DNA strand

Contact

Mr Erik Mayer
e.mayer@imperial.ac.uk

What we do

As part of a multi-disciplinary team, we realise the value of curated and linked healthcare data to develop, apply and evaluate both digital and non-digital interventions to improve the effectiveness, safety, and patient experiences of care. Through data fusion we combine relevant information of different varieties (structured and unstructured) and multiple sources to provide a more accurate description of the interactions patients have with the healthcare system. Our Health Services Research applies big data analytics principles and techniques to better understand quality in healthcare using a mixed methods approach focusing on the intersection of healthcare policy and practice. We aim to apply robust evaluation to interventions and changes that enable the translation of an evidence-base to the real-world healthcare setting.

Why it is important

Healthcare providers collect a wealth of data concerning the delivery of patient care in multiple Electronic Patient Records systems, covering the full patient pathway, and other systems that capture safety and experience insights and complaints from patients and carers (Consumer informatics). In the increasingly digitally enabled and digitally mature NHS, the problem is no longer a lack of data, but making sense of the huge volumes of information to allow both healthcare professionals to access the right data, at the right time, in the correct context; and for organisations to be able to take these data from silos and use them in supporting clinical services and understanding healthcare utilisation.

Our work uses translational data analytics for organisational knowledge, supporting clinical services and direct patient care.

How it can benefit patients

The appropriate application of data analytic techniques (Natural Language Processing/Machine Learning/Artificial Intelligence) against curated and linked datasets provides new knowledge to improve the quality, safety and patient experiences of care and care delivery. Real-time data-driven insights, in addition, provides opportunities to feed this information back into clinical systems for direct patient benefit.

Summary of current research

Additional information

PhD students

Current

Asem Abdulaziz Asem Abdulaziz - Data Science for Cancer Pathway Analysis

 

 

Baoru HuangBaoru Huang - Development of surgical navigational and visualisation tools to enable surgeons to intuitively use a “tethered laparoscopic molecular probe” and optical biopsy device for accurate identification of prostate cancer and image-guided surgery

 

Daniela RodriguesDaniela Rodrigues - Evaluation of digital-first models of care using routinely collected data

 

 

Jackie Van Dael - Improving the analysis and use of patient complaints for quality monitoring in the English National Health Service (NHS)

Katelyn

Katelyn Smalley - Patient Academy: Empowering Patients to Self-Manage

 

 

Lisa Freise - Engaging patients in their care through electronic record access

Marcos Faquer Manhaes

Marcos Manhaes - Improving safety culture through digital enabled networks: a novel patient safety strategy

 

 

MustafaMustafa Khanbhai - Exploring the opportunities and challenges of measuring patient experience data in real-time using digital technology

 

 

Sneha Jha - Application of Machine Learning to defining problems and diagnosis from the interoperable electronic patient record

Completed
  • Archie Hughes Hallett - The Development of an Image Enhanced Operating Environment in Robotic Partial Nephrectomy
  • Bushra Siddiqi - The Application of Process Mining to Care Pathway Analysis in the NHS
  • James Dilley - Evaluating the opportunities for image guidance as a surgical decision-support technology to improve
  • Jochem Caris - The role of the patient in evaluating Quality of Care
  • Kelsey Flott - Improving the usefulness and use of patient experience feedback
  • Mafalda Camara - Patient-Specific Simulation Environment for Surgical Planning and Preoperative Rehearsal
  • Sabine Vuik - The application of data-driven population segmentation to design patient-centred integrated care

Our researchers

Abdulrahim Mulla

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Abdulrahim Mulla
Deputy Data Warehouse Manager - Research

Algirdas (Anthony) Galdikas

Algirdas (Anthony) Galdikas

Algirdas (Anthony) Galdikas
Senior SQL Developer

Ben Glampson

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Ben Glampson
Research Informatics Programme Manager, NIHR HIC Imperial Programme Manager, Health Informatician

Dimitri Papadimitriou

Dimitri Papadimitriou

Dimitri Papadimitriou
Deputy Research Informatics Programme Manager

Lan Wang

Lan Wang

Lan Wang
Research Assistant (Clinical Analytics & Data Science)

Luca Mercuri

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Luca Mercuri
Deputy Data Warehouse Manager Research

Rohini Subramaniam

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Rohini Subramaniam
Research Assistant (Clinical Analytics & Data Science)

Sridhar Reddy

Sridhar Reddy

Sridhar Reddy
Senior SQL Developer