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

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

3. 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

4. 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

5. 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

6. 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

7. 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%

8. Variation between practices after casemix adjustment

9. 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

10. 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

11. 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)

12. 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

13. 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

14. 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…

15. Where next – multimorbidity & polypharmacy?

16. Tayside

17. 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

18. 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

19. 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?