Medical Device Innovation Consortium Device Product Quality Metrics - - PowerPoint PPT Presentation

medical device innovation consortium
SMART_READER_LITE
LIVE PREVIEW

Medical Device Innovation Consortium Device Product Quality Metrics - - PowerPoint PPT Presentation

Medical Device Innovation Consortium Device Product Quality Metrics September 8, 2015 1 Presentation Outline Topics to be Addressed Team Members Timeline and Process Pre-Production Metric Development Production Metric Development


slide-1
SLIDE 1

Medical Device Innovation Consortium

Device Product Quality Metrics September 8, 2015

1

slide-2
SLIDE 2

Presentation Outline Topics to be Addressed

Team Members Timeline and Process Pre-Production Metric Development Production Metric Development Post-Production Metric Development Pilot Study Design and Next Steps

2

slide-3
SLIDE 3

Team Members

First Last Title Company

Paul Andreassi * Vice President of Quality & Regulatory Fisher & Paykel Healthcare Pat Baird * Director, Engineering Baxter Healthcare Anupam Bedi * Director of Quality AtriCure Pankit Bhalodia Director PwC KB Bheda Senior Associate PwC Steve Binion Director Regulatory Affairs/Corporate Clinical Development BD Robin Blankenbaker Divisional Quality Operations Leader W.L. Gore & Associates Gina Brackett * Compliance Officer FDA Patrick Caines * Dir, Quality & Global post market surveillance Baxter Healthcare Kara Carter Senior Director, QA Operations Abbott Vascular Division Vizma Carver Founder and CEO Carver Global Health Group Ryan Eavey Senior Manager, Quality Systems Stryker

3

* Participated in initial work

slide-4
SLIDE 4

Team Members

First Last Title Company

Joanna Engelke Senior Vice President Global Quality Boston Scientific Chris Hoag Director of Global CAPA and Quality eSystems Stryker Frank Johnston Corporate Director, Regulatory Compliance BD Jonathan Lee Senior Associate PwC Bill MacFarland Director, Division of Manufacturing Quality FDA Kristin McNamara * Senior Advisor FDA Rhonda Mecl * Supervisory CSO FDA Brian Motter * VP Quality and Compliance, Diabetes J&J MD&D Ravi Nabar

  • Sr. Director Supplier Quality Management

Philips Steven Niedelman * Lead Quality Systems and Compliance Consultant King & Spalding LLP Pete Palermo * VP Quality Assurance CR Bard Marla Phillips * Director Xavier University

4

* Participated in initial work

slide-5
SLIDE 5

Team Members

5 First Last Title Company

Greg Pierce President and Founder Engisystems Susan Rolih * Executive Vice President, Regulatory and Quality Systems Meridian Bioscience, Inc. Joe Sapiente * VP Global Quality Operations Covidien Benjamin Smith Vice President, Global Quality System & Compliance Biomerieux Isabel Tejero * Quality System Workgroup Lead CSO FDA Shelley Turcotte WW Director Quality Information Systems DePuy Synthes Sam Venugopal Partner PwC Marta Villarraga Principal Biomedical Engineering Exponent Monica Wilkins * Divisional Vice President of Quality and Business Support Abbott

* Participated in initial work

slide-6
SLIDE 6

Purpose and Goals

Purpose:

– To support the Case for Quality by increasing the assurance of product quality

Goals:

1. Identify, pilot and publicize predictive product quality metrics 2. Improve assessment of the evolving state of product quality 3. Enable FDA risk-based resource allocation decisions 4. Provide Payor visibility to product quality risk

slide-7
SLIDE 7

Power and Benefits of Measures

Linkage to Critical Quality Systems Linkage to Total Product Lifecycle Linkage to Critical Requirements

Patient Safety Design Robustness Process Reliability Quality System Robustness Failure Costs

slide-8
SLIDE 8

Timeline and Process

Sept. 2014

  • Oct. 2014 –

Mar 2015 Mar – May 2015 Jun – Sept 2015

  • Oct. 2015 –

Jun 2016 Beyond Jun 2016

Kick-off Critical Systems Gold/Silver Activities C&E Matrix Finalization

  • f Measures

Selection of Top 3 Measures Pilot Pilot Analysis Finalization Conversion

  • f Measures

into Metrics Advanced Analytics Maturity Model FDA Risk Assessment Industry Risk Assessment Competency Initiative

slide-9
SLIDE 9

How we Chose the Top 3 Measures

Pre-Production Production

Transfer Production Continual Improvement & Risk Mgmt.

Enterprise-Wide Continual Improvement

R&D Continual Improvement & Risk Mgmt.

Post- Production

slide-10
SLIDE 10

Conversion of Top 4 Measures

Process Steps

  • 1. Reviewed the Pre-Work Packet for the Measure to be discussed
  • 2. Aligned on Common Terminology
  • 3. Revised/Improved Wording of Measure if Needed
  • 4. Discussed Metric Ideas Provided
  • 5. Proposed Final Metric(s)
  • 6. Repeated the Process for the remaining 3 measures

10

slide-11
SLIDE 11

Pre-Production

11

Identification of design and process elements that eliminate, reduce, and prevent design failures throughout the product lifecycle (including transfer, production, and post-production failures) Metric: – Design Robustness Metric Total # of product design changes driven by quality issues / total # of product designs *(factor for age)

  • Product agnostic
  • Measured by “Design Center” / Product Family / Business Unit (as

determined by the company, for their design control process)

slide-12
SLIDE 12

Pre-Production

  • It was determined that this would be better suited as

a guidance than a metric

  • Deemed out of scope for the work of this team

12

Evidence that customer input, both internal and external, is actively solicited, documented, and assessed, at all stages

  • f design project. This includes early feedback from

controlled market release (pilot) and post-launch VOC data from related products.

slide-13
SLIDE 13

Production

Metric: # of units mfg. without Non-conformances / # of units attempted

  • excludes planned rework and set up scrap
  • “units” can be changed out with “lots” if appropriate
  • Timeframe: Monthly
  • Metrics will be measured by site and if possible, by product
  • Metrics can also be measured by “value stream” (i.e. category of

products / work centers) and by site

  • Track and trend on a rolling basis

13

Tracking and trending of right first time data (i.e. product built with no non-conformance/rework/failed inspections).

slide-14
SLIDE 14

Post-Production

Metric: Complaints * (0.20) + Service Records * (0.10) + Installation Failures * (0.10) + MDRs * (0.10) + Recalls (units) * (0.10) + Recalls (total) * (0.10) + Design Changes * (0.20) + Non- conformances (0.10)

14

Trending/analyzing key post market surveillance data (e.g., complaints, FCAs, PHOs, HHEs) for overall QMS performance and feed into holistic QMS scorecard.

slide-15
SLIDE 15

Post-Production Index Metric

  • Complaints: Complaints for the product / units sold (for the product)
  • Service Records: Records per product / # of total units in service (for the period)
  • Installation failures: # of installation failures/ total # of installations (for the

period)

  • MDRs – MDRs for the product / units sold (for the product)
  • Recalls – # of units recalled / # of units sold (for the period) – worldwide (if

applicable)

  • Recalls - # of recalls (for the period) – worldwide
  • # of product Design Changes – Count for the period
  • Non-conformances - total # of NCs / # of units (produced, released, sold, etc.)

15

slide-16
SLIDE 16

Pilot Study Design

  • Each company chooses products/work centers to include in the

study that have differing levels of complexity and success

  • The study will only be retrospective, and participants have 6

months to complete the work

  • Goal: demonstrate that the metrics are sensitive enough to

differentiate between varying levels of product quality

– Companies will not be compared to each other – Pilot Companies to date: Biomerieux, J&J Diabetes, Stryker, WL Gore

16

slide-17
SLIDE 17

Immediate Next Steps

  • Virtual meeting on September 10th
  • Establish NDA with pilot companies
  • Pilot refinement with company input
  • Refinement of metrics tailored to company-specific

business

  • Launch of retrospective pilot October - March

17

slide-18
SLIDE 18

Pulling it All Together

AdvaMed Best Practices FDA/Xavier MDIC Metrics MDIC Maturity Model

MDIC Advanced Analytics MDIC Competency

Risk Assessment