Big Data: The Power and Importance of Accurate Surveillance

Professor Alan Johnson Department of HCAI & AMR National Infection Service

Public Health England

Principles of Surveillance

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Data need to be: • Collected (Source) • Stored • Analyzed • Made available • Acted upon Information for action!

Data on Antimicrobial Resistance

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Hospital laboratories routinely: •  Identify bacteria •  Undertake AST Data stored in LIMS

Sources of Microbiology Data

•  LabBase/SGSS (collects routinely-generated laboratory data)

•  MOLIS (Reference Lab Database)

•  Mandatory surveillance programmes (Trust data) •  Bacteraemia due to MRSA, MSSA, E. coli •  C. difficile infection •  Surgical site infection (SSI)

•  GRASP (Gonococcal Resistance to Antimicrobials Surveillance Programme)

•  BSAC Sentinel surveillance (collects isolates) •  Bacteraemia •  Respiratory

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MRSA and E. coli Bacteraemia in England

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MRSA E. coli

Making Use of AMR Data •  Inform national guidance for treatment •  Highlight burden of antibiotic-resistant infections •  Strategic planning

• Need for new antibiotics • Rapid diagnostics • Antibiotic stewardship

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What the Data Doesn’t Tell us

Procedures?

Device related?

Underlying Infections?

Antibiotic Treatment?

Co-morbidities? Nosocomial?

Speciality?

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Clinical outcomes?

Transmission?

Sources of Clinical and Other Data •  Hospital Episode statistics

•  Death registrations (ONS)

•  Renal registry

•  National joint registry

•  Prescribing data

•  Patient Reported Outcome Measures (NHS)

•  Paediatric Intensive Care Audit Network

•  Neonatal Data Analysis Unit (Imperial College)

•  Intensive Care National Audit & Research Centre

•  Clinical Practice Research Datalink

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Data Linkage

•  Linkage of disparate but complementary data sets provides a much more comprehensive picture

•  Requires patient-level record linkage • Deterministic linkage (e.g. NHS number) • Probabilistic linkage (multiple identifiers)

•  Highly robust information governance and secure IT systems essential to ensure patient confidentiality

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LabBase Microbiology surveillance

data Positive blood cultures Patients aged 1m-18y

(N=8,718)

HES Hospital administrative

in-patient data Individual patient records

Patients aged 1m-18y (N=1,834,300)

Example of Data Linkage

Linked PHE & HES data

Study to investigate the incidence, epidemiology and impact (mortality; LoS) of paediatric HA-bacteraemia

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Health Protection Research Units (Funded by NIHR)

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DATA GENOMICS INTERVENTIONS

Antimicrobial use, assessment and impact

Key PHE priority healthcare-associated pathogens and target infections

Exploiting database technologies

Applying WGS to increase insights into resistance transfer

Public and patient involvement

Strain archives

Imperial College University of Oxford

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UK Five Year Antimicrobial Resistance Strategy 2013 to 2018

1.  Improving infection prevention and control practices

2.  Optimising prescribing (through antimicrobial stewardship)

3.  Improving professional education, training and public engagement

4.  Developing new drugs, treatments and diagnostics

5.  Better access to and use of surveillance data

6.  Better identification and prioritization of AMR research needs

7.  Strengthened international Collaboration

UK 5-Year AMR Strategy 7 Key Areas for Future Action

PHE Fingertips Web Portal

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Summary

Surveillance

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•  Surveillance epidemiology •  Disparate data sources •  Link to combine information •  “Big data” gives the “Big Picture”