Changes in the burden of medications that may impair driving among older adults before and after a motor vehicle crash.

Melissa R Riester, Adam M D'Amico, Marzan A Khan, Nina R Joyce, Melissa R Pfeiffer, Seth A Margolis, Brian R Ott, Allison E Curry, Thomas A Bayer, Andrew R Zullo
Author Information
  1. Melissa R Riester: Department of Epidemiology, Brown University School of Public Health, Providence, Rhode Island, USA. ORCID
  2. Adam M D'Amico: Center for Gerontology and Health Care Research, Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island, USA.
  3. Marzan A Khan: Center for Gerontology and Health Care Research, Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island, USA.
  4. Nina R Joyce: Department of Epidemiology, Brown University School of Public Health, Providence, Rhode Island, USA. ORCID
  5. Melissa R Pfeiffer: Center for Injury Research and Prevention, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
  6. Seth A Margolis: Department of Neuropsychology, Rhode Island Hospital, Providence, Rhode Island, USA.
  7. Brian R Ott: Department of Neurology, Brown University, Providence, Rhode Island, USA. ORCID
  8. Allison E Curry: Center for Injury Research and Prevention, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
  9. Thomas A Bayer: Division of Geriatrics and Palliative Medicine, Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA. ORCID
  10. Andrew R Zullo: Department of Epidemiology, Brown University School of Public Health, Providence, Rhode Island, USA. ORCID

Abstract

BACKGROUND: Medications are one of the most easily modifiable risk factors for motor vehicle crashes (MVCs) among older adults, yet limited information exists on how the use of potentially driver-impairing (PDI) medications changes following an MVC. Therefore, we examined the number and types of PDI medication classes dispensed before and after an MVC.
METHODS: This observational study included Medicare fee-for-service beneficiaries aged ���67���years who were involved in a police-reported MVC in New Jersey as a driver between 2008 and 2017. Analyses were conducted at the "person-crash" level because participants could be involved in more than one MVC. We examined the use of 36 PDI medication classes in the 120���days before and 120���days after MVC. We described the number and prevalence of PDI medication classes in the pre-MVC and post-MVC periods as well as the most common PDI medication classes started and stopped following the MVC.
RESULTS: Among 124,954 person-crashes, the mean (SD) age was 76.0 (6.5) years, 51.3% were female, and 83.9% were non-Hispanic White. The median (Q , Q ) number of PDI medication classes was 2 (1, 4) in both the pre-MVC and post-MVC periods. Overall, 20.3% had a net increase, 15.9% had a net decrease, and 63.8% had no net change in the number of PDI medication classes after MVC. Opioids, antihistamines, and thiazide diuretics were the top PDI medication classes stopped following MVC, at incidences of 6.2%, 2.1%, and 1.7%, respectively. The top medication classes started were opioids (8.3%), skeletal muscle relaxants (2.2%), and benzodiazepines (2.1%).
CONCLUSIONS: A majority of crash-involved older adults were exposed to multiple PDI medications before and after MVC. A greater proportion of person-crashes were associated with an increased rather than decreased number of PDI medications. The reasons why clinicians refrain from stopping PDI medications following an MVC remain to be elucidated.

Keywords

References

  1. Inj Prev. 2014 Apr;20(2):81-7 [PMID: 23873499]
  2. Am J Geriatr Psychiatry. 2011 Dec;19(12):998-1006 [PMID: 22123273]
  3. Accid Anal Prev. 2016 Nov;96:255-270 [PMID: 27569655]
  4. Drug Saf. 2011 Feb 1;34(2):125-56 [PMID: 21247221]
  5. Drugs Real World Outcomes. 2023 Sep;10(3):357-362 [PMID: 37233904]
  6. J Aging Soc Policy. 2022 Dec 4;:1-15 [PMID: 36463560]
  7. J Trauma. 2008 Feb;64(2):304-10 [PMID: 18301191]
  8. Lancet Public Health. 2021 Jun;6(6):e374-e385 [PMID: 33887232]
  9. J Pharm Technol. 2022 Feb;38(1):54-62 [PMID: 35141728]
  10. BMC Geriatr. 2019 Oct 10;19(1):260 [PMID: 31601189]
  11. Pharmaceuticals (Basel). 2023 Mar 29;16(4): [PMID: 37111265]
  12. Inj Prev. 2021 Oct;27(5):472-478 [PMID: 33685949]
  13. Accid Anal Prev. 2017 Dec;109:123-131 [PMID: 29059534]
  14. PLoS One. 2021 Aug 3;16(8):e0255642 [PMID: 34343225]
  15. JAMA Intern Med. 2016 Apr;176(4):473-82 [PMID: 26998708]
  16. Accid Anal Prev. 2014 Nov;72:44-54 [PMID: 25003969]
  17. BMC Geriatr. 2022 Jan 3;22(1):4 [PMID: 34979970]
  18. J Clin Epidemiol. 2021 Jul;135:170-175 [PMID: 33753229]
  19. J Clin Epidemiol. 2011 Jul;64(7):749-59 [PMID: 21208778]
  20. Epidemiology. 1994 Nov;5(6):591-8 [PMID: 7841240]
  21. J Am Geriatr Soc. 2011 Sep;59(9):1575-80 [PMID: 21883110]
  22. Ann Pharmacother. 2014 Apr;48(4):476-82 [PMID: 24473491]
  23. PLoS Med. 2010 Nov 16;7(11):e1000366 [PMID: 21125020]
  24. Am J Epidemiol. 2009 Mar 15;169(6):761-8 [PMID: 19181876]
  25. Inj Epidemiol. 2020 Aug 3;7(1):38 [PMID: 32741358]

Grants

  1. R01AG065722/NIA NIH HHS
  2. R21 AG061632/NIA NIH HHS
  3. R21AG061632/NIA NIH HHS
  4. R01AG077620/NIA NIH HHS
  5. R01AG079295/NIA NIH HHS
  6. R01 AG077620/NIA NIH HHS
  7. R01 AG079295/NIA NIH HHS
  8. R01 AG065722/NIA NIH HHS

MeSH Term

Humans
Aged
Female
United States
Male
Accidents, Traffic
Medicare
Risk Factors
Motor Vehicles
New Jersey
Automobile Driving

Word Cloud

Created with Highcharts 10.0.0PDIMVCmedicationclassesmedicationsnumberolderadultsfollowing23%netonemotorvehicleamonguseexaminedMedicareinvolved120���dayspre-MVCpost-MVCperiodsstartedstoppedperson-crashes69%Q1top2%1%BACKGROUND:MedicationseasilymodifiableriskfactorscrashesMVCsyetlimitedinformationexistspotentiallydriver-impairingchangesThereforetypesdispensedMETHODS:observationalstudyincludedfee-for-servicebeneficiariesaged���67���yearspolice-reportedNewJerseydriver20082017Analysesconducted"person-crash"levelparticipants36describedprevalencewellcommonRESULTS:Among124954meanSDage7605years51female83non-HispanicWhitemedian4Overall20increase15decrease638%changeOpioidsantihistaminesthiazidediureticsincidences7%respectivelyopioids8skeletalmusclerelaxantsbenzodiazepinesCONCLUSIONS:majoritycrash-involvedexposedmultiplegreaterproportionassociatedincreasedratherdecreasedreasonscliniciansrefrainstoppingremainelucidatedChangesburdenmayimpairdrivingcrashpolypharmacyprescriptiondrugstrafficaccidents

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