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Needs assessment

Understanding rural health needs, parish by parish

We are conducting a statewide rural health needs assessment to guide program funding. The work is being developed in partnership with state and local government agencies, rural partners, and patients.

Explore the map or choose a parish profile below. Each profile brings together health indicators, facility records, rurality, and identified RHTP projects, with the source and vintage shown alongside the data.

View profile

Parish profiles

{{ pl.name }} Parish →

Use the search to open any of Louisiana’s 64 parish profiles.
Rurality

Is my location rural?

Check a Louisiana organization or location before applying for Rural Health Transformation Program (RHTP) funding. Search by organization name, identifier, or address. The result shows the matched facility and the record used to determine it.

Check rurality
CSV with a name, address, or zip column · up to 100 rows

Search results

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The location falls in one of three categories.
Rural
The location meets the geographic rural definition

The matched ZIP is classified Rural or Partially Rural under the published methodology. This satisfies Pathway 1 geographic screening, subject to application review.

Not rural
The location does not meet the geographic rural definition

Pathway 1 does not pass for the matched ZIP. Facility designation or rural patient-share pathways may still apply.

Unspecified / not enumerated
The available records cannot support a determination

The organization or ZIP was not found, or the source lacks a classification. This is a data-coverage result, not evidence that the location is not rural.

Transitional At-Risk identifies a location near the rurality threshold that may be vulnerable to losing rural status as population or commuting patterns change. It is a planning flag, not a separate eligibility result: Pathway 1 passes only when the underlying geographic classification is Rural or Partially Rural. Applicants should review the classification and effective date shown in the result.
The challenge

Current rurality methods don't reach every patient

Census-tract codes like RUCA classify geography, not people. A clinic on the "wrong" side of a tract line, a new road that changed drive times, or a practice type no registry enumerates can all leave a genuinely rural patient outside the definition.

RHTLA's work is to expand the reach of these methods — layering drive time, service availability, and enumeration coverage on top of the federal codes — with the patient at the center of the determination, not the tract.

How Louisiana defines rural today

Primary pathwayRUCA 4–10
Alternate pathwaysFORHP · ZIP-level
Under studyDrive-time · access
Read the LDH rural eligibility definition & methodology (PDF) →
Matching runs on identifiers first — NPI, CCN, TIN — then a maintained alias table of legal and trading names. When only a name match is possible, the result names the record it actually matched and carries a confidence level. A proxy match is never substituted silently. Every determination can be reproduced from the stated methodology: the pathway applied, the record matched, and the source vintage used are part of the result — and the record is downloadable for your application file.
Home›Needs assessment›{{ parishName }} Parish

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As of: {{ asOf }} · every figure carries its source and vintage
Rural needs indexComposite score from 0–100. Higher values indicate greater combined health need and access barriers; weights remain provisional.
Need rankOrders all 64 parishes from greatest need (#1) to lowest relative need (#64).
ZIP codes assessedCount of ZIP-level records contributing to this parish profile, out of 542 statewide.

Need indicators

Indicators were selected when they were statewide, reproducible, relevant to rural health decisions, and maintained by a named public steward. They are grouped into vetted domains below. Bars show this parish (navy) vs. state (hairline).

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Services on file

One record per location. Counts are only as complete as registry coverage — read the coverage column with each count.

Facility typeIn parishRegistry coverageSource · vintage
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A zero means "none on file," not "none exists." Read each facility count with its named source and registry notes before drawing conclusions about local access.
{{ parishName }} Parish, LouisianaOpen this parish in the Atlas →

RHTP in this parish

Projects identified{{ parishProjects }}
Participating facilities{{ parishFacilities }}
See all program activity →

Ask about this parish

"What would close the primary-care gap in {{ parishName }} Parish?"

Ask RHTLA
Focus areas

Understanding rural patient needs, by domain

Statewide views · source vintages shown
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The challenge
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The RHTP response
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Program transparency

What RHTP plans to fund, and how progress will be tracked

Louisiana committed specific Year 1–5 outcomes to CMS. This page shows projects identified for funding and every committed target against its baseline — in one place, on the record.

Committed outcomes: establishing baseline

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The four headline targets from the state's application to CMS. Progress bars run baseline → Year-5 target.
(All committed outcomes are reported to CMS)

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Projects identified for funding

Identified projects are grouped by organization type and priority region. Selections are not awards, and funding amounts are not shown until awards are made.

Organization typeRegionProjects identified
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Grouped public view · 128 projects identifiedOpen project records in the Atlas →
This project is supported by CMS/HHS as part of a financial assistance award totaling $208,374,447.57, with 100 percent of funding provided by CMS/HHS.
Data & methods

Every figure has a source, a vintage, and a method

RHTLA is built to be checked. This page lists what the platform holds, how complete it is, and how the rural accessibility index is computed — so a determination can be reproduced by anyone.

Selected source inventory

Highlights the primary sources used across the public Atlas. This is not the complete field-level data dictionary; expanded source documentation is planned with the full methodology package.

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Facilities on file by type

Counts show records currently carried in the Atlas. They describe the registry, not a verified census of every operating facility.

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The displayed types match the Atlas facility layers: acute and specialty hospitals, FQHCs, rural health clinics, dental facilities, and pharmacies.

Rural accessibility index

A 0–100 composite of need and access, computed per ZIP and rolled up to parish:

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Weights are provisional — pending ORHTS sign-off and external academic review.

The three-state model

No silent blanks. Every lookup returns verified rural, verified not rural, or not enumerated — and a "not enumerated" result is a statement about the registry, never about the place.

For researchers

Full methodology documentation, a REST API specification, and bulk extracts are planned but are not yet published. The rural eligibility methodology below is available now.

Read the methodology (PDF) →
About RHTLA

Closing the gap between data and decisions for Rural Health

Louisiana's rural communities face uneven health needs, limited access to care, workforce shortages, and transportation and broadband barriers. Yet the data needed to understand these challenges is spread across multiple agencies, datasets, and systems, often using different measures and definitions of rural — making it difficult to see the full picture of need and determine where resources should go.

RHTLA.net closes this decision gap with a unified, AI-powered GIS platform built on high-quality, validated Louisiana-specific data and public health expertise. Designed for transparency and ease of use, it turns complex data into actionable insights — helping ensure rural health resources reach the communities that need them most. The project is developed with support from the Louisiana Department of Health's Office of Rural Health Transformation and Sustainability through a CMS/HHS financial assistance award totaling $208,374,447.57, with 100 percent of funding provided by CMS/HHS. The contents are those of the author(s) and do not necessarily represent the official views of, nor an endorsement by, CMS/HHS or the U.S. Government.

The portal is built by the UL Lafayette Center for Applied Artificial Intelligence in partnership with the NSF Accessible Healthcare through AI-Augmented Decisions Center and the Louisiana Center for Health Innovation.

AI and usability in an academic environment

Test the answer, not just the interface

Our academic team treats AI output as a claim to be checked. The assistant is grounded in named Atlas sources, exposes the evidence used, and is tested with rural partners, patients, public agencies, and researchers for clarity, accuracy, and appropriate trust. Usability sessions ask participants to complete realistic decisions and explain what they believe the result means.

How to use the Atlas

Choose a parish or ZIP, turn facility layers on and off, inspect a source-labelled indicator, or ask the assistant a question. Counts of zero should always be interpreted alongside the source and registry notes.

RHTLA Atlas with the map layers, health indicator controls, facility legend, and AI assistant visible Open the Atlas and try these tasks →

Example usability tasks

  1. Determine whether your organization is eligible as a rural provider and download the determination for your file. Does this help, is it clear, and is it accurate?
  2. Find the three indicators where your parish is worst relative to the state, and identify the source of each. Is this accurate, and how do you know?
  3. Find whether RHTP projects have been identified in your parish and for which organizations. What does that say about rural transformation, and what questions do you have?
  4. Find how many facilities of a given type are in your parish, and decide what a count of zero means.
  5. Ask the AI assistant about broadband, workforce, or access to clinical services in your parish, then decide whether you would trust the answer enough to put it in a federal application.
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Center for Applied Artificial Intelligence
Delivery partner

UL Lafayette Center for Applied Artificial Intelligence

caai.louisiana.edu →
This project is supported by CMS/HHS as part of a financial assistance award totaling $208,374,447.57, with 100 percent of funding provided by CMS/HHS.