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How a US Home Care Provider Built the Data Foundation to Serve More Patients

Caregiver, patient, payroll and billing data sat in separate systems across home health and hospice. Parkar built one governed data foundation on Snowflake that gives caregivers and branches more time for patients, and prepares the provider to put AI agents to work in the near term.

  • Home care
  • Data foundation
  • Snowflake
  • AI readiness
A caregiver and an older man checking his health readings on a tablet at home

The business

Our client is a Southwest-based home care provider, and one of the largest in the US. It provides home health, hospice and personal care to tens of thousands of patients a day across more than a dozen states. Its mission is to serve more patients, and to help its caregivers give each one better care.

The challenge

More time for patients, and a clear view of the business

Time away from care

Visit checks, payroll tie-outs and mileage were reconciled by hand, taking time that branch teams could give to patients and caregivers.

No single view of caregivers and patients

Caregiver and patient records sat in separate clinical, HR and scheduling systems, so branches could not easily see who was free to take on new patients.

Different numbers in different programs

Home health and hospice used different systems and definitions, so leaders saw different numbers for the same question.

Caregivers paid right and on time

Visit, payroll and billing data had to agree, so caregivers are paid correctly and every visit is billed.

The solution

What we delivered

  1. Connect every systemDone
  2. One governed foundationDone
  3. Daily views for leaders and branchesLive
Every system connected
Automated pipelines bring in data from the clinical record systems, HR and payroll, billing, scheduling and vendor feeds, with monitoring that flags any failed load.
One governed foundation
A data foundation on Snowflake with shared business rules for home health and hospice, quality checks, duplicate records removed, and lineage for every number.
Daily checks, automated
Payroll, electronic visit verification (EVV) and mileage are reconciled automatically each day, with exceptions sent to the right branch.
Views for leaders and branches
Dashboards across programs and branches, built on the same numbers.

Results

The outcomes

60%

Less time on manual checks

Payroll, EVV and mileage are reconciled automatically each day, with only the exceptions left for people to review.

8 hours

A week back for each branch

Time that branch teams now give to patients, caregivers and new admissions.

One

Set of numbers

Leaders across home health, hospice and every branch now see the same figures.

Same day

Data issues flagged

Monitoring flags a failed load or a bad record the same day, before it affects care coordination, payroll or billing.

What’s next

AI agents on the same foundation

The provider plans to put AI agents to work in the near term. Each agent will read from the governed foundation, and a person on the care team will approve each step.

Referral intake

Read each referral, check coverage and match the patient to existing records, so new patients start care sooner.

Caregiver scheduling

Match each new patient to an available caregiver with the right skills, near the patient’s home.

Visit documentation checks

Check visit notes and OASIS assessments before claims go out.

Payroll and EVV exceptions

Prepare each exception with its likely cause, so branch teams resolve it in minutes.

Keep reading

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Industry Healthcare and Life Sciences Data and AI for health systems and home care providers. AI workflow · Healthcare Referral intake Admit more referred patients, sooner. Case study · Healthcare How a US Health System Is Modernizing Its Apps and Data for AI Applications and data modernized, with AI use cases now being scored.

Get started

Start with where your data stands.

A two- to three-week Data Readiness Assessment scores your platform, data quality and governance against your analytics and AI priorities, and ends with a ranked plan.

Download a sample report ›
Data Readiness Assessment2 to 3 weeks

Ends with a ranked list of work and clear next steps.

In the first phase
  • One business area on a modern data platform
  • One trusted data set in daily use
  • Governance in place on your first data set

From there we build in stages, starting where the payback is fastest.