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Electronic prescribing – an NHS guide
to building the case and implementing
electronic prescribing for improved
patient sa...
NHS | Presentation to [XXXX Company] | [Type Date]2
Safer Hospitals
Why ePrescribing?
Benefits
Challenges
Background
• Equip Study
• 124,260 medication orders across 19 hospitals
• 8.9% error rate
• FY1 8.4%, FY2 10.3%
• Most er...
Source: Garbutt JM, Highstein G, Jeffe DB, Dunagan WC, Fraser VJ. Safe medication prescribing:
training and experience of ...
• 23/25 show ↓risk
reduction
• One study with increased
rate due to disconnection
and transcription errors
• Home-grown sy...
ePrescribing Uptake
• 2011
• 13% NHS trusts use for inpatient prescribing in adult
medical and surgical wards
• 11% adult ...
NHS | Presentation to [XXXX Company] | [Type Date]8
Safer Hospitals
Why ePrescribing?
Benefits
Challenges
Legibility & Completeness
• Reduced risk of misinterpretation
• Reduced time for transcription & re-writing
• Medical and ...
Efficiency gains
▪ Improved communication
▪ between different departments and care settings
▪ Reductions in paperwork-rela...
Medication Error
• Decreased risk of medication errors
▪ more legible and complete prescriptions
▪ guidance for inexperien...
13
The average medicines reconciliation rate pre-implementation was 77%,
the average medicines reconciliation rate post im...
Decision Support for Prescribing
• Passive
• Guidance
• Active
• Alerts
Basic Passive Support
• Description
• Set basic field parameters
• E.g. Numeric/text, required fields
• Effective as seen ...
Structured Orders
• Description
• Templates for orders
• Guide choices with allowable
values, defaults
• Dose support for ...
Newcastle Benefits
• Structured orders
• Standard medicines nomenclature
• Standard doses
• Order sets promoting standardi...
£0
£20
£40
£60
£80
£100
£120
£140
£160
£180
Drug Expenditure per FCE
Source Clinical Benchmarking Company Ltd
Wirral Hospi...
Reduction in Drug Expenditure
• 12.5% or £48,734 over first few months
19
0
10,000
20,000
30,000
40,000
50,000
60,000
2012...
0
5000
10000
15000
20000
25000
30000
35000
40000
£
Time (months)
Drug A
Drug B
Formulary Changes
Active Decision Support Rules
• Description
• Real time prompts at the time of
order entry based on explicit
rules
• Effec...
Password-level warnings ignored
6 month period
1113
22039
3453
51805
1854
23773
12323
54935
0%
20%
40%
60%
80%
100%
Contra...
Detecting Errors
23
• Impact Tool
• List of indicators high severity/high frequency
• Amenable to decision support
• Aller...
Detecting Errors
• Impact tool
• 4000 orders before and after implementation
• Baseline
• Support configuration
• Post imp...
Cost of Medication Errors
• Annual treatment cost of ADE
• 400 bedded hospital
• £599k direct cost; £17.754 with lost heal...
Prescribing Decision Support
• Not all on day one……
• Lots to learn about specificity and tolerances
• Guidance during pre...
Administration support
• Often overlooked yet just as important
• Taxis et al – 50% errors on administration of IVs
• Miss...
Quality Initiatives…..
Non-charted medicines….
0.00
4.00
8.00
12.00
16.00
Percentage
System A
System B
System C
Reductions in Missed Doses - Antibiotics
CarruthersT,Curt...
Non-antibiotics - % Missed
Doses
0%
1%
2%
3%
4%
5%
6%
7%
8%
9%
10%
11%
12%
13%
14%
15%
16%
17%
18%
19%
20%
21%
Jan 08 Mar ...
NHS | Presentation to [XXXX Company] | [Type Date]32
Safer Hospitals
Why ePrescribing?
Benefits
Challenges
Where now with ePrescribing?
• One of, if not, the most complex area to implement
• Culturally challenging
• Realising ben...
Expectations management….
• No system will meet all needs
• Technically challenging
• Different types of prescription
• In...
Possible harms
• New sorts of problems
• Key stroke errors
• Picklist errors
• Sociotechnical issues
• Human-computer inte...
Metzger et al. Mixed Results In The Safety Performance of Computerized Physician Order Entry. Health Affairs 2010 29(4): 6...
Successful implementation
• Requires
• Support for change from leaders and staff
• Development of a gradual and flexible i...
The Implementation Lifecycle
www.eprescribingtoolkit.com
• What are the drivers?
• Clinical or Financial
• Local requirements?
• Helps drive needs assessment
• Create a vision of ...
Preparing for the journey…
• Leadership
• Executive buy-in
• Clinical champion(s)
• Change management
• Resources
• Infras...
• Project team continue evaluation and
improvement over early terms of project
• Pause for System Stabilisation before
Opt...
Average Number of Items Prescribed by
Hour, 1996
0
10
20
30
40
50
60
NoItems
Hour Commencing
Inpatient
TTH
Slee AL, Farrar...
When do things happen in 2011?
ePrescribing Toolkit
www.eprescribingtoolkit.comwww.eprescribingtoolkit.com
Summary
• ePrescribing does deliver benefits
• It is not a panacea
• No single system can deliver everything
• Implementat...
48
Acknowledgement: Dr J Coleman, NIHRePrescribing research team,
Iain Richardson, Neil Watson and others for sharing thei...
S209 - Day 1 - 1200 - Electronic prescribing
S209 - Day 1 - 1200 - Electronic prescribing
S209 - Day 1 - 1200 - Electronic prescribing
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S209 - Day 1 - 1200 - Electronic prescribing

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Health and Care Innovation Expo 2014, Pop-up University

S209 - Day 1 - 1200 - Electronic prescribing

Paul Rice
Ann Slee

#Expo14NHS

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  • Another systematic review by ElskeAmmerwerth from Austria evaluated all types of CPOE systems comparing electronic systems with written prescriptions or more advanced with less advanced systems. Risk ratios varied from 0.01 to 0.87 indicating a 13 to 99% reduction in medication errors. One study showed an increase in error rates of 26% and only included voluntary reports in their paper – in this system there was no connection between the CPOE system and pharmacy so orders were entered twice and there were many more transcription errors in the intervention period.A further inconclusive study only analysed 320 orders.Pre-specified subgroup analyses showed that home grown systems and those with advanced decision support reduced error rates more.
  • Transcript of "S209 - Day 1 - 1200 - Electronic prescribing"

    1. 1. Electronic prescribing – an NHS guide to building the case and implementing electronic prescribing for improved patient safety
    2. 2. NHS | Presentation to [XXXX Company] | [Type Date]2 Safer Hospitals Why ePrescribing? Benefits Challenges
    3. 3. Background • Equip Study • 124,260 medication orders across 19 hospitals • 8.9% error rate • FY1 8.4%, FY2 10.3% • Most errors intercepted before caused harm • Incorrect dosage most common error 3 An in depth investigation into causes of prescribing errors by foundation trainees in relation to their medical education – EQUIP study. GMC, 2009
    4. 4. Source: Garbutt JM, Highstein G, Jeffe DB, Dunagan WC, Fraser VJ. Safe medication prescribing: training and experience of medical students and housestaff at a large teaching hospital. Acad Med. 2005;80:594-599.
    5. 5. • 23/25 show ↓risk reduction • One study with increased rate due to disconnection and transcription errors • Home-grown systems compared better to commercial systems Ref: Ammenwerth et al. J Am Med Inform Assoc. 2008 15(5): 585–600. Relative risk reduction of 13% to 99% Review of the impact of CPOE on medication errors
    6. 6. ePrescribing Uptake • 2011 • 13% NHS trusts use for inpatient prescribing in adult medical and surgical wards • 11% adult critical care • 1% paediatric/neonatal critical care • 3% renal • 34% chemotherapy • 48% discharge prescribing 7 Ahmed Z, McLeod MC, Barber N, Jacklin A, Franklin BD (2013) The Use and Functionality of Electronic Prescribing Systems in English Acute NHS Trusts: A Cross-Sectional Survey. PLoS ONE 8(11): e80378. doi:10.1371/journal.pone.0080378
    7. 7. NHS | Presentation to [XXXX Company] | [Type Date]8 Safer Hospitals Why ePrescribing? Benefits Challenges
    8. 8. Legibility & Completeness • Reduced risk of misinterpretation • Reduced time for transcription & re-writing • Medical and pharmacy • Reduced risk of transcription error • 50% error rate on some TTO audits 10
    9. 9. Efficiency gains ▪ Improved communication ▪ between different departments and care settings ▪ Reductions in paperwork-related problems ▪ e.g. fewer lost prescriptions ▪ Clearer and more complete audit trails
    10. 10. Medication Error • Decreased risk of medication errors ▪ more legible and complete prescriptions ▪ guidance for inexperienced prescribers ▪ alerts for contra-indications, allergic reactions and drug- drug interactions ▪ support for timely and accurate medicines administration
    11. 11. 13 The average medicines reconciliation rate pre-implementation was 77%, the average medicines reconciliation rate post implementation is 90%.
    12. 12. Decision Support for Prescribing • Passive • Guidance • Active • Alerts
    13. 13. Basic Passive Support • Description • Set basic field parameters • E.g. Numeric/text, required fields • Effective as seen as guidance • Effect on safety • Reduce errors due to grossly erroneous information
    14. 14. Structured Orders • Description • Templates for orders • Guide choices with allowable values, defaults • Dose support for paediatrics • Effect on safety • More complete, actionable orders
    15. 15. Newcastle Benefits • Structured orders • Standard medicines nomenclature • Standard doses • Order sets promoting standardisation • Pain control • Antibiotic use • Minimum mandatory data set for prescribing • Complete prescriptions • ….and more… 17
    16. 16. £0 £20 £40 £60 £80 £100 £120 £140 £160 £180 Drug Expenditure per FCE Source Clinical Benchmarking Company Ltd Wirral Hospital
    17. 17. Reduction in Drug Expenditure • 12.5% or £48,734 over first few months 19 0 10,000 20,000 30,000 40,000 50,000 60,000 2012 2013 Royal Cornwall Hospitals
    18. 18. 0 5000 10000 15000 20000 25000 30000 35000 40000 £ Time (months) Drug A Drug B Formulary Changes
    19. 19. Active Decision Support Rules • Description • Real time prompts at the time of order entry based on explicit rules • Effect on safety • Reduced errors of omission or commission
    20. 20. Password-level warnings ignored 6 month period 1113 22039 3453 51805 1854 23773 12323 54935 0% 20% 40% 60% 80% 100% Contraindication Dose Interaction Dose/Freq Presc Admin Carried on Backed off lvlcat 2 Count of msgid qtype catname state Lower (red) histograms show the number of times the user „backed off‟ when presented with a password level warning
    21. 21. Detecting Errors 23 • Impact Tool • List of indicators high severity/high frequency • Amenable to decision support • Allergy • Contra-indications • Dosing • Drug-drug interactions • Frequency • Route
    22. 22. Detecting Errors • Impact tool • 4000 orders before and after implementation • Baseline • Support configuration • Post implementation • Support system optimisation • Identify benefits eprescribingresearch@uhb.nhs.uk Developing consensus on hospital prescribing indicators of potential harms amenable to decision support. Thomas et al. Br J Clin Pharmacol 201324
    23. 23. Cost of Medication Errors • Annual treatment cost of ADE • 400 bedded hospital • £599k direct cost; £17.754 with lost health benefit • Annual cost of ADE in ePrescribing hospital • £415k direct cost : saving of £184k • £10.880 with lost health benefit : saving of £6.874 • Audit Commission 2001 – 5% error rate; +8.5 days • £2.7m saving Karnon et al. Modelling the expected net benefits of interventions to reduce the burden of medication errors. Journal of Health Services Research & Policy;13(2):2008:85-91 25
    24. 24. Prescribing Decision Support • Not all on day one…… • Lots to learn about specificity and tolerances • Guidance during prescribing more effective • Hard stops should be used minimally • Alerts should be last resort 26
    25. 25. Administration support • Often overlooked yet just as important • Taxis et al – 50% errors on administration of IVs • Missed doses upto 20% in some areas • Improved information on medicines due • Increased clarity of orders • More visibility of omitted or missed doses • Opportunity to provide IV preparation support – links to Medusa • Barcode opportunities…. 27
    26. 26. Quality Initiatives…..
    27. 27. Non-charted medicines….
    28. 28. 0.00 4.00 8.00 12.00 16.00 Percentage System A System B System C Reductions in Missed Doses - Antibiotics CarruthersT,CurtisC,MarriottJ,SleeA.Amultisiteanalysisofmisseddosesofantibiotics administeredinhospitalcare.EurJHospPharm2013;20:207-211
    29. 29. Non-antibiotics - % Missed Doses 0% 1% 2% 3% 4% 5% 6% 7% 8% 9% 10% 11% 12% 13% 14% 15% 16% 17% 18% 19% 20% 21% Jan 08 Mar 08 May 08 Jul 08 Sep 08 Nov 08 Jan 09 Mar 09 May 09 Jul 09 Sep 09 Nov 09 Jan 10 Mar 10 May 10 Jul 10 Sep 10 Nov 10 %ofMissedNon-Antibiotics Initial Gradient -0.01 Percentage Points per Week p=0.01 % Missed Doses Parsimonious Model Intervention Period of Data Removed Step Change -0.92 Percentage Points p<0.001 Step Change -0.33 Percentage Points p=0.045
    30. 30. NHS | Presentation to [XXXX Company] | [Type Date]32 Safer Hospitals Why ePrescribing? Benefits Challenges
    31. 31. Where now with ePrescribing? • One of, if not, the most complex area to implement • Culturally challenging • Realising benefits requires change • Involves three key professional groups • All want it for something different • Unrealistic expectations 33
    32. 32. Expectations management…. • No system will meet all needs • Technically challenging • Different types of prescription • Inpatient, discharge, outpatient, A/E, theatres etc • High levels of complexity • Infusions, insulin, warfarin, etc • Speciality specific needs • Paediatrics, anaesthetics, critical care, chemotherapy etc 34
    33. 33. Possible harms • New sorts of problems • Key stroke errors • Picklist errors • Sociotechnical issues • Human-computer interactions • Alert fatigue • „Workarounds‟ Unanticipated or unintended consequences of IT “To Err is System”. Aarts and Gorman. Int J Med Informatics 2007;76: S1
    34. 34. Metzger et al. Mixed Results In The Safety Performance of Computerized Physician Order Entry. Health Affairs 2010 29(4): 655-663 Not all implementations are equal… HospitalScoresfordetectionoftestorderscausing anADRaccordingtoproduct
    35. 35. Successful implementation • Requires • Support for change from leaders and staff • Development of a gradual and flexible implementation approach • Adequate resources • Equipment, staff, infrastructure • Acceptance that setbacks will occur and will need managing 38 Spetz et al. What determines successful implementation of inpatient IT systems? Am J Manag Care. 2012;18(3):157-162
    36. 36. The Implementation Lifecycle www.eprescribingtoolkit.com
    37. 37. • What are the drivers? • Clinical or Financial • Local requirements? • Helps drive needs assessment • Create a vision of a HEPMA-based hospital environment • Allows a focus • Establish short and longer term goals Conceptualisation
    38. 38. Preparing for the journey… • Leadership • Executive buy-in • Clinical champion(s) • Change management • Resources • Infrastructure • People • Training • Rollout plan
    39. 39. • Project team continue evaluation and improvement over early terms of project • Pause for System Stabilisation before Optimisation • A driver for medicines optimisation • Ensuring best use through expert users and ongoing training • Increased and „tweaked‟ clinical decision support • Studying and remedying unintended consequences System Optimisation
    40. 40. Average Number of Items Prescribed by Hour, 1996 0 10 20 30 40 50 60 NoItems Hour Commencing Inpatient TTH Slee AL, Farrar KT. Pharm J 1998;260:923-925
    41. 41. When do things happen in 2011?
    42. 42. ePrescribing Toolkit www.eprescribingtoolkit.comwww.eprescribingtoolkit.com
    43. 43. Summary • ePrescribing does deliver benefits • It is not a panacea • No single system can deliver everything • Implementation is challenging but NOT impossible • We know what should be done • It is a journey….
    44. 44. 48 Acknowledgement: Dr J Coleman, NIHRePrescribing research team, Iain Richardson, Neil Watson and others for sharing their work
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