1. How to reduce hospital admissions due to high risk drugs Dr Martin Duerden m.g.duerden@bangor.ac.uk 1

2. Which drugs? 2

3. Adverse drug reactions as cause of admission to hospital Pirmohamed M et al. BMJ 2004;329:15-19 18,820 patients admitted over six months to a Liverpool Hospital assessed for cause of admission Prevalence 6.5%, with ADR directly leading to the admission in 80% of cases – 4% of hospital capacity Overall fatality was 0.15% (2% of those admitted with ADR) Most reactions predictable – 72% were deemed either definitely or possibly avoidable Drugs most commonly implicated in causing these admissions: aspirin and NSAIDs (30%); diuretics (27%); warfarin (10%); ACEIs/ARBs (8%) The most common ADR was gastrointestinal bleeding 3

4. Other evidence – drugs and preventable admissions Howard R, et al. Systematic review, Br J Pharmacol 2007;63:136-147. 4 drug classes: 1. Antiplatelets 2. Diuretics 3. NSAIDs 4. Anticoagulants 50% of drug related admissions With opioids, beta-blockers, ACEI/ARB, diabetes, digoxin, & corticosteroids =75% of admissions 4

5. Other evidence – drugs and medication errors Saedder EA, et al. Systematic Review. Eur J Clin Pharmacol 2014;70:637-645 47 % of all serious MEs were caused by 7 drugs or drug classes: 1. Methotrexate 2. Warfarin 3. NSAIDs 4. Digoxin 5. Opioids 6. Aspirin 7. Beta-blockers; The top ten drugs involved in fatal events accounted for 73 % of all drugs identified. “Increasing focus on seven drugs/drug classes can potentially reduce hospitalizations, extended hospitalizations, disability, life-threatening conditions, and death by almost 50 %” 5

6. Beware NSAIDs – summary of hazards NSAIDs, including coxibs. associated with: CV adverse outcomes – AMI and stroke GI adverse events – including GI bleeding Renal adverse events – including AKI Risk of CV adverse events is particularly high with coxibs and diclofenac. Low-dose ibuprofen (≤ 1200 mg/day) and naproxen associated with lowest CV risk Concomitant use of an NSAID/coxib with either an SSRI, an anticoagulant, an antiplatelet drug or a corticosteroid increases GI bleeding risk. Concomitant use of an NSAID/coxib with an ACE inhibitor/ARB/ aliskiren and/or diuretic or increases risk of renal impairment or failure 6

7. Age and hospitalisations associated with NSAIDs Seager and Hawkey BMJ 2001; 323: 1236-1239 7

8. Other drugs that are tolerated poorly in frail patients (www.nhsgrampian.com/grampianfoi/files/PolyPh_538_0912.pdf) Antipsychotics, e.g. quetiapine, haloperidol Tricyclic Antidepressants, e.g. amitriptyline Benzodiazipines (particularly long acting, e.g. nitrazepam, diazepam) Phenothiazines, e.g. prochlorperazine (Stemetil®, Buccastem®) Digoxin at a dose of 250mcg + Opiate containing painkillers, e.g. co-dydramol, dihydrocodeine, MST® Anticholinergics and other drugs that increase the anticholinergic burden 8

9. Which patients? 9

10. Which patients are most at risk? Risk of an ADR resulting in hospital admission is particularly high in the following groups: Elderly and/or frail Patients with multimorbidity Patients on many drugs – polypharmacy Patients with acute medical problems (e.g. AKI) Patients with impaired renal function Patients with impaired cognition Patients with poor dexterity, vision, hearing Patients with poor adherence to prescribed medication People who have recently been in hospital 10

11. Number of Chronic Disorders by Age Group Barnett K et al. Lancet 2012; 380: 37-43. 11

12. Potentially serious drug-drug interactions between drugs recommended by clinical guidelines for three index conditions and drugs recommended by each of other 11 other guidelines. Dumbreck et al. BMJ 2015;350:bmj.h949 12

13. 13 Payne et al. Eur J Clin Pharmacol 2014; DOI 10.1007/s00228- 013-1639-9 Prevalence of polypharmacy in a Scottish primary care population.

14. Polypharmacy – identifying high risk A pragmatic approach to identifying higher-risk polypharmacy in practice is to focus on patients at particularly high risk. For example: Those receiving 10 or more regular medicines, or Those receiving 4 to 9 regular medicines together with other unfavourable factors (examples include: a contraindicated drug; where there is potential for drug-drug interaction; or where medicine taking has proved a problem in the past). 14

15. PRACtICe Study – How common are GP prescribing errors over one year? Avery et al, 2012. www.gmc-uk.org/about/research/12996.asp Patients who had received at least one medication (n=1,200): 17.8% (95% CI 15.7%-20%) Patients aged 75 years and older who had received at least one medication (n=129): 38% (95% CI 29.5%- 46.5%) Patients who had received five or more drugs over the data collection period (n=471): 30.1% (95% CI 26.6%- 35%) Patients who had received 10 or more drugs over the data collection period (n=172): 47% (95% CI 39%-54%) 15

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17. So what can you do? 17

18. Defining medicines optimisation NICE, Medicines Optimisation Guideline NG1, March 2015. A person ‑ centred approach to safe and effective medicines use, to ensure people obtain the best possible outcomes from their medicines. Medicines optimisation applies to people who may or may not take their medicines effectively. Shared decision ‑ making is an essential part of evidence ‑ based medicine, seeking to use the best available evidence to guide decisions about the care of the individual patient, taking into account their needs, preferences and values. 18

19. Supporting practices Reviewing systems – repeat prescriptions, drug monitoring protocols, response to hazard/warnings Significant event reviews, audits Identifying and targeting those: on high risk drugs at risk ((polypharmacy, multimorbidity, frail etc.) on inappropriate/unsafe drugs Post discharge and reconciliation reviews Support to care homes Medication reviews – medicines optimisation Case management Supporting Unplanned Admission Enhanced Service (or equivalent) 19

20. Get with the programme Many GP practices are involved with Reducing Unplanned Admission Enhanced Service (or equivalent) Risk stratification – 2% of practice population Case management - personal care plans Reviewing and auditing unplanned admission Identifying patients: Previous unplanned admissions particularly if COPD (8%), HF (5%) 10 or more medicines, particularly if risky medicines Those requesting frequent home visits End of life (where admission best avoided) Use of IT tools, such as: PINCER query tool (unsafety indicators), STOPP/START (inappropriate Rx) SPARRA (Scotland) QAdmissions and IQ Risk Stratification 20

21. Examples of prescribing (un)safety indicators used in the PINCER trial Avery et al. BJGP 2014;64:259-261 1. Patients with a history of peptic ulcer who have been prescribed an NSAID without co-prescription of a PPI 2. Patients with a history of asthma who have been prescribed a beta-blocker. 3. Patients aged ≥75 years who have been prescribed an ACEI/ARB or a loop diuretic long term who have not had a computer- recorded check of their U&E in the previous 15 months. 4. Patients receiving methotrexate for at least 3 months who have not had a recorded FBC or LFT within the previous 3 months. 5. Patients receiving warfarin for at least 3 months who have not had a recorded check of their INR within the previous 12 weeks. 6. Patients receiving amiodarone for at least 6 months who have not had a thyroid function test within the previous 6 months. 21

22. QAdmissions: predictors Hippisley-Cox J and Coupland C. BMJ Open 2013;3:e003482 Age, sex, BMI Ethnicity Deprivation Strategic Health Authority Smoking & alcohol Lab values Abnormal LFTs Anaemia Raised platelets Medication Anticoagulants Antidepressants antipsychotics NSAIDs Steroids Prior admissions Type of Diabetes CVD, AF, CCF Chronic renal disease Venous thrombosis Cancer Asthma/COPD Manic depression or schizophrenia Malabsorption Chronic liver/pancreas disease Falls 22

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24. Measuring your effectiveness 24

25. Pharmacist-led interventions to reduce unplanned admissions for older people: a systematic review and meta-analysis of RCTs Thomas R et al. Age Ageing (2014) 43 (2): 174-187. 27 RCTs were identified; 7 trials were excluded The 20 included trials:16 for older people; 4 for older people with heart failure. Interventions led by hospital pharmacists (7 trials) or community pharmacists (9 trials) did not reduce unplanned admissions in the older population (RR 0.97 95% CI: 0.88, 1.07; 1.07 95% CI: 0.96, 1.20). 3 trials in older people with heart failure showed that hospital pharmacist interventions reduced the RR of admissions. These trials were heterogeneous in intensity and duration of follow-up. One trial had a high risk of bias. 25

26. Measuring your impact Therefore there is insufficient evidence to demonstrate reduced admissions from pharmacist interventions, but… There is evidence that optimising medicines use by pharmacists reduces prescribing errors, and reduces harmful ADRs (e.g. PINCER study). Some evidence that medication review/optimisation improves quality of life (and reduces waste) The likelihood is that doing this where risk is high reduces admissions Important to keep a record of interventions that have improved safety – particularly involving the drugs most closely associated with unplanned admissions 26

27. Conclusions Antiplatelets, diuretics, NSAIDs, anticoagulants (+NOACs?) represent high risk drugs and increase the chances of unplanned admissions due to ADRs Methotrexate (DMARDs), opioids, digoxin, ACEIs/ARBs are also risky Multimorbidity and polypharmacy compound these risks Frail, older people on these drugs will be at even greater risk Primary care pharmacists and technicians can do much to mitigate these risks through focusing on them, improving prescribing systems and safety, and via medication reviews It is highly likely that this work will help reduce unplanned admission Reducing unplanned admissions is a high priority and a ‘hot topic’ in the NHS 27