Drugs & Aging

, Volume 25, Issue 8, pp 693–706 | Cite as

What Factors Predict Potentially Inappropriate Primary Care Prescribing in Older People?

Analysis of UK Primary Care Patient Record Database
  • Iain M. Carey
  • Stephen De Wilde
  • Tess Harris
  • Christina Victor
  • Nicky Richards
  • Sean R. Hilton
  • Derek G. Cook
Original Research Article



Potentially inappropriate prescribing (PIP) in older people has been identified as a substantial problem, but few large population-based studies have investigated the underlying factors that predict it.


To: (i) examine trends in PIP in UK older primary care patients; and (ii) assess factors associated with PIP.


An analysis of routine, anonymized, computerized patient records of 201 UK general practices providing data to the DIN-LINK database between 1996 and 2005, which included approximately 230 000 registered patients per year aged ≥65 years. The main outcome measures were the number of different drugs prescribed per patient annually and the percentage of patients prescribed a PIP drug (modified 2003 Beers criteria). These were assessed for all drugs, and then for selected sub-classes (analgesics, antidepressants and sedatives/anxiolytics).


Whilst the number of drugs prescribed per patient increased, the percentage of subjects receiving a PIP drug declined from 32.2% in 1996 to 28.3% in 2005, largely due to a fall in co-proxamol (dextropropoxyphene/paracetamol [acetaminophen]) prescribing. In 2005, female gender, being older, more socioeconomically deprived or in a care home were strongly associated with PIP. However, the number of drugs prescribed was strongly associated with these variables and the strongest predictor of PIP; adjusting for number of drugs dramatically reduced the strength of all other associations except female gender with PIP. Factors predicting PIP in drug sub-groups were similarly reduced when adjusted for polypharmacy. However, some age trends remained: in the oldest group (aged ≥85 years), PIP of analgesics was less likely (odds ratio [OR] = 0.70, 95% CI 0.66, 0.75) while PIP of antidepressants was more likely (OR =1.39, 95% CI 1.28, 1.51).


PIP amongst older people in the UK, although declining, remains at a high level. The association of PIP with age, deprivation and care homes is largely explained by the higher overall prescribing rates in these groups. The overall rise in prescribing emphasizes that polypharmacy does not necessarily increase PIP and attempts to reduce PIP by focusing on polypharmacy have not been successful. Reductions in PIP have previously been achieved by introducing national guidelines (e.g. co-proxamol), but might also be achieved by alerting practitioners at the point of prescribing.


Care Home Doxazosin Read Code Potentially Inappropriate Prescribe Outcome Framework 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This study was funded by the Bupa Foundation.

Nicky Richards is a former director of Cegedim Strategic Data, which markets DIN-LINK data to pharmaceutical companies. The other authors have no conflicts of interest that are directly relevant to the content of this article.

This study was approved by the National Health Service Research Ethics Committee for Wandsworth (reference 05/Q0803/162).

Supplementary material

40266_2012_25080693_MOESM1_ESM.pdf (110 kb)
Supplementary material, approximately 113 KB.


  1. 1.
    Goulding MR. Inappropriate medication prescribing for elderly ambulatory care patients. Arch Intern Med 2004; 164(3): 305–12PubMedCrossRefGoogle Scholar
  2. 2.
    Liu GG, Christensen DB. The continuing challenge of inappropriate prescribing in the elderly: an update of the evidence. J Am Pharm Assoc (Wash) 2002; 42(6): 847–57CrossRefGoogle Scholar
  3. 3.
    De Wilde S, Carey IM, Harris T, et al. Trends in potentially inappropriate prescribing amongst older UK primary care patients. Pharmacoepidemiol Drug Saf 2007; 16(6): 658–67PubMedCrossRefGoogle Scholar
  4. 4.
    Fick DM, Cooper JW, Wade WE, et al. Updating the Beers criteria for potentially inappropriate medication use in older adults: results of a US consensus panel of experts. Arch Intern Med 2003; 163(22): 2716–24PubMedCrossRefGoogle Scholar
  5. 5.
    Zhan C, Sangl J, Bierman AS, et al. Potentially inappropriate medication use in the community-dwelling elderly: findings from the 1996 Medical Expenditure Panel Survey. JAMA 2001; 286(22): 2823–9PubMedCrossRefGoogle Scholar
  6. 6.
    van der Hooft CS, Jong GW, Dieleman JP, et al. Inappropriate drug prescribing in older adults: the updated 2002 Beers criteria — a population-based cohort study. Br J Clin Pharmacol 2005; 60(2): 137–44PubMedCrossRefGoogle Scholar
  7. 7.
    Maio V, Yuen EJ, Novielli K, et al. Potentially inappropriate medication prescribing for elderly outpatients in Emilia Romagna, Italy: a population-based cohort study. Drugs Aging 2006; 23(11): 915–24PubMedCrossRefGoogle Scholar
  8. 8.
    Aparasu RR, Mort JR. Prevalence, correlates, and associated outcomes of potentially inappropriate psychotropic use in the community-dwelling elderly. Am J Geriatr Pharmacother 2004; 2(2): 102–11PubMedCrossRefGoogle Scholar
  9. 9.
    Mort JR, Aparasu RR. Prescribing potentially inappropriate psychotropic medications to the ambulatory elderly. Arch Intern Med 2000; 160(18): 2825–31PubMedCrossRefGoogle Scholar
  10. 10.
    Aparasu RR, Mort JR. Inappropriate prescribing for the elderly: Beers criteria-based review. Ann Pharmacother 2000; 34(3): 338–46PubMedCrossRefGoogle Scholar
  11. 11.
    Pugh MJV, Hanlon JT, Zeber JE, et al. Assessing potentially inappropriate prescribing in the elderly veterans population using the HEDIS 2006 quality measure. J Manag Care Pharm 2006; 12: 537–45PubMedGoogle Scholar
  12. 12.
    Fialova D, Topinkova E, Gambassi G, et al. Potentially inappropriate medication use among elderly home care patients in Europe. JAMA 2005; 293(11): 1348–58PubMedCrossRefGoogle Scholar
  13. 13.
    Doran T, Fullwood C, Gravelle H, et al. Pay-for-performance programs in family practices in the United Kingdom. New Engl J Med 2006; 355: 375–84PubMedCrossRefGoogle Scholar
  14. 14.
    Department of Health. The GMS contract. Anex A quality indicators: 2003 [online]. Available from URL: [Accessed 2007 Aug 15]
  15. 15.
    Carey IM, Cook DG, De Wilde S, et al. Developing a large electronic primary care database (Doctors’ Independent Network) for research. Int J Med Inform 2004; 73(5): 443–53PubMedCrossRefGoogle Scholar
  16. 16.
    Carey IM, Cook DG, De Wilde S, et al. Implications of the problem orientated medical record (POMR) for research using electronic GP databases: a comparison of the Doctors Independent Network Database (DIN) and the General Practice Research Database (GPRD). BMC Fam Pract 2003; 4: 14PubMedCrossRefGoogle Scholar
  17. 17.
    De Wilde S, Carey IM, Bremner SA, et al. A comparison of the recording of 30 common childhood conditions in the Doctor’s Independent Network and General Practice Research Databases. Health Stat Q 2004; (22): 21–31Google Scholar
  18. 18.
    ACORN user guide. London: CACI Limited, 2001Google Scholar
  19. 19.
    Office of the Deputy Prime Minister. Indices of deprivation 2004. Summary (revised): 2004 [online]. Available from URL: [Accessed 2007 Aug 17]
  20. 20.
    Armitage P, Berry G, Matthews JNS. Statistical methods in epidemiology. In: Armitage P, Berry G, Matthews JNS, editors. Statistical methods in medical research. 4th ed. Oxford: Blackwell Science, 2002: 648–716CrossRefGoogle Scholar
  21. 21.
    Withdrawal of co-proxamol products and interim updated prescribing information: 2005 [online]. Available from URL: [Accessed 2007 Aug 17]
  22. 22.
    Stuart B, Kamal-Bahl S, Briesacher B, et al. Trends in the prescription of inappropriate drugs for the elderly between 1995 and 1999. Am J Geriatr Pharmacother 2003; 1: 61–74PubMedCrossRefGoogle Scholar
  23. 23.
    Spore DL, Mor V, Larrat P. Inappropriate drug prescriptions for elderly residents of board and care facilities. Am J Public Health 1997; 87: 404–9PubMedCrossRefGoogle Scholar
  24. 24.
    Aparasu RR, Sitzman SJ. Inappropriate prescribing for elderly outpatients. Am J Health Syst Pharm 1999; 56: 433–9PubMedGoogle Scholar
  25. 25.
    Lester H, Sharp DJ, Hobbs FD, et al. The quality and outcomes framework of the GMS contract; a quiet evolution for 2006. Br J Gen Pract 2006; 56: 244–6PubMedGoogle Scholar
  26. 26.
    Piecoro LT, Browning SR, Prince TS, et al. A database analysis of potentially inappropriate drug use in an elderly Medicaid population. Pharmacotherapy 2000; 20(2): 221–8PubMedCrossRefGoogle Scholar
  27. 27.
    McCormick A, Fleming D, Chariten J. Morbidity statistics from general practice: fourth national study 1991–1992: MB5 no. 3. London: HMSO, 1995Google Scholar
  28. 28.
    Williams BR, Nichol MB, Lowe B, et al. Medication use in residential care facilities for the elderly. Ann Pharmacother 1999; 33(2): 149–55PubMedCrossRefGoogle Scholar
  29. 29.
    De Wilde S, Carey IM, Emmas C, et al. Trends in the prevalence of diagnosed atrial fibrillation, its treatment with anticoagulation and predictors of such treatment in UK primary care. Heart 2006; 92(8): 1064–70CrossRefGoogle Scholar
  30. 30.
    De Wilde S, Carey IM, Richards N, et al. Trends in secondary prevention of ischaemic heart disease in the UK 1994–2005: use of individual and combination treatment. Heart 2008; 94: 83–8CrossRefGoogle Scholar
  31. 31.
    Department of Health. National service framework for older people. 2001 May 24 [online]. Available from URL: [Accessed 2008 Jun 12]
  32. 32.
    Salter C, Holland R, Harvey I, et al. “I haven’t even phoned my doctor yet.” The advice giving role of the pharmacist during consultations for medication review with patients aged 80 or more: qualitative discourse analysis. BMJ 2007; 334(7603): 1101. Epub 2007 Apr 20PubMedCrossRefGoogle Scholar
  33. 33.
    Commission on Human Medicines. Withdrawal of co-proxamol. In: Current problems in pharmacovigilance. Vol. 31. 2006 May, page 11 [online]. Available from URL: [Accessed 2008 Jun 12]
  34. 34.
    Simon SR, Smith DH, Feldstein AR, et al. Computerized prescribing alerts and group academic detailing to reduce the use of potentially inappropriate medications in older people. J Am Geriatr Soc 2006; 54: 963–8PubMedCrossRefGoogle Scholar
  35. 35.
    Budnitz DS, Shehab N, Kegler SR, et al. Medication use leading to emergency department visits for adverse drug events in older adults. Ann Intern Med 2007; 147(11): 755–65PubMedGoogle Scholar

Copyright information

© Adis Data Information BV 2008

Authors and Affiliations

  • Iain M. Carey
    • 1
  • Stephen De Wilde
    • 1
  • Tess Harris
    • 1
  • Christina Victor
    • 2
  • Nicky Richards
    • 3
  • Sean R. Hilton
    • 1
  • Derek G. Cook
    • 1
  1. 1.Division of Community Health Sciences, St George’sUniversity of LondonUK
  2. 2.University of ReadingReading, BerkshireUK
  3. 3.Cegedim Strategic Data UK LtdChertsey, SurreyUK

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