Providing actionable healthcare analytics at scale: Insights from the National

Hip Fracture Database

Christopher Boulton, Falls and Fragility Fracture Audit Programme Manager, Royal

College of Physicians

Rob Wakeman, Clinical Lead for Orthopaedic Surgery, National Hip Fracture

Database

Chair: Sarah Deeny, Assistant Director of Data Analytics, The Health Foundation

Background

• NHFD conceived 2004. Data collection 2007.

• Joint initiative of BOA and BGS

• Managed by RCP since 2012

• Commissioned by HQIP

• Part of the Falls and Fragility Fracture Audit Programme

• 450,000 records, 100% participation

Traditional reporting

• Annual written report

• Comparative data

• Written for clinicians

• Assurance focussed

Audiences for audit data

People who deliver care

• Real time

• Longitudinal

• Public domain

• Improvement

focussed

People who receive care • Developed with

patients • Focussed on what

good looks like • Empowers patients to

ask questions of caregivers

• Data light

People who commission care

• Key indicators of care quality

• Population and provider level data

• Some focus on pathway outcome

People who regulate care

• Quality and safety indicators for inspection packs

• Assurance focussed

• Supported by clinical context notes

People who improve care

• All of the above

• Audit data can support data driven QI

• PDSA/Model for Improvement/Six Sigma/SPC

• Run charts allow real time monitoring

Time series charts in monitoring safety

Patient safety The proportion of hip fractures that occur while patients are in NHS care The proportion that develop pressure ulcers The proportion that have a second operation

Time series charts in monitoring safety

Peterborough Hospital Moved to a new site with a high proportion of single rooms A project to reduce in-hospital falls saw a reduction of in-hospital fractures from 7.5% to 2.5%, compared with a national figure of 4%

Time series charts in monitoring compliance with national guidelines

Basildon Hospital Provision of Total Hip Replacements for hip fracture patients Has seen an increase in ‘eligible’ patients, rising from an annual rate of 10.9% to 54.3% This has been achieved without a specific QI project

Time series charts in quality improvement

Brighton has a well developed academic anaesthetic department and is at the forefront of implementing high quality care Interventions that are cheap to implement and which have a significant ‘clinician’ preference can be rapidly adopted as part of a QI project Continuous data collection makes completing the PDSA easier

Time series charts in quality improvement

Best Practice Tariff NHS England 2010 Individual patient

assessment: Falls Risk Bone Health Cognitive Function Perioperative assessment by

a Specialist Orthogeriatrician Surgery within 36 hrs of

presentation Hospital is paid £1335 more than they would if any factor is missing.

Steady rise in medical assessments with continuing improvement in ‘tick box factors’ as medical assessment improves. No change in surgery.

Time series charts in quality improvement

Best Practice Tariff doesn’t apply in Wales and very few patients get the same degree of medical assessment and early surgery as England although the rates are improving

Time series charts in Quality Improvement

• Focussed meetings to draw up local guidelines for #NOF patients.

• Extra Sunday trauma list established and staffed with senior anaesthetists.

• #NOF / BPT achievement as a rolling agenda item for monthly consultant meetings.

Time series charts and funnel plots tracking mortality

Quality Assurance Funnel plots allow for a fairer comparison of units that are of different sizes, but are controversial in their interpretation of ‘Alert’ and ‘Alarm’ Casemixing relies on accurate data entry, particularly of pre-injury mobility and physical status Annual 8 months after last data entry

Time series charts and funnel plots tracking mortality

Time series give a hospital the opportunity of investigating changes in crude mortality as they happen, allowing for Quality Assurance and a real time assessment of the Clinical significance of a Statistical variation

Conclusions

• Data are powerful, but need to suit purpose

• Traditional audit reporting cycles are slow, unwieldy and assurance focussed

• Real time longitudinal data better suited for QI

• SPC charts may be useful where early detection is important, or where over-interpretation of chance fluctuations is a problem.