# U.S. Digital Response SNAP Payment Accuracy Playbook

## Introduction

### Background

[U.S. Digital Response (USDR)](https://www.usdigitalresponse.org/) created this playbook as a resource for Supplemental Nutrition Assistance Program (SNAP) leaders at state and local governments and civic technologists. USDR developed it based on discovery research and insights from eight states from September 2025 through February 2026. This included providing direct, hands-on technical assistance to three states and also interviewing an additional five states regarding their SNAP programs.

### Why does this playbook exist?

This playbook aims to help those responsible for implementing SNAP changes in response to the new Payment Error Rate (PER) cost-sharing provisions required under the [H.R.1 – 119th Congress (2025-2026)](https://www.congress.gov/bill/119th-congress/house-bill/1/text). PER is a metric used to assess how often the state makes accurate determinations about the benefit amount for households.

This playbook focuses on strategies that states can test right away — within weeks or months — to improve payment accuracy and reduce the burden on frontline eligibility workers. We focused on technology and process changes that don’t require changes to current policy (to the best of our knowledge) or expensive new tech investments.

{% hint style="info" %}
**USDR will continue adding to this playbook over time**

This is a **living** document. Since timing to address PER is urgent, USDR will publish findings as we uncover them, iteratively building on this playbook. As of March 2026, this playbook includes research from eight states.
{% endhint %}

{% hint style="success" icon="circle-info" %}
**Have questions or want to collaborate with USDR?**

Find out how in our [Get in touch](https://usdr.gitbook.io/benefits-resource-hub/snap-payment-accuracy-playbook/section-4-get-in-touch) section.
{% endhint %}

### Why now?

Based on discussions with eight states, USDR identified SNAP payment accuracy as an urgent need. The H.R. 1 PER provisions are updated standards that states are measured against when implementing SNAP. In Fiscal Year (FY) 2028, two-thirds of all states will have to pay at least $100 million in additional SNAP funding annually if they don’t reduce PERs 6% or below ([source](https://www.nytimes.com/2025/09/20/us/politics/food-stamps-snap.html)). If state lawmakers can't come up with the money, some states warn they will have to stop offering SNAP altogether.

<figure><img src="https://3888017948-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F-MNjl-2Nbq2ka0VqYZSk%2Fuploads%2FlmKS686ClvVnIn5RsKZL%2Fstats-states-will-have-to-pay-100m.svg?alt=media&#x26;token=770a4a43-ff48-43cd-8071-980bc6ca136a" alt=""><figcaption></figcaption></figure>

States are being forced to make difficult program decisions to reduce PERs. As it exists now, SNAP case processing is highly manual. Eligibility is complex and includes considerations ranging from housing, to work, to Social Security, to how a client heats their home.

State eligibility systems and processes reflect this complexity. It is very common for workers to juggle over a dozen systems, interfaces, manuals, and more, to complete a single client’s case. Based on our hands-on research, USDR found in one state's eligibility system, which generates a large volume of tasks, that one worker had more than 2,000 assigned tasks. SNAP staff across states report feeling overwhelmed with their daily workload.

### USDR’s Theory of Change

USDR believes that **reducing worker burden is a crucial — and often overlooked — aspect of improving SNAP payment accuracy.** Over the course of USDR’s research, we reviewed specifically where frontline SNAP staff encountered barriers that made maintaining quality difficult. We also dug into what drives issues for top categories like income, household, and shelter.

We would like to note upfront that frontline staff are under **tremendous pressure.** We want to help make their jobs more straightforward. We are looking to support states to shape their systems and tooling to **make it easier to be accurate and harder to make mistakes.**

We can help **reduce administrative burden and payment errors** while improving the overall work experience for frontline staff by:

<figure><img src="https://3888017948-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F-MNjl-2Nbq2ka0VqYZSk%2Fuploads%2FSF2eQawG0s1tVd0GubNF%2Fdiagram-theory-or-change-blue.svg?alt=media&#x26;token=61d28aab-d45c-4df8-90be-fc39d549ff94" alt=""><figcaption></figcaption></figure>

As with any changes, each state may come across challenges related to staffing, IT systems, and managing other priorities. Given this, we are not recommending any one set of solutions — rather this playbook shares a menu of different options based on USDR’s research with our state partners. With this flexible approach, we hope to support each state to decide for themselves what changes to make.

&#x20;

***

### How to use this playbook

We have designed this playbook based on questions states may be asking about payment errors:

#### <i class="fa-circle-arrow-right">:circle-arrow-right:</i>  Go to sections

{% content-ref url="section-1-where-should-states-focus-first" %}
[section-1-where-should-states-focus-first](https://usdr.gitbook.io/benefits-resource-hub/snap-payment-accuracy-playbook/section-1-where-should-states-focus-first)
{% endcontent-ref %}

{% content-ref url="section-2-what-can-states-do-now" %}
[section-2-what-can-states-do-now](https://usdr.gitbook.io/benefits-resource-hub/snap-payment-accuracy-playbook/section-2-what-can-states-do-now)
{% endcontent-ref %}

{% content-ref url="section-3-how-can-you-run-a-similar-state-project" %}
[section-3-how-can-you-run-a-similar-state-project](https://usdr.gitbook.io/benefits-resource-hub/snap-payment-accuracy-playbook/section-3-how-can-you-run-a-similar-state-project)
{% endcontent-ref %}

{% content-ref url="section-4-get-in-touch" %}
[section-4-get-in-touch](https://usdr.gitbook.io/benefits-resource-hub/snap-payment-accuracy-playbook/section-4-get-in-touch)
{% endcontent-ref %}

&#x20;

{% hint style="warning" %}
This playbook is **not** an authoritative, legal, or regulatory guidance. It has not been endorsed by USDA or its Food and Nutrition Service (FNS). The playbook is advisory only; states can decide what to adopt for their situations. It is the responsibility of state officials to ensure any implementation of any project is compliant with federal SNAP statute and state policy. Refer to [FNS](https://www.fns.usda.gov/resources?keywords=\&f%5B0%5D=resource_type%3A401) for the latest official guidance. Finally, these recommendations and opinions of USDR do not necessarily reflect the opinions of state participants or stakeholders.
{% endhint %}

{% hint style="info" %}

* **Version published:** March 2026
* **Playbook licensing:** All content in this USDR playbook is available under the [Creative Commons Attribution 4.0 License (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/).
* [**USDR Benefits Response Team**](https://www.usdigitalresponse.org/services/benefits-response) **authors and contributors:** Navin Eluthesen, Amy Meng, María Reyes-Gaskin, and Dillon Vrosh.
* **Acknowledgements:** We would like to thank all of our state partners, with special thanks to the Arizona Department of Economic Security, North Carolina Department of Health and Human Services - Opportunity and Wellbeing, and Maryland Department of Human Services - Family Investment Administration. Your leadership and commitment to preserving SNAP programs and supporting workers and clients is inspiring. We also would like to thank all frontline staff for being generous with their time and sharing their experiences with us. Finally, thank you to all of the USDR volunteers who supported our state sprints and the creation of this playbook with their deep expertise and care: Toni Aguilar, Amanda Bush, Vincent Chin, Bekah Choi, Erin Gamble, Sonia Jacob, Lauren Piedy, Nithika Sanghi, Katrina Sharpe, Patrick Sier, Eric St. Pierre, and Steven Todd.
  {% endhint %}

&#x20;
