/serve federally-designated medically underserved

areas

• Non-profit, must be open to all

• Comprehensive health services

– Care team, care integration, community partners

– “Enabling” and social services

• Community needs assessments

• Strict performance/accountability standards

– Quality Improvement/Assurance Plans

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• FREE EHR Templates Available*:

– NextGen

– eClinical Works

– GE Centricity

– Epic

– Cerner*

– Greenway Intergy

– Meditab

Available for FREE after signing EULA at www.nachc.org/prapare

• In development:

– Greenway Success

EHS

– Allscripts

– Athena

– Meditech

8 PRAPARE EHR Templates

70% of all health

centers

Current 7 + New EHRs =

85-95% of all health centers

* Automatically map to ICD-10 Z codes so you can easily add relevant Z codes to problem or diagnostic list

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PRAPARE Domains

Publication pending. Do not quote or

distribute without permission from NACHC.

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PRAPARE’s Unique Design

• STANDARDIZED and WIDELY USED– Measures Linked with standardized codes

• EVIDENCE-BASED and STAKEHOLDER-DRIVEN

• FREE EHR Templates: eClinicalWorks, Epic, NextGen, GE

Centricity, +

• FREE PRAPARE Implementation and Action

Resources

• WORKFLOW AGNOSTIC– Can fit within existing workflows and be combined with

other tools/data

• PATIENT-CENTERED and ACTIONABLE– Actionable at patient and population level

– Meant to facilitate conversations and build relationships with

patients

– Standardize the need rather than the question

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Pilot Results (2015 and 2017)

• Easy to administer

• Possible to implement using various workflows and staffing models

• Builds patient-provider relationship

• Identifies new needs

• Leads to positive changes at the patient, health center, and community/population levels

• Facilitates collaboration with community partners

• Importance of targeted messaging and staff support

Publication pending. Do not quote or

distribute without permission from NACHC.

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0%

5%

10%

15%

20%

25%

30%

35%

0 1 2 3 4 5 6 7 8 9 10111213141516171819202122

Tally Score

Alliance/Iowa Waianae New York Oregon Total3 CHCs 1 CHC 2 CHCs 1 CHC 7 CHCs

Percent of Patients with Number* of SDH “Tallies”

N = 2,694 patients for all teams

* Excludes

low income

This health center pilot

population had highest burden

of chronic illness.

Publication pending. Do

not quote or distribute

without permission from

NACHC.

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Positive Correlation Between SDH Factors* and Hypertension: All Teams

0%

10%

20%

30%

40%

50%

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Tally Score

% of POF % of the tally score with Hypertension

r = 0.61

*Excludes low income

Publication pending. Do not quote or

distribute without permission from NACHC.

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BOTH are necessary to:

• Demonstrate value to payers

• Advocate for upstream investments

• Seek adequate financing to ensure interventions are sustainable

• Achieve integrated, value-driven delivery system and reduce total costof care

Importance of Social Determinants

Intervention & Enabling Services Data

NEED DATA • Standardized data on patient social risk /barriers (PRAPARE)

RESPONSE DATA

• Standardized data

on interventions

(Enabling Services +

others)

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Examples of Using PRAPARE Data

• Patient-level improvements:

– Matching Rx and Tx plans to patient circumstances

– In-house and community assistance programs

• Organizational and Community level actions

– Expand enabling services

– Mobile outreach

– Prioritize development of community partnerships

– Referral resource guides and referral networks

– Risk segmentation and stratification

• System level

– Payer and delivery system partner engagement

– Alternative payment methodologies Publication pending. Do not

quote or distribute without

permission from NACHC.

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Inform Care and Services:

Inform services provided in Collaborative

Consortia Model and Co-Location Model

Build/strengthen partnerships with local

orgs. Ex: Negotiate bulk discounts and new

bus routes with local transportation agency

Build on SDH and “Touches” work

Inform Payment

Guide work of co-located foundation to pay

for non-clinical services

Inform both

Medicaid and

Medicare ACO

discussions and

care management

policies

Inform payment

reform discussions

with state Medicaid

agency

Inform Risk

Adjustment

Create SDH risk

score for risk

stratification and

risk adjustment

Streamline and expand care management

plans

Assign weights: Put

every PRAPARE

element in

regression model

with certain

outcome or cost

Inform APM

discussions at

state level

Ways to Use PRAPARE Data

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PRAPARE-Interventions/ES Conceptual framework

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Appropriate Care(e.g., HbA1c test, preventive

vaccinations)

Health Outcomes

(e.g., HbA1c level, ED

visits)

Enabling Services & other non-clinical SDH interventions

Social Determinants of

Health

(PRAPARE)

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Example of Risk Stratification Using PRAPARE Data

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• 1,000+ downloaded a PRAPARE EHR template, but reach is higher

• Not just health centers

– Hospitals, health systems, ACOs, payers, population health vendors

• State-based spread activities

• Happy to work with new vendors and partners!

– Please reach out to NACHC before you get started

19 PRAPARE Reach as of Jan 2018

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Key Challenges in Standardizing Data on Patient Social Risks

• Growing awareness of the impact of social and economic factors impacting health has lead to development of several screening tools & innovative clinical interventions

• Scaling the screening and clinical intervention efforts remains difficult:

– Lack of existing data and data value sets to accelerate interoperability

– Misaligned incentives (fee for medical service)

– Healthcare workforce competent in addresses social care needs

– Fragmentation of clinical and social care services

22Also includes neighborhood and optional questions (incarceration history, refugee status,

safety, domestic violence).

SDOH Data Elements in National Data Programs

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HIT Vendor Response by Type

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Vendor Practices

Freij M, Dullabh P, Hovey L, Leonard J, Card A, Dhopeshwarkar R. Incorporating

Social Determinants of Health in Electronic Health Records: A Qualitative Study of

Perspectives on Current Practices among Top Vendors. Washington, DC: U.S.

Department of Health and Human Services Office of Health Policy; 2018.

Motivation to Support Collection of

SDOH Data

• Requests by Customers

• Data for Performance Improvement

• ONC Certification Requirements

Key Challenge:

• Lack of National Data Standards

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Value Sets

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http://sirenetwork.ucsf.edu/sites/sirenetwork.ucsf.edu/files/Compendium%20Social%20Risk%20Factors%20Codes%206.20.18.xlsx

Compendium of Medical Terminology for Social Risk Factors

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• Summary of Care

• Population Health

• Health Information Exchange

• Data/Analytics & Predictive Model

• Research

Interoperability of SDH data

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After Visit Summary & Care Coordination

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Pop Health and SDH data

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Pop Health and SDH data

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Diabetes Screening: Traditional Approach

* A project in partnership with the University of

Chicago Data Science for Social Good Program

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Predictive Analytics

SDH Data

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SDH Data in Predictive Models

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Predictive Model Outperforms USPSTF

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Distributed Research Network

Facilitate multisite research collaborations between investors and data stewards by creating secure networking capabilities and analysis tools

– Ability to work with analysis-ready datasets

– Standardized data using a common data model

– Data stewards keep and analyze their own data

– Provide results (not full set) of raw data to requestor

– All activities audited and secured

NIH Webinar: https://www.nihcollaboratory.org/Pages/distributed-research-

network.aspx

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Common Data Model - PCORnet

https://pcornet.org/pcornet-common-data-model/

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• Strengthening Public Health through National Partnerships

• 39 Funded Agencies including NACHC

• CDC & NACHC Clinical Focus:

o Cardiac Disease

o Hepatitis B & C

o Family Planning

o Post-Partum Diabetes

o Adult Vaccination

CDC & NACHC: Essential Public Health Services

https://www.cdc.gov/publichealthgateway/partnerships/capacity-building-

assistance-OT18-1802.html

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HCV Care Cascade

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• Collecting SDH data in the healthcare setting is possible, however requires thoughtful consideration in terms of workflow as well as staff and patient education

• There are several SDH screening tools, however, data standards are not fully defined, therefore interoperability of these data continues to be a challenge

• HIT vendors are beginning to incorporate SDH data

• There are several use cases related to SDH data including point of care, population health, decision support, research and public health

• As SDH data standards are developed, existing shared data models will need to be updated to include these data

Summary

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Acknowledging Our Funders

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Questions

Andrew Hamilton, RN, BSN, MS

Chief Informatics Officer/Deputy Director

AllianceChicago

312.267.2017

ahamilton@alliancechicago.org

Rosy Chang Weir, PhD

Director of Research

Association of Asian Pacific Community Health Organizations

510-272-9536

rcweir@aapcho.org

To sign up for the PRAPARE listserv, email prapare@nachc.org