Background and Objective
We recently showed that a pharmacist-led information technology-based intervention (PINCER) was significantly more effective in reducing medication errors in general practices than providing simple feedback on errors, with cost per error avoided at £79 (US$131). We aimed to estimate cost effectiveness of the PINCER intervention by combining effectiveness in error reduction and intervention costs with the effect of the individual errors on patient outcomes and healthcare costs, to estimate the effect on costs and QALYs.
We developed Markov models for each of six medication errors targeted by PINCER. Clinical event probability, treatment pathway, resource use and costs were extracted from literature and costing tariffs. A composite probabilistic model combined patient-level error models with practice-level error rates and intervention costs from the trial. Cost per extra QALY and cost-effectiveness acceptability curves were generated from the perspective of NHS England, with a 5-year time horizon.
The PINCER intervention generated £2,679 less cost and 0.81 more QALYs per practice [incremental cost-effectiveness ratio (ICER): −£3,037 per QALY] in the deterministic analysis. In the probabilistic analysis, PINCER generated 0.001 extra QALYs per practice compared with simple feedback, at £4.20 less per practice. Despite this extremely small set of differences in costs and outcomes, PINCER dominated simple feedback with a mean ICER of −£3,936 (standard error £2,970). At a ceiling ‘willingness-to-pay’ of £20,000/QALY, PINCER reaches 59 % probability of being cost effective.
PINCER produced marginal health gain at slightly reduced overall cost. Results are uncertain due to the poor quality of data to inform the effect of avoiding errors.
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The Evidence Centre on behalf of The Health Foundation. Research scan: improving safety in primary care. London: The Health Foundation; 2011.
Sheikh A, Panesar SS, Larizgoitia I, Bates DW, Donaldson LJ. Safer primary care for all: a global imperative. Lancet Global Health. 2013;1:e182–3.
Department of Health. An organisation with a memory: report of an expert group on learning from adverse events in the NHS, London: Department of Health; 2000.
Kohn L, Corrigan J, Donaldson M. To err is human-building a safer health system. Washington, DC: Institute of Medicine; 1999.
Wu T-Y, Jen M-H, Bottle A, Molokhia M, Aylin P, Bell D, et al. Ten-year trends in hospital admissions for adverse drug reactions in England 1999–2009. J R Soc Med. 2010;103:239–50.
Department of Health. Equity and excellence: liberating the NHS. London: Department of Health; 2010.
Elliott RA. Is QUM an efficient use of healthcare resources? J Pharm Pract Res. 2008;38:172.
The Evidence Centre on behalf of The Health Foundation. Evidence scan: reducing prescribing errors. London: The Health Foundation; 2012 Apr.
Royal S, Smeaton L, Avery AJ, Hurwitz B, Sheikh A. Interventions in primary care to reduce medication related adverse events and hospital admissions: systematic review and meta-analysis. Qual Saf Health Care. 2006;15(1):23–31.
Sculpher M. Evaluating the cost-effectiveness of interventions designed to increase the utilization of evidence-based guidelines. Fam Pract. 2000;17(Suppl 1):S26–31.
Gray A. Adverse events and the National Health Service: an economic perspective. A report to the National Patient Safety Agency. Oxford: Health Economics Research Centre, Department of Public Health, University of Oxford; 2003.
Thomsen LA, Winterstein AG, Sondergaard B, Haugbolle LS, Melander A. Systematic review of the incidence and characteristics of preventable adverse drug events in ambulatory care. Ann Pharmacother. 2007;41:1411–26.
Garfield S, Barber N, Walley P, Willson A, Eliasson L. Quality of medication use in primary care—mapping the problem, working to a solution: a systematic review of the literature. BMC Med. 2009;7:50.
Niquille A, Ruggli M, Buchmann M, Jordan D, Bugnon O. The nine-year sustained cost-containment impact of swiss pilot physicians–pharmacists quality circles. Ann Pharmacother. 2010;44:650–7.
Avery AJ, Rodgers S, Cantrill JA, 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.
Husereau D, Drummond M, Petrou S, Carswell C, Moher D, Greenberg D, et al. Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement. BMC Med. 2013;11:80.
Howard RL, Avery AJ, Howard PD, Partridge M. Investigation into the reasons for preventable drug related admissions to a medical admissions unit: observational study. Qual Saf Health Care. 2003;12:280–5.
Howard RL, Avery AJ, Slavenburg S, Royal S, Pipe G, Lucassen P, et al. Which drugs cause preventable admissions to hospital? A systematic review. Br J Clin Pharmacol. 2007;63:136–47.
Chen YF, Avery AJ, Neil KE, Johson C, Dewey ME, Stockley IH. Incidence and possible causes of prescribing potentially hazardous/contraindicated drug combinations in general practice. Drug Saf. 2005;28:67–80.
Avery A, Rodgers S, Cantrill J, Armstrong S, Elliott R, Howard R, et al. Protocol for the PINCER trial: a cluster randomised trial comparing the effectiveness of a pharmacist-led IT-based intervention with simple feedback in reducing rates of clinically important errors in medicines management in general practices. Trials. 2009;10:28.
Avery AJ, Rodgers S, Cantrill JA, Armstrong S, Boyd M, Cresswell K, et al. PINCER trial: a cluster randomised trial comparing the effectiveness and cost-effectiveness of a pharmacist-led IT-based intervention with simple feedback in reducing rates of clinically important errors in medicines management in general practices. In: Patient Safety Research Portfolio. Birmingham: University of Birmingham; 2010.
HM Treasury. The Green Book: appraisal and evaluation in central government. London: The Stationery Office; 2013.
Elliott RA, Putman K, Franklin M, Verhaeghe N, Annemans L, Eden M, et al. Economic evaluation of a pharmacist-led IT-based intervention with simple feedback in reducing rates of clinically important errors in medicines management in general practices (PINCER). In: Department of Health Patient Safety Research Portfolio. Birmingham: University of Birmingham; 2013.
Brown TJ, Hooper L, Elliott RA, Payne K, Webb R, Roberts C, et al. A comparison of the cost-effectiveness of five strategies for the prevention of non-steroidal anti-inflammatory drug-induced gastrointestinal toxicity: a systematic review with economic modelling. Health Technol Assess. 2006;10:iii-183.
Elliott RA, Hooper L, Payne K, Brown TJ, Roberts C, Symmons D. Preventing non-steroidal anti-inflammatory drug-induced gastrointestinal toxicity: are older strategies more cost-effective in the general population? Rheumatology. 2006;45:606–13.
Maetzel A, Ferraz MB, Bombardier C. The cost-effectiveness of misoprostol in preventing serious gastrointestinal events associated with the use of nonsteroidal antiinflammatory drugs. Arthritis Rheum. 1998;41:16–25.
Steuten L, Palmer S, Vrijhoef B, van Merode F, Spreeuwenberg C, Severens H. Cost-utility of a disease management program for patients with asthma. Int J Technol Assess Health Care. 2007;23:184–91.
Price MJ, Briggs AH. Development of an economic model to assess the cost effectiveness of asthma management strategies. Pharmacoeconomics. 2002;20:183–94.
Soares-Weiser K, Bravo Vergel Y, Beynon S, Dunn G, Barbieri M, Duffy S, et al. A systematic review and economic model of the clinical effectiveness and cost-effectiveness of interventions for preventing relapse in people with bipolar disorder. Health Technol Assess. 2007;11:1–226.
Bridle C, Palmer S, Bagnall A, Darba J, Duffy S, Sculpher M, et al. A rapid and systematic review and economic evaluation of the clinical and cost-effectiveness of newer drugs for treatment of mania associated with bipolar affective disorder. Health Technol Assess. 2004;8:iii–iv, 1–187.
Sharma S, Joshi S, Chadda RK. Therapeutic drug monitoring of lithium in patients with bipolar affective disorder: experiences from a tertiary care hospital in India. Am J Ther. 2009;16:393–7.
Tanda ML, Piantanida E, Lai A, Liparulo L, Sassi L, Bogazzi F, et al. Diagnosis and management of amiodarone-induced thyrotoxicosis: similarities and differences between North American and European thyroidologists. Clin Endocrinol. 2008;69:812–8.
Amir O, Hassan Y, Sarriff A, Awaisu A, Abd AN, Ismail O. Incidence of risk factors for developing hyperkalemia when using ACE inhibitors in cardiovascular diseases. Pharm World Sci. 2009;31:387–93.
de Denus S, Tardif JC, White M, Bourassa MG, Racine N, Levesque S, et al. Quantification of the risk and predictors of hyperkalemia in patients with left ventricular dysfunction: a retrospective analysis of the Studies of Left Ventricular Dysfunction (SOLVD) trials. Am Heart J. 2006;152:705–12.
Geddes JR, Burgess S, Hawton K, Jamison K, Goodwin GM. Long-term lithium therapy for bipolar disorder: systematic review and meta-analysis of randomized controlled trials. Am J Psychiatry. 2004;161:217–22.
Young AH, Newham JI. Lithium in maintenance therapy for bipolar disorder. J Psychopharmacol. 2006;20:17–22.
Pettitt D, Goldstein JL, McGuire A, Schwartz JS, Burke T, Maniadakis N. Overview of the arthritis cost consequence evaluation system (ACCES): a pharmacoeconomic model for celecoxib. Rheumatology. 2000;39:33–42.
Baraldi A, Ballestri M, Rapana R, Lucchi L, Borella P, Leonelli M, et al. Acute renal failure of medical type in an elderly population. Nephrol Dial Transplant. 1998;13(Suppl 7):25–9.
Mittalhenkle A, Stehman-Breen CO, Shlipak MG, Fried LF, Katz R, Young BA, et al. Cardiovascular risk factors and incident acute renal failure in older adults: the cardiovascular health study. Clin J Am Soc Nephrol. 2008;3:450–6.
Knight EL, Glynn RJ, McIntyre KM, Mogun H, Avorn J. Predictors of decreased renal function in patients with heart failure during angiotensin-converting enzyme inhibitor therapy: results from the studies of left ventricular dysfunction (SOLVD). Am Heart J. 1999;138:849–55.
Wynckel A, Ebikili B, Melin JP, Randoux C, Lavaud S, Chanard J. Long-term follow-up of acute renal failure caused by angiotensin converting enzyme inhibitors. Am J Hypertens. 1998;11:1080–6.
Bartalena L, Wiersinga WM, Tanda ML, Bogazzi F, Piantanida E, Lai A, et al. Diagnosis and management of amiodarone-induced thyrotoxicosis in Europe: results of an international survey among members of the European Thyroid Association. Clin Endocrinol. 2004;61:494–502.
Spiegel BMR, Chiou CF, Ofman JJ. Minimizing complications from nonsteroidal antiinflammatory drugs: cost effectiveness of competing strategies in varying risk groups. Arthritis Rheum. 2005;53:185–97.
Revicki DA, Hanlon J, Martin S, Gyulai L, Nassir Ghaemi S, Lynch F, et al. Patient-based utilities for bipolar disorder-related health states. J Affect Disord. 2005;87:203–10.
Revicki DA, Wood M. Patient-assigned health state utilities for depression-related outcomes: differences by depression severity and antidepressant medications. J Affect Disord. 1998;48:25–36.
NICE. The management of bipolar disorder in adults, children and adolescents, in primary and secondary care: national clinical practice guideline number 38. London: The British Psychological Society and The Royal College of Psychiatrists; 2006.
Barber JA, Thompson SG. Analysis of cost data in randomized trials: an application of the non-parametric bootstrap. Stat Med. 2000;19:3219–36.
Fenwick E, Byford S. A guide to cost-effectiveness acceptability curves. Br J Psychiatry. 2005;187:106–8.
Fenwick E, Claxton K, Sculpher MJ. Representing uncertainty: the role of cost effectiveness acceptability curves. Health Econ. 2001;10:779–87.
McCabe C, Claxton K, Culyer AJ. The NICE cost-effectiveness threshold: what it is and what that means. Pharmacoeconomics. 2008;26:733–44.
Bond CM, Fish A, Porteous TH, Reid JP, Scott A, Antonazzo E. A randomised controlled trial of the effects of note-based medication review by community pharmacists on prescribing of cardiovascular drugs in general practice. Int J Pharm Pract. 2007;15:39–46.
Payne K, McAllister M, Davies LM. Valuing the economic benefits of complex interventions: when maximising health is not enough. Health Econ. 2013;22:258–71.
Curtis L. Unit costs of health and social care 2012. Canterbury: University of Kent, Personal Social Services Research Unit; 2012.
Office for National Statistics. Mortality rates UK. Newport: Office for National Statistics; 2010.
Ohmann C, Imhof M, Ruppert C, Janzik U, Vogt C, Frieling T, et al. Time-trends in the epidemiology of peptic ulcer bleeding. Scand J Gastroenterol. 2005;40:914–20.
Blower AL, Brooks A, Fenn GC, Hill A, Pearce MY, Morant S, et al. Emergency admissions for upper gastrointestinal disease and their relation to NSAID use. Aliment Pharmacol Ther. 1997;11:283–91.
Brooks TW, Creekmore FM, Young DC, Asche CV, Oberg B, Samuelson WM. Rates of hospitalizations and emergency department visits in patients with asthma and chronic obstructive pulmonary disease taking beta-blockers. Pharmacotherapy. 2007;27:684–90.
Hansson L, Lindholm LH, Niskanen L, Lanke J, Hedner T, Niklason A, et al. Effect of angiotensin-converting-enzyme inhibition compared with conventional therapy on cardiovascular morbidity and mortality in hypertension: the Captopril Prevention Project (CAPPP) randomised trial. Lancet. 1999;353:611–6.
Garg R, Yusuf S. Overview of randomized trials of angiotensin-converting enzyme inhibitors on mortality and morbidity in patients with heart failure. Collaborative Group on ACE Inhibitor Trials. JAMA. 1995;273:1450–6.
Malatjalian DA, Ross JB, Williams CN, Colwell SJ, Eastwood BJ. Methotrexate hepatotoxicity in psoriatics: report of 104 patients from Nova Scotia, with analysis of risks from obesity, diabetes and alcohol consumption during long term follow-up. Can J Gastroenterol. 1996;10:369–75.
Haustein UF, Rytter M. Methotrexate in psoriasis: 26 years’ experience with low-dose long-term treatment. J Eur Acad Dermatol Venereol. 2000;14:382–8.
Bologna C, Viu P, Picot MC, Jorgensen C, Sany J. Long-term follow-up of 453 rheumatoid arthritis patients treated with methotrexate: an open, retrospective, observational study. Br J Rheumatol. 1997;36:535–40.
Choi HK, Hernan MA, Seeger JD, Robins JM, Wolfe F. Methotrexate and mortality in patients with rheumatoid arthritis: a prospective study. Lancet. 2002;359:1173–7.
Berman K, Tandra S, Forssell K, Vuppalanch R, Burton JR, Nguyen J, et al. Incidence and predictors of 30-day readmission among patients hospitalized for advanced liver disease. Clin Gastroenterol Hepatol. 2011;9:254–9.
Lim AY, Gaffney K, Scott DG. Methotrexate-induced pancytopenia: serious and under-reported? Our experience of 25 cases in 5 years. Rheumatology. 1051;44:1051–5.
Schumann C, Lenz G, Berghöfer A, Müller-Oerlinghausen B. Non-adherence with long-term prophylaxis: a 6-year naturalistic follow-up study of affectively ill patients. Psychiatry Res. 1999;89:247–57.
Rosa AR, Marco M, Fachel JMG, Kapczinski F, Stein AT, Barros HMT. Correlation between drug treatment adherence and lithium treatment attitudes and knowledge by bipolar patients. Progress Neuropsychopharmacol Biol Psychiatry. 2007;31:217–24.
Angst J, Angst F, Gerber-Werder R, Gamma A. Suicide in 406 mood-disorder patients with and without long-term medication: a 40 to 44 years’ follow-up. Arch Suicide Res. 2005;9:279–300.
Thorne SA, Barnes I, Cullinan P, Somerville J. Amiodarone-associated thyroid dysfunction: risk factors in adults with congenital heart disease. Circulation. 1999;100:149–54.
Osman F, Gammage MD, Sheppard MC, Franklyn JA. Cardiac dysrhythmias and thyroid dysfunction—the hidden menace? J Clin Endocrinol Metab. 2002;87:963.
Yiu K-H, Jim M-H, Siu C-W, Lee C-H, Yuen M, Mok M, et al. Amiodarone-induced thyrotoxicosis is a predictor of adverse cardiovascular outcome. J Clin Endocrinol Metab. 2009;94:109–14.
Houghton SG, Farley DR, Brennan MD, van Heerden JA, Thompson GB, Grant CS. Surgical management of amiodarone-associated thyrotoxicosis: Mayo Clinic experience. World J Surg. 2004;28:1083–7.
Euroqol Group. Measuring self-reported population health—an international perspective based on EQ-5D. 2008. http://www.euroqol.org/fileadmin/user_upload/Documenten/PDF/Books/Measuring_Self-Reported_Population_Health_An_International_Perspective_based_on_EQ-5D.pdf. Accessed 1 Oct 2012
British Thoracic Society. 2008 British guideline on the management of asthma. Thorax. 2008;63:iv1–121.
Burstrom K, Johannesson M, Diderichsen F. Swedish population health-related quality of life results using the EQ-5D. Qual Life Res. 2001;10:621–35.
Smith A. Preventable drug related morbidity (PDRM) associated with patients who have been prescribed an angiotensin-converting enzyme inhibitor (ACEI) who have not had a recorded check of their renal function and electrolytes in the previous 15 months. Manchester: University of Manchester, School of Pharmacy and Pharmaceutical Science; 2006.
Spiraki C, Kaitelidou D, Papakonstantinou V, Prezerakos P, Maniadakis N. Health-related quality of life measurement in patients admitted with coronary heart disease and heart failure to a cardiology department of a secondary urban hospital in Greece. Hellenic J Cardiol. 2008;49:241–7.
Department of Health. NHS reference costs (2008–2009). London: Department of Health; 2009.
Lee AJ, Morgan CL, Conway P, Currie CJ. Characterisation and comparison of health-related quality of life for patients with renal failure. Curr Med Res Opin. 2005;21:1777–83.
Lindgren P, Kahan T, Poulter N, Buxton M, Svarvar P, Dahlof B, et al. Utility loss and indirect costs following cardiovascular events in hypertensive patients: the ASCOT health economic substudy. Eur J Health Econ. 2007;8:25–30.
Ahlstrom A, Tallgren M, Peltonen S, Rasanen P, Pettila V. Survival and quality of life of patients requiring acute renal replacement therapy. Intensive Care Med. 2005;31:1222–8.
Revicki D, Willian MK, Saurat JH, Papp KA, Ortonne JP, Sexton C, et al. Impact of adalimumab treatment on health-related quality of life and other patient-reported outcomes: results from a 16-week randomized controlled trial in patients with moderate to severe plaque psoriasis. Br J Dermatol. 2008;158:549–57.
Hood A. Trust guideline for use of oral methotrexate, shared care guideline for adults. Hertfordshire: East and North Hertfordshire NHS Trust; 2007.
McLernon DJ, Dillon J, Donnan PT. Health-state utilities in liver disease: a systematic review. Med Decis Making. 2008;28:582–92.
Buxton M, Caine N, Chase D, Connelly D, Grace A, Jackson C, et al. A review of the evidence on the effects and costs of implantable cardioverter defibrillator therapy in different patient groups, and modelling of cost-effectiveness and cost-utility for these groups in a UK context. Health Technol Assess. 2006;10:1–132.
Sullivan PW, Ghushchyan V. Mapping the EQ-5D Index from the SF-12: US general population preferences in a nationally representative sample. Med Decis Making. 2006;26:401–9.
Nolan JP, Tarsa NJ, DiBenedetto G. Case-finding for unsuspected thyroid disease: costs and health benefits. Am J Clin Pathol. 1985;83:346–55.
Esnaola NF, Cantor SB, Sherman SI, Lee JE, Evans DB. Optimal treatment strategy in patients with papillary thyroid cancer: a decision analysis. Surgery. 2001;130:921–30.
We would like to thank the referees for the time they spent reviewing our draft report, and for comments that have helped to improve the final version; the members of the Health Economics Study Group for comments on a submitted paper of this report; Dr Ed Wilson, University of East Anglia, for detailed comments on an earlier draft; and Richard Morriss (Professor of Psychiatry and Community Mental Health, Faculty of Medicine and Health Sciences, University of Nottingham) and Jayne Franklyn (Professor of Medicine and Head of School of Clinical and Experimental Medicine, University of Birmingham) for their clinical input.
Role of the funding source
Funding: Patient Safety Research Program of the UK Department of Health.
The sponsor of the study had no role in study design, data collection, data analysis, data interpretation or writing of the manuscript. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication.
Aziz Sheikh is supported by The Commonwealth Fund, a private independent foundation based in New York City, NY, USA. The views presented here are those of the author and not necessarily those of The Commonwealth Fund, its directors, officers or staff.
This study is registered with Current Controlled Trials: ISRCTN21785299.
Conflicts of interest
The authors (Rachel A. Elliott, Koen Putman, Matthew Franklin, Nick Verhaeghe, Lieven Annemans, Martin Eden, Jasdeep Hayre, Aziz Sheikh, Sarah Rodgers and Anthony J. Avery) declare that they have no competing interests.
Rachel A. Elliott designed and led the economic analysis, including all error models, intervention costs and composite model, led drafting of the manuscript and was on the Trial Management Group.
Koen Putman designed the NSAIDs and β-blockers model, contributed to all other models, built the composite model and was involved in the drafting of the manuscript.
Matthew Franklin designed the lithium model and was involved in the drafting of the manuscript.
Nick Verhaeghe designed the methotrexate and ACEI models and was involved in the drafting of the manuscript.
Lieven Annemans contributed to the design of the composite model and was involved in the drafting of the manuscript.
Martin Eden contributed to intervention cost analysis, CHEERS criteria and was involved in the drafting of the manuscript.
Jasdeep Hayre designed the amiodarone model and was involved in the drafting of the manuscript.
Sarah Rodgers was the trial coordinator from the start of the trial to June 2009 and was involved in the drafting of the manuscript.
Aziz Sheikh contributed to the design and execution of the PINCER trial and was involved in the drafting of the manuscript.
Anthony J. Avery was the principal investigator, had overall responsibility for the day-to-day management of the trial and for the conduct of the trial in the area around Nottingham, and was involved in the drafting of the manuscript.
Rachel A. Elliott will act as overall guarantor.
On behalf of the PINCER Team.
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Elliott, R.A., Putman, K.D., Franklin, M. et al. Cost Effectiveness of a Pharmacist-Led Information Technology Intervention for Reducing Rates of Clinically Important Errors in Medicines Management in General Practices (PINCER). PharmacoEconomics 32, 573–590 (2014). https://doi.org/10.1007/s40273-014-0148-8
- Medication Error
- ACEI Model
- Simple Feedback
- Reduce Medication Error