Adverse drug reactions in older people and their prevention: the - PowerPoint PPT Presentation

Adverse drug reactions in older people and their prevention: the need for a new approach Mir irko Petr trovic Department of Geriatrics Ghent University

CONFLICT OF IN INTEREST DIS ISCLOSURE I have no potential conflict of interest to disclose

Drug related problems (DRPs) and adverse drug reactions (ADR) represent a major burden on health care • So Some mers A. et t al al., Nutr Health Aging 2003: Hospital admission related to ADRs in older inpatients  20% % of of adm admissio ions due due to o ADR ADRs (12 (12% % do domi minantly ly; ; 8% % par partly ly); • Pirmohammed M. M. et al., BMJ 2004: 18820 adult admissions (all ages)  6.5% % of of admi admissio ions due due to o ADR ADRs;  projected annual cost £466M ( € 706M) in UK  median LOS 8 days i.e. 4% % of of al all NHS NHS bed bed da days • Le Leendertse A. et t al al. Arch Intern Med 2008: Hospital Admissions Related to Medication (HARM) study  5.6% .6% of of un unpl planned adm admissions (n=13000; all ages) due to adverse medication; 46.5% were preventable  Aver erage cos ost t of of € 6000 6000 for one preventable medication-related hospitalization (adults all ages) • Ham Hamil ilton H. H. et al. Arch Intern Med 2011: ADE prevalence in 600 consecutive acute admissions of older patients  26.3% % of of pa patie tients had had no non-triv ivia ial l ADE ADEs at t admi admissio ion  2/3 ADEs causal/contributory to admission (69% avoidable)

Hospitali lization an and ADR pre revalence • Alh lhawassi T. T. et al., Clin Interv Aging 2014 : systematic review of prevalence and risk factors for ADRs in older people in the acute care setting  median 11.5 .5% pre revalence in in hosp ospital;  ADR factors: fem emale gender, multi-morb rbidity, poly olypharmacy

Hospitali lization an and ADR in inci cidence • O’Connor et al. , Age & Ageing 2011: prospective study of ADRs in 511 consecutive patients aged > 65 hospitalized with acute illness in one large teaching hospital in Ireland  26% in incid cidence of non-trivial ADRs • La Lattanzio et t al. l., J Am Med Dir Assoc 2012: prospective observational study in 11 Italian medical centres  11.5 .5% in incid ciden ence e of ADRs • SENATOR stu tudy (unpublished, 2016): prospective analysis of ADRs during acute illness hospitalization in 650 consecutive patients aged over 65 yrs in 6 European centres  21.6 .6% in incid cidence of non-trivial ADRs

Rationale • Who is most at risk of suffering an ADR? • What makes them have a higher risk of an ADR? • Can we predict who these people are? • Can risk prediction models id identify fy patients at risk of suffering an ADR?

Background • Accurate risk prediction models are the result of four key stages: development, vali lidation, im impact, and im implementation. • Often only the first two stages are completed, the methods and outcomes of which are often poorly reported. • To be of practical use, these models should – use cle clearly defi fined easil ily obtainable data, – have good predictive power, – be tested in in a la large sample representative of the target population, and – have hig igh relia liability and face ce vali lidity.

Inclusion criteria • Majority of patients ≥65 years old • Included patients who experienced an adverse drug event (ADE) or ADR but excluded prescription errors • A multivariable approach in design and analysis was followed • The model had been validated St Stevenson J et t al al. Clin Interv Aging 2014; 9: 1581-1593

Quality assessment • All studies were reviewed using a standard approach for developing and testing clinical prediction models to satisfy a range of criteria representing four stages: – development (identification of candidate predictor variables and model design); – validation (testing the performance of the model); – impact (measurement of usefulness in the clinical setting); and – implementation (widespread acceptance and adoption in clinical practice).

Quality assessment • Can andidate predic ictor var ariab iables were grouped into th three categories to allow for comparison between studies: dem emographic factors; med edical factors and med edication factors. • Even ent rate was calculated as per erce centage ADR/ R/ADE rate where it was not reported by the authors in this form. • Qual ality of of desi esign and reporting of the studies was compared based on ability to comply with the standard criteria derived from the published literature. • The over erall per erformance of the models was determined by review of their ac accu curacy, dis iscr crimination, an and cali alibration th through in inter ernal or or extern rnal vali alidation.

Included studies: McElnay J et al., 1997 Study y de desig sign Var ariable le Score OR (95 95% CI) Valid alidatio ion Cou ountr try: y: UK Anti tidepressants ts No No sco score 5. 5.79 79 (2. 2.12-5.85) Sensit itiv ivit ity= y=40.5% Settin ing: Ho Hospit ital inpa npatie ient Digoxin in 1.99 1. 99 (1. 1.05-2.33) Spe pecif ific icit ity= y=69.0% Out utcome: inpa npati tient t ADE DE GI pr GI proble lems 2.57 2. 57 (1. 1.35-4.91) Di Discrim imin inatio tion= no not t bnormal K + leve Inc nclu lusio ion: >65 65 ye year ars, no non-ele lectiv ive Abn vel 4.21 4. 21 (2. 2.18-8.14) me meas asured admis issio ion, consent Thi hinks dr drug ug respon onsib ible le 0.17 0. 17 (0. 0.07-0.42) Meth thod: Phas Phase 1 1 var variable le Ang ngin ina 2.40 2. 40 (1. 1.06-5.44) ide dentif ific icatio ion and nd mo model l COPD Sig. p=0 p=0.15 de desig ign (n= n= 92 929) 9), Pha Phase 2 2 Internal valid validatio ion (n=2 n=204). ). Char art t revie view, computeris ised ho hospital l records, structu tured pa patie tient interv terview wi within in 72 72 ho hours of adm dmis issio ion Assessment t of ADE/ADR: Modifi ified Naranjo Nar

Included studies: Tangiisuran B et al., 2014 Study dy desi sign gn Va Variab able Score OR (95% 5% CI) Va Validat ation on Coun untry: : UK UK Hyper erlipi pidaem aemia 1 3.32 32 (1.81 81-6. 6.07) 7) Sens nsitivity=80 80.0% 0% Setting ng: : Hospi pital al inpat atient nt No. of medi No dication ons s >8 1 3.30 30 (1.93 93-5. 5.65) 5) Spec ecificity=55. 5.0% 0% Outcom ome: : inpa patient ent ADR Length Le h of stay >12 days 1 2.27 27 (1.35 35-3. 3.83) 3) Disc scrimina nation on (AUCRO ROC)= Inclusi sion on: : (Pha hase e 1)>65 65 years, s, not Hypog oglycae aemic age gent nts 1 1.91 91 (1.04 04 — 3. 3.49) 9) 0.73 73 (95% 5% CI, 0.66- admitted d wi with self^ f^po poison oning ng; ; High gh WB WBC (adm dmiss ssion) n) 1 1.55 55 (0.94 94-2. 2.55) 5) 0.80) 80) medi dical al notes es availab able e (validat ation on) Sig. g. p<0.1 >65 5 years, s, cons nsent ent, no anticanc ncer er medi dicat ation on, no ADR on/c /caus using ng admission Metho Me hod: d: Phase ase 1 variab able e ident ntification on and d model del desi sign n (n= 690), 0), Phase ase 2 Exter ernal al valida dation on (n=483 483). Review ew of drug g chart, lab param ametrs, repo ports/ s/refer erral als from om other er heal althcare e provider ders, obser servat ation onal al data a on admiss ssion n and daily ther ereaf eafter Asses ssessmen ent of ADE/A /ADR: R: Hallas as algor gorithm hm and d liker ert scal ale e derived ed by Bates es et al. (Pha hase e 1), naran anjo jo (Pha hase e 2)

Included studies: Onder G et al., 2010 Study de design Va Varia riable Score OR R (95% CI) Va Validation Cou ountry: Italy >4 co-morbidities 1 1.31 (1.04-1.64) Sensiti tivity=68.5% Sett tting: : Hos Hospital inp npati tient He Heart failure 1 1.79 (1.39-2.30) Spe peci cifici city=65.0% Outco come: : inpa npatient ADR ADR Liver di disease 1 1. 1.36 (1. 1.06 06-1.74) Discr Di crimination (AU AUCROC) Inclu nclusion: : >65 years, taking No. o. of of dr drugs gs <5 0 1.00 re reference ce = 0.70 (95% CI, 0.63- = medica med cation, com omplete da data for or No. o. of of dr drugs gs 5-7 1 1.90 (1.35 — 2.68) 0.78) variables available, cons onsent, t, not not No. o. of of dr drugs gs >8 4 4.07 (2.93-5.65) on on anti ntica cance cer me medication, no no Previous AD Pr ADR 2 2.41 (1.79-3.23) AD ADR on/ on/ca causing adm dmission Renal failure Re 1 1.21 (0.96-1.51) Method: Met : Ph Phase 1 vari riable Sig. g. p< p<0.1 ide dentifica cati tion and nd mo mode del de design (n= n= 5936), Ph Phase 2 Ex Exte ternal validati tion (n= n=483). Re Review of of char hart, t, x-ray ray films, lab b pa param rameters, medica med cal hi histo tories to o com omplete qu questionnaire an n adm dmission and nd da daily the hereafter As Assessment of of AD ADE/ADR: : Naran ranjo