Systematic Analysis of Housing Referral Outcomes in New York City's WholeYouNYC Social Care Network: Identifying Barriers to Service Connection

This mixed-methods study of 4,258 housing referrals within New York City's WholeYouNYC network reveals a 45% acceptance rate and identifies systemic barriers such as CBO response delays, missing documentation, and client engagement challenges, prompting recommendations for standardized protocols and automated follow-ups to improve service connection.

The Gist

Imagine New York City's Social Care Network (SCN) as a massive, high-tech mailroom designed to help people who are struggling to find a place to live. In this mailroom, "Social Care Navigators" act as the mail carriers. Their job is to take a request from a person in need (a "referral") and deliver it to a Community-Based Organization (CBO)—like a shelter or a housing agency—that might have an empty room or a rental voucher available.

This paper is a report card on how well that mailroom is actually working. The authors looked at 4,258 letters (housing referrals) sent between June 2025 and January 2026 to see what happened to them.

Here is the breakdown of what they found, using simple analogies:

1. The "Half-Empty" Success Rate

Out of every 100 letters the mailroom sent out, only 45 got a "Yes" from the housing agencies.

• 45 letters were accepted (the person got a lead on housing).
• 19 letters were rejected (the agency said "no," usually because the person didn't qualify).
• 32 letters just sat in a "black hole." They were sent, but the housing agency never replied, accepted, or rejected them. They were just... ignored.
• 3 letters were still being looked at.

The authors found that this 45% success rate was the same whether they sent the letter to a huge agency or a small one. This suggests the problem isn't that specific agencies are bad at their jobs; it's that the whole system is clogged.

2. The Three "Traffic Jams"

The researchers talked to the mail carriers (the staff) and looked at the workflow to find out why so many letters weren't getting through. They found three major traffic jams:

• Jam #1: The Silent Phone (Delayed Responses)
  Imagine sending a text message to a friend and waiting weeks for a reply. That's what happens here. 32% of the referrals sat in "Sent" status with no answer. The housing agencies are often too busy or understaffed to reply quickly. The study found that when a referral does get accepted, the waiting time for that reply takes up nearly half of the total time it takes to get help.
• Jam #2: The Missing Puzzle Pieces (Incomplete Paperwork)
  To get a housing referral accepted, you need specific documents (proof of income, eviction history, etc.). Often, the mail carrier sends the letter without all the puzzle pieces because they don't know exactly which pieces the housing agency needs until after they've already sent the letter. This causes a game of "back-and-forth" where the carrier has to chase the client for more papers, adding about 8 days of delay every time.
• Jam #3: The Moving Target (Client Engagement)
  This is the hardest part. The people needing help are often in crisis. Their phones might be disconnected, they might not have a stable address, or they are so focused on surviving the day (finding food, staying safe) that they can't answer the mail carrier's calls. The housing agencies often reject referrals simply because they couldn't reach the person. The paper notes this isn't the mail carrier's fault; it's the nature of the crisis.

3. The "Stuck in Traffic" Problem

The study looked at the 1,382 letters that were "stuck" (sent but no response).

• On average, these letters had been sitting there for 45 days.
• Some had been sitting there for 62 days.
• The worst-case scenario? One letter had been sitting in the system for 271 days (more than nine months) with no one ever answering.

The authors describe this as a "black hole" where people in need are left waiting indefinitely, with no idea if they will ever get help.

4. What Can Be Done? (The Recommendations)

The paper suggests that to fix this, the mailroom needs to change its rules, not just work harder:

• Set a "Reply by" Rule: Housing agencies should be held accountable for replying within a set time (like 5 or 10 days). If they don't, the system should automatically send a reminder.
• The "Checklist" Fix: Create a clear list of documents needed before the letter is sent, so the mail carrier doesn't have to guess.
• Better Ways to Reach People: Since people in housing crises are hard to reach by phone, the system needs to try different methods (text, in-person visits, etc.) to make sure the client is actually part of the process.

The Big Picture

The authors conclude that while fixing the paperwork and the phone calls will help, there is one thing the mailroom cannot fix: There simply aren't enough houses.

Even if the mailroom becomes perfect and 100% of the letters get answered, if there are 1,000 people needing homes but only 400 empty rooms, 600 people will still be turned away. The system needs better coordination (fixing the traffic jams) and more houses (fixing the supply).

In short: The system is trying to help, but it's bogged down by slow replies, missing paperwork, and the difficulty of reaching people in crisis. The data shows that without fixing these specific bottlenecks, many people in New York City are left waiting in the dark for months.

Technical Summary

Technical Summary: Systematic Analysis of Housing Referral Outcomes in NYC SCN

Problem Statement
Housing instability is a critical health-related social need (HRSN) driving poor health outcomes and high healthcare utilization among Medicaid populations. While New York State's Social Care Network (SCN) initiative, launched under the NYHER 1115 Medicaid Waiver, aims to systematically connect members to housing services through coordinated referral systems, there is a lack of systematic analysis regarding referral patterns. Existing literature focuses primarily on screening for social needs or patient acceptability, leaving a gap in understanding the performance of referral systems themselves. Specifically, there is limited evidence on referral acceptance rates, time-to-service metrics, and the specific workflow bottlenecks that hinder successful service connections at scale.

Methodology
The authors conducted a mixed-methods quality improvement study at the Public Health Solutions' WholeYouNYC SCN Coordination Center. The study period spanned eight months (June 1, 2025 – January 30, 2026).

• Quantitative Analysis: The study analyzed 4,258 housing referrals submitted by Public Health Solutions staff via the Unite Us platform. Data were extracted from a Microsoft Power BI dashboard and analyzed in Microsoft Excel. Key metrics included referral status (accepted, rejected, pending, or sent/awaiting action), acceptance rates by receiving organization, and time metrics (time to acceptance and "days open" for unresolved cases). The analysis stratified data by the top five receiving organizations and examined temporal trends.
• Qualitative Analysis: To contextualize the quantitative data, the researchers conducted semi-structured consultations with seven staff members (five navigators and two supervisors) and reviewed internal workflow documentation. Thematic analysis was used to identify workflow bottlenecks, which were then integrated with quantitative findings to triangulate evidence.
• Study Design: The project was classified as quality improvement using administrative data, requiring no IRB approval.

Key Results
The analysis of 4,258 housing referrals yielded the following outcomes:

• Low Connection Rates: Only 45% (n=1,936) of referrals were accepted by receiving organizations. 19% (n=815) were rejected, 3% (n=125) remained pending, and a significant portion, 32% (n=1,382), were categorized as "sent" with no recorded response.
• Systemic Consistency: Acceptance rates were remarkably consistent across the top five receiving organizations (ranging from 44% to 46%) and remained stable over the eight-month study period (43%–46%). This suggests that low connection rates are driven by systemic barriers rather than performance variations among specific Community-Based Organizations (CBOs) or seasonal factors.
• Time Metrics: The average time to acceptance for successful referrals was 8 days. However, unresolved referrals showed significant aging; the median time open was 45 days, with a mean of 62 days. Notably, 21% of unresolved referrals had been open for over 150 days, with the longest pending case remaining unresolved for 271 days.
• Identified Bottlenecks: Qualitative data identified three primary workflow barriers:
  1. Delayed CBO Response: 32% of referrals received no response, indicating a lack of standardized response timeframes and automated follow-up.
  2. Missing Documentation: Complex and unclear documentation requirements (e.g., income verification, eviction history) led to back-and-forth communication, adding an estimated 8 days to the process and contributing to 15% of rejections.
  3. Client Engagement Challenges: Navigators reported significant difficulty engaging members experiencing housing instability due to disconnected phones, lack of stable addresses, and competing survival priorities.

Key Contributions

• Evidence-Based Workflow Analysis: The study provides one of the first large-scale systematic analyses of housing referral outcomes within the emerging SCN model, moving beyond screening data to analyze the performance of the referral system itself.
• Identification of Systemic vs. Partner-Specific Barriers: By demonstrating consistent acceptance rates across high-volume and low-volume partners, the study shifts the focus from blaming individual CBOs to addressing structural constraints, such as housing supply limits and communication gaps.
• Operational Data Utilization: The paper demonstrates the feasibility of using administrative data from platforms like Unite Us for continuous quality improvement, offering a framework for monitoring acceptance rates, time-to-connection, and referral aging.

Significance and Claims
The authors claim that the findings provide an evidence-based framework for quality improvement in social care coordination programs. They assert that while workflow optimization (e.g., establishing response benchmarks, standardizing documentation, and enhancing client engagement strategies) can address communication and administrative inefficiencies, it cannot fully overcome fundamental housing supply constraints.

The paper concludes that Social Care Networks must implement routine performance reporting and accountability mechanisms while simultaneously advocating for upstream policy interventions to expand affordable housing resources. The study emphasizes that low connection rates are a pervasive challenge in social care coordination, not unique to housing services, and that addressing them requires multi-level interventions ranging from operational protocol changes to structural policy shifts.