You know the intake form that looks almost identical to two others in the dropdown. You know which one feeds the authorization workflow and which one feeds nothing. You know because a colleague showed you, and you have since shown every new clinician you onboard.
That knowledge is raw material. It’s precise, it’s grounded in daily practice, and it has a direct line to data quality, outcome reporting, and payer readiness. But right now it lives in hallway conversations and onboarding walkthroughs. This framework gives it a shape your whole organization can use.
Every Workaround Is a Finding Waiting for a Frame
Workarounds are adaptive. When a system does not support the way clinical work actually happens, frontline staff build solutions. Research on EHR workflows confirms what you already know: workarounds emerge when the system blocks the way the work actually needs to get done (Zheng et al., 2020). A JAMIA study of 2.5 million outpatient visits found over 100,000 unique templates across a single health center, with 83 percent used by only one clinician (Rule & Hribar, JAMIA, 2022). Each of those individual templates represents a clinician solving a documentation problem the system did not solve for them.
The most accurate diagnostic tool in any behavioral health organization is the workaround a clinician teaches a new hire on day three. It tells you exactly where the system is misaligned with the work.
What makes that diagnostic valuable to the broader team is structure. “The templates are confusing” is an observation. “Three versions of the intake form exist, only one feeds the outcome dashboard, and new hires default to the wrong one based on alphabetical order” is a finding. The difference is specificity, a downstream connection, and an implied cost. Observation, connection, cost. Three components that turn informal knowledge into something your team can sequence against.
The Observation-Connection-Cost Framework in Practice
Each of these follows the same pattern. You start with what you see in daily practice. You connect it to an operational or financial outcome your organization tracks. You estimate what it costs or risks. Adapt the details to your setting.
Template confusion. You see multiple versions of the same form in the template dropdown. The structured finding: “Program X has four active intake templates. Template A feeds the outcome dashboard. Templates B, C, and D do not. New hires are not trained on which to use and default to Template B based on display order. Intake data entered through the wrong template does not reach the outcome report, which means a portion of completed intakes are invisible to the reporting infrastructure.” That finding connects to data quality, outcome reporting accuracy, and payer audit readiness. It also gives the template cleanup effort a specific starting point: which templates, which program, which downstream report.
Screening data gaps. You see PHQ-9 scores documented in progress note narratives. The structured finding: “Clinicians in Program Y administer the PHQ-9 at intake and every 90 days per protocol. Scores are documented in the clinical narrative. The EHR’s discrete screening field is not populated during this workflow. These scores do not appear in HEDIS reporting queries or in outcome dashboards.” NCQA’s DMS-E measure requires PHQ-9 scores captured in discrete EHR fields, time-stamped and linked to diagnosis codes (NCQA, 2025). SAMHSA defines measurement-based care as the systematic use of validated instruments to track progress and inform treatment decisions (SAMHSA, 2023). The clinical practice is happening, but the data pipeline is not capturing it.
Handoff friction. You see information getting reconstructed manually when clients move between levels of care. The structured finding looks different from the first two because it spans programs: “When a client steps down from IOP to outpatient in Program Z, the outpatient clinician does not have access to the IOP treatment plan summary within the EHR workflow. Transitions each month rely on a phone call or printed summary.” That finding connects to continuity of care documentation, clinical risk during transitions, and the time cost of manual reconstruction. It also identifies a specific EHR configuration gap that can be scoped independently.
Three examples, one framework. The observations are already in your daily practice. The connection and the cost are what turn them into starting points for the optimization conversation.
Timing Is the Multiplier
Structured findings carry the most weight before sequencing decisions solidify. FY27 planning is happening now. Your organization’s leadership is weighing where to invest optimization effort first, and the specificity of the input they receive shapes the specificity of the plan they build. A one-page summary with three to five structured findings gives the planning conversation concrete starting points that would otherwise take weeks of formal assessment to surface.
This is a way of packaging expertise you already carry into a format the whole team can act on. The workarounds you navigate daily take energy. They cost you time you could spend with clients. The diagnostic detail embedded in that effort is what tells your organization where the EHR, the workflow, or the process needs attention first.
Xpio Health’s optimization engagements start with exactly this kind of frontline input, because the people closest to the workflows see what no dashboard can surface. If your team is ready to connect those findings to a structured optimization plan, we’re here to help you build it.
The difference between “the EHR is frustrating” and “here are three findings that connect to outcomes we report to the board” is the difference between an observation and a contribution. You already have the observations.
Xpio Health’s optimization work starts with exactly this kind of frontline input. If your team has findings that need a plan behind them, reach out. We’ll help you build one.
#BehavioralHealth #PeopleFirst #XpioHealth #EHROptimization #FY27 #FrontlineLeadership
References
- Zheng K, Ratwani RM, Adler-Milstein J. Studying Workflow and Workarounds in Electronic Health Record-Supported Work to Improve Health System Performance. Annals of Internal Medicine. 2020. https://pmc.ncbi.nlm.nih.gov/articles/PMC8061456/
- Rule A, Hribar MR. Frequent but fragmented: use of note templates to document outpatient visits at an academic health center. Journal of the American Medical Informatics Association. 2022. https://pmc.ncbi.nlm.nih.gov/articles/PMC8714279/
- NCQA. HEDIS Depression Measures Specified for Electronic Clinical Data. 2025. https://www.ncqa.org/hedis/hedis-depression-measures-specified-for-electronic-clinical-data/
- SAMHSA. Use of Measurement-Based Care for Behavioral Health Care in Community Settings. 2023. https://www.samhsa.gov/sites/default/files/ismicc-measurement-based-care-report.pdf
