Journal of Medical Engineering & Technology
ISSN: 0309-1902 (Print) 1464-522X (Online) Journal homepage: http://www.tandfonline.com/loi/ijmt20
An analytical approach to identifying potential use-related issues concerning a medical device under development Suresh P. Gupta & Andy Pidgeon To cite this article: Suresh P. Gupta & Andy Pidgeon (2016) An analytical approach to identifying potential use-related issues concerning a medical device under development, Journal of Medical Engineering & Technology, 40:3, 61-71, DOI: 10.3109/03091902.2015.1132785 To link to this article: http://dx.doi.org/10.3109/03091902.2015.1132785
Published online: 21 Jan 2016.
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Date: 31 May 2016, At: 23:20
JOURNAL OF MEDICAL ENGINEERING & TECHNOLOGY, 2016 VOL. 40, NO. 3, 61–71 http://dx.doi.org/10.3109/03091902.2015.1132785
INNOVATION
An analytical approach to identifying potential use-related issues concerning a medical device under development Suresh P. Gupta and Andy Pidgeon
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Cambridge Consultants, Cambridge, UK
ABSTRACT
ARTICLE HISTORY
Identifying potential use-related issues at the onset of the design process of a medical device can reduce use errors, enhance safety and improve usability of the product. Regulatory bodies such as the US Food and Drug Administration (FDA) suggest manufacturers should investigate use-related problems that have occurred in the past with devices that are similar to the one under development. Publically available device incident databases, such as the FDA’s Manufacturer and User Facility Device Experience (MAUDE) database, are a good source of information. However, haphazard searches of these databases can be confounding and unproductive. This paper presents a systematic approach to conducting the database searches, analysing the data and reporting the findings in a meaningful way. The approach outlined in this paper is an extract of the methodology that has been effectively implemented in a number of medical products that are already on the market, in submission or under development.
Received 23 September 2015 Revised 3 December 2015 Accepted 13 December 2015 Published online 21 January 2016 KEYWORDS
Medical device; human factors; use error; safety; effectiveness
1. Introduction The use of medical devices for diagnosis, monitoring and treatment of patients is increasing.[1] These devices are not only used by healthcare professionals, but also by lay users outside professional healthcare facilities for a variety of reasons such as the ageing population and the prevalence of chronic diseases.[2] Medical devices by their very nature are intended to improve and save lives. However, each year the FDA receives a large number of reports of suspected adverse incidents and device malfunctioning.[3] Reports compiled by the FDA suggest that as many as one-third of device failures that resulted in sub-optimal medical treatment, injuries and even deaths can be attributed to use-related failures (use errors) rather than failure of the devices themselves.[4] Many of these use errors can be and should be eliminated or reduced by implementing effective human factors and usability engineering (HFE/UE) principles and processes into the design of the products. In recent years, the FDA and other regulatory bodies have required manufacturers of medical devices to demonstrate that they have incorporated HFE/UE into their design process. The application of HFE/UE helps manufacturers to develop medical devices that reduce use errors, enhance patient and user safety, improve product usability and efficiency and enhance user satisfaction.[4] The FDA in 2011 developed a guidance document for the industry which presents the Agency’s CONTACT: Suresh P. Gupta ! 2016 Taylor & Francis
[email protected]
current thinking on how HFE/UE should be applied to the medical device development process.[5] The European Union (EU) regulatory bodies have also produced a similar standard on the application of usability engineering to medical devices.[1] Both of these documents lay the foundation for the HFE/UE process for the development of medical devices. One of the early stage human factors activities that both the FDA and EU documents suggest is to understand use-related issues that have occurred in the past with devices that are similar to the one under development.[5] Understanding use-related issues at the onset of the design process of a new medical device produces a number of benefits: These issues can be addressed in the design of the new device in order to minimise use errors. The information contributes to the product’s risk management process which is an integral part of the development process. It fulfils the FDA and EU requirements for a submission. The information could also potentially generate ideas for a new product. The FDA guidance suggests that information regarding the use-related issues can be obtained by contacting users of existing devices and the training and sales staff that are familiar with issues encountered by users. The other
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methods that the document suggests are more analytical. These methods include reviewing customer complaint files, published articles and searching relevant databases. Although getting information from users, training and sales staff of similar devices is a good way of getting rich and first-hand user experience data, the sample of these users needs to be broad and large enough to identify a good breadth of prevalent use-related issues. This method could also be time-consuming, costly and may only identify a limited number of use-related issues. Similarly, customer complaints data for existing devices on the market may be very difficult to acquire unless they are related to the manufacturer’s own existing products. Other analytical methods such as reviewing published articles may also have a very limited success, as articles that provide use-related issues with medical devices are sparse. The search of databases of reported medical device incidents may identify a good range of use-related issues with minimum time and budget. Some of these databases contain a very large number of reports that can be searched and retrieved over the internet free of cost. This paper focuses on this particular method. No one single method can reveal all use-related issues and each method has its own advantages and limitations. Therefore, the authors encourage the designers and manufacturers of medical devices to consider all suitable methods within their budget and resources. The FDA guidance document[5] provides a list of databases, as presented below. However, neither the FDA nor the EU document provides any method or approach to conduct the search of these databases. Random and haphazard searches of these databases can be confusing, inefficient and unproductive. Therefore, this paper presents a systematic approach to conducting the database search, analysing the data and reporting the findings in a meaningful way. FDA’s Manufacturer and User Facility Device Experience (MAUDE) database; FDA’s Medical Device Reporting (MDR) Program Search; FDA’s Adverse Event Reporting Data Files; FDA’s MedSun: Medical Product Safety Network; CDRH Medical Device Recalls; CDRH Alerts and Notices (Medical Devices); CDRH Public Health Notifications; ECRI’s Medical Device Safety Reports; The Institute of Safe Medical Practices (ISMP’s) Medication Safety Alert Newsletters; and The Joint Commission’s Sentinel Events. There are other sources, such as the UK Medicines and Healthcare Regulatory Agency (MHRA) website, internet forums, blogs and search engines that may also be useful to explore.
The paper first presents the overview of the proposed approach followed by detailed discussion on each element of the approach. The people who would conduct this type of research are referred to as researchers in this paper. The approach discussed in this paper is applicable to any medical product. However, for the purpose of facilitating the discussion, an example of a new autoinjector for the treatment of rheumatoid arthritis (RA) has been used. An autoinjector is generally a spring-loaded handheld device that, upon activation, inserts a needle and delivers a dose of medication automatically into a patient’s skin. Autoinjectors are widely used by patients and their caregivers, as well as by healthcare professionals for the treatment of RA. Readers should imagine that a manufacturer is developing a new single-use, disposal autoinjector for RA and wants to identify use-related issues with current autoinjectors on the market so that they could be addressed in the new device. The approach discussed in this paper is original and the authors are not aware of any other similar paper in this area.
2. Overview of proposed approach The overview of the proposed approach for identifying use-related isssues with existing medical devices similar to the one under development is depicted in Figure 1.
Figure 1. Overview of the proposed approach to identifying use-related issues.
JOURNAL OF MEDICAL ENGINEERING & TECHNOLOGY
2.1. Understand device landscape
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The first step in the process is to understand the landscape of products on the market that are ‘similar’ to the one under development. The quality of this activity determines the quality of the search results later in the process. On the one hand, if the scope is limited to a very narrow range of devices, the search of the databases may only identify fewer types of use-related issues. On the other hand, if the scope is too broad such that it includes devices that have little or no similarity to the one under development, the search may result in diminishing returns. An approach to how similar devices can be identified effectively is presented in Figure 2. There are two stages in identifying similar devices on the market—exploring the therapeutic area and then identifying the relevant devices.
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therapy and what devices are used for delivering these drugs or treatments. At this stage, not all devices identified will be relevant. The process is explained in detail with an example below. Let us imagine that a manufacturer wants to develop an autoinjector for the treatment of rheumatoid arthritis (RA). An internet search will reveal that there are mainly two types of treatments—disease-modifying antirheumatic drugs (DMARDs) which are mainly oral tablets, and biological treatments which are primarily injectable drugs such as etanercept, infliximab, adalimumab, certolizumab, golimumab, rituximab, abatacept and tocilizumab.[6] Within the injectable drugs market, there are drugs that are available in vials, pre-filled syringes (PFS) and/or autoinjectors. Not all of these delivery mechanisms are of interest to us.
2.1.2 Identifying the relevant devices 2.1.1 Exploring the therapeutic area The starting point is to understand what drug or treatment the device under development is intended to provide. The next steps are to investigate what other drugs or treatments are on the market for the same
Following the identification of all the drugs and treatments available on the market and the devices used to deliver these drugs and treatments, devices that are relevant to the device under development should be identified. First, all devices that are in the therapeutic
Figure 2. An approach to understanding device landscape for further analysis.
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area and similar to the device under development should be identified. These devices should be in the ‘first priority’ list for further investigation. Some devices may be used for drugs or treatments that are different from the therapeutic area that the manufacturer is interested in. It is not uncommon to find different drug products supplied with the same type of device. These devices make the ‘second priority’ list. Moreover, the manufacturer may also be interested in investigating devices that fall within the family of the device under development, e.g. single-use, disposable autoinjectors. The list of these devices is the ‘third priority’ list. The authors encourage manufacturers to explore all three priority lists, but their decision may depend on their budget and resources. In our example above, oral tablets, pre-filled syringes and vials are of little or no interest to us. Therefore, by the method of elimination, the list is shortened to injectable drug products that use autoinjectors. There are primarily three single-use, disposable autoinjectors for the treatment of rheumatoid arthritis on the market—EnbrelÕ (etanercept), HumiraÕ (adalimumab) and SimponiÕ (golimumab). These three autoinjectors, as shown in Figure 3, form the first priority list. At the time of writing this paper, CimziaÕ (Certolizumab pegol) did not have an autoinjector. EnbrelÕ (etanercept) is an Amgen drug product which comes in an autoinjector named SureClickÕ . There are other drug products that also use the SureclickÕ autoinjector. AranespÕ (darbepoetin alfa), a drug product for treating patients with anaemia due to chemotherapy, and NeulastaÕ (pegfilgrastim), a drug product to decrease the incidence of infection, use the SureClickÕ autoinjector. These devices form the second priority list. The NeulastaÕ autoinjector may now have been recalled from the market, but any past incidents
may still be of interest to the researchers. The authors are not aware of any other drug products in the HumiraÕ or SimponiÕ autoinjectors. All of the autoinjectors in the first and second priority lists are single-use, disposable autoinjectors. There are other autoinjectors on the market that fall within this family of autoinjectors which might be of interest to the manufacturer. For example, Rebif RebidoseÕ (interferon beta-1a) and Avonex PenÕ (interferon beta-1a) are single-use, disposable autoinjectors for the treatment of multiple sclerosis (MS). Likewise, EpiPenÕ (epinephrine), epinephrine injection USP autoinjectorÕ (epinephrine), AnaPenÕ (adrenaline) and TwinJectÕ (epinephrine) are for the treatment of anaphylaxis. AnaPenÕ and TwinJectÕ may have been recalled from the market, but any use-related incident reports may still be useful. All of these devices form the third priority list. Figure 4 summarises the landscape of devices that are similar and relevant to our example autoinjector. Once all the relevant devices are identified, the researchers should attempt to understand how these devices work and how users are intended to use them. This will help understand the incident reports from the databases.
2.2. Identify search terms People from different backgrounds—e.g. healthcare professionals, clinical engineering staff, pharmacists, patients and caregivers—report device incidents in different ways. They may also refer to the devices they report with different names and terms. Whilst searching the databases, it is important to understand the ways in which these people refer to the devices in question. Some people may use the brand name, such as EnbrelÕ , HumiraÕ and SimponiÕ ; whereas others may use the drug’s generic name, e.g. etanercept, adalimumab and golimumab, or even the drug manufacturer’s name. Some users may also use the device name, e.g. SureClickÕ and/or the device manufacturer’s name, e.g. SHL for SureClickÕ . Some people, especially lay users, may also use the device’s generic family name and disease name, e.g. ‘‘autoinjector for rheumatoid arthritis’’. Therefore, a broad range of search terms should be used to search the databases for use-related issues. This paper suggests the following search terms:
Figure 3. Autoinjectors for the treatment of rheumatoid arthritis.
Drug brand name; Drug generic name; Drug manufacturer’s name; Device name (if any); Device manufacturer’s name (this can be different from drug manufacturer’s name); Device generic name, e.g. autoinjector; and
JOURNAL OF MEDICAL ENGINEERING & TECHNOLOGY
Disease or condition name, e.g. rheumatoid arthritis (RA). The above search terms should be used on their own as well as in combinations.
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2.3. Search databases and tabulate results The approach of searching the available databases and tabulating the results is depicted in Figure 5. The authors of this paper encourage researchers to search as many databases as possible. The FDA’s Manufacturer and User Facility Device Experience (MAUDE) database is a good starting point as this database is likely to identify the majority of device-related incidents in the U.S. It is likely that some reports will appear in more than one database. Researchers should use individual search terms as well as combinations of search terms to facilitate the search process. Each search term (or a combination of terms) is likely to return a number of device incident reports, some of which may be relevant, others may not. The researcher must read the contents of the reports in order to distinguish the relevant ones. If a search term
returns a large number of reports, the researchers may use the ‘‘find’’ tool of their internet browser to check the context in which the search term has appeared in the report. Sometimes the search term is mentioned in the report, which does not have much significance to the incident itself. For example, a report describing a fault with an IV line with a patient in hospital may also mention the patient’s background information, e.g. the patient uses EnbrelÕ amongst other medication at home. This type of report is clearly not relevant to us. Each relevant report or the relevant part of the report should be tabulated on a spreadsheet with the search information, such as the search term, database name, time and date of report and web link. The process is explained in detail with our example autoinjector below. Let us search the FDA’s MAUDE database for the search term SureClickÕ , as shown in Figure 6. The search returns three reports, as shown in Figure 7. Two reports relate to EnbrelÕ , which is in our first priority list, and the third relates to AranespÕ that is in our second priority list.
Figure 4. Landscape of devices relevant to the example autoinjector for rheumatoid arthritis.
Figure 5. Process of searching databases and tabulating results.
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Figure 6. FDA’s MAUDE database being searched for ‘‘SureClick’’, accessed on 23 September 2015.[3].
Figure 7. Search returns for ‘‘SureClick’’ from FDA MAUDE database, accessed on 23 September 2015.[3].
The next step is to read the reports and identify if they are relevant. Figure 8 shows an excerpt from one of the reports above. The report suggests that some patients ‘‘returned their products saying that the injectors locked and failed
to discharge medication’’. No specific details have been provided and this issue could well be a manufacturing defect. However, if the researchers are familiar with the functioning and use of the SureClickÕ autoinjector, it is plausible to imagine that this issue could arise from a
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Figure 8. An incident report from FDA’s MAUDE database, accessed on 23 September 2015.[3].
use error. SureClickÕ has a safety guard at the needle end that needs to be fully depressed into the autoinjector body by pressing it against the injection site in order to unlock the injection button. If the injection button on the top of the device is pressed before the safety guard has been fully depressed, the mechanism can jam and the device will neither unlock nor activate until the user releases the button, starts the process again and follows the correct sequence. Therefore, this report might be relevant. The next step in the process is to record all relevant search results, preferably in a tabular form, as show in Figure 9. The authors of this paper encourage researchers to search all available databases with all search terms. However, this will depend on how much time and resources are available.
2.4. Analyse search results The approach of analysing the search results is depicted in Figure 10. The tabulation of relevant use-related incident reports may itself be sufficient to highlight the potential userelated issues pertaining to the medical device under development. However, if the number of reports is large and the reports themselves are not specific, it may be beneficial to further analyse the data and present the results in a meaningful way. This paper suggests the use
of the principle of open coding.[7] In this process, the researchers analyse the excerpts of the relevant incident reports in an attempt to develop early ‘‘concepts’’ based on their understanding of the functionality and uses of the devices. The process of development of an early concept consists of identifying units of data, e.g. key words, phrases, sentences or paragraphs in the reports that represent or are examples of a common use issue[8] and attaching a code to it. A code is a term given by the researchers to a concept. At this stage of analysis the coding is ‘‘unfocused’’ and ‘‘open’’and the researchers may generate a number of codes.[9] These codes are temporal and are likely to be changed as the analysis progresses.[10] The open coding method and the generation of concepts for our example-autoinjector are demonstrated in Figure 11. Once all the initial concepts are identified and coded, these concepts are constantly compared with one another so as to explore similarities and differences across them.[7] This is an iterative process and many early concepts may undergo a series of changes—some are merged while others are split; some may be renamed, and others restructured. The idea is to group concepts that describe a similar use issue, to form a ‘‘category’’. Categories are of a higher and more abstract order than are concepts and are closer to explaining a top-level use-related issue.[11] The third step of the analysis is to refine and finalise the categories. This may include exploring the categories
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Figure 9. An example of search results being recorded in a tabular form.
Figure 10. Process of analysing the search results.
in greater depth, which may result in further restructuring, refining, splitting, merging and eliminating of some existing categories, as well as the addition of the new ones. This process continues until saturation is reached. Saturation is the state in which the researchers make the subjective determination that further analysis will not provide any new insights.[10] The final categories form the basis for writing the report.
2.5. Report finding The report should present in a coherent manner all userelated issues found or inferred from the analysis of the device incident reports. The purpose of the report should not be to provide statistical data on the number or percentage of occurrence of these use errors. The report should focus on highlighting likely use-related issues that are either reported specifically or inferred by
the researchers. The purpose is to address these issues in the design of the device under development. The report should be written in a way that is understandable and useful to different types of prospective users of the report. The report should feed into the design and risk management process of the medical device under development for which this research has been done. Hence, it should be understandable and meaningful to the designers as well as to people who carry out risk management activities for the device. The report also forms part of the human factors and usability engineering (HFE/UE) report. The HFE/UE report is part of the Design History File (DHF), which is a requirement for submission to the FDA and other regulatory bodies for a market approval. The report should also describe the methodology, as described in this paper, so that the readers understand the methods and the underlying rationales that governed the selected methods. There may be various ways in which the use-related issues can be presented. This paper suggests that the ‘‘categories’’ developed in section 2.4 should be used as the top-level findings. These categories should then be elaborated with discussion and supported by excerpts from the incident reports, if necessary. Some top-level findings for our example autoinjector for the treatment of rheumatoid arthritis are presented below. Please note that these are for
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Figure 11. Demonstration of an open coding method of data analysis.
illustrative purposes only and do not present all userelated issues.
Some people can’t stand the pain the pen causes. If you’re like me, it’s the click that the pen makes that is so anxiety provoking.[13,p.1]
2.5.1. Device mix-up (look-alike mix-up) 2.5.3. Needlestick injuries There have been some reports on device mix-up due to the resemblance in their appearances of some autoinjectors. For example, an EpiPenÕ and an EpiPenÕ training device have been reported to have been accidentally used interchangeably, resulting in hazardous situations. A nurse opened a carton of EpiPens and administered what she thought was EPINEPHrine to a patient experiencing a severe infusion reaction to CARBOplatin. The pen was actually a trainer device that did not contain EPINEPHrine. The patient arrested and failed to regain consciousness. The trainer device is labelled as a trainer, but the font is small and the pens look very similar.[12,p.1]
2.5.2. Perceived pain and anxiety Some reports suggest that the appearance and feel of some autoinjectors can increase patients’ perceived pain and anxiety.
There are reports of needlestick injuries because users were confused about the needle end of the device and also how the device actually activated. A nurse unfamiliar with the new design of the EpiPen accidentally injected her thumb by pushing on the wrong end (orange tip) of the pen.[14,p.11]
2.5.4. Challenges to activate device and premature activations There are reports of difficulties, confusion and failures to activate a number of autoinjectors on the market. The issues are related to users not removing the safety feature; not pressing the device hard enough against the skin (these devices activate when pressed against the skin); not pressing the injection button hard enough (these devices activate when a button is pressed); and not following the correct sequence of use steps, e.g. where the device first needs to be unlocked by pressing
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against the skin and then activated by pressing the injection button. These confusions could also lead to accidental premature activation. Received 3 reports—(b)(6) 2011—from three patients who returned their products saying that the injectors locked and failed to discharge medication.[15,p.1]
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2.5.5. Premature removal from the injection site There have been reports of liquid seen on the skin, drops still coming out of the device and a spray of liquid in the air after removal of the device from the skin. These errors could result in an under-dose. The source of the error could potentially be in users removing the devices from the injection site prematurely. It is sometimes difficult even for experienced users to understand when the device should be removed from the skin, as the device feedback is either inadequate or misleading in many of these devices. As usual, I waited until a few seconds after the yellow marker appeared in the window, and pulled the pen away. When I did, a bunch of un-injected medicine dribbled onto the floor. I did have a tiny needle mark, so it’s possible that some of it injected, but I don’t know how much . . . if any.[16,p.1]
of the approach, it is believed to be applicable to a wide range of medical products. As with many research methods, there are certain limitations to this method too. The method in this paper relies primarily on publically available databases. Many of these databases are not specifically designed to capture use-related issues. They simply capture device and/or treatment related issues which may or may not be related to the use of a device. Therefore, the researchers would have to rely on their informed interpretations in order to elicit potential use-related issues from these reports. Also, people do not usually report usability issues, such as difficulties in using a device. They tend to blame themselves and develop coping strategies around the problems. In such circumstances, talking to users of existing devices may be more helpful. Therefore, although the method presented in the paper helps researchers to identify a good range of use-related issues with minimum time and budget, the authors encourage the designers and manufacturers of medical devices to consider other suitable methods too, as no one single method can reveal all use-related issues.
Acknowledgements The authors would like to thank Cambridge Consultants for its support in writing this paper.
Disclosure statement 3. Discussion and conclusion Understanding use-related issues with current and past medical devices that are similar to the one under development is an important aspect of the design process of a medical device. This helps to reduce and eliminate use errors, thereby making the product safer, more effective and usable. Regulatory bodies such as the FDA encourage manufacturers to investigate the known use problems as part of their human factors and usability engineering process. There are different ways in which this can be achieved. This paper has presented a systematic step-by-step approach to conducting this essential human factors activity. The method includes understanding the landscape of marketed devices relevant to the device in question, formulating effective search terms, searching the publically available medical device incident databases, analysing the data and reporting the findings in a meaningful way. The approach outlined in this paper is an extract of the methodology that has been effectively implemented to a number of medical products that are on the market, in submission or under development. Although an example of an autoinjector has been presented in this paper for the purpose of illustration, given the generic nature
The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.
References [1] International Electrotechnical Commission. 62366-1:2015 Medical Devices – Part 1: Application of usability engineering to medical devices. Brussels: European Committee for Electrotechnical Standardization; 2015. [2] US Food and Drug Administration. Draft guidance for industry and food and drug administration staff – Design considerations for devices intended for home use. Rockville (MD): US Food and Drug Administration; 2014. [3] MAUDE - Manufacturer and user facility device experience, medical report database [Internet]. US Food and Drug Administration; [cited 2015 Sep 23]. Available from: http://www.accessdata.fda.gov/scripts/cdrh/ cfdocs/cfmaude/search.cfm. [4] American National Standards Institute/Association for the Advancement of Medical Instrumentation. HE75:2009 Human factors engineering – Design of medical devices. Arlington, (VA): Association for the Advancement of Medical Instrumentation; 2009. [5] 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 design. Rockville (MD): US Food and Drug Administration; 2001.
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[6] Rheumatoid arthritis – treatment [Internet]. National Health Service; [cited 2015 Sep 23]. Available from: www.nhs.uk/Conditions/Rheumatoid-arthritis/Pages/ treatment.aspx. [7] Grounded theory: some reflections on paradigm, procedures and misconceptions [Internet]. Wolverhampton (UK): Management Research Centre, Wolverhampton Business School, University of Wolverhampton Goulding C; 1999 [cited 2015 Sep 23]. Available from: http:// www.ssnpstudents.com/wp/wp-content/uploads/2015/ 02/Grounded-theory.pdf. [8] Spiggle S. Analysis and interpretation of qualitative data in consumer research. J Consumer Res. 1994;21: 491–503. [9] Moghaddam A. Coding issues in grounded theory. Iss Educ Re 2006;16:52–66. [10] Gupta SP. Design and delivery of medical devices for home-use: Driver and challenges [PhD Thesis]. Cambridge (UK): Cambridge University; 2008. [11] Strauss AL, Corbin JM. Basics of qualitative research: Techniques and procedures for developing grounded theory. London: Sage Publications; 1998.
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[12] Quarterly Action Agenda [Internet]. Institution for Safe Medication Practices; 2014 [cited 2015 Sep 23]. Available from: http://www.ismp.org/Newsletters/acutecare/ActionAgendas_PDF/ActionAgenda1402.pdf. [13] Getting closer to myself, a blog post [Internet]. ‘‘Leslie’’; 2012 [cited 2015 Sep 23]. Available from: http://gettingclosertomyself.blogspot.co.uk/2012/07/humira-pen-isout-humira-pre-filled.html. [14] Medication errors: A year in review [Internet]. Institution for Safe Medication Practices; 2011 [cited 2015 Sep 23]. Available from: http://pharmacypracticenews.com/download/Med_errors_ppnse11_WM.pdf. [15] MAUDE adverse event report: Amgen Enbrel Sureclick 5mg injector [Internet]. Rockville, MD: US Food and Drug Administration; [cited 2015 Sep 23]. Available from http://www.accessdata.fda.gov/ scripts/cdrh/cfdocs/cfmaude/ Detail.CFM?MDRFOI__ID¼2484837. [16] My Humira Pen misfired, a web article [Internet]. Arthritis Insight; [cited 2014 Nov 13]. Available from: http://www.arthritisinsight.com/archives/test16504.htm.
ISSN: 0309-1902 (Print) 1464-522X (Online) Journal homepage: http://www.tandfonline.com/loi/ijmt20
An analytical approach to identifying potential use-related issues concerning a medical device under development Suresh P. Gupta & Andy Pidgeon To cite this article: Suresh P. Gupta & Andy Pidgeon (2016) An analytical approach to identifying potential use-related issues concerning a medical device under development, Journal of Medical Engineering & Technology, 40:3, 61-71, DOI: 10.3109/03091902.2015.1132785 To link to this article: http://dx.doi.org/10.3109/03091902.2015.1132785
Published online: 21 Jan 2016.
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Date: 31 May 2016, At: 23:20
JOURNAL OF MEDICAL ENGINEERING & TECHNOLOGY, 2016 VOL. 40, NO. 3, 61–71 http://dx.doi.org/10.3109/03091902.2015.1132785
INNOVATION
An analytical approach to identifying potential use-related issues concerning a medical device under development Suresh P. Gupta and Andy Pidgeon
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Cambridge Consultants, Cambridge, UK
ABSTRACT
ARTICLE HISTORY
Identifying potential use-related issues at the onset of the design process of a medical device can reduce use errors, enhance safety and improve usability of the product. Regulatory bodies such as the US Food and Drug Administration (FDA) suggest manufacturers should investigate use-related problems that have occurred in the past with devices that are similar to the one under development. Publically available device incident databases, such as the FDA’s Manufacturer and User Facility Device Experience (MAUDE) database, are a good source of information. However, haphazard searches of these databases can be confounding and unproductive. This paper presents a systematic approach to conducting the database searches, analysing the data and reporting the findings in a meaningful way. The approach outlined in this paper is an extract of the methodology that has been effectively implemented in a number of medical products that are already on the market, in submission or under development.
Received 23 September 2015 Revised 3 December 2015 Accepted 13 December 2015 Published online 21 January 2016 KEYWORDS
Medical device; human factors; use error; safety; effectiveness
1. Introduction The use of medical devices for diagnosis, monitoring and treatment of patients is increasing.[1] These devices are not only used by healthcare professionals, but also by lay users outside professional healthcare facilities for a variety of reasons such as the ageing population and the prevalence of chronic diseases.[2] Medical devices by their very nature are intended to improve and save lives. However, each year the FDA receives a large number of reports of suspected adverse incidents and device malfunctioning.[3] Reports compiled by the FDA suggest that as many as one-third of device failures that resulted in sub-optimal medical treatment, injuries and even deaths can be attributed to use-related failures (use errors) rather than failure of the devices themselves.[4] Many of these use errors can be and should be eliminated or reduced by implementing effective human factors and usability engineering (HFE/UE) principles and processes into the design of the products. In recent years, the FDA and other regulatory bodies have required manufacturers of medical devices to demonstrate that they have incorporated HFE/UE into their design process. The application of HFE/UE helps manufacturers to develop medical devices that reduce use errors, enhance patient and user safety, improve product usability and efficiency and enhance user satisfaction.[4] The FDA in 2011 developed a guidance document for the industry which presents the Agency’s CONTACT: Suresh P. Gupta ! 2016 Taylor & Francis
[email protected]
current thinking on how HFE/UE should be applied to the medical device development process.[5] The European Union (EU) regulatory bodies have also produced a similar standard on the application of usability engineering to medical devices.[1] Both of these documents lay the foundation for the HFE/UE process for the development of medical devices. One of the early stage human factors activities that both the FDA and EU documents suggest is to understand use-related issues that have occurred in the past with devices that are similar to the one under development.[5] Understanding use-related issues at the onset of the design process of a new medical device produces a number of benefits: These issues can be addressed in the design of the new device in order to minimise use errors. The information contributes to the product’s risk management process which is an integral part of the development process. It fulfils the FDA and EU requirements for a submission. The information could also potentially generate ideas for a new product. The FDA guidance suggests that information regarding the use-related issues can be obtained by contacting users of existing devices and the training and sales staff that are familiar with issues encountered by users. The other
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methods that the document suggests are more analytical. These methods include reviewing customer complaint files, published articles and searching relevant databases. Although getting information from users, training and sales staff of similar devices is a good way of getting rich and first-hand user experience data, the sample of these users needs to be broad and large enough to identify a good breadth of prevalent use-related issues. This method could also be time-consuming, costly and may only identify a limited number of use-related issues. Similarly, customer complaints data for existing devices on the market may be very difficult to acquire unless they are related to the manufacturer’s own existing products. Other analytical methods such as reviewing published articles may also have a very limited success, as articles that provide use-related issues with medical devices are sparse. The search of databases of reported medical device incidents may identify a good range of use-related issues with minimum time and budget. Some of these databases contain a very large number of reports that can be searched and retrieved over the internet free of cost. This paper focuses on this particular method. No one single method can reveal all use-related issues and each method has its own advantages and limitations. Therefore, the authors encourage the designers and manufacturers of medical devices to consider all suitable methods within their budget and resources. The FDA guidance document[5] provides a list of databases, as presented below. However, neither the FDA nor the EU document provides any method or approach to conduct the search of these databases. Random and haphazard searches of these databases can be confusing, inefficient and unproductive. Therefore, this paper presents a systematic approach to conducting the database search, analysing the data and reporting the findings in a meaningful way. FDA’s Manufacturer and User Facility Device Experience (MAUDE) database; FDA’s Medical Device Reporting (MDR) Program Search; FDA’s Adverse Event Reporting Data Files; FDA’s MedSun: Medical Product Safety Network; CDRH Medical Device Recalls; CDRH Alerts and Notices (Medical Devices); CDRH Public Health Notifications; ECRI’s Medical Device Safety Reports; The Institute of Safe Medical Practices (ISMP’s) Medication Safety Alert Newsletters; and The Joint Commission’s Sentinel Events. There are other sources, such as the UK Medicines and Healthcare Regulatory Agency (MHRA) website, internet forums, blogs and search engines that may also be useful to explore.
The paper first presents the overview of the proposed approach followed by detailed discussion on each element of the approach. The people who would conduct this type of research are referred to as researchers in this paper. The approach discussed in this paper is applicable to any medical product. However, for the purpose of facilitating the discussion, an example of a new autoinjector for the treatment of rheumatoid arthritis (RA) has been used. An autoinjector is generally a spring-loaded handheld device that, upon activation, inserts a needle and delivers a dose of medication automatically into a patient’s skin. Autoinjectors are widely used by patients and their caregivers, as well as by healthcare professionals for the treatment of RA. Readers should imagine that a manufacturer is developing a new single-use, disposal autoinjector for RA and wants to identify use-related issues with current autoinjectors on the market so that they could be addressed in the new device. The approach discussed in this paper is original and the authors are not aware of any other similar paper in this area.
2. Overview of proposed approach The overview of the proposed approach for identifying use-related isssues with existing medical devices similar to the one under development is depicted in Figure 1.
Figure 1. Overview of the proposed approach to identifying use-related issues.
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2.1. Understand device landscape
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The first step in the process is to understand the landscape of products on the market that are ‘similar’ to the one under development. The quality of this activity determines the quality of the search results later in the process. On the one hand, if the scope is limited to a very narrow range of devices, the search of the databases may only identify fewer types of use-related issues. On the other hand, if the scope is too broad such that it includes devices that have little or no similarity to the one under development, the search may result in diminishing returns. An approach to how similar devices can be identified effectively is presented in Figure 2. There are two stages in identifying similar devices on the market—exploring the therapeutic area and then identifying the relevant devices.
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therapy and what devices are used for delivering these drugs or treatments. At this stage, not all devices identified will be relevant. The process is explained in detail with an example below. Let us imagine that a manufacturer wants to develop an autoinjector for the treatment of rheumatoid arthritis (RA). An internet search will reveal that there are mainly two types of treatments—disease-modifying antirheumatic drugs (DMARDs) which are mainly oral tablets, and biological treatments which are primarily injectable drugs such as etanercept, infliximab, adalimumab, certolizumab, golimumab, rituximab, abatacept and tocilizumab.[6] Within the injectable drugs market, there are drugs that are available in vials, pre-filled syringes (PFS) and/or autoinjectors. Not all of these delivery mechanisms are of interest to us.
2.1.2 Identifying the relevant devices 2.1.1 Exploring the therapeutic area The starting point is to understand what drug or treatment the device under development is intended to provide. The next steps are to investigate what other drugs or treatments are on the market for the same
Following the identification of all the drugs and treatments available on the market and the devices used to deliver these drugs and treatments, devices that are relevant to the device under development should be identified. First, all devices that are in the therapeutic
Figure 2. An approach to understanding device landscape for further analysis.
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area and similar to the device under development should be identified. These devices should be in the ‘first priority’ list for further investigation. Some devices may be used for drugs or treatments that are different from the therapeutic area that the manufacturer is interested in. It is not uncommon to find different drug products supplied with the same type of device. These devices make the ‘second priority’ list. Moreover, the manufacturer may also be interested in investigating devices that fall within the family of the device under development, e.g. single-use, disposable autoinjectors. The list of these devices is the ‘third priority’ list. The authors encourage manufacturers to explore all three priority lists, but their decision may depend on their budget and resources. In our example above, oral tablets, pre-filled syringes and vials are of little or no interest to us. Therefore, by the method of elimination, the list is shortened to injectable drug products that use autoinjectors. There are primarily three single-use, disposable autoinjectors for the treatment of rheumatoid arthritis on the market—EnbrelÕ (etanercept), HumiraÕ (adalimumab) and SimponiÕ (golimumab). These three autoinjectors, as shown in Figure 3, form the first priority list. At the time of writing this paper, CimziaÕ (Certolizumab pegol) did not have an autoinjector. EnbrelÕ (etanercept) is an Amgen drug product which comes in an autoinjector named SureClickÕ . There are other drug products that also use the SureclickÕ autoinjector. AranespÕ (darbepoetin alfa), a drug product for treating patients with anaemia due to chemotherapy, and NeulastaÕ (pegfilgrastim), a drug product to decrease the incidence of infection, use the SureClickÕ autoinjector. These devices form the second priority list. The NeulastaÕ autoinjector may now have been recalled from the market, but any past incidents
may still be of interest to the researchers. The authors are not aware of any other drug products in the HumiraÕ or SimponiÕ autoinjectors. All of the autoinjectors in the first and second priority lists are single-use, disposable autoinjectors. There are other autoinjectors on the market that fall within this family of autoinjectors which might be of interest to the manufacturer. For example, Rebif RebidoseÕ (interferon beta-1a) and Avonex PenÕ (interferon beta-1a) are single-use, disposable autoinjectors for the treatment of multiple sclerosis (MS). Likewise, EpiPenÕ (epinephrine), epinephrine injection USP autoinjectorÕ (epinephrine), AnaPenÕ (adrenaline) and TwinJectÕ (epinephrine) are for the treatment of anaphylaxis. AnaPenÕ and TwinJectÕ may have been recalled from the market, but any use-related incident reports may still be useful. All of these devices form the third priority list. Figure 4 summarises the landscape of devices that are similar and relevant to our example autoinjector. Once all the relevant devices are identified, the researchers should attempt to understand how these devices work and how users are intended to use them. This will help understand the incident reports from the databases.
2.2. Identify search terms People from different backgrounds—e.g. healthcare professionals, clinical engineering staff, pharmacists, patients and caregivers—report device incidents in different ways. They may also refer to the devices they report with different names and terms. Whilst searching the databases, it is important to understand the ways in which these people refer to the devices in question. Some people may use the brand name, such as EnbrelÕ , HumiraÕ and SimponiÕ ; whereas others may use the drug’s generic name, e.g. etanercept, adalimumab and golimumab, or even the drug manufacturer’s name. Some users may also use the device name, e.g. SureClickÕ and/or the device manufacturer’s name, e.g. SHL for SureClickÕ . Some people, especially lay users, may also use the device’s generic family name and disease name, e.g. ‘‘autoinjector for rheumatoid arthritis’’. Therefore, a broad range of search terms should be used to search the databases for use-related issues. This paper suggests the following search terms:
Figure 3. Autoinjectors for the treatment of rheumatoid arthritis.
Drug brand name; Drug generic name; Drug manufacturer’s name; Device name (if any); Device manufacturer’s name (this can be different from drug manufacturer’s name); Device generic name, e.g. autoinjector; and
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Disease or condition name, e.g. rheumatoid arthritis (RA). The above search terms should be used on their own as well as in combinations.
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2.3. Search databases and tabulate results The approach of searching the available databases and tabulating the results is depicted in Figure 5. The authors of this paper encourage researchers to search as many databases as possible. The FDA’s Manufacturer and User Facility Device Experience (MAUDE) database is a good starting point as this database is likely to identify the majority of device-related incidents in the U.S. It is likely that some reports will appear in more than one database. Researchers should use individual search terms as well as combinations of search terms to facilitate the search process. Each search term (or a combination of terms) is likely to return a number of device incident reports, some of which may be relevant, others may not. The researcher must read the contents of the reports in order to distinguish the relevant ones. If a search term
returns a large number of reports, the researchers may use the ‘‘find’’ tool of their internet browser to check the context in which the search term has appeared in the report. Sometimes the search term is mentioned in the report, which does not have much significance to the incident itself. For example, a report describing a fault with an IV line with a patient in hospital may also mention the patient’s background information, e.g. the patient uses EnbrelÕ amongst other medication at home. This type of report is clearly not relevant to us. Each relevant report or the relevant part of the report should be tabulated on a spreadsheet with the search information, such as the search term, database name, time and date of report and web link. The process is explained in detail with our example autoinjector below. Let us search the FDA’s MAUDE database for the search term SureClickÕ , as shown in Figure 6. The search returns three reports, as shown in Figure 7. Two reports relate to EnbrelÕ , which is in our first priority list, and the third relates to AranespÕ that is in our second priority list.
Figure 4. Landscape of devices relevant to the example autoinjector for rheumatoid arthritis.
Figure 5. Process of searching databases and tabulating results.
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Figure 6. FDA’s MAUDE database being searched for ‘‘SureClick’’, accessed on 23 September 2015.[3].
Figure 7. Search returns for ‘‘SureClick’’ from FDA MAUDE database, accessed on 23 September 2015.[3].
The next step is to read the reports and identify if they are relevant. Figure 8 shows an excerpt from one of the reports above. The report suggests that some patients ‘‘returned their products saying that the injectors locked and failed
to discharge medication’’. No specific details have been provided and this issue could well be a manufacturing defect. However, if the researchers are familiar with the functioning and use of the SureClickÕ autoinjector, it is plausible to imagine that this issue could arise from a
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Figure 8. An incident report from FDA’s MAUDE database, accessed on 23 September 2015.[3].
use error. SureClickÕ has a safety guard at the needle end that needs to be fully depressed into the autoinjector body by pressing it against the injection site in order to unlock the injection button. If the injection button on the top of the device is pressed before the safety guard has been fully depressed, the mechanism can jam and the device will neither unlock nor activate until the user releases the button, starts the process again and follows the correct sequence. Therefore, this report might be relevant. The next step in the process is to record all relevant search results, preferably in a tabular form, as show in Figure 9. The authors of this paper encourage researchers to search all available databases with all search terms. However, this will depend on how much time and resources are available.
2.4. Analyse search results The approach of analysing the search results is depicted in Figure 10. The tabulation of relevant use-related incident reports may itself be sufficient to highlight the potential userelated issues pertaining to the medical device under development. However, if the number of reports is large and the reports themselves are not specific, it may be beneficial to further analyse the data and present the results in a meaningful way. This paper suggests the use
of the principle of open coding.[7] In this process, the researchers analyse the excerpts of the relevant incident reports in an attempt to develop early ‘‘concepts’’ based on their understanding of the functionality and uses of the devices. The process of development of an early concept consists of identifying units of data, e.g. key words, phrases, sentences or paragraphs in the reports that represent or are examples of a common use issue[8] and attaching a code to it. A code is a term given by the researchers to a concept. At this stage of analysis the coding is ‘‘unfocused’’ and ‘‘open’’and the researchers may generate a number of codes.[9] These codes are temporal and are likely to be changed as the analysis progresses.[10] The open coding method and the generation of concepts for our example-autoinjector are demonstrated in Figure 11. Once all the initial concepts are identified and coded, these concepts are constantly compared with one another so as to explore similarities and differences across them.[7] This is an iterative process and many early concepts may undergo a series of changes—some are merged while others are split; some may be renamed, and others restructured. The idea is to group concepts that describe a similar use issue, to form a ‘‘category’’. Categories are of a higher and more abstract order than are concepts and are closer to explaining a top-level use-related issue.[11] The third step of the analysis is to refine and finalise the categories. This may include exploring the categories
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Figure 9. An example of search results being recorded in a tabular form.
Figure 10. Process of analysing the search results.
in greater depth, which may result in further restructuring, refining, splitting, merging and eliminating of some existing categories, as well as the addition of the new ones. This process continues until saturation is reached. Saturation is the state in which the researchers make the subjective determination that further analysis will not provide any new insights.[10] The final categories form the basis for writing the report.
2.5. Report finding The report should present in a coherent manner all userelated issues found or inferred from the analysis of the device incident reports. The purpose of the report should not be to provide statistical data on the number or percentage of occurrence of these use errors. The report should focus on highlighting likely use-related issues that are either reported specifically or inferred by
the researchers. The purpose is to address these issues in the design of the device under development. The report should be written in a way that is understandable and useful to different types of prospective users of the report. The report should feed into the design and risk management process of the medical device under development for which this research has been done. Hence, it should be understandable and meaningful to the designers as well as to people who carry out risk management activities for the device. The report also forms part of the human factors and usability engineering (HFE/UE) report. The HFE/UE report is part of the Design History File (DHF), which is a requirement for submission to the FDA and other regulatory bodies for a market approval. The report should also describe the methodology, as described in this paper, so that the readers understand the methods and the underlying rationales that governed the selected methods. There may be various ways in which the use-related issues can be presented. This paper suggests that the ‘‘categories’’ developed in section 2.4 should be used as the top-level findings. These categories should then be elaborated with discussion and supported by excerpts from the incident reports, if necessary. Some top-level findings for our example autoinjector for the treatment of rheumatoid arthritis are presented below. Please note that these are for
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Figure 11. Demonstration of an open coding method of data analysis.
illustrative purposes only and do not present all userelated issues.
Some people can’t stand the pain the pen causes. If you’re like me, it’s the click that the pen makes that is so anxiety provoking.[13,p.1]
2.5.1. Device mix-up (look-alike mix-up) 2.5.3. Needlestick injuries There have been some reports on device mix-up due to the resemblance in their appearances of some autoinjectors. For example, an EpiPenÕ and an EpiPenÕ training device have been reported to have been accidentally used interchangeably, resulting in hazardous situations. A nurse opened a carton of EpiPens and administered what she thought was EPINEPHrine to a patient experiencing a severe infusion reaction to CARBOplatin. The pen was actually a trainer device that did not contain EPINEPHrine. The patient arrested and failed to regain consciousness. The trainer device is labelled as a trainer, but the font is small and the pens look very similar.[12,p.1]
2.5.2. Perceived pain and anxiety Some reports suggest that the appearance and feel of some autoinjectors can increase patients’ perceived pain and anxiety.
There are reports of needlestick injuries because users were confused about the needle end of the device and also how the device actually activated. A nurse unfamiliar with the new design of the EpiPen accidentally injected her thumb by pushing on the wrong end (orange tip) of the pen.[14,p.11]
2.5.4. Challenges to activate device and premature activations There are reports of difficulties, confusion and failures to activate a number of autoinjectors on the market. The issues are related to users not removing the safety feature; not pressing the device hard enough against the skin (these devices activate when pressed against the skin); not pressing the injection button hard enough (these devices activate when a button is pressed); and not following the correct sequence of use steps, e.g. where the device first needs to be unlocked by pressing
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against the skin and then activated by pressing the injection button. These confusions could also lead to accidental premature activation. Received 3 reports—(b)(6) 2011—from three patients who returned their products saying that the injectors locked and failed to discharge medication.[15,p.1]
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2.5.5. Premature removal from the injection site There have been reports of liquid seen on the skin, drops still coming out of the device and a spray of liquid in the air after removal of the device from the skin. These errors could result in an under-dose. The source of the error could potentially be in users removing the devices from the injection site prematurely. It is sometimes difficult even for experienced users to understand when the device should be removed from the skin, as the device feedback is either inadequate or misleading in many of these devices. As usual, I waited until a few seconds after the yellow marker appeared in the window, and pulled the pen away. When I did, a bunch of un-injected medicine dribbled onto the floor. I did have a tiny needle mark, so it’s possible that some of it injected, but I don’t know how much . . . if any.[16,p.1]
of the approach, it is believed to be applicable to a wide range of medical products. As with many research methods, there are certain limitations to this method too. The method in this paper relies primarily on publically available databases. Many of these databases are not specifically designed to capture use-related issues. They simply capture device and/or treatment related issues which may or may not be related to the use of a device. Therefore, the researchers would have to rely on their informed interpretations in order to elicit potential use-related issues from these reports. Also, people do not usually report usability issues, such as difficulties in using a device. They tend to blame themselves and develop coping strategies around the problems. In such circumstances, talking to users of existing devices may be more helpful. Therefore, although the method presented in the paper helps researchers to identify a good range of use-related issues with minimum time and budget, the authors encourage the designers and manufacturers of medical devices to consider other suitable methods too, as no one single method can reveal all use-related issues.
Acknowledgements The authors would like to thank Cambridge Consultants for its support in writing this paper.
Disclosure statement 3. Discussion and conclusion Understanding use-related issues with current and past medical devices that are similar to the one under development is an important aspect of the design process of a medical device. This helps to reduce and eliminate use errors, thereby making the product safer, more effective and usable. Regulatory bodies such as the FDA encourage manufacturers to investigate the known use problems as part of their human factors and usability engineering process. There are different ways in which this can be achieved. This paper has presented a systematic step-by-step approach to conducting this essential human factors activity. The method includes understanding the landscape of marketed devices relevant to the device in question, formulating effective search terms, searching the publically available medical device incident databases, analysing the data and reporting the findings in a meaningful way. The approach outlined in this paper is an extract of the methodology that has been effectively implemented to a number of medical products that are on the market, in submission or under development. Although an example of an autoinjector has been presented in this paper for the purpose of illustration, given the generic nature
The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.
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[6] Rheumatoid arthritis – treatment [Internet]. National Health Service; [cited 2015 Sep 23]. Available from: www.nhs.uk/Conditions/Rheumatoid-arthritis/Pages/ treatment.aspx. [7] Grounded theory: some reflections on paradigm, procedures and misconceptions [Internet]. Wolverhampton (UK): Management Research Centre, Wolverhampton Business School, University of Wolverhampton Goulding C; 1999 [cited 2015 Sep 23]. Available from: http:// www.ssnpstudents.com/wp/wp-content/uploads/2015/ 02/Grounded-theory.pdf. [8] Spiggle S. Analysis and interpretation of qualitative data in consumer research. J Consumer Res. 1994;21: 491–503. [9] Moghaddam A. Coding issues in grounded theory. Iss Educ Re 2006;16:52–66. [10] Gupta SP. Design and delivery of medical devices for home-use: Driver and challenges [PhD Thesis]. Cambridge (UK): Cambridge University; 2008. [11] Strauss AL, Corbin JM. Basics of qualitative research: Techniques and procedures for developing grounded theory. London: Sage Publications; 1998.
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[12] Quarterly Action Agenda [Internet]. Institution for Safe Medication Practices; 2014 [cited 2015 Sep 23]. Available from: http://www.ismp.org/Newsletters/acutecare/ActionAgendas_PDF/ActionAgenda1402.pdf. [13] Getting closer to myself, a blog post [Internet]. ‘‘Leslie’’; 2012 [cited 2015 Sep 23]. Available from: http://gettingclosertomyself.blogspot.co.uk/2012/07/humira-pen-isout-humira-pre-filled.html. [14] Medication errors: A year in review [Internet]. Institution for Safe Medication Practices; 2011 [cited 2015 Sep 23]. Available from: http://pharmacypracticenews.com/download/Med_errors_ppnse11_WM.pdf. [15] MAUDE adverse event report: Amgen Enbrel Sureclick 5mg injector [Internet]. Rockville, MD: US Food and Drug Administration; [cited 2015 Sep 23]. Available from http://www.accessdata.fda.gov/ scripts/cdrh/cfdocs/cfmaude/ Detail.CFM?MDRFOI__ID¼2484837. [16] My Humira Pen misfired, a web article [Internet]. Arthritis Insight; [cited 2014 Nov 13]. Available from: http://www.arthritisinsight.com/archives/test16504.htm.
