30 Sep 2021

AI Supported Regulation in Health and Care

Case Study: Methods Analytics discuss the Care Quality Commission and the challenge to make this a data-driven organisation as part of techUK's Data Analytics week #DataWeek

OUR CLIENT

The Care Quality Commission (CQC) is the independent health and social care regulator for England.

It makes sure health and social care services are providing people with safe, effective, compassionate, high-quality care. It employs over 3,000 people

THE CHALLENGE WE FACED

CQC aspired to become a more data-driven organisation. In particular, they wanted their inspection resources to be more effective.

After completing a successful Discovery project for them, we were asked to provide a Proof of Concept (PoC) for machine learning fed by their regular monitoring data. We were to explore and support the case for investing in a full system. The system needed to help sift, present and link information to support decision making. Providing the following benefits:

  1. INCREASED EFFICIENCY in assessing incoming information
  2. ASSESSABLE DATA at the point of decision
  3. LEVERAGE the tacit knowledge of inspectors
  4. INCREASING CONSISTENCY between decisions

Author:

Methods Analytics

 

Katherine Holden

Katherine Holden

Associate Director, Data Analytics, AI and Digital ID, techUK

Katherine joined techUK in May 2018 and currently leads the Data Analytics, AI and Digital ID programme. 

Prior to techUK, Katherine worked as a Policy Advisor at the Government Digital Service (GDS) supporting the digital transformation of UK Government.

Whilst working at the Association of Medical Research Charities (AMRC) Katherine led AMRC’s policy work on patient data, consent and opt-out.    

Katherine has a BSc degree in Biology from the University of Nottingham.

Email:
[email protected]
Phone:
020 7331 2019

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