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Journal of Safety Research Publication, December 3, 2015

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Journal of Safety Research Publication, December 3, 2015

  1. 1. Research communication Applying human factors to develop an improved package design for (Rx) medication drug labels in a pharmacy setting Julie M. Gerhart, a Holly Spriggs, a Tonja W. Hampton, a Rose Mary B. Hoy, a Allison Y. Strochlic, b Susan Proulx, c Debra B. Goetchius a, ⁎ a Merck & Co., Inc., 2000 Galloping Hill Road, Kenilworth, NJ 07033, USA b Wiklund Research & Design, Inc. (WR&D, now a UL LLC company), 300 Baker Ave, Concord, MA 01742, USA c Med-ERRS Inc.,200 Lakeside Dr, Horsham, PA 19044, USA a b s t r a c ta r t i c l e i n f o Article history: Received 20 May 2014 Received in revised form 23 February 2015 Accepted 26 August 2015 Available online 9 September 2015 Keywords: Medication Label Human factors usability test Medication error As many as 98,000 people die every year from preventable medical errors. Among pharmacists, the most com- mon error reported is the selection of the wrong drug. Merck met with the U.S. Food and Drug Administration (FDA) to discuss the optimization of the U.S. label for solid oral dosage forms of Merck medications. These discus- sions led to the development of revised label designs for six products that were then evaluated using failure modes and effects analysis and an expert review by human factors specialists. There were no errors among 425 filled prescriptions in the validation test of the final label. Key changes to the original labels include the use of a non-branded logo, high-contrast color bands for dosage strength, and an enhanced three-dimensional tablet image. The redesigned labels were approved by the US FDA in June 2011. Practical applications: The redesigned label should improve the accurate selection of medications from pharmacy shelves. © 2015 National Safety Council and Elsevier Ltd. All rights reserved. 1. Introduction The Institute of Medicine's (IOM) seminal study “To Err Is Human: Building a Safer Health System” estimated that as many as 98,000 people die every year from preventable medication errors (Kohn, Corrigan, & Donaldson, 2000). The National Coordinating Council for Medication Error Reporting and Prevention defines a medication error as “any preventable event that may cause or lead to inappropriate medication use or patient harm while the medication is in the control of the health care professional, patient, or consumer.” (United States Food and Drug Administration website, n.d.) It states further that one of the several causes of medication errors is related to product labeling and packaging, as well as dispensing and distribution. Pharmacists are highly skilled professionals delivering essential health care, but errors can occur when dispensing medication (Abood, 1996; Gianutsos, n.d.). In a national observational study of 50 U.S. pharmacies, dispensing errors occurred at a rate of 4 per 250 prescriptions per day, resulting in an estimated 51.5 million errors among the 3 billion prescriptions filled each year (Flynn, Barker, & Carnahan, 2003). Among pharmacists, the most common error reported is the selection of the wrong drug (Gianutsos, n.d.). An IOM report published in 2006 cited package labeling as the cause of 33% of all medication errors and 30% of the fatalities from medication errors (Aspden et al., 2006). Some of the labeling and packaging issues identified were unclear dose concentrations or strength designations, cluttered labeling, small font, lack of adequate background contrast, and over- emphasis on company logos (Aspden et al., 2006). The IOM report requested that the U.S. Food and Drug Administration (FDA) develop a guidance document for industry for labeling and packaging (Aspden et al., 2006). The report also urged that the FDA and industry collaborate to develop methods of applying failure mode and effects analysis (FMEA) to labeling and packaging, emphasizing that labeling and packaging should be designed for the end user—be it the health care provider, phar- macist, or patient. In 2007, representatives of Merck met with the FDA to discuss the optimization of its U.S. package labeling for solid oral dosage forms. Merck presented a proposed label design that was developed based on a combination of FDA comments, pharmacist survey results, as well as internal package engineering requirements. The FDA then recommended that Merck test the label design in actual use environments using suitable methodologies to identify weaknesses that might lead to user error. In this paper, we describe the methodology used to develop and select an im- proved design that would support consistent, accurate dispensing of Merck products under typical retail pharmacy conditions. Journal of Safety Research 55 (2015) 177–184 ⁎ Corresponding author at: 13 Meadow View Road, Gladstone, NJ 07934, USA. Tel.: +1 908 672 5972. E-mail address: debby.g@comcast.net (D.B. Goetchius). http://dx.doi.org/10.1016/j.jsr.2015.08.005 0022-4375/© 2015 National Safety Council and Elsevier Ltd. All rights reserved. Contents lists available at ScienceDirect Journal of Safety Research journal homepage: www.elsevier.com/locate/jsr
  2. 2. 2. Materials and methods 2.1. Objective This study's objective was to apply medication safety and human factors engineering expertise and methodologies to develop an improved label design for six of Merck's solid oral medications: JANUVIA®, JANUMET®, COZAAR®, HYZAAR®, SINGULAIR®, and CRIXIVAN®. The goal was to facil- itate consistent and accurate dispensing of Merck medications by retail pharmacists and to further minimize the potential for confusion that might contribute to medication errors. 2.2. FMEA, expert review by human factors specialists, and simulated use testing Two external consultants were contracted to provide independent, objective subject matter expertise: Med-ERRS® (a subsidiary of the Institute for Safe Medication Practices [ISMP]); and Wiklund Research & Design, Inc. (WR&D, now a UL LLC company), a human factors engineering company. Two tools which both the U.S. FDA Center for Drug Evaluation and Research and the IOM recommend to develop drug products were utilized—simulated use testing and FMEA (Aspden et al., 2006; US Food and Drug Administration, n.d.-a; US Food and Drug Administration, n.d.-b). Per the FDA's guidance, simulated use testing begins with formative evaluations—defined as evaluations which inform product development in progress (US Food and Drug Administration, n.d.-b). These evaluations derive information from user interaction with the device (i.e., the label) under conditions of varying degrees of formality. Formative studies that involve use of the device by representative end users are useful for identi- fying problems that are not identified or sufficiently understood using analytical methods. Formative studies are conducted informally, with simple mock-up devices or preliminary prototypes and with small numbers of test participants. Formative evaluation is then followed by a validation test (US Food and Drug Administration, n.d.-b). The purpose is to demonstrate that the intended users of a medical device (i.e., a label) can safely and effectively perform critical tasks for the intended uses in the expected use environ- ments. The validation testing uses a production version of the device, representative device users, actual use or simulated use in an environment of appropriate realism, to address all aspects of intended use. FMEA is a risk assessment method based on the simultaneous analysis of failure modes, their consequences, and their associated risk factors (Carayon, 2012). The FMEA process seeks to identify design flaws in a way that may predict and limit the frequency and consequence of human error. The following criteria were used by Med-ERRS during the FMEA when reviewing the label design options: 1) aesthetics and overall readability; 2) readability and hierarchical placement of the most critical information; 3) interference with readability by brand logos or corporate dress; and 4) visibility and positioning of expiration dates, lot numbers, and barcodes. The independent expert review of the label design was conducted by three WR&D human factors specialists. The specialists reviewed the existing medication labels and the proposed redesigns and compared their findings to reach a consensus on the labels' design strengths and opportunities for improvement. WR&D evaluated the labels based on established human factors design principles and relevant industry standards and guidelines that were in place at the time of the study (e.g., AAMI HE48–1993, a draft of AAMI HE75–200X, and pertinent content in the Code of Federal Regulations), and their professional judgment. 3. Results 3.1. Initial evaluation As part of the initial phase of this project, three alternate label designs (1, 2a, 2b, Fig. 1) were generated by Merck based on FDA comments, phar- macist survey results, and internal package engineering requirements. The alternate label designs included a three-dimensional tablet image; a color band highlighting the dosage strength’ increased contrast between the text, color bands, and the paper substrate; and overall usage of a densely weighted sans-serif font for enhanced legibility (Fig. 2). For dosage strength, colors had to be very clearly distinct from each other, most especially within a product line and among products with the same initial letter in trade and generic names. Color selection began with the product brand colors (i.e., blue, green, and bright pink for JANUVIA®). When brand colors would not provide clear discrimination among strengths and products, other distinctive colors were explored. The determination whether to use white or black type on top of the color band was based on maximum contrast. A computer-based color contrast analyzer tool (http://www. paciellogroup.com/resources/contrastanalyser) was utilized to measure the contrast of one color atop another. The use of medium-brightness colors was avoided as the background for black or white text in order to ensure adequate contrast and good legibility for the strength display. Med-ERRS® and WR&D reviewed background on the existing labels, including FDA comments, pharmacists' comments from previous research, and error reports provided by Merck and the U.S. Pharmacopeia (USP)-ISMP Medication Errors Reporting Program. The FMEA and expert review re- sulted in the following changes to the initial three label designs: 1) Abandoning design option 1 due to lack of differentiation between Merck medications. Although the standard color assignments were improved through the use of brighter, more vibrant colors than some of those used historically, it was ultimately decided that this application of color was akin to “color-coding” which was found to be unfavorable by FDA as well as Med-ERRS. While it provided differentiation within a product group, the team believed it did not provide sufficient differentiation within a product family where similar product names were used (i.e., JANIUVIA®, JANUMET®). There was also a concern regarding the possibility of running out of enough distinct color options. 2) Increasing the design options to four (by adding designs 3a and 3b, Fig. 2) to explore the effectiveness of printing the dosage strength and National Drug Code (NDC) on a color band, and the use of plain font for the brand name. 3) Enlarging the font of the medication trade name, dosage strength, NDC, lot number, and expiry legends. 4) Simplifying and standardizing fonts and improving the use of white space and functional grouping. 5) Centering the dosage strength in the color band for designs 2a and 2b. 178 J.M. Gerhart et al. / Journal of Safety Research 55 (2015) 177–184
  3. 3. 3.2. Formative usability test Formative usability testing was employed to evaluate designs 2a, 2b, 3a, and 3b. For the formative test, WR&D recruited and compensated four pharmacists and four pharmacy technicians from the Metropolitan Boston area. The test was conducted in the WR&D usability test laboratory. The participants' ages ranged from 22 to 57, and approximately two-thirds (n = 5) were women (Table 1). The retail pharmacy experience ranged from 3 to 33 years. There were no visual or physical impairments reported and all participants were asked to bring or wear any prescription eyewear. The pharmacy environment was simulated by positioning four shelving units together, two units at a right angle to the other two units. Each of the four shelving units contained 72 medications: 17 Merck medications representing all available strengths of the six medications (CRIXIVAN® [3 strengths], SINGULAIR® [3 strengths], HYZAAR® [3 strengths], JANUVIA® [3 strengths], JANUMET® [2 strengths], and COZAAR® [3 strengths]), and 55 non-Merck medications. Each shelving unit contained a single label design type for the six products (e.g., 2a or 2b) and the 17 Merck med- ications were positioned consistently on each shelving unit (e.g., the three COZAAR® bottles were always on the right side of the top shelf). The 55 non-Merck medications included both brand name and generic medications. The medications were alphabetized within the four shelving units, with brand and generic names intermixed. The bottles were partially filled with plain M&M® candies so that the bottles' weight and sound (when shaken) resembled that of actual medication bottles. Each test session lasted approximately 1 hour. Participants received little information regarding the study's purpose and sponsor to ensure par- ticipants were not biased when performing the tasks. Alternate labels designs 1 2a Modified version selected for summative usability testing (see Figure 4) 2b 3a 3b Key characteristic(s) Color band for dosage strength (yes/no) Yes Yes Yes No No Branded logotype (yes/no) No No Yes No No Color Band for NDC (yes/no) No No No Yes Yes Original Label Fig. 1. Label designs and key characteristics using SINGULAIR® as an example. Prescription Filling Times 0 2 4 6 8 10 12 Januvia 100 mg Janumet 50 / 500 mg Singulair 5mg Hyzaar 100 mg - 12.5 mg Crixivan 100 mg Cozaar 50 mg Drug Averagetime(seconds) 2a 2b 3a 3b 14 Fig. 2. The average time it took participants to fill prescriptions without distractions. The average time to retrieve the requested medication (excluding instances where the participant was distracted by a phone call or other interruption) was calculated. Single factor analysis of variance (ANOVA) was performed to identify any significant differences in retrieval time among the four label designs within each of the six Merck medications, for retrieving a certain medication within each of the label designs, and for retrieving Merck medications and non-Merck medications. 179J.M. Gerhart et al. / Journal of Safety Research 55 (2015) 177–184
  4. 4. 3.2.1. Prescription filling tasks Each test participant filled the same 10 prescriptions from each of the four shelving units (a total of 40 prescriptions) in a counterbalanced order. Six of the 10 prescriptions were for Merck medications, with three bulk (i.e., high-count) bottles and three unit-of-use bottles (typically containing a one month supply of the drug). The unit-of-use medications selected for this portion of the test were CRIXIVAN®, as this medication is not available in bulk packaging, as well as SINGULAIR® and HYZAAR®, as the relatively low color contrast of some dosage strengths as presented on the label (e.g., SINGULAIR® 5 mg, HYZAAR® 100–12.5 mg) created a worst-case scenario. Four prescriptions for non-Merck medications (Effexor XR®, Nexium®, sertraline HCL, and Valtrex®) were included to prevent participants from focusing solely on Merck products and each of these medica- tions' label presented information somewhat differently. Each participant read the prescription, placed the prescription on the interview table, walked to one of the shelving units (labeled A, B, C, or D), selected what they considered to be the correct medication, and then returned to the interview table. The time between placing the prescription form on the table and placing the medication on the table was recorded and the test administrator documented whether the participant retrieved the cor- rect medication. If the participant retrieved the incorrect medication, the test administrator did not notify him/her of the error until after the partic- ipant performed all tasks. The test sessions were video recorded and the test administrator intermittently took still photographs to document the test environment and participants' interactions with the medication bottles. Real-world conditions were simulated by playing a looping soundtrack of audible distractions representative of a retail environment (e.g., the sound of banging shopping carts and overhead announcements), as well as five interruptions by “customers” (role-played by the test administrator) and five simulated pharmacy phone calls in a randomized order. Participants did not commit any errors during the prescription filling tasks. However, there were four instances in which a participant selected the incorrect medication and then self-corrected: 1) within design 2b, one participant initially selected JANUVIA® 50 mg instead of JANUMET® 50 mg/ 500 mg; 2) within design 3b, the same participant as above initially retrieved JANUVIA® 100 mg instead of JANUVIA® 50 mg; 3) within design 2a, one participant first selected JANUMET® 50 mg/1000 mg then exchanged it for JANUMET® 50 mg/500 mg; 4) also within design 2a, one participant ini- tially chose CRIXIVAN® 400 mg before returning to the shelf to retrieve CRIXIVAN® 100 mg. There were no significant differences between the time it took participants to retrieve any of the Merck or non-Merck medications. Moreover, there were no significant differences in retrieval time between the six Merck medications or between the four label designs for each Merck medica- tion. The average retrieval time among the four label designs was 7.6–9.8 s (Fig. 2). 3.2.2. Label legibility assessment After completion of all the prescription filling tasks, participants stood 15 ft from the medication positioned on a pharmacy shelf and stepped for- ward in 1-ft increments, stopping briefly at each interval, until they were close enough to confidently state the medication's brand name and dosage strength. Participants were asked to read at a distance the medication's brand name and dosage strength for two examples of each label design (e.g. two examples of 2a, 2b, 3a, and 3b). A worst-case scenario was created by asking each participant to read unit-of-use labels, which are considerably smaller (2″ × 3.624″) than bulk labels (3.75″ × 3.0625″). The assessment included Merck labels that displayed dosage strengths in the lowest text-to- background color contrast, that is, the dose strength for a particular drug that had the lowest relative contrast between the dose strength text (in white or black) against the color band as determined by a computer-based color contrast analyzer tool (http://www.paciellogroup.com/resources/ contrastanalyser). For example, of the labels listed in Supplementary Fig. 1, the analyzer was used to determine which item from each row (which dose strength of each drug) had the lowest text-to-background ratio and this item was included in the legibility assessment to enable a worst- case assessment of the characters (numbers, hyphen, period) against the color band. The six Merck medications with product dose strengths that participants might have become familiar with while performing directed retrieval tasks were excluded. The participants' final distances from the Table 1 Characteristics of the study participants (self-reported data). Characteristic Formative usability test N = 8 Validation test N = 25 Mean age (range)—yr 39 (22–57) 35 (18–65) Gender—no. (%) Male 3 (38) 10 (40) Female 5 (62) 15 (60) Occupation—no. (%) Pharmacist 4 (50) 10 (40)⁎ Technician 4 (50) 15 (60)† Current pharmacy type—no. (%) Chain drug store Not recorded 22 (88) Outpatient hospital Not recorded 1 (4) Independent Not recorded 1 (4) Long-term care Not recorded 1 (4) Mean retail pharmacy experience (range) – yr 13 (3–33) 12 (.17–50) 0–5—no. (%) Not recorded 9 (36) 5–15—no. (%) Not recorded 10 (40) 15+—no. (%) Not recorded 6 (24) Mean shift length (range) – hr 9 (8–12) 9 (6–12) Mean personal no. scripts filled per shift (range) 109 (40–200) 141 (20–325) Mean pharmacy no. scripts filled per shift (range) 335 (75–700) 286 (70–575) NDC number verification method—no. (%) Scanning barcode and reading label Not recorded 13 (52) Scanning barcode only Not recorded 12 (48) ⁎ Includes 3 pharmacy managers. † Includes 4 pharmacy interns. 180 J.M. Gerhart et al. / Journal of Safety Research 55 (2015) 177–184
  5. 5. medication and the reported brand name and dosage strength were recorded. The minimum, maximum, and average reading distances were calcu- lated at which participants accurately reported the brand name and dosage strength. The legibility assessment included a total of 64 trials (8 participants × 8 labels), and 16 trials per label design (8 participants × 2 sample labels). There were no significant differences between the distances at which participants accurately read each medication's brand name and dosage strength (Fig. 3). The closest average reading distance was 6 ft 5 in. (JANUMET® 50 mg/1000 mg, design 2b) and the farthest distance was 8 ft 3 in. (JANUVIA® 100 mg, design 2a). The overall average reading distance was 7 ft 5 in. 3.2.3. Label ranking, comparison, and subjective feedback interview After each participant performed the retrieval tasks and label legibility assessment, the test administrator asked him/her to indicate a preference among the four label designs. Specifically, the participant was asked to indicate his/her preference based on: 1) legibility—how easy/difficult it was to read and understand the letters and symbols in the medication's brand name, generic name, and dosage strength; 2) readability—how easy/difficult it was to read the label's content based on the spacing, font, color, and the use of white space; 3) discriminability—how easy/difficult it was to distinguish between the labels for different medications; 4) how easy/difficult it was to read the NDC number on the label; and 5) overall preference considering all design attributes. To facilitate this preference-focused interview, each participant was shown four display boards (one for each label design) for JANUVIA® 50 mg, SINGULAIR® 4 mg, and HYZAAR® 100–12.5 mg. Each participant was asked to arrange the boards in order of their preference according to the above criteria. After ranking the designs, participants were asked to explain their preferences. The test administrator then asked a series of standard ques- tions, along with open-ended follow-up questions and requests for suggested improvements. Participants' preferences varied substantially among the four label designs with respect to legibility, readability, discriminability, and readability of the medication's NDC number. Five of the eight participants cited design 2b, which had the brand name in a stylized logo and the dosage strength on a color band, as their least favorite design because the colors and fonts used for the brand name, generic name, and dosage strength were distracting. However, six of the eight participants thought labels featuring the stylized, branded logos clearly differentiated the medications. Nearly all participants ranked label designs 2a and 3a in first or second place for readability. When asked whether readability or discriminability was more important, four participants asserted that readability was paramount. Participants' preferences varied regarding the NDC number presentation. Half of the participants preferred the use of a color band to highlight the NDC number, but others considered black or white text difficult to read on a col- ored background due to some text-background color combinations' relatively low contrast. The quantitative test data and participants' anecdotal feedback suggested that each of the four label designs were viable. The formative usability test data strongly favored design 3a because it maximized legibility; however, participants also preferred the designs that utilized color bands to highlight the dosage strengths to increase strength differentiation (i.e., designs 2a and 2b). WR&D and Med-ERRS' ultimately recommended utilizing a color band to differentiate dosage strengths, provided that care was taken to avoid duplication of color pairs for medications likely to be stored near each other and/or share similar names or strengths; the use of mid-range colors was avoided for the color bands; and text color (i.e., black vs. white) was adjusted to produce an acceptably high contrast between the text and the background. Based on these recommendations, a modified version of design 2a (Fig. 4) was chosen over design 3a. A complete display of the final modified design 2a for each medication, as well as colors selected for each medication and strength for the initial label review, formative usability test, and validation test are shown in Supplementary Figs. 1 and 2. Average Reading Distance 0 1 2 3 4 5 6 7 8 9 10 11 12 13 Januvia 100 mg (2a) Hyzaar 100 mg -25 mg (2a) Singulair 4 mg (2b) Janumet 50 mg / 1000 mg (2b) Cozaar 25 mg (3a) Crixivan 200 mg (3a) Hyzaar 50 mg - 12.5 mg (3b) Januvia 25 mg (3b) Drug (design) DisancefromShelf(feet) Fig. 3. The minimum, maximum, and average distances at which participants accurately reported the brand name and dosage strength. Error bars represent the minimum and maximum reading distances. 181J.M. Gerhart et al. / Journal of Safety Research 55 (2015) 177–184
  6. 6. 3.3. Validation testing Based on the results of the formative usability test and following the FDA's recommendation to apply human factors, a single label design was selected for validation testing (modified 2a, Fig. 4). The purpose was to validate that the new label design presented critical information in a manner that enables prospective users to accurately identify and retrieve a prescribed Merck medication from a set of stocked shelves in a simulated phar- macy setting. WR&D recruited and compensated 10 pharmacists and 15 pharmacy technicians from the Metropolitan Boston area. Individuals who participated in the formative test were excluded. Participants' ages ranged from 18 to 65 (average = 35 years), 15 (60%) were women, and retail pharmacy ex- perience ranged from 2 months to 50 years (average = 12 years) (Table 1). One participant reported being legally blind in his left eye, but that his monocular vision did not affect his ability to fill prescriptions. No other physical impairments were reported. The test environment and conditions were identical to that used for the formative test. The four shelving units contained a total of 384 medica- tions: 17 Merck medications (all available strengths of the six products, Supplementary Fig. 1) and 367 non-Merck medications (brand and generic). The medications were alphabetized with brand and generic names intermixed. Each medication was grouped in a set of alternative dosage strengths as done in retail pharmacies. As in the formative usability test, each of the non-Merck medications' labels presented critical information (i.e., brand name, generic name, and dosage strength) somewhat differently. Two WR&D staff administered the test sessions and documented test data in real-time. Representatives from Med-ERRS® and Merck observed the test sessions, each of which lasted approximately 45 min. Participants were given little information regarding the study's purpose and sponsor. 3.3.1. Prescription filling tasks Each participant filled 40 prescriptions (17 Merck; 23 non-Merck) in a randomized order. The 17 Merck medications were unit-of-use bottles fea- turing the new label design. Participants were directed to retrieve the exact medication requested and not to make substitutions, as is common prac- tice when a generic equivalent is available. Increased prominence of NDC code Enlarged brand and generic name Unique color band to highlight dosage strength with sufficient contrast Improved 3-dimensional picture of the tablet or capsule so that the imprint on the tablet or capsule is visible. Lot number and expiration date in contrasting text and moved to more prominent location. Manufacturer information moved to less prominent location Final Revised Label (Modified 2a) Original Label Enlarged 4-digit product code Moved Rx only statement to primary surface. Created consistent location for tablet count. Fig. 4. Comparison of original and final, revised label, using SINGULAIR® as an example. The picture of the final label represents the availability of the product at the time the new label design was approved by the FDA. 182 J.M. Gerhart et al. / Journal of Safety Research 55 (2015) 177–184
  7. 7. The participant read the prescription aloud (to enable the test administrator to ensure the participant did not misread the medication name), then placed the mock prescription on the interview table. Next, the participant walked to the stocked shelves, selected what he/she considered to be the correct medication bottle, and placed the bottle on the prescription form on the interview table. Participants were permitted to review the mock pre- scription if needed before finalizing their medication selection. If the participant retrieved the incorrect medication, the test administrator did not notify him/her of the error until after the participant performed all tasks. Real-world conditions were simulated in the same manner as the formative testing, and 10 of 40 tasks were interrupted with in-person or tele- phone interruptions presented in a random manner during the 40 tasks. All 25 test participants successfully retrieved each of the 17 Merck medica- tions requested on the mock printed prescription forms. Two participants retrieved the incorrect medication bottle when seeking a non-Merck medication. One participant (a pharmacy technician with 2 months of experience) selected the wrong dosage of Levothyroxine, retrieving the bottle for 0.025 mg instead of 0.125 mg in a task not featuring a customer service interruption. The second participant (a pharmacy technician with 11 years of experience) retrieved Amlodipine 5 mg instead of Norvasc 2.5 mg. Amlodipine is the generic version of Norvasc, the requested medication, and the participant had been instructed to retrieve Amlodipine 5 mg 23 trials earlier. This occurred after the participant fielded a simulated pharmacy call. In several instances, participants selected the incorrect bottle and then self-corrected, a behavior observed more during the distracted tasks than during non-distracted tasks. After completing retrieval tasks, participants responded to open-ended questions to collect their impressions of the label design's overall appro- priateness and suitability for use in pharmacies. The exit interview questions were: 1) Please summarize your opinion of the basic label design as reflected in these samples. 2) Do you feel the label designs would enable you to correctly identify the medication bottle's contents? 3) From a safety standpoint, can you think of any changes that have to be made to this label design before it is brought to market? 4) Do you have any suggestions as to how a manufacturer should introduce a new label design for an existing medication into retail pharmacies? Specifically, what should be done to alert pharmacy staff to the change and reduce the chance of confusion during the transition period? Participants' anecdotal feedback from the exit interview was reviewed and consolidated. Participants unanimously reported that the proposed label design would effectively enable them to correctly identify the medication. Although participants were not specifically asked why they regarded the label design as effective, three individuals volunteered that the different color bands would facilitate differentiation and three other individuals attributed the labels' effectiveness to the realistic tablet image. One participant commented that the NDC number was clearly displayed at the top of the label. 4. Conclusions The changes made to the medication labels in this study are in line with the April 2013 U.S. FDA Draft Guidance for Industry, “FDA Safety Consid- erations for Container Labels and Carton Labeling Design to Minimize Medication Errors” (US Food and Drug Administration, n.d.-a). In the draft guid- ance, the FDA proposes that the critical product information that should appear on the principal display panel (PDP) should include the brand name, established name or proper name, product strengthroute(s) of administration, and warnings (if any) or cautionary statements (if any). Other infor- mation on the PDP such as the “Rx only” statement, net quantity statement, and manufacturer name and logo should not compete in size and prom- inence with the above information. The guidance also emphasizes that text highlighted by color should have adequate color contrast. Product labeling is among the most important tools to assist pharmacists. A label should be designed in such a way that product selection and dispensing tasks are performed accurately in order to help ensure patient safety. The goal of this project was to develop a scientific approach to label design through human factors engineering and usability studies and based on feedback from the FDA. The approach included collaboration with independent experts from a medication safety company as well as a human factors engineering firm. Prior to the usability test phase of the pro- ject, an initial assessment of the current and proposed package label designs identified strengths and potential areas of concern that might increase the risk of a dispensing error. The independent experts then designed and conducted a preliminary (i.e., formative) usability study of four package label designs developed based on the initial label assessment. The resulting quantitative and qualitative data informed the selection and refinement of the final design that was subsequently validated. The validation suggests that the final label design could be safe and effective for use in an outpa- tient pharmacy setting. In designing the labels, patient safety was a primary consideration, thus we focused on several key attributes. In compliance with 21CFR§201.10(g) (1) (2), the generic name appears in parentheses below the brand name in a specific size ratio of slightly larger than half the size of the brand name. A sans serif type style was selected as it is a clear and legible typeface that works well in regular, bold, italic, and condensed styles. In selecting the colors for highlighting the dosage strength, there were instances when it was necessary to deviate from the brand colors to ensure sufficient brightness against the white background, an adequate contrast ratio of text to background color, and to ensure that within a given product line, strengths are sufficiently distinct from one another, and between products that share similar names and/or strengths. The opti- mized label also replaced the former two-dimensional line drawing used to represent the tablet or capsule with an enhanced three-dimensional image. The new label was developed as a result of research conducted directly with pharmacists and pharmacy technicians to further support the accu- racy of medication dispensing; however, the study is accompanied by some limitations. It was conducted in the Boston area, which may not be re- flective of the U.S. pharmacy system as a whole. In addition, the rank ordering of the label designs in the formative test potentially unblinded the participant to the purpose of the study and the sponsor. In the validation testing, participants were generally pleased by the new label design. They commented positively on how the new label design presented critical information – specifically the medication's brand name, generic name, and dose strength – in large, bold text. Most participants complimented the vivid color bands forming the background to the dose strength and hypothesized that the color bands would enable them to ef- fectively differentiate between different medications. Participants also valued the realistic tablet image – displayed prominently on the label's front panel – as an additional means of differentiation. On June 10, 2011, the U.S. FDA approved Merck's redesigned drug container labels noting that they include an enhanced format to improve read- ability and that they provide better information on product and strength differentiation (http://www.fda.gov/NewsEvents/Newsroom/ PressAnnouncements/ucm258725.htm, n.d.). To better access the impact of these label changes, the FDA encourages health care providers to report medication errors related to the products included in Merck's Label Redesign Project to MedWatch, the FDA's adverse event reporting program. 183J.M. Gerhart et al. / Journal of Safety Research 55 (2015) 177–184
  8. 8. Practical applications These revised labels could improve the accurate selection of medications from pharmacy shelves. Funding and conflicts of interest The study was funded by Merck. The authors report the following conflicts of interest. Julie M. Gerhart, Holly Spriggs, Tonja W. Hampton, and Rose Mary B. Hoy, are employees of Merck and hold stock/stock options. Debra B. Goetchius is a former employee of Merck and holds stock/stock options. Susan Proulx is an employee of Med-ERRS®, which was retained by Merck to evaluate the proposed label designs. Allison Strochlic is an employee of Wiklund Research & Design, which was retained by Med-ERRS to concurrently conduct an expert review of the same package labels. Acknowledgements We thank Heather L. Sings (Merck) for assistance in the preparation of this manuscript and Sheila Erespe (Merck) for assistance with submission. We also thank Stephanie DeGraw (Med-ERRS Inc) and Michael Wiklund (WR&D, now a UL LLC company) for their contributions to this work. References Abood, R. R. (1996). Errors in pharmacy practice. US Pharmacist, 21(3), 122–130. Aspden, P., Wolcott, J., Bootman, J. L., Cronenwett, L. R., Aspden, P., Wolcott, J. A., Bootman, J. L., & Cronenwett, L. R. (Eds.). (2006). Preventing Medication Errors. Institute of Medicine. Washington DC: The National Academies Press (Chapter 6:275. Available at http://www.nap.edu/catalog/11623.html. Accessed May 10, 2013). Chapter 29 – Human factors risk management for medical products, failure mode and effects analysis. Handbook of Human Factors and Ergonomics in Health Care and Patient Safety, Second Edition; Edited by Pascale Carayon, 2012:479–487. FDA News Release. FDA approves redesigned labels for some Merck drugs. Available at http://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm258725.htm. Accessed May 10, 2013. Flynn, E. A., Barker, K. N., & Carnahan, B. J. (2003). National observational study of prescription dispensing accuracy and safety in 50 pharmacies. Journal of the American Pharmaceutical Association (Washington), 43(2), 191–200. Gianutsos G. Identifying factors that cause pharmacy errors. Available at http://www.uspharmacist.com/continuing_education/ceviewtest/lessonid/105916. Accessed May 14, 2013. Kohn, L. T., Corrigan, J. M., & Donaldson, M. S. (2000). (Institute of medicine) to err is human: building a safer health system. Washington, DC: National Academy Press. United States Food and Drug Administration website. Available at http://www.fda.gov/drugs/drugsafety/medicationerrors/default.htm. (Accessed May 8, 2013). US Food and Drug Administration. Safety considerations for product design to minimize medication errors. (Available at http://www.fda.gov/Drugs/ GuidanceComplianceRegulatoryInformation/Guidances/ucm331808.htm. Accessed April 25, 2013). US Food and Drug Administration. Draft guidance for industry and food and drug administration staff—Applying human factors and usability engineering to optimize medical device de- sign. (Available at http://www.fda.gov/downloads/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocuments/UCM259760.pdf. Accessed January 27, 2015). Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx.doi.org/10.1016/j.jsr.2015.08.005. Julie M. Gerhart is currently at Merck. She obtained her master of science in pharmacy in 1994 from the Philadelphia College of Pharmacy and Science and her master of science in bio- medical writing in 2005 from the University of the Sciences in Philadelphia. Holly Spriggs is currently at Merck. She obtained her bachelors of fine arts in graphic design from The College of New Jersey in 1996. Tonja W. Hampton is currently at Merck. She obtained her MD from the University of North Carolina-Chapel Hill in 1990. Rose Mary B. Hoy is currently at Merck. She obtained her pharmacy degree from the Philadelphia College of Pharmacy & Science in 1982. Allison Y. Strochlic is currently at WR&D, now a UL LLC company. She obtained her master of science in human factors in information design from Bentley University in 2007. Susan Proulx is currently at Med-ERRS. She obtained her pharmacy degree from Northeastern University in 1990. Debra B. Goetchius is a former employee of Merck. She obtained her bachelor of science in biology from Montclair State University in 1980. 184 J.M. Gerhart et al. / Journal of Safety Research 55 (2015) 177–184

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