Communicating non-steroidal anti-inflammatory drug risks: Verbal counseling, written medicine information, and patients’ risk awareness

Patient Education and Counseling 83 (2011) 391–397

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Medication information

Communicating non-steroidal anti-inflammatory drug risks: Verbal counseling, written medicine information, and patients’ risk awareness Michael R. Schmitt a,*, Michael J. Miller b, Donald L. Harrison b, Kevin C. Farmer b, Jeroan J. Allison c, Daniel J. Cobaugh d, Kenneth G. Saag e,f,g a

VA Butler Healthcare, Butler, PA, USA University of Oklahoma Health Sciences Center, College of Pharmacy, Department of Pharmacy, Clinical and Administrative Sciences, Oklahoma City, OK, USA University of Massachusetts Medical School, Department of Quantitative Health Sciences, Worcester, MA, USA d American Society of Health-System Pharmacists Research and Education Foundation, Bethesda, MD, USA e University of Alabama at Birmingham Center for Education and Research on Therapeutics of Musculoskeletal Diseases, Birmingham, AL, USA f University of Alabama at Birmingham Center for Outcomes and Effectiveness Research and Education, Birmingham, AL, USA g University of Alabama School of Medicine, Division of General Internal Medicine, Birmingham, AL, USA b c

A R T I C L E I N F O

A B S T R A C T

Article history: Received 5 March 2010 Received in revised form 24 October 2010 Accepted 30 October 2010

Objective: To assess potential associations among physician counseling, pharmacist counseling, written medicine information (WMI) and patient awareness of non-steroidal anti-inflammatory drug (NSAID) risks. Methods: Three-hundred and eighty-two older, white and African American patients prescribed NSAIDs were surveyed regarding their NSAID risk awareness defined as an index score ranging from zero to four correctly identified risks (i.e., gastrointestinal bleeding, heart attack, hypertension, and kidney disease). Associations among NSAID risk awareness and patient-reported physician counseling, pharmacist counseling, and reading of WMI were evaluated in multivariable ordered logistic regression models and confirmed using path analysis. Results: Physician counseling was positively associated with reading WMI (p < 0.001) and NSAID risk awareness (p < 0.001). Pharmacist counseling was not associated with reading WMI (p = 0.622) and neither pharmacist counseling (p = 0.366) nor reading WMI (p = 0.916) was associated with NSAID risk awareness. Conclusions: Physicians play a prominent role in facilitating NSAID risk awareness whereas pharmacist counseling and WMI may have limited impact. Practice implications: The lack of significant associations among pharmacist counseling and reading WMI with NSAID risk awareness suggests a missed opportunity to improve patient understanding. There is a need for coordinated and effective strategies to communicate risk information among physicians and pharmacists and to better integrate WMI into this process. Published by Elsevier Ireland Ltd.

Keywords: Non-steroidal anti-inflammatory drugs Patient counseling Physicians Pharmacists Written medicine information Risk communication

1. Introduction Non-steroidal anti-inflammatory drugs (NSAIDs), including COX-2 inhibitors, are some of the most commonly prescribed medications in the ambulatory care setting [1]. However, they can lead to a number serious adverse effects including cardiovascular, renal, and gastrointestinal complications, especially in older patients [2–5]. Overall, there is a lack of information about NSAID-related mortality; however, available information suggests that NSAID-related deaths are significant. NSAIDs contribute to

* Corresponding author at: VA Butler Healthcare, 325 New Castle Rd., Butler, PA 16001, USA. Tel.: +1 724 287 4781x5512; fax: +1 724 285 2440. E-mail address: [email protected] (M.R. Schmitt). 0738-3991/$ – see front matter . Published by Elsevier Ireland Ltd. doi:10.1016/j.pec.2010.10.032

16,500 annual deaths in arthritis patients in the United States [6]. A more recent study from Spain has attributed 15.3 deaths per 100,000 NSAID/aspirin users to NSAID/aspirin use, with approximately one-third of such deaths related to low-dose aspirin therapy [7]. Although these studies only focused on GI-related mortality, the inclusion of mortality related to cardiovascular and renal disease could ultimately increase rates. Unnecessary exposure to higher than recommended doses of NSAIDs may result from the highly prevalent usage of over-thecounter (OTC) NSAIDs [8], leading to therapeutic redundancy. A national survey in the United States estimated that 38% of NSAID users take both prescription and OTC NSAIDs [9]. Important drug– drug interactions can also increase the risk of serious adverse effects [2,3]. Additionally, age and predisposing comorbid conditions (e.g., hypertension) physiologically linked to NSAID-related

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adverse effects, increase the risks of NSAIDs, especially in chronic users [3]. Recent studies raise concern whether NSAID users adequately understand the therapeutic risks and benefits of these medications [9–11]. Hence, education plays a critical role in patients’ and caregivers’ understanding, to better manage their disease. In communicating with patients, it is essential to account for patient health literacy [12]. While the link between health literacy and risk communication has yet to be explicitly studied, suboptimal health literacy has been associated with medication misunderstanding leading to diminished capacity to reconcile medications [13], greater likelihood of misinterpreting prescription drug labels [14], decreased comprehension of verbal counseling from healthcare providers [15], and a decreased likelihood to read written information distributed with prescription medications [16,17]. Estimates from the literature demonstrate a national prevalence in the United States of suboptimal health literacy in excess of one-third of the population [18], suggesting that a substantial number of patients may not be able to adequately understand the risks and benefits of their drug therapy without appropriately targeted communication strategies. While it is a practice standard for physicians to ‘‘. . .counsel patients on their medications, emphasizing what is medically significant’’ [19], suboptimal health literacy may limit patients’ medical vocabulary and health knowledge as well as impair their ability to assimilate new information. Simple health literacysensitive strategies to verify patient understanding, such as the teach-back method, in which healthcare providers ask patients to repeat back the information given to them, are infrequently used [20]. Despite the importance of patient education, there is still need for improvement and strong organizational support to enhance patient learning. Similarly, professional standards for pharmacists also suggest that ‘‘. . .pharmacists should educate and counsel all patients to the extent possible, going beyond the minimum requirements of laws and regulations. . .’’ [21]. Therefore, pharmacists in the community setting may be well positioned to identify and aid patients with suboptimal health literacy. However, counseling rates have been found to vary due to pharmacy workload, state regulations, and pharmacist age [22]. A recent study using trained shoppers cited a historical downward trend in pharmacist counseling rates compared to previous reports [23]. Such trends are concerning, given the available opportunity to address patients at risk for misunderstanding their drug therapy. To supplement verbal counseling, written medicine information (WMI) is regularly distributed by pharmacies in the U.S. The U.S. Food and Drug Administration mandates the provision of approved Medication Guides to patients receiving specific medications that ‘‘pose a serious and significant public health concern’’ [24], including NSAIDs as a class, to facilitate understanding of the risks and benefits of treatment [25]. However, the text of Medication Guides generally has exceeded the recommended 6th–8th grade reading level, limiting their usefulness to persons with suboptimal health literacy [17]. Similarly, comprehension of common, yet unregulated, consumer information leaflets has also been linked to health literacy [16]. A recent report cites that only 75% of the information contained in such leaflets meets minimum standards of usefulness [26]. However, a 2009 Cochrane Database review recommends that WMI should still be distributed as it may yield benefits in drug knowledge, despite its limitations [27]. Physician counseling, pharmacist counseling, and WMI provide optimal intervention strategies to increase patient risk awareness of prescription NSAID medications although their effectiveness may be confounded by health literacy level and sociodemographic characteristics [15,16,28]. Therefore, the objective of this study is

to assess patient self-report of physician counseling, pharmacist counseling, and reading WMI in relationship to patient awareness of NSAID risks in a sample of older, white and African American patients prescribed NSAIDs. 2. Methods 2.1. Study design overview Cross-sectional secondary data from the follow-up phase of the Alabama NSAID Patient Safety Study (2006) were used to assess the potential relationships among physician counseling, pharmacist counseling, patient reading of WMI, and patient NSAID risk awareness while controlling for potentially influential background characteristics. The parent project (i.e., Alabama NSAID Patient Safety Study) was approved by the University of Alabama at Birmingham Institutional Review Board and described in detail elsewhere [29]. 2.2. Patient recruitment and interview administration Patients were recruited from a convenience sample of 39 private, community-based, general, family, and internal medicine physician practices in Alabama. Patient eligibility criteria included: (1) established patient of a participating physician; (2) prescribed a prescription strength NSAID; (3) 50 years of age or older within the year of study; and (4) provision of contact information, consent, and completion of a 30 minute telephone survey. The in-depth survey was administered using a computer assisted telephone interview. Patients taking part in the survey received a $20 gift card. 2.3. Timeline, participation rates, and exclusions Patients were recruited and data were collected between June 2006 and February 2007. Among the participating, eligible patients, 74.1% completed the telephone interview. Participation in the study was intended to be race-inclusive; however, only one patient-reported race/ethnicity other than white or AfricanAmerican and was excluded from analysis due to inadequate representation of a third race category. 2.4. Measurements Three principal independent variables were studied in this research. Of those, two separate independent variables were defined as the presence or absence of physician and pharmacist counseling, respectively. Counseling from each provider on each risk was ascertained through a series of eight questions asking patients, ‘‘Did your (doctor); or (pharmacist or druggist) talk with you about the risk of NSAIDs and (high blood pressure or hypertension); (kidney disease); (stomach or intestinal problems such as, ulcers, bleeding, or irritation); or (heart attack)?’’ A ‘‘Yes’’ response was defined as a patient having been counseled on that respective risk from that respective provider and a ‘‘No’’ response was defined as a patient having not been counseled. An ordinal index score was created for each provider ranging from zero to four counseled risks. In the U.S., ‘‘druggist’’ is an antiquated, yet synonymous title for pharmacist that is used among older age groups. For the sake of simplicity, the sole designation of ‘‘pharmacist’’ will be used henceforth to represent this healthcare professional. The third independent variable of primary interest, reading of WMI, was established using a ‘‘Yes’’/‘‘No’’ question to assess if patients had read about NSAID risks contained in written information such as pamphlets or handouts distributed with their prescription NSAID by a pharmacy.

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The dependent variable was NSAID risk awareness defined as an ordinal index score ranging from 0 to 4 correctly identified risks. The NSAID risk awareness variable was a composite score summed from the responses of a series of four questions asking patients, ‘‘How do you think taking NSAIDs affects the risk of (high blood pressure or hypertension); (kidney disease); (stomach or intestinal problems such as, ulcers, bleeding, or irritation); or (heart attack)?’’ The response set included ‘‘Increases Risk’’, ‘‘Decreases Risk’’, or ‘‘Does Not Affect Risk’’. The correct answer to all four questions was ‘‘Increases Risk’’. Patients answering ‘‘Decreases Risk’’ or ‘‘Does Not Affect Risk’’ were coded as an incorrect response. While numerous NSAID-related risks exist, the four studied risks were selected in the parent project from a review of the literature and subsequent consensus agreement among experienced clinicians relating to their clinical significance and likely prevalence in the studied sample. Through a decrease in the production of the gastrointestinal mucosa, the risk of upper gastrointestinal bleeding and perforation has been found to be significantly increased with NSAID use, with prior incidence of GI bleed, advanced age, history of smoking or peptic ulcer, and use of oral corticosteroids and anticoagulants being additional risk factors [2]. Due to their pressor effects, NSAID use has also been linked to clinically significant increases in blood pressure, especially in patients diagnosed with a hypertensive disorder [3]. Additionally, NSAID use can increase the risk of myocardial infarction through enhanced thrombosis, especially in patients who have recently (i.e., within the past 30 days) initiated NSAID therapy [4]. Finally, older patients and those predisposed to renal dysfunction are at greater risk for rapid chronic kidney disease progression and decreased mean glomerular filtration rate due NSAID-related changes in blood flow to the kidneys [5].Covariates included race, age, sex, income adequacy, insurance status, education level, degree of comorbidity, and health literacy estimated by three validated screening questions (SQs) [30,31] (Table 1). All data collected were from patient self-report. Responses of ‘‘Not Sure/Don’t Know’’ or ‘‘Refused’’ were coded as missing. Previous research has established that the option of a ‘‘Don’t Know’’ response may decrease guessing and lead to more accurate assessment of knowledge [32]. Therefore, ‘‘Not Sure/Don’t

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Know’’ responses were set to missing for analysis in the absence of a convention for their coding. All patients were prefaced with a definition of the term ‘‘NSAID’’ prior to responding to survey items. 2.5. Analysis Univariate descriptive statistics for all variables were used to characterize study patients. Bivariate relationships among sociodemographic factors, estimates of health literacy, physician counseling, pharmacist counseling, reading of WMI, and number of correctly identified NSAID risks were assessed using x2 analysis. Although data were collected at the patient level in this study, there may have been potential heterogeneity among physicians’ practices. Therefore, the Generalized Linear Latent and Mixed Models (GLLAMM) [33] procedure with ordered logistic regression models was used to account for the nesting of patients within physicians’ practices. For the primary analysis, four separate ordered logistic regression models were used to assess NSAID risk awareness (i.e., the number of correctly identified NSAID risks) in relationship to race, sex, age, income adequacy, insurance status, degree of comorbidity, number of physician counseled risks, number of pharmacist counseled risks, the reading of WMI, estimated health literacy, and education level. Because education level and each of the three estimates of health literacy were collinear (x2 = 52.3– 57.6, p < 0.001) in preliminary analyses, they were tested in separate models. Additionally, combinations of screening questions have not demonstrated improved discriminatory ability compared to single-items alone [30,31]. Therefore, each of the three health literacy screening items were tested in separate statistical models to establish consistency among the health literacy estimates. Each model only varied by inclusion of a health literacy screening or education variable. Because the data collected for this study originated from a randomized clinical trial, potential confounding of relationships among key predictor variables was assessed with ordered logistic regression models that included the intervention indicator variable. Key predictor variables were also stratified by intervention status using Mantel–Haenszel x2 tests to confirm homogene-

Table 1 Definitions of independent variables and covariates. Indicator variable

Definition

Race

                   

Sex Age Income adequacy (food, clothing, shelter, medical care) Insurance status Education Estimates of health literacya,b,c Comorbidities Physician counseling Pharmacist counseling Reading of written medicine information (WMI)

White (reference) African American Male (reference) Female 49–65 years (reference) 65 years Inadequate to meet basic needs (reference) Adequate to meet basic needs Private/Medicare/other (e.g., Tricare, workers’ compensation, etc.) (reference) Medicaid/uninsured High school graduate or less (reference) At least some college or above Inadequate (reference) Adequate/marginal Median # of comorbidities (reference) >Median # of comorbidities Counseling on 0–4 NSAID risks Counseling on 0–4 NSAID risks Did not read information (reference) Read information

a Screening question (SQ) 1: ‘‘How often do you have problems learning about your medical condition because of difficulty understanding written information?’’ Response set: never; occasionally (adequate/marginal) vs. sometimes; often; always (inadequate). b SQ2: ‘‘How confident are you in filling out medical forms by yourself?’’ Response set: extremely; quite a bit (adequate/marginal) vs. somewhat; a little bit; not at all (inadequate). c SQ3: ‘‘How often do you have someone (like a family member, friend, hospital/clinic worker, or caregiver) help you read hospital materials?’’ Response set: never; occasionally (adequate/marginal) vs. sometimes; often; always (inadequate).

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ity of odds ratios within intervention and control strata. Finding no confounding or effect modification by intervention status, all data were used in aggregate for the final analysis without the inclusion of the intervention indicator variable. All analyses were calculated using STATA 10.1 [34]. An a priori alpha level of 0.05 was the criterion for statistical significance. Following the primary analysis, confirmatory path analysis was used to test the total effect (i.e., combined direct and indirect effects) of principal predictor variables while controlling for covariates. The path analysis was performed using MPLUS version 5.2 [35] because of its robust support of categorical dependent variables. A final model was selected based on tests of model fit as determined by a non-significant x2 statistic, Comparative Fit (CFI) and Tucker-Lewis (TLI) indices with values greater than 0.95, a root mean square error of approximation (RMSEA) less than 0.05, and a weighted root mean square residual (WRMR) less than 1.0. In particular, the TLI has been indicated as a better measure than the CFI for use in categorical data, as used in this study [36]. 3. Results

Table 2 Overall participant characteristics (n = 382).

a

NSAID risk awareness, median African American Female Age  65 years At least some college education Income adequate to meet needsb Medicaid/uninsured Number of comorbidities, medianc Adequate/marginal health literacy: SQ1 Adequate/marginal health literacy: SQ2 Adequate/marginal health literacy: SQ3 Risks counseled by physician, mediana Risks counseled by pharmacist, mediana Read WMId

n

%

2 148 275 145 165 274 67 2 296 282 296 1 0 250

n/a 38.7 72.0 38.1 43.3 72.3 17.6 n/a 77.9 73.8 77.5 n/a n/a 67.6

a Risks included: high blood pressure or hypertension; kidney disease; stomach or intestinal problems such as, ulcers, bleeding, or irritation; and heart attack. b Adequate income assessed by, ‘‘Currently, is your income enough to meet your basic needs for food, housing, clothing, and medical care?’’ Response: Yes vs. No. c Comorbidities include: gastrointestinal bleeding; hypertension; heart attack; history of cerebrovascular accident; heart failure; liver disease; kidney disease; diabetes; arthritis. d Written medicine information.

3.1. Descriptive statistics After applying exclusion criteria, 382 patients completed the telephone survey (Table 2). All patients were recruited from community-based, primary care physicians’ offices and an excess of 90% of patients indicated that their primary pharmacy was in the community/retail environment. Most patients (91.9%) reported taking a prescription NSAID for one month or more. At the time of survey administration, a majority of patients (63.4%) were also still taking their originally prescribed medication. A majority of patients (67.6%) reported having read WMI distributed with their prescription NSAIDs. Patients reported a median of one counseled risk from physicians and zero counseled risks from pharmacists. Approximately one-half of patients (50.7%) were counseled by a physician on at least one risk (Table 3). A majority of patients (82.1%) did not receive pharmacist counseling on any of the four risks (Table 3). Patients correctly identified a median of two risks (Table 3). Thirty-one patients (8.1%) were ‘‘Not Sure’’ on any of the four items related to risks of NSAIDs, and were excluded as previously described in the methodology. 3.2. Bivariate analysis In bivariate analyses, race (x2 = 9.53, p = 0.049), age (x2 = 13.90, p = 0.008), education (x2 = 13.82, p = 0.008), and each estimate of health literacy (SQ1: x2 = 9.47, p = 0.050; SQ2: x2 = 11.54,

p = 0.021; SQ3: x2 = 11.91, p = 0.018) were significantly associated with the number of correctly identified NSAID risks. No other sociodemographic variables were associated with NSAID risk awareness in bivariate analyses. Regarding risk communication, the number of physician counseled risks (x2 = 53.22, p < 0.001) was significantly associated with number of risks correctly identified by patients. There was no association between the number of pharmacist counseled risks (p = 0.282) or the reading of WMI (p = 0.122) in relationship to the number of correctly identified NSAID risks. 3.3. Multivariable analysis Results from the four ordered logistic regression models (Table 4) are presented as inclusive ranges. The number of physician counseled risks was found to be significantly and positively associated with patients correctly identifying higher numbers of NSAID risks (adjusted odds ratio (AOR): 1.34–1.37, p < 0.001). Patients with adequate-marginal health literacy (AOR: 1.70–2.11, p = 0.007–0.038) or at least some college education (AOR: 1.61, p = 0.035) were significantly more likely to correctly identify a greater number of NSAID risks. In contrast, patients 65 years of age and older were significantly less likely to identify higher numbers of risks (AOR: 0.49–0.52, p = 0.002–

Table 3 Provider counseling and patient awareness of NSAID risks (n = 382). Physician

Counseled risks Gastrointestinal bleed Heart attack Hypertension Kidney disease No. counseled risks 0 1 2 3 4 All responses ‘missing’ a

Pharmacist

n

Usable %a

158 113 125 119

43.29 31.13 34.63 33.06

185 52 30 29 79 7

49.33 13.87 8.00 7.73 21.07 n/a

Counseled risks Gastrointestinal bleed Heart attack Hypertension Kidney disease No. counseled risks 0 1 2 3 4 All responses ‘missing’

Patient

Usable %a

n 53 39 49 41

14.13 10.40 13.10 10.88

312 19 10 13 26 2

82.11 5.00 2.63 3.42 6.84 n/a

For individual risks, percentages represent the number of patients with non-missing responses.

Recognized risks Gastrointestinal bleed Heart attack Hypertension Kidney disease No. recognized risks 0 1 2 3 4 All responses ‘missing’

n

Usable %a

274 95 107 151

86.16 44.19 51.69 68.95

56 106 86 63 40 31

15.95 30.20 24.50 17.95 11.40 n/a

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Table 4 Adjusted odds ratios (AORs) and 95% confidence intervals (CI) from GLLAMM ordered logistic regression for NSAID risk-awarenessa (n = 382). Model I

African American Female Age  65 years Adequate incomeb Medicaid/uninsured Number of comorbidities > medianc Health literacy estimate SQ1 Health literacy estimate SQ2 Health literacy estimate SQ3 At least some college education Physician counseled risks (0–4)a Pharmacist counseled risks (0–4)a Read WMId

Model II

Model III

Model IV

AOR

95% CI

AOR

95% CI

AOR

95% CI

AOR

95% CI

1.50 1.00 0.49 0.75 0.42 1.15 2.11

(0.91–2.47) (0.63–1.60) (0.31–0.76) (0.45–1.26) (0.23–0.74) (0.75–1.75) (1.23–3.62)

1.50 1.01 0.50 0.78 0.42 1.17

(0.91–2.49) (0.63–1.62) (0.32–0.78) (0.46–1.30) (0.23–0.76) (0.76–1.78)

1.46 0.95 0.52 0.73 0.41 1.18

(0.89–2.39) (0.60–1.52) (0.33–0.82) (0.44–1.22) (0.23–0.73) (0.77–1.80)

1.43 1.03 0.52 0.78 0.46 1.16

(0.87–2.35) (0.64–1.64) (0.34–0.82) (0.47–1.30) (0.25–0.83) (0.76–1.77)

1.70

(1.03–2.79) 2.02

(1.20–3.41)

1.37 0.93 0.99

(1.17–1.59) (0.76–1.13) (0.63–1.56)

1.61 1.34 0.95 1.04

(1.03–2.51) (1.15–1.56) (0.78–1.16) (0.66–1.63)

1.34 0.94 0.98

(1.15–1.56) (0.78–1.14) (0.62–1.55)

1.35 0.94 1.00

(1.16–1.58) (0.78–1.14) (0.63–1.58)

a

Risks included: high blood pressure or hypertension; kidney disease; stomach or intestinal problems such as, ulcers, bleeding, or irritation; and heart attack. Adequate income assessed by, ‘‘Currently, is your income enough to meet your basic needs for food, housing, clothing, and medical care?’’ Response: Yes vs. No. c Comorbidities include: gastrointestinal bleeding; hypertension; heart attack; history of cerebrovascular accident; heart failure; liver disease; kidney disease; diabetes; arthritis. d Written medicine information. b

variation from original models; therefore, an indicator variable for intervention status was not used in the analyses.

0.005), as were patients enrolled in Medicaid or who were uninsured (AOR: 0.41–0.46, p = 0.003–0.010). Pharmacist counseling (p = 0.449–0.630) and the reading of WMI (p = 0.871–0.994) were not associated with number of identified NSAID risks. No other sociodemographic factors were significantly associated with NSAID risk awareness.

3.5. Path models The results of the path analysis were similar to the results of the ordered logistic regressions (Fig. 1). Physician counseling was significantly and positively associated with the reading of WMI (p < 0.001) and awareness of NSAID risks (p < 0.001). The number of pharmacist counseled risks with respect to the reading of WMI (p = 0.622) and NSAID risk awareness (p = 0.366) was not statistically significant nor was the reading of WMI with respect to NSAID risk awareness (p = 0.916). The model demonstrated good fit with a non-significant x2 (p = 0.867), CFI of 1.000, and TLI of 1.102. Additional fit indices were indicative of good fit, with a RMSEA of less than 0.001 and a WRMR of 0.401.

3.4. Confounding and effect modification No evidence of confounding or effect modification was found. All Mantel–Haenszel tests for the homogeneity of odds ratios among predictor variables and NSAID risk awareness, stratified by intervention status (i.e., intervention vs. control groups in the parent study), yielded non-significant results (p > 0.11). Furthermore, multivariable models including an indicator variable to account for intervention status demonstrated no important

Age ≥ 65 Years

Medicaid

-0.483* -0.386*

-0.399*

Female Sex

0.482*

Est. Adequate Health Literacy

0.138*

0.236*

NSAID Risk Awareness

p = 0.004

Read Writt en Medicine Info

-0.008

0.152* 1.300*

-0.048 0.198*

At least some College Education

Physician Counseling

0.041 Pharmacist Counseling

Chi-Sq Test of Model Fit Chi-Square: 3.888 p = 0.8670 Goodness of Fit Indices:a CFI = 1.000 TLI = 1.102 RMSEA < 0.001 WRMR = 0.401

* p < 0.05 level a Comparative Fit Index (CFI); Tucker-Lewis Index (TLI); Root mean square error of approximation (RMSEA); Weighted root mean square residual (WRMR) Fig. 1. Path model for NSAID risk awareness and associated parameters.

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4. Discussion and conclusion 4.1. Discussion In this sample of older, white and African American adults only 29.4% of patients were aware of three or more of the studied NSAID risks. Moreover, several vulnerable population subgroups were found to have a lower awareness of NSAID risks. Medicaid/ uninsured status and age were inversely related to NSAID risk awareness. Those patients estimated to have adequate/marginal health literacy had higher odds of being more risk aware compared to those estimated to have inadequate health literacy. Of the three points of risk communication intervention, pharmacist counseling and reading WMI were not associated with number of known NSAID risks. Despite a need to raise counseling rates regarding risk information, physicians appear to be the predominant contributor to patient NSAID risk awareness. Although pharmacist counseling and WMI have the potential to alleviate some physician–patient education burden, they do not seem to be effective means for communicating NSAID risk information as currently provided. The results of our study highlight a missed opportunity to raise NSAID risk awareness in ambulatory care. There is a need to coordinate physician and pharmacist communication to promote efficient delivery of risk information. For example, in this study patients reported higher rates of counseling on gastrointestinal risk from both physicians and pharmacists while reporting comparatively lower rates of counseling on heart attack risk from both providers. Given the sample’s median age of 61 years, and the vast majority of patients indicating chronic NSAID use, higher counseling rates were expected due to the potential risk factors in this group. Nonetheless, it is likely that pharmacists and physicians may not counsel more widely on severe, yet less frequent side effects because they do not want to alarm patients who would likely benefit from therapy. However, as seen in this study, the redundancy in counseling on gastrointestinal risk information and suboptimal counseling on heart attack risk information, despite variations in prevalence and severity of each of these risks, may leave patients with an incomplete understanding of the risks of their NSAID therapy. This would especially affect vulnerable populations such as the elderly, those with suboptimal health literacy, and those enrolled in Medicaid or who are uninsured. Patients deserve to fully understand the risks and benefits of their NSAID therapy. This need is underscored among patients who are likely to be chronic users or have factors that predispose them to increased risk. While there is a dearth of literature relating how NSAID risks should be communicated, it has been suggested that a multifaceted approach is needed to contextualize risks to enhance patient understanding [37]. Additional research in this area is needed to provide guidance as to how healthcare providers can balance patients’ rights to receive information to make informed decisions while at the same time minimizing unnecessary apprehension which may delay or prevent treatment. The lack of coordination between physicians and pharmacists in serving patients’ needs has been acknowledged as a problem with respect to counseling responsibilities for various aspects of medication-related information (e.g., directions for use, side effects, dosage, etc.) [38]. Patients more often attribute the responsibility of providing medication-related information to physicians than pharmacists [39]. An inference that can be drawn from that study and the results of the current study is that physicians are largely the driver of patient risk awareness and behaviors such as reading of WMI, and therefore, bear a significant burden for risk communication. Pharmacists in the community setting may be an unrealized resource to potentially alleviate physicians’ patient education burden. While pharmacists believe

themselves to be risk information providers [39], given current patient perceptions and the results from our study, physicians will likely need to facilitate the sharing of responsibility for patient education with pharmacists. As well, pharmacists must also assume a more active role in initiating risk communication given their professional responsibility and accessibility. Alternative models of care outside of the community/retail pharmacy environment have demonstrated success in patient education [40]. Thus, future research may seek to examine potential models for shared responsibility and coordination between physicians and community pharmacists to optimize risk communication. Additionally, our study found no association between patient reading of WMI and awareness of NSAID risks, which is consistent with primary research [16,26,41] questioning the effectiveness of FDA-mandated Medication Guides and consumer information leaflets. Beyond revision and simplification of WMI to improve risk communication [42], the study of strategies to integrate WMI into patient-provider counseling is paramount to improving its usefulness to patients. Despite barriers to patient counseling [22,23], a recent study of the integration of WMI into counseling found that an educational workshop could increase pharmacist use of WMI in patient counseling [43]. While FDA mandates Medication Guides for certain drugs or drug classes [24], and is actively working to enhance patient education materials [42], they do not and cannot regulate the practice of medicine or pharmacy nor providers’ use of WMI in effectively educating patients. Therefore, it is essential for healthcare providers’ organizations to jointly develop guidelines and promote policy and system change that optimizes interdisciplinary coordination of risk communication and integration of WMI into risk communication practices. 4.1.1. Limitations Several limitations must be considered in this study. All data were derived from patient self-report. Such data are subject to reporting/recall errors or social desirability bias. Recall errors may be more prevalent in patients for which more time has elapsed since the initiation of NSAID therapy. Additionally, the quality of patient counseling or written information received could not be evaluated. The cross-sectional design precludes evaluating any cause and effect relationships. While the health literacy screening questions only estimate health literacy, they have been previously validated [30,31]. The studied risks do not represent the complete array of NSAID risks, but do represent either common and/or potentially serious consequences specific to NSAID therapy, especially within older, chronic NSAID users participating in this study. Alternative strategies for risk communication, specifically the Internet, were not assessed in this study. Shared variation between physician and pharmacist counseling related to NSAIDs may have also influenced results; however, removal of physician counseling from all models failed to improve the significance of pharmacist counseling or the reading of WMI. Furthermore, while no evidence of confounding and effect modification due to the design of the parent study was found, undetected residual effects may remain. Finally, the media coverage of the safety issues associated with the withdrawal of COX-2 inhibitors occurred before and during this study and may have posed a historical threat by confounding risk awareness through a mechanism other than provider counseling and/or WMI. 4.2. Conclusion This research underscores physicians’ current and prominent role in facilitating NSAID risk awareness while presenting an opportunity for pharmacists to enhance their role in the risk communication process. The results suggest a need to better coordinate physician and pharmacist counseling to improve

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efficiency and eliminate redundancy to communicate clear and complete risk information to all patients. Improved coordination of patient education, a focus on more literacy sensitive counseling strategies, and integration of written materials into the counseling process may increase the effectiveness of risk information. 4.3. Practice implications In a system that relies heavily on the physician, pharmacist, and WMI working together to communicate risk information, the result in the case of NSAIDs is suboptimal. There exists a need to better coordinate patient NSAID risk communication among physicians and pharmacists to ensure complete and effective patient counseling, while integrating useful WMI to facilitate patient understanding. Future efforts should develop and evaluate methods to improve the flow of information among community practitioners so they may be able to best meet patient needs with respect to risk communication. Conflicts of interest The authors report no conflicts of interest. Acknowledgements This project was supported in part by the Agency for Healthcare Research and Quality (AHRQ), Centers for Education and Research on Therapeutics cooperative agreement (U18-HS010389) and was presented in part at the 2010 Annual Meeting and Exposition of the American Pharmacists Association. References [1] Raofi S, Schappert SM. Medication therapy in ambulatory medical care: United States, 2003–04. Vital Health Stat 2006;163:1–40. [2] Garcı´a Rodrı´guez LA, Jick H. Risk of upper gastrointestinal bleeding and perforation associated with individual non-steroidal anti-inflammatory drugs. Lancet 1994;343:769–72. [3] Johnson AG. NSAIDs and increased blood pressure: what is the clinical significance? Drug Safety 1997;17:277–89. [4] Johnsen SP, Larsson H, Tarone RE, McLaughlin JK, Nørga˚rd B, Friis S, et al. Risk of hospitalization for myocardial infarction among users of rofecoxib, celecoxib, and other NSAIDs: a population-based case–control study. Arch Intern Med 2005;165:978–84. [5] Gooch K, Culleton BF, Manns BJ, Zhang J, Alfonso H, Tonelli M, et al. NSAID use and progression of chronic kidney disease. Am J Med 2007;120:280.e1–7. [6] Singh G, Rosen RD. NSAID induced gastrointestinal complications: the ARAMIS perspective – 1997. Arthritis, Rheumatism, and Aging Medical Information System. J Rheumatol 1998;(Suppl. 51):8–16. [7] Lanas A, Perez-Aisa MA, Feu F, Ponce J, Saperas E, Santolaria S, et al. A nationwide study of mortality associated with hospital admission due to severe gastrointestinal events and those associated with nonsteroidal antiinflammatory drug use. Am J Gastroenterol 2005;100:1685–93. [8] National Consumers League. Over-the-counter pain medication study [executive summary]. Available from: http://www.nclnet.org/otcpain/harrisesummary.htm; 2003 [accessed 14.07.09]. [9] Wilcox CM, Cryer B, Triadafilopoulos G. Patterns of use and public perception of over-the-counter pain relievers: focus on nonsteroidal antiinflammatory drugs. J Rheumatol 2005;32:2218–24. [10] Cham E, Hall L, Ernst AA, Weiss SJ. Awareness and use of over-the-counter pain medications: a survey of emergency department patients. S Med J 2002;95:529–35. [11] Cullen G, Kelly E, Murray FE. Patients’ knowledge of adverse reactions to current medications. Brit J Clin Pharmacol 2006;62:232–6. [12] Ratzan SC, Parker RM. Introduction. In: Selden CR, Zorn M, Ratzan SC, Parker RM, editors. National Library of Medicine current bibliographies in medicine: health literacy. Bethesda, MD: NLM Pub. No. CBM 2000-1. National Institutes of Health, U.S. Department of Health and Human Services; 2000. [13] Persell S, Osborn C, Richard R, Skripkauskas S, Wolf M. Limited health literacy is a barrier to medication reconciliation in ambulatory care. J Gen Intern Med 2007;22:1523–6. [14] Davis TC, Wolf MS, Bass PF, Thompson JA, Tilson HH, Neuberger M, et al. Literacy and misunderstanding prescription drug labels. Ann Intern Med 2006;145:887–94.

397

[15] Schillinger D, Bindman A, Wang F, Stewart A, Piette J. Functional health literacy and the quality of physician–patient communication among diabetes patients. Patient Educ Couns 2004;52:315–23. [16] Koo MM, Krass I, Aslani P. Patient characteristics influencing evaluation of written medicine information: lessons for patient education. Ann Pharmacother 2005;39:1434–40. [17] Wolf MS, Davis TC, Shrank WH, Neuberger M, Parker RM. A critical review of FDA-approved Medication Guides. Patient Educ Couns 2006;62:316–22. [18] Kutner M, Greenberg E, Jin Y, Paulsen C. The health literacy of America’s adults: results from the 2003 National Assessment of Adult Literacy (NCES 2006-483): U.S. Department of Education. Washington, DC: National Center for Education Statistics; 2006. [19] Guidelines for physicians for counseling patients about prescription medications in the ambulatory setting. Chicago, IL: American Medical Association; 2004. [20] Schwartzberg JG, Cowett A, VanGeest J, Wolf M. Communication techniques for patients with low health literacy: a survey of physicians, nurses, and pharmacists. Am J Health Behav 2007;31:96–104. [21] American Society of Health-System Pharmacists. ASHP guidelines on pharmacist-conducted patient education and counseling. Am J Health Syst Ph 1997;54:431–4. [22] Svarstad BL, Bultman DC, Mount JK. Patient counseling provided in community pharmacies: effects of state regulation, pharmacist age, and busyness. J Am Pharm Assoc 2004;44:22–9. [23] Flynn EA, Barker KN, Berger BA, Lloyd KB, Brackett PD. Dispensing errors and counseling quality in 100 pharmacies. J Am Pharm Assoc 2009;49:171–80. [24] Medication Guides for prescription drug products. 21 CFR 208.1. Available form: http://edocket.access.gpo.gov/cfr_2008/aprqtr/21cfr208.1.htm; 2008 [accessed 04.09.08]. [25] Steering Committee for the Collaborative Development of a Long-Range Action Plan for the Provision of Useful Prescription Medicine Information. Action plan for the provision of useful prescription medicine information. Unpublished report presented to The Honorable Donna E. Shalala, Secretary of the Department of Health and Human Services; 1996. [26] Kimberlin CL, Winterstein AG. Expert and consumer evaluation of consumer medication information – 2008. University of Florida; 2008. [27] Nicolson D, Knapp P, Raynor DK, Spoor P. Written information about individual medicines for consumers. Cochrane Database Syst Rev 2009. Available from: http://www.mrw.interscience.wiley.com/cochrane/clsysrev/articles/ CD002104/frame.html. [28] Willems S, De Maesschalck S, Deveugele M, Derese A, De Maeseneer J. Socioeconomic status of the patient and doctor–patient communication: does it make a difference? Patient Educ Couns 2005;56:139–46. [29] Cobaugh DJ, Angner E, Kiefe CI, Ray MN, Lacivita CL, Weissman NW, et al. Effect of racial differences on ability to afford prescription medications. Am J Health Syst Ph 2008;65:2137–43. [30] Chew LD, Bradley KA, Boyko EJ. Brief questions to identify patients with inadequate health literacy. Fam Med 2004;36:588–94. [31] Chew LD, Griffin JM, Partin MR, Noorbaloochi S, Grill JP, Snyder A, et al. Validation of screening questions for limited health literacy in a large VA outpatient population. J Gen Intern Med 2008;23:561–6. [32] Courtenay BC, Weidemann C. The effects of a ‘‘don’t know’’ response on Palmore’s Facts on Aging quizzes. Gerontologist 1985;25:177–81. [33] Rabe-Hesketh S, Skrondal A. Multilevel modelling of complex survey data. J Roy Stat Soc A 2006;169:805–27. [34] Stata statistical software (computer program). Version 10. College Station, TX: StataCorp LP; 2007. [35] Muthe´n LK, Muthe´n BO. fifth ed., Mplus user’s guide, Los Angeles, CA: Muthe´n & Muthe´n; 2007. [36] Hox JJ. Multilevel analysis: techniques and applications. Mahwah, NJ: Lawrence Erlbaum Associates; 2002. [37] Moore RA, Derry S, McQuay HJ, Paling J. What do we know about communicating risk: a brief review and suggestion for contextualising serious, but rare, risk, and the example of cox-2 selective and non-selective NSAIDs. Arthritis Res Ther 2008;10:R20. [38] Tarn DM, Paterniti DA, Williams BR, Cipri CS, Wenger NS. Which providers should communicate which critical information about a new medication? Patient, pharmacist, and physician perspectives. J Am Geriatr Soc 2009;57:462–9. [39] Schommer JC, Pedersen CA, Worley MM, Brown LM, Hadsall RS, Ranelli PL, et al. Provision of risk management and risk assessment information: the role of the pharmacist. Res Social Adm Pharm 2006;2:458–78. [40] American Society of Health System Pharmacists. Value of pharmacy in patient care. Available form: http://www.ashp.org/DocLibrary/Policy/PPMI/ValueOutpatient.aspx; 2009 [accessed 08.02.10]. [41] Shrank WH, Avorn J. Educating patients about their medications: the potential and limitations of written drug information. Health Affair 2007;26:731–40. [42] U.S. Food and Drug Administration. Risk Communication Advisory Committee. Available from: http://www.fda.gov/oc/advisory/OCRCACACpg.html; 2009 [accessed 22.05.09]. [43] Aslani P, Benrimoj SI, Krass I. Development and evaluation of a training program to foster the use of written drug information in community pharmacies. Part 2: evaluation. Pharm Educ 2007;7:141–9.