PwC Healthcare United States

CareQuest Institute for Oral Health

Data Lake / Data Warehouse Modernization · Enterprise Knowledge Search

CareQuest needed to turn fragmented oral, medical, and social datasets into a secure self-service platform so researchers, policymakers, and internal teams could get timely insights without overwhelming a small central analytics group.

10X increase in the research output with only incremental increases in operating cost
5X increase in the number of users in just the first two months
90%+ reduction in response time for press inquiries—from days to hours
more than 1,500 queries across multiple internal functions and teams

Reported impact

Business outcome

CareQuest moved from manual, capacity-constrained insight delivery to a governed self-service model that drove 5x user growth, 10x more research output, faster press and policy responses, and broader collaboration across the oral-health ecosystem.

  • Productivity Improvement
  • Scalability
  • Speed to Market

Solution

CareQuest and PwC rebuilt a data program centered on a small analytics team into a governed, AI-enabled health data platform. Using Microsoft Azure as the foundation, the team created the Health Data Exchange to connect oral, medical, and social data in one trusted environment, standardize access controls, and make self-service analytics available to internal teams and external stakeholders. PwC also helped shift the operating model to a center of excellence responsible for governance, security, platform operations, and data science. On top of the platform, OpenAI-powered tools expanded access: AI Research Explorer lets users query CareQuest’s published research archive in natural language with links back to source papers, and AI Data Explorer lets users interrogate underlying datasets without waiting on the central analytics team. The architecture pairs AI interfaces with cost monitoring, thresholds, and alerts so the Exchange can scale responsibly.

Data flow

Oral, medical, and social datasets are loaded into the Health Data Exchange on Azure, standardized, and governed for secure self-service use. OpenAI-powered AI Research Explorer queries the published research archive with links back to source papers, while AI Data Explorer lets users interrogate underlying datasets and deliver insights to philanthropy, policy, communications, researchers, and partner organizations.

Solution architecture

5 components · 2 layers
  1. Compute
    • Microsoft Azure Provides the cloud foundation used to host and operate the governed data platform.
    • OpenAI Powers the natural-language interfaces used to query research and datasets.
  2. Serving
    • Health Data Exchange Serves as the trusted environment that unifies oral, medical, and social data for secure analysis.
    • AI Research Explorer Lets users query CareQuest’s research archive and returns synthesized answers with links to the original papers.
    • AI Data Explorer Allows users to interrogate underlying datasets directly without routing every request through the core analytics team.

Architecture clues

  • A center of excellence owns governance, security, platform operations, and data science.
  • AI Research Explorer links natural-language answers back to original source papers.
  • Cloud spend is monitored with thresholds and alerts to keep the Exchange sustainable as it scales.
  • The platform combines oral, medical, and social data in one governed environment.

Evidence from the source

AI Data Explorer lets users interrogate underlying data sets to perform data analysis independently.
AI Research Explorer allows users to query CareQuest’s deep archive of published research in natural language and rapidly obtain synthesized insights with direct links to original source papers.
In the first few weeks, the platform handled more than 1,500 queries across multiple internal functions and teams.
PwC helped CareQuest engineer a trusted, AI-enabled platform that turned fragmented data into a strategic asset—delivering the required insights at the right time—with only incremental operating costs.
What once took days of manual processing and capacity delays now takes minutes with AI-enabled self-service.
Transparency Evidence & methodology 100/100 reference value · 100% confidence · 3 sources

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value100/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    3 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence100%
  • Source authority25/25
    The deployment is described by the adopting organization or a government source.
  • Claim traceability25/25
    12 of 12 key fields link to a named source.
  • Direct evidence20/20
    5 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency10/10
    3 source references document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. PwC

    CareQuest: Building an AI-enabled health data platform: PwC

    First-party
    https://www.pwc.com/us/en/library/case-studies/carequest-ai-enabled-health-data.html
    Source type
    Vendor-published customer story
    Published
    Jun 5, 2026
    Supports
    • Customer
    • Region
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • Business outcome
    • Metrics
    • Architecture
    • Publication date
    • evidence quotes
  2. Cause IQ

    CareQuest Institute for Oral Health

    Independent secondary
    https://www.causeiq.com/organizations/catalyst-institute,384016550/

    The quick fields list Num. employees as 129 and Most recent tax filings as 2024-12-01.

    Source type
    Structured company profile
    Supports
    • Company size
  3. ProPublica

    Carequest Institute For Oral Health - Nonprofit Explorer

    Government-derived
    https://projects.propublica.org/nonprofits/organizations/384016550

    The IRS-derived summary lists Fiscal Year Ending Dec. 2024 and states that Form 990 data is from the IRS.

    Source type
    Government filing aggregator
    Supports
    • Company size

Date evidence

Not separately sourced Industry. Treat these normalized attributes as lower-confidence until a dedicated source is added.