#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#

Validating a popular outpatient antibiotic database to reliably identify high prescribing physicians for patients 65 years of age and older


Autoři: Kevin L. Schwartz aff001;  Cynthia Chen aff002;  Bradley J. Langford aff001;  Kevin A. Brown aff001;  Nick Daneman aff001;  Jennie Johnstone aff001;  Julie HC Wu aff001;  Valerie Leung aff001;  Gary Garber aff001
Působiště autorů: Public Health Ontario, Toronto, Ontario, Canada aff001;  ICES, Toronto, Ontario, Canada aff002;  Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada aff003;  Unity Health Toronto, Toronto, Ontario, Canada aff004;  Sunnybrook Research Institute, Division of Infectious Diseases, Toronto, Ontario, Canada aff005;  The Institute of Health Policy, Management, and Evaluation, University of Toronto, Ontario, Canada aff006;  Sinai Health System, Toronto, Ontario, Canada aff007;  Ottawa Research Institute, Ottawa, Ontario, Canada aff008
Vyšlo v časopise: PLoS ONE 14(9)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0223097

Souhrn

Objective

Many jurisdictions lack comprehensive population-based antibiotic use data and rely on third party companies, most commonly IQVIA. Our objective was to validate the accuracy of the IQVIA Xponent antibiotic database in identifying high prescribing physicians compared to the reference standard of a highly accurate population-wide database of outpatient antimicrobial dispensing for patients ≥65 years.

Methods

We conducted this study between 1 March 2016 and 28 February 2017 in Ontario, Canada. We evaluated the agreement and correlation between the databases using kappa statistics and Bland-Altman plots. We also assessed performance characteristics for Xponent to accurately identify high prescribing physicians with sensitivity, specificity, positive predictive value (PPV), and negative predictive value.

Results

We included 9,272 physicians. The Xponent database has a specificity of 92.4% (95%CI 92.0%-92.8%) and PPV of 77.2% (95%CI 76.0%-78.4%) for correctly identifying the top 25th percentile of physicians by antibiotic volume. In the sensitivity analysis, 94% of the top 25th percentile physicians in Xponent were within the top 40th percentile in the reference database. The mean number of antibiotic prescriptions per physician were similar with a relative difference of -0.4% and 2.7% for female and male patients, respectively. The error was greater in rural areas with a relative difference of -8.4% and -5.6% per physician for female and male patients, respectively. The weighted kappa for quartile agreement was 0.68 (95%CI 0.67–0.69).

Conclusion

We validated the IQVIA Xponent antibiotic database to identify high prescribing physicians for patients ≥65 years, and identified some important limitations. Collecting accurate population-based antibiotic use data will remain vital to global antimicrobial stewardship efforts.

Klíčová slova:

Antibiotics – Antimicrobials – Outpatients – Physicians – Primary care – Rural areas – Ontario – Canada


Zdroje

1. O'Neill J. Tackling drug-resistant infections globally: final report and recommendations. London: Wellcome Trust & HM Government; 2015. [cited 2017 Nov 14]. Available from: https://amr-review.org/sites/default/files/160518_Final%20paper_with%20cover.pdf

2. Costelloe C, Metcalfe C, Lovering A, Mant D, Hay AD. Effect of antibiotic prescribing in primary care on antimicrobial resistance in individual patients: systematic review and meta-analysis. BMJ. 2010;340: c2096. doi: 10.1136/bmj.c2096 20483949

3. Bell BG, Schellevis F, Stobberingh E, Goossens H, Pringle M. A systematic review and meta-analysis of the effects of antibiotic consumption on antibiotic resistance. BMC Infect Dis. 2014; 14: 13. doi: 10.1186/1471-2334-14-13 24405683

4. Public Health Agency of Canada. Antimicrobial resistance and one health: pan-Canadian framework for action on antimicrobial resistance and antimicrobial use. Can Commun Dis Rep. 2017; 43(11): 217–219. 29770049

5. Sanchez GV, Fleming-Dutra KE, Roberts RM, Hicks LA. Core elements of outpatient antibiotic stewardship. MMWR Recomm Rep 2016;65(No. RR-6): 1–12.

6. World Health Organization. Global action plan on antimicrobial resistance [internet]. Geneva: World Health Organization 2015; 2015 [cited February 7, 2019]. Available online at: https://www.who.int/antimicrobial-resistance/publications/global-action-plan/en/

7. Schwartz KL, Achonu C, Brown KA, Langford B, Daneman N, Johnston J et al. Regional variability in outpatient antibiotic use in Ontario, Canada: a retrospective cross-sectional study. CMAJ Open. 2018; 6: E445–E452. doi: 10.9778/cmajo.20180017 30381321

8. Karlowsky JA, Lagacé-Wiens PR, Low DE, Zhanel GG. Annual macrolide prescription rates and the emergence of macrolide resistance among Streptococcus pneumoniae in Canada from 1995 to 2005. Int J Antimicrob Agents. 2009; 34: 375–379. doi: 10.1016/j.ijantimicag.2009.05.008 19560902

9. Tan C, Graves E, Lu H, Chen A, Li S, Schwartz KL et al. A decade of outpatient antimicrobial use in senior residents of Ontario. CMAJ Open. 2017;5: E878–E885. doi: 10.9778/cmajo.20170100 29273579

10. Fernandez-Lazaro CI, Brown KA, Langford BJ, Daneman N, Garber G, Schwartz KL. Late-career Physicians Prescribe Longer Courses of Antibiotics. Clin Infect Dis. 2019; January 7. doi: 10.1093/cid/ciy1130 [Epub ahead of print]. 30615108

11. Schwartz KL, Wilton AS, Langford BJ, Brown KA, Daneman N, Garber G et al. Comparing prescribing and dispensing databases to study antibiotic use: a validation study of the Electronic Medical Record Administrative data Linked Database (EMRALD). J Antimicrob Chemother. 2019; 74: 2091–2097. doi: 10.1093/jac/dkz033 30805603

12. Lin SJ, Lambert B, Tan H, Toh S. Frequency estimates from prescription drug datasets (revision of #04-11-066A). Pharmacoepidemiol Drug Saf. 2006; 15: 512–520. doi: 10.1002/pds.1149 16136624

13. Hicks LA, Taylor THJ, Hunkler RJ. U.S. Outpatient Antibiotic Prescribing, 2010. N Engl J Med. 2013;368: 1461–1462. doi: 10.1056/NEJMc1212055 23574140

14. Hicks LA, Chien YW, Taylor TH Jr, Haber M, Klugman KP. Outpatient antibiotic prescribing and nonsusceptible Streptococcus pneumoniae in the United States, 1996–2003. Clin Infect Dis. 2011; 53: 631–639. doi: 10.1093/cid/cir443 21890767

15. Hicks LA, Bartoces MG, Roberts RM, Suda KJ, Hunkler RJ, Taylor TH Jr, et al. US outpatient antibiotic prescribing variation according to geography, patient population, and provider specialty in 2011. Clin Infect Dis. 2015; 60: 1308–1316. doi: 10.1093/cid/civ076 25747410

16. Hsia Y, Sharland M, Jackson C, Wong ICK, Magrini N, Bielicki JA. Consumption of oral antibiotic formulations for young children according to the WHO Access, Watch, Reserve (AWaRe) antibiotic groups: an analysis of sales data from 70 middle-income and high-income countries. Lancet Infect Dis. 2019; 19: 67–75. doi: 10.1016/S1473-3099(18)30547-4 30522834

17. Kabbani S, Palms D, Bartoces M, Stone N, Hicks LA. Outpatient Antibiotic Prescribing for Older Adults in the United States: 2011 to 2014. J Am Geriatr Soc. 2018; 66: 1998–2002. doi: 10.1111/jgs.15518 30221746

18. Kourlaba G, Kourkouni E, Spyridis N, Gerber JS, Kopsidas J, Mougkou K, et al. Antibiotic prescribing and expenditures in outpatient paediatrics in Greece, 2010–13. J Antimicrob Chemother, 2015; 70: 2405–2408. doi: 10.1093/jac/dkv091 25881618

19. Klein EY, Makowsky M, Orlando M, Hatna E, Braykov NP, Laxminarayan R. Influence of provider and urgent care density across different socioeconomic strata on outpatient antibiotic prescribing in the USA. J Antimicrob Chemother. 2015 70: 1580–1587. doi: 10.1093/jac/dku563 25604743

20. Dantes R, Mu Y, Hicks LA, Cohen J, Bamberg W, Beldavs ZG, et al. Association between outpatient antibiotic prescribing practices and community-associated Clostridium difficile Infection. Open Forum Infect Dis. 2015; 2: ofv113. doi: 10.1093/ofid/ofv113 26509182

21. Van Boeckel TP, Gandra S, Ashok A, Caudron Q, Grenfell BT, Levin SA, et al. Global antibiotic consumption 2000 to 2010: an analysis of national pharmaceutical sales data. Lancet Infect Dis. 2014;14: 742–750. doi: 10.1016/S1473-3099(14)70780-7 25022435

22. Adam HJ, Hoban DJ, Gin AS, Zhanel GG. Association between fluoroquinolone usage and a dramatic rise in ciprofloxacin-resistant Streptococcus pneumoniae in Canada, 1997–2006. Int J Antimicrob Agents. 2009;34: 82–85. doi: 10.1016/j.ijantimicag.2009.02.002 19342204

23. Goossens H, Ferech M, Coenen S, Stephens P, European Surveillance of Antimicrobial Consumption Project Group. Comparison of outpatient systemic antibacterial use in 2004 in the United States and 27 European countries. Clin Infect Dis. 2007; 44: 1091–1095. doi: 10.1086/512810 17366456

24. Public Health Agency of Canada. Canadian antimicrobial resistance surveillance system 2017 report. Ottawa: Her Majesty the Queen in Right of Canada, as represented by the Minister of Health, 2018; 2017. [cited 2017 Nov 14]. Available from: https://www.canada.ca/en/public-health/services/publications/drugs-health-products/canadian-antimicrobial-resistance-surveillance-system-2017-report-executive-summary.html

25. Levy A, O'Brien B, Sellors C, Grootendorst P, Willison D. Coding accuracy of administrative drug claims in the Ontario Drug Benefit database. Can J Clin Pharmacol. 2003; 10: 67–71. 12879144

26. Government of Ontario. The Ontario Drug Benefit Program [internet]. 2019 [cited 2019 April 23]. Available from: https://www.ontario.ca/page/check-medication-coverage/

27. Boardman C, inventor; IMS Health Incorporated, assignee. System and method for estimating prdouct distribution using a product specific universe. US patent 7,174,304. 2007.

28. Landis JR, Koch GG. An application of hierarchical kappa-type statistics in the assessment of majority agreement among multiple observers. Biometrics. 1977; 33: 363–374. 884196

29. Bland JM, Altman D. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986; 327: 307–310.

30. Benchimol EI, Manuel DG, To T, Griffiths AM, Rabeneck L, Guttmann A. Development and use of reporting guidelines for assessing the quality of validation studies of health administrative data. J Clin Epidemiol. 2011; 64: 821–829. doi: 10.1016/j.jclinepi.2010.10.006 21194889

31. Tan C, Ritchie M, Alldred J, Daneman N. Validating hospital antibiotic purchasing data as a metric of inpatient antibiotic use. J Antimicrob Chemother. 2015;71: 547–553. doi: 10.1093/jac/dkv373 26546668

32. Dalton B, Svenson L, Bresee L, Sabuda D, Missaghi B, Larios OE, et al. External validation of estimates of antibacterial dispensing in the IMS Brogan Xponent® database in a Canadian province. Poster session presented at: IDWeek 2013; 2013 October 2–6; San Fransisco, CA. Available from: https://idsa.confex.com/idsa/2013/webprogram/Paper41244.html

33. Hong M, Dutil L, Bhatia T, Marra F, Patrick DM. Assessing antimicrobial consumption using two different methodologies in British Columbia. Can J Infect Dis Med Microbiol. 2007; 18: 35 Abstract A3.

34. Schneeweiss S, Seeger JD, Maclure M, Wang PS, Avorn J, Glynn RJ. Performance of comorbidity scores to control for confounding in epidemiologic studies using claims data. Am J Epidemiol. 2001; 154: 854–864. doi: 10.1093/aje/154.9.854 11682368


Článek vyšel v časopise

PLOS One


2019 Číslo 9
Nejčtenější tento týden
Nejčtenější v tomto čísle
Kurzy

Zvyšte si kvalifikaci online z pohodlí domova

KOST
Koncepce osteologické péče pro gynekology a praktické lékaře
nový kurz
Autoři: MUDr. František Šenk

Sekvenční léčba schizofrenie
Autoři: MUDr. Jana Hořínková

Hypertenze a hypercholesterolémie – synergický efekt léčby
Autoři: prof. MUDr. Hana Rosolová, DrSc.

Svět praktické medicíny 5/2023 (znalostní test z časopisu)

Imunopatologie? … a co my s tím???
Autoři: doc. MUDr. Helena Lahoda Brodská, Ph.D.

Všechny kurzy
Kurzy Podcasty Doporučená témata Časopisy
Přihlášení
Zapomenuté heslo

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

Přihlášení

Nemáte účet?  Registrujte se

#ADS_BOTTOM_SCRIPTS#