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# Teray Johnson Puts Workflow at the Center of Healthcare Analytics
- URL: https://www.healthdatacon.io/dr-teray-johnson-puts-workflow-at-the-center-of-healthcare-analytics/
- Published: 2026-10-15T17:13:55.000Z
- Updated: 2026-10-15T18:39:47.000Z
- Description: At HealthDataCon 2026, Teray Johnson described how clearer dashboards, automation and staff participation improved hospital workflows, sharing reported gains in imaging scheduling and lessons from rebuilding physician outreach tools.
- Author: Health Data Management
- Tags: Americas

Healthcare transformation leader Teray Johnson, PhD reported a roughly 20% improvement in imaging order-to-scheduling time and four hours saved per scheduler each week during her October 15 presentation at [HealthDataCon 2026](https://www.healthdatacon.io/agenda/). Her account of projects at her previous employer, Lifepoint Health, placed those gains within a broader argument: useful analytics must connect directly to the work people need to complete.

Speaking in the Americas program, Johnson, PhD, an independent consultant, described how clearer reporting, automation and redesigned workflows supported imaging access and physician outreach. Her session, *Saving Time, Boosting Performance: Best Practices to Connect Data to Operations*, treated data translation as a practical leadership responsibility. Analysts need to understand the decisions their audiences face, and leaders need to know who will act when a metric changes.

![](https://storage.ghost.io/c/91/db/91db0927-dd9a-4578-9944-921da70f6885/content/images/2026/10/image.png)

Photo Credit: Courtesy of Dr. Johnson's October 15, 2026 HealthDataCon 2026 Presentation.

## Start with the decision and a shared definition

“Actionable data, on the other hand, is specific, relevant, timely and clear,” Johnson said. A number detached from its population, location or timeframe offers little direction. Her illustrative referral example added a percentage change, a division and a reporting period, giving leaders a defined problem to investigate rather than a vague indication that activity had fallen.

She described a sequence from current conditions to a baseline or benchmark, then to the gap, a recommendation and an assigned action. Understanding operations matters at every stage: an analyst cannot explain a bottleneck convincingly without knowing how work moves between people and systems. “Make sure that you understand the audience and the workflow before analysis so that you're not creating something in a vacuum,” she said.

During questions, Johnson recommended placing metric definitions prominently on dashboards so users interpret results consistently. She also urged designers to remove unnecessary complexity: “Make sure that your visualizations are as simple as possible.” That emphasis aligns with Microsoft's [design guidance](https://learn.microsoft.com/en-us/power-bi/create-reports/service-dashboards-design-tips?ref=healthdatacon.io), which recommends prioritizing audience needs, decision-relevant metrics and an uncluttered overview that readers can investigate in greater detail.

Johnson also described an early-career dashboard she had built without consulting its intended users. The reception was poor, she said, and the experience taught her that technical effort could be wasted when the underlying need had not been established. Her lesson was to ask operational questions before beginning the analysis, then keep checking whether the resulting view helped people do their jobs.

## Rebuilding the path from imaging order to appointment

Johnson's first case concerned paper imaging orders that could become lost or remain unscheduled. She described delays affecting patients in rural communities, where traveling to another facility could be difficult. Multiple electronic health record systems across Lifepoint's hospital network complicated efforts to create a consistent process.

She said she helped develop the business case for a custom imaging-order application, UMA, gathered developer bids and worked with schedulers, operational managers and executive sponsors on its design. AI-supported extraction of information from physician notes reduced manual entry. Users helped map existing workflows and shape the replacement, including standardized options for scheduling before or after prior authorization.

The reported results included an approximately 20% improvement in order-to-scheduling time, a 7% increase in outpatient referrals, a 3% increase in visits, and four hours of weekly time savings per scheduler. Johnson also described improved access and patient satisfaction. In the question period, she said a prior-authorization automation pilot at a few facilities substantially reduced denials, although she did not give a denial-rate figure.

Her approach reflects an established implementation principle. The Agency for Healthcare Research and Quality's [workflow toolkit](https://digital.ahrq.gov/health-it-tools-and-resources/evaluation-resources/workflow-assessment-health-it-toolkit?ref=healthdatacon.io) emphasizes that health technology changes both clinical and administrative work. In Johnson's account, the software rollout therefore included decisions about handoffs, staff responsibilities and local variation alongside technical development.

## Measure the process, the performance and the outcome

Johnson built Power BI reporting for different audiences. Operational managers wanted to see scheduling speed, daily order activity and productivity; executives needed a concise view of cycle times and emerging constraints. She described using those views to support discussions about staffing and sharing personnel across hospitals, connecting reporting to decisions about capacity.

“I measured process, performance and outcomes,” Johnson said. She examined how accurately the automation read physician notes and populated the application, brought problems back to developers, tracked scheduling performance and assessed patient satisfaction. She also described using agentic AI to help build software and dashboards, an experience she said saved development time.

The Institute for Healthcare Improvement's [measurement guidance](https://www.ihi.org/library/model-for-improvement/establishing-measures?ref=healthdatacon.io) distinguishes outcomes, processes and balancing measures, including whether an improvement creates problems elsewhere. For AI, the National Institute of Standards and Technology's [risk framework](https://nvlpubs.nist.gov/nistpubs/ai/nist.ai.100-1.pdf?ref=healthdatacon.io) calls for performance evaluation under conditions resembling deployment and monitoring during operation. These frameworks provide context for evaluating automation beyond its apparent speed.

The project figures remain Johnson's reported results. The supplied session transcript does not provide underlying datasets, baseline scheduling durations, evaluation periods or a comparison group. It consequently cannot establish how much improvement was attributable to software, workflow redesign or other changes, nor demonstrate improved clinical outcomes from higher referral and visit volumes alone.

## Replacing fragmented outreach tools with a common workspace

The second case involved growth and outreach liaisons cultivating physician and community relationships. Johnson said their legacy TrackVia application required too many steps, while relevant information was dispersed across systems. Reports could lag by one or two months, and managers lacked automated alerts when activity, such as surgical volume, declined.

She described replacing that application with a solution built in Palantir Foundry, combining provider information, encounter logging and performance reporting. Palantir's [application documentation](https://www.palantir.com/docs/foundry/app-building/overview?ref=healthdatacon.io) describes tools for turning data and actions into operational workflows; Johnson's account concerned how her team applied that capability. The project required coordination across business development, analytics, strategy, performance improvement, software development and IT.

Johnson said the replacement reached more than 60 hospitals and eliminated over $50,000 in annual legacy application costs. Those avoided charges are distinct from net savings: the presentation did not provide the replacement platform's full implementation or operating costs. She also described integrating data from another system so declining surgical volumes could trigger alerts and prompt managers to investigate.

Migration accuracy was central to adoption. Johnson worked with users to reconcile historical information and understand discrepancies, while office hours and staged implementation allowed requirements to evolve. “Being flexible was paramount as I created this software and built those dashboards,” she said.

She separated essential functions from later enhancements, using a phased plan with deadlines and measures of implementation success. The immediate requirement was for liaisons to record encounters, calls and events reliably; additional features could follow. Provider profiles were intended to reduce the time staff spent assembling information from separate reports before outreach, while preserving access to the details needed for conversations with community partners.

## Earn trust through participation and visible correction

Johnson challenged the assumption that pilot participants should all be highly technical. “One thing to remember is that these super users don't necessarily have to be the most technology savvy,” she said. People less comfortable with software could expose confusing steps that experienced designers overlooked, making their feedback especially useful before a wider rollout.

In the discussion, she returned to mapping current workflows with employees, agreeing on goals and explaining where the numbers came from. She described an open channel for questions and corrections, with many reporting problems addressed within 24 hours. That was her account of the project, rather than a formal service guarantee, and illustrated how responsiveness could strengthen confidence in both the team and its tools.

“There are always trade-offs, but by involving those users early, we can make sure that we can address most of their needs and the most critical needs so that we improve patient care and workforce experience,” Johnson said. She closed with a challenge to analysts that linked technical work back to operational judgment: “Make sure that you're staying curious, always asking the why behind the data.”