Trauma-Informed Data Collection Infrastructure: Leveraging your Homeless Management Information System (HMIS) to Support Trauma-Informed Care

Trauma overwhelmingly and disproportionately impacts people experiencing homelessness. Homelessness itself represents a profound and multifaceted trauma, as people who are unhoused endure not only the daily challenges of survival but also a heightened vulnerability to violence and victimization. An overwhelming number of people experiencing homelessness exhibit symptoms of Post-Traumatic Stress Disorder (PTSD), with those experiencing chronic homelessness most highly impacted (Deck & Platt, 2014). Chronic and recurrent homelessness have been correlated with experiences of developmental trauma and childhood abuse (Hopper, et al., 2010). People experiencing homelessness face trauma preceding their homelessness at much higher rates than the general population, with studies showing up to 90% experiencing lifetime trauma (as opposed to 50-60% of the general population) (Dinnen, et al., 2014).

This paper emphasizes the importance of addressing trauma at all levels of the homelessness response system, focusing most closely on applying a trauma-informed approach to homelessness data infrastructure and Homeless Management Information Systems (HMIS).  The paper serves to propose a working definition of trauma-informed data collection infrastructure, propose six best practices for approaching a trauma-informed HMIS infrastructure, and identify six strategies homeless service systems can use to leverage their HMIS to support trauma-informed care.

Addressing Trauma in the Homeless Service Sector

Increased awareness and recognition of the pervasiveness of trauma experienced by people who are unhoused has led to widespread interest and adoption of trauma-informed care (TIC) across the homeless service sector. While there is no one definition for trauma-informed care can best be described as “a strengths-based framework that is grounded in an understanding and responsiveness to the impact of trauma, that emphasizes physical, psychological, and emotional safety for both providers and survivors, and that creates opportunities for survivors to rebuild a sense of control and empowerment” (Hopper et al., 2010, p. 82). Trauma-informed care is founded on six principles: safety, trustworthiness and transparency, peer support, collaboration, empowerment, humility, and responsiveness (Trauma-Informed Care Implementation Resource Center [TIC IRC], 2021). Trauma-informed care is a human-centered approach to care. In the human-centered approach, the experiences and needs of those served are central to developing and implementing services (Landry, 2020).

Trauma-informed care has been shown to improve participant service engagement, service outcomes, and provider and staff wellbeing across a variety of health and service sectors (TIC IRC, 2021). In the homeless service sector specifically, trauma-informed care is associated with improved housing outcomes. Integration of trauma-informed care principles in homeless service provision is correlated with higher rates of housing stability when exiting homelessness (Hopper, et al., 2010; Lisitski, 2019).

The Necessity of Trauma-Informed Perspective at All Levels of the System

Studies suggest that trauma-informed interventions are less effective when delivered in a context or setting that is not trauma-informed (Lisitski, 2019). This indicates that trauma-informed care should not be an addition to the services available in a system of care; rather it should be integrated at all levels (Clervil & Decandia, 2013; Crawford, 2022). One method to integrate trauma-informed care principles across all domains in a system is the trauma-informed approach. The trauma-informed approach is a mechanism through which organizations and systems of care incorporate trauma-informed care’s principles at the clinical, organizational, and structural levels of a system (TIC IRC, 2021). The trauma-informed approach identifies ten implementation domains: training and workforce development; governance and leadership; cross sector collaboration; financing; physical environments; engagement and involvement; screening, assessment, and treatment services; progress monitoring and quality assurance; policy; and evaluation (Substance Abuse and Mental Health Services Administration [SAMHSA], 2023).

While many homeless service systems have effectively used a trauma-informed approach to implement trauma-informed care in their practice domains such as treatment and assessment, implementation in structural domains, if addressed at all, is not always as effective (Knight, 2019; Levenson, 2020; Twis, et al., 2022). There are general principles available to guide systemic application of the trauma-informed approach in social service organizations; however, there is a lack of specific guidance for homeless service systems which have unique considerations (Twis, et al., 2022). The National Center on Family Homelessness developed the Trauma-Informed Organizational Toolkit, designed to help homeless service organizations self-assess and create organizational change. The toolkit provides guidance on creating organizational change, focusing most of the content on a self-assessment that serves as a current state analysis for organizations looking to implement a trauma-informed approach. This guide is an excellent starting place; however, the guide is limited to a few implementation domains (training and workforce development, physical environments, and policy), focuses primarily on a current state analysis, and does not mention a structural element common to almost all homeless service systems in the United States: HMIS. 

Trauma Informed Approach and Homeless Management Information Systems

HMIS stands at an intersection of several of the 10 trauma-informed approach implementation domains, including (but not limited to) screening, assessment, and treatment; progress monitoring and quality assurance; evaluation; and, in many communities; governance and leadership, policy, and cross-sector collaboration. Despite this, little guidance is available on implementing trauma-informed approach in HMIS practices. In fact, groups convening to plan trauma-informed practices in their homeless service systems sometimes leave out the data governance side entirely (Crawford, 2022).

When not planned using a trauma-informed and human-centered lens, data collection can result not only in traumatizing and exploitative experiences for people experiencing homelessness, but also result in lowered trust between the participant and provider, leading to poor-quality data–particularly when the data collection is intrusive and imposed (Buer, 2023). The US Department of Housing and Urban Development (HUD) recognizes the importance of human-centered data collection, stating in the most recent data standards that “communities [should] employ a person-centered approach to the review and use of the HMIS Data Manual with a clear foundational understanding of racial trauma and trauma-informed practices, cultural humility, and a person first, data-informed perspective” (HUD, 2024). Much guidance is available to set up HMIS in ways that collect all required information and conform to HUD HMIS Data Standards, but not always how to do so in a way that is trauma informed.

Trauma-Informed Data Collection Infrastructure

Many best practices around human-centered and trauma-informed data collection rely on the assumption that the data collectors have control over the data they are collecting. In the homeless service sector, at least some of the data being collected is prescribed by the funder. Many of the required data elements address areas that may be traumatic for service participants, including domestic violence, labor exploitation, and human trafficking. In trying to ascertain eligibility or prioritizing participants for resource allocation, homeless service systems may ask additional questions about participants’ vulnerability and violent experiences. The sensitive nature of much of the information collected and stored in HMIS, combined with the high prevalence of trauma and PTSD in the population served, leads to a need to establish data collection practices and infrastructure that are human-centered and trauma-informed. 

Defining Trauma-Informed Data Collection Infrastructure

Currently, there are not well-established standards for what constitutes a trauma-informed data collection infrastructure; however, there are guiding principles for organizational and structural adoption of the trauma-informed perspective (Cervil & DeCandida, 2013; trauma-informed approach IRC, 2021). There are also guidelines for trauma-informed data collection practices (Fisher & Paradise, 2019; SAMHSA, 2023). We draw on these resources to develop an early and working definition of a trauma-informed data collection infrastructure: 

A Trauma-informed data collection infrastructure consists of hardware, software, networking, services, and policies that are designed and configured with a grounded understanding of and sensitivity to the impacts and experiences of trauma. The infrastructure meets the following qualifications:

• Databases and database related workflows are set up to support trauma-informed care principles as they pertain to assessment, screening, data collection, data sharing, and storage.

• Data fields, screens, and templates are configured in such a way that it is possible for providers and assessors to apply trauma-informed care principles when using these tools to collect data.

• Data collection infrastructure, including tools and workflows, at a minimum, do not serve as a barrier to the provision of trauma-informed care, and, ideally, facilitate increased application of trauma-informed care principles.

Proposing Best Practices for a Trauma-Informed HMIS Data Infrastructure

The following proposed best practices are based on an understanding that HMIS should meet the definition proposed for a trauma-informed data collection infrastructure. They are also based on the trauma-informed care core principles and adapted to apply to HMIS infrastructure.

Center Participants in Data Collection

A human-centered approach is core to the trauma-informed approach. Data collection decisions and workflows should center around participant experience and needs. People with lived expertise should serve as key decision-makers in data collection infrastructure set up. People with lived experience should also regularly be asked for feedback (and fairly compensated for such feedback) on their experience of workflows. Without centering participants in the implementation of data collection practices, the associated work would not be considered human-centered.

Focus on Anti-Oppressive Practices

Anti-oppressive practice is critical to providing trauma-informed care. Anti-oppressive practice actively recognizes that oppression is present at the structural, cultural, and personal levels of our society (CICMH, 2022) and works to mitigate and equalize power imbalances by centering the experiences of equity-deserving and marginalized groups. 

The way data collection is structured in HMIS can contribute to structural inequities and reflect systemic bias. A great example of this is the Vulnerability-Index Service Prioritization Assistance Tool (VI-SPDAT), an assessment often used in HMIS. This tool was adopted across the United States and Canada and used for years in many communities as the key factor in prioritizing allocation of housing resources. Now, it is widely recognized that VI-SPDAT scores are not a reliable measure of vulnerability and, in fact, show evidence of racial and gender bias (Cronley, 2020). Yet, for many years, this tool was a key deciding factor in resource allocation.

Use a Minimalist Approach to Data Collection

The minimalist approach builds off the human-centered and anti-oppressive approaches. There are many things that are interesting or potentially useful to collect information about; however, not all of it is necessary to connect people to housing and services. Center data collection practices on collecting only what is necessary to connect people to services and meet their immediate needs. Consult with people with lived expertise of homelessness who have experienced the data collection processes a community uses to better ascertain what is useful and what is interesting.

Take a Harmonized Approach to Community Data Collection

With minimalism comes a need for collaboration and harmony across service providers and organizations in a system. Collaborate as a system of care on data collection points. Many parts of a system need to collect the same kinds of information. Find points where this information can be shared rather than re-collected. Also, find points where sharing may not be necessary and may in fact cause harm, re-traumatization, or make a participant feel unsafe.

Prioritize Physical, Emotional, and Psychological Safety

It is critical to prioritize participant safety over system data collection needs.  It is critical that rapport be built between data collectors and participants to ensure participants feel safe and supported while providing sensitive self-report data. Thus, items should be worded and asked in ways that do not compromise participants’ emotional and psychological safety. Data collection workflows should ensure participants’ physical safety is explicitly prioritized. Participants should have multiple opportunities to consent or withdraw consent for data collection. They should also only be asked sensitive questions in places they feel comfortable and safe.

Ensure Data is Private and Secure

Trauma-informed data collection infrastructure needs to be secure and private. Participants should always know where their data is stored, who can see it, and why. Any related workflows, such as reporting or case conferencing, that use private participant information should also be secure and private to ensure the information is shared and stored in ways that conform to data privacy standards. Any outside systems should also include privacy agreements to which participants can consent.

Trauma-Informed HMIS Strategies

We use the best practices above to illustrate six actionable strategies CoCs can implement in their HMIS to leverage the system to support trauma-informed practices, meet the definition of a trauma-informed data collection infrastructure, and follow the proposed trauma-Informed HMIS best practices. We begin by addressing the simplest and most accessible strategy: an HMIS assessment crosswalk and field analysis. Next, we address three more involved configuration strategies that can be planned after conducting a crosswalk and analysis:

1. Configuring cross-functionality between screens,
2. Tailoring display names and tooltips, and
3. Enabling data cascading.

Finally, we propose two higher-level systemic strategies:

1. Trauma-informed policies and tools to support participant autonomy and
2. Trauma-informed coordinated entry functionality and workflows.

HMIS Assessment Crosswalk and Field Analysis

A crosswalk is a strategy designed to compare fields across a variety of sources. A field analysis is a strategy designed to analyze the information intended to be collected by each field in a database. An HMIS assessment crosswalk and field analysis is a process designed for a community to compare fields across different HMIS assessments and other data collection screens (such as enrollment screens) to 1) identify which fields are present across multiple data collection tools and 2) identify unique fields designed to collect the similar or the same information as other existing fields. 

The crosswalk and field analysis strategy provides opportunities for CoCs to engage in minimalist and harmonized approaches to their data collection screens. Ensuring the workgroup includes stakeholders representative of the people who will be using the tools (both participants and front-line staff) provides opportunity for a human-centered design process. Ensuring the workgroup is diverse and representative of the participants in a homeless response system works towards an anti-oppressive approach to HMIS infrastructure design. 

To complete an HMIS assessment crosswalk and field analysis, it is recommended to convene a working group of stakeholders representative of the gender, ethnic, and racial makeup of the people served in the community by the homeless service sector. The workgroup should include HMIS administrators, people with lived experience of homelessness, and front-line staff using the data collection tools. The workgroup should gather all assessments, other data collection screens, and a list of all fields used in their HMIS. To complete the assessment crosswalk, use a spreadsheet to compare assessment fields across each assessment. Identify fields collecting the same or similar kinds of information. Note whether these fields are the same or different fields and, if the same, whether data cascades between assessments. This means data from one assessment or screen auto-populates to another assessment or screen. 

To complete the field analysis, begin by grouping all fields in the HMIS by high-level topic. Once this is complete, begin identifying fields that are designed to collect the same information. Once the workgroup has completed the initial crosswalk and analysis, it is time to make decisions. Identify redundant fields, both across assessments and in the system in general. Make decisions about which fields can be removed because they are duplicative. Once these decisions are made, make changes to the affected assessments by updating the fields both inside and outside HMIS as necessary.  

Bitfocus can provide hands-on support for communities using Clarity Human Services who want to complete an HMIS assessment crosswalk and field analysis by providing a robust suite of tools, workgroup administration, project management support, change management support, and configuration support tailored to community needs.

Data Cascading 

Data cascading allows the data collected in one screen to automatically populate in other screens where the same field is used. An example of this would be information collected during a program enrollment or coordinated entry assessment auto-populating into fields in a case management or housing navigation assessment. This allows the case manager or navigator to see information but not have to ask the participant the same question they already answered previously and consented to share. 

When done with careful consideration to the participants’ autonomy and right to privacy, data cascading serves to minimize the data collection burden on the participant and limit retraumatizing questions. It also may serve to improve data quality by increasing the consistency of information across assessments. Finally, enabled data cascading may serve to improve performance on data analysis tools embedded in or external to the HMIS by limiting the number of fields that are pulled into the data analysis tool. For example, Clarity Human Services uses Looker as an embedded and standalone data analysis tool. Many communities using Clarity Human Services rely on robust dashboards built in Looker for reporting, performance management, evaluation, coordinated entry, case conferencing workflows and more. The number of fields that are pulled into Looker can impact the speed the dashboards load. More data cascading can lead to fewer needed fields and lower loading times for dashboards important in the day-to-day work of a homeless service provider.

Enabling data cascading functionality can be a natural next step after completing an HMIS assessment crosswalk and field analysis, thus lending itself towards a harmonized and minimized approach to data collection. It can also be explored without completing a full crosswalk and analysis, though likely some cross comparison will be necessary when making decisions. If the community has already completed a crosswalk and analysis, data cascading functionality can be embedded into the decision-making process. If the community has not, it is recommended to conduct a cursory 

When making decisions about enabling data cascading functionality, it is important to consider a few things. First, will the cascading data help reduce the assessment burden on the participant? Will it reduce the possibility of possible re-traumatization for the participant? On the flip side of this is the importance of the participants’ privacy and autonomy when it comes to sharing sensitive information. Is it made clear to the participant that sensitive information they discuss during one data collection phase will be made available to other service providers at later data collection phases? When making these decisions, it is recommended to consult people with lived experience of homelessness to ensure decisions are made using a human-centered and anti-oppressive approach.

Clarity Human Services makes enabling data cascading easy, allowing communities personalized control over the age of data cascaded as well as the direction of the data cascading. 

Screen Cross-Functionality

Screen cross-functionality refers to the mechanisms through which different data collection screens in an HMIS can communicate with one another to improve workflows and minimize duplicative data collection. Data cascading is one type of screen cross-functionality, but this section refers to more advanced configuration and functionality which includes—in addition to data cascading—calculations, hidden fields, conditional formatting, and display constraints. 

Because this functionality is so broad and implementation is highly community specific, configuration decisions and implementation should take place as part of a broader analysis of a community’s assessments and data collection screens (such as the previously mentioned Analysis Crosswalk and Fields Analysis or the current state analysis discussed in the next section), during a coordinated entry improvement project, or as part of the process of adding new assessments or screens to a current community workflow. To connect this functionality back to the trauma-informed approach, we will provide a few use cases highlighting how screen cross-functionality can be used by a community to leverage their HMIS as a trauma-informed database. These use cases center on participant safety and security, while also using a human-centered, harmonized, and minimalist approach. 

From Assessment to Treatment Plans

Information collected on an enrollment or assessment screen can auto-populate information on screens used later in the service provision process. A large CoC seeking opportunities to lessen the data collection burden on their participants configured their Goal Plan screen in such a way that information from their initial assessment automatically created goal categories based on a previous needs assessment. Questions about health, safety, and other sensitive subjects in the needs assessment were configured to generate a hidden score for the domain associated with the question. If the hidden score reached a threshold, a section would appear on the Goal Plan with items related to the domain. When implemented in the community, this process allowed case managers to focus on providing services to the participant instead of conducting further assessment of sensitive topics participants had already disclosed and agreed to share. Case managers could then ask whether participants wanted to talk about certain subjects in more detail, allowing for multiple points of consent in the process, a key piece to trauma-informed data collection (Futures without Violence, 2024). 

Communities interested in embedding this kind of functionality in their HMIS assessment workflows should ensure any decision-making groups include people with lived expertise of homelessness. They should also ensure they elicit feedback from people experiencing homelessness before implementing the process at a larger scale to ensure the new workflows are human-centered.

Protecting Privacy while Providing Care

The same strategy described above can be used in a similar fashion to prompt case managers to connect participants with services related to their needs without providing details of the participant’s related traumatic experience. Often, triage or coordinated entry assessors explore traumatic events with participants because they are related to the prioritization process. However, once the participant has moved through the assessment and prioritization stages of coordinated entry, the needs identified in previous stages are not always communicated to the service providers participants are working with. This can result in participants needing to re-disclose this information, despite agreeing to share it with all providers using the HMIS at the start of the process. Screen cross-functionality can be configured in such a way that service providers enrolling participants in their programs or completing assessments like the previously mentioned Goal Plan will be alerted to provide service referrals, mental health support, safety planning, and more without providing details unless the participant has explicitly consented. 

Identifying Opportunities for Screen Cross-Functionality

As previously mentioned, it is recommended that decisions about cross-screen functionality and how they can further systemic implementation of trauma-informed care should be embedded in larger work, such as a broader assessment and field analysis, coordinated entry improvement projects, or as part of a new community assessment workflow. It is important to center input and feedback from people with lived experience of homelessness in these review processes. Communities using Clarity Human Services have the opportunity to work with Bitfocus Professional Services or Community Administration to identify opportunities for this advanced configuration. Tiered support is available, ranging from consultation to implementation. 

Display Names and Tooltips

Display names and tooltips are two kinds of functionality embedded in most HMISs and comparable databases. Display name refers to the text that displays on the user-facing side of a database. For example, a field may be named “education_attained” in the database table, but its display name is “What is the highest level of education you have completed?” Tooltips refer to additional information available about a field if one clicks on or hovers over an icon or item. For example, if a field in Clarity Human Services has a tooltip attached to it, the tooltip text will appear when one hovers over the field display name with their mouse. The education field previously mentioned may have a tooltip that says something like, “if the participant has selected trade school, please specify the trade.”

The wording of data collection items (display names) and how these questions are asked (instructions via tooltips) can be excellent tools when implementing a trauma-informed approach to one’s data collection infrastructure. Items should be clear so that participants are providing the correct information while also being worded in ways that are trauma-informed, human-centered, and anti-oppressive. Instructions for collecting data associated with fields should include tips for eliciting information in a way that prioritizes participant psychological safety, builds rapport to ensure the participants feel comfortable with the data collector, and centers participant consent and autonomy by emphasizing the importance of participant choice in deciding what information to share with the data collector.

Communities have a few options when considering their system display names and tooltips, and the direction a community can choose will depend on their current state, including how their assessments are currently configured and what training materials they have for data collectors. It may be helpful for communities to begin by conducting a current state analysis to determine opportunities to update field display names to conform with trauma-informed care principles and opportunities for building in tooltips that provide instruction on how to collect data in ways that are trauma-informed. This current state analysis can be added on as part of an Assessment Crosswalk and Field Analysis or be conducted as an independent activity. In a current state analysis, a diverse and representative working group that includes people with lived experience of homelessness, front-line homeless response workers, and people with trauma-informed care expertise would review all existing community assessments and data collection screens, analyzing how assessment items are named and what instructions may be helpful to include for the data collectors. Once the current state analysis is complete, the workgroup would put together a list of proposed changes to field display names, tooltips, and other data collection training materials. Finally, these changes would be made in HMIS and to any accompanying paper forms.

The Bitfocus Professional Services team can provide hands-on assistance to communities using Clarity Human Services who want to conduct a current state analysis. The team provides various tiers of support, from serving as a consultant and subject matter expert on a community workgroup to leading the analysis, writing a recommendation report, and updating configuration. 

Policies and Tools to Support Participant Autonomy and Self-Determination

Trauma-informed services aim to empower participant decision-making with the goal of promoting a sense of control over participants’ own care in the service delivery environment (Levenson, 2017). HMIS data collection policies and procedures are usually provider focused—that is, there is a strong emphasis on data quality, timeliness, and security as it relates to legal requirements. To foster a Trauma-informed data collection infrastructure, equal if not more emphasis should be placed on policies and workflows that support and facilitate participant autonomy and self-determination. This paper emphasizes three primary mechanisms through which this can be achieved: privacy and consent policies, advanced sharing configuration, and participant-facing data collection screens and tools.

Privacy Policies and Consent to Share

A great starting place for many communities looking to implement a Trauma-informed data collection infrastructure is to ensure their policies and procedures center participant choice. While HUD provides baseline standards for privacy and data sharing requirements, communities often find these baseline requirements insufficient to ensure participants feel safe in sharing their private information with providers. In trauma-informed data collection, it is important to emphasize that participation is always voluntary and provide multiple decision points where participants can choose whether to continue the data collection process (Futures without Violence, 2024). In addition to providing multiple decision points, it is important to ensure language in participant-facing documents is written in an accessible way, provided in multiple languages and formats, and explicit about what information is shared, to whom, and why.

Review of current privacy notices, releases of information (ROI), and other HMIS-related privacy policies can shed light on opportunities for improvement. Communities using Clarity Human Services can work with the Bitfocus Professional Services team, which includes subject matter experts in HMIS policies, privacy, and trauma-informed care, to conduct an analysis and recommended improvements.

Advanced Sharing Configuration

Many HMISs offer advanced configuration options to tailor sharing to meet their community’s needs. For example, Clarity Human Services has advanced sharing functionality that includes system-wide, user-based, and agency-based (within and between agencies) sharing options, allowing for customized approaches to all aspects of a client record, including the client record itself, location, contact information, notes, files, assessments, services, program enrollments, referrals, and coordinated entry events.

First, it is important to assess the current state of sharing in HMIS. Does it conform to related policies and agreements? Are participants satisfied with how their data is shared? Once current state is understood, improvements can be planned and then implemented. It is important to include people with lived experience of homelessness in the analysis, improvement planning, and implementation stages of this process. Communities using Clarity Human Services can draw on resources from the Bitfocus Help Center to plan their sharing configuration or work with the Professional Services or Community Administration teams to get hands-on support.

Participant-Facing Data Collection Screens and Tools

Participant-facing data collection screens and tools maximize participant autonomy and self-determination by providing a means through which participants can disclose information about themselves privately and on their own terms. For communities using systems without participant-facing functionality, options may include paper forms a participant can fill out privately and return to a service provider, or a secure online data collection form that can be integrated into HMIS data collection workflows. Communities using Clarity Human Services may be interested in exploring a new participant facing module called the Client Portal. The Client Portal includes functionality that allows participants to complete assessments, schedule and view appointments with providers, upload documents, and send messages directly through HMIS using their phone, a computer, or a tablet. People with lived expertise and experience of homelessness were involved through the design process and provided input and feedback to ensure the Client Portal would meet the needs of the community.

HMIS Coordinated Entry Functionality

It is only recently that coordinated entry data elements became required as part of the HUD data standards. Many coordinated entry processes, such as prioritization, referrals, and case conferencing, still take place outside of HMIS. This can pose risks to participant data privacy. It can also, in some cases, inadvertently violate the consent provided by the participant to share their information in HMIS unless the outside data sharing is also covered by the agreement. By using advanced HMIS functionality, such as embedded data analysis tools, advanced reports, eligibility, referrals, and more, communities can manage their coordinated entry systems within HMIS rather than relying on external tools that are not always secure. This harmonized approach to coordinated entry centers on security and privacy, emphasizing the importance of participant consent in the data sharing process.

Referrals and Community Queues

Rather than using external spreadsheets with lists of participants for placement in certain project types, these lists can be managed directly in HMIS through a tool called the Community Queue. Community Queues are tools available in Clarity Human Services that allow users to triage and prioritize client referrals across programs, agencies, and systems of care. Up to 10 queues can be made, allowing communities to tailor each to meet the needs of the program type to which the queue is connected. Referrals can be made directly through the community queue. 

Prioritization

Prioritization can be tricky to complete within HMIS, so communities often rely on external tools, leaving data potentially unprotected. Clarity Human Services’ Tracked Characteristics (conditions based on fields in assessments), Assessment Processors (which create scores from assessments, which can be used later in the coordinated entry process), and Score Ranges (a setting configured to help matchmakers make decisions) allow for advanced and dynamic prioritization within HMIS. 

Case Conferencing and By Name Lists

Communities participating in Community Solutions’ Built for Zero (BFZ) initiative are likely familiar with using a by-name list as the primary tool during case conferencing. A by-name list is a list of all people currently experiencing homelessness in a community. It is often separated by population (chronic, veteran, family, youth, etc.) and can be prioritized according to the community’s prioritization protocol. Often, these lists are created and stored outside of HMIS. In fact, this is usually how it is explained by Built for Zero coaches. However, these lists can be created, stored, and shared within HMIS, keeping them secure, private, and accessible only to those with HMIS user agreements and the proper access role permissions. Communities using Clarity Human Services can use our BFZ templates to build a customized by-name list report they can access directly from HMIS.

Next Steps

An easy next step for communities looking to create a Trauma-Informed Data Infrastructure with their HMIS is to begin with training on trauma-informed care, the trauma-informed approach, and ethical and human-centered data collection. Often, only clinical staff have the opportunity to complete trauma-informed care training, but it is highly recommended to also train HMIS administrative staff and data collectors, such as coordinated entry assessors, triage staff, and diversion specialists. 

Collect Feedback from People with Lived Experience

As a Trauma-informed data collection infrastructure is a human-centered and anti-oppressive practice, it is important to center participant experience in the improvements being made in the system. Thus, it is important to collect feedback from people who are currently using the homeless service system. Use a trauma-informed perspective to guide the creation of any interview protocols or surveys created to collect this information. The annual Coordinated Entry Evaluation may be an excellent opportunity to collect this feedback as part of regular CoC operations.

Begin a Current State Analysis

All strategies described above (Assessment Crosswalk and Field Analysis, Date Cascading, Screen Cross-Functionality, Display Names and Tooltips, Policies and Tools to Support Participant Autonomy and Self-Determination, and HMIS Coordinated Entry Functionality) require some level of current state analysis before beginning the improvement process. The National Center on Family Homelessness’ Trauma-Informed Organizational Toolkit is an excellent tool to use when planning a current state analysis. Workgroups convening to complete these current state analyses should include HMIS administrators, people with lived experience of homelessness, front-line staff using the data collection tools, and stakeholders representative of the gender, ethnic, racial, and economic makeup of the people served in the community by the homeless service sector. It is also recommended to include people who have been trained in trauma-informed care.

Plan Improvements

Once the current state analysis is complete, begin to plan improvements. 

Conclusion

It is critical that the homeless service sector view the HMIS Data Standards and our HMIS data infrastructure through the lens of trauma-informed care. The proposed concept of a Trauma-informed data collection infrastructure can help provide a foundation on which to collaborate as a sector to embed the trauma-informed approach to all data-related aspects of the homeless service sector. The Trauma-informed data collection infrastructure best practices–centering participants in data collection; focusing on anti-oppressive practice; using a minimalist approach; using a harmonized approach, prioritizing physical, emotional, and psychological safety; and ensuring data is private and secure–can serve as an initial guide as we improve our data collection processes and infrastructure over time. Collectively, we can work to define and refine what it means to have a Trauma-Informed HMIS Data Infrastructure.

Bitfocus is committed to providing human-centered software that supports communities working to end homelessness. We understand the importance of viewing and interpreting the HUD Data Standards through a trauma-informed, human-centered, and anti-oppressive lens. Our team of over 95 professionals come to Bitfocus with diverse backgrounds in homelessness, human services, and technology. We are dedicated to supporting communities in their journeys to providing evidence-based, trauma-informed wrap-around services to end homelessness for their unhoused neighbors.

To learn more about our work in Trauma-Informed HMIS Data Collection Infrastructure, contact us

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