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IBM Healthcare Brazil

Oncoclínicas&Co

Customer Service Automation

Oncoclínicas&Co needed to unify fragmented patient communication channels, reduce wait times and automate routine interactions without losing the personalized and empathetic experience patients expected.

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38% improvement in appointment attendance
75% lower disconnection rates, bringing it down to 10% from 40%
93% patient satisfaction score
98% reduction in wait times

Reported impact

Business outcome

Oncoclínicas&Co sharply reduced waiting and disconnects, improved appointment attendance and raised patient satisfaction while scaling digital engagement across its oncology network.

  • Customer Experience
  • Productivity Improvement

Solution

Oncoclínicas&Co engaged IBM and PROA.AI to redesign its digital engagement model around a governed automation and AI stack. The solution uses IBM watsonx.ai for natural-language processing and generative AI, IBM Cloud Pak for Business Automation with RPA to automate workflows such as scheduling and follow-up tasks, and IBM Cloud Pak for Integration to connect WhatsApp, chat and email through a single secure integration layer. Governance controls were added to align with Brazil’s LGPD requirements and reinforce trust. In practice, patient requests enter through unified digital channels, are routed through the integration layer, processed by automation and AI services, and then returned as real-time responses, confirmations and proactive reminders. The architecture lets Oncoclínicas scale service interactions across more than 140 units while keeping support consistent and timely.

Data flow

Patient messages from WhatsApp, chat and email flow through IBM Cloud Pak for Integration, where automation and watsonx.ai services classify, respond to and trigger workflows such as scheduling updates and reminders before results are returned through the same channels.

Solution architecture

3 components · 2 layers
  1. Compute
    • IBM watsonx.ai Provides the generative AI and natural-language-processing layer used to understand patient requests and generate responses.
  2. Orchestration
    • IBM Cloud Pak for Business Automation Automates scheduling and other patient-service workflows through RPA and workflow tooling.
    • IBM Cloud Pak for Integration Unifies WhatsApp, chat and email under a single secure integration framework.

Architecture clues

  • Real-time responses and proactive reminders are generated at scale
  • Serves more than 140 units across the healthcare network
  • Unified governance framework spans watsonx and Cloud Pak components

Evidence from the source

Reduced average wait times by 98% through automated scheduling and centralized channels.
The implementation also included IBM Cloud Pak for Business Automation with Robotic Process Automation (RPA) for workflow automation, and IBM Cloud Pak for Integration to unify WhatsApp, chat and email under a single, secured framework.
The solution leveraged IBM watsonx.ai studio for natural language processing and gen AI.
Transparency Evidence & methodology 100/100 reference value · 84% confidence · 1 source

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
    4 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence84%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence15/20
    3 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency8/10
    1 source reference 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. IBM

    Oncoclínicas&Co customer story

    First-party
    https://www.ibm.com/case-studies/oncoclinicas
    Source type
    Vendor-published customer story
    Published
    Dec 18, 2025
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date

Date evidence

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

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