Optimal Adoption of Healthcare Technology in the NHS

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(No Transcript)
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• Optimal Adoption of Healthcare Technology in the
  NHS

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What we were asked to do

• To develop a methodology to assess the optimal
  level of technology adoption, for medical devices
  and diagnostic techniques.
• To consider how his model will fit with the
  current Technology Adoption Centre selection
  process.
• To consider how the benefits of a technology can
  better be evaluated within the Technology
  Adoption Centre selection process.

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How many of these should there be in Britain?
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How many of these should you have in your home?
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Changing the shape of the adoption curve

• Units

Speed and optimum levels of technology adoption
changing to appropriate levels.

• Time

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Why is optimal adoption so important for the NHS?

• People missing out, dying etc.
• Limited resources
• Scope for better decisions

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Approaches to identifying optimal adoption
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Where are we now?

• A model is being tested by the TAC on the Supra
  Pubic Foley Catheter
• Could have value for SHAs, commissioners etc. who
  are trying to compare new ideas/innovations

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The output
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How we got there

• Literature review
• Nationally, optimal technology adoption the
  number of units required for the total benefits
  to most exceed total costs for the NHS as a
  whole.
• Optimal differs depending on the perspective of
  the individual and/or organisation.
• Optimal is as dependent on the rate of adoption
  as it is the level of adoption-this should not be
  ignored.
• Stakeholder interviews
• The tool should be user-friendly and transparent.
  
• The success of the model will be dependent upon
  the availability of data sources, its ability to
  model uncertainty and flexibility of costs and
  benefits, and regional needs and ideals.
• Workshop
• The TAC should consider the barriers to
  technology adoption to consider the
  achievability of getting from actual to optimal.

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Key stages in using the tool
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What do you need to know?

• For whom is the technology cost-effective?
• Possible data source NICE, DH, Clinicians,
  Suppliers, peer reviewed journals.
• For how many people is the technology
  cost-effective nationally?
• Possible data source NICE, DH, Clinicians,
  Suppliers, peer reviewed journal.
• How many units of technologies are required to
  treat a patient within the selected population?
• Possible data source Clinicians, NICE, DH,
  suppliers

NB The ability to do this effectively will
depend on the availability and reliability of
data on these three questions
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What do you need to know?

• What is the cost of the technology and its
  implementation?
• Possible data sources PASA, Suppliers, Finance
  dept. of hospitals.
• What are the benefits associated with the
  technology?
• Possible data sources NICE, DH, Clinicians,
  Staff, Peer-reviewed journals.
• What are the risks associated with the data?
• Possible data sources Clinicians, Suppliers.
• What are the barriers and facilitators associated
  with the technology?
• Possible data sources Clinicians, Staff,
  relevant stakeholders.

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The main elements of the tool
General information on the tool and product.

• Optimal units

Selecting among competing technologies
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PRODUCT INFORMATION
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Key steps

• Step 1 Input current units of technology adoption

Step 2 Select technology type (drop-down
list) One-to-One technology Clinical
and home environment technologies
Diagnostic and treatment technologies
Step 3 Select relevant population (drop-down
list) One-to-One technology (4
categories) Clinical and home environment
technologies (6 categories) Diagnostic and
treatment technologies (2 categories)
Step 4 Input prevalence and throughput data
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National optimal adoption
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Analysing costs
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Identifying non-financial benefits
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Data reliability
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Achievability
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Output sheet
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Limitations of the model

• Limitation 1 Assessment of optimal requires we
  know for whom the technology is cost-beneficial.
  This data might not exist for a given technology.
  
• The user could substitute cost-benefit data with
  best estimates from clinicians or suppliers.
• Possibility of hurdle criteria

• Limitation 2 Estimated costs and benefits will
  not take into account the change in costs and
  benefits over time the change in costs and
  benefits depending on geographic area or
  organisational size/type.
• These limitations are in part considered within
  the data uncertainty tab.
• The model should be updated when new data becomes
  available.

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Contact details
E Andrew.Beale_at_matrixknowledge.com t 44
(0)20 7684 5777 w www.matrixknowledge.com