Age and sex patterns of drug prescribing in a defined American population

Mayo Clinic Proceedings

Volumn 88, Issue 7, 2013, Pages 697-707

  Zhong, Wenjun ^a   Maradit Kremers, Hilal ^a   St Sauver, Jennifer L ^a   Yawn, Barbara P ^a,b   Ebbert, Jon O ^a   Roger, Véronique L ^a   Jacobson, Debra J ^a   McGree, Michaela E ^a   Brue, Scott M ^a   Rocca, Walter A ^a  

^a MAYO CLINIC   (United States)

^b OLMSTED MEDICAL CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANTIASTHMATIC AGENT; ANTIDEPRESSANT AGENT; ANTILIPEMIC AGENT; BETA LACTAM ANTIBIOTIC; CARDIOVASCULAR AGENT; NARCOTIC ANALGESIC AGENT; PENICILLIN DERIVATIVE; PRESCRIPTION DRUG; TOXOID; VACCINE;

ADOLESCENT; ADULT; AGE; AGED; CHILD; CONFERENCE PAPER; CONTROLLED STUDY; DRUG CLASSIFICATION; DRUG UTILIZATION; FEMALE; GENDER; HUMAN; INFANT; MAJOR CLINICAL STUDY; MALE; MIDDLE AGED; POLYPHARMACY; POPULATION RESEARCH; PRESCRIPTION; UNITED STATES; YOUNG ADULT;

EID: 84880219377     PISSN: 00256196     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.mayocp.2013.04.021     Document Type: Conference Paper

References (51)

1. Gu Q, Dillon CF, Burt VL. Prescription drug use continues to increase: U.S. prescription drug data for 2007-2008. NCHS Data Brief. 2010;42:1-8.
2. National Center for Health Statistics. Health, United States, 2011: with special feature on socioeconomic status and health. http://www.cdc.gov/nchs/ data/hus/hus11.pdf. Accessed April 12, 2013.
3. Centers for Disease Control and Prevention (CDC). CDC grand rounds: prescription drug overdoses: a U.S. epidemic. MMWR Morb Mortal Wkly Rep. 2012;61(1):10-13.
4. Centers for Disease Control and Prevention (CDC). Unintentional drug poisoning in the United States. http://www.cdc. gov/HomeandRecreationalSafety/ pdf/poison-issue-brief.pdf. Published July 2010. Accessed April 12, 2013.
5. Lucado J, Paez K, Elixhauser A. Medication-related adverse outcomes in U.S. hospitals and emergency departments, 2008. HCUP Statistical Brief #109. http://www.hcup-us.ahrq.gov/reports/statbriefs/sb109.pdf. Published April 2011. Accessed May 23, 2013.
6. Cossman RE, Cossman JS, James WL, et al. Correlating pharmaceutical data with a national health survey as a proxy for estimating rural population health. Popul Health Metr. 2010; 8:25.
7. Cossman RE, Cossman JS, James WL, et al. Evaluating heart disease prescriptions-filled as a proxy for heart disease prevalence rates. J Health Hum Serv Adm. 2008;30(4):503-528.
8. Zhang Y, Baicker K, Newhouse JP. Geographic variation in Medicare drug spending. N Engl J Med. 2010;363(5):405-409.
9. Wennberg J, Cooper M. The Dartmouth atlas of health care in the US; 1999. http://www.dartmouthatlas.org/downloads/atlases/99Atlas.pdf. Accessed May 23, 2013.
10. Wennberg J, Wennberg D. Practice variations and the use of prescription drugs: Dartmouth atlas of health care in Michigan 2000. http://www.bcbsm.com/ content/dam/public/Consumer/Documents/about-us/dartmouth-atlas.pdf. Accessed May 23, 2013.
11. Jorgensen T, Johansson S, Kennerfalk A, Wallander MA, Svardsudd K. Prescription drug use, diagnoses, and healthcare utilization among the elderly. Ann Pharmacother. 2001;35(9): 1004-1009.
12. Fernandez-Liz E, Modamio P, Catalan A, Lastra CF, Rodriguez T, Marino EL. Identifying how age and gender influence prescription drug use in a primary health care environment in Catalonia, Spain. Br J Clin Pharmacol. 2008;65(3):407-417.
13. Morgan S, Raymond C, Mooney D, Martin D, eds. The Canadian Rx Atlas. 2nd ed. Vancouver: Centre for Health Services and Policy Research, University of British Columbia; 2008.
14. Sommer A. Getting What We Deserve: Health and Medical Care in America. Baltimore, MD: Johns Hopkins University Press; 2009.
15. Baum C, Kennedy DL, Forbes MB, Jones JK. Drug use in the United States in 1981. JAMA. 1984;251(10):1293-1297.
16. Baum C, Kennedy DL, Forbes MB, Jones JK. Drug use and expenditures in 1982. JAMA. 1985;253(3):382-386.
17. Baum C, Kennedy DL, Knapp DE, Juergens JP, Faich GA. Prescription drug use in 1984 and changes over time. Med Care. 1988;26(2):105-114.
18. Kaufman DW, Kelly JP, Rosenberg L, Anderson TE, Mitchell AA. Recent patterns of medication use in the ambulatory adult population of the United States: the Slone survey. JAMA. 2002; 287(3):337-344.
19. Kotzan L, Carroll NV, Kotzan JA. Influence of age, sex, and race on prescription drug use among Georgia Medicaid recipients. Am J Hosp Pharm. 1989;46(2):287-290.
20. LaVange LM, Silverman HA. Outpatient prescription drug utilization and expenditure patterns of noninstitutionalized aged Medicare beneficiaries. Natl Med Care Util Expend Surv B. 1987;12:1-43.
21. Roe CM, McNamara AM, Motheral BR. Gender- and agerelated prescription drug use patterns. Ann Pharmacother. 2002;36(1):30-39.
22. Roe CM, McNamara AM, Motheral BR. Use of chronic medications among a large, commercially-insured US population. Pharmacoepidemiol Drug Saf. 2002;11(4):301-309.
23. Stuart B, Ahern F, Rabatin V, Johnson A. Patterns of outpatient prescription drug use among Pennsylvania elderly. Health Care Financ Rev. 1991;12(3):61-72.
24. Khandker RK, Simoni-Wastila LJ. Differences in prescription drug utilization and expenditures between Blacks and Whites in the Georgia Medicaid population. Inquiry. 1998; 35(1):78-87.
25. Kennedy J, Tuleu I, Mackay K. Unfilled prescriptions of Medicare beneficiaries: prevalence, reasons, and types of medicines prescribed. J Manag Care Pharm. 2008;14(6):553-560.
26. St Sauver JL, Grossardt BR, Yawn BP, Melton LJ III, Rocca WA. Use of a medical records linkage system to enumerate a dynamic population over time: the Rochester Epidemiology Project. Am J Epidemiol. 2011;173(9):1059-1068.
27. St Sauver JL, Grossardt BR, Leibson CL, Yawn BP, Melton LJ III, Rocca WA. Generalizability of epidemiological findings and public health decisions: an illustration from the Rochester Epidemiology Project. Mayo Clin Proc. 2012;87(2):151-160.
28. Rocca WA, Yawn BP, St Sauver JL, Grossardt BR, Melton LJ III. History of the Rochester Epidemiology Project: half a century of medical records linkage in a US population. Mayo Clin Proc. 2012;87(12):1202-1213.
29. St Sauver JL, Grossardt BR, Yawn BP, et al. Data resource profile: the Rochester Epidemiology Project (REP) medical records-linkage system. Int J Epidemiol. 2012;41(6): 1614-1624.
30. Pathak J, Chute CG. Analyzing categorical information in two publicly available drug terminologies: RxNorm and NDF-RT. J Am Med Inform Assoc. 2010;17(4):432-439.
31. Pathak J, Murphy SP, Willaert BN, et al. Using RxNorm and NDF-RT to classify medication data extracted from electronic health records: experiences from the Rochester Epidemiology Project. AMIA Annu Symp Proc. 2011;2011:1089-1098.
32. Anderson DW, Mantel N. On epidemiologic surveys. Am J Epidemiol. 1983;118(5):613-619.
33. Deming WE. Boundaries of statistical inference. In: Smith H, Johnson NL, eds. New Developments in Survey Sampling. New York, NY: Wiley-Interscience; 1969:652-670.
34. Rocca WA, Cha RH, Waring SC, Kokmen E. Incidence of dementia and Alzheimer's disease: a reanalysis of data from Rochester, Minnesota, 1975-1984. Am J Epidemiol. 1998; 148(1):51-62.
35. Lin SJ, Lambert B, Tan H, Toh S. Frequency estimates from prescription drug datasets (revision of #04-11-066A). Pharmacoepidemiol Drug Saf. 2006;15(7):512-520.
36. Roger VL, Go AS, Lloyd-Jones DM, et al. Heart disease and stroke statistics - 2012 update: a report from the American Heart Association [published correction appears in Circulation. 2012;125(22):e1002]. Circulation. 2012;125(1):e2-e220.
37. Courtenay WH. Constructions of masculinity and their influence on men's well-being: a theory of gender and health. Soc Sci Med. 2000;50(10):1385-1401.
38. Lipton RB, Bigal ME. Migraine: epidemiology, impact, and risk factors for progression. Headache. 2005;45(suppl 1): S3-S13.
39. Smolinski MS, Hamburg MA, Lederberg J, eds. Microbial Threats to Health: Emergence, Detection, and Response. Washington, DC: The National Academies Press; 2003.
40. Anthony M, Lee KY, Bertram CT, et al. Gender and age differences in medications dispensed from a national chain drugstore. J Womens Health (Larchmt). 2008;17(5):735-743.
41. Centers for Disease Control and Prevention (CDC). Current depression among adults - United States, 2006 and 2008. MMWR Morb Mortal Wkly Rep. 2010;59(38):1229-1235.
42. Olfson M, Marcus SC. National patterns in antidepressant medication treatment. Arch Gen Psychiatry. 2009;66(8): 848-856.
43. Mojtabai R. Increase in antidepressant medication in the US adult population between 1990 and 2003. Psychother Psychosom. 2008;77(2):83-92.
44. Mojtabai R, Olfson M. Proportion of antidepressants prescribed without a psychiatric diagnosis is growing. Health Aff (Millwood). 2011;30(8):1434-1442.
45. Parsells Kelly J, Cook SF, KaufmanDW, Anderson T, Rosenberg L, Mitchell AA. Prevalence and characteristics of opioid use in the US adult population. Pain. 2008;138(3):507-513.
46. Wiesenfeld-Hallin Z. Sex differences in pain perception. Gend Med. 2005;2(3):137-145.
47. Berkley KJ. Sex differences in pain. Behav Brain Sci. 1997;20(3): 371-380.
48. Dixon KE, Thorn BE, Ward LC. An evaluation of sex differences in psychological and physiological responses to experimentally-induced pain: a path analytic description. Pain. 2004;112(1-2):188-196.
49. St Sauver JL, Warner DO, Yawn BP, et al. Why patients visit their doctors: assessing the most prevalent conditions in a defined American population. Mayo Clin Proc. 2013;88(1):56-67.
50. Centers for Disease Control and Prevention (CDC). Vital signs: prevalence, treatment, and control of high levels of low-density lipoprotein cholesterol - United States, 1999-2002 and 2005-2008. MMWR Morb Mortal Wkly Rep. 2011;60(4):109-114.
51. Hill SC, Zuvekas SH, Zodet MW. Implications of the accuracy of MEPS prescription drug data for health services research. Inquiry. 2011;48(3):242-259.