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Microsoft Healthcare United States

Zimmer Biomet

Risk Management

The company believed that better information about a patient’s recovery could notify clinicians of slow progress or unusual symptoms. Zimmer Biomet needed to develop a broad AI framework with customized algorithms to analyze the data and help patients and clinicians understand specific aspects of their recovery progress.

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Zimmer Biomet, a medical technology company with more than 90 years of experience, is leading responsible AI for healthcare with customized algorithms that predict patient gait speed recovery after hip and knee replacement surgeries.
mymobility collects gait data and patient-reported data, which WalkAI uses to predict which patients are on track with their recovery and which are expected to have a lower gait pace (compared to similar patients) 90 days after a knee or hip replacement.

Reported impact

Business outcome

Zimmer Biotech credits its AI framework with helping it revolutionize the industry, and the company is seeking new ways to improve patient outcomes through objective data. “With WalkAI, we’ve created the first AI-based predictive analytics model in orthopedics,” says Ivan Tornos, President and Chief Executive Officer of Zimmer Biomet. “We have a relentless focus on investing in innovation that will enable our customers to deliver best-in-class care for the patients they serve and breakthrough technologies like WalkAI help move our mission forward.”

  • Cost Reduction
  • Customer Experience
  • Risk Reduction

Solution

The company believed that better information about a patient’s recovery could notify clinicians of slow progress or unusual symptoms. Zimmer Biomet needed to develop a broad AI framework with customized algorithms to analyze the data and help patients and clinicians understand specific aspects of their recovery progress. Zimmer Biomet, a medical technology company with more than 90 years of experience, is leading responsible AI for healthcare with customized algorithms that predict patient gait speed recovery after hip and knee replacement surgeries. The company’s WalkAI™ technology, backed by its broader AI framework, allows patients and clinicians to monitor individual recoveries from knee or hip replacement surgery using data from the mymobility® patient engagement app.

Solution architecture

2 components · 2 layers
  1. Compute
    • Azure Machine Learning Supports model training, experimentation, and deployment for custom machine learning workloads.
  2. Orchestration
    • Azure DevOps Coordinates engineering workflows, source control, and delivery processes across development teams.

Architecture clues

  • Azure DevOps: Coordinates engineering workflows, source control, and delivery processes across development teams.
  • Azure Machine Learning: Supports model training, experimentation, and deployment for custom machine learning workloads.
  • Zimmer Biomet, a medical technology company with more than 90 years of experience, is leading responsible AI for healthcare with customized algorithms that predict patient gait speed recovery after hip and knee replaceme
  • mymobility collects gait data and patient-reported data, which WalkAI uses to predict which patients are on track with their recovery and which are expected to have a lower gait pace (compared to similar patients) 90 day

Evidence from the source

The company believed that better information about a patient’s recovery could notify clinicians of slow progress or unusual symptoms. Zimmer Biomet needed to develop a broad AI framework with customized algorithms to analyze the data and help patients and clinicians understand specific aspects of their recovery progress.
The medical technology company Zimmer Biomet has a long record of supporting orthopedic patients and clinicians through technical innovations. The company’s mission to alleviate pain and improve quality of life spurred exploration into how technology can empower clinicians and patients before, during, and after orthopedic surgeries.
The mymobility app is part of Zimmer Biomet’s broader ZBEdge™ ecosystem, a suite of digital health tools, robotics, and implant technologies. ZBEdge offers hospitals and ambulatory surgery centers access to pre-, intra-, and post-operative technologies through an integrated product experience.
Zimmer Biomet, a medical technology company with more than 90 years of experience, is leading responsible AI for healthcare with customized algorithms that predict patient gait speed recovery after hip and knee replacement surgeries. The company’s WalkAI™ technology, backed by its broader AI framework, allows patients and clinicians to monitor individual recoveries from knee or hip replacement surgery using data from the mymobility® patient engagement app.
Zimmer Biotech credits its AI framework with helping it revolutionize the industry, and the company is seeking new ways to improve patient outcomes through objective data. “With WalkAI, we’ve created the first AI-based predictive analytics model in orthopedics,” says Ivan Tornos, President and Chief Executive Officer of Zimmer Biomet. “We have a relentless focus on investing in innovation that will enable our customers to deliver best-in-class care for the patients they serve and breakthrough te
Transparency Evidence & methodology 75/100 reference value · 87% 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 value75/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth15/25
    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 impact15/25
    1 metric describe measurable impact.
  • Deployment scale5/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence87%
  • 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 evidence20/20
    5 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 specificity8/10
    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. Microsoft

    Zimmer Biomet customer story

    First-party
    https://www.microsoft.com/en/customers/story/1679005558310406801-zimmer-biomet-health-provider-azure-en-united-states
    Source type
    Vendor-published customer story
    Published
    Sep 11, 2023
    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

  • Published on source page Sep 11, 2023 · Microsoft · First-party
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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