A Quality Improvement Initiative for Strengthening Prescription Writing Practices Among Medical Interns at Healthcare Facilities of Delhi

A Quality Improvement Initiative for Strengthening Prescription Writing Practices Among Medical Interns at Healthcare Facilities of Delhi | 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 A Quality Improvement Initiative for Strengthening Prescription Writing Practices Among Medical Interns at Healthcare Facilities of Delhi Dr Anshita Mishra, Dr Akshithanand K J, Dr Mansi Mandal, Dr Bratati Banerjee This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6573743/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: Prescription errors, often leading to inadequate treatment and adverse effects, are a global concern. In Delhi, a significant percentage of prescriptions have been found to be irrational, highlighting the need for improved prescription writing practices. Objective: This study aims to evaluate and enhance the prescription writing practices of medical interns at healthcare facilities in Delhi through a Quality Improvement (QI) initiative. Methods: The study was conducted over three weeks at three Rural/Urban Health Training Centres under the Department of Community Medicine of a Medical College in Delhi. A total of 50 prescriptions written by interns were audited using a standardized checklist. The QI intervention included training sessions on prescription writing, supervision by junior residents, and the use of checklists. The interventions were developed and tested through repeated Plan-Do-Study-Act (PDSA) cycles. Results: Baseline prescription audits revealed a mean prescription score of 11.88 ± 2.44 with an average of 2.63 ± 1.25 drugs prescribed per prescription. Significant improvements were observed in the mean scores reaching 15.90 ± 2.29 after the final intervention, which was statistically significant (p-value = 0.000). The number of drugs prescribed per prescription decreased, and the proportion of prescriptions with a presumptive diagnosis and appropriate antibiotic use increased. Conclusion: The QI interventions significantly improved the prescription writing practices of medical interns, reducing prescription errors and enhancing patient care. Refresher training and supervision are essential to sustain these improvements. Epidemiology Quality Improvement in Healthcare Prescription audit Medical education Figures Figure 1 Figure 2 Figure 3 INTRODUCTION A prescription is an order of medicines, investigations, and interventions given by the doctor in the management of a patient. 1 Prescriptions are valid legal documents and must include various information, like the date, patient’s data, drug name, strength, form, dosage, and directions for use, ensuring that the patient gets the appropriate required care. 2 Irrational prescriptions have been a global problem, and prescription errors can be seen in a maximum of up to 82% of the prescriptions. These errors can be costly, result in inadequate, erroneous treatment, and potentially cause adverse effects. 3 Hence, healthcare professionals must follow proper prescription writing practices. For regulating such issues, prescription audits are an integral component of comprehensive clinical auditing, forming an essential process for Quality Improvement (QI) in healthcare to enhance patient care and treatment outcomes. It involves a structured assessment of healthcare practices against predefined standards, followed by adopting adjustments to improve care delivery. 3 A prescription audit previously done at a hospital in Delhi highlighted the poor prescribing practices and the need to train our doctors in good prescription practices. 4 A QI strategy refers to any deliberate action directed towards improving the quality of care for a specific patient population similar to everyday clinical settings. 5 QI involves identifying gaps in delivery and implementing small targeted changes to achieve measurable objectives aimed at optimizing patient care and enhancing productivity in a healthcare setting. 6 QI research examines how services delivered to people can achieve the highest level of quality and how to bridge the gap between clinical trials and routine care in a healthcare setup. 7 Through this research, we will study the prescription writing practices of Interns at a medical college in Delhi and train them to improve the quality of care provided at the Primary Health Centres under the Department of Community Medicine. MATERIAL AND METHODS The study was conducted at three Rural/Urban Health Training Centres (RHTC/UHC), under the Department of Community Medicine of a Government Medical College in Delhi. It was designed as a QI study, carried out over three weeks. The study population consisted of MBBS Interns posted at these centers during the study period. According to the National Medical Commission’s Internship curriculum, 15 Interns were posted weekly at the centers. Prior to this study, the Interns had received theoretical training in prescription writing during their medical coursework. However, no structured, hands-on prescription writing training sessions were implemented as part of their clinical rotation at these centers. This lack of practical training was identified as a significant gap, leading to the focus of this study on improving the quality of prescription writing. 1.1 The sample size for the prescription audit was calculated based on NHSRC Prescription Auditing Guidelines, resulting in a requirement of 50 prescriptions. The sample size was determined following recommendations from the guidelines rather than calculated independently. These guidelines provide sample sizes based on total Outpatient Department (OPD) attendance, with a margin of error of -10% and a confidence level of 95%. According to these recommendations, for instance, a population (OPD attendance) of 10 requires a sample size of 9 prescriptions, a population of 50 requires 34 prescriptions, a population of 100 requires 50 prescriptions, a population of 200 requires 66, and a population of 1,000 requires 88 and so on. Fifty prescriptions, written by the Interns across the three centers on the same day, were audited for the study. Table 1 summarizes the study timeline. Table 1: Timeline of activities PHASE DAY ACTIVITY 1 1 Baseline data collection and analysis 2 2 - 3 Planning the intervention/training 3 4 - 5 Carrying out the intervention/training - 1 4 6 Post intervention/training data collection – 1 and analysis 5 7 - 10 Intervention/training – 2 6 11 - 12 Post intervention/training data collection – 2 and analysis 7 13 - 14 Intervention/training – 3 8 15 - 18 Post intervention/training data collection – 3 and analysis A baseline prescription audit was conducted on the first day of the study, coinciding with the beginning of the Interns’ postings at the centers. A standardized checklist, based on the NHSRC Prescription Auditing Guidelines, was used to assess the quality of prescription writing. The checklist included 26 items, of which 25 were used to calculate the total score. The 26th item was the number of drugs prescribed per prescription, used to monitor prescription patterns. To evaluate the quality of the prescriptions, the checklist covered essential elements such as patient details, drug details, dose, frequency, and legibility. Each prescription was reviewed for the presence or absence of these elements, which contributed to the overall score. 1.2 The analysis was followed by Root Cause Analysis (RCA) using a fishbone diagram (Fig. 1) to identify the reasons behind suboptimal prescription practices. Quality improvement tools like the Plan-Do-Study-Act (PDSA) cycles were employed to test and implement interventions aimed at improving prescription writing practices. These interventions included structured training sessions on prescription writing, continuous supervision by Junior Residents, and dissemination of checklist tools at each center for easy reference. Quality improvement tools: We incorporated repeated plan-do-study-act (PDSA) cycles for developing and testing the interventions. 8 In the “plan” phase, meetings were conducted with Interns and Junior Residents, directly supervising the Interns on duty. The team identified the problems and bottlenecks in prescription writing and discussed the possible interventions. The “do” phase involved the execution of the planned interventions. In the “study” phase, the prescription audit using the standard checklist was repeated. Based on the findings of the “study” phase, the “act” phase involved incorporating the changes in the intervention. The PDSA cycle was repeated (Fig. 2). Each intervention was meticulously documented and evaluated to determine the next steps. Details of QI intervention : The QI team brainstormed how to improve the prescription writing practices. For developing the change, various methods were employed in the “do” phase of the PDSA cycles as follows: a. Train Interns on prescription writing and standard treatment guidelines, to develop knowledge and skills. b. Supervising Interns is to be done meticulously by the Junior Residents posted with them for better guidance on a one-to-one basis. c. Checklists were disseminated to all the centers and pasted on the OPD tables so that standard prescription writing guidelines could be easily remembered. The study team did weekly assessments in the form of prescription audits to assess the effectiveness of the interventions. The study was started after receiving Ethical approval from the Institutional Ethics Committee with IEC no:- F.1/IEC/MAMC/109/02/2024/No.321, and waiver for consent had been received. The data collected were entered into MS Excel and analyzed using SPSS version 25. Quantitative data was expressed as mean ± standard deviation. Statistical significance was analyzed using appropriate statistical tools. Analysis of variance (ANOVA) was used to detect the significance of the difference in mean between errors obtained at baseline, before, and after the PDSA cycles, confidence intervals were also calculated for the sample means. RESULTS A baseline prescription audit was conducted on day one, revealing a mean prescription quality score of 11.88 ± 2.44, with a 95% confidence interval (CI) of the mean between 11.36 and 12.76. On average, 2.63 ± 1.25 drugs were prescribed per prescription. This baseline assessment highlighted several areas for improvement, which were visualized using a fishbone diagram to identify major shortcomings (Figure 1). Intervention Phases and Results: Session on Prescription Writing and Standard Treatment Guidelines: The first intervention was an interactive session for Interns where the baseline audit results were presented and discussed. Interns received targeted training on prescription writing and adherence to Standard Treatment Guidelines. This intervention led to a statistically significant improvement in prescription quality, as reflected by a rise in the mean score to 14.29 ± 2.71 (95% CI: 13.56, 14.98). The results of this phase are summarized in Figure 3.a, which demonstrates the distribution of prescription quality scores before and after the intervention. Exercise Session with Scenario-Based Prescription Writing: A week after the first session, Interns participated in a practical exercise involving scenario-based prescription writing. They were given various clinical scenarios to work through, followed by detailed feedback on common errors and areas of improvement. The second intervention further improved the mean score to 14.68 ± 3.4 (95% CI: 13.82, 15.58). Figure 3.a displays the incremental changes in prescription quality scores, with fewer outliers observed as Interns became more proficient. Training Session for Residents: Junior Residents were trained to support and supervise the Interns more effectively, focusing on key errors identified during the audits. Prescription checklists were distributed to the health centers and displayed prominently in the OPD areas for easy reference. This intervention led to a final increase in the mean score to 15.90 ± 2.29 (95% CI: 15.28, 16.56). The box-and-whisker plot (Figure 3.a) illustrates the score distribution across all three phases, highlighting the progressive improvement in prescription quality. The improvements in mean prescription scores across the interventions were found to be statistically significant, as confirmed by an ANOVA test (F = 21.67, p-value = 0.000). Figure 3.a visually emphasizes the reduction in score variability and the overall upward trend in prescription quality scores. Additionally, the number of drugs prescribed per prescription also showed a decreasing trend over the course of the study. At baseline, the average was 2.63 ± 1.25 drugs per prescription, ranging from 1 to 7 drugs. After the first, second, and third interventions, the averages dropped to 2.29 ± 1.38, 2.28 ± 0.86, and 2.17 ± 0.88 drugs per prescription, respectively. This is illustrated in Figure 3.b, which shows a steady reduction in the number of drugs prescribed as Interns adhered more closely to Standard Treatment Guidelines and rational prescribing practices. Table 2: Change in prescription parameters over the different phases. Prescription parameter Baseline (%) Post Intervention 1 (%) Post Intervention 2 (%) Post Intervention 3 (%) Presumptive diagnosis 10 24 38 50 Antibiotic use 12 4 14 12 Appropriateness of antibiotic use 10 4 10 12 Investigations advised 14 10 6 8 Table 2 illustrates key prescription parameters assessed at each phase of the study, demonstrating improvements in the inclusion of presumptive diagnoses and the rational use of antibiotics. The reduction in inappropriate antibiotic use is particularly noteworthy, as it reflects the success of the training sessions in reinforcing evidence-based prescribing practices. Figure 3.a shows the spread and central tendency of prescription quality scores at baseline and after each intervention. The trend of increasing scores and decreasing variability indicates a positive impact of the interventions on prescription quality. Figure 3.b presents the distribution of the number of drugs prescribed per prescription over the different phases of the study. The plot highlights a decreasing trend, showing that the interventions helped reduce polypharmacy and encouraged more focused prescribing practices. Overall, the interventions significantly improved both the quality of prescriptions and the number of drugs prescribed per prescription. Changes in key prescription parameters are detailed in Table 2, further illustrating the impact of the quality improvement efforts. DISCUSSION This QI study aimed to enhance the prescription writing skills of interns at the urban and rural health training centers under the Department of Community Medicine of a Medical College in Delhi. By focusing on improving these practices, the study empowered interns to provide better patient care. After the final intervention, the average prescription score increased to 15.90 ± 2.29, demonstrating significant improvement in prescription quality. Antibiotic use was reduced to 12%, and, importantly, all instances of antibiotic use were deemed appropriate. Notably, the proportion of prescriptions that included a presumptive diagnosis increased from 10% at baseline to 50% post-intervention. Additionally, only 8% of prescriptions included investigation requests, suggesting more selective and evidence-based clinical decision-making. One of the most crucial measures of prescription quality in this study was the number of drugs prescribed per prescription. At baseline, the average was 2.63 ± 1.25, with a maximum of seven drugs prescribed in some cases. After the interventions, the average number of drugs prescribed per prescription reduced to 2.17 ± 0.88, with no more than four drugs being prescribed at any given time. This decrease is significant, as polypharmacy—defined by the World Health Organization (WHO) as the use of five or more medications—is associated with increased risk of adverse drug reactions, medication errors, and higher healthcare costs. Reducing polypharmacy is critical for promoting rational drug use and improving patient safety. 1 . 4 In comparison, Singh et al. reported antibiotic usage rates of 50%, which is significantly higher than the WHO recommendation of 20–25.4%. 4 The results from our study fall well within the WHO’s recommended range, underscoring the effectiveness of our interventions in promoting rational antibiotic use. Furthermore, the findings from this study align with those from a study conducted at a medical college in Madhya Pradesh, which reported an average of 2.2 drugs per prescription. 10 These findings support the broader applicability of the interventions used in our study to improve prescription practices across different settings. Additionally, our study draws parallels to the work by Gupta et al., where prescription audits were conducted in pediatric outpatient departments to reduce prescription errors. 11 Similar to our findings, the creation of customized standard treatment guidelines significantly reduced errors in their study. In our study, interns suggested during discussions that department-developed standard treatment guidelines tailored for trainees would help boost their confidence and reduce prescription errors, making it a sustainable intervention. This feedback highlights the importance of providing simple, accessible tools that reinforce best practices in prescription writing. CONCLUSION This Quality Improvement (QI) study successfully enhanced the prescription writing skills of medical interns through targeted interventions, resulting in measurable improvements in prescription quality and patient care. The use of PDSA cycles enabled a structured approach to identify and address key deficiencies in prescription practices. Notably, the interventions led to a significant reduction in polypharmacy, with the average number of drugs prescribed per prescription dropping from 2.63 to 2.17. In addition, antibiotic use was reduced and better aligned with evidence-based guidelines, as demonstrated by the decrease in inappropriate antibiotic prescriptions. The substantial increase in prescriptions including a presumptive diagnosis (from 10–50%) indicates improved diagnostic clarity, which is essential for appropriate patient management. These improvements were supported by continuous supervision and scenario-based training, which fostered a deeper understanding of rational prescribing. To ensure that the improvements observed in this study are sustained, several steps need to be taken. Refresher training sessions need to be set up for each new batch of interns posted at the health centers. Additionally, supervision and guidance by Junior Residents, aided by the introduction of standardized treatment guidelines for common conditions could provide a long-term solution, offering a readily available reference for interns and other healthcare providers. While the study’s short duration limited our ability to observe long-term effects, the results highlight the value of incorporating standard treatment guidelines and routine audits to ensure sustained improvements. By embedding these practices into the medical training curriculum, there is potential to continuously enhance prescription quality and optimize patient outcomes across various clinical settings. Declarations FUNDING There is no source of funding for this study. CONFLICTS OF INTEREST There is no conflict of interests. References Definition of prescription [Internet]. National Cancer Institute. 2011; [cited 2024 Feb 26]. Available from: https://www.cancer.gov/publications/dictionaries/cancer-terms/def/prescription Kenny BJ, Preuss CV. Pharmacy Prescription Requirements. [Internet]. StatPearls Publishing. 2024; [cited 2024 Feb 26]. Available from: http://www.ncbi.nlm.nih.gov/books/NBK538424/ Van den Bogert C, Mestrinaro M, Weerasuriya K. The pursuit of responsible use of medicines: Sharing and learning from country experiences. World Health Organization. 2012. Singh T, Banerjee B, Garg S, Sharma S. A prescription audit using the World Health Organization-recommended core drug use indicators in a rural hospital of Delhi. J Educ Health Promot. 2019;8:37. Prescription Audit Guidelines [Internet]. National Health Systems Resource Centre. 2021; [cited 2024 Feb 20]. Available from: https://nhsrcindia.org/sites/default/files/2021-07/1534_Prescription%20Audit%20Guidelines16042021.pdf Hughes RG. Tools and Strategies for Quality Improvement and Patient Safety. Patient Safety and Quality: An Evidence-Based Handbook for Nurses [Internet]. Rockville (MD): Agency for Healthcare Research and Quality (US). 2008; [cited 2024 Feb 26]. Available from: http://www.ncbi.nlm.nih.gov/books/NBK2682/ Simpson B, Statile AM, Schondelmeyer AC. How to Perform Quality Improvement Projects. Pediatr Rev. 2022 Oct 1;43(10):549–60. Berwick DM. Developing and testing changes in delivery of care. Ann Intern Med. 1998;128(8):651e656 Medication safety in polypharmacy: technical report [Internet]. World Health Organization; 2019 [cited 2024 Jun 16]. Available from: https://www.who.int/publications/i/item/WHO-UHC-SDS-2019.11 Rai N, Jhaj R, S. B. An audit of outpatient prescriptions and drug use pattern at a tertiary care centre of Central India. Indian J Pharm Pharmacol. 2018;5(1):33-36. Gupta A, Malhotra S, Mandal S, Ahmad A, Polisetty V, Shaik DN, et al. A quality improvement initiative to reduce prescription error in a pediatrics outpatient department at a secondary-level community hospital. Cureus. 2024;16(3):e56004. Additional Declarations The authors declare no competing interests. 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. 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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-6573743","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":450754045,"identity":"c955f68e-8fc7-4ffc-bf83-169e5d8f1244","order_by":0,"name":"Dr Anshita Mishra","email":"","orcid":"","institution":"Maulana Azad Medical College","correspondingAuthor":false,"prefix":"Dr","firstName":"Anshita","middleName":"","lastName":"Mishra","suffix":""},{"id":450754046,"identity":"86084ec9-5e1d-4aca-92be-cae77fe6116d","order_by":1,"name":"Dr Akshithanand K J","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIiWNgGAWjYDACHgY2hgQQxczG+ADE5yNFC7MBiM9GlBYIYGOTAFOEdPD3HH/24MEfOxlzdra0yq85djJsDMwPH93Ao0XibI+5QWJbMo9lM9ux27LbkoEOYzM2zsFnzXkeNonEBmYeg8PsbbcltzEDtfCwSePTIn+e/ZlEwp96sJZiyW31hLUYnG0wk0hgOwzUwnaM8eO2w4S1GJ45YyaR2HYcpCVZmnHbcR42ZgJ+kTuT/kzyx59qe4Pzxww//txWbc/P3vzwMV7vIwNmHjBJrHIQYPxBiupRMApGwSgYMQAAHDdATfcReOgAAAAASUVORK5CYII=","orcid":"","institution":"Maulana Azad Medical College","correspondingAuthor":true,"prefix":"Dr","firstName":"Akshithanand","middleName":"K","lastName":"J","suffix":""},{"id":450754047,"identity":"b373a3b5-5282-4d2f-8436-0a268e6cf502","order_by":2,"name":"Dr Mansi Mandal","email":"","orcid":"","institution":"Maulana Azad Medical College","correspondingAuthor":false,"prefix":"Dr","firstName":"Mansi","middleName":"","lastName":"Mandal","suffix":""},{"id":450754048,"identity":"3836444c-930f-4eb9-9d7d-4b00a543f7fb","order_by":3,"name":"Dr Bratati Banerjee","email":"","orcid":"","institution":"Maulana Azad Medical College","correspondingAuthor":false,"prefix":"Dr","firstName":"Bratati","middleName":"","lastName":"Banerjee","suffix":""}],"badges":[],"createdAt":"2025-05-01 18:26:44","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6573743/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6573743/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":81966634,"identity":"1f872f1a-580f-4fa8-b48b-1e5f47e883c9","added_by":"auto","created_at":"2025-05-05 11:37:29","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":200191,"visible":true,"origin":"","legend":"\u003cp\u003eFishbone diagram for root cause analysis of inadequate prescription writing by Interns\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6573743/v1/82c7d29d4ff42a745d5cb4f0.png"},{"id":81965380,"identity":"ccd398f9-8915-469b-a5b7-898f9df41db0","added_by":"auto","created_at":"2025-05-05 11:29:29","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":200735,"visible":true,"origin":"","legend":"\u003cp\u003eSummary of PDSA cycles done across the three phases of intervention.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6573743/v1/0d98ff1d0064c49b807b0c81.png"},{"id":81967925,"identity":"94fd305d-b941-4333-97e6-a049d0e894cd","added_by":"auto","created_at":"2025-05-05 11:45:29","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":114144,"visible":true,"origin":"","legend":"\u003cp\u003ea: Change in mean score\u003c/p\u003e\n\u003cp\u003eb: Change in number of drugs per prescription\u003c/p\u003e\n\u003cp\u003eNote: The asterisk in the diagram represents the mean and the horizontal line in the box, the median. The whiskers show the range, and any outliers are plotted as individual points.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6573743/v1/a05f063155c52a50cfd2b9ad.png"},{"id":81968729,"identity":"b48e914e-013a-4fe6-95d3-0d67f246e0c8","added_by":"auto","created_at":"2025-05-05 11:53:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":894463,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6573743/v1/755f655f-f680-465b-8da9-e547e48cc3c2.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eA Quality Improvement Initiative for Strengthening Prescription Writing Practices Among Medical Interns at Healthcare Facilities of Delhi\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eA prescription is an order of medicines, investigations, and interventions given by the doctor in the management of a patient.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e Prescriptions are valid legal documents and must include various information, like the date, patient\u0026rsquo;s data, drug name, strength, form, dosage, and directions for use, ensuring that the patient gets the appropriate required care.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Irrational prescriptions have been a global problem, and prescription errors can be seen in a maximum of up to 82% of the prescriptions. These errors can be costly, result in inadequate, erroneous treatment, and potentially cause adverse effects.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Hence, healthcare professionals must follow proper prescription writing practices.\u003c/p\u003e \u003cp\u003eFor regulating such issues, prescription audits are an integral component of comprehensive clinical auditing, forming an essential process for Quality Improvement (QI) in healthcare to enhance patient care and treatment outcomes. It involves a structured assessment of healthcare practices against predefined standards, followed by adopting adjustments to improve care delivery.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e A prescription audit previously done at a hospital in Delhi highlighted the poor prescribing practices and the need to train our doctors in good prescription practices.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eA QI strategy refers to any deliberate action directed towards improving the quality of care for a specific patient population similar to everyday clinical settings.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e QI involves identifying gaps in delivery and implementing small targeted changes to achieve measurable objectives aimed at optimizing patient care and enhancing productivity in a healthcare setting.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e QI research examines how services delivered to people can achieve the highest level of quality and how to bridge the gap between clinical trials and routine care in a healthcare setup.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThrough this research, we will study the prescription writing practices of Interns at a medical college in Delhi and train them to improve the quality of care provided at the Primary Health Centres under the Department of Community Medicine.\u003c/p\u003e"},{"header":"MATERIAL AND METHODS","content":"\u003cp\u003eThe study was conducted at three Rural/Urban Health Training Centres (RHTC/UHC), under the Department of Community Medicine of a Government Medical College in Delhi. It was designed as a QI study, carried out over three weeks. The study population consisted of MBBS Interns posted at these centers during the study period. According to the National Medical Commission\u0026rsquo;s Internship curriculum, 15 Interns were posted weekly at the centers.\u003c/p\u003e\n\u003cp\u003ePrior to this study, the Interns had received theoretical training in prescription writing during their medical coursework. However, no structured, hands-on prescription writing training sessions were implemented as part of their clinical rotation at these centers. This lack of practical training was identified as a significant gap, leading to the focus of this study on improving the quality of prescription writing.\u003csup\u003e1.1\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eThe sample size for the prescription audit was calculated based on NHSRC Prescription Auditing Guidelines, resulting in a requirement of 50 prescriptions. The sample size was determined following recommendations from the guidelines rather than calculated independently. These guidelines provide sample sizes based on total Outpatient Department (OPD) attendance, with a margin of error of -10% and a confidence level of 95%. According to these recommendations, for instance, a population (OPD attendance) of 10 requires a sample size of 9 prescriptions, a population of 50 requires 34 prescriptions, a population of 100 requires 50 prescriptions, a population of 200 requires 66, and a population of 1,000 requires 88 and so on. Fifty prescriptions, written by the Interns across the three centers on the same day, were audited for the study. Table 1 summarizes the study timeline.\u003c/p\u003e\n\u003cp\u003eTable 1: Timeline of activities\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"631\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePHASE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDAY\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 433px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eACTIVITY\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 433px;\"\u003e\n \u003cp\u003eBaseline data collection and analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e2 - 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 433px;\"\u003e\n \u003cp\u003ePlanning the intervention/training\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e4 - 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 433px;\"\u003e\n \u003cp\u003eCarrying out the intervention/training - 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 433px;\"\u003e\n \u003cp\u003ePost intervention/training data collection \u0026ndash; 1 and analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e7 - 10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 433px;\"\u003e\n \u003cp\u003eIntervention/training \u0026ndash; 2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e11 - 12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 433px;\"\u003e\n \u003cp\u003ePost intervention/training data collection \u0026ndash; 2 and analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e13 - 14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 433px;\"\u003e\n \u003cp\u003eIntervention/training \u0026ndash; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003e15 - 18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 433px;\"\u003e\n \u003cp\u003ePost intervention/training data collection \u0026ndash; 3 and analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eA baseline prescription audit was conducted on the first day of the study, coinciding with the beginning of the Interns\u0026rsquo; postings at the centers. A standardized checklist, based on the NHSRC Prescription Auditing Guidelines, was used to assess the quality of prescription writing. The checklist included 26 items, of which 25 were used to calculate the total score. The 26th item was the number of drugs prescribed per prescription, used to monitor prescription patterns.\u003c/p\u003e\n\u003cp\u003eTo evaluate the quality of the prescriptions, the checklist covered essential elements such as patient details, drug details, dose, frequency, and legibility. Each prescription was reviewed for the presence or absence of these elements, which contributed to the overall score.\u003csup\u003e1.2\u003c/sup\u003e The analysis was followed by Root Cause Analysis (RCA) using a fishbone diagram (Fig. 1) to identify the reasons behind suboptimal prescription practices.\u003c/p\u003e\n\u003cp\u003eQuality improvement tools like the Plan-Do-Study-Act (PDSA) cycles were employed to test and implement interventions aimed at improving prescription writing practices. These interventions included structured training sessions on prescription writing, continuous supervision by Junior Residents, and dissemination of checklist tools at each center for easy reference.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuality improvement tools:\u003c/strong\u003e We incorporated repeated plan-do-study-act (PDSA) cycles for developing and testing the interventions.\u003csup\u003e8\u003c/sup\u003e In the \u0026ldquo;plan\u0026rdquo; phase, meetings were conducted with Interns and Junior Residents, directly supervising the Interns on duty. The team identified the problems and bottlenecks in prescription writing and discussed the possible interventions. The \u0026ldquo;do\u0026rdquo; phase involved the execution of the planned interventions. In the \u0026ldquo;study\u0026rdquo; phase, the prescription audit using the standard checklist was repeated. Based on the findings of the \u0026ldquo;study\u0026rdquo; phase, the \u0026ldquo;act\u0026rdquo; phase involved incorporating the changes in the intervention. The PDSA cycle was repeated (Fig. 2). Each intervention was meticulously documented and evaluated to determine the next steps.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDetails of QI intervention\u003c/strong\u003e: The QI team brainstormed how to improve the prescription writing practices. For developing the change, various methods were employed in the \u0026ldquo;do\u0026rdquo; phase of the PDSA cycles as follows:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ea. Train Interns on prescription writing and standard treatment guidelines, to develop knowledge and skills.\u003c/p\u003e\n\u003cp\u003eb. Supervising Interns is to be done meticulously by the Junior Residents posted with them for better guidance on a one-to-one basis.\u003c/p\u003e\n\u003cp\u003ec. Checklists were disseminated to all the centers and pasted on the OPD tables so that standard prescription writing guidelines could be easily remembered.\u003c/p\u003e\n\u003cp\u003eThe study team did weekly assessments in the form of prescription audits to assess the effectiveness of the interventions.\u003c/p\u003e\n\u003cp\u003eThe study was started after receiving Ethical approval from the Institutional Ethics Committee with IEC no:- F.1/IEC/MAMC/109/02/2024/No.321, and waiver for consent had been received. The data collected were entered into MS Excel and analyzed using SPSS version 25. Quantitative data was expressed as mean \u0026plusmn; standard deviation. Statistical significance was analyzed using appropriate statistical tools. Analysis of variance (ANOVA) was used to detect the significance of the difference in mean between errors obtained at baseline, before, and after the PDSA cycles, confidence intervals were also calculated for the sample means.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eA baseline prescription audit was conducted on day one, revealing a mean prescription quality score of 11.88 \u0026plusmn; 2.44, with a 95% confidence interval (CI) of the mean between 11.36 and 12.76. On average, 2.63 \u0026plusmn; 1.25 drugs were prescribed per prescription. This baseline assessment highlighted several areas for improvement, which were visualized using a fishbone diagram to identify major shortcomings (Figure 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIntervention Phases and Results:\u003c/strong\u003e\u003c/p\u003e\n\u003col start=\"1\" type=\"1\"\u003e\n \u003cli\u003e\u003cstrong\u003eSession on Prescription Writing and Standard Treatment Guidelines:\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;The first intervention was an interactive session for Interns where the baseline audit results were presented and discussed. Interns received targeted training on prescription writing and adherence to Standard Treatment Guidelines. This intervention led to a statistically significant improvement in prescription quality, as reflected by a rise in the mean score to 14.29 \u0026plusmn; 2.71 (95% CI: 13.56, 14.98). The results of this phase are summarized in Figure 3.a, which demonstrates the distribution of prescription quality scores before and after the intervention.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eExercise Session with Scenario-Based Prescription Writing:\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;A week after the first session, Interns participated in a practical exercise involving scenario-based prescription writing. They were given various clinical scenarios to work through, followed by detailed feedback on common errors and areas of improvement. The second intervention further improved the mean score to 14.68 \u0026plusmn; 3.4 (95% CI: 13.82, 15.58). Figure 3.a displays the incremental changes in prescription quality scores, with fewer outliers observed as Interns became more proficient.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eTraining Session for Residents:\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Junior Residents were trained to support and supervise the Interns more effectively, focusing on key errors identified during the audits. Prescription checklists were distributed to the health centers and displayed prominently in the OPD areas for easy reference. This intervention led to a final increase in the mean score to 15.90 \u0026plusmn; 2.29 (95% CI: 15.28, 16.56). The box-and-whisker plot (Figure 3.a) illustrates the score distribution across all three phases, highlighting the progressive improvement in prescription quality.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThe improvements in mean prescription scores across the interventions were found to be statistically significant, as confirmed by an ANOVA test (F = 21.67, p-value = 0.000). Figure 3.a visually emphasizes the reduction in score variability and the overall upward trend in prescription quality scores.\u003c/p\u003e\n\u003cp\u003eAdditionally, the number of drugs prescribed per prescription also showed a decreasing trend over the course of the study. At baseline, the average was 2.63 \u0026plusmn; 1.25 drugs per prescription, ranging from 1 to 7 drugs. After the first, second, and third interventions, the averages dropped to 2.29 \u0026plusmn; 1.38, 2.28 \u0026plusmn; 0.86, and 2.17 \u0026plusmn; 0.88 drugs per prescription, respectively. This is illustrated in Figure 3.b, which shows a steady reduction in the number of drugs prescribed as Interns adhered more closely to Standard Treatment Guidelines and rational prescribing practices.\u003c/p\u003e\n\u003cp\u003eTable 2: Change in prescription parameters over the different phases.\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"504\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003ePrescription parameter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eBaseline (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003ePost\u003c/p\u003e\n \u003cp\u003eIntervention 1\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003ePost\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eIntervention 2\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003ePost\u003c/p\u003e\n \u003cp\u003eIntervention 3\u003c/p\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003ePresumptive diagnosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eAntibiotic use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eAppropriateness of antibiotic use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eInvestigations advised\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eTable 2 illustrates key prescription parameters assessed at each phase of the study, demonstrating improvements in the inclusion of presumptive diagnoses and the rational use of antibiotics. The reduction in inappropriate antibiotic use is particularly noteworthy, as it reflects the success of the training sessions in reinforcing evidence-based prescribing practices.\u003c/p\u003e\n\u003cp\u003eFigure 3.a shows the spread and central tendency of prescription quality scores at baseline and after each intervention. The trend of increasing scores and decreasing variability indicates a positive impact of the interventions on prescription quality.\u003c/p\u003e\n\u003cp\u003eFigure 3.b\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003epresents the distribution of the number of drugs prescribed per prescription over the different phases of the study. The plot highlights a decreasing trend, showing that the interventions helped reduce polypharmacy and encouraged more focused prescribing practices.\u003c/p\u003e\n\u003cp\u003eOverall, the interventions significantly improved both the quality of prescriptions and the number of drugs prescribed per prescription. Changes in key prescription parameters are detailed in Table 2, further illustrating the impact of the quality improvement efforts.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis QI study aimed to enhance the prescription writing skills of interns at the urban and rural health training centers under the Department of Community Medicine of a Medical College in Delhi. By focusing on improving these practices, the study empowered interns to provide better patient care. After the final intervention, the average prescription score increased to 15.90\u0026thinsp;\u0026plusmn;\u0026thinsp;2.29, demonstrating significant improvement in prescription quality. Antibiotic use was reduced to 12%, and, importantly, all instances of antibiotic use were deemed appropriate. Notably, the proportion of prescriptions that included a presumptive diagnosis increased from 10% at baseline to 50% post-intervention. Additionally, only 8% of prescriptions included investigation requests, suggesting more selective and evidence-based clinical decision-making.\u003c/p\u003e \u003cp\u003eOne of the most crucial measures of prescription quality in this study was the number of drugs prescribed per prescription. At baseline, the average was 2.63\u0026thinsp;\u0026plusmn;\u0026thinsp;1.25, with a maximum of seven drugs prescribed in some cases. After the interventions, the average number of drugs prescribed per prescription reduced to 2.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88, with no more than four drugs being prescribed at any given time. This decrease is significant, as polypharmacy\u0026mdash;defined by the World Health Organization (WHO) as the use of five or more medications\u0026mdash;is associated with increased risk of adverse drug reactions, medication errors, and higher healthcare costs. Reducing polypharmacy is critical for promoting rational drug use and improving patient safety.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e.\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn comparison, Singh et al. reported antibiotic usage rates of 50%, which is significantly higher than the WHO recommendation of 20\u0026ndash;25.4%.\u003csup\u003e4\u003c/sup\u003e The results from our study fall well within the WHO\u0026rsquo;s recommended range, underscoring the effectiveness of our interventions in promoting rational antibiotic use. Furthermore, the findings from this study align with those from a study conducted at a medical college in Madhya Pradesh, which reported an average of 2.2 drugs per prescription.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e These findings support the broader applicability of the interventions used in our study to improve prescription practices across different settings.\u003c/p\u003e \u003cp\u003eAdditionally, our study draws parallels to the work by Gupta et al., where prescription audits were conducted in pediatric outpatient departments to reduce prescription errors.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e Similar to our findings, the creation of customized standard treatment guidelines significantly reduced errors in their study. In our study, interns suggested during discussions that department-developed standard treatment guidelines tailored for trainees would help boost their confidence and reduce prescription errors, making it a sustainable intervention. This feedback highlights the importance of providing simple, accessible tools that reinforce best practices in prescription writing.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis Quality Improvement (QI) study successfully enhanced the prescription writing skills of medical interns through targeted interventions, resulting in measurable improvements in prescription quality and patient care. The use of PDSA cycles enabled a structured approach to identify and address key deficiencies in prescription practices. Notably, the interventions led to a significant reduction in polypharmacy, with the average number of drugs prescribed per prescription dropping from 2.63 to 2.17. In addition, antibiotic use was reduced and better aligned with evidence-based guidelines, as demonstrated by the decrease in inappropriate antibiotic prescriptions. The substantial increase in prescriptions including a presumptive diagnosis (from 10\u0026ndash;50%) indicates improved diagnostic clarity, which is essential for appropriate patient management. These improvements were supported by continuous supervision and scenario-based training, which fostered a deeper understanding of rational prescribing.\u003c/p\u003e \u003cp\u003eTo ensure that the improvements observed in this study are sustained, several steps need to be taken. Refresher training sessions need to be set up for each new batch of interns posted at the health centers. Additionally, supervision and guidance by Junior Residents, aided by the introduction of standardized treatment guidelines for common conditions could provide a long-term solution, offering a readily available reference for interns and other healthcare providers.\u003c/p\u003e \u003cp\u003e While the study\u0026rsquo;s short duration limited our ability to observe long-term effects, the results highlight the value of incorporating standard treatment guidelines and routine audits to ensure sustained improvements. By embedding these practices into the medical training curriculum, there is potential to continuously enhance prescription quality and optimize patient outcomes across various clinical settings.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFUNDING\u003c/h2\u003e\n\u003cp\u003eThere is no source of funding for this study.\u003c/p\u003e\n\u003ch2\u003eCONFLICTS OF INTEREST\u003c/h2\u003e\n\u003cp\u003eThere is no conflict of interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eDefinition of prescription [Internet]. National Cancer Institute. 2011; [cited 2024 Feb 26]. Available from: https://www.cancer.gov/publications/dictionaries/cancer-terms/def/prescription\u003c/li\u003e\n \u003cli\u003eKenny BJ, Preuss CV. Pharmacy Prescription Requirements. [Internet]. StatPearls Publishing. 2024; [cited 2024 Feb 26]. Available from: http://www.ncbi.nlm.nih.gov/books/NBK538424/\u003c/li\u003e\n \u003cli\u003eVan den Bogert C, Mestrinaro M, Weerasuriya K. The pursuit of responsible use of medicines: Sharing and learning from country experiences. World Health Organization. 2012.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSingh T, Banerjee B, Garg S, Sharma S. A prescription audit using the World Health Organization-recommended core drug use indicators in a rural hospital of Delhi. J Educ Health Promot. 2019;8:37.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003ePrescription Audit Guidelines [Internet]. National Health Systems Resource Centre. 2021; [cited 2024 Feb 20]. Available from: https://nhsrcindia.org/sites/default/files/2021-07/1534_Prescription%20Audit%20Guidelines16042021.pdf\u003c/li\u003e\n \u003cli\u003eHughes RG. Tools and Strategies for Quality Improvement and Patient Safety. Patient Safety and Quality: An Evidence-Based Handbook for Nurses [Internet]. Rockville (MD): Agency for Healthcare Research and Quality (US). 2008; [cited 2024 Feb 26]. Available from: http://www.ncbi.nlm.nih.gov/books/NBK2682/\u003c/li\u003e\n \u003cli\u003eSimpson B, Statile AM, Schondelmeyer AC. How to Perform Quality Improvement Projects. Pediatr Rev. 2022 Oct 1;43(10):549\u0026ndash;60.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eBerwick DM. Developing and testing changes in delivery of care. Ann Intern Med. 1998;128(8):651e656\u003c/li\u003e\n \u003cli\u003eMedication safety in polypharmacy: technical report [Internet]. World Health Organization; 2019 [cited 2024 Jun 16]. Available from: https://www.who.int/publications/i/item/WHO-UHC-SDS-2019.11\u003c/li\u003e\n \u003cli\u003eRai N, Jhaj R, S. B. An audit of outpatient prescriptions and drug use pattern at a tertiary care centre of Central India. Indian J Pharm Pharmacol. 2018;5(1):33-36.\u003c/li\u003e\n \u003cli\u003eGupta A, Malhotra S, Mandal S, Ahmad A, Polisetty V, Shaik DN, et al. A quality improvement initiative to reduce prescription error in a pediatrics outpatient department at a secondary-level community hospital. Cureus. 2024;16(3):e56004.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"Quality Improvement in Healthcare, Prescription audit, Medical education","lastPublishedDoi":"10.21203/rs.3.rs-6573743/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6573743/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Prescription errors, often leading to inadequate treatment and adverse effects, are a global concern. In Delhi, a significant percentage of prescriptions have been found to be irrational, highlighting the need for improved prescription writing practices.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e This study aims to evaluate and enhance the prescription writing practices of medical interns at healthcare facilities in Delhi through a Quality Improvement (QI) initiative.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e The study was conducted over three weeks at three Rural/Urban Health Training Centres under the Department of Community Medicine of a Medical College in Delhi. A total of 50 prescriptions written by interns were audited using a standardized checklist. The QI intervention included training sessions on prescription writing, supervision by junior residents, and the use of checklists. The interventions were developed and tested through repeated Plan-Do-Study-Act (PDSA) cycles.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Baseline prescription audits revealed a mean prescription score of 11.88 ± 2.44 with an average of 2.63 ± 1.25 drugs prescribed per prescription. Significant improvements were observed in the mean scores reaching 15.90 ± 2.29 after the final intervention, which was statistically significant (p-value = 0.000). The number of drugs prescribed per prescription decreased, and the proportion of prescriptions with a presumptive diagnosis and appropriate antibiotic use increased.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e The QI interventions significantly improved the prescription writing practices of medical interns, reducing prescription errors and enhancing patient care. Refresher training and supervision are essential to sustain these improvements.\u003c/p\u003e","manuscriptTitle":"A Quality Improvement Initiative for Strengthening Prescription Writing Practices Among Medical Interns at Healthcare Facilities of Delhi","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-05 11:29:24","doi":"10.21203/rs.3.rs-6573743/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":"5bf5fe4c-22f2-4bd8-896a-f8e9f1d57935","owner":[],"postedDate":"May 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":48056366,"name":"Epidemiology"}],"tags":[],"updatedAt":"2025-05-05T11:29:24+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-05 11:29:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6573743","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6573743","identity":"rs-6573743","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}