RESEARCH NOTES
Characteristics of online pharmacy users in a nationally representative sample Joshua Brown and Chenghui Li
Abstract Objective: To identify health care–related factors associated with online pharmacy use by considering patients’ prescription drug insurance coverage, number of prescriptions, health care expenditures, types of medications purchased, and health status. Methods: Data were obtained from the Agency for Healthcare Research and Quality’s 2002–2010 Medical Expenditure Panel Survey. Online pharmacy users were compared with nonusers across study variables in unadjusted and adjusted comparisons using logistic regression. Survey weights were applied to generate nationally representative estimates. Results: A total of 443 online pharmacy users were identified, representing an average of 1.5 million individuals per year. Online users were found to be older and to have more prescriptions compared with nonusers, as well as to have higher health care expenditures and higher Charlson comorbidity index scores. Online users were also more likely to be privately insured, white, and married, and to be more educated. In logistic regression models, higher prescription expenditures (odds ratio [OR] 1.17 [1.05–1.32]), higher number of prescriptions (OR 5.13 [1.4–19]), medium to high income (OR 1.82 (1.3–2.5)], and use of erectile dysfunction drugs (OR 2.09 [1.06–4.10]) were associated with greater odds of online pharmacy use. Black race (OR 0.47 [0.3–0.72]), Medicaid insurance coverage (OR 0.23 [0.1–0.5]), and use of narcotic medications (OR 0.72 [0.53–0.97]) were associated with decreased odds of online pharmacy use. Conclusion: This study showed that age, race, income level, insurance coverage, high health care expenditures, and higher number of prescriptions are predictors for online pharmacy use. Keywords: Internet, laws and regulations, drug supply, drug distribution, pharmaceutical services, pharmacy classifications J Am Pharm Assoc. 2014;54:289–294. doi: 10.1331/JAPhA.2014.13169
Journal of the American Pharmacists Association
T
he National Association of Boards of Pharmacy (NABP) has created two categories for online pharmacies: “recommended Internet pharmacies” and “not recommended sites.”1 To achieve accreditation through NABP’s Verified Internet Pharmacy Practice Sites (VIPPS) program, pharmacies are subjected to a review of their policies and procedures and an on-site inspection.1 Most of the online pharmacies recommended by NABP are Internet sites operated by large retail pharmacy chains or as a service through a health care insurance plan. Nonrecommended sites include those that are noncompliant with NABP practice standards and state and/or federal laws. Through an online site review, NABP identified 10,065 online drug outlets, 96.71% of which it does not recommend. Only 73 of all the outlets reviewed achieved VIPPS accreditation, with the remainder listed as “potentially legitimate.”2 The U.S. Food and Drug Administration (FDA) also provides educational materials about online pharmacies. FDA’s BeSafeRx program informs professionals and patients about the dangers and signs of rogue Internet pharmacies.3 FDA and the World Health Organization have referred to the purchasing of prescription medications over the Internet as a “serious public health risk” and a “global public health crisis.”3,4 Their concern is rooted in findings that more than 50% of medications purchased over the Internet are counterfeit and substandard.5,6 A May 2012 FDA survey found that 25% of adults participating in e-commerce reported purchasing prescription drugs online, with 17% of those individuals making such purchases using Internet pharmacies not associated with a health plan.7 Purchasing medications online may also bypass interaction with physicians and pharmacists, disrupting the continuum of care for prescription medications.5 As Received August 14, 2013, and in revised form November 18, 2013. Accepted for publication December 8, 2013. Joshua Brown is a fourth-year student pharmacist and senior MS student in Pharmaceutical Evaluation and Policy, and Chenghui Li, PhD, is Associate Professor, Division of Pharmaceutical Evaluation and Policy, College of Pharmacy, University of Arkansas for Medical Sciences, Little Rock. Correspondence: Chenghui Li, PhD, 4301 West Markham Street, Slot #522, Little Rock, AR 72205. Fax: 501-686-5156. E-mail: [email protected] Disclosure: The authors declare no conflicts of interest or financial interests in any product or service mentioned in this article, including grants, employment, gifts, stock holdings, or honoraria. Chenghui Li is a consultant to eMaxHealth Systems on unrelated projects. Previous presentation: International Society for Pharmacoeconomics and Outcomes Research International Meeting, New Orleans, LA, May 18, 2013.
j apha.org
MAY/JU N 2014 | 54:3 |
JAPhA 289
RESEARCH NOTES
a result, the online purchase of medications is associated with an increased potential for adverse events and substandard care.5,6 Previous research in online pharmacy use has described online drug-purchasing behaviors and demographics but has not explored the health-related characteristics of individuals using these sites or the medications being purchased in this manner in a nationally representative population.8–10
Objectives This study explores the characteristics of patients using online pharmacies and the types of medications being purchased in a nationally representative sample. Online pharmacy users are compared with nonusers by demographic information, classes of medications, insurance coverage, health care expenditures, and medical conditions.
Methods This study used publicly available data from the Agency for Healthcare Research and Quality’s 2002–2010 Medical Expenditure Panel Survey (MEPS)—a nationally representative survey of civilian, noninstitutionalized individuals. Public-use data are deidentified and collected for research purposes, and are therefore exempt from institutional review board review. MEPS uses an overlapping panel design, with a new cohort (“panel”) added each year and participating in the survey for up to 2 years. This study included individuals who participated in the survey for 2 years and obtained at least one prescription medication. Variables were selected from three MEPS data files: full-year consolidated, medical conditions, and prescribed medicines. Online pharmacy users were defined as those who reported purchasing a prescription through an online pharmacy by the “pharmacy type” variable for each medication. Individual characteristics examined included age (0–17 years, 18–64 years, 65 years or older); gender; race/ethnicity; marital status (married or not); education (less than high school, high school or equivalent, some college or more); family income (less than 200% federal poverty limit or 200% or more); prescription insurance coverage; health care use and expenditures; and comorbidities. Prescription insurance coverage was ascertained if a person reported having Medicaid, Medicare Part D (2006 onward), or private insurance with prescription coverage. Those failing to report one of these three classifications were determined to not have prescription drug coverage. Health care expenditures included both prescription and nondrug expenditures (emergency department visits, inpatient visits, office-based visits, and outpatient visits). Medications were classified into broad therapeutic categories using Multum Lexicon 290 JAPhA | 5 4 :3 | M AY /JUN 2 0 1 4
ja p h a.org
classification (Cerner Multum, Denver, CO). The total number of prescriptions was categorized as 1, 2–4, 5–9, or 10+. Overall comorbidity burden was assessed using the Charlson comorbidity index (CCI) calculated with the algorithm developed by D’hoore et al.8 Comparisons between online pharmacy users and nonusers were made using chi-square and t tests where appropriate. Logistic regression was used to assess the association of individual characteristics with online pharmacy use. Subgroup analyses were conducted of the older group (65 or over) and younger adults (18–64), with the latter broken down into three smaller categories: 18–34 years, 35–54 years, and 55–64 years. Statistical significance was determined at P
Characteristics of online pharmacy users in a nationally representative sample Joshua Brown and Chenghui Li
Abstract Objective: To identify health care–related factors associated with online pharmacy use by considering patients’ prescription drug insurance coverage, number of prescriptions, health care expenditures, types of medications purchased, and health status. Methods: Data were obtained from the Agency for Healthcare Research and Quality’s 2002–2010 Medical Expenditure Panel Survey. Online pharmacy users were compared with nonusers across study variables in unadjusted and adjusted comparisons using logistic regression. Survey weights were applied to generate nationally representative estimates. Results: A total of 443 online pharmacy users were identified, representing an average of 1.5 million individuals per year. Online users were found to be older and to have more prescriptions compared with nonusers, as well as to have higher health care expenditures and higher Charlson comorbidity index scores. Online users were also more likely to be privately insured, white, and married, and to be more educated. In logistic regression models, higher prescription expenditures (odds ratio [OR] 1.17 [1.05–1.32]), higher number of prescriptions (OR 5.13 [1.4–19]), medium to high income (OR 1.82 (1.3–2.5)], and use of erectile dysfunction drugs (OR 2.09 [1.06–4.10]) were associated with greater odds of online pharmacy use. Black race (OR 0.47 [0.3–0.72]), Medicaid insurance coverage (OR 0.23 [0.1–0.5]), and use of narcotic medications (OR 0.72 [0.53–0.97]) were associated with decreased odds of online pharmacy use. Conclusion: This study showed that age, race, income level, insurance coverage, high health care expenditures, and higher number of prescriptions are predictors for online pharmacy use. Keywords: Internet, laws and regulations, drug supply, drug distribution, pharmaceutical services, pharmacy classifications J Am Pharm Assoc. 2014;54:289–294. doi: 10.1331/JAPhA.2014.13169
Journal of the American Pharmacists Association
T
he National Association of Boards of Pharmacy (NABP) has created two categories for online pharmacies: “recommended Internet pharmacies” and “not recommended sites.”1 To achieve accreditation through NABP’s Verified Internet Pharmacy Practice Sites (VIPPS) program, pharmacies are subjected to a review of their policies and procedures and an on-site inspection.1 Most of the online pharmacies recommended by NABP are Internet sites operated by large retail pharmacy chains or as a service through a health care insurance plan. Nonrecommended sites include those that are noncompliant with NABP practice standards and state and/or federal laws. Through an online site review, NABP identified 10,065 online drug outlets, 96.71% of which it does not recommend. Only 73 of all the outlets reviewed achieved VIPPS accreditation, with the remainder listed as “potentially legitimate.”2 The U.S. Food and Drug Administration (FDA) also provides educational materials about online pharmacies. FDA’s BeSafeRx program informs professionals and patients about the dangers and signs of rogue Internet pharmacies.3 FDA and the World Health Organization have referred to the purchasing of prescription medications over the Internet as a “serious public health risk” and a “global public health crisis.”3,4 Their concern is rooted in findings that more than 50% of medications purchased over the Internet are counterfeit and substandard.5,6 A May 2012 FDA survey found that 25% of adults participating in e-commerce reported purchasing prescription drugs online, with 17% of those individuals making such purchases using Internet pharmacies not associated with a health plan.7 Purchasing medications online may also bypass interaction with physicians and pharmacists, disrupting the continuum of care for prescription medications.5 As Received August 14, 2013, and in revised form November 18, 2013. Accepted for publication December 8, 2013. Joshua Brown is a fourth-year student pharmacist and senior MS student in Pharmaceutical Evaluation and Policy, and Chenghui Li, PhD, is Associate Professor, Division of Pharmaceutical Evaluation and Policy, College of Pharmacy, University of Arkansas for Medical Sciences, Little Rock. Correspondence: Chenghui Li, PhD, 4301 West Markham Street, Slot #522, Little Rock, AR 72205. Fax: 501-686-5156. E-mail: [email protected] Disclosure: The authors declare no conflicts of interest or financial interests in any product or service mentioned in this article, including grants, employment, gifts, stock holdings, or honoraria. Chenghui Li is a consultant to eMaxHealth Systems on unrelated projects. Previous presentation: International Society for Pharmacoeconomics and Outcomes Research International Meeting, New Orleans, LA, May 18, 2013.
j apha.org
MAY/JU N 2014 | 54:3 |
JAPhA 289
RESEARCH NOTES
a result, the online purchase of medications is associated with an increased potential for adverse events and substandard care.5,6 Previous research in online pharmacy use has described online drug-purchasing behaviors and demographics but has not explored the health-related characteristics of individuals using these sites or the medications being purchased in this manner in a nationally representative population.8–10
Objectives This study explores the characteristics of patients using online pharmacies and the types of medications being purchased in a nationally representative sample. Online pharmacy users are compared with nonusers by demographic information, classes of medications, insurance coverage, health care expenditures, and medical conditions.
Methods This study used publicly available data from the Agency for Healthcare Research and Quality’s 2002–2010 Medical Expenditure Panel Survey (MEPS)—a nationally representative survey of civilian, noninstitutionalized individuals. Public-use data are deidentified and collected for research purposes, and are therefore exempt from institutional review board review. MEPS uses an overlapping panel design, with a new cohort (“panel”) added each year and participating in the survey for up to 2 years. This study included individuals who participated in the survey for 2 years and obtained at least one prescription medication. Variables were selected from three MEPS data files: full-year consolidated, medical conditions, and prescribed medicines. Online pharmacy users were defined as those who reported purchasing a prescription through an online pharmacy by the “pharmacy type” variable for each medication. Individual characteristics examined included age (0–17 years, 18–64 years, 65 years or older); gender; race/ethnicity; marital status (married or not); education (less than high school, high school or equivalent, some college or more); family income (less than 200% federal poverty limit or 200% or more); prescription insurance coverage; health care use and expenditures; and comorbidities. Prescription insurance coverage was ascertained if a person reported having Medicaid, Medicare Part D (2006 onward), or private insurance with prescription coverage. Those failing to report one of these three classifications were determined to not have prescription drug coverage. Health care expenditures included both prescription and nondrug expenditures (emergency department visits, inpatient visits, office-based visits, and outpatient visits). Medications were classified into broad therapeutic categories using Multum Lexicon 290 JAPhA | 5 4 :3 | M AY /JUN 2 0 1 4
ja p h a.org
classification (Cerner Multum, Denver, CO). The total number of prescriptions was categorized as 1, 2–4, 5–9, or 10+. Overall comorbidity burden was assessed using the Charlson comorbidity index (CCI) calculated with the algorithm developed by D’hoore et al.8 Comparisons between online pharmacy users and nonusers were made using chi-square and t tests where appropriate. Logistic regression was used to assess the association of individual characteristics with online pharmacy use. Subgroup analyses were conducted of the older group (65 or over) and younger adults (18–64), with the latter broken down into three smaller categories: 18–34 years, 35–54 years, and 55–64 years. Statistical significance was determined at P
