HomeMy WebLinkAboutAudience Comment Submittal V. Blakeney 2/2/2026VJ
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Renton Student Health Hub
2025 Q4 Qua rte r ly Report
OCTOBER -DECEMBER 2025
Supporting student well-being in Renton,Washington
S BRIEF INTERVENTION REFER.B-IRE.I1EN
In Q4 2025,we rolled out new Hub Housing Services—eviction prevention and rapid re-housing—to all
26 district schools,ensuring every student has access to critical stability supports.Since launching in
January 2024,the Hub has screened hundreds of students,with nearly half requiring follow-up.Of those
seeking additional care,91%were successfully matched with a provider.
HERE’S A QUICK RECAP OF 2025 Q4
“Student Health Hub”
launched in all 26 schools.
949 students screened 47%of students screened
for social emotional needs and substance required brief intervention
abuse issues using the “Check Yourself’online 28%yellow flags (brief intervention),
tool developed by Seattle Children’s Hospital.20%red flags (immediate brief intervention)
REFERRAL TO BEHAVIORAL HEALTH AND HOUSING SERVICES
233 211 6.74*97%
students referred to students days closed loop
care matched avg turnaround rate
after meeting with with a behavioral health or time from referral Students needing a
the school staff.housing service provider if submission to match.referral matched with a
referred to care hub provider.
96 56 45 14 46%
students students not students unknown successful
enrolled in care enrolled in care with pending enrollment connection rate
enrollment status
TOP 5 REASONS FOR REFERRAL
#1 #2 #3 #4 #5
ANXIETY!EMOTIONAL DEPRESSION ACADEMIC SELF-ESTEEM
EXCESSIVE WORRY REGULATION CONCERNS
NUMBER OF REFERRALS BY PROVIDER ORGANIZATION
52 28 24
C’r
19 •
3 5 more
-Coos
Student
Gender*
89 Csgenaer
69 Cisgender male
I-%
4 Genderqueer/Gender
non-conf ormng/Norrbinary/
Gender fluid
2 Transgender male
7
*Behavioral health data only.Housing-related services are not included in these fields.
Our priorities
for 2026Q1:
•Pilot new Housing Services to support students and families
•Implement grant-funded projects with technical assistance and oversight
•Complete independent evaluation of the Student Health Hub
“Renton’s Student Health Hub,along with the newer Housing Referral
options,have helped streamline and expedite pathways to support students
and families.The systems now in place have significantly reduced the time
required to make referrals and do the initial outreach to families.”
21 17 8 6 4
VALLEY CITIES ri
SENECA oEa SAFE
REFREE CEO NGS
.or..Communityb1vIe3
‘Vthe,
Student Preferred
Lang LI age
202
Student Race!
Ethnicity
6 5 —sparc,
ore 0/,
---
3 American Indian
or Alaska Native
3 Native Hawaiian
or other Pacific
Islander S
2$
1 1 1
English Span-Vietnamese Ossoe Other
•6’Elockor
t Aft can
—American,
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ieshoningNot sure
of gender identity
Renton School Counselor,Renton School District
QUOTES about the Student Health Hub experiences so far:
“One of our students was living in a shelter where ongoing conftict and bullying created an
unsafe and unstabte environment.The constant stress took a serious toll on the child’s
emotional well-being,leading to severe distress and suicidal ideation as a direct result of
the living situation within the shelter.Although the parent was actively seeking stable
housing,they were unable to afford the required move-in costs,leaving the family trapped
in crisis.Thanks to the quick and effective response of the Housing Referral Pathway,the
familywas able to transition into stable,permanent housing.Today,they are in a safe and
supportive environment,and the child’s mental health has improved significantly,restoring
a sense of security,hope,and the abitity to heal.”
“This year I have referred 13 students to the Hub for in-school counseling with licensed
mental health professionals.lam truly gratefulfor this opportunity to provide students
with the support they need.Without an accessible referral process for parents and staff,
many of these students might not have received the criticat mental health services they
deserve.The COVID-1 9 pandemic not only contributed to heightened levels of anxiety for
many individuals,but it also significantly reduced access to therapists-particularly for
children under the age of 18.”
“Renton’s Student Health Hub,along with the newer Housing Referral options,has helped
streamline and expedite pathways to support students and families.The systems now in
place have significantly reduced the time required to make referrals and do the initial
outreach to families.”
“I recall a student who had previously disengaged from outside services after feeling
misunderstood and unheard.Through the Student Health Hub,I connected them with a
provider who reflected their identity and approached care with cultural humility.As a
result,the student not onty re-engaged in services but began attending school more
consistently and advocating for their own needs.For counselors,this shift meant less
crisis-driven intervention and more sustained,preventative support,allowing us to focus
on long-term student wellness rather than short-term stabilization alone.”
“Neighborhood House (the HousingReferrat pathway)has already provided eviction
prevention to two of our families.One family included a mother,father,and three young
children.They were homeless and sleeping in their care at the beginning of the year.
Despite the barriers they faced,the family found an apartment in October.However,they
were not abte to pay the full rent.In November the family got an eviction notice.They
would have nowhere to go and be steeping in their care for the winter.Neighborhood
House was able to work with the family and tandlord to prevent their eviction!Providing
this service was a wonderful way to care for our student and to build trust and relationship
with this famity.And because the family remained housed,the mother has been able to
work a stabte job.The student’s struggle with behavior has also improved significantly.I
cannot stress enough the significance of housing services and the quantity of families who
need them!”
V?ORPRN
UI!Oregon Rural Practice-based
liii Research Network
Mixed-Methods
Evaluation of Renton
Student Health Hub
A School-Based Model for
Addressing Washington’s Youth
Behavioral Health Crisis
January 29,2026
Table of Contents
Acknowledgements 3
Executive Summary 4
Program Background 5
Methods 6
Hub Referral Data 6
Semi-Structured Interviews 8
Participants &Data Sources 8
Hub Referral Data 8
Semi-Structured Interviews 8
Findings 9
Hub Reach and Functionality 9
Effectiveness and Enrollment 11
Barriers and Bottlenecks 14
Platform Experience and Requested Features 17
Discussion 19
Summary and Recommendations 20
Key Recommendations 21
Conclusion 22
Analytic Endnotes 23
References 25
Appendices and Supplemental Tables 28
Appendix A.Student Health Hub Behavioral Health Pathway Model 28
Appendix B.Semi-structured Interview Guide 29
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Appendix C.Student Enrollment by Characteristics 33
Appendix D.Reach and Penetration of the Hub 34
Supplemental Table 1.Data Dictionary:Evaluation Dataset 35
Supplemental Table 2.Cox Proportional Hazards Model Results for Time to Enrollment 38
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Acknowledgements
Prepared by:
Alex Moore,MPH Research Project Coordinator
Anders Herreid-O’NeiII,MA I Qualitative Data Analyst
Michael Wohner,MPH I Biostatistician
Brian Frank,MD I Principal Investigator,Associate Professor of Family Medicine
Martha Snow,MPH ISenior Research Project Manager
Acknowledgements:The authors would like to thank the team at HCP-One Health Port as well as
the providers and Renton school district staff and administrators who participated in one-on-one
interviews.
Oregon Rural Practice-based Research Network (ORPRN)
Oregon Health &Science University
3181 S.W.Sam Jackson Park Rd.
Portland,OR 97239-3098
tel 503 494-0361
fax 503 494 1513
ohsu.edu/orprn
\?ORPRN 3
/Oregon Rural Practice based
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Executive Summary
In July 2025,HCP-OneHealth Port (HCP-OHP)engaged the Oregon Rural Practice-based
Research Network (ORPRN)to conduct an independent evaluation of the Student Health
Hub (“the Hub”),a school-based mental health referral system that facilitates schools in
matching eligible students with community mental health providers for 17 Renton School
District schools in Washington state.ORPRN used a mixed-methods approach that
leveraged referral data and interviews with school staff,administrators,providers,and
Hub implementation staff to analyze student match-to-enrollment time and identify
operational barriers and referral bottlenecks.The following report details the findings of
this evaluation and key recommendations for continued implementation.
Evaluation results showed that between 2024 Qi to 2025 Q4,the Hub expanded from 2
schools to 17,grew its number of users nearly 500%,and consistently matched 93-100%
of students with providers.The percentage of enrolled students trended upwards,with
the highest enrollment in 2024 Q4 (62%).By mid-2025,the median time-to-enrollment
had reduced from 195 days to 35 days.The overall median enrollment time was 35 days,
outperforming the national median time to mental health services by 2 weeks.Overall,
the Hub is very well-liked.Users felt that the Hub was more efficient than their prior
referral systems and that it reduced workload burdens,decreased wait times,and
created a more equitable system by centralizing data.Analysis additionally identified
differences in enrollment,barriers,and bottlenecks.There were disparities in enrollment
speed by student race/ethnicity,while students from families whose first language is not
English were connected to services twice as fast as those from English-primary families.
Larger school size and larger population of students with disabilities were associated
with slower enrollment.Interviews identified parental hesitation,release of information
delay,minimum referral requirements,and insurance-related challenges as prominent
bottlenecks.Hub users requested interface changes such as simplified navigation,
expanded Hub training materials,additional referral pathways,and the ability to filter
providers by specific characteristics or services during the matching process.Users
named 1)increased training on the Hub platform,2)prioritizing clinic onboarding,
community-building,partner management,and 3)maintaining platform flexibility to
localize and tailor referral processes as necessary to expanding the Hub beyond Renton.
This evaluation has determined nine recommendations for further refinement of the Hub:
1)address racial and ethnic disparities in enrollment;2)optimize resource allocation for
large schools and schools with large populations of students with disabilities;3)
institutionalize linguistic navigation access;4)aim to decrease match-to-enrollment
speed to under 30 days;5)expand the Hub platform to include pathways to additional
services;6)host the Hub on an independent website;7)develop a process to mitigate
insurance barriers and avoid counselor burnout;8)develop responsive matching
processes;and 9)provide shareable parental education materials on the Hub platform.
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Program Background
Washington State is currently facing a significant,wide-ranging youth behavioral health
crisis that has reached every corner of the state.1 In a 2024 report released by the
national non-profit,Mental Health America,Washington was ranked 48th in the nation
for youth mental health.2 Since 2013,youth in the state have experienced a 600%
increase in rates of suicide and suicide attempts and nearly triple the rates of opioid
related fatalities since 2022.Despite Washington adolescents reporting slight declines
in suicidality and depression in the most recent Healthy Youth Survey,over half still
experience anxiety and/or depression.21 Adverse Childhood Experiences (ACEs),
including neglect,abuse,and poverty,are associated with worse mental health,
underscoring the need for early intervention as well as universal screening and referral
programs.15’6 School-Based Screening,Brief Intervention,and Referral to Treatment (SB
SBIRT),has been used by Washington tribal,public,and private schools to identify and
connect students to mental health resources,however,many schools statewide lack the
information technology infrastructure needed to facilitate timely referrals from school-
based counselors to youth behavioral health providers.7,1 Youth wait times for behavioral
health services are not universally captured or reported across the United States;
however,the wait times that have been reported are near or above the 60-day duration
associated with high rates of non-attendance and crisis escalation.813 This discrepancy
between ideal and actual time to enrollment is a significant barrier to wider adoption of
early detection and intervention models such as SB-SB IRT.
To address this barrier,The City of Renton,Renton School District,and their provider
partners contracted with HCP—OneHealthPort—the nonprofit operator of Washington
State’s Health Data Utility (the Washington Alliance for Health Data Exchange,
WAHDX)—to implement the Renton Student Health Hub.Adapted from the Camden
Coalition’s Community Health Hub model,the Student Health Hub,called “the Hub”
throughout this report,serves approximately 170 students across 17 schools in the
Renton School District.The Hub is an online system that facilitates school counselors
connecting students to behavioral health providers,from matching students with a
provider to their enrollment in services.Each student represents a case within the Hub’s
system.Students are referred to counselors for behavioral health needs.Referrals can
come from SB-SBIRT screening,school staff,students themselves,or parents/guardians.
Once a student is referred,the Hub allows school counselors to match students with a
community mental health provider through an online platform.Once counselors match
students with providers,the provider enrolls the student in services and confirms
enrollment via the Hub.A model of the Hub’s behavioral health pathway can be found in
Appendix A.
In July 2025,HCP-OHP engaged the Oregon Rural Practice-based Research Network
V?ORPRN
I Oregon Rural Prcticebased
I Research Network
(ORPRN)at Oregon Health &Science University (OHSU)to conduct an independent
evaluation of the Hub.The aims of the evaluation were:1)analyze the use and
experience of the Hub by school staff and local health/social services providers,2)
evaluate the effectiveness of the Hub model,3)develop systematic protocols for
implementing Hub into other public,private,and tribal schools in Washington State.
Qualitative interview findings were evaluated alongside quantitative data to assess
congruence between measured performance and user-reported experience and
identified operational barriers and referral bottlenecks.The following report details the
findings of this evaluation as well as key recommendations for continued implementation
in Renton and future expansion of the Hub.
Methods
This mixed-methods evaluation was conducted by Michael Wohner,MPH,and Anders
Herreid-O’Neill,MA,and completed using two primary data sources:student case data
from the Hub and interviews with platform users.HCP-OHP provided 1.9 years of
deidentified referral data to Mr.Wohner to evaluate the functionality and effectiveness
of the platform.Mr.Herreid-O’Neill conducted interviews to better understand the user
experience of the Hub,including impacts on efficiency and workfiow,as well as any
perceived impact on students.
Hub Referral Data
Case data from the Hub was used to evaluate how effective the platform was in
connecting students to behavioral health providers.The data included referrals for 170
grade K-12 students from 17 Renton schools from January 2024 through November
2025.The dataset included 29 deidentified case characteristics including student age,
who referred the student,date students were matched to a provider,and the date
students were enrolled into services.A data dictionary of all characteristics can be found
in Supplemental Table 1.Effectiveness was measured by calculating the median time
between the referral date (the date the Hub received the referral from the school)and
the date the provider confirmed the student was enrolled in services.The analysis
additionally accounted for students still being matched and enrolled in services in 2025,
ensuring that these more recent referrals did not skew the results.’1
Criteria for effectiveness and Hub feasibility was organized into three “zones”based on
reported wait-time trends for youth behavioral health referrals.The blue “Feasible”zone
represents the ideal state of less than 30-day wait,which minimizes deterioration,aligns
with international goals,and acknowledges Washington Medicaid’s ambitious goal of
connecting adults with non-urgent,symptomatic mental health needs to services in ten
days or less.14’9 The amber “Amend”zone represents standard care,which aligns with
national averages.10’15 Finally,the red “Not Feasible”zone represents wait times
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exceeding two months,which are associated with high rates of non-attendance and crisis
escalation.14’16
Figure 1.Diagram of Feasibility Zones
30
Feasible men
30 days to services
31 -60 days to services
Standard care aligns
SignificantLy faster with national averages
than national
averages •...50 nays
Median wait time for new
patient appointment with a
child psychiatrist
60 days
Not feasible
60 days to services
Characteristics of the schools and students were analyzedi to evaluate if they affected
how quickly and equitably the Hub process connected students to behavioral health
services.Structural-level characteristics of schools are known to influence both access to
and continuity of behavioral health services,including percent of students from low-
income households,percent of students experiencing housing instability,percent of
students enrolled in special education,percent of English language learners,racial and
ethnic demographics,and gender composition.17’18
School and student-level characteristics included in the model were:
•Student race/ethnicity
•Student insurance coverage type
•Primary contact (i.e.,student vs.parent/staff)
•School type (elementary,middle,or high school)
•School populations’
•Percent of students enrolled in special education
•Percent of students experiencing housing instability
•Discipline ratesi
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Oregon Rurai Practicebased
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Semi-Structured Interviews
Interviews were conducted with Renton School District administrators,school district
staff who matched students using the Hub,and community providers with whom
students are matched through the Hub.Additional interviews were conducted with HCP
OHP staff on the Hub implementation team in order to understand program workflows
and staff experience.Participants were identified in coordination with HCP-OHP,and
outreach was designed to prioritize both active users and a representative range of user
perspectives.Interview invitations were distributed in three rounds,each following
informal introductions by HCP-OHP staff.24 participants were invited and 11 interviews
were compIeted.h The OHSU evaluation team developed the interview guide in
coordination with HCP-OHP which can be found in Appendix B.Interviews lasted 60
minutes and were conducted and transcribed using Webex.Deidentified transcripts were
analyzed1ui for themes related to Hub user experience,workflow,impact on students,
and any additional themes that emerged.
Participants &Data Sources
Hub Referral Data
Case data from January 9,2024 through November 20,2025 were extracted directly
from the Hub internal database.Publicly available school-level data from the Washington
Office of Superintendent of Public Instruction (OSPI)Report Card were used to
determine school-level characteristics.19 For a full table of student characteristics,see
Appendix C.
Figure 2.Hub Referral Funnel (N=158),Qi 2024 to Q4
Participant Demographics 2025
Reterrais ReceivedFromJanuary2024toNovember2025,170 =170
K-12 students were referred to the Hub.Of
those 170 students,twelve could not be
Matched to Provider Not Matchedmatchedwithprovidersandwereexcludedn=158(93%)n=12(7%)
from the analysis.Of the 158 students
matched to providers,42%(n=67)were
Enrolled in Services Not Yet Enrolledenrolledflbehavioralhealthservices.n=67 (42%of matched)n=91 (58%of matched)
Note:Enrollment counts from provider reports as of 11/20/2025.
Semi-Structured Interviews
Participants were grouped into three categories:
1)School staff involved with matching students via the Hub
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2)Behavioral health providers accepting matches through the Hub
3)Hub-involved leadership and school staff,additional partners,&HCP-OHP staff
Eleven interviews were completed between October and December 2025.Participants
included four school counselors (two elementary schools and two middle schools),two
behavioral health providers,and five leadership or administrative partners from the
Renton area coalition responsible for implementing the Hub.Interviews.
Findings
Hub Reach and Functionality
Of the 158 students who matched
58 6°/awithproviders,most matches Eenienryschoot
originated from middle schools
(n=97);however,matched elementary Elementary schools
school students (n=29)were most had the highest
likely to enroll in behavioral health I enrotment rateservices(58.6%).87%(n=137)of
__________
matched students had Medicaid
insurance,and students with 312°/a 41.2°/a
Medicaid were more likely to enroll in High schooL 1idde shoot
services than students with other
insurance types.
Students identifying as Black or
____________________________
African American (27%,n=43)and ac or flfricanmuerican students I
Hispanic or Latino (25%,n=40)27°Io a Hispanicor Latino students
were the largest subgroups of 4 represented over half of all referrals
students to be matched with 25°!a
______________________
services.
The highest enrollment rate (50%,n20)was seen among both Hispanic or Latino
students and Asian or Asian American students.The lowest enrollment rate (30.2%,
n=13)was seen among Black or African American students.
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46.90/u
Asian or AsianAmerican s1uents
a Hispanicor Latinostudents
hod the highest enrollment rate
White students and students who identified as multiple races/ethnicities or “other”were
enrolled in services more quickly than any other single race/ethnicity group.The number
of students identifying as “multiple race”or “other”race were too small to analyze
independently and thus were combined into the single group “Other/Multiple.”
Parents or guardians initiated most of referrals
(n=120);however,when students self-referred
(n38),they were more likely to follow
through and enroll in services.44.7%of
referrals initiated by students resulted in
enrollment compared to the 41.7%rate from
parents or guardians.
Parents or guardians
initiated contact in
76%of otl referrals..SelIreferrals
had a 3%greater
enrollment rote
Since the Hub’s inception,the number of participating schools increased from 2 in the
first quarter of 2024 to 17 in the final quarter of 2025.The number of school counselors
and support staff referring students via the Hub grew nearly 500%in just under two
years and quarterly referral volume reached its peak in the final quarter of 2025,a nearly
four-fold increase compared to the program’s inception in January 2024.
Figure 3.Hub Participation and Referral Volume,QI 2024 to Q4 2025
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10
50°/a
Hispanc or
t anna
50°/a
Asian or
Asian Anier,can
.:II
30.2°/o
B(oth or
4frican
,Srner,can
Black or African
American students
hod the 10West enrooment rate
41.9°Io
White
50
-10
30
20
10
0
41
2
17 14—I.I 7
2
01 2021 04 2025 0 2021 Ql 2025 Qt 1J 042025
Qatrl It 1tj
Effectiveness and Enrollment
The Hub’s median time to enrollment was 35 days.Based on the feasibility zones
developed to evaluate effectiveness,in the program falls in the amber “Amend”zone.
Figure 4.Hub Performance Status Mapped to Feasibility Zones
feasible
30 days to services
SignificantLy faster
than national
averages
Median time to
enrollment in services
Amend
31 -60 days to services
Standard core,aLigns
with nationat averages
50 days
Median waft time for new
patient appointment with
a hitd psychiatrist
6Odas
Not Feasible
60 days to services
The rate of students matching with providers through the Hub has remained above 90%.
The percentage of enrolled students increased from 29%in 2024 Qi to 50%in 2025 Q3,
with the highest enrollment (62%)occurring in the final quarter of 2024.
Figure 5.Percentages of Matches and Enrollments,2024 Qi to 2025 Q3
100%
93%96’o
7Q%
60450
40
30t,
20.
10
0,a
35 nays
I
Student
Health Hub
100%100%96%
62%56%29%
2024 01 202.4 Q2 2024 Q1 2025 Qi 2025 Q2 2025 Q3
—Percent ol students motched Percent of students enrolled
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Oregon Rural Practice-based
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Two school characteristics,school size and population of students with disabilities,were
associated with slower enrollment into services.Larger schools showed substantially
slower enrollment overall;specifically,a doubling of school size was associated with an
approximately 69%reduction in the rate of enrollmentP Additionally,schools with
higher percentages of students with disabilities had slower rates of enroIIment)Further
evaluation is needed to understand the causes for these delays.
Trne to Teatment
Over the two-year study period,qualitative feedback from counselors indicated that wait
times decreased from months to days.A time-to-event analysis of the full dataset
(concluding in 2025 Q4)established an overall median time from referral to enrollment of
35 days (95%Cl:33,45).Throughout 2025,the median time to find a match remained at
or below 5 days,meaning the 35-day waiting period was primarily located in the
enrollment phase,not the matching phase.One user noted that students “don’t have to
wait four or five months;it’s days at this point,”which,“has created so much access for ftheir]
kids and families”(Participant 7).
Prior to the Hub implementation,school counselors described a time-intensive process
of online searches and phone calls to find available mental health providers.Often,the
information was outdated or incorrect,and there was no standardization of referral
processes.One user described the previous process as “terrible.I would do a search myself
just online,like,‘what are the agencies?’and then try to reach out to somebody at those sites.
Not a lot of responses,not a lot of emails back for]‘That person doesn’t work here anymore,”
(Participant 5).In addition,referrals often went unacknowledged,requiring counselors to
follow-up with students to learn whether the student had been enrolled.The Hub has
virtually eliminated these workload burdens and uncertainties,increasing coordination
between schools,parents,and providers.According to one interviewee,the efficiency
created by the Hub was “a weight off the shoulders of school counselors”(Participant 7).
“Because I don’t have to make referrals to a multitude of outside agencies,it’s
just super streamlined.I make the one referral to the Student Health Hub and
out it goes.”
Participant 8
Providers also noted increased efficiency and that the Hub has consequently increased
their capacity to offer services.One provider noted,“I have some therapists that are going
to,throughout the week,10-15 different schools.But with the Hub,because we were getting
multiple referrals from one school,that helps their day because they can go to one school see
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four to five clients instead of driving from school to school”(Participant 6).Another
described how families are easier to contact,suggesting that the Hub allows them to be
more involved in enrollment and more aware of next steps and what to expect.
User Integration and System Efficiency
Figure 4 charts the Hub’s expansion by ploffing the total number of Hub users (i.e.,
counselors/staff)alongside enrollment speed.The red zone (2025 Q3—Q4)represents a
provisional data window subject to right-censoring regarding enrollment.While the
referral volume is accurate,not all cases in the red zone had completed the enrollment
process at the time of data analysis and thus the median days to enrollment in the zone
cannot be considered comprehensive,final results.
Figure 6.Hub Expansion vs.Operational Efficiency,)a 2024 Qi to 2025 Q4
60
a)
2C0(Provisional)
15 0
Quarter
From January 2024 to December 2025,the Hub saw a 6-fold increase in unique Hub
users (from 7 to 41)without a slowing of the process.The Hub also became more
efficient,reducing the median time to enrollment from 195 days to 35 days—an 82%
improvement.For a full table of reach and functionality data,see Appendix D.
Increased Personalization of Matching
Individual students may feel more comfortable seeing a provider who shares some of
their characteristics;for example,it is well-established that racial concordance between
provider and client leads to a more therapeutic relationship.20 Before the Hub,a
counselor’s ability to match students with providers based on demographics or other
characteristics was primarily dependent on the network that the counselor had
developed.One Hub user explained that “pre -Student Health Hub model,one of the issues
is...it’s all about who you know.So,when you are a school counselor in a building and you need
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to find a resource for a kid,it’s all really about who you know,and can you get them to
respond”(Participant 1).Users reported that the Hub’s centralization had improved
counselors’ability to connect students with providers more tailored to their unique
needs,which they believe benefifted students from under-resourced communities.
“The ability for us to be able to have so many agencies connect to the Hub has
allowed choice.We have a huge BIPOC population,so when it comes to
students and who they’re comfortable with...maybe they have tried therapy
before and it hasn’t worked because they were just stuck with whoever worked
within their insurance or just somebody who was available at the time.”
Participant 10
Additionally,centralizing data,such as student demographics and reasons for referral,to
the Hub has allowed schools and districts to tailor interventions to better serve their
students,with one interviewee describing how seeing the type and frequency of referral
reasons has helped them guide their comprehensive counseling programs (Participant 4).
‘..now we see a variety of providers working with students and it’s pretty cool
that different agencies have different strengths to them.And so,it’s cool to see
that matching what they’re good at with the student need.That’s much more
evident than it was when we were stuck with just the one silo.”
Participant 5
Crisis Prevention
Providers reported early indicators that the Hub is successfully shifting care away from
acute crisis settings.One interview participant noted that a provider accustomed to
receiving referrals via the Emergency Department is now seeing Hub-referred youth
enter care in a stabilized state,saying that,“they’ve had enough students referred from the
health hub that the outcomes are just better for the young people and the families because
you have this different space...they’re not in a crisis space.”
Barriers and Bottlenecks
The Hub has broadly improved matching and enrollment times and is well received by all
users;however,interviews identified several areas of friction within the system,including
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parental hesitation,requests for in-person services,and insurance delays.Addressing
these three areas would further improve upon the current achievements of the system.
Parental Hesitation
Due to student age or preference,school counselors must often rely on parents,
guardians,and families at key points in the Hub referral process,leaving enrollment
success potentially vulnerable to parental hesitation or refusal to establish with a
provider through the Hub.Interviewees described cases where refusal resulted from
stigma regarding mental health care or specific mental health needs.
‘..a lot of times families will say,‘we want fservices]’and then when you send
them the information,they back off of it.”
Participant 8
Documentation delays additionally contributed to bottlenecks.Counselors described
how parents or guardians often failed to return Release of Information documents in
timely fashion,preventing their child’s referral from progressing.One counselor named
this delay as the “biggest challenge”they faced (Participant 8).Multiple interview
participants developed strategies to mitigate documentation delays,such as requesting
parents to complete paperwork at the school office or sending multiple follow-ups.
“There’s still a stigma,there’s still beliefs like,‘you’re saying something’s wrong
with me’or the one I hear a lot from people is ‘1don’t want people to know my
business.’The families just feel it’s invasive.”
Participant 5
Referral Minimum Requirements
Both counselors and behavioral health providers identified referral minimums for in-
person treatment as a source of enrollment bottlenecks.Many providers require a
minimum number of students seeking services at a given school before the provider can
offer in-person services there.As one counselor said,‘..the drawback has been,well,we
need to have at least four students receiving therapy to make it worth their time to be in-
person because it does require traveling and then a space”(Participant 8).Counselors for
elementary age students specifically highlighted referral minimums as a priority
improvement,due to the significant benefits of in-person treatment for this age group.
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“Teletherapy is not great for anyone younger than third grade.They just do not
have the stamina and engagement because when they stare at a screen it’s for
entertainment...even the upper grades unless they are really wanting counseling
and they want to talk to someone.I mean,I’ve had students put on YouTube and
sit there and draw while the therapist is trying to engage them in conversation.
They’re not even seeing the therapist.”
Participant 8
Conversely,provider interviewees saw minimums as an opportunity to manage capacity
and streamline workflow to be geographically responsive.One provider described that
while they do not have a minimum number of referral requests needed to send staff to a
school,they are considering incorporating one into their provider allocation process.As
one provider described,after being asked if they had a minimum,“No,and that’s been our
problem and why I have people at ten different schools right now”(Participant 6).
Ins ura n c
All Hub users,from providers to counselors to implementation staff,have described that
confusion,hesitation,and additional work surrounding insurance can cause friction at
many points in the referral process.Mid-enrollment insurance lapses,matching delays
due to Medicaid requirements and confirmation,and uncertainty around which insurance
types are accepted by the Hub are three prominent and common sources of this friction.
Counselors expressed confusion around who can be referred through the Hub and
described student confusion around insurance coverage.One counselor interviewed said
they “automatically filter [out]based on insurance need”because of confusion over who
qualifies for Hub referral and the perception that only state Medicaid is accepted.
Another counselor interviewee noted that uninsured students seem to have difficulty
matching or enrolling with providers,particularly those offering in-person services.
“I think sometimes just students don’t know and so that’s something common.
Sometimes it’s describing like,what does a Medicaid card look like?What could
they have heard when they went to the doctor?Especially if they’re not trying to
involve family because they’re not going to support their decision to have
counseling services.So,it’s just like ‘this is what the little card looks like for
health insurance through the state,have you seen this card before with your
name on it?”
Participant 7
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The primary insurance barrier that providers encountered was lapsed insurance in the
time between matching and enrollment.These lapses can delay or even prevent
enrollment by deterring families from completing enrollment out of a concern of paying
out-of-pocket for their child’s services.Alleviating these concerns often required Hub
implementation staff to invest significant time confirming eligibility at the matching stage,
which ultimately resulted in lengthy delays.
Outside of the matching process,insurance barriers also impacted referral capacity.Hub
implementation staff described that providers most often decline referrals due to their
own capacity and acuity of patient needs,but that ‘..the other times are almost always
related to insurance,or coverage related”(Participant 11).One member of the Hub staff
additionally described that,as the Hub expanded to more schools and the number of
referrals increased,“apart from the amount of time I’m spending on care coordination,
meaning the back and forth with counselors fand providers]about student insurance...a part
from that time just really exponentially increasing...l haven’t found a lot of change fto the
workload]”(Participant 11).This experience indicates that the Hub referral system is
scalable,but that confirmation of insurance coverage could become a major barrier as the
number of referrals increases.
Platform Experience and Requested Features
Hub users were generally satisfied with the system but expressed some frustration with
platform access and complexity.Some users found accessing the Hub through Microsoft
Teams particularly difficult,and one interviewee noted that the history of the district
switching between using Microsoft suite and Google products meant they were less
familiar with Teams as a platform.Other users experienced technical issues,such as no
longer receiving alerts to update their patients’progress through the system or being
unable to delete referrals that should be closed or were erroneously entered.
Some users expressed that reporting and data entry could be a heavy workload.One
provider specifically mentioned reporting back to schools as a time burden.One staff
member felt that less time spent on data entry could translate into more time spent
identifying the most appropriate care setting for their students.
Requests for new or refined features included:
1)More in-depth training materials
2)More provider feedback about how schools can support students (as privacy
allows)
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3)Ability to create “test”student profiles to allow counselors to demo the referral
process and explore the Hub more easily,either during training or in order to
improve their skills with the system
4)Ability to filter for providers offering in-person services (particularly important
for elementary students)
5)Ability to filter for religiously affiliated providers
6)Increased automation of certain aspects of the process while maintaining the
ability for counselors to tailor matches to student needs
Additional Functionality
Hub users expressed a desire to see several aspects of the platform expanded,including
adding non-clinical treatment/service pathways,expanding into additional school
districts,and expanding information available to counselors.Most interviewees wished
they could use the Hub to refer their students to sports,clubs,and more community
resources.One interview participant imagined pathways to cooking classes or “support
groups for kids who are going through a divorce”(Participant 3).Identifying and treating
these needs early could help students avoid future behavioral health treatment later.
‘..we were talking to a girl who wasn’t coming to school and then finally,
because they trusted one of my team members,they said,‘Well,I can’t afford
getting my hair done and I’m tired of having to just wear the same scarf over it
and it’s embarrassing and I just don’t want to go to school.’So eventually I would
love it if we could find a way for the Hub to bring in all the community so that
we could just say,‘here’s a need,which Renton community member would be
willing to help us do this girl’s hair?”
Participant 4
Additionally,many counselors and school staff expressed a desire to receive more
information back from providers on ways they can support enrolled students during
school time.While acknowledging student privacy is paramount,these interviewees
mentioned that they could reinforce provider suggestions or make time for regulation
strategies if providers were able to make this kind of information available through the
Hub.As one counselor described,“if fstudents are]drawing to release their feelings or write
in a notebook...we don’t have to read the notebook or look at the pictures,but if we know
that,then we can make provide time and space for that”(Participant 8).
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Scaling and Expansion
When asked what would be needed to ensure a smooth rollout of the Hub model in
other school districts,users described a range of suggestions from onboarding training to
community engagement.For counselors,the key to effective expansion was to ensure
counselors understood the platform from the outset.Several interviewees expressed that
the training videos they watched were insufficient for their needs and suggested in-
person training.Some users suggested in-person opportunities for counselors to meet
providers,both to build community and to better match students with providers in the
future.Providers suggested prioritizing clinic onboarding with specific focus on Hub
platform training and preparing for referral increases without becoming overwhelmed.
School administrators underscored the importance of partner management—nurturing
Hub program champions,exploring new partnerships,and keeping the Hub a priority for
decision makers was considered key to program expansion.One interviewee emphasized
the importance of both community and parent/family engagement.
“1 think the other lesson learned there is patent involvement and parent
communication around what we’re doing here and why we’re doing it...because
it really is focused on supporting kids and families and helping caregivers too.I
don’t see it just as focusing fonlyl on the youth.”
Participant 3
Hub implementation staff highlighted system flexibility as a key strength to ensure
successful rollout.While the Hub’s methodology is standardized to be replicable in many
different environments,one staff member emphasized that localization and tailoring are
crucial to success,stating,“I think there has to be some flexibility alongside a standard.”They
went on to say that familiarity with the community and provider options is an important
feature of that flexibility on a community-by-community basis,“I think that having someone
fmatching referrals]...that is pretty familiar with the communities that are being served and has
a good touch point into the local community health mental health providers who can serve
those students”(Participant 11).
Discussion
The Hub has facilitated a consistent volume of matches made by school counselors to
providers and users feel that the platform improves their ability to match students with
providers based on demographics and other relevant characteristics.Additionally,since
its inception,the Hub has substantially decreased median enrollment time,which
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currently sits at 35 days.There is no single,national benchmark for how long it should
take to connect a child or adolescent to behavioral health services;however,
contextualizing the Hub’s median enrollment time using several wait-time trends for
pediatric psychiatric care demonstrates that the 35-day time to enrollment as a clear
success with room for improvement.While 35 days falls just short of the aggressive 30-
day cutoff of the Feasible zone,the Hub easily outperforms reported median wait times
by 2 weeks,demonstrating a clear efficiency gain over the current standard of care.
Despite its many successes,the platform has not yet equalized the speed of enrollment
for all students.Differences remain between time to treatment for students depending
on race/ethnicity and certain school characteristics.In large schools or those with higher
percentages of students with disabilities,the administrative complexity of coordinating
space for in-person services may create significant structural barriers to fast enrollment.
On the other hand,linguistic and cultural supports provided by the Hub or its users are
not merely equitable but may increase efficiency for families whose first language is not
English.The high enrollment speed among students from these families suggests that the
cultural and linguistic navigation processes of school staff or their connection to
additional linguistic support services outside of the Hub may help to effectively bypass
hesitation and stigma barriers.
While counselors and Hub implementation staff identified insurance as a source of
workload burden and confusion,insurance type ultimately was not shown to affect
enrollment times.One reason for this discrepancy may be that Hub users are mitigating
impacts through their labor and care coordination,presenting a burnout risk for current
Hub users and a consideration for potential expansion to additional districts.
Summary and Recommendations
Over the course of nearly two years of implementation,the Student Health Hub has
successfully developed into a scalable platform reaching seventeen schools in the Renton
School District.Quarterly referral volume has increased four-fold since the Hub’s
inception and the median time from provider match to student enrollment in behavioral
health services has substantially decreased,stabilizing at 35 days.While this metric has
not yet reached the benchmark optimal target of enrollment in less than a month,the
Hub easily outperforms the national median time for pediatric psychiatric access by over
two weeks while showing strength in cultural and linguistic navigation.The Hub was
additionally very well received by its users.
The Hub’s strengths and successes are clear,and,while the evaluation team was not
ultimately positioned to develop full implementation protocols from this assessment,the
evaluation has determined several areas for additional improvement and refinement
ahead of protocol development.Significant disparities in enrollment speeds associated
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with student-level and school-level characteristics persist,and recommendations have
been gleaned from experiences and requests of Hub users.The evaluation team
acknowledges limitations of this analysis,including the small sample size,the multi-
factorial nature of mental and behavioral health,and the many factors outside of the
Hub’s influence that affect matching and enrollment success.
Key Recommendations
•Address Racial and Ethnic Disparities in Enrollment.We recommend conducting a
qualitative audit of the referral-to-enrollment pipeline for Asian or Asian American
and Black or African American students,who experience the slowest enrollment
speeds to determine barriers and bottlenecks.Outreach protocols used for
families whose first language is not English may be adapted and leveraged to
improve trust and engagement with underserved groups.
•Optimize Resource Allocation for Large Schools and Schools with Large
Populations of Students with Disabilities.We recommend implementing
additional navigation administrative support for larger schools as well as
developing specialized workflows or additional direct-to-family coordination for
schools with high percentages of students with disabilities.
•Institutionalize Linguistic Navigation Success.We recommend formalizing and
scaling outreach protocols used for families whose first language is not English,
such as investing in bilingual/multicultural navigators as a core staffing
requirement
•Aim to decrease match-to-enrollment speed to under 30 days.We recommend
further qualitative evaluation to understand specific factors and delays
contributing to the current 35-day median enrollment speed.This evaluation
currently suggests that school-level factors cause the most friction enrolling
students with services,and that family coordination is where the greatest
efficiency gains remain.
•Expand the Hub platform to include pathways to additional services.We
recommend expanding the Hub platform to include additional social services.We
acknowledge that pathways are currently in development or early piloting,such as
the housing pathway,and recommend evaluation of these pathways’pilot years.
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•Host the Hub on an independent website.We recommend shifting the Hub host
platform from Microsoft Teams to an independent website to expand access for
school,provider,and staff users as well as lay the groundwork for direct access for
students and parents in the future.
•Develop a process to mitigate insurance barriers and avoid counselor burnout.
We recommend a qualitative audit to further understand insurance barriers and ad
hoc processes developed by Hub users to mitigate the impact of enrollment
delays.Understanding what confusions,delays,and burdens exist are critical to
improving workload burdens from insurance confusion and delays.
•Develop responsive matching processes.We recommend developing new or
expanding current matching processes to be responsive to both the number of
students who need services and provider availability for in-person services.
•Provide shareable parental education materials on the Hub platform.We
recommend developing and/or collating education materials that counselors can
share with parents when their students enter the referral process.Suggested
materials include Release of Information documents,an explainer of the school’s
referral process and information privacy,mental health stigma education,and
education on early intervention.For maximum impact,we recommend offering
translations in multiple languages.
Conclusion
Utilizing interviews and nearly two years of referral data,this evaluation confirms the
Student Health Hub has successfully transitioned from a pilot concept to a high-
performance system.The Hub achieved a median enrollment time of 35 days,
significantly outperforming previously reported national data and stakeholders
consistently affirmed how the system streamlines care coordination and reduces
administrative friction.While the current data cannot distinguish whether observed
enrollment speed disparities by race/ethnicity stem from internal Hub workflows or
external structural factors,the platform is well-positioned to both respond to and
mitigate these barriers.Ultimately,the Hub is a proven tool with potential for refinement
in Renton School District and serves as a scalable model for equity and access
throughout Washington State.
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Analytic Endnotes
‘Additional metrics collected by the Hub platform were excluded from the final model due to data
reliability concerns.
Preliminary Kaplan-Meier survival analysis was used to determine overall median time from provider
match to enrollment,and a Cox Proportional Hazards fCox PH)regression model was used to allow for the
inclusion of “closed”cases (successful enrollments)and ‘censored”data (students currently navigating the
system).See Supplemental Table 2.
Feasibility zones were developed using limited peer-reviewed studies on pediatric wait times and wait
times reported in the grey literature.The United Kingdom Children’s Commissioner’s annual report on the
state of children’s mental health services calls for no more than 4 weeks wait to services.14 The 50-day
median wait to services was sourced from Edbrooke-Childs and Deighton and Steinman.10,15 The “Not
Feasible”zone was benchmarked based on the impact of wait time on mental health outcomes and
collected reports of national pediatric wait times (where measured).11-13
v To ensure statistical power and protect confidentiality within smaller subpopulations,categorical variables
were aggregated into broader analytical groups where necessary.Model selection was conducted using the
Akaike Information Criterion tAlC)to identify the most accurate and parsimonious set of predictors.The
Cox PH model was subsequently used to determine how specific factors (such as race or school setting)
accelerated or delayed this baseline timeline.To characterize school-level contextual factors,student
records were linked to the Washington Office of Superintendent of Public Instruction (OSPI)Report Card.19
Candidate covariates were selected a priori to represent distinct,policy-relevant dimensions of the school
environment while minimizing redundancy due to collinearity.
The final covariate set included percent of students from low-income households and percent of homeless
students to capture complementary aspects of socioeconomic disadvantage and instability;percent of
students with disabilities to reflect the intensity of special education service needs;percent of English
language learners as an indicator of language access barriers;percent of White students as a parsimonious
representation of racial composition given the compositional dependence among race/ethnicity variables;
and percent female students to account for gender composition.
Highly correlated or conceptually overlapping variables (e.g.,multiple race/ethnicity percentages or
redundant language measures)were excluded to reduce multicollinearity and improve interpretability of
hazard ratio estimates in Cox proportional hazards models.Final model specification was further refined
using Akaike Information Criterion (AIC)—based model selection.
Total number of students enrolled in the school was log-transformed.
vi Discipline Rate refers to the percentage of the student body that received at least one exclusionary
discipline action (short-term suspension,long-term suspension,or expulsion)during the 2023-24 school
year.8 Discipline rates were included in the initial maximal model but were removed during the backward
stepwise selection tAlC)for the final analysis.This variable did not contribute significantly to model fit,
likely due to covariance with ‘Percent Disability’and ‘School Size.’
Participants were provided with an information sheet about the study prior to participation as part of
OHSU IRB approval for research.
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VIII Transcriptions were analyzed by Mr.Herreid-ONeill using ATLAS.ti and a rapid analysis approach.21
Thematic analysis was shared back to topic area experts and the Hub team to ensure data reliability as a
form of member-checking.22
Total school enrollment was log-transformed and a highly significant inverse predictor (p<0.001).For
every unit increase in log-enrollment,the rate of successful linkage decreased by 69%fHR=0.31).
A 10-percentage-point increase in the share of students enrolled in special education was associated with
roughly a 50%reduction in the rate of successful enrollment.This decrease suggests that schools with
larger special education populations face additional structural or operational barriers that slow referral
progression.
XI Recent quarters are subject to right-censoring lag.KM Median for full cohort is 35 days (95%Cl:33-45).
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Appendix B.Semi-structured Interview Guide
Introduction:
Thank you for joining me for this interview today,this is a 60-minute interview about your
experience with the Student Heatth “HUB”program to connect students with behavioral
heatth services.The purpose of this interview is to understand your experience of the
platform as welt as the impact it has had on students and patients you work with.First,
we’LL review the information sheet you were provided with and answer any questions you
have.Then we’ll start with some general questions about the platform and your
interactions with it,then move to some questions about the previous referral system,
before finishingwith some questions about your specific role and any changes you might
like to see going forward.Do you have any questions before we get started?
We’d like to audio record this interview so we can compile and analyze our interview
findings.Any recordings would be transcribed and anonymized so your name would not
appear in any data retained by our team.Is it Ok for me to start the recording?
[Start Recording if yes]
Guide:
Thank you so much!To start,we have a few questions about your role and background.
Intro
1.Can you tell me your current organization and role?
2.How did you get introduced to the HUB referral system?
Experience with system
Now,we’d love to hear about your interactions with the Hub.
3.Can you tell me about the process you use to send/receive referrals through the
Hub?
i.Probe:What is your next step?What are your follow-up actions?
4.With that in mind,can you describe your overall experience working with the Hub?
5.Tell me about any barriers to placing/receiving referrals using the Hub.
i.Probe:Are there any particular points in the referrat process with the Hub
that prevent students from getting the services they need?
Changes to previous experience
Next,we have a few questions about the processes and tools you used to send/receive
referrals prior to the Hub,and how the new way of sending/receiving referrals through the
Hub compares to the old your referral method.
6.Can you describe the process you used to make referrals to behavioral health
providers prior to the Hub?
a.Can you describe the tools you used to make referrals to behaviorat health providers
prior to the hub?(Phone,email,faxes,etc.)
7.When you think about these two different processes and tools,what works better in
the Hub?
8.What is harder about the Hub?
9.Is the new Hub your needs?
10.Is the Hub meeting the needs of students?
Questions for SchooL staff
Now I have some questions about your specific experience with the Hub as a school
employee.
11.Can you walk me through how you decide which students should be referred
through the Hub?
i.Are there levels of severity you consider?
ii.Do you always refer from a screening?Or do you refer for other reasons?
12.What have you heard from students about their experience with the referral process
in the Hub?
13.What have you heard from parents/legal guardians about the new system?
if,ORPRN 30
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Questions for providers
Now I have some questions about your specific experience with the HUB platform as a
behavioral health provider.
14.How has this new system impacted your capacity to deliver care or social services?
15.How has the new system changed your interactions with schools and school staff?
16.Have you noticed any change to the ‘kind’of referrals coming to you?For example,
are they more acute or complex??
i.Probe:Can you estimate how many referrals are coming directly from
screening vs other sources/reasons for referrat?
Questions for Leadership Teams
Now we have a few questions for you from your perspective on the leadership team.
Li 7.Why did your organization participate in the co-development and
implementation of Student HeaLth Hub?
Li 8.What problems were you trying to solve?
Li9.Is the Hub adequately addressingthis problem?
L20.What do you hear from your staff about the Hub?What’s working?What’s not
working?
a.Is the Hub financiaLly sustainable?If not:What could help with Hub
sustainability?
L2i.What other types of schools/providers would you like to add to the Hub in the
future?
L22.What other types of services would you like to add to the Hub in the future?
Impacts to personaL work
Next,I have a couple questions about how the new system has impacted your work
specifically.
17.How has the new system changed your work experience?
i.Probe:Has it affected any feeLings of stress or burnout?
ORPRN 31
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18.How has the Hub changed your worki tows?
19.Has the new system impacted how many students you are abte to work with?
Changes to system
Finally,I have a few questions about any changes you might like to see to the HUB platform.
20.If you could make any changes to the system,what would those be?
21.If you could imagine a perfect referral to treatment process,what would it look like?
22.Can you describe any major barriers that remain to efficient referral and treatment
for this population?
23.If this program were to be implemented at other school districts and clinics,is there
anything that would help make that roll out smoother?
o utro:
24.Is there anything we didn’t discuss today that you were hoping to talk about?
[End RecordingJ
Thank you so much for participating in this interview,your feedback will really help us
understand the impact of the HUB platform.If you have any questions for me going
forward,you can reach me at [email].
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Appendix C.Student Enroflrnent by Characteristics
(N=15$)
Oth””iple/Dedined ,
Gender
School Level
Type of Mental Health Need*
I11i3.!.‘1 L
42.3%
45.6%
36.7%
58.6%
41.2%
31.2%
41.7%
44.7%
46.0%
12.5%
23.1%
40.0%
38.0%
Student Characteristics Students Referred Students Enrolled Enrollment
Rate
Asian orAsianAmerican
Black orAfdcan American
Hispanic or Latino
Cisgender female
Cisgender male
Unknown
I::Irr:nLdI9 SchOol (K-5)
Middle School (6-8)
High School
•.P ary Contact
Paren
Student
Insurance Coverage
12 6 50.0%
43 13 30.2%
40 20 50.0%
31 13 41.9%
32 15 46.9%
71 30
57 26
30 11
29 17
97 40
32 10
120 50
38 17
137 63
8 1
13 3
50 20
71 27
38 20 54.1%.
137 55 40.1%
21 12 57.1%
I
5.
f
I
Insurance not accesstble
Externiig (behavioral concerns)
Crisis (immediate safety concerns)1-Iu
English
Other Language
Nore:This table chowc rmJents ho were iccccfully marc fscd to mental health providecs (N=1 -i8.An additional I
rcidems could not be marched to proJes cod am e,c!udcd from tiis anoIvis.See the ooocnthx for fui thec cxpiaiiation of
th’gauupmr stmtcv Color coding:Green =50%+enrollment.Dark blue =below 40%enrollment
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Appendix D.Reach and Penetration of the HubByquarterPd.Median -Cumulative
quarter #of matches Enrollments Match Days ##
referrals to schools referrers
enrolled
2024.1 14 13 4 93%4.0 29%195 2 7
2024.2 9 9 5 100%5.5 56%117 2 10
2024.4 24 23 15 96%7.0 62%40 7 16
2025.1 25 25 12 100%2.0 48%34.5 7 20
2025.2 20 20 10 100%4.0 50%33 9 21
2025.3 26 25 13 96%1.0 50%26 15 31
2025A 52 43 8 83%2.0 15%15 17 41
‘Note:The lower enrollment rote (15%)and lower time-to-enrollment (15 days)observed in Q4 2025 reflect right-
censoring;the majority of these recent reterrals are likely still proceeding through the intake process.
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Match
Pd..-•Median
Enrolled Days to
Reported
Enrollment1
Supplemental Table 1.Data Dictionary:Evaluation Dataset
Unique identifier for the
student
Date the referral was
received by the Hub
Current administrative
status of the case
Student’s preferred
language-grouped
Student’s preferred
language
Type of insurance
coverage held by student
Person initiating/managing
the referral
198 Unique Values
Jan 09,2024 -Nov
20,2025
11 Levels (Top:
Closed,Active,
Scheduled)
2 Levels (Top:
English,Spanish,
Other,Russian)
5 Levels(English,
Not_English)
3 Levels (Medicaid,
No Insurance,
Insurance not
accessible)
2 Levels
(Parent/Guardian,
Student)
6 Levels (Black,
Hispanic,White,
Asian,Other,
Mixed)
8 Levels (Cis
Male!Female,
Gender Diverse,
Unknown)
13 Unique Values
(K-12)
47 Unique Values
18 Levels
Variable Name Description Groupings /Range
Referral &
Demographics
childjd
received_date
referral_status
language_grouped
student_preferred_I
anguage
insurance_cove
_type
primary_contact
race_ethnicfty_grou
ped
student_gender
student_grade
referrer
provider_partner
reason_count
complexity_level
r,
/Oregon Rural Practiceha5ed
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Aggregated race/ethnicity
categories for analysis
Gender identity of the
student
Grade level of the student
Individual or role making
the referral
Behavioral health agency
receiving the referral
Number of distinct reasons
listed for referral
Assessed complexity of
student needs
Continuous (Range:
1 —15)
3 Levels (Low,
Medium,High)
•
o (0%)
0 (0%)
0 (0%)
0(0%)
0(0%)
0(0%)
0(0%)
0(0%)
°(0%)
0(0%)
°(0%)
0(0%)
°(0%)
°(0%)
35
Classification of school
level
District where the student
is enrolled
Total student enrollment
count at the school
Log-transformed
enrollment count (for
modeling)
Percentage of students
with disabilities at the
school
Percentage of mobile
(transient)students at
school
Percentage of low-income
students at school
School-wide discipline rate
(suspensions/expulsions)
Indicator if student was
matched to a provider
Indicator if student
successfully enrolled in
4 Levels
(Elementary,
Middle,High,
Other)
2 Levels tRenton,
Seattle)
Continuous (Range:
1 -479)
Continuous (Range:
0.69 -6.17)
Continuous (Range:
0%-100%)
Continuous (Range:
0%-16.7%)
Continuous (Range:
0%-83.3%)
Continuous (Range:
0.01 -0.16)
Binary (0/1)
Binary (0/1)0(0%)
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School
Environment
Variables obtained trom Washington OfIce of Superintendent of
Public Instruction (OSPI)Report Card,202310
school_thstrict 1
log_aflstudents
pd_disability
J
0(0%)
0(0%)
0(0%)
0(0%)
0(0%)
0(0%)
0(0%)
3 (1.5%)
pdjowincome
discipline_rate_flu
m
Outcomes &TiminA
matched_flag 0 (0%)
enrolled
tat_match_days
tat_enroll_days
c care
Date the match occurred Jan 10,2024 —Nov 16 (8.1%)
_______________
19,2025
Date the enrollment was Aug 13,2024 -Nov
______________
confirmed 10,2025
Days elapsed between Continuous (Range:17 (8.6%)
___________________
Receipt and Match 0 —75 days)
Days elapsed between Continuous (Range:
__________________
Match and Enrollment 6 —307 days)
Reason for seeking referral 3 Levels (Crisis 0 (0%)
Externalizing,and
Internalizing)
‘Note:High missingness in enrollment fields is expected as it represents students who are either currently in process
(censored)or did not enroll.2 To facilitate analysis of student clinical needs,referral reasons were aggregated into three
mutually exclusive categories based on the primary symptom presentation:Crisis,Externalizing,and Internalizing.This
classification was hierarchical,prioritizing the highest level of acuity and behavioral visibility.Any referral indicating immediate
119 (60.1%)1
119 (60.1%)1
safety risks—such as suicidal ideation,self-harm,or psychiatric events—was classified as Crisis (n=54),regardless of other co
occurring symptoms.Students not presenting with crisis markers were categorized based on the directionality of their
symptoms.Externalizing behaviors (n=84)were defined by outwardly directed actions,including aggression,substance abuse,
truancy,and disruptive conduct,Internalizing behaviors (n=60)encompassed inwardly focused emotional struggles,such as
anxiety,depression,trauma,and grief.In instances where students exhibited a “mixed’presentation of both internalizing and
externalizing symptoms (without crisis markers),cases were grouped under Externalizing to capture the disruptive behavioral
component often driving the referral urgency in school settings.
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Hispanic or Latino
White or Caucasian
Other/Multiple
Language (Ref:English)
Other Language
School Level (Re1:Elementary K-5)
Middle School (6-8)
High School (9-12)
School Characteristics
Log (Total Student Enrollment)’
Percent Disability2
40 2.33
30 4.54
30 7.65
134
21 2.16
28
96 0.71
31 3.07
155 0.31
155 0.002
1.30 -3.59
0.36-1.39
0.95 -9.91
0.18 -0.52
<0.001 -0.06
0.003
0.319
0.061
<0.001
<0.001
Supplemental Table 2.Cox Proportional Hazards Model Results for Time to
Enrollment
Black orAfrican American 43 1.99 0.64 -6.24
0.74 -7.35
1.58 -13.05
2.54 -23.07
0.23 7
0.149
0.005
<0.001
Note:Bold values indicate statistical significance at p <0.05.Robust standard errors were used,clustered by provider partner.
Footnoted variables are obtained from Washington Office of Superintendent of Public Instruction (OSPI)Report Card,2023.
‘Log-transformed population of students;HR <1 indicates that as school size increases,the rate of enrollment significantly
slows.2 Count of students identified as being a student with a disability/student population.
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