Improving prescribing safety using electronic data Quality, Safety and Informatics Research Group Bruce Guthrie

Outline Why does prescribing safety matter Informatics to improve prescribing safety DQIP trial EFIPPS trial Summary

Why prescribing safety? Some safety events are black and white Never cut the wrong leg off But never events are also rare Most harm is caused by drugs that are indicated Most prescribing is more ambiguous Prescribers and patients are balancing benefit, risk and cost in uncertain circumstances Can define ‘high-risk’ prescription indicators High-risk ≠ inappropriate or wrong

Prescribing is risky 6.5% of hospital admissions are related to ADEs ADE directly leading to admission in 80% Half such admissions are judged preventable Mostly due to ‘appropriate’ drugs that guidelines tell us to prescribe more of Warfarin Aspirin (Non steroidal anti-inflammatory drugs) ACEI/ARB and other renal toxic drugs Hypoglycaemic drugs Blood pressure lowering drugs

Is high-risk prescribing common? Data from 310 Scottish practices 1.75 million patients of whom 139,000 particularly vulnerable to ADEs 15 measures of high-risk prescribing Examines variation by patient and practice characteristics http://www.bmj.com/content/342/bmj.d3514.full

Indicators examined Non-steroidal anti-inflammatory drugs (4 indicators) Peptic ulcer or age>75 without gastro-protection Age>65 with eGFR<60 or co-prescribed diuretic & ACEI/ARB Warfarin co-prescription (4) NSAIDs, antiplatelets, high risk antibiotics, azole antifungals Drugs to avoid in heart failure (4) NSAIDs, tricyclics, glitazones, verapamil and others Methotrexate dosing/dose instructions (2) Mixed dose tablets, ‘not weekly’ instructions Antipsychotics in people with dementia (1) Risperidone and olanzapine

Variables associated with outcome No. of chronically prescribed drugs   % of patients receiving any high-risk prescription None (n=19082) 1-2 (n=21709) 3-4 (n=30460) 5-6 (n=30345) 7-8 (n=20445) 9-10 (n=10372) ≥11 (n=6991) 4% 11% 13% 14% 18% 22% 27%

Variation between practices after casemix adjustment

How to improve it? Decision support at the point of prescribing All GP IT systems have drug-drug, drug-age/sex, and drug-disease alerts Variably implemented and probably variably effective Only trigger for ‘new’ prescriptions Supported identification and review Not available in existing GP systems DQIP and EFIPPs are examples

What is DQIP? Data-driven Quality Improvement in Primary Care CSO funded cluster randomised trial of an intervention to improve prescribing safety in general practice Completed recruitment of 40 practices in Tayside and Fife (50% of those eligible), trial started in November 2011 Targets high-risk NSAID & antiplatelet prescribing

What’s the intervention? Educational intervention Practice visit Written and online material Web-based tool Identify patients with high-risk prescribing Support review Show change over time Financial payment (modelled on enhanced service) £350 at start of study £15 per patient reviewed (expect an average of 20 patients/1000 patients needing review over 1 year)

What is EFIPPS? Effective Feedback to Improve Primary care Prescribing Safety CSO funded Will run in 240 Scottish practices in 3 Boards 3 monthly feedback of 6 indicators Simpler and therefore cheaper intervention Development phase Aug 2011 – Apr 2012 Trial starts Jul 2012 Uses existing NHS Scotland prescribing data

newPIS data Uses newPIS patient level prescribing dataset Not perfect Held by NHS Scotland Information Services Division Currently ~94% complete CHI (and will backfill to early 2009) Not perfect Good enough for high level use Good enough for feedback of patterns and trends Support GPs to identify patients in their own data

Where next? DQIP and EFIPPS focus on a small set of focused indicators Polypharmacy is strongly associated with high risk prescribing, but can’t be reduced to focused indicators Polypharmacy is growing…

Where next – multimorbidity & polypharmacy?

Tayside 1995-2010

GP-POLY? Highland polypharmacy LES Feasible, pragmatic, plausible 98% practice uptake ~4000 reviews, 25% get drugs stopped (the frailest patients), average of 2.5 drugs stopped Education and guidelines Uses ESCRO to run payment and monitoring £60 per review (!) Feasible, pragmatic, plausible Needs a trial – HTA Rapid Clinical Trials call

Summary Complex/expensive vs simpler/cheaper interventions Will they work? We’re in a state of equipoise… Electronic datasets create new opportunities Different datasets serve different purposes GP data is highly ‘owned’ and timely but fragmented Existing centrally held routine data is incomplete and old Ideally would have GP data held by Boards or NHS Scotland and available for linkage Data governance issues >> technical ones

Thank you! Any questions? Acknowledgements Chief Scientist Office for funding both studies DQIP – Aileen Grant, Tobias Dreischulte, Colin McCowan, Peter Davey, Peter Donnan (Dundee), and NHS Tayside, NHS Fife and participating practices EFIPPS team – Karen Barnett, Shaun Treweek, Dennis Petrie (Dundee), Marion Bennie (ISD and Strathclyde), Chris Robertson (Strathclyde), Lewis Ritchie (Aberdeen) and participating Health Boards (Lothian, Lanarkshire, Ayrshire & Arran) Thank you! Any questions?