The Many Approaches to Digital Health and why

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The Many Approaches to Digital Health and why we need to work together Professor

The Many Approaches to Digital Health and why we need to work together Professor Anne Graham ADRKT Faculty of Life Sciences 1 16 January 2022 DHEZ Seminar FLS Digital Health

Digital tools for citizen empowerment for person centred care EC e. Health Strategy Healthcare

Digital tools for citizen empowerment for person centred care EC e. Health Strategy Healthcare practices supported by electronic processes and communication EU What is DIGITAL HEALTH? Umbrella term including e. Health, advanced computing sciences in big data, genomics and artificial intelligence 2019 Report WHO https: //www. who. int/publications-detail/who-guidelinerecommendations-on-digital-interventions-for-health-systemstrengthening 2 16 January 2022 DHEZ Seminar FLS Digital Health

Research in Life Sciences 3 16 January 2022 DHEZ Seminar FLS Digital Health

Research in Life Sciences 3 16 January 2022 DHEZ Seminar FLS Digital Health

Bioinformatics • the science of developing computer databases and algorithms for the purpose of

Bioinformatics • the science of developing computer databases and algorithms for the purpose of speeding up and enhancing biological research. What. Is. com Human Genome Project • The sum of the computational approaches to analyze, manage, and store biological data. Bioinformatics involves the analysis of biological information using computers and statistical techniques, the science of developing and utilizing computer databases and algorithms to accelerate and enhance biological research. -used in analyzing genomes, proteomes (protein sequences), three-dimensional modeling of biomolecules and biologic systems, Medicine. Net • the collection, classification, storage, and analysis of biochemical and biological information using computers especially as applied to molecular genetics and genomics Merriam-Webster 4 16 January 2022 POWERPOINT PRESENTATION TEMPLATE BLUE

Bioinformatics/Biostatistics & Translational Research Machine learning (ML) & biomedical data • for identification of

Bioinformatics/Biostatistics & Translational Research Machine learning (ML) & biomedical data • for identification of omics/clinical parameters associated with response to treatment • ‘melanoma project’ - W Alshaly (Ph. D student) • collaboration with NIHR Leeds Biomedical Research Centre around psoriasis/lupus/eczema • Developed software for Epigenome-Wide-Association Studies analysis – K Murat (MPhil, PT Ph. D student) https: //galaxyproject. org/use/ewas-galaxy/ • case study investigating DNA methylation population profiles for patients showing resistance to BRAF and MEK inhibitor therapies • our software is integrated into https: //usegalaxy. eu/ together with human multi-omics data from UK Personal Genome Project • Interested in integration of genome sequencing and longitudinal EHRs/clinical parameters (Elixir UK 18 Universities – Human Data Group) 5 16 January 2022 DHEZ Seminar FLS Digital Health Krzysztof Poterlowicz Senior Lecturer Bioinformatics & Biostatistics k. poterlowicz@bradford. ac. uk

Bioinformatics/Biostatistics & Translational Research Elixir human Copy Number Variant (h. CNV) implementation study grant

Bioinformatics/Biostatistics & Translational Research Elixir human Copy Number Variant (h. CNV) implementation study grant (2019 -2021) UK PI, GOALS: • To establish and define data exchange formats • To create a process to facilitate the identification of patients with similar genotypes and phenotypes • To define optimal CNV detection pipelines • Funds to organize two hackathons in Bradford 6 16 January 2022 DHEZ Seminar FLS Digital Health Krzysztof Poterlowicz Senior Lecturer Bioinformatics & Biostatistics

Geocoded mobile phone data in infectious disease outbreaks Conor Meehan, School of Chemistry and

Geocoded mobile phone data in infectious disease outbreaks Conor Meehan, School of Chemistry and Biosciences c. meehan 2@Bradford. ac. uk; @con_meehan ACKNOWLEDGEMENTS Mycobacteriology unit, ITM, Belgium Bernard Nocht Institute, Germany Bradford Royal Infirmary Bouke de Jong Florian Gehre Sulman Hasnie Jackie Todd MRC Unit as LSHTM, The Gambia PHE Cian O’Siochain Badou Gaye Anna Roca Martin Antonio Field team 7 16 January 2022 David Wyllie Esther Robinson Suzanne Coles Grace Smith Miles Denton DHEZ Seminar FLS Digital Health

Digital Epidemiology • Epidemiology is undertaken in 2 primary ways: Ø Classic -Patient interviews

Digital Epidemiology • Epidemiology is undertaken in 2 primary ways: Ø Classic -Patient interviews and follow up Ø Molecular -Genomic data and clustering • Digital epidemiology Ø Incorporating digital data into epidemiology Ø Generally data collected outside of a Public Health remit • Data collection Ø Social media Ø Google searches Ø GPS data 8 16 January 2022 DHEZ Seminar FLS Digital Health

Tracking TB transmission in The Gambia • 10 million deaths per year • Transmitted

Tracking TB transmission in The Gambia • 10 million deaths per year • Transmitted by aerosols (long latency/ close contact) • Important in drug resistance Research Questions: • Where do TB patients cross in space and time? • Use the CDRs of patients to see where they overlap • Target intervention to these potential hotspots • Relatively fast and cheap • CDRs means dealing with phone companies 9 16 January 2022 DHEZ Seminar FLS Digital Health

Ap pl ica tio ns in Br ad fo rd Tracking TB transmission in

Ap pl ica tio ns in Br ad fo rd Tracking TB transmission in The Gambia • Enhanced case finding – Ran 2012 -2014 • Greater Banjul Area (600, 000 people) • Cluster-randomized trial – Intervention arm: Enhanced-Case-Finding – Control arm: Passive-Case-Finding – Includes measurement of GPS coordinates • Outcome measures: – Case-detection rate (Global Fund study) – Reduction in transmission (ERC) 10 16 January 2022 DHEZ Seminar FLS Digital Health

Geospatial data for infectious diseases • A brand new and growing field • Potential

Geospatial data for infectious diseases • A brand new and growing field • Potential to gather large datasets passively • Need to be aware of the inherent biases (e. g. socioeconomical) and ethical problems • Applications are wide ranging o Endemic diseases (communicable and non-communicable) o Outbreaks o Seasonal behaviours o Predicting risk factors 11 16 January 2022 DHEZ Seminar FLS Digital Health

Healthy eye 3 -D En face OCT reconstructions of the retinal nerve fibre layer

Healthy eye 3 -D En face OCT reconstructions of the retinal nerve fibre layer in the eye Eye with glaucoma Loss of nerve fibres visible as white striations in the healthy eye, indicative of early glaucoma Working on developing this technique for use in glaucoma diagnosis Contact: Dr Jonathan Denniss -automated analysis, image processing j. denniss@bradford. ac. uk -? deep learning 12 16 January 2022 DHEZ Seminar FLS Digital Health

Diabetes: Big Data Opportunities A. graham@bradford. ac. uk Continuous blood glucose monitoring – Abbott

Diabetes: Big Data Opportunities A. graham@bradford. ac. uk Continuous blood glucose monitoring – Abbott Libreview - Dexcom Records carbohydrate: insulin and effects on blood glucose Ø Predicts Hb. A 1 c levels Based on data collected from patients improved advice to patients: Ø administer insulin 15 minutes before eating (previous advice = 5 min beforehand) 13 16 January 2022 DHEZ Seminar FLS Digital Health

Patient Self Management Support Systems • Health Opportunities for Patient Empowerment in Gestational Diabetes

Patient Self Management Support Systems • Health Opportunities for Patient Empowerment in Gestational Diabetes (HOPE-GDM) • Intensive clinical intervention in GDM women improved maternal & foetal outcomes Fatema Ashraf, Surawahardy Medical College, Dhaka Bangladesh Ø Patient diaries to monitor blood glucose, carbohydrate intake, activity Ø Clinician training required to enable interpretation (patient self empowerment) Ø Opportunities for digitisation • Ph. D student project based in UK with Bangladesh visits 14 16 January 2022 DHEZ Seminar FLS Digital Health

Patient Self Management Support Systems: Clinician Benefits • Ability to for patient to share

Patient Self Management Support Systems: Clinician Benefits • Ability to for patient to share digital data with clinical team • Speeds up clinical responses • Decision support systems being digitised (with no compromise of care) 15 16 January 2022 DHEZ Seminar FLS Digital Health

BRea. THe project Building Resilience, Well-being and Cohesion In Displaced Societies Using Digital Heritage

BRea. THe project Building Resilience, Well-being and Cohesion In Displaced Societies Using Digital Heritage brad. ac. uk/breathe/ AHRC (GCRF) funded research Adrian Evans (PI) Karina Croucher Owen Green Andrew Wilson 16 16 January 2022 DHEZ Seminar FLS Digital Health

“We aren’t able to see Syria with our own eyes, but through VR, you

“We aren’t able to see Syria with our own eyes, but through VR, you brought Syria to us. ” – A refugee in Azraq Camp BRea. THe project Building Resilience, Well-being and Cohesion In Displaced Societies Using Digital Heritage brad. ac. uk/breathe/ 17 16 January 2022 DHEZ Seminar FLS Digital Health

“We considered Azraq Refugee camp as a prison and living in the fenced area

“We considered Azraq Refugee camp as a prison and living in the fenced area of Village 5 is like living in a prison inside a prison. We can’t go outside to see the world, but through the VR, you brought the world to us. ” – A 16 year old refugee. BRea. THe project Building Resilience, Well-being and Cohesion In Displaced Societies Using Digital Heritage 18 16 January 2022 DHEZ Seminar FLS Digital Health

“The moment I started seeing pictures from back home I instantly started smelling the

“The moment I started seeing pictures from back home I instantly started smelling the jasmine tree I had in my house back in Syria. ” – A 40 year old refugee BRea. THe project Building Resilience, Well-being and Cohesion In Displaced Societies Using Digital Heritage 19 16 January 2022 DHEZ Seminar FLS Digital Health

Opportunities from Wealth of NHS Data Acknowledgment: Janet Lord; University of Birmingham (unpublished data)

Opportunities from Wealth of NHS Data Acknowledgment: Janet Lord; University of Birmingham (unpublished data) Ageing and Multi-morbidity Queen Elizabeth Hospital Birmingham. Electronic admissions. • Analysed all admissions for July 2016 to 1 st Jan 2017 • 14767 emergency admissions of adults aged over 50 • Median age 73 (range 50 – 116 years) • Median length of stay (LOS) 11 days (range 1 – 223 days) No single presenting disease associated with highest number of admissions (breathlessness, falls, delirium) § Median number of co-morbidities person = 6 (range 0 - 13) § 83% had > 3 co-morbidities; > 70% had 4 co-morbidities Length of stay was related to age but a stronger association was seen with multi-morbidity (how badly you age!) 20 16 January 2022 DHEZ Seminar FLS Digital Health

Pre-existing Statin use reduces mortality risk in Pneumonia patients Janet Lord: Birmingham p<0. 005

Pre-existing Statin use reduces mortality risk in Pneumonia patients Janet Lord: Birmingham p<0. 005 Grudzinska F et al (2017) Clin Med 21 16 January 2022 DHEZ Seminar FLS Digital Health

Working Together for Success Ø Academics and clinicians Ø Bioinformaticians and fundamental scientists -

Working Together for Success Ø Academics and clinicians Ø Bioinformaticians and fundamental scientists - design of research; maximising output from data analysis Ø Fundamental scientists and computing experts - artificial intelligence and machine learning Ø Digital Heritage Scientists and Social Scientists 22 16 January 2022 DHEZ Seminar FLS Digital Health