Improving primary care prescribing safety using routine data for intervention and evaluation: four trials in 500+ practices

Transcription

1 University of Dundee School of Medicine Improving primary care prescribing safety using routine data for intervention and evaluation: four trials in 500+ practices

2 University of Dundee School of Medicine Improving primary care prescribing safety using routine data for intervention and evaluation: three trials and 1 interrupted time series study in 500+ practices

3 University of Dundee School of Medicine Preventable drug related harm Preventable drug-related morbidity (PRDM) is a concern o ~ 6.5% of all emergency hospital admissions are drug-related o ~ 2 to 4% are drug-related and preventable High-risk prescribing and monitoring cause 2/3 of PDRM o NSAIDs and antithrombotics: ~35% o Antihypertensives: ~30% o CNS active drugs: ~10% High-risk prescribing inappropriate or wrong prescribing o o Balance of benefit/risk Regular review necessary to ensure it continues to be appropriate

4 University of Dundee Odds ratio of patient receiving a high risk prescription in each practice School of Medicine 3.5 High-risk prescribing: Practice variation Odds ratio for each practice 3 Upper 95% CI 2.5 Lower 95% CI Practices ranked in ascending order of prevalence of high risk prescribing

5 High risk prescribing and polypharmacy No. of chronic drugs 0 drugs 1-2 drugs 3-4 drugs 5-6 drugs 7-8 drugs 9-10 drugs 11+ drugs % getting a high risk prescription Adjusted OR Four fold variation between practices Guthrie B et al. BMJ 2011;342:d3514

6 Percentage of patients receiving specified number of drugs No. of drug classes dispensed in previous 84 days in % 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% drugs 1 drug 2 drugs 3 drugs 4 drugs 5 drugs 6 drugs 7 drugs 8 drugs 9 drugs 10 drugs 11 drugs 12 drugs 13 drugs 14 drugs 15+ drugs Age group Guthrie B et al. BMC Medicine 2015

7 Percentage of patients receiving specified number of drugs Percentage of patients receiving specified number of drugs 100% No. of drug classes No. of drug dispensed classes dispensed in previous in last days days in 1995 in % 90% 90% 80% 80% 70% 70% 60% 60% 50% 50% 40% 40% 30% 30% 20% 20% 10% 10% 0% 0% Age group Guthrie B et al. BMC Medicine drugs 1 drug 2 drugs 3 drugs 4 drugs 5 drugs 6 drugs 7 drugs 8 drugs 9 drugs 10 drugs 11 drugs 12 drugs 13 drugs 14 drugs 15+ drugs

8 Intervention design Which intervention components? Identify patients with high-risk prescribing from EMRs Review of patients identified Corrective action High-risk prescribing Emergency admissions

9 Intervention design Which intervention components? Behaviour change model (Michie et al)

10 Intervention design Which intervention components? Identify patients with high-risk prescribing from EMRs Review of patients identified Corrective action IT component Motivation Education High-risk prescribing Emergency admissions

11 EFIPPS

12 EFIPPS Study Design 262 practices from three Scottish health boards Study arm Randomised practices 1. Low intensity 88 practices 2. Higher intensity 87 practices 3. Highest intensity 87 practices

13 EFIPPS Intervention design Study arm 1. Low intensity 2. Higher intensity 3. Highest intensity Education Motivation IT Written education al material Written education al material Written education al material - Downloadable EMR searches to identify patients Feedback with benchmark Feedback with benchmark PLUS theory informed behaviour change intervention Downloadable EMR searches to identify patients Downloadable EMR searches to identify patients

14 EFIPPS findings

15 EFIPPS findings OR at 12 months Arm 2 vs Arm (0.80 to 0.96) Arm 3 vs Arm (0.78 to 0.95) Antipsychotics dementia 1.01/1.02 Triple whammy 0.91/0.91 NSAID aged /0.82 Antiplatelet + NSAID 0.88/0.82 OAC + NSAID 0.92/0.73 OAC + antiplatelet 0.82/0.72 Guthrie B et al BMJ 2016: i4079

16 DQIP

17 Study arm 1. Low intensity EFIPPS Intervention design Education Motivation IT Higher intensity Written educational material PLUS Educational Outreach Visit Financial incentives ( 350 participation fee plus 15 per review) IT tool - list of patients to review - facilitation of review - Run charts to monitor progress

18 DQIP Study Design 33 practices from one Scottish health board

19 DQIP findings

20 DQIP findings Primary outcome OR 0.63 (95% CI ) Ongoing high-risk prescribing OR 0.60 (95% CI ) New high-risk prescribing OR 0.77(95% CI ) Sustained 12 months after the intervention stopped GI bleeding admissions OR 0.66 (95% CI ) Heart failure admissions OR 0.73 (95% CI ) Acute kidney injury admissions OR 0.84 (95% CI ) Unrelated ACSA OR 1.02 (95% CI ) Dreischulte T et al. NEJM 2016; 374:

21 EPIPP design Cluster-randomised trial in 242 (100%) practices Both arms active Targets potentially problematic prescribing in asthma vs multiple urinary antibiotic prescribing Includes feedback of data for individual patients

22 EFIPPS Study Design 242 practices from one Scottish health board Study arm 1. Antibiotics for UTIs (control for arm 2) 2. Suboptimal prescribing for asthma (control for arm 1) Randomised practices 121 practices 121 practices

23 EPIPP Intervention design Study arm 1. Frequent use of antibiotics (control for arm 2) 2. Suboptimal asthma prescribing (control for arm 1) Education Motivation IT - - Practice level feedback - - Practice level feedback - Use of PIS to generate lists of individual patients for review - Use of PIS to generate lists of individual patients for review

24 POEMS design ITS in 54 (100%) practices Intervention is an informatics tool to support contractually incentivised polypharmacy review in people aged 75+ taking 10 or more drugs Operationalises 50+ pages of Scottish guidance 122 indicators of high-risk prescribing, potential overuse, potential underuse and monitoring failure Links data from primary care record, laboratories and unscheduled care (hospital, A&E/ER, GP out of hours)

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27 Conclusion Prescribing safety is common and improvable Adds to evidence from previous trials PINCER (pharmacist led) OPTISCRIPT (GP led) All feasible in routine practice Many remaining questions Evidence is for selected indicators Apart from DQIP little data on sustainability Electronic vs paper

28 DQIP Aileen Grant, Adrian Hapca, Peter Donnan, Colin McCowan, Bruce Guthrie Health Informatics Centre EFIPPS Marion Bennie, Chris Robertson, Kim Kavanagh, Karen Barnett, Shaun Treweek, Lewis Ritchie, Dennis Petrie, Iain Bishop, Bruce Guthrie, ISD Scotland, edris EPIPP Sean Macbride-Stewart, Charis Marwick, Bruce Guthrie POEMS Jason Tang, Peter Donnan, Lyall Cameron, Graeme Longair, Neil Mellon, Grant McHattie, Bruce Guthrie

29 QUESTIONS?

30 DQIP References Dreischulte T et al. Safer prescribing: a trial of incentives, informatics and education. New England Journal of Medicine 2016: Guthrie B et al. The rising tide of polypharmacy and drug-drug interactions: population database analysis BMC Medicine 2015;13:74 Grant A et al. Developing a complex intervention to improve prescribing safety in primary care: mixed methods feasibility and optimisation pilot study. BMJ Open 2014;4:1 Guthrie B et al. High-risk prescribing in primary care patients particularly vulnerable to adverse drug events: cross-sectional population database analysis in Scottish general practice. BMJ 2011;342:d3514 EFIPPS Guthrie B et al. Data feedback and behavioural change intervention to improve primary care prescribing safety (EFIPPS): multicentre, three arm, cluster randomised controlled trial. BMJ 2016; 354: i4079 Barnett KN et al. Effective Feedback to Improve Primary Care Prescribing Safety (EFIPPS) a pragmatic three-arm-cluster randomised trial: designing the intervention. Implementation Science 2014:9(1);133