Evaluation of a pharmacist-led actionable audit and feedback intervention for improving medication safety in UK primary care: An interrupted time series analysis

Autoři: Niels Peek aff001;  Wouter T. Gude aff004;  Richard N. Keers aff001;  Richard Williams aff001;  Evangelos Kontopantelis aff007;  Mark Jeffries aff001;  Denham L. Phipps aff001;  Benjamin Brown aff001;  Anthony J. Avery aff001;  Darren M. Ashcroft aff001
Působiště autorů: NIHR Greater Manchester Patient Safety Translational Research Centre, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom aff001;  NIHR Manchester Biomedical Research Centre, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom aff002;  Centre for Health Informatics, Division of Informatics, Imaging and Data Science, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom aff003;  Department of Medical Informatics, Amsterdam UMC, Amsterdam Public Health Research Institute, University of Amsterdam, Amsterdam, Netherlands aff004;  Centre for Pharmacoepidemiology and Drug Safety, Division of Pharmacy and Optometry, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Sciences Centre, Manchester, United Kingdom aff005;  Pharmacy Department, Greater Manchester Mental Health NHS Foundation Trust, Manchester, United Kingdom aff006;  NIHR School for Primary Care Research, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom aff007;  Centre for Primary Care, Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United aff008;  Division of Primary Care, School of Medicine, University of Nottingham, Nottingham, United Kingdom aff009
Vyšlo v časopise: Evaluation of a pharmacist-led actionable audit and feedback intervention for improving medication safety in UK primary care: An interrupted time series analysis. PLoS Med 17(10): e32767. doi:10.1371/journal.pmed.1003286
Kategorie: Research Article
doi: 10.1371/journal.pmed.1003286



We evaluated the impact of the pharmacist-led Safety Medication dASHboard (SMASH) intervention on medication safety in primary care.

Methods and findings

SMASH comprised (1) training of clinical pharmacists to deliver the intervention; (2) a web-based dashboard providing actionable, patient-level feedback; and (3) pharmacists reviewing individual at-risk patients, and initiating remedial actions or advising general practitioners on doing so. It was implemented in 43 general practices covering a population of 235,595 people in Salford (Greater Manchester), UK. All practices started receiving the intervention between 18 April 2016 and 26 September 2017. We used an interrupted time series analysis of rates (prevalence) of potentially hazardous prescribing and inadequate blood-test monitoring, comparing observed rates post-intervention to extrapolations from a 24-month pre-intervention trend. The number of people registered to participating practices and having 1 or more risk factors for being exposed to hazardous prescribing or inadequate blood-test monitoring at the start of the intervention was 47,413 (males: 23,073 [48.7%]; mean age: 60 years [standard deviation: 21]). At baseline, 95% of practices had rates of potentially hazardous prescribing (composite of 10 indicators) between 0.88% and 6.19%. The prevalence of potentially hazardous prescribing reduced by 27.9% (95% CI 20.3% to 36.8%, p < 0.001) at 24 weeks and by 40.7% (95% CI 29.1% to 54.2%, p < 0.001) at 12 months after introduction of SMASH. The rate of inadequate blood-test monitoring (composite of 2 indicators) reduced by 22.0% (95% CI 0.2% to 50.7%, p = 0.046) at 24 weeks; the change at 12 months (23.5%) was no longer significant (95% CI −4.5% to 61.6%, p = 0.127). After 12 months, 95% of practices had rates of potentially hazardous prescribing between 0.74% and 3.02%. Study limitations include the fact that practices were not randomised, and therefore unmeasured confounding may have influenced our findings.


The SMASH intervention was associated with reduced rates of potentially hazardous prescribing and inadequate blood-test monitoring in general practices. This reduction was sustained over 12 months after the start of the intervention for prescribing but not for monitoring of medication. There was a marked reduction in the variation in rates of hazardous prescribing between practices.

Klíčová slova:

Antiplatelet therapy – Drug safety – Extrapolation – Medical risk factors – NSAIDs – Patients – Pharmacists – Primary care


1. Donaldson LJ, Kelley ET, Dhingra-Kumar N, Kieny M-P, Sheikh A. Medication without harm: WHO’s Third Global Patient Safety Challenge. Lancet. 2017;389:1680–1. doi: 10.1016/S0140-6736(17)31047-4 28463129

2. Panagioti M, Khan K, Keers RN, Abuzour A, Phipps D, Kontopantelis E, et al. Prevalence, severity, and nature of preventable patient harm across medical care settings: systematic review and meta-analysis. BMJ. 2019;366:l4185. doi: 10.1136/bmj.l4185 31315828

3. Aitken M, Gorokhovich L. Advancing the responsible use of medicines: applying levers for change. SSRN 2012 Sep 17. doi: 10.2139/ssrn.2222541

4. Taché SV, Sönnichsen A, Ashcroft DM. Prevalence of adverse drug events in ambulatory care: a systematic review. Ann Pharmacother. 2011;45:977–89. doi: 10.1345/aph.1P627 21693697

5. Elliott R, Camacho E, Campbell F, Jankovic D, Martyn-St James M, Kaltenthaler E, et al. Prevalence and economic burden of medication errors in the NHS in England: rapid evidence synthesis and economic analysis of the prevalence and burden of medication error in the UK. Policy Research Unit in Economic Evaluation of Health and Care Interventions; 2018.

6. Stocks SJ, Kontopantelis E, Akbarov A, Rodgers S, Avery AJ, Ashcroft DM. Examining variations in prescribing safety in UK general practice: cross sectional study using the Clinical Practice Research Datalink. BMJ. 2015;351:h5501. doi: 10.1136/bmj.h5501 26537416

7. Bates DW, Gawande AA. Improving safety with information technology. N Engl J Med. 2003;348:2526–34. doi: 10.1056/NEJMsa020847 12815139

8. Hayward J, Thomson F, Milne H, Buckingham S, Sheikh A, Fernando B, et al. ‘Too much, too late’: mixed methods multi-channel video recording study of computerized decision support systems and GP prescribing. J Am Med Inform Assoc. 2013;20:e76–84. doi: 10.1136/amiajnl-2012-001484 23470696

9. Nanji KC, Slight SP, Seger DL, Cho I, Fiskio JM, Redden LM, et al. Overrides of medication-related clinical decision support alerts in outpatients. J Am Med Inform Assoc. 2014;21:487–91. doi: 10.1136/amiajnl-2013-001813 24166725

10. Tuti T, Nzinga J, Njoroge M, Brown B, Peek N, English M, et al. A systematic review of electronic audit and feedback: Intervention effectiveness and use of behaviour change theory. Implement Sci. 2017;12:61. doi: 10.1186/s13012-017-0590-z 28494799

11. Hudson PTW, Guchelaar H-J. Risk assessment in clinical pharmacy. Pharm World Sci. 2003;25:98–103. doi: 10.1023/a:1024068817085 12840962

12. Avery AJ, Rodgers S, Cantrill J A, Armstrong S, Cresswell K, Eden M, et al. A pharmacist-led information technology intervention for medication errors (PINCER): a multicentre, cluster randomised, controlled trial and cost-effectiveness analysis. Lancet. 2012;379:1310–9. doi: 10.1016/S0140-6736(11)61817-5 22357106

13. Ivers N, Jamtvedt G, Flottorp S, Young JM, Odgaard-Jensen J, French SD, et al. Audit and feedback: effects on professional practice and healthcare outcomes. Cochrane Database Syst Rev. 2012;6:CD000259. doi: 10.1002/14651858.CD000259.pub3 22696318

14. Williams R, Keers R, Gude WT, Jeffries M, Davies C, Brown B, et al. SMASH! The Salford medication safety dashboard. J Innov Health Inform. 2018;25:183–93. doi: 10.14236/jhi.v25i3.1015 30398462

15. Anderson C, Zhan K, Boyd M, Mann C. The role of pharmacists in general practice: a realist review. Res Social Adm Pharm. 2019;15:338–45. doi: 10.1016/j.sapharm.2018.06.001 29907317

16. Bradley F, Seston E, Mannall C, Cutts C. Evolution of the general practice pharmacist’s role in England: a longitudinal study. Br J Gen Pract. 2018;68:e727–34. doi: 10.3399/bjgp18X698849 30154077

17. NHS England. Clinical pharmacists. London: NHS England; 2019 [cited 2019 Jun 2]. Available from: https://www.england.nhs.uk/gp/gpfv/workforce/building-the-general-practice-workforce/cp-gp/.

18. Des Jarlais DC, Lyles C, Crepaz N, TREND Group. Standards for reporting non-randomized evaluations of behavioral and public health interventions: the TREND statement. Am J Public Health. 2004;94(3):361–6. doi: 10.2105/ajph.94.3.361 14998794

19. Hoffmann TC, Glasziou PP, Boutron I, Milne R, Perera R, Moher D, et al. Better reporting of interventions: template for intervention description and replication (TIDieR) checklist and guide. BMJ. 2014;348:g1687. doi: 10.1136/bmj.g1687 24609605

20. Rodgers S, Salema N-E, Waring J, Armstrong S, Mehta R, Bell B, et al. Improving medication safety in general practices in the East Midlands through the PINCER intervention: scaling up PINCER. Nottingham: University of Nottingham; 2018 [cited 2020 Apr 13]. Available from: https://nottingham-repository.worktribe.com/output/1778784/improving-medication-safety-in-general-practices-in-the-east-midlands-through-the-pincer-intervention-scaling-up-pincer.

21. Akbarov A, Kontopantelis E, Sperrin M, Stocks SJ, Williams R, Rodgers S, et al. Primary care medication safety surveillance with integrated primary and secondary care electronic health records: a cross-sectional study. Drug Saf. 2015;38:671–82. doi: 10.1007/s40264-015-0304-x 26100143

22. New JP, Leather D, Bakerly ND, McCrae J, Gibson JM. Putting patients in control of data from electronic health records. BMJ. 2018;360:j5554. doi: 10.1136/bmj.j5554 29295813

23. National Institute for Health and Care Excellence. Medicines optimisation: the safe and effective use of medicines to enable the best possible outcomes. London: National Institute for Health and Care Excellence; 2018 [cited 2019 Jun 2]. Available from: https://www.nice.org.uk/guidance/ng5.

24. Sadler S, Rodgers S, Howard R, Morris CJ, Avery AJ. Training pharmacists to deliver a complex information technology intervention (PINCER) using the principles of educational outreach and root cause analysis. Int J Pharm Pract. 2014;22:47–58. doi: 10.1111/ijpp.12032 23600928

25. Jeffries M, Keers RN, Phipps DL, Williams R, Brown B, Avery AJ, et al. Developing a learning health system: insights from a qualitative process evaluation of a pharmacist-led electronic audit and feedback intervention to improve medication safety in primary care. PLoS ONE. 2018;13:e0205419. doi: 10.1371/journal.pone.0205419 30365508

26. Jeffries M, Phipps DL, Howard RL, Avery AJ, Rodgers S, Ashcroft DM. Understanding the implementation and adoption of a technological intervention to improve medication safety in primary care: a realist evaluation. BMC Health Serv Res. 2017;17:196. doi: 10.1186/s12913-017-2131-5 28288634

27. Salford Clinical Commissioning Group. Salford standard. Salford: Salford Clinical Commissioning Group; 2019 [cited 2019 Jun 2]. Available from: https://www.salfordccg.nhs.uk/transformation/salford-standard.

28. StataCorp. Stata statistical software. Release 15. College Station (TX): StataCorp; 2017.

29. Linden A. Conducting interrupted time-series analysis for single- and multiple-group comparisons. Stata J. 2015;15:480–500.

30. Stevens S, Valderas JM, Doran T, Perera R, Kontopantelis E. Analysing indicators of performance, satisfaction, or safety using empirical logit transformation. BMJ. 2016;352:i1114. doi: 10.1136/bmj.i1114 26964829

31. Kontopantelis E, Doran T, Springate DA, Buchan I, Reeves D. Regression based quasi-experimental approach when randomisation is not an option: interrupted time series analysis. BMJ. 2015;350:h2750. doi: 10.1136/bmj.h2750 26058820

32. Petropoulou M, Mavridis D. A comparison of 20 heterogeneity variance estimators in statistical synthesis of results from studies: a simulation study. Stat Med. 2017;36:4266–80. doi: 10.1002/sim.7431 28815652

33. Kontopantelis E, Springate DA, Reeves D. A re-analysis of the Cochrane Library data: the dangers of unobserved heterogeneity in meta-analyses. PLoS ONE. 2013;8:e69930. doi: 10.1371/journal.pone.0069930 23922860

34. Kontopantelis E, Reeves D. Metaan: Random-effects meta-analysis. Stata J. 2010;10:395–407.

35. Higgins JPT, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002;21:1539–58. doi: 10.1002/sim.1186 12111919

36. Keers R, Phipps D, Ojeleye L, Hassan L, Chuter A, Mann F, et al. Improving medication safety in primary care: developing a stakeholder-centred electronic prescribing safety indicator dashboard. Pharmacoepidemiol Drug Saf. 2018;27:O15–44. doi: 10.1002/pds.3812 26075570

37. Morales DR, Dreischulte T, Lipworth BJ, Donnan PT, Jackson C, Guthrie B. Respiratory effect of beta‐blocker eye drops in asthma: population‐based study and meta‐analysis of clinical trials. Br J Clin Pharmacol. 2016;82:814–22. doi: 10.1111/bcp.13006 27161880

38. Morales DR, Lipworth BJ, Donnan PT, Jackson C, Guthrie B. Respiratory effect of beta-blockers in people with asthma and cardiovascular disease: population-based nested case control study. BMC Med. 2017;15:18. doi: 10.1186/s12916-017-0781-0 28126029

39. Jeffries M, Gude WT, Keers RN, Phipps DL, Williams R, Kontopantelis E, et al. Understanding the utilisation of a novel interactive electronic medication safety dashboard in general practice: a mixed methods study. BMC Med Inform Decis Mak. 2020;20(1):69. doi: 10.1186/s12911-020-1084-5 32303219

40. NHS England. A five-year framework for GP contract reform to implement the NHS Long Term Plan. London: NHS England; 2019 [cited 2019 Jun 2]. Available from: https://www.england.nhs.uk/publication/gp-contract-five-year-framework/.

41. Dreischulte T, Donnan P, Grant A, Hapca A, McCowan C, Guthrie B. Safer prescribing—a trial of education, informatics, and financial incentives. N Engl J Med. 2016;374:1053–64. doi: 10.1056/NEJMsa1508955 26981935

42. MacBride-Stewart S, Marwick C, Houston N, Watt I, Patton A, Guthrie B. Evaluation of a complex intervention to improve primary care prescribing: a phase IV segmented regression interrupted time series analysis. Br J Gen Pract. 2017;67:e352–60. doi: 10.3399/bjgp17X690437 28347986

43. Bush J, Langley CA, Jenkins D, Johal J, Huckerby C. Clinical pharmacists in general practice: an initial evaluation of activity in one English primary care organisation. Int J Pharm Pract. 2018;26:501–6. doi: 10.1111/ijpp.12426 29280513

44. Hazen ACM, de Bont AA, Boelman L, Zwart DLM, de Gier JJ, de Wit NJ, et al. The degree of integration of non-dispensing pharmacists in primary care practice and the impact on health outcomes: a systematic review. Res Social Adm Pharm. 2018;14:228–40. doi: 10.1016/j.sapharm.2017.04.014 28506574

45. Friedman CP, Rubin JC, Sullivan KJ. Toward an information infrastructure for global health improvement. Yearb Med Inform. 2017;26:16–23. doi: 10.15265/IY-2017-004 28480469

46. Charlson ME, Pompei P, Ales KL, et al. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40:373–83. doi: 10.1016/0021-9681(87)90171-8 3558716

47. Iacobucci G. General practices achieve 95% of QOF points. BMJ. 2016;355:i5834. doi: 10.1136/bmj.i5834 27793795

Článek vyšel v časopise

PLOS Medicine

2020 Číslo 10

Nejčtenější v tomto čísle

Tomuto tématu se dále věnují…


Zvyšte si kvalifikaci online z pohodlí domova

Imunitní trombocytopenie (ITP) u dospělých pacientů
nový kurz
Autoři: prof. MUDr. Tomáš Kozák, Ph.D., MBA

Pěnová skleroterapie
Autoři: MUDr. Marek Šlais

White paper - jak vidíme optimální péči o zubní náhrady
Autoři: MUDr. Jindřich Charvát, CSc.

Hemofilie - série kurzů

Faktory ovlivňující léčbu levotyroxinem

Všechny kurzy
Kurzy Doporučená témata Časopisy
Zapomenuté heslo

Nemáte účet?  Registrujte se

Zapomenuté heslo

Zadejte e-mailovou adresu se kterou jste vytvářel(a) účet, budou Vám na ni zaslány informace k nastavení nového hesla.


Nemáte účet?  Registrujte se

VIRTUÁLNÍ ČEKÁRNA ČR Jste praktický lékař nebo pediatr? Zapojte se! Jste praktik nebo pediatr? Zapojte se!