Developing Valid Prescribing Quality Indicators Petra Denig

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1 Developing Valid Prescribing Quality Indicators Petra Denig Clinical Pharmacology Department, University Medical Center Groningen, University Groningen, The Netherlands

2 2 Disclosure Funding sources: University Medical Center Groningen, The Netherlands No other personal or financial relationships relevant to this presentation existed in the past year or during the conduct of the study Acknowledgements University Medical Center Groningen: Flora Haaijer-Ruskamp, Jaco Voorham, Grigory Sidorenkov, Liana Martirosyan

3 What you can expect 3 Part I: concepts underlying prescribing quality measurement quality assessment clinical pharmacological aspects of quality drug-oriented vs disease-oriented PQI Part II: indicator requirements face/content, concurrent and predictive validity data quality, samples (size), comparability relevance, actionability, unintended effects

4 Donabedian model of quality of care 4 Structure Process Outcome Environment in which health care is provided Organizational support & resources, e.g. alerting systems, CPOE Method by which health care is provided Prescriptions, related monitoring, tests, etc. Consequence of health care provided Intermediate or long term effects of prescribing Donabedian, 1988

5 Quality assessment 5 Evidence from clinical trials & experts consensus Clinical practice guideline recommendations Medication prescribing in practice Quality assessment

6 Prescribing Quality Indicators (PQI) 6 Measurable element of prescribing quality with sufficient rationale / evidence Clear definition of nominator and denominator (eligible patients) Example to be added Can be used for various purposes

7 Prescribing (quality) indicators Hospital audit, Punjab India, JDCR NHS Audit Scotland, Statins per 1000 adjusted population

8 8 Who needs quality information? Information on prescribing quality Internal use by health care professionals General public/patients, media External use by policy makers Feedback, improvement of prescribing practices Better provider (doctor/hospital) choice by patients P-4-P, monitoring, benchmarking, accreditation

9 Prescribing quality assessment in the 90 ies 9 Implicit assessment (record review) MAI= medication appropriateness index per drug on pharmacological aspects (Hanlon 1992) PAI= prescribing appropriateness indicator on (documented) agreement with formulary recommendations (indication, dose, etc.) (Cantrill 1998) Explicit assessment (various data sources) using explicit criteria, lists or quality indicators

10 Agreement between measures 10 Sins of Omission Hayward RA, et al. J Gen Int Med 2005 Overuse/misuse ~2-5% Underprescribing ~35-50% Steinman MA, e.a. Med Care 2007;45: 95-9 Steinman MA, e.a. Arch Int Med 2009;169:

11 Quality from clinical pharmacological perspective 11 Overprescribing of drugs avoid inappropriate drugs or drugs not needed avoid inappropriate Rx-Rx, Rx-DIS avoid duplication Suboptimal prescribing of drugs suboptimal selection (not first choice) dosing, duration age, drug burden follow-up, monitoring Underprescribing of drugs needed adequate and timely start of treatment

12 Classification of PQI 12 Drug-oriented PQI medication irrespective of the indication, e.g. firstchoice drugs, inappropriate drugs, costs, dosing Disease-oriented PQI medication in relation to disease, e.g. over/undertreatment Both can be patient specific: medication (not) prescribed for specific subpopulations, e.g. elderly, using comedication, having contraindications medication modified after indication, e.g. after specific event or uncontrolled risk factor level

13 Drug-oriented quality aspects 13 Overprescribing, avoid inappropriate drugs % longacting SU-derivatives/ all SU-derivatives First-choice drugs / formulary adherence % simvastatin/ all statins Dosing/duration % high dosed hydrochlorthiazide/ all HCT % 1-daily dosing antihypertensive/ all antihypertensives Comedication duplicate: % patients with multiple thiazides safety: % ACE-i + NSAID + diuretic Stepwise prescribing % starting on metformin/ all oral glucose regulating drugs % single agents prior to combi/ all combi users Rx level Patient level Martirosyan L, e.a. Pharmacoepi Drug Saf 2010;19:319-34

14 14 Most drug-oriented PQI focus on what is prescribed and not on what is NOT prescribed

15 Overprescribing disparate concepts 15 Lund BC, e.a. J Rural Health 2013;29:172-9

16 HEDIS High risk medication in the elderly (HMRE) Trends in large VA population 16 Pugh MJV, e.a. J Am Geriatr Soc ;59:

17 First choice at different therapeutic levels - incentivized indicators in Andalusia, Spain 17 Indicator Low quality High quality Mean (SD) Simvastatin / total statins >50% 60% 55± 16 ACE-inhibitors/ total RAAS-inhibitors Thiazide diuretics/ total antihypertensives >59% 75% 59± 15 >15% 20% 16 ± 6 Urrusuno RF, e.a. Eur J Clin Pharmacol 2013; epub

18 18 Drug-oriented PQI cover broad concepts of prescribing but it may be difficult to set quality benchmarks

19 Disease-oriented quality aspects 19 Adequate or timely treatment medication prescribed in patients with a specific diagnosis (treatment status) medication prescribed or modified after a specific event or uncontrolled risk factor (sequential) Optimal prescribing in view (co)morbidity % patients with coronary heart disease on aspirin or alternative therapy (QOF) % patients with diabetes and proteinuria or microalbuminuria treated with an ACE-I or ARBs (BMA) Avoid Rx-Dx, contra-indications IF a vulnerable elder has hypertension and asthma, THEN beta blocker therapy for hypertension should not be used (ACOVE)

20 Inappropriate prescribing in elderly overview of criteria 20 Beers USA 1991, 1997 Fick update 2003, 2012 adapted versions Diseaseoriented Rx-Rx Rx-Dx Omissions partly ~ Rx-Rx - McLeod Canada 1997 partly + - Laroche France 2007 partly + - Rognstad Norway no Rx-Dx - Basger Australia 2008 largely implicit + Gallagher Ireland START/STOPP 2008 largely + + Levy HB, e.a. Annals Pharmacother 2010;44:

21 Inappropriate prescribing - non overlapping issues 21 Study comparing utility of three established criteria in measuring prescribing appropriateness in a sample of hospitalized elderly patients in Australia Most Commonly Identified (202 records) Medication Beers McLeod NPS Total Aspirin Benzodiazipines Beta blockers Dipyridamol Pattanaworasate W e.a. Pharmacy Practice (Internet) 2010;8:132-8

22 STOPP / START criteria for elderly patients 22 STOPP: 65 indicators for potentially inappropriate overprescribing 10 physiological systems 10 drug oriented 55 are related to disease (history) of patient START: 22 indicators for prescribing omissions (underprescribing) 6 physiological systems 21 disease oriented 1 drug oriented (biphosponates when taking maintenance oral corticosteroid therapy)

23 23 Australian appropriateness criteria for 65 years Overprescribing (contra-indications, safety) 13. patients with cardiovascular disease NOT taking an NSAID 34. patients with COPD NOT taking benzodiazepines Underprescribing 2. patients at high risk recurrent CV event prescribed statins 15. with diabetes & albuminuria prescribed ACE-inhibitors Basger BJ, e.a. IJPP 2012;20:172-82

24 Underprescribing: treatment status or action Treatment status (cross-sectional) HEDIS (USA) % prescribing beta-blockers of patients with myocardial infarction QoF (UK) % prescribing ACE-i for diabetes patients with (micro)albuminuria 24 Adequate and timely action (sequential) ACOVE, e.g. IF a diabetic has an elevated HbA1c, THEN an intervention should occur within 3 months "tightly linked" quality measures, e.g. start or intensify treatment for patients having an LDL-cholesterol>3.4 mmol/l

25 Sequential indicator: treatment modifications within 6 months in patients with moderate and poor control of HbA1c, systolic blood pressure or LDL-cholesterol % patients Intensification Start 10 0 Good (n=3.839 n=1.143) Moderate (n=1.360 n=121) Poor (n=16 n=23) Good (n=2.315 n=1.117) Moderate (n=2.462 n=665) Poor (n=714 n=134) Good (n=2.824 n=417) Moderate (n=963 n=740) Poor (n=261 n=306) HbA1c Systolic BP LDL-cholesterol Voorham J, e.a. Pharmacoepi Drug Saf 2010;19:

26 Indicators with additional conditions (patient level) 26 % elderly with uncontrolled HbA1c who get medication intensification within 3 months in case of HbA1c 9% within 1 month in case of HbA1c 11% % diabetes patients prescribed statins unless contra-indicated % diabetes patient with flu-vaccination unless refused

27 27 Disease-oriented PQI capture overprescribing, underprescribing as well as timely prescribing but some may include few eligible patients

28 Part II: Indicator requirements 28 Necessity, importance -for patient outcomes Scientifically sound -content, face valid -precise, clear definition -concurrent validity -predictive validity Feasible / reliable -data collection, quality -fairness (case mix) Implementation -actionability, acceptability -easily interpreted

29 Scientific value of PQI 29 Face validity: assessed by experts and accepted by the health care professionals in the field place and time dependent Content validity: based on scientific evidence (guidelines) Concurrent validity: measures what it purports to measure (correlates with gold standard) Predictive validity: predicts health outcome (better patient outcomes)

30 Indicator development: first steps (for elderly) 30 Comprehensive literature review & existing criteria & clinical experience incomplete knowledge on benefits in elderly Content of most criteria validated in 2 or 3 rounds of a Delphi technique using 6- to 47-member expert panels composed of gerontologists and physicians Dimitrow MS, e.a. JAGS 2011;59:

31 Face validity in addition to content validity appropriateness criteria for older Australians based on guidelines evidence for specific subpopulations is limited (oldest old, comorbidity) RAND/UCLA expert evaluation and panel discussion 7 deleted for reasons of redundancy, 1 for irrelevance, 1 for poor evidence 25 reworded or redefined to better fit or restrict the eligible patients e.g. "Patient with heart failure is taking a β-blocker" changed to "Patient with stable heart failure due to left ventricular systolic dysfunction is taking a β-blocker Basger BJ, e.a. BMJ Open 2012;2: e001431

32 Clear definitions local specifications/adaptations 32 Example specification STOPP criteria digoxin at long term dose >125 ug/day with impaired renal function 2 Rx ATC C01AA05 with daily dose >125 ICPC U99.01 or egfr <50 ml/min Adaptation START/STOPP criteria Aspirin 150 mg/day => salicylates >160 mg/day (NL) criteria warfarin => oral anticoagulants

33 Concurrent validity between simple generic prescribing or substitution index 33 Quantity based generic share may be unfair for not taking room for substitution into account Kunisawa S, e.a. J Health Serv Res Policy 2013; epub

34 Concurrent validity treatment status (E) vs action (G) % 35-48% Reference Method % appropriate G G E F G E Glycaemic Blood pressure Lipid Equality F 20% deviation F E % Indicator % appropriate 38-95% Voorham J, e.a. Med Care 2008;46:133-41

35 Predictive validity of treatment status indicators for CV/diabetes 35 Cardio Vascular (CV) risk ratio GLD=glucose lowering drugs LLD=lipid lowering drugs AHD=antihypertensive drugs ACE-I or ARB=RAS inhibitors Sidorenkov G, e.a., BMJ Qual Saf 2013;22: Sidorenkov G e.a. PLoS One. 2013;8(10):e78821

36 Predictive validity of HEDIS measures for elderly 36 High risk medication in elderly (HRME) Drug-disease interaction (Rx-DIS) Prediction on mortality (both) and hospitalization, emergency care (HRME) Pugh MJV, e.a. Drugs Aging 2013; epub

37 STOPP / START validity review of 13 studies 37 Concurrent validity STOPP criteria were more sensitive in comparison to Beers criteria (6 studies) START criteria less sensitive in comparison to Australian appropriateness criteria (1 study) Predictive validity each problem identified with STOPP increased risk of ADEs (Odds Ratio 1.85, 95% CI ) insufficient evidence to determine the impact of implementing the criteria in practice Hill-Taylor B, e.a. J Clin Pharmacy Ther 2013, epub

38 38 Most PQI have content validity, many have been tested for face validity PQI assessing overprescribing as well as underprescribing have shown predictive validity

39 Methodological and statistical value of PQI Operational feasibility feasibility of data collection and calculation of PQI valid data are available for appropriate population 39 Reliability & sample size same outcome when measured by different persons or at different times minimal number of patients per PQI required for meaningful quality assessment (differentiate) Fairness: case-mix not affected by patient-related attributes (or controlled for relevant patient characteristics) comparability/uniformity/completeness of data and population

40 PQI types and operational feasibility 40 Drug oriented: Rx (pharmacy) Avoid inappropriate drugs Use of appropriate drugs Disease oriented: Rx & Dx (administrative) Indicated drugs: general under/overtreatment Patient oriented: Rx-Dx-?x linkage (Electronic Health Records) Medication prescribed for specific patients, e.g. contra-indicated drugs (cross-sectional) Event oriented action: Rx-Dx-?x linkage and related dates Medication modification after indication, e.g. after uncontrolled risk factor levels or specific event (sequential -> timely action)

41 Possible problems with data 41 All databases: included patients Pharmacy datasets reflect dispensing and not prescribing! 10-30% of patients do not collect medication Administrative/claims datasets cave: items covered (diseases/ drugs) availability of patient ID/ clinical data limited Electronic health records or GP data quality of registration: (diagnostic) coding may vary from provider to provider incomplete data: external/incoming data not always available

42 Inter-rater reliability 42 STOPP Spanish criteria START Spanish criteria ACOVE 37 underprescribing QI for 11 conditions Range Kappa (IQR) Kappa to 76 % 0.97 ( ) -benzo s (2x) -vasodilators 43 to 76 % 0.92 ( ) -ACE in HF, -aspirin/ clopidogrel in high risk 43 to 76% 0.95 ( ) -stroke prophylaxis in dementia -anticoagulation in high risk San-Jose A, e.a. Arch Gerontol Geriatr. 2014;58:460-4.

43 STOPP/START criteria with or without clinical data 43 Inappropriate prescribing detection is likely to be overestimated using STOPP without clinical information Underprescribing detection is likely to be underestimated using START without clinical information Some criteria can be assessed using only patients drug lists Ryan C, e.a. Int J Clin Pharm 2013;35: 230 5

44 Sample size: proportion of patients per GP with appropriate glucose-regulating treatment ,9 Proportion appropriate 0,8 0,7 0,6 0,5 0,4 0, ,2 0,1 0 GPs

45 Proportion patients per GP with confidence intervals ,9 Proportion appropriate 0,8 0,7 0,6 0,5 0,4 0, ,2 0,1 0 GPs

46 Case-mix: beta-blocker prescription after MI Adjustment for sociodemographic characteristics changed rates for most groups and measures by <5 percentage points (but some >10%) 46 Zaslavsky AM e.a. Int J Qual Health Care 2005;17:67-74

47 Comparability 47 Approaches to adjust for population differences standardization (e.g. many drug-oriented PQIs are age-standardized) stratification or restriction according to certain characteristic (e.g. including patients with certain indication) weighting (e.g. UK ASTRO PU or STAR PU)

48 48 Operational feasibility may limit a comprehensive review of prescribing quality Beware of sample size and case-mix adjustment when using PQI for external review and comparison

49 Implementation in practice 49 Relevance: phenomenon measured represents significant (public) interest, disease burden, cost systematic selection (not data-availability driven) Actionability: factors which influence phenomenon can be positively influenced patient level factors may interfere Unintended effects measurement fixation, e.g. statins in patients which short life expectancy gaming (perverse incentives, data checks)

50 Which PQI should we use? 50 PQI covering different aspects of prescribing simple drug/problem oriented indicators cost-effectiveness: first choice, obsolete dosing and duration co-medication (safety) indicators linked to patient/disease under/overprescribing specific conditions (elderly, comorbidity) sequential action indicators timely action Choice may depend on aim of use internal use: monitoring and quality improvement external use: accountability, P4P, public reporting

51 51 Indicator sets - examples General drug oriented WHO core drug use indicators Quality, Innovation, Productivity & Prevention (QIPP) Prescribing comparators (NHS) Monitor Prescription Behaviour (NL) Disease oriented (*part of general quality of care) Assessing Care of Vulnerable Elders (ACOVE)* Quality Outcome Framework (QOF)* Data-driven Quality Improvement in Primary care (DQIP) Prescribing safety indicators for GPs (UK)

52 52 Summary Drug-oriented PQI cover broad concepts of prescribing.....but cannot address what is NOT prescribed may highlight variation & support discussion....but difficult to set quality benchmarks Disease-oriented PQI can capture overprescribing, underprescribing and timely prescribing.....but may require detailed (clinical) data There are many PQI out there important to select PQI appropriate / valid for your purpose

53 Final remarks for PQI development and/or selection 53 Scientific soundness face/content validity: most PQI predictive validity: under/overprescribing PQI Methodological/statistical reliable measurement (definitions!): most PQI data collection: easiest for drug oriented PQI fairness (beware of sample size!): stratify or restrict eligible population for PQI Selection for practice relevance, actionability: poor for some PQI concerns about unintended consequences: broad selection of PQI

54 Multiple choice question 1 54 Drug-oriented prescribing quality indicators are not very suitable to measure: selection of preferred drug treatment prescribing of indicated drug treatment dosing of drug treatment duplication of drug treatment prescribing of drugs to avoid in the elderly

55 Multiple choice question 2 55 Which of the statements is correct? A patient identifier is needed to calculate first choice drug treatment Clinical data are needed to validly assess the STOPP/START criteria Large numbers of eligible patients are needed when using PQI for internal purposes Most drug-oriented PQI have shown to be predictive of better patient outcomes Age-gender standardisation is the best method to adjust for case-mix differences