# ASCEND: ApproacheS to CHC ImplEmeNtation of SDH Data Collection and Action

> **NIH NIH R18** · KAISER FOUNDATION RESEARCH INSTITUTE · 2021 · $689,379

## Abstract

PROJECT SUMMARY/ABSTRACT: Health risks, outcomes, and care quality for people with / at risk for
diabetes mellitus (DM) are profoundly affected by non-clinical factors called ‘social determinants of health’
(SDH). Diverse public health leaders and initiatives – including the Institute of Medicine, the Office of the
National Coordinator for Health Information Technology, the Medicare Access & CHIP Reauthorization Act of
2015, and the Centers for Medicare & Medicaid Services 2016 Quality Strategy – emphasize the importance
of documenting patients’ SDH data in electronic health records (EHRs), and using this data to inform care.
However, little is known about how to help primary care teams routinely collect and act on SDH data using
EHR-based tools. This knowledge gap is particularly problematic for the community health centers (CHCs)
serving our nation’s most vulnerable patients, whose DM prevalence and risk (notably, obesity rates) are
higher than the general population’s, and whose health is particularly impacted by SDH. The proposed trial
builds on an NIDDK-funded pilot study in which we developed a suite of EHR-based SDH data management
tools for primary care CHCs. In June 2016, these tools went live in 440 CHCs that are located in 19 states,
but share a centrally-managed EHR. Having demonstrated that ‘SDH data tools’ can be built for CHCs, we
now propose to assess: whether and how pragmatic implementation strategies that support other
types of practice change will also help CHC teams systematically identify and take action on the
SDH-related needs of adult patients with / at risk for DM; and, the impact of doing so on DM risk
management. We will do this as follows. Step 1: Evaluate current EHR-based SDH data collection in 440
CHCs; use those formative results to hone a set of approaches for helping CHCs routinely collect SDH data
and integrate it into care plans. Step 2: Conduct a pragmatic, stepped-wedge, cluster-randomized trial.
Thirty CHCs will be randomized to one of five 6-month wedges, with staggered timing for receiving the
intervention: a scalable implementation support package including technical assistance, training, and six
months of access to an ‘SDH Implementation Team’ that will tailor support to meet each CHC’s needs. Step
3: Conduct a realist evaluation of how the impact on: (i) integration of SDH data collection into workflows; (ii)
integration of SDH data into care; and (iii) DM risk management (controlled BP, HbA1c, BMI, lipids, etc.; up-
to-date recommended care). Per PAR-15-157, we will test implementation strategies that are pragmatic,
replicable, delivered under routine conditions, use existing resources, and target standard care processes.
Our multidisciplinary team includes experts in SDH, implementation science, informatics, and primary care
transformation. Study deliverables will include scalable strategies; results will inform SDH data collection and
action implementation guidelines and materials for use by CHCs an...

## Key facts

- **NIH application ID:** 10224176
- **Project number:** 5R18DK114701-05
- **Recipient organization:** KAISER FOUNDATION RESEARCH INSTITUTE
- **Principal Investigator:** RACHEL GOLD
- **Activity code:** R18 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $689,379
- **Award type:** 5
- **Project period:** 2017-08-25 → 2023-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10224176

## Citation

> US National Institutes of Health, RePORTER application 10224176, ASCEND: ApproacheS to CHC ImplEmeNtation of SDH Data Collection and Action (5R18DK114701-05). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10224176. Licensed CC0.

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