Investigating Safety Incidents with High-Risk Medications: Insights from the National Reporting and Learning System (NRLS) on Opioids, Insulins, and Anticoagulants

Investigating Safety Incidents with High-Risk Medications: Insights from the National Reporting and Learning System (NRLS) on Opioids, Insulins, and Anticoagulants | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Investigating Safety Incidents with High-Risk Medications: Insights from the National Reporting and Learning System (NRLS) on Opioids, Insulins, and Anticoagulants Abdulrhman Alrowily, Khalid Alfaraidy, Saleh Almutairi, Abdullah Alamri, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4115984/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Ensuring patient safety is paramount in any healthcare system. Rising concerns about medical errors in the UK have necessitated greater focus to be placed on studying the nature of such errors, particularly those involving high-risk medications. This research aims to conduct a retrospective analysis of incidents related to patient safety in the UK, based on data from the NRLS. Methods This research was conducted based on the review of NRLS patient safety reports published during the period January 1st, 2015 to December 31st, 2015. NHS Improvement provided details regarding the incidents, following approval using a data-sharing agreement. In total, 1,500 incidents were analyzed, equally divided among three categories of high-risk drugs; opioids, insulin and anticoagulants. Excel features and deductive reasoning (thematic analysis) were used in the data analysis. Results The results showed that the insulin category had both the highest risk and the most errors compared to anticoagulants and opioids. These errors primarily resulted from issues in administering, prescribing, and dispensing drugs. Inadequate drug checks, communication difficulties among staff and with patients, and high staff workload were often linked to these errors. Conclusion This study confirms that the NRLS database is a valuable source of data, while the suggestions put forth, based on these results, could contribute to the formulation of measures that diminish the occurrence of errors related to high-risk drugs in healthcare settings. Information technology should enhance medication safety by tracking the processing of medication use. Clinical pharmacology Drug safety opioids insulins anticoagulants medication error. Figures Figure 1 Impact of findings on practice statements With the aid of the NRLS database, this study is the first of its kind that highlights the potential errors associated with the use of opioids, insulins, and anticoagulants which should consequently enhance safety measures, increase training, and revise guidelines for administering, prescribing, and dispensing insulin. Continuous analysis and learning from this reporting system can improve the healthcare delivery process and prevent medication errors. Emphasising the nature, types and causes of safety incidents of these medications can promote better healthcare staff communication, workload management, continuous evaluation of patient safety Introduction According to the World Health Organization (WHO), pharmacovigilance is the science and activities that relate to the detection, assessment, understanding and prevention of drug-related problems including adverse drug events (ADE) [ 1 ]. It plays a crucial role in promoting patient safety by preventing further issues associated with medication use. In the UK, National Health Services (NHS) and Medications and Healthcare Products Regulatory Agency (MHRA) developed a National Report Learning System (NRLS) that is used for reporting and monitoring pharmacovigilance issues including medication incidence [ 2 ]. The NRLS database has been standardised across all NHS trusts and is designed to be accessible to any health provider for voluntary reporting. The prescribing process of medication is complex and risky. Due to a rising patient population, the NHS has observed a corresponding increase in the number of prescriptions issued daily [ 3 ]. This increase can lead to a corresponding increase in the potential for medication errors and a huge economic burden despite the advancements in medical technology and treatment strategies. The cost estimation of drug-related injury treatments is at least $ 3.5 billion annually besides that medication errors are estimated to incur $ 77 billion annually in morbidity and mortality costs [ 4 ]. Medication errors are categorized into two main categories: the errors of commission and the errors of omission [ 4 ]. These errors can occur throughout the medication use process, including prescribing, dispensing, administration and monitoring. Research indicates that there is a significantly small number of dispensing errors that have been found and identified at the final stage in UK hospital pharmacies. High-risk medications can be defined as medications that have a high potential for causing severe injury or harm if misused or administered incorrectly [ 6 ]. These types of medications do not have significant error differences from other medications but when misused or used in error, they cause severe harm or death. Hospitals identify high-risk medications based on published evidence (e.g. The Institute for Safe Medication Practices, ISMP or International Medication Safety Network, IMSN) of their potential to cause harm. These medications are then labeled as "high alert" and accompanied by specific policies and guidelines to aid clinicians in safe prescribing, dispensing, and administration. Opioids, insulin and anticoagulants are considered high-risk medications due to their high potential for errors, particularly related to dosing. Therefore, these medications require precise and frequent dosage calculations, and relying solely on weight is insufficient and can increase error risk. This study aims to investigate the nature, types and causes of safety incidents of opioids, insulin, and anticoagulants by analysing reported incidents involving these high-risk drug categories through the NRLS. Methods A mixed methods research approach, consisting of both quantitative and qualitative techniques, was adopted in this study. The quantitative part looked at the safety incidents data that were reported to the NRLS during the period from 1st January 2015 to 31st December 2015. Data source This research utilized the NRLS database as its main data source. The database was searched during May and June 2016, focusing on reports published during the time interval mentioned above. The procedure involved using appropriate keywords to obtain the reports related to patient incidents associated with three drug categories: opioids, insulin and anticoagulants. Both the generic and trade names of the potential drugs in the three chosen categories were used to refine the search and ensure a comprehensive capture of relevant data. We used randomisation to include a proportion of the reports in data analysis. In order to undertake sample randomisation, MS Excel was employed due to its high level of efficiency for samples consisting of more than 100 items [ 7 , 8 ]. The random selection of reports from the total number of 51,994 NRLS reports was performed by the RAND functionality tool. On this basis, 500 reports were selected for each of the three categories of high-risk drugs (anticoagulants, opioids and insulin), giving a total of 1,500 reports. In the examination of these reports, a number of four distinct aspects were addressed, namely, ‘description of what happened’, ‘apparent causes’, ‘medication process (MD01)’, and ‘medication error category (MD02)’. Prior to commencing the actual research, a pilot study was conducted to test the chosen methods. To this end, a total number of 150 NRLS records, 50 for each of the three high-risk drugs, were chosen at random. Random sampling was further applied to select a set of reports associated with one of the three high-risk drug categories. Data analysis Quantitative data were saved in Excel to facilitate their processing and analysis to match the objectives of this study. Also, “top-down”, deductive reasoning was used to narrow down the general information and principles to specific knowledge’ this enabled logical conclusions to be drawn by using thematic analysis of the qualitative data. Inclusion criteria This study utilized reports published in 2015, from January to December. The medications chosen in this study were intended for both sexes and all ages. Only those patient incident reports relating to the three categories of high-risk drugs (anticoagulants, opioids and insulin) have been included and data were collected from all levels of care. Exclusion criteria Incident reports associated with drugs other than anticoagulants, opioids and insulin, and incident reports associated with the use of codeine phosphate at dosages of 60 mg or less were excluded from the study. Ethical considerations Approval for study conduct was obtained from the Research Ethics Committee (REC). The research study started after receiving written approval from the REC. The data were kept secure through storage on a password-encrypted personal pen drive. Furthermore, every research procedure and all steps of the quantitative and qualitative analysis were carried out on a personal computer. Results This research was carried out in four phases. The first phase started by choosing initial incidents from NRLS reports (51,994); this phase covered three main categories: Insulins (12,188; 23.44%), Anticoagulants (17,910; 34.45%) and Controlled Drugs (21,896; 42.11%). The second phase was a random selection (550 reports) from the database of the three main medication categories mentioned earlier. The third phase was a pilot study of a random selection (50 reports) of the 550 reports designed to ensure the validity and reliability of data analysis during this and other research, with the two lots of analyzed data then compared. The last phase was conducted with 500 reports from each medication category minus the 50 reports that had been used for the pilot study, as shown in Figure 1 . Types of medication error among the 51,994 reports The highest percentages of medication errors were seen in administration (25,166 errors, 48.40%) followed by prescribing errors (11,564 errors, 22.24%) and the preparation of medications in all locations / dispensing in a pharmacy (4,574 errors, 8.80%), as shown in Table 1 . Sub-types of medication error for the 51,994 reports The highest sub-types of medication error among the three main categories were omitted medication/ingredient [insulins: 32.14% (3,917 reports); anticoagulants: 32% (5,732 reports); and controlled drugs: 11.42% (2,500 reports)], as shown in Table 2 . Medication errors involved among studied categories of medications The main drug involved in medication errors in the studied categories of medication was well reported in Table 3 . Degree of harm for the studied categories of medications (n = 51,994) The degree of ‘No Harm’ was the highest incident and the degree of ‘Death’ was the lowest incident level in general studied categories of medication Table 4 . Patients’ age range for the three studied categories of medication (n = 51,994) The highest number of reported incidents occurred among patients who were above 66 years of age. Details are provided in Table 5. Care setting locations of medication incidents for the three studied drugs The top care settings of those incidents which occurred among the main three categories of medication were: acute/general hospital, 76.13% (39,583 reports); community nursing, medical and therapy service (including community hospital), 15.97% (8,303 reports); and mental health service, 4.52% (2,350 reports), Table 6. The NRLS search output concerned a huge number of incidents (51,994 reports) among the three main drug classes, namely Insulins, Anticoagulants and Controlled Drugs. Therefore, the research used only 500 reports, which were selected randomly according to the randomization method explained at the beginning, for further and specific data analysis from each category. Types of medication error for each of the studied drug categories The types of medication error found among the randomization sample (1,500 reports), which was taken from the original database (51,994 reports) by using PivotTable in Excel for the three categories of medication (Insulins, Anticoagulants and Opioids), are presented in table 7 . Following the application of the exclusion criteria, a total of 1,330 incident reports were classified according to the type of medication error identified, as follows: 48.4% of all errors for all three categories were attributed to incorrect administration/supply of medication and the number of errors related to insulin is the highest at 50.6%, followed by controlled drugs (48.4%) and anticoagulants (46.2%). The second most common type of medication error is ‘prescribing medication’ (24.33%); with errors related to anticoagulants (31.80%) being greater than those related to insulin (23.40%) and controlled drugs (17.80%). In addition, the most common type of insulin-related medication errors is attributed to administration errors (50.60%); followed by prescribing errors (23.40%) and preparation and dispensing errors (7.80%). In the case of anticoagulants, the most common type of medication error is attributed to administration errors (46.20%) followed by prescribing errors (31.80%) and preparation and dispensing errors (4.20%). The most common type of medication error related to controlled drugs is attributed to administration errors (48.40%), followed by prescribing errors (17.80%), and preparation/dispensing errors (11.20%). Sub-types of medication errors for each of the studied drug categories Omitted medication/ingredient, 26.33% (395 reports) followed by wrong/unclear dose or strength, 13.47% (202 reports) were the highest number of sub-types of medication error, table 8 . Reported degree of harm for the three studied categories of medication There were three cases of severe harm while 13.31% (180 patients) reported low harm; the highest number of people who reported low harm was in the Insulins category, table 9 . Nature of errors for the three categories of medication The most common types of error for the three categories of medications were not adequately checking (task), 26.73% (401); high workload (work environment), 10.67% (160 reports); and communication problem (team), 8.40% (126 reports), table 10 . Quality of learning from the reports The quality of learning gleaned across the three main categories of medication was poor, 61.01% (834 reports), and many of these poor reports belonged to Anticoagulants, 75.82% (345 reports) followed by Controlled Drugs, 67.28% (292 reports), as shown in Table 11 . Thematic analysis The thematic analysis was conducted to identify the type of error across the three main medication categories. After coding the nature of all the errors, refining the codes and grouping them into categories, the following themes were generated and defined. There were two major themes in the Insulins, Anticoagulants and Controlled Drug categories: System factor errors, which represented individual factors, design of equipment and supplies; and Human factor errors, which represented individual, team and patient factors. Discussion High-risk medications are associated with an increase in incidents of medical harm. This research aims to conduct e retrospective analysis of incidents regarding patient safety in the UK, based on data from the National Report Learning System (NRLS). The research presented here was secondary research, conducted based on the review of NRLS patient safety reports published during the period January to December 2015. It investigated the increasing safety risk associated with incidents involving medication and also discussed emerging themes concerning such medication incidents. The results showed that errors in the insulin category had the highest level of occurrence (50.60%), besides that it represented the highest number of incidents that reported ‘low harm’ (18.03%) in comparison to anticoagulants (11.45%) and controlled drugs (9.98%). The degree of ‘moderate harm’ attributed to insulin-related incidents was the highest at 2.52% (12 patients) in comparison to anticoagulants (1.54%) and controlled drugs (1.19%). Recently in the UK, safety issues concerning the use of insulins raised significant concerns, especially in view of the fact that some of the many delivery devices are a cause of confusion to patients; in addition, further confusion arises concerning overdose adjustment of medication [9]. Similarly, in June 2010, a report published by the National Patient Safety Agency (NPSA) in the UK raised grave concerns regarding the issue of safety associated with the administering and prescribing of types of insulin by independent health institutes and the NHS, and called for urgent action in order to reduce any further medication errors involving insulin [10]. This alarming indicator regarding insulin-related medication errors requires further and deeper study using verified data from the NRLS. The findings of this current study are alarming and should be of concern to all healthcare providers such as consultant doctors, GPs, pharmacists, nurses, health policymakers and healthcare management, and should prompt further, and immediate, action targeted at the minimisation of risk and harm associated with medication errors, especially with regard to insulin-related cases. Medication errors are defined by the as incidents in which a drug has been prescribed, dispensed, prepared, administered, or monitored inadequately, irrespective of the occurrence of harm [11]. The findings of this current study indicated that administration, prescribing and dispensing errors from a total of 11 error types were the major causes of risk and harm in relation to the three categories of medication (insulin, anticoagulants, controlled drugs). In this current study, half of the medication errors are related to drug administration, with the most common medication errors being related to insulin drugs (50.60%), followed by controlled drugs (48.40%) and anticoagulant drugs (46.20%). Similarly, A review of relevant literature revealed that half of the total number of medication error reports (n = 12,552) represented hospital medication administration errors (MAE) with regard to young patients (Ameer, 2015). This indicates a high level of risk when half of the medication errors are related to drug administration involving human and system errors. Moreover, concern was raised by Kelly and others (2011) when it was reported that administration errors in hospitals were at a level of between 3.0 and 8.0%, and that prescribing errors in hospitals had reached 7% [12]. When combined with high-risk drugs, medication errors can be severe and even lead to endangering the lives of patients. This is especially true in the case of medication errors related to the administration of drugs, as outlined by ISMP which are considered to be high risk. Medication errors are becoming an increasingly prevalent problem in the British healthcare system, and such unintentional mistakes related In this current study, it was found that the reported degree of harm for the three categories of medication showed no incidences of death occurring in the three categories. However, 3 patients were reported to have experienced ‘severe harm’, and there were 180 patients (13.31%) who were reported to have experienced ‘low harm’; the highest number of cases which reported ‘low harm’ was in the insulin category. The degree of ‘moderate harm’ was also the highest for incidents involving insulin 2.52% (12 patients), while anticoagulants accounted for 1.54% (7 patients), and controlled drugs 1.19% (5 patients). During the period from October 2011 to March 2012, a total of 612,414 patient safety incidents were reported to the NRLS in England. Of these, a moderate level of harm occurred in 6% of the incidents, while a severe level of harm, or death, occurred in 1% of the incidents (n = 5,235) [13, 14]. This study found that, in general, the quality of learning for the three main categories of medications was poor, 61.01%, and many of the poor reports belonged to the category of anticoagulants 75.82%, and controlled drugs 67.28%. In contrast, adequate quality of learning was lower for the three main categories, 3.80%, and most of these adequate reports belonged to the category of insulin, 9.41%, while the other categories accounted for 1.57%. Based on the findings of the current research presented above, there remains significantly low quality in the reporting of incidents in the NHS in some medication categories such as anticoagulants and controlled drugs, which prompts a strong recommendation here to health policymakers in the NHS to deal with this concern expeditiously. Similar studies have raised this concern, such as that by Donaldson et al. (2014), which examined NRLS reports on deaths due to care errors and categorised them according to dimensions of systemic failure [15]. Thematic analysis was used as part of this study in order to identify the nature of errors in relation to the main three medication categories: insulin, anticoagulants, and controlled drugs. This was achieved through reviewing and reading all the reports/incidents not excluded by the research criteria, and subsequently coding all the nature of error types (See Appendix 1), refining the codes and then grouping them into categories. Based on these categories, the major themes and sub-themes were generated and defined. The current researcher found contributing a number of factors contributing to patient safety incidents. There were factors found, which contributed to patient safety incidents, which were similar between insulin, anticoagulant and controlled drug cases. With this in mind, only the factors extracted from insulin-related data are presented here. Most insulin-related errors are caused by human mistakes such as lapse of concentration and forgetfulness [16]. The first theme established is ‘Individual Factor’, such as ‘no adequate checking’, as illustrated in the following example: “ Nurse not adequately checking and review TTO: - Insulin Missing – and other medication complete on TTO.” The second theme is ‘Team Factor’, as illustrated by the following example which relates to ‘protocols not followed’: “Patient admitted with diabetic ketoacidosis. Sliding scale insulin not recommenced in ED as per plan by ED Dr.” The third theme is ‘Design of Equipment and Supplies’, and the following example illustrates issues of ‘product’ and ‘packaging storage’: “Pharmacist dispensing patient’s medication Humalin mix 30 instead Humalin mix 30 kiwipen because same packaging product.” The fourth theme is the ‘Patient Factor’, and the following example illustrates the issues of ‘task’ and ‘patient refusal’: “Routine daily visit patient to administer prescribed daily dose of Insulin, patient refused to administered without any realistic reason.” The four themes, as defined in this study, are part of a set of themes/factors that contribute to patient safety. Lawton et al. (2012) reviewed 34 different studies, of which 13 were carried out in the UK, which identified a number of factors contributing to patient safety incidents: (a) individual variables: these variables refer to attributes such as lack of experience, anxiety, personality, and attitudes that the caregiver may possess and which may be determinants of active failures; (b) communication systems: successful interaction between personnel, patients, groups, departments and services depends on efficient communication systems, written (e.g. documentation) as well as verbal (e.g. handover); and (c) equipment and resources: these must be adequately available and operational [17]. This study identified two major themes that were found across the three main categories of medication: insulin, anticoagulants and controlled drugs. These were extracted from the above themes mentioned: (a) system factor errors, which represent the individual factor, design of equipment and supplies; and (b) human factor errors, which represent the individual factor, team factor and patient factor. High-risk medications can be defined as medications that are highly likely to cause injury or harm when prescribed incorrectly or when administered incorrectly. This type of medication does not have significant error difference compared to other medications, but when applied incorrectly the potential for harm to the patient is considerably higher than in other cases. High-risk medications include opioids, insulin, and anticoagulants [18]. The strength of the current research lies in the analysis of recent NRLS data for 2015 and using a pilot study to ensure reliability and validity; also, the use of thematic analysis to enrich the findings, in particular regarding the nature of errors and exploring their contributory factors to patient safety is beneficial. The major limitation of the current study is its small sample size, which restricts the scale of presenting the phenomena of the research; in addition, not using research questions limits the benefit of this study in terms of its publication in an academic journal. During the course of the research, various challenges and limitations had to be acknowledged and dealt with. Among them were the following: - Limitations associated with this study include the randomisation process, which reduced the number of incident reports, as well as the data, which was not representative. In addition, as part of this study, it was not feasible to examine the severity of incidents, or cases resulting in death, due to time restrictions. The sample size used in this study was small and the period of the study was one year, from January 2015 to December 2015; however, if the period of study was extended to 6 months, then the random sample could be more representative. - Some incidents were repeated; referred to as duplicate incidents, and, therefore, were excluded from the analysis. - Some incidents lacked, or had little, description; they were classified as “others” and also excluded from the analysis. - The description of some incidents mentioned NOAC (Noval Oral Anticoagulant); however, a search did not produce any drugs in this group because the term was entered in its acronym form. - Sometimes, an incident report was written by an individual wishing to make a complaint regarding the procedure. Such incidents are referred to as “call for concern” cases. This type of incident report was typically written by someone not satisfied with the hospital policy, and who wished to change or amend the existing procedure. - Any errors related to medical devices, such as insulin syringes, should not be treated as medication errors. Therefore, the interpretation and analysis of incidents require researchers to have good experience and knowledge. - Viewing the incident reports in the NHS database posed a challenge in terms of understanding the abbreviations commonly used in the reporting of incidents. It was therefore necessary to consult the terms used in the NHS Abbreviation List in order to fully understand the content of the incident reports as part of the analysis. - Dispensing errors can happen when a doctor prescribes warfarin (3mg) and a nurse administers a different drug instead, or when a pharmacist dispenses NovoMix instead of NovoRapid insulin. In addition, some incidents contained more than one error. When both dispensing errors and administration errors were found in the same incident report, such cases were categorised as ‘multi-process errors.’ - In some cases, multiple themes were found in the same incident. One incident included three themes that were relevant to the analysis. Consequently, researchers must approach the analysis of incidents in the NHS database with care. - Deductive reasoning (thematic analysis) was used to identify the themes from the original incident reports. Although this approach is interesting; making use of it for the first time within the limited timeframe of this study proved to be a challenge. Based on the findings of the current research, it would be useful to review the incidence of medication errors every year using various methods to evaluate patient safety such as questionnaires, interviews, observation and case studies. Also, involving a number of patients at various levels in terms of reviewing and evaluating patient safety and medication errors. MHRA and the NHS strongly recommended regular evaluation of national medication safety in the UK; they suggest that the staff of health providers should be encouraged to engage in a systemic way with medication incidents. Further research can be specifically targeted at investigating the major medication errors that significantly affect patients’ safety, such as the administering, prescribing and dispensing of medication in the NHS compared with the private health sector in the UK. Conclusion In summary, insulin produced the highest risk and medication errors compared to anticoagulants and opioids. Moreover, the greatest number of errors could be attributed to three factors: administration of drugs, prescription of drugs, and dispensing of drugs, and that these three factors were related to another three components that determined the nature of medication errors, such as ‘no adequate checking of drugs’, ‘communication difficulties among staff and between staff and patients’, and ‘high workload of staff’. Furthermore, the overall quality of learning in relation to the three main categories of medications was found to be poor, 61.01% and adequate quality of learning was very low for all three main categories, 3.80%, and most of these adequate reports related to insulin, 9.41%, while the other categories accounted for only 1.57%. Health information technology is crucial tool for enhancing patient safety through tracking the medication use process. Declarations Conflicts of Interest The authors declare no conflict of interest. Funding This research was funded by the Researchers Supporting Project number (RSPD2024R778), King Saud University, Riyadh, Saudi Arabia. Author Contribution AR: Conceptualization, Data curation, Investigation, Writing – original draft, Writing – review &editing, Methodology. M.A: ˜ Conceptualization, Supervision, Validation, Writing – review & editing. WS:Conceptualization, Validation, Writing – review & editing, Supervision.MJ: ´ Conceptualization, Supervision, Validation, Writing – review & editing. KF: Methodology, Validation,Writing – review & editing, SH: Validation, Writing – review & editing, MZ: Methodology, Validation,Writing – review & editing, AM:review & editing Acknowledgments: The authors would like to extend their gratitude to Researchers Supporting Project number (RSPD2024R778), King Saud University, Riyadh, Saudi Arabia for funding this work. References WHO. 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Computer-based diabetes self-management interventions for adults with type 2 diabetes mellitus. The Cochrane database of systematic reviews 2013; 2013: Cd008776. Tables Table 1 to 11 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Tables.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4115984","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":281231614,"identity":"78b07bdf-7792-4ec7-b2c8-9093319681cb","order_by":0,"name":"Abdulrhman 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Complex","correspondingAuthor":false,"prefix":"","firstName":"Khalid","middleName":"","lastName":"Alfaraidy","suffix":""},{"id":281231616,"identity":"d65e6a8c-1e28-4f65-b2d5-10868c7fafa0","order_by":2,"name":"Saleh Almutairi","email":"","orcid":"","institution":"King Fahd Military Medical Complex","correspondingAuthor":false,"prefix":"","firstName":"Saleh","middleName":"","lastName":"Almutairi","suffix":""},{"id":281231617,"identity":"aef6c659-c4e9-4134-8773-ecfe26a2f060","order_by":3,"name":"Abdullah Alamri","email":"","orcid":"","institution":"King Fahd Military Medical Complex","correspondingAuthor":false,"prefix":"","firstName":"Abdullah","middleName":"","lastName":"Alamri","suffix":""},{"id":281231618,"identity":"6a7cba6c-59c1-4068-b32d-86da75d1ae02","order_by":4,"name":"Wejdan Alrowily","email":"","orcid":"","institution":"King Fahd Military Medical Complex","correspondingAuthor":false,"prefix":"","firstName":"Wejdan","middleName":"","lastName":"Alrowily","suffix":""},{"id":281231619,"identity":"274ecda5-b261-4586-b672-eefd62d3a5a6","order_by":5,"name":"Mohammed Abutaleb","email":"","orcid":"","institution":"King Fahad Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mohammed","middleName":"","lastName":"Abutaleb","suffix":""},{"id":281231620,"identity":"abd741a2-b6d8-4a6a-82a3-7d241501f26d","order_by":6,"name":"Mohammad Zaitoun","email":"","orcid":"","institution":"Riyadh Armed Forces Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mohammad","middleName":"","lastName":"Zaitoun","suffix":""},{"id":281231621,"identity":"29a24038-9a0c-433b-a8b9-59aba5e83297","order_by":7,"name":"Wedad Sarawi","email":"","orcid":"","institution":"King Saud University","correspondingAuthor":false,"prefix":"","firstName":"Wedad","middleName":"","lastName":"Sarawi","suffix":""},{"id":281231622,"identity":"7495e35d-f861-468d-a0f1-93d8f1589748","order_by":8,"name":"Mashael Aljead","email":"","orcid":"","institution":"King Fahad Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mashael","middleName":"","lastName":"Aljead","suffix":""}],"badges":[],"createdAt":"2024-03-17 08:03:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4115984/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4115984/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53196540,"identity":"df5f8ddf-cadc-4048-94ad-7b05a3935669","added_by":"auto","created_at":"2024-03-21 18:30:47","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":87494,"visible":true,"origin":"","legend":"\u003cp\u003eDiagram of the data structure for randomisation and analysis\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-4115984/v1/5bb4eaaa071ef2443db8b629.png"},{"id":54593234,"identity":"7463b1a6-c0f3-4643-a96c-e55941755bb4","added_by":"auto","created_at":"2024-04-12 18:00:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":538099,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4115984/v1/85a46a25-436e-43b7-a5a0-c1827aea680c.pdf"},{"id":53196547,"identity":"e2a0936c-0a58-421a-b08c-fc9c2ef6430f","added_by":"auto","created_at":"2024-03-21 18:30:49","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1422213,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-4115984/v1/276a3b8c5aaca6ab2b940750.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Investigating Safety Incidents with High-Risk Medications: Insights from the National Reporting and Learning System (NRLS) on Opioids, Insulins, and Anticoagulants","fulltext":[{"header":"Impact of findings on practice statements","content":"\u003cul\u003e\n \u003cli\u003eWith the aid of the NRLS database, this study is the first of its kind that highlights the potential errors associated with the use of\u0026nbsp;opioids, insulins, and anticoagulants\u0026nbsp;which should consequently enhance safety measures, increase training, and revise guidelines for administering, prescribing, and dispensing insulin.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eContinuous analysis and learning from this reporting system can improve the healthcare delivery process and prevent medication errors.\u003c/li\u003e\n \u003cli\u003eEmphasising the nature, types and causes of safety incidents of these medications can promote better healthcare staff communication, workload management, continuous evaluation of patient safety\u0026nbsp;\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Introduction","content":"\u003cp\u003eAccording to the World Health Organization (WHO), pharmacovigilance is the science and activities that relate to the detection, assessment, understanding and prevention of drug-related problems including adverse drug events (ADE) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. It plays a crucial role in promoting patient safety by preventing further issues associated with medication use. In the UK, National Health Services (NHS) and Medications and Healthcare Products Regulatory Agency (MHRA) developed a National Report Learning System (NRLS) that is used for reporting and monitoring pharmacovigilance issues including medication incidence [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The NRLS database has been standardised across all NHS trusts and is designed to be accessible to any health provider for voluntary reporting.\u003c/p\u003e \u003cp\u003eThe prescribing process of medication is complex and risky. Due to a rising patient population, the NHS has observed a corresponding increase in the number of prescriptions issued daily [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This increase can lead to a corresponding increase in the potential for medication errors and a huge economic burden despite the advancements in medical technology and treatment strategies. The cost estimation of drug-related injury treatments is at least \u003cspan\u003e$\u003c/span\u003e3.5\u0026nbsp;billion annually besides that medication errors are estimated to incur \u003cspan\u003e$\u003c/span\u003e77\u0026nbsp;billion annually in morbidity and mortality costs [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMedication errors are categorized into two main categories: the errors of commission and the errors of omission [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. These errors can occur throughout the medication use process, including prescribing, dispensing, administration and monitoring. Research indicates that there is a significantly small number of dispensing errors that have been found and identified at the final stage in UK hospital pharmacies.\u003c/p\u003e \u003cp\u003eHigh-risk medications can be defined as medications that have a high potential for causing severe injury or harm if misused or administered incorrectly [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. These types of medications do not have significant error differences from other medications but when misused or used in error, they cause severe harm or death. Hospitals identify high-risk medications based on published evidence (e.g. The Institute for Safe Medication Practices, ISMP or International Medication Safety Network, IMSN) of their potential to cause harm. These medications are then labeled as \"high alert\" and accompanied by specific policies and guidelines to aid clinicians in safe prescribing, dispensing, and administration. Opioids, insulin and anticoagulants are considered high-risk medications due to their high potential for errors, particularly related to dosing. Therefore, these medications require precise and frequent dosage calculations, and relying solely on weight is insufficient and can increase error risk. This study aims to investigate the nature, types and causes of safety incidents of opioids, insulin, and anticoagulants by analysing reported incidents involving these high-risk drug categories through the NRLS.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eA mixed methods research approach, consisting of both quantitative and qualitative techniques, was adopted in this study. The quantitative part looked at the safety incidents data that were reported to the NRLS during the period from 1st January 2015 to 31st December 2015.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData source\u003c/h2\u003e \u003cp\u003eThis research utilized the NRLS database as its main data source. The database was searched during May and June 2016, focusing on reports published during the time interval mentioned above. The procedure involved using appropriate keywords to obtain the reports related to patient incidents associated with three drug categories: opioids, insulin and anticoagulants. Both the generic and trade names of the potential drugs in the three chosen categories were used to refine the search and ensure a comprehensive capture of relevant data.\u003c/p\u003e \u003cp\u003eWe used randomisation to include a proportion of the reports in data analysis. In order to undertake sample randomisation, MS Excel was employed due to its high level of efficiency for samples consisting of more than 100 items [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The random selection of reports from the total number of 51,994 NRLS reports was performed by the RAND functionality tool. On this basis, 500 reports were selected for each of the three categories of high-risk drugs (anticoagulants, opioids and insulin), giving a total of 1,500 reports. In the examination of these reports, a number of four distinct aspects were addressed, namely, \u0026lsquo;description of what happened\u0026rsquo;, \u0026lsquo;apparent causes\u0026rsquo;, \u0026lsquo;medication process (MD01)\u0026rsquo;, and \u0026lsquo;medication error category (MD02)\u0026rsquo;. Prior to commencing the actual research, a pilot study was conducted to test the chosen methods. To this end, a total number of 150 NRLS records, 50 for each of the three high-risk drugs, were chosen at random. Random sampling was further applied to select a set of reports associated with one of the three high-risk drug categories.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eQuantitative data were saved in Excel to facilitate their processing and analysis to match the objectives of this study. Also, \u0026ldquo;top-down\u0026rdquo;, deductive reasoning was used to narrow down the general information and principles to specific knowledge\u0026rsquo; this enabled logical conclusions to be drawn by using thematic analysis of the qualitative data.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003eInclusion criteria\u003c/h2\u003e \u003cp\u003eThis study utilized reports published in 2015, from January to December. The medications chosen in this study were intended for both sexes and all ages. Only those patient incident reports relating to the three categories of high-risk drugs (anticoagulants, opioids and insulin) have been included and data were collected from all levels of care.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003eExclusion criteria\u003c/h2\u003e \u003cp\u003eIncident reports associated with drugs other than anticoagulants, opioids and insulin, and incident reports associated with the use of codeine phosphate at dosages of 60 mg or less were excluded from the study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003eEthical considerations\u003c/h2\u003e \u003cp\u003eApproval for study conduct was obtained from the Research Ethics Committee (REC). The research study started after receiving written approval from the REC. The data were kept secure through storage on a password-encrypted personal pen drive. Furthermore, every research procedure and all steps of the quantitative and qualitative analysis were carried out on a personal computer.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThis research was carried out in four phases. The first phase started by choosing initial incidents from NRLS reports (51,994); this phase covered three main categories: Insulins (12,188; 23.44%), Anticoagulants (17,910; 34.45%) and Controlled Drugs (21,896; 42.11%). The second phase was a random selection (550 reports) from the database of the three main medication categories mentioned earlier. The third phase was a pilot study of a random selection (50 reports) of the 550 reports designed to ensure the validity and reliability of data analysis during this and other research, with the two lots of analyzed data then compared. The last phase was conducted with 500 reports from each medication category minus the 50 reports that had been used for the pilot study, as shown in \u003cstrong\u003eFigure 1\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTypes of medication error among the 51,994\u0026nbsp;reports\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe highest percentages of medication errors were seen in administration (25,166 errors, 48.40%) followed by prescribing errors (11,564 errors, 22.24%) and the preparation of medications in all locations / dispensing in a pharmacy (4,574 errors, 8.80%), as shown in \u003cstrong\u003eTable 1\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSub-types of medication error for the 51,994 reports\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe highest sub-types of medication error among the three main categories were omitted medication/ingredient [insulins: 32.14% (3,917 reports); anticoagulants: 32% (5,732 reports); and controlled drugs: 11.42% (2,500 reports)], as shown in \u003cstrong\u003eTable 2\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMedication errors involved among studied categories of medications\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe main drug involved in medication errors in the studied categories of medication was well reported in \u003cstrong\u003eTable 3\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDegree of harm for the studied categories of medications (n = 51,994)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe degree of \u0026lsquo;No Harm\u0026rsquo; was the highest incident and the degree of \u0026lsquo;Death\u0026rsquo; was the lowest incident level in general studied categories of medication \u003cstrong\u003eTable 4\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatients\u0026rsquo; age range for the three studied categories of medication (n = 51,994)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe highest number of reported incidents occurred among patients who were above 66 years of age. Details are provided in \u003cstrong\u003eTable 5.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCare setting locations of medication incidents for the three studied drugs\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe top care settings of those incidents which occurred among the main three categories of medication were: acute/general hospital, 76.13% (39,583 reports); community nursing, medical and therapy service (including community hospital), 15.97% (8,303 reports); and mental health service, 4.52% (2,350 reports), \u003cstrong\u003eTable 6.\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe NRLS search output concerned a huge number of incidents (51,994 reports) among the three main drug classes, namely Insulins, Anticoagulants and Controlled Drugs. Therefore, the research used only 500 reports, which were selected randomly according to the randomization method explained at the beginning, for further and specific data analysis from each category.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTypes of medication error for each of the studied drug categories\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe types of medication error found among the randomization sample (1,500 reports), which was taken from the original database (51,994 reports) by using PivotTable in Excel for the three categories of medication (Insulins, Anticoagulants and Opioids), are presented in \u003cstrong\u003etable 7\u003c/strong\u003e. Following the application of the exclusion criteria, a total of 1,330 incident reports were classified according to the type of medication error identified, as follows: 48.4% of all errors for all three categories were attributed to incorrect administration/supply of medication and the number of errors related to insulin is the highest at 50.6%, followed by controlled drugs (48.4%) and anticoagulants (46.2%). The second most common type of medication error is \u0026lsquo;prescribing medication\u0026rsquo; (24.33%); with errors related to anticoagulants (31.80%) being greater than those related to insulin (23.40%) and controlled drugs (17.80%).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn addition, the most common type of insulin-related medication errors is attributed to administration errors (50.60%); followed by prescribing errors (23.40%) and preparation and dispensing errors (7.80%). In the case of anticoagulants, the most common type of medication error is attributed to administration errors (46.20%) followed by prescribing errors (31.80%) and preparation and dispensing errors (4.20%). The most common type of medication error related to controlled drugs is attributed to administration errors (48.40%), followed by prescribing errors (17.80%), and preparation/dispensing errors (11.20%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSub-types of medication errors for each of the studied drug categories\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOmitted medication/ingredient, 26.33% (395 reports) followed by wrong/unclear dose or strength, 13.47% (202 reports) were the highest number of sub-types of medication error, \u003cstrong\u003etable 8\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReported degree of harm for the three studied categories of medication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere were three cases of severe harm while 13.31% (180 patients) reported low harm; the highest number of people who reported low harm was in the Insulins category, \u003cstrong\u003etable 9\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNature of errors for the three categories of medication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe most common types of error for the three categories of medications were not adequately checking (task), 26.73% (401); high workload (work environment), 10.67% (160 reports); and communication problem (team), 8.40% (126 reports), \u003cstrong\u003etable 10\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuality of learning from the reports\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe quality of learning gleaned across the three main categories of medication was poor, 61.01% (834 reports), and many of these poor reports belonged to Anticoagulants, 75.82% (345 reports) followed by Controlled Drugs, 67.28% (292 reports), as shown in \u003cstrong\u003eTable 11\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThematic analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe thematic analysis was conducted to identify the type of error across the three main medication categories. After coding the nature of all the errors, refining the codes and grouping them into categories, the following themes were generated and defined. There were two major themes in the Insulins, Anticoagulants and Controlled Drug categories: \u003cstrong\u003eSystem factor errors,\u003c/strong\u003e which represented individual factors, design of equipment and supplies; and \u003cstrong\u003eHuman factor errors,\u003c/strong\u003e which represented individual, team and patient factors.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eHigh-risk medications are associated with an increase in incidents of medical harm. This research aims to conduct e retrospective analysis of incidents regarding patient safety in the UK, based on data from the National Report Learning System (NRLS). The research presented here was secondary research, conducted based on the review of NRLS patient safety reports published during the period January to December 2015. It investigated the increasing safety risk associated with incidents involving medication and also discussed emerging themes concerning such medication incidents.\u003c/p\u003e\n\u003cp\u003eThe results showed that errors in the insulin category had the highest level of occurrence (50.60%), besides that it represented the highest number of incidents that reported \u0026lsquo;low harm\u0026rsquo; (18.03%) in comparison to anticoagulants (11.45%) and controlled drugs (9.98%). The degree of \u0026lsquo;moderate harm\u0026rsquo; attributed to insulin-related incidents was the highest at 2.52% (12 patients) in comparison to anticoagulants (1.54%) and controlled drugs (1.19%). Recently in the UK, safety issues concerning the use of insulins raised significant concerns, especially in view of the fact that some of the many delivery devices are a cause of confusion to patients; in addition, further confusion arises concerning overdose adjustment of medication [9]. Similarly, in June 2010, a report published by the National Patient Safety Agency (NPSA) in the UK raised grave concerns regarding the issue of safety associated with the administering and prescribing of types of insulin by independent health institutes and the NHS, and called for urgent action in order to reduce any further medication errors involving insulin [10]. This alarming indicator regarding insulin-related medication errors requires further and deeper study using verified data from the NRLS. The findings of this current study are alarming and should be of concern to all healthcare providers such as consultant doctors, GPs, pharmacists, nurses, health policymakers and healthcare management, and should prompt further, and immediate, action targeted at the minimisation of risk and harm associated with medication errors, especially with regard to insulin-related cases.\u003c/p\u003e\n\u003cp\u003eMedication errors are defined by the as incidents in which a drug has been prescribed, dispensed, prepared, administered, or monitored inadequately, irrespective of the occurrence of harm [11]. The findings of this current study indicated that administration, prescribing and dispensing errors from a total of 11 error types were the major causes of risk and harm in relation to the three categories of medication (insulin, anticoagulants, controlled drugs). In this current study, half of the medication errors are related to drug administration, with the most common medication errors being related to insulin drugs (50.60%), followed by controlled drugs (48.40%) and anticoagulant drugs (46.20%). Similarly, A review of relevant literature revealed that half of the total number of medication error reports (n = 12,552) represented hospital medication administration errors (MAE) with regard to young patients (Ameer, 2015). This indicates a high level of risk when half of the medication errors are related to drug administration involving human and system errors. Moreover, concern was raised by Kelly and others (2011) when it was reported that administration errors in hospitals were at a level of between 3.0 and 8.0%, and that prescribing errors in hospitals had reached 7% [12]. When combined with high-risk drugs, medication errors can be severe and even lead to endangering the lives of patients. This is especially true in the case of medication errors related to the administration of drugs, as outlined by ISMP which are considered to be high risk. Medication errors are becoming an increasingly prevalent problem in the British healthcare system, and such unintentional mistakes related\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn this current study, it was found that the reported degree of harm for the three categories of medication showed no incidences of death occurring in the three categories. However, 3 patients were reported to have experienced \u0026lsquo;severe harm\u0026rsquo;, and there were 180 patients (13.31%) who were reported to have experienced \u0026lsquo;low harm\u0026rsquo;; the highest number of cases which reported \u0026lsquo;low harm\u0026rsquo; was in the insulin category. The degree of \u0026lsquo;moderate harm\u0026rsquo; was also the highest for incidents involving insulin 2.52% (12 patients), while anticoagulants accounted for 1.54% (7 patients), and controlled drugs 1.19% (5 patients). During the period from October 2011 to March 2012, a total of 612,414 patient safety incidents were reported to the NRLS in England. Of these, a moderate level of harm occurred in 6% of the incidents, while a severe level of harm, or death, occurred in 1% of the incidents (n = 5,235) [13, 14].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study found that, in general, the quality of learning for the three main categories of medications was poor, 61.01%, and many of the poor reports belonged to the category of anticoagulants 75.82%, and controlled drugs 67.28%. In contrast, adequate quality of learning was lower for the three main categories, 3.80%, and most of these adequate reports belonged to the category of insulin, 9.41%, while the other categories accounted for 1.57%. Based on the findings of the current research presented above, there remains significantly low quality in the reporting of incidents in the NHS in some medication categories such as anticoagulants and controlled drugs, which prompts a strong recommendation here to health policymakers in the NHS to deal with this concern expeditiously. Similar studies have raised this concern, such as that by Donaldson \u003cem\u003eet al.\u0026nbsp;\u003c/em\u003e(2014), which examined NRLS reports on deaths due to care errors and categorised them according to dimensions of systemic failure [15].\u003c/p\u003e\n\u003cp\u003eThematic analysis was used as part of this study in order to identify the nature of errors in relation to the main three medication categories: insulin, anticoagulants, and controlled drugs. This was achieved through reviewing and reading all the reports/incidents not excluded by the research criteria, and subsequently coding all the nature of error types (See Appendix 1), refining the codes and then grouping them into categories. Based on these categories, the major themes and sub-themes were generated and defined. The current researcher found contributing a number of factors contributing to patient safety incidents. There were factors found, which contributed to patient safety incidents, which were similar between insulin, anticoagulant and controlled drug cases. With this in mind, only the factors extracted from insulin-related data are presented here. Most insulin-related errors are caused by human mistakes such as lapse of concentration and forgetfulness [16].\u003c/p\u003e\n\u003cp\u003eThe first theme established is \u0026lsquo;Individual Factor\u0026rsquo;, such as \u0026lsquo;no adequate checking\u0026rsquo;, as illustrated in the following example:\u003c/p\u003e\n\u003cp\u003e\u0026ldquo;\u003cem\u003eNurse not adequately checking and review TTO: - Insulin Missing \u0026ndash; and other medication complete on TTO.\u0026rdquo;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe second theme is \u0026lsquo;Team Factor\u0026rsquo;, as illustrated by the following example which relates to \u0026lsquo;protocols not followed\u0026rsquo;:\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cem\u003e\u0026ldquo;Patient admitted with diabetic ketoacidosis. Sliding scale insulin not recommenced in ED as per plan by ED Dr.\u0026rdquo;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe third theme is \u0026lsquo;Design of Equipment and Supplies\u0026rsquo;, and the following example illustrates issues of \u0026lsquo;product\u0026rsquo; and \u0026lsquo;packaging storage\u0026rsquo;:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;Pharmacist dispensing patient\u0026rsquo;s medication Humalin mix 30 instead Humalin mix 30 kiwipen because same packaging product.\u0026rdquo;\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe fourth theme is the \u0026lsquo;Patient Factor\u0026rsquo;, and the following example illustrates the issues of \u0026lsquo;task\u0026rsquo; and \u0026lsquo;patient refusal\u0026rsquo;:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;Routine daily visit patient to administer prescribed daily dose of Insulin, patient refused to administered without any realistic reason.\u0026rdquo;\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe four themes, as defined in this study, are part of a set of themes/factors that contribute to patient safety.\u0026nbsp;Lawton\u003cem\u003e\u0026nbsp;et al.\u0026nbsp;\u003c/em\u003e(2012) reviewed 34 different studies, of which 13 were carried out in the UK, which identified a number of factors contributing to patient safety incidents: (a) individual variables: these variables refer to attributes such as lack of experience, anxiety, personality, and attitudes that the caregiver may possess and which may be determinants of active failures; (b) communication systems: successful interaction between personnel, patients, groups, departments and services depends on efficient communication systems, written (e.g. documentation) as well as verbal (e.g. handover); and (c) equipment and resources: these must be adequately available and operational [17].\u003c/p\u003e\n\u003cp\u003eThis study identified two major themes that were found across the three main categories of medication: insulin, anticoagulants and controlled drugs. These were extracted from the above themes mentioned: (a) system factor errors, which represent the individual factor, design of equipment and supplies; and (b) human factor errors, which represent the individual factor, team factor and patient factor. High-risk medications can be defined as medications that are highly likely to cause injury or harm when prescribed incorrectly or when administered incorrectly. This type of medication does not have significant error difference compared to other medications, but when applied incorrectly the potential for harm to the patient is considerably higher than in other cases. High-risk medications include opioids, insulin, and anticoagulants [18].\u003c/p\u003e\n\u003cp\u003eThe strength of the current research lies in the analysis of recent NRLS data for 2015 and using a pilot study to ensure reliability and validity; also, the use of thematic analysis to enrich the findings, in particular regarding the nature of errors and exploring their contributory factors to patient safety is beneficial. The major limitation of the current study is its small sample size, which restricts the scale of presenting the phenomena of the research; in addition, not using research questions limits the benefit of this study in terms of its publication in an academic journal.\u003c/p\u003e\n\u003cp\u003eDuring the course of the research, various challenges and limitations had to be acknowledged and dealt with. Among them were the following: \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e- Limitations associated with this study include the randomisation process, which reduced the number of incident reports, as well as the data, which was not representative. In addition, as part of this study, it was not feasible to examine the severity of incidents, or cases resulting in death, due to time restrictions. The sample size used in this study was small and the period of the study was one year, from January 2015 to December 2015; however, if the period of study was extended to 6 months, then the random sample could be more representative.\u003c/p\u003e\n\u003cp\u003e- Some incidents were repeated; referred to as duplicate incidents, and, therefore, were excluded from the analysis.\u003c/p\u003e\n\u003cp\u003e- Some incidents lacked, or had little, description; they were classified as \u0026ldquo;others\u0026rdquo; and also excluded from the analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e- The description of some incidents mentioned NOAC (Noval Oral Anticoagulant); however, a search did not produce any drugs in this group because the term was entered in its acronym form.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e- Sometimes, an incident report was written by an individual wishing to make a complaint regarding the procedure. Such incidents are referred to as \u0026ldquo;call for concern\u0026rdquo; cases. This type of incident report was typically written by someone not satisfied with the hospital policy, and who wished to change or amend the existing procedure.\u003c/p\u003e\n\u003cp\u003e- Any errors related to medical devices, such as insulin syringes, should not be treated as medication errors. Therefore, the interpretation and analysis of incidents require researchers to have good experience and knowledge.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e- Viewing the incident reports in the NHS database posed a challenge in terms of understanding the abbreviations commonly used in the reporting of incidents. It was therefore necessary to consult the terms used in the NHS Abbreviation List in order to fully understand the content of the incident reports as part of the analysis.\u003c/p\u003e\n\u003cp\u003e- Dispensing errors can happen when a doctor prescribes warfarin (3mg) and a nurse administers a different drug instead, or when a pharmacist dispenses NovoMix instead of NovoRapid insulin. In addition, some incidents contained more than one error. When both dispensing errors and administration errors were found in the same incident report, such cases were categorised as \u0026lsquo;multi-process errors.\u0026rsquo;\u003c/p\u003e\n\u003cp\u003e- In some cases, multiple themes were found in the same incident. One incident included three themes that were relevant to the analysis. Consequently, researchers must approach the analysis of incidents in the NHS database with care.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e- Deductive reasoning (thematic analysis) was used to identify the themes from the original incident reports. Although this approach is interesting; making use of it for the first time within the limited timeframe of this study proved to be a challenge.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBased on the findings of the current research, it would be useful to review the incidence of medication errors every year using various methods to evaluate patient safety such as questionnaires, interviews, observation and case studies. Also, involving a number of patients at various levels in terms of reviewing and evaluating patient safety and medication errors. MHRA and the NHS strongly recommended regular evaluation of national medication safety in the UK; they suggest that the staff of health providers should be encouraged to engage in a systemic way with medication incidents. Further research can be specifically targeted at investigating the major medication errors that significantly affect patients\u0026rsquo; safety, such as the administering, prescribing and dispensing of medication in the NHS compared with the private health sector in the UK.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, insulin produced the highest risk and medication errors compared to anticoagulants and opioids. Moreover, the greatest number of errors could be attributed to three factors: administration of drugs, prescription of drugs, and dispensing of drugs, and that these three factors were related to another three components that determined the nature of medication errors, such as \u0026lsquo;no adequate checking of drugs\u0026rsquo;, \u0026lsquo;communication difficulties among staff and between staff and patients\u0026rsquo;, and \u0026lsquo;high workload of staff\u0026rsquo;. Furthermore, the overall quality of learning in relation to the three main categories of medications was found to be poor, 61.01% and adequate quality of learning was very low for all three main categories, 3.80%, and most of these adequate reports related to insulin, 9.41%, while the other categories accounted for only 1.57%. Health information technology is crucial tool for enhancing patient safety through tracking the medication use process.\u003c/p\u003e"},{"header":"Declarations","content":" \u003ch2\u003eConflicts of Interest\u003c/h2\u003e \u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research was funded by the Researchers Supporting Project number (RSPD2024R778), King Saud University, Riyadh, Saudi Arabia.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAR: Conceptualization, Data curation, Investigation, Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp;editing, Methodology. M.A: ˜ Conceptualization, Supervision, Validation, Writing \u0026ndash; review \u0026amp; editing. WS:Conceptualization, Validation, Writing \u0026ndash; review \u0026amp; editing, Supervision.MJ: \u0026acute; Conceptualization, Supervision, Validation, Writing \u0026ndash; review \u0026amp; editing. KF: Methodology, Validation,Writing \u0026ndash; review \u0026amp; editing, SH: Validation, Writing \u0026ndash; review \u0026amp; editing, MZ: Methodology, Validation,Writing \u0026ndash; review \u0026amp; editing, AM:review \u0026amp; editing\u003c/p\u003e\u003ch2\u003eAcknowledgments:\u003c/h2\u003e \u003cp\u003eThe authors would like to extend their gratitude to Researchers Supporting Project number (RSPD2024R778), King Saud University, Riyadh, Saudi Arabia for funding this work.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWHO. Pharmacovigilance. 2024 [cited 29.02.2024]; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/teams/regulation-prequalification/regulation-and-safety/pharmacovigilance\u003c/span\u003e\u003cspan address=\"https://www.who.int/teams/regulation-prequalification/regulation-and-safety/pharmacovigilance\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAvery AJ, Rodgers S, Cantrill JA, et al. A pharmacist-led information technology intervention for medication errors (PINCER): a multicentre, cluster randomised, controlled trial and cost-effectiveness analysis. Lancet (London England). 2012;379:1310\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang F, Mamtani R, Scott FI, et al. Increasing use of prescription drugs in the United Kingdom. Pharmacoepidemiol Drug Saf. 2016;25:628\u0026ndash;36.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePharmacy AMC. Medication Errors. 2023 [cited 29.02.2024]; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.amcp.org/about/managed-care-pharmacy-101/concepts-managed-care-pharmacy/medication-errors\u003c/span\u003e\u003cspan address=\"https://www.amcp.org/about/managed-care-pharmacy-101/concepts-managed-care-pharmacy/medication-errors\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eA N, GC P. Monitoring and preliminary analysis of internal dispensing errors within a hospital trust. Pharm World Sci 2003; 25: A42\u0026ndash;3.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCousins DH, Gerrett D, Warner B. A review of medication incidents reported to the National Reporting and Learning System in England and Wales over 6 years (2005\u0026ndash;2010). Br J Clin Pharmacol. 2012;74:597\u0026ndash;604.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim J, Shin W. How to do random allocation (randomization). Clin Orthop Surg. 2014;6:103\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAgresti A, Franklin C, Statistics. The Art and Science of Learning from Data: Pearson Education 2013.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDashora U, Castro E. Insulin U100, 200, 300 or 500? Br J Diabetes. 2016;16:10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLamont T, Cousins D, Hillson R, et al. Safer administration of insulin: summary of a safety report from the National Patient Safety Agency. BMJ (Clinical Res ed). 2010;341:c5269.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlshammari FM, Alanazi EJ, Alanazi AM, et al. Medication Error Concept and Reporting Practices in Saudi Arabia: A Multiregional Study Among Healthcare Professionals. Risk Manage Healthc policy. 2021;14:2395\u0026ndash;406.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKelly J, Eggleton A, Wright D. An analysis of two incidents of medicine administration to a patient with dysphagia. J Clin Nurs. 2011;20:146\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStavropoulou C, Doherty C, Tosey P. How Effective Are Incident-Reporting Systems for Improving Patient Safety? A Systematic Literature Review. Milbank Q. 2015;93:826\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNPSA. Organisation patient safety incident reports. 2014. [cited 04.03.2024]; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.nrls.npsa.nhs.uk/patient-safety-data/organisation-patient-safety-incident-reports/\u003c/span\u003e\u003cspan address=\"http://www.nrls.npsa.nhs.uk/patient-safety-data/organisation-patient-safety-incident-reports/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDonaldson LJ, Panesar SS, Darzi A. Patient-safety-related hospital deaths in England: thematic analysis of incidents reported to a national database, 2010\u0026ndash;2012. PLoS Med. 2014;11:e1001667.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrod M, Pohlman B, Kongs JH. Insulin administration and the impacts of forgetting a dose. patient. 2014;7:63\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLawton R, McEachan RRC, Giles SJ, et al. Development of an evidence-based framework of factors contributing to patient safety incidents in hospital settings: a systematic review. BMJ Qual Saf. 2012;21:369\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePal K, Eastwood SV, Michie S et al. Computer-based diabetes self-management interventions for adults with type 2 diabetes mellitus. \u003cem\u003eThe Cochrane database of systematic reviews\u003c/em\u003e 2013; 2013: Cd008776.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 to 11 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Clinical pharmacology, Drug safety, opioids, insulins, anticoagulants, medication error.","lastPublishedDoi":"10.21203/rs.3.rs-4115984/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4115984/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eEnsuring patient safety is paramount in any healthcare system. Rising concerns about medical errors in the UK have necessitated greater focus to be placed on studying the nature of such errors, particularly those involving high-risk medications. This research aims to conduct a retrospective analysis of incidents related to patient safety in the UK, based on data from the NRLS.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis research was conducted based on the review of NRLS patient safety reports published during the period January 1st, 2015 to December 31st, 2015. NHS Improvement provided details regarding the incidents, following approval using a data-sharing agreement. In total, 1,500 incidents were analyzed, equally divided among three categories of high-risk drugs; opioids, insulin and anticoagulants. Excel features and deductive reasoning (thematic analysis) were used in the data analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe results showed that the insulin category had both the highest risk and the most errors compared to anticoagulants and opioids. These errors primarily resulted from issues in administering, prescribing, and dispensing drugs. Inadequate drug checks, communication difficulties among staff and with patients, and high staff workload were often linked to these errors.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study confirms that the NRLS database is a valuable source of data, while the suggestions put forth, based on these results, could contribute to the formulation of measures that diminish the occurrence of errors related to high-risk drugs in healthcare settings. Information technology should enhance medication safety by tracking the processing of medication use.\u003c/p\u003e","manuscriptTitle":"Investigating Safety Incidents with High-Risk Medications: Insights from the National Reporting and Learning System (NRLS) on Opioids, Insulins, and Anticoagulants","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-21 18:30:13","doi":"10.21203/rs.3.rs-4115984/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7a6a607d-f11c-43d6-89fe-f181f9ab9fc0","owner":[],"postedDate":"March 21st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-04-12T18:00:08+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-21 18:30:13","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4115984","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4115984","identity":"rs-4115984","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}