Prescribing trends-branded versus unbranded generics and rational use of medicine at public health facilities in Maharashtra, India

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To address the issue of accessibility, a generic medicine scheme called Jan Aushadhi (JA translates to People’s Medicine) was revamped and expanded in 2015. Additionally, physicians were advised to comply with the erstwhile Medical Council of India’s regulation of prescribing medicines by their salt names. This is the first study which not only assessed the quality of prescriptions in public health facilities, but also examined whether the doctors' prescribing behaviours in public facilities are in sync with the government’s intent to improve access to medicines through promotion of generics. Methods A survey was conducted at JA pharmacies near 11 public healthcare facilities in Mumbai and Palghar. Prescription slips written by doctors from the public healthcare system were collected from all patients who visited the JA pharmacies. After excluding prescriptions with illegible handwritings and incomplete data, a total of 330 prescriptions were included in the analysis. Results: The mean number of drugs per prescription was 2.7 and 4 for outpatients and inpatients, respectively. More than 53% of the outpatient prescription slips had no diagnosis on them, nearly 60% were devoid of patients’ signs and symptoms, and listed branded medicines instead of generics. Among outpatient prescriptions, 1% contained injectable, while 32% included antibiotics. However, for those hospitalised, 82% of their prescriptions included injectable, and 64% contained antibiotics. Nearly 78% of the medicines prescribed came from the JA list. A total of 85% of drugs were prescribed from the Maharashtra State essential medicine list (EML) with 86% of OPD drugs and 83% of IPD drugs falling under this category. Conclusion: The analysis reveals highly unsatisfactory prescribing practices in public health facilities. This underscores the urgent need to review the current laws regulating the practice of medicines, particularly those concerning the requirements for writing legible prescriptions, documenting patients' signs and symptoms, recording complete medical histories, selecting appropriate medications, making accurate diagnoses, and providing proper follow-up care. Equally important is to arm the public health authorities to ensure the implementation of these prescription regulations. Jan Aushadhi scheme essential medicines prescription pattern prescribing indicators polypharmacy generics rational drug practices Background According to the World Health Organization (WHO), while nearly a third of the global population lacks access to essential medicines [ 1 , 2 ], about half of all medications worldwide are improperly prescribed, dispensed, or consumed [ 1 ]. This widespread inappropriate usage contributes to irrational prescribing, which can lead to adverse drug reactions (ADRS). ADRs pose a serious threat to public health, contributing to increased rates of mortality and escalating medical costs [ 3 ]. Inappropriate prescribing practices limit access to essential medicines, often resulting in ineffective or harmful treatments, prolonged illnesses, and increased healthcare expenditures [ 3 ]. It is estimated that effective medication use could alleviate up to 80% of the burden of non-communicable diseases (NCDs) [ 4 ]. However, overprescribing and polypharmacy represent serious public health concerns globally, and India is no exception. A study conducted in India reveals that 69.2% of medicine expenditure in the private sector and 55.2% in the public sector are wasteful [ 5 ]. Moreover, high out-of-pocket expenditures (OOPE) on healthcare push about 3% of Indians below the poverty line annually [ 6 ]. Notably, medicine is the dominant contributor to OOP health payments in India [ 7 ]. More importantly, many in India either postpone or completely avoid seeking treatment owing to the high cost of medicines, which further worsens their health conditions [ 8 ]. Conversely, a large number of patients suffer harm and increased costs of treatment because of inappropriate and non-beneficial overuse of medicines. Porter and Grills (2016) estimated that 50% of household OOP health spending in India is on unnecessary medications or investigations [ 9 ]. Moreover, the consumption of useless medicines leads to adverse effects, including antibiotic resistance. Around 400,000 die every year due to ADRs in India [ 10 ]. Addressing these challenges necessitates improved access to affordable essential medicines and enhanced prescribing efficiency. The promotion of generic medicines, as opposed to more expensive branded alternatives, plays a fundamental role in improving accessibility and affordability. Jan Aushadhi Scheme In 2008, the United Progressive Alliance (UPA) government launched the ‘Jan Aushadhi Scheme’ (JAS), an initiative aimed at providing unbranded, quality-assured generic medicines at affordable prices, particularly benefiting economically disadvantaged populations across the country. As part of this scheme, dedicated outlets known as ‘Jan Aushadhi Kendras’ were established to ensure access to these affordable medicines. However, the programme experienced a slow start, and by 2015—after six years of operation—only 80 Jan Aushadhi Kendras had been set up in selected states [ 11 ]. Despite its objectives, the scheme faced numerous challenges that hindered its success. These included excessive reliance on state governments for implementation, inefficiencies in supply chain operations, reluctance among physicians to prescribe generic medicines, competition from state-sponsored schemes distributing free medicines, limited availability of drugs under JAS, and public misconceptions regarding the quality of generic medicines [ 12 , 13 ]. To address these challenges, the JAS was restructured and rebranded in September 2015 as the Pradhan Mantri Bhartiya Jan Aushadhi Pariyojana (PMBJP) under the National Democratic Alliance (NDA) government, accompanied by the introduction of a new Strategic Action Plan (SAP). This revamped initiative aimed to expand the number of PMBJP pharmacies, particularly in rural areas, while enhancing public awareness of the scheme and encouraging government doctors to prescribe generic medicines, with active collaboration from state governments. Since its restructuring in 2015, the number of PMBJP stores has significantly increased, rising from 80 in 2015 to over 13,822 in 2024 [ 14 ]. In India, current regulations require registered physicians to prescribe medications using generic names, which should be clearly written and preferably in capital letters. Physicians are also expected to ensure that prescriptions are rational and that drugs are used appropriately. The National Medical Commission Act of 2019 gives the relevant State Medical Councils or the Ethics and Medical Registration Board (EMRB) of the National Medical Commission the authority to take disciplinary action against any doctor who violates these regulations. However, concerns regarding the quality and effectiveness of generics persist within the medical fraternity. To tackle these issues, the Indian government has mandated that suppliers obtain WHO-GMP certification and has established requirements for bioequivalence studies to secure manufacturing licenses. Additionally, to ensure that generic medicines are affordable for everyone, the Department of Pharmaceuticals and the Pharmaceuticals & Medical Devices Bureau of India (PMBI) is actively promoting PMBJP initiative through advertisements in electronic media, print media, and outdoor publicity [ 15 ]. Despite these measures, real-world adoption remains low due to persisting physician scepticism about effectiveness of certain non-branded generic medicines [ 16 ]. Studies show that only a small (10–16%) percentage of prescriptions are for generics, contradicting India's National Standard Treatment Guidelines (STG) , which emphasize the prescription of medicines in their generic form, and the WHO’s global standard of 100% generic prescription [ 17 , 18 ]. Importance of rational prescribing practices Rational prescribing is essential to prevent the widespread issue of irrational medicine use. Common examples include polypharmacy, which involves prescribing too many medicines per patient which are often more expensive and offer no advantage over single compound products. Other issues include the unnecessary use of injections when oral administration is appropriate, the overuse of antimicrobials, and poor adherence to standard treatment guidelines [ 1 ]. These practices can result in delayed diagnoses, increased side effects, drug resistance, high treatment costs, wasted resources, diminished trust in medical systems, prolonged disease states, and even mortality in chronic conditions [ 19 ]. Various researches indicated a rising trend of inappropriate medication use in the current Indian healthcare system with wide variation in prevalence rate of polypharmacy across different states with 5.8% in West Bengal to 93.1% in Uttaranchal [ 20 ]. Also, it is worthwhile to note that rising trend of polypharmacy practices was seen specifically among older adults and paediatric patients [ 21 , 22 , 23 ]. Besides India, similar trends in irrational prescribing have been observed in other South Asian and African countries. For instance, in Nepal, the average number of medications per prescription is considerably high, antibiotics are overprescribed; and the generic prescribing rate is quite low [ 24 ]. Comparable patterns are evident in Sudan, Nigeria, and Ethiopia, where antibiotic use often surpasses WHO-recommended levels [ 3 , 19 ]. Antimicrobial resistance imposes an immense financial burden on healthcare systems across the globe [ 5 ]. Two fundamental aspects of rational prescribing are cost-effectiveness and the safety and efficacy of treatment options. In India, promoting the use of unbranded generic medicines can significantly enhance consumer access to essential drugs while reducing healthcare expenses, without compromising therapeutic quality [ 25 ]. Given the pivotal role of prescribing behaviour in facilitating the adoption of generic medicines, evaluating physicians' prescribing patterns is critical. Additionally, irrational prescribing contributes substantially to high out-of-pocket expenditures (OOPE) for medicines, highlighting the necessity of assessing prescription rationality using the World Health Organization’s core prescribing indicators. However, there remains a lack of comprehensive evidence regarding the correlation between prescribing behaviours in public healthcare facilities and initiatives aimed at improving medicine accessibility, such as the Jan Aushadhi scheme. The present study aims to fill this knowledge gap by examining prescribing trends in public healthcare facilities located near PMBJP pharmacies in the Mumbai and Palghar districts of Maharashtra. Methods Study Design We have used quantitative research design involving an observational cross sectional survey of PMBJPY pharmacies located in the periphery of three levels of public health facilities to collect prescription based data. Copies of prescriptions collected (from July 2019 to August, 2019) from all patients visited to the selected PMBJPY pharmacy located in the periphery of primary health centres (PHCs), rural hospitals (RHs) or sub district hospitals (SDHs) and medical colleges and tertiary hospitals in two districts of Maharashtra. Study setting The survey was conducted in two districts of Maharashtra, namely Mumbai metropolitan region and Palghar. In terms of per capita income, Maharashtra is one of the richer states in India and Mumbai is its capital city. With a population of more than 20 million, the city is one of the most populous urban centres in the world. It has the distinction of being home to the largest slum population in any city in the world, displaying a high level of income inequality. On the other hand, Palghar is an economically backward district with a population of nearly 3 million and is primarily inhabited by the tribal people. In India, healthcare is provided by both private for-profit and not-for-profit and public healthcare facilities. The public healthcare system has three levels: primary, secondary and tertiary. The primary level is the first level of health service contact for individuals, families and communities. It consists of primary health centres (PHC), sub-centres (SC) and health posts (HP). The secondary level comprises rural hospitals and municipal general hospitals that people go to after referral from primary healthcare centres. Finally, the tertiary level comprises medical college and hospitals. These facilities have specialists and facilities for advanced medical investigation and treatment. Sampling of Public health facilities and PMBJP pharmacy The WHO’s guidelines on drug use recommend at least 20 facilities and at least 30 encounters per facility, which entails a total of 600 prescriptions to describe drug use patterns [26]. However, considering the availability of PMBJP pharmacies and public health facilities in these districts, a total of 11 public health facilities were purposively selected based on their proximity to PMBJP pharmacies. Public health facilities include medical college (Tertiary level), Municipal General Hospital (Secondary Level) and PHCs and HPs (Primary level). PMBJP pharmacy’s proximity to the public health facilities was assessed using google maps. The details of the sampled PMBJP pharmacies are provided in Table. 1. Data Collection A structured tool was used to gather information on the prescribing patterns comprises three sections: the average number of medicines per prescription, the number of medicines prescribed by generic and brand names, and the number of medicines prescribed per the Maharashtra State Essential Drug List (2019). The information retrieved from the prescriptions included bio demographic data; working diagnosis; list of prescribed drugs; the dose, frequency and route of administration; and duration of therapy. Any prescription containing one or more medications was considered for collection irrespective of the patients’ disease state (acute or chronic). As all three levels of healthcare facilities were considered, prescriptions of both inpatient and outpatient departments were included in the study. Survey was conducted at 11 PMBJPY pharmacies located in the periphery of the eleven selected Public health care facilities at the primary, secondary and tertiary levels. Public health facilities include Medical College & Hospital (Tertiary level), Municipal General Hospital (Secondary Level) and Health Post (Primary level). Around 30 Prescription slips written by doctors from the public healthcare system were collected from all patients who visited the PMBJPY pharmacies. A total of 330 prescriptions were considered for prescription analysis, excluding those having illegible handwritings and incomplete data. In order to collect data in an accurate and reliable manner, one of the researchers personally visited the selected PMBJPY pharmacy located in the periphery of public health facilities to collect prescription copies. The researcher cum field investigator is trained in both pharmacy and public health with previous experience of conducting primary data collection for health systems research. The WHO, in collaboration with INRUD (The International Network for Rational Use of Drugs), has developed a set of core indicators for measuring the rational use of medicines in healthcare settings. These indicators will enable comparison between health facilities. The core indicators are: prescribing, patient care and healthcare facility-specific indicators. The prescribing indicators help improve prescribing habits and reduce the cost burden on the patient and healthcare systems. The core prescribing indicators are as follows [27,28], The mean number of drugs per prescription. The percentage of drugs prescribed with generic names. The percentage of encounters with antibiotics prescribed. The percentage of encounters with prescribed injections. The number of drugs prescribed from the Essential Medicines List (EML). Data analysis SPSS version 21.0 and MS Excel were used to analyse the quantitative data to assess the WHO prescribing indicators using the WHO guidelines on investigation of drug use in healthcare facilities. The WHO core prescribing indicators were calculated as follows: The mean number of drugs per prescription or encounter was calculated by dividing the total number of different drug products by the number of prescriptions evaluated. The percentage of drugs prescribed using the generic name was determined by dividing the number of drugs prescribed with generic names by the total number of drugs in the prescriptions, multiplied by 100. The percentage of encounters with antibiotics prescribed was calculated by dividing the number of patient encounters during which an antibiotic was prescribed by the total number of patients encountered, multiplied by 100. The percentage of encounters with an injection was determined by dividing the number of encounters during which an injection was prescribed by the total number of patients encountered, multiplied by 100. The percentage of drugs in prescription from the EML was calculated by dividing the number of drugs in the prescription from the EML by the total number of drugs in the prescriptions, multiplied by 100. Results Profile of the prescribers in the study Table 1 presents the profile of the prescribers and the number of prescriptions written by them. In the present study, almost 91% of the prescriptions were written by consultants (medical practitioners with postgraduate education in specialized medical streams such as dermatology, surgery, gynaecology, and internal medicine), and the remaining 9% of the prescriptions were written by general medical practitioners (graduated with an MBBS degree only). Demographic characteristics of the outpatient and inpatients attendees As mentioned earlier, the drug prescriptions of 330 patients were studied. Of these, approximately 62% were aged between 15 and 49 years, 17% were between 50 and 59 years, 11% were between 5 and 14 years and 2% were children under 5 years. Furthermore, the sample distribution of outpatients is skewed in favour of females (56%). However, in the case of IPD patients, there were more male attendees (68%) (Table 3) Drug prescribing practices in outpatient departments The observations on core prescribing indicators suggested by the WHO are presented in Table 4. Approximately 92% of the prescriptions contained 1-4 drugs, followed by 8% with 5-9 drugs. The average number of drugs prescribed per prescription was 2.78±1.27. The mode value was 2, implying that the most common number of medicines prescribed was 2. Notably, in approximately 99% of the sample prescriptions that we analysed, injections were not prescribed. Nearly 1% had 1 injection prescribed. About 32% of prescriptions contained one antibiotic, while 3% had two antibiotics. A total of 86% of the OPD drugs were prescribed from the Maharashtra state EML. The evaluation of prescriptions suggests that a total of 218 (71%) prescriptions had drugs from the EML only, whereas 82 (26.62%) of them had some drugs from the EML and another 08 (2.59%) of them had all drugs that do not feature in the EML. Another important finding that needs to be highlighted is that of all drugs prescribed by the physicians, approximately two-fifths (37%) were found to be branded generics, while the rest (63%) were unbranded generics. Additionally, nearly 78% of the OPD drugs were found to be prescribed from the PMBJP list. However, in regard to the prescriptions of outpatients, almost half of them (49.6%) had drugs from the PMBJP list only, whereas 44.4% of them had some drugs from the PMBJP list, and the remaining 5.8% had no drugs from the PMBJP list. Drug prescribing practices in inpatient departments On average, the total number of medicines prescribed per prescription was found to be 4. 04 . More than half of the IPD prescriptions had one to four drugs per prescription. Moreover, more than one-fourth of prescriptions contained five or more drugs, which is more than double the number of drugs (3 per patient) ideally prescribed to a patient. Almost 82% of the prescriptions had injections, of which nearly 55% had 1-2 injections and nearly 27% of the prescriptions had 4-5 injections. Similarly, approximately 64% of prescriptions contained antibiotics, out of which 45% of prescriptions had one antibiotic and 9% prescriptions had 2-3 antibiotics. Of the total drugs prescribed, 68.2% were generic-generic, while 32% were branded generics. Importantly, the evaluation of prescriptions suggests that only half of the prescriptions had all the drugs prescribed from the EDL list, and the remaining half had some drugs from the EML Overall, 83% of the IPD drugs are listed in the Maharashtra State EML. As far as drugs from the PMBJP list are concerned, 80.9% were prescribed from its drug basket (table 5). Other core prescribing indicators at outpatient departments Of those who sought medical care for conditions not requiring hospitalizations, over 71% were prescribed medicines for three days, and 26% were prescribed medicines for more than four days. The analysis suggests that more than half (53.2%) of the prescription slips had no diagnosis on them, and nearly 60% of the prescriptions were devoid of patients’ signs and symptoms (Table 6). Other core prescribing indicators at inpatient departments More than three-fifths of the inpatients (63.6%) were prescribed drugs for up to 5 days and about one-fourth were prescribed medicines for 6-10 days. In nearly 5% of prescription slips, the diagnosis of the hospitalized patients was not mentioned, and almost one-fourth (23%) of prescriptions did not contain any signs or symptoms (Table 7). Table 8 provides findings on various WHO’s core prescribing indicators and WHO’s optimal value regarding each prescribing indicator. The relationship between antibiotic prescriptions, injections, FDCs, and the total number of drugs prescribed per prescription It is evident from Table 9 that the probability of prescriptions with antibiotics, injections, FDCs and vitamins increases considerably with the quantity of drugs per prescription. Additionally, the examination of prescribing patterns reveals the practice of polypharmacy, with a significant number of prescriptions containing even more than 3 medicines. Discussion According to the WHO manual on investigating drug use patterns, prescription pattern analysis provides valuable insights into the drug utilization scenario at national, state, or individual health facility level [ 27 , 28 ]. The present study systematically examines the prescribing practices of physicians across different levels of public health facilities located near unbranded generic medicine pharmacies in Mumbai and Palghar districts of Maharashtra. In this study, particular attention has been given to the quality of prescriptions, including legibility, the type and quantity of drugs prescribed, adherence to generic naming conventions, and whether the prescribed medicines are included in the state Essential Medicines List (EML) or the PMBJP drug list. Our analysis indicates that, on average, 2.8 medications were prescribed per outpatient prescription, while hospitalized patients received an average of 4 medications per prescription. This prescribing rate surpasses the WHO recommended ideal range of 1.6–1.8 medications per prescription [ 29 ]. However, it remains lower than findings from other studies conducted in different regions of India, where the average ranged from 3.0 to 4.1 medications per prescription [ 30 , 31 , 32 ]. Similarly, prescription rates in neighbouring South Asian countries, Sri Lanka (3.1), Nepal (3.2), and Bangladesh (5.1) also exhibited higher averages [ 33 , 34 , 24 ]. Our findings are consistent with a previously reported study in Central India, which documented an average of 2.89 prescriptions per patient [ 35 ]. However, this rate remains notably higher than reported averages from countries and regions such as Indonesia (2.2), Eritrea (1.62), and Sub-Saharan Africa (2.2) [ 36 , 37 , 38 ]. Our study findings suggest a practice of polypharmacy, with 8% of outpatients and 36% of inpatients receiving 5 or more medications. It implies that many of these prescriptions, particularly for inpatients, are probably irrational. It is worth noting that a recent study across six different urban locations in India estimated the prevalence of polypharmacy to be 33.7% amongst older adults [ 22 ]. Notably, inappropriate polypharmacy is a serious issue in India, and its prevalence is rising, which may be partly ascribed to lack of effective mechanisms in healthcare facilities for ensuring the rational use of drugs, to the inducements given by the pharmaceutical companies to the doctors to overprescribe and physicians’ lack of knowledge concerning rational drug prescribing [ 39 ]. The analysis of prescribed medications revealed a significant predominance of antibiotic use. Specifically, one-third of outpatient prescriptions and two-thirds of inpatient prescriptions contained at least one antibiotic, which is considerably higher than the standard endorsed by the WHO (20.0%-26.8%) [ 26 ]. Like in this study, Sulis et al (2020), using simulated patients, found a very high prevalence of inappropriate antibiotic use in primary healthcare settings in India (49.9%), Kenya (50%) and China (28.8%) [ 43 ]. The issue of inappropriate use of antimicrobials has also been reported in other Asian countries, with rates of 37.9% and 44% found in studies from Nepal and Bangladesh, respectively [ 24 , 33 ]. A study in Africa reported a high prevalence of antibiotic use among hospitalized patients in this region. It concluded that prevalence was relatively higher in West Africa (51.4–83.5%) and North Africa (79.1%) than in East Africa (27.6–73.7%) and South Africa (33.6–49.7%) [ 41 ]. Our study findings of 66.6% of inpatient antibiotic prescription align with trends observed in West and East Africa. What is very concerning is that India has the highest antibiotic consumption and antimicrobial resistance globally [ 42 ]. The significant burden of infectious diseases in India partly explain such a high level of antibiotic use. Studies indicate that inappropriate prescriptions of antibiotics for viral infections and the unnecessary use of broad-spectrum antibiotics when they are not required are significant drivers of antibiotic resistance in the country [ 43 ]. The unnecessary prescribing of broad-spectrum antibiotics arises from various factors, including perceived resistance to narrower-spectrum antibiotics, expectations from both patients and doctors, and a lack of diagnostic tools to identify specific bacterial infections. In response to these issues, the Ministry of Health and Family Welfare has urged doctors to explicitly state the clinical indications, reasons, and justifications when prescribing antimicrobials. This is expected to promote the responsible use of these drugs and reduce the emergence of antimicrobial resistance (AMR) [ 44 ]. Aside from large-scale use of antibiotics, the analysis shows that 34.1% of OPD prescriptions and 81.8% of IPD prescriptions included injections, significantly exceeding the WHO reference value of less than 20% [ 26 ]. The use of injectable in OPD prescriptions is much lower than in IPD prescriptions. In fact, a large proportion of OPD injectable medications were administered to diabetic patients, primarily for insulin therapy. Nevertheless, our study findings related to the percentage of prescriptions with injectable are much higher than those reported in other Asian countries such as Nepal (0.7%), and Bangladesh (17.01%) [ 24 , 33 ]. As mentioned earlier, we explored the extent to which physicians at public health facilities are prescribing medications using generic names. Our analysis reveals that about 40% of prescriptions included medications prescribed by their brand names. This prescribing pattern could plausibly be explained by several factors, including the influence of prescribing mentors, financial incentives, the role of pharmaceutical detailers, the differing levels of training and experience among prescribers, and the availability and adherence to standard treatment guidelines. Besides these reasons, the physicians in India also prefer to prescribe branded generics because of the perceived poor quality of unbranded generics [ 16 ]. Generics dominate the Indian pharmaceutical market, accounting for nearly 97% of the medicines consumed by value. However, most of these are branded generics, with unbranded generics making up only 10% of the share [ 45 ]. Despite their identical chemical composition, branded generics command a significant price premium ranging from 1–200% making them unaffordable for many [ 25 ]. Hence, switching from branded-generic medicine to unbranded generic medicines would lead to substantial cost savings for medicine consumers. We had earlier argued that unbranded generic substitution would reduce pharmaceutical expenditure by 6–1129% of patient’s spending [ 16 ]. In addition to estimating the percentage of generic prescriptions, our study also assesses the proportion of drugs prescribed from the PMBJP list. The findings reveal that almost 78% of the total OPD-prescribed drugs and nearly 81% of the total IPD-prescription drugs align with the PMBJP medicines list and can be dispensed accordingly. When it comes to PMBJP medicines (unbranded generics), it is evident from multiple studies that medicines covered under PMBJPY scheme are significantly cheaper than frequently prescribed branded generics for common ailments and hence unbranded generic substitution through PMBJP initiative could create significant OOP savings for individual patients and for the healthcare system [ 46 , 47 ]. Further, our study estimates that more than three-fourths (85.6%) of OPD drugs and 83.1% of IPD drugs were prescribed from EML. Although the EML prescribing adherence of 86% of OPD and 83% of IPD drugs is in consonance with the results of other study conducted in North India (84%) [ 29 ], but still below the WHO recommended optimal value of 100% [ 26 ]. Studies conducted in various parts of India have shown differing rates of essential medicines prescribing. In Maharashtra, the prescribing rate was found to be 68.9%, while in Central India, it was slightly higher at 75.3%. In contrast, a study from South India reported a significantly higher rate of 93.3% [ 30 , 31 , 35 ]. Our study found that 84% of prescriptions included essential medicines slightly lower than the WHO’s optimal value but still relatively close. This moderate-to-high adherence to the Essential Medicines Drug List (EMDL) may be attributed to the robustness of the State EMDL, which effectively meets patient needs. The increasing adoption of EMDL across the country, along with the continuous expansion of various Essential Medicines Lists (EMLs), including the National EML, likely contributes to this trend. Completeness and legibility of prescriptions We examined the completeness of prescriptions in terms of critical information such as diagnosis, frequency of dosage, strength, and dosage forms, and follow-up visits. The analysis indicates that half of the sample prescriptions were incomplete in different respects. One of the studies from Central India reported that only 19% of prescriptions mentioned proper dose, duration, and frequency (DDF) of prescribed drugs [ 35 ]. Moreover, about half (47%) of the prescriptions were also found to be not legible. Prescription audit studies show that legibility improves with more complete prescriptions but decreases when more brand names are used and as the number of prescribed drugs increases [ 48 ]. Unlike in our study, the percentage of illegible prescriptions was found to be less than 20% in Saudi Arabia (19.8%) and Eritrea (14.1%) [ 48 , 49 ]. This study highlights significant shortcomings in enforcing prescription guidelines, as evidenced by the high number of incomplete and illegible prescriptions. To improve compliance, monitoring capacity should be enhanced within the public health system. Additionally, efforts must be made to significantly improve the doctor-patient ratio, which can help reduce physicians' workload, foster better doctor-patient interactions, and ultimately lead to improved patient outcomes. Relationship between prescribing of antibiotics, injections, FDCs etc. and quantity of drugs prescribed per prescription Aside from legibility, incompleteness and branded drug use issues, prescribing indicators reveal polypharmacy as a prevalent prescription practice, which is a matter of great concern. According to this study, the proportion of prescriptions with antibiotics, injections, fixed dose combinations and vitamins is positively related to the number of drugs per prescription. Likewise, a study conducted in Ethiopia also found that the number of medications prescribed was significantly associated with the prescription of antibiotics [ 50 ]. Another study reveals that patients prescribed three to four medicines are two times more likely to be prescribed an antibiotic compared to those prescribed one to two medicines per encounter [ 51 ]. Responsible use of antibiotics and FDCs are essentially important to reduce prescription cost, enhance treatment adherence, improved health outcomes and confine AMR nationally and internationally. Conclusions Our analysis draws attention to unsatisfactory prescribing practices in public health facilities. This highlights that some interventions, such as dissemination of the guidelines for writing legible prescriptions to all public health facilities, writing complete prescriptions with patient signs and symptoms, complete medical history, rational selection of medicines, diagnosis and follow-up assistance, are needed. In addition, institutions such as the NMC should review the current regulations to address the aforementioned concerns and especially the public health issue of inappropriate polypharmacy and formulate approaches that can lead to appropriate medicine usage in all levels of health care settings. Abbreviations Maharashtra State EML: Maharashtra State Essential Medicine List PMBJP list: Pradhan Mantri Bhartiya Jan Aushadhi Pariyojan list UPA: United Progressive Alliance NDA: National Democratic Alliance PMBI: Pharmaceuticals & Medical Devices Bureau of India SAP: Strategic Action Plan FDC: Fixed-dose combination WHO: World Health Organization OPD: Out Patient Department IPD: Patient Department PHCs: Primary Health Centres RH: Rural Hospital SDH: Subdistrict Hospital AMR: Antimicrobial resistance STGs: Standard Treatment Guidelines Declarations Ethics approval and consent to participate All participants gave their verbal informed consent before the interviews. The study protocol was approved by the School of Health Systems Studies, Tata Institute of Social Sciences, Mumbai. Additionally, the permission to conduct the study was obtained from Pharmaceuticals & Medical Devices Bureau of India (PMBI), Department of Pharmaceuticals, Government of India, The Department of Public Health, Mumbai and the District Collectorate of Palghar district All methods were performed in accordance with the relevant guidelines and regulations. Consent for publication Not applicable Availability of data and materials The data used and or analysed during the current study are not publicly available. The datasets can be obtained from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding We have not received any funding for this study. Authors’ contributions SG was involved in the conception and design of the study as well as drafting, analysis, interpretation and editing. SL was involved in the study conception, data acquisition, analysis, interpretation and drafting the manuscript. Both authors read and approved the final version of the manuscript to be considered for publication. Acknowledgements Not applicable. References World Health Organization. The pursuit of responsible use of medicines: Sharing and learning from country experiences [Internet]. Geneva, Switzerland; 2012 [cited 2021 May 31]. Available from: https://apps.who.int/iris/bitstream/handle/10665/75828/WHO_EMP_MAR_2012.3_eng.pdf?sequence=1 Access to Medicines Foundation. Access to Medicines Index, 2022 [Internet]. 2022 [cited 2025 Apr 6]. Available from: https://accesstomedicinefoundation.org/resource/2022-access-to-medicineindex Tefera BB, Getachew M, Kebede B. Evaluation of drug prescription pattern using World Health Organization prescribing indicators in public health facilities found in Ethiopia: systematic reviews and meta-analysis. J Pharm Policy Pract. 2021;14(31). 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Unmet need for treatment-seeking from public health facilities in India: An analysis of sociodemographic, regional and disease-wise variations. PLOS Glob Public Health. 2022 Apr 19;2(4): e0000148 Porter G, Grills N. Medication misuse in India: a major public health issue in India. J Public Health. 2016;38(2):e150–e157. doi:10.1093/pubmed/fdv072. Thakur H, Thawani V, Raina RS, Kothiyal G, Chakarabarty M. Noncompliance pattern due to medication errors at a Teaching Hospital in Srikot, India. Indian J Pharmacol. 2013;45(3):289-92. doi:10.4103/0253-7613.111899. PMID: 23833376; PMCID: PMC3696304. Kurian O. Jan Aushadhi’s rapid expansion: subnational analysis. 2025. Available from: https://www.orfonline.org/expert-speak/jan-aushadhi-s-rapid-expansion-a-sub-national-analysis Stoppler M, Hecht BK. Generic drugs: are they as good as brand names?. 2014. Available from: http://www.medicinenet.com/script/main/art.asp?articlekey=46204. [Last accessed on 2025 Mar 22]. Thawani V, Mani A, Upmanyu N. Why the Jan Aushadhi Scheme has lost its steam in India? J Pharmacol Pharmacother. 2017;8(3):134–6. doi:10.4103/jpp.JPP_38_17.15. Government of India. Press release. 2024. Available from: https://www.pib.gov.in/PressReleasePage.aspx?PRID=2061631 Government of India. Press release. 2024. Available from: https://www.pib.gov.in/PressReleaseIframePage.aspx?PRID=2108862 Lavtepatil S, Ghosh S. Improving access to medicines by popularising generics: a study of ‘India’s People’s Medicine’ scheme in two districts of Maharashtra. BMC Health Serv Res. 2022;22(643). doi:10.1186/s12913-022-08022-1. Atal S, Jhaj R, Mathur A, Rai N, Misra S, Sadasivam B. Outpatient prescribing trends, rational use of medicine and impact of prescription audit with feedback at a tertiary care centre in India. Int J Health Plan Manage. 2021;36(3):738–753. doi:10.1002/hpm.3116. Hussain S, Yadav SS, Sawlani KK, Khattri S. 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Polypharmacy and self-medication among older adults in Indian urban communities—a cross-sectional study. Sci Rep. 2025 Feb 3;15(1):4062. doi: 10.1038/s41598-024-84627-2. PMID: 39900582; PMCID: PMC11791031. Patel M, Dave D, Shukla A, Patel A, Shah A. Polypharmacy and drug interactions in pediatric prescribing. Hosp Pharmacol Int Multidiscip J. 2025;12:1620-7. doi: 10.5937/hpimj2501620P. Shrestha R, Prajapati S. Assessment of prescription pattern and prescription error in outpatient department at tertiary care district hospital, Central Nepal. J Pharm Policy Pract. 2019;12:16. doi: 10.1186/s40545-019-0177-y. Subramaniam M, Budhia S. Regulating the generic drugs market: Eliminating the difference between branded and unbranded generics. Gujarat Natl Law Univ. 2022. Available from: https://cbcl.nliu.ac.in/competition-law/regulating-the-generic-drugs-market-eliminating-the-difference-between-branded-and-unbranded-generics/. Harvard Medical School, Harvard Pilgrim Health, World Health Organization. Using indicators to measure country pharmaceutical situations: Fact book on WHO level I and level II monitoring indicators. Geneva: WHO; 2006. Isah AO, Ross-Degnan D, Quick J, Laing R, Mabadeje AF. The development of standard values for the WHO drug use prescribing indicators. Geneva: WHO; 2018. World Health Organization. How to investigate drug use in health facilities: selected drug use indicators. http://apps.who.int/medicinedocs/pdf/s2289e/s2289e.pdf. Accessed 10 Jan 2025. Tripathy JP, Bahuguna P, Prinja S. Drug prescription behavior: A cross-sectional study in public health facilities in two states of North India. Perspect Clin Res 2018 [cited 2021 May 31];9:76-82 Shivgunde P, Kodilkar A. Investigation of drug use at primary health centres in Nashik, Maharashtra, India. Int J Res Med Sci. 2019;8:290. doi:10.18203/2320-6012.ijrms20195925 Meena DK, Mathaiyan J, Thulasingam M, Ramasamy K. Assessment of medicine use based on WHO drug-use indicators in public health facilities of the South Indian Union Territory. Br J Clin Pharmacol. 2021;88(5):2315-2326. doi:10.1111/bcp.15165. 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. doi:10.4103/jehp.jehp_90_18. Samad MA, Sikdar KMYK, Munia AT, Patwary FT, Sarkar MR, Rashed MRI. Comparative analysis of prescription patterns and errors in government versus private hospitals in Dhaka: A cross-sectional study. Health Sci Rep. 2024;7(8):e2302. doi:10.1002/hsr2.2302. Galappatthy P, Ranasinghe P, Liyanage CK, Wijayabandara MS, Mythily S, Jjayakody RL. WHO/INRUD Core drug use indicators and commonly prescribed medicines: A National Survey from Sri Lanka. BMC Pharmacol Toxicol. 2021;22:67. doi:10.1186/s40360-021-00535-5. Raghute P, Jaiswal K, Dudhgoankar S, Turkar A, Jawade A, Vaishnao L. A Cross-sectional Study Assessing Prescriptions of a Tertiary Care Teaching Institute of Central India using the WHO Core Drug Indicators. J Med Sci Health. 2019;5(1):1-6. doi:10.46347/jmsh.2019.v05i01.001. Zairina E, Dhamanti I, Nurhaida I, Mutia DS, Natesan A. Analysing drug patterns in primary healthcare centers in Indonesia based on WHO's prescribing indicators. Clin Epidemiol Glob Health. 2024;30:101815. doi:10.1016/j.cegh.2024.101815. Siele SM, Abdu N, Ghebrehiwet M, Hamed MR, Tesfamariam EH. Drug prescribing and dispensing practices in regional and national referral hospitals of Eritrea: Evaluation with WHO/INRUD core drug use indicators. PLoS One. 2022;17(8):e0272936. doi:10.1371/journal.pone.0272936. Ag Ahmed MA, Ravinetto R, Diop K, Trasancos Buitrago V, Dujardin C. Evaluation of Rational Medicines Use Based on World Health Organization Core Indicators: A Cross-Sectional Study in Five Health Districts in Mauritania. Integr Pharm Res Pract. 2024;13:17-29. doi:10.2147/IPRP.S447664. Fickweiler F, Fickweiler W, Urbach E. Interactions between physicians and the pharmaceutical industry generally and sales representatives specifically and their association with physicians’ attitudes and prescribing habits: A systematic review. BMJ Open. 2017;7:e016408. doi:10.1136/bmjopen-2017-016408. Sulis G, Daniels B, Kwan A, Gandra S, Daftary A, Das J, et al. Antibiotic overuse in the primary health care setting: A secondary data analysis of standardised patient studies from India, China and Kenya. BMJ Glob Health. 2020;5(9):e003393. doi:10.1136/bmjgh-2020-003393. Abubakar U, Salman M. Antibiotic use among hospitalized patients in Africa: A systematic review of point prevalence studies. J Racial Ethn Health Disparities. 2024;11(3):1308–1329. Available from: https://doi.org/10.1007/s40615-023-01610-9 Mehta A, Brhlikova P, McGettigan P, Pollock AM, Roderick P, Farooqui HH. Systemic antibiotic sales and WHO recommendations, India. Bull World Health Organ. 2022;100(10):610–619. Available from: https://doi.org/10.2471/BLT.22.287908 Koya S, Ganesh S, Selvaraj S, Wirtz V, Galea S, Rockers P. Antibiotic consumption in India: Geographical variations and temporal changes between 2011 and 2019. JAC-Antimicrob Resist. 2022;4(5):dlac112. Available from: https://doi.org/10.1093/jacamr/dlac112 Govt asks doctors, pharmacists to mention reasons for prescribing antibiotics. The Economic Times [Internet]. [cited 2024 May 24]. Available from: https://economictimes.indiatimes.com/industry/healthcare/biotech/healthcare/govt-asks-doctors-pharmacists-to-mention-reasons-for-prescribing-antibiotics/articleshow/106986244.cms?from=mdr McKinsey & Company. India Pharma 2020: Propelling access and acceptance, realising true potential. 2020. Available from: https://www.mckinsey.com/~/media/mckinsey/dotcom/client_service/Pharma%20and%20Medical%2 0Products/PMP%20NEW/PDFs/778886_India_Pharma_2020_Propelling_Access_and_Acceptance_Realising_True_Potential.ashx Garg R, Garg S, Singh K, Ranga A, Singh A, Kumar K. Comparison of prices of commonly used drugs in AMRIT pharmacy, Jan Aushadhi Centre and private chemist shop: An analytical study from a tertiary care centre in Haryana. Indian J Community Health. 2022;34(2):196–201. Available from: https://doi.org/10.47203/IJCH.2022.v34i02.011 Prinja S. Cost-effectiveness of Pradhan Mantri Bhartiya Janaushadhi Pariyojna and its impact on financial risk protection in India. 2022. Available from: https://htain.dhr.gov.in/images/pdf/outcome_reports/89.PMBJP_(PGIMER).pdf Weldemariam DG, Amaha ND, Abdu N, et al. Assessment of completeness and legibility of handwritten prescriptions in six community chain pharmacies of Asmara, Eritrea: A cross-sectional study. BMC Health Serv Res. 2020;20:570. Available from: https://doi.org/10.1186/s12913-020-05418-9 Idris SA, Hussien TMA, Al-Shammari FF, Nagi HA, Bashir AI, Elhussein GEMO et al. An evaluation of drug prescribing patterns and prescription completeness. Healthcare (Basel). 2024;12(22):2221. Available from: https://doi.org/10.3390/healthcare12222221 Dereje B, Workneh A, Megersa A, Yibabie S. Prescribing pattern and associated factors in community pharmacies: A cross-sectional study using AWaRe classification and WHO antibiotic prescribing indicators in Dire Dawa, Ethiopia. Drugs Real World Outcomes. 2023;10(3):459–469. Available from: https://doi.org/10.1007/s40801-023-00367-1 Amaha ND, Weldemariam DG, Abdu N, Tesfamariam EH. Prescribing practices using WHO prescribing indicators and factors associated with antibiotic prescribing in six community pharmacies in Asmara, Eritrea: A cross-sectional study. Antimicrob Resist Infect Control. 2019;8:163. Available from: https://doi.org/10.1186/s13756-019-0620-5 Tables Tables 1 to 9 are available in the Supplementary Files section. Additional Declarations No competing interests reported. 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This widespread inappropriate usage contributes to irrational prescribing, which can lead to adverse drug reactions (ADRS). ADRs pose a serious threat to public health, contributing to increased rates of mortality and escalating medical costs [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eInappropriate prescribing practices limit access to essential medicines, often resulting in ineffective or harmful treatments, prolonged illnesses, and increased healthcare expenditures [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. It is estimated that effective medication use could alleviate up to 80% of the burden of non-communicable diseases (NCDs) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. However, overprescribing and polypharmacy represent serious public health concerns globally, and India is no exception. A study conducted in India reveals that 69.2% of medicine expenditure in the private sector and 55.2% in the public sector are wasteful [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Moreover, high out-of-pocket expenditures (OOPE) on healthcare push about 3% of Indians below the poverty line annually [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Notably, medicine is the dominant contributor to OOP health payments in India [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. More importantly, many in India either postpone or completely avoid seeking treatment owing to the high cost of medicines, which further worsens their health conditions [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eConversely, a large number of patients suffer harm and increased costs of treatment because of inappropriate and non-beneficial overuse of medicines. Porter and Grills (2016) estimated that 50% of household OOP health spending in India is on unnecessary medications or investigations [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Moreover, the consumption of useless medicines leads to adverse effects, including antibiotic resistance. Around 400,000 die every year due to ADRs in India [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Addressing these challenges necessitates improved access to affordable essential medicines and enhanced prescribing efficiency. The promotion of generic medicines, as opposed to more expensive branded alternatives, plays a fundamental role in improving accessibility and affordability.\u003c/p\u003e\n\u003ch3\u003eJan Aushadhi Scheme\u003c/h3\u003e\n\u003cp\u003eIn 2008, the United Progressive Alliance (UPA) government launched the \u0026lsquo;Jan Aushadhi Scheme\u0026rsquo; (JAS), an initiative aimed at providing unbranded, quality-assured generic medicines at affordable prices, particularly benefiting economically disadvantaged populations across the country. As part of this scheme, dedicated outlets known as \u0026lsquo;Jan Aushadhi Kendras\u0026rsquo; were established to ensure access to these affordable medicines. However, the programme experienced a slow start, and by 2015\u0026mdash;after six years of operation\u0026mdash;only 80 Jan Aushadhi Kendras had been set up in selected states [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite its objectives, the scheme faced numerous challenges that hindered its success. These included excessive reliance on state governments for implementation, inefficiencies in supply chain operations, reluctance among physicians to prescribe generic medicines, competition from state-sponsored schemes distributing free medicines, limited availability of drugs under JAS, and public misconceptions regarding the quality of generic medicines [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. To address these challenges, the JAS was restructured and rebranded in September 2015 as the Pradhan Mantri Bhartiya Jan Aushadhi Pariyojana (PMBJP) under the National Democratic Alliance (NDA) government, accompanied by the introduction of a new Strategic Action Plan (SAP). This revamped initiative aimed to expand the number of PMBJP pharmacies, particularly in rural areas, while enhancing public awareness of the scheme and encouraging government doctors to prescribe generic medicines, with active collaboration from state governments. Since its restructuring in 2015, the number of PMBJP stores has significantly increased, rising from 80 in 2015 to over 13,822 in 2024 [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn India, current regulations require registered physicians to prescribe medications using generic names, which should be clearly written and preferably in capital letters. Physicians are also expected to ensure that prescriptions are rational and that drugs are used appropriately. The National Medical Commission Act of 2019 gives the relevant State Medical Councils or the Ethics and Medical Registration Board (EMRB) of the National Medical Commission the authority to take disciplinary action against any doctor who violates these regulations.\u003c/p\u003e \u003cp\u003eHowever, concerns regarding the quality and effectiveness of generics persist within the medical fraternity. To tackle these issues, the Indian government has mandated that suppliers obtain WHO-GMP certification and has established requirements for bioequivalence studies to secure manufacturing licenses. Additionally, to ensure that generic medicines are affordable for everyone, the Department of Pharmaceuticals and the Pharmaceuticals \u0026amp; Medical Devices Bureau of India (PMBI) is actively promoting PMBJP initiative through advertisements in electronic media, print media, and outdoor publicity [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite these measures, real-world adoption remains low due to persisting physician scepticism about effectiveness of certain non-branded generic medicines [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Studies show that only a small (10\u0026ndash;16%) percentage of prescriptions are for generics, contradicting India's \u003cem\u003eNational Standard Treatment Guidelines (STG)\u003c/em\u003e, which emphasize the prescription of medicines in their generic form, and the WHO\u0026rsquo;s global standard of 100% generic prescription [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eImportance of rational prescribing practices\u003c/h2\u003e \u003cp\u003eRational prescribing is essential to prevent the widespread issue of irrational medicine use. Common examples include polypharmacy, which involves prescribing too many medicines per patient which are often more expensive and offer no advantage over single compound products. Other issues include the unnecessary use of injections when oral administration is appropriate, the overuse of antimicrobials, and poor adherence to standard treatment guidelines [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. These practices can result in delayed diagnoses, increased side effects, drug resistance, high treatment costs, wasted resources, diminished trust in medical systems, prolonged disease states, and even mortality in chronic conditions [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eVarious researches indicated a rising trend of inappropriate medication use in the current Indian healthcare system with wide variation in prevalence rate of polypharmacy across different states with 5.8% in West Bengal to 93.1% in Uttaranchal [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Also, it is worthwhile to note that rising trend of polypharmacy practices was seen specifically among older adults and paediatric patients [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBesides India, similar trends in irrational prescribing have been observed in other South Asian and African countries. For instance, in Nepal, the average number of medications per prescription is considerably high, antibiotics are overprescribed; and the generic prescribing rate is quite low [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Comparable patterns are evident in Sudan, Nigeria, and Ethiopia, where antibiotic use often surpasses WHO-recommended levels [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Antimicrobial resistance imposes an immense financial burden on healthcare systems across the globe [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTwo fundamental aspects of rational prescribing are cost-effectiveness and the safety and efficacy of treatment options. In India, promoting the use of unbranded generic medicines can significantly enhance consumer access to essential drugs while reducing healthcare expenses, without compromising therapeutic quality [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Given the pivotal role of prescribing behaviour in facilitating the adoption of generic medicines, evaluating physicians' prescribing patterns is critical.\u003c/p\u003e \u003cp\u003eAdditionally, irrational prescribing contributes substantially to high out-of-pocket expenditures (OOPE) for medicines, highlighting the necessity of assessing prescription rationality using the World Health Organization\u0026rsquo;s core prescribing indicators. However, there remains a lack of comprehensive evidence regarding the correlation between prescribing behaviours in public healthcare facilities and initiatives aimed at improving medicine accessibility, such as the Jan Aushadhi scheme. The present study aims to fill this knowledge gap by examining prescribing trends in public healthcare facilities located near PMBJP pharmacies in the Mumbai and Palghar districts of Maharashtra.\u003c/p\u003e \u003c/div\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cem\u003eStudy Design\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe have used quantitative research design involving an observational cross sectional survey of PMBJPY pharmacies located in the periphery of three levels of public health facilities to collect prescription based data.\u0026nbsp;Copies of prescriptions collected (from July 2019 to August, 2019) from all patients visited to the selected PMBJPY pharmacy located in the periphery of primary health centres (PHCs), rural hospitals (RHs) or sub district hospitals (SDHs) and medical colleges and tertiary hospitals in two districts of Maharashtra.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStudy setting\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe survey was conducted in two districts of Maharashtra, namely Mumbai metropolitan region and Palghar. In terms of per capita income, Maharashtra is one of the richer states in India and Mumbai is its capital city. With a population of more than 20 million, the city is one of the most populous urban centres in the world. It has the distinction of being home to the largest slum population in any city in the world, displaying a high level of income inequality. On the other hand, Palghar is an economically backward district with a population of nearly 3 million and is primarily inhabited by the tribal people.\u003c/p\u003e\n\u003cp\u003eIn India, healthcare is provided by both private for-profit and not-for-profit and public healthcare facilities. The public healthcare system has three levels: primary, secondary and tertiary. The primary level is the first level of health service contact for individuals, families and communities. It consists of primary health centres (PHC), sub-centres (SC) and health posts (HP). The secondary level comprises rural hospitals and municipal general hospitals that people go to after referral from primary healthcare centres. Finally, the tertiary level comprises medical college and hospitals. These facilities have specialists and facilities for advanced medical investigation and treatment.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSampling of Public health facilities and PMBJP pharmacy\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe WHO\u0026rsquo;s guidelines on drug use recommend at least 20 facilities and at least 30 encounters per facility, which entails a total of 600 prescriptions to describe drug use patterns [26]. However, considering the availability of PMBJP pharmacies and public health facilities in these districts, a total of 11 public health facilities were purposively selected based on their proximity to PMBJP pharmacies. Public health facilities include medical college (Tertiary level), Municipal General Hospital (Secondary Level) and PHCs and HPs (Primary level). PMBJP pharmacy\u0026rsquo;s proximity to the public health facilities was assessed using google maps. The details of the sampled PMBJP pharmacies are provided in Table. 1.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eData Collection\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA structured tool was used to gather information on the\u0026nbsp;prescribing patterns comprises three sections: the average number of medicines per prescription, the number of medicines prescribed by generic and brand names, and the number of medicines prescribed per the Maharashtra State Essential Drug List (2019).\u003c/p\u003e\n\u003cp\u003eThe information retrieved from the prescriptions included bio demographic data; working diagnosis; list of prescribed drugs; the dose, frequency and route of administration; and duration of therapy. Any prescription containing one or more medications was considered for collection irrespective of the patients\u0026rsquo; disease state (acute or chronic). As all three levels of healthcare facilities were considered, prescriptions of both inpatient and outpatient departments were included in the study.\u003c/p\u003e\n\u003cp\u003eSurvey was conducted at 11 PMBJPY pharmacies located in the periphery of the eleven selected Public health care facilities at the primary, secondary and tertiary levels. Public health facilities include Medical College \u0026amp; Hospital (Tertiary level), Municipal General Hospital (Secondary Level) and Health Post (Primary level). Around 30 Prescription slips written by doctors from the public healthcare system were collected from all patients who visited the PMBJPY pharmacies. A total of 330 prescriptions were\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003econsidered for prescription analysis, excluding those having illegible handwritings and incomplete data. \u003c/p\u003e\n\u003cp\u003eIn order to collect data in an accurate and reliable manner, one of the researchers personally visited the selected PMBJPY pharmacy located in the periphery of public health facilities to collect prescription copies. The researcher cum field investigator is trained in both pharmacy and public health with previous experience of conducting primary data collection for health systems research.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe WHO, in collaboration with INRUD (The International Network for Rational Use of Drugs), has developed a set of core indicators for measuring the rational use of medicines in healthcare settings. These indicators will enable comparison between health facilities. The core indicators are: prescribing, patient care and healthcare facility-specific indicators. The prescribing indicators help improve prescribing habits and reduce the cost burden on the patient and healthcare systems. The core prescribing indicators are as follows [27,28],\u003c/p\u003e\n\u003col start=\"1\" type=\"1\"\u003e\n \u003cli\u003eThe mean number of drugs per prescription.\u003c/li\u003e\n \u003cli\u003eThe percentage of drugs prescribed with generic names.\u003c/li\u003e\n \u003cli\u003eThe percentage of encounters with antibiotics prescribed.\u003c/li\u003e\n \u003cli\u003eThe percentage of encounters with prescribed injections.\u003c/li\u003e\n \u003cli\u003eThe number of drugs prescribed from the Essential Medicines List (EML).\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u003cem\u003eData analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eSPSS version 21.0 and MS Excel were used to analyse the quantitative data to assess\u0026nbsp;the WHO prescribing indicators using the WHO guidelines on investigation of drug use in healthcare facilities.\u003c/p\u003e\n\u003cp\u003eThe WHO core prescribing indicators\u003csup\u003e\u0026nbsp;\u003c/sup\u003ewere calculated as follows:\u003c/p\u003e\n\u003col start=\"1\" type=\"1\"\u003e\n \u003cli\u003eThe mean number of drugs per prescription or encounter was calculated by dividing the total number of different drug products by the number of prescriptions evaluated.\u003c/li\u003e\n \u003cli\u003eThe percentage of drugs prescribed using the generic name was determined by dividing the number of drugs prescribed with generic names by the total number of drugs in the prescriptions, multiplied by 100.\u003c/li\u003e\n \u003cli\u003eThe percentage of encounters with antibiotics prescribed was calculated by dividing the number of patient encounters during which an antibiotic was prescribed by the total number of patients encountered, multiplied by 100.\u003c/li\u003e\n \u003cli\u003eThe percentage of encounters with an injection was determined by dividing the number of encounters during which an injection was prescribed by the total number of patients encountered, multiplied by 100.\u003c/li\u003e\n \u003cli\u003eThe percentage of drugs in prescription from the EML was calculated by dividing the number of drugs in the prescription from the EML by the total number of drugs in the prescriptions, multiplied by 100.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cem\u003eProfile of the prescribers in the study\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTable 1 presents the profile of the prescribers and the number of prescriptions written by them. In the present study, almost 91% of the prescriptions were written by consultants (medical practitioners with postgraduate education in specialized medical streams such as dermatology, surgery, gynaecology, and internal medicine), and the remaining 9% of the prescriptions were written by general medical practitioners (graduated with an MBBS degree only).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDemographic characteristics of the outpatient and inpatients attendees\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAs mentioned earlier, the drug prescriptions of 330 patients were studied. Of these, approximately 62% were aged between 15 and 49 years, 17% were between 50 and 59 years, 11% were between 5 and 14 years and 2% were children under 5 years. Furthermore, the sample distribution of outpatients is skewed in favour of females (56%). However, in the case of IPD patients, there were more male attendees (68%) (Table 3)\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDrug prescribing practices in outpatient departments\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe observations on core prescribing indicators suggested by the WHO are presented in Table 4. Approximately 92% of the prescriptions contained 1-4 drugs, followed by 8% with 5-9 drugs. The average number of drugs prescribed per prescription was 2.78\u0026plusmn;1.27. The mode value was 2, implying that the most common number of medicines prescribed was 2. Notably, in approximately 99% of the sample prescriptions that we analysed, injections were not prescribed. Nearly 1% had 1 injection prescribed. About 32% of prescriptions contained one antibiotic, while 3% had two antibiotics. A total of 86% of the OPD drugs were prescribed from the Maharashtra state EML. The evaluation of prescriptions suggests that a total of 218 (71%) prescriptions had drugs from the EML only, whereas 82 (26.62%) of them had some drugs from the EML and another 08 (2.59%) of them had all drugs that do not feature in the EML.\u003c/p\u003e\n\u003cp\u003eAnother important finding that needs to be highlighted is that of all drugs prescribed by the physicians, approximately two-fifths (37%) were found to be branded generics, while the rest (63%) were unbranded generics. Additionally, nearly 78% of the OPD drugs were found to be prescribed from the PMBJP list. However, in regard to the prescriptions of outpatients, almost half of them (49.6%) had drugs from the PMBJP list only, whereas 44.4% of them had some drugs from the PMBJP list, and the remaining 5.8% had no drugs from the PMBJP list.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDrug prescribing practices in inpatient departments\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOn average, the total number of medicines prescribed per prescription was found to be 4.\u003cu\u003e04\u003c/u\u003e. More than half of the IPD prescriptions had one to four drugs per prescription. Moreover, more than one-fourth of prescriptions contained five or more drugs, which is more than double the number of drugs (3 per patient) ideally prescribed to a patient. Almost 82% of the prescriptions had injections, of which nearly 55% had 1-2 injections and nearly 27% of the prescriptions had 4-5 injections. Similarly, approximately 64% of prescriptions contained antibiotics, out of which 45% of prescriptions had one antibiotic and 9% prescriptions had 2-3 antibiotics.\u003c/p\u003e\n\u003cp\u003eOf the total drugs prescribed, 68.2% were generic-generic, while 32% were branded generics. Importantly, the evaluation of prescriptions suggests that only half of the prescriptions had all the drugs prescribed from the EDL list, and the remaining half had some drugs from the EML Overall, 83% of the IPD drugs are listed in the Maharashtra State EML. As far as drugs from the PMBJP list are concerned, 80.9% were prescribed from its drug basket (table 5).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eOther core prescribing indicators at outpatient departments\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOf those who sought medical care for conditions not requiring hospitalizations, over 71% were prescribed medicines for three days, and 26% were prescribed medicines for more than four days. The analysis suggests that more than half (53.2%) of the prescription slips had no diagnosis on them, and nearly 60% of the prescriptions were devoid of patients\u0026rsquo; signs and symptoms (Table 6).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eOther core prescribing indicators at inpatient departments\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMore than three-fifths of the inpatients (63.6%) were prescribed drugs for up to 5 days and about one-fourth were prescribed medicines for 6-10 days. In nearly 5% of prescription slips, the diagnosis of the hospitalized patients was not mentioned, and almost\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eone-fourth (23%) of prescriptions did not contain any signs or symptoms (Table 7).\u003c/p\u003e\n\u003cp\u003eTable 8 provides findings on various WHO\u0026rsquo;s core prescribing indicators and WHO\u0026rsquo;s optimal value regarding each prescribing indicator.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe relationship between antibiotic prescriptions, injections, FDCs, and the total number of drugs prescribed per prescription\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIt is evident from Table 9 that the probability of prescriptions with antibiotics, injections, FDCs and vitamins increases considerably with the quantity of drugs per prescription. Additionally, the examination of prescribing patterns reveals the practice of polypharmacy, with a significant number of prescriptions containing even more than 3 medicines.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAccording to the WHO manual on investigating drug use patterns, prescription pattern analysis provides valuable insights into the drug utilization scenario at national, state, or individual health facility level [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The present study systematically examines the prescribing practices of physicians across different levels of public health facilities located near unbranded generic medicine pharmacies in Mumbai and Palghar districts of Maharashtra. In this study, particular attention has been given to the quality of prescriptions, including legibility, the type and quantity of drugs prescribed, adherence to generic naming conventions, and whether the prescribed medicines are included in the state Essential Medicines List (EML) or the PMBJP drug list.\u003c/p\u003e \u003cp\u003eOur analysis indicates that, on average, 2.8 medications were prescribed per outpatient prescription, while hospitalized patients received an average of 4 medications per prescription. This prescribing rate surpasses the WHO recommended ideal range of 1.6\u0026ndash;1.8 medications per prescription [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. However, it remains lower than findings from other studies conducted in different regions of India, where the average ranged from 3.0 to 4.1 medications per prescription [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Similarly, prescription rates in neighbouring South Asian countries, Sri Lanka (3.1), Nepal (3.2), and Bangladesh (5.1) also exhibited higher averages [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Our findings are consistent with a previously reported study in Central India, which documented an average of 2.89 prescriptions per patient [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. However, this rate remains notably higher than reported averages from countries and regions such as Indonesia (2.2), Eritrea (1.62), and Sub-Saharan Africa (2.2) [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur study findings suggest a practice of polypharmacy, with 8% of outpatients and 36% of inpatients receiving 5 or more medications. It implies that many of these prescriptions, particularly for inpatients, are probably irrational. It is worth noting that a recent study across six different urban locations in India estimated the prevalence of polypharmacy to be 33.7% amongst older adults [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Notably, inappropriate polypharmacy is a serious issue in India, and its prevalence is rising, which may be partly ascribed to lack of effective mechanisms in healthcare facilities for ensuring the rational use of drugs, to the inducements given by the pharmaceutical companies to the doctors to overprescribe and physicians\u0026rsquo; lack of knowledge concerning rational drug prescribing [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe analysis of prescribed medications revealed a significant predominance of antibiotic use. Specifically, one-third of outpatient prescriptions and two-thirds of inpatient prescriptions contained at least one antibiotic, which is considerably higher than the standard endorsed by the WHO (20.0%-26.8%) [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Like in this study, Sulis et al (2020), using simulated patients, found a very high prevalence of inappropriate antibiotic use in primary healthcare settings in India (49.9%), Kenya (50%) and China (28.8%) [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. The issue of inappropriate use of antimicrobials has also been reported in other Asian countries, with rates of 37.9% and 44% found in studies from Nepal and Bangladesh, respectively [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. A study in Africa reported a high prevalence of antibiotic use among hospitalized patients in this region. It concluded that prevalence was relatively higher in West Africa (51.4\u0026ndash;83.5%) and North Africa (79.1%) than in East Africa (27.6\u0026ndash;73.7%) and South Africa (33.6\u0026ndash;49.7%) [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Our study findings of 66.6% of inpatient antibiotic prescription align with trends observed in West and East Africa.\u003c/p\u003e \u003cp\u003eWhat is very concerning is that India has the highest antibiotic consumption and antimicrobial resistance globally [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. The significant burden of infectious diseases in India partly explain such a high level of antibiotic use. Studies indicate that inappropriate prescriptions of antibiotics for viral infections and the unnecessary use of broad-spectrum antibiotics when they are not required are significant drivers of antibiotic resistance in the country [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. The unnecessary prescribing of broad-spectrum antibiotics arises from various factors, including perceived resistance to narrower-spectrum antibiotics, expectations from both patients and doctors, and a lack of diagnostic tools to identify specific bacterial infections. In response to these issues, the Ministry of Health and Family Welfare has urged doctors to explicitly state the clinical indications, reasons, and justifications when prescribing antimicrobials. This is expected to promote the responsible use of these drugs and reduce the emergence of antimicrobial resistance (AMR) [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAside from large-scale use of antibiotics, the analysis shows that 34.1% of OPD prescriptions and 81.8% of IPD prescriptions included injections, significantly exceeding the WHO reference value of less than 20% [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The use of injectable in OPD prescriptions is much lower than in IPD prescriptions. In fact, a large proportion of OPD injectable medications were administered to diabetic patients, primarily for insulin therapy. Nevertheless, our study findings related to the percentage of prescriptions with injectable are much higher than those reported in other Asian countries such as Nepal (0.7%), and Bangladesh (17.01%) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAs mentioned earlier, we explored the extent to which physicians at public health facilities are prescribing medications using generic names. Our analysis reveals that about 40% of prescriptions included medications prescribed by their brand names. This prescribing pattern could plausibly be explained by several factors, including the influence of prescribing mentors, financial incentives, the role of pharmaceutical detailers, the differing levels of training and experience among prescribers, and the availability and adherence to standard treatment guidelines. Besides these reasons, the physicians in India also prefer to prescribe branded generics because of the perceived poor quality of unbranded generics [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGenerics dominate the Indian pharmaceutical market, accounting for nearly 97% of the medicines consumed by value. However, most of these are branded generics, with unbranded generics making up only 10% of the share [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Despite their identical chemical composition, branded generics command a significant price premium ranging from 1\u0026ndash;200% making them unaffordable for many [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Hence, switching from branded-generic medicine to unbranded generic medicines would lead to substantial cost savings for medicine consumers. We had earlier argued that unbranded generic substitution would reduce pharmaceutical expenditure by 6\u0026ndash;1129% of patient\u0026rsquo;s spending [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn addition to estimating the percentage of generic prescriptions, our study also assesses the proportion of drugs prescribed from the PMBJP list. The findings reveal that almost 78% of the total OPD-prescribed drugs and nearly 81% of the total IPD-prescription drugs align with the PMBJP medicines list and can be dispensed accordingly. When it comes to PMBJP medicines (unbranded generics), it is evident from multiple studies that medicines covered under PMBJPY scheme are significantly cheaper than frequently prescribed branded generics for common ailments and hence unbranded generic substitution through PMBJP initiative could create significant OOP savings for individual patients and for the healthcare system [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFurther, our study estimates that more than three-fourths (85.6%) of OPD drugs and 83.1% of IPD drugs were prescribed from EML. Although the EML prescribing adherence of 86% of OPD and 83% of IPD drugs is in consonance with the results of other study conducted in North India (84%) [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], but still below the WHO recommended optimal value of 100% [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Studies conducted in various parts of India have shown differing rates of essential medicines prescribing. In Maharashtra, the prescribing rate was found to be 68.9%, while in Central India, it was slightly higher at 75.3%. In contrast, a study from South India reported a significantly higher rate of 93.3% [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur study found that 84% of prescriptions included essential medicines slightly lower than the WHO\u0026rsquo;s optimal value but still relatively close. This moderate-to-high adherence to the Essential Medicines Drug List (EMDL) may be attributed to the robustness of the State EMDL, which effectively meets patient needs. The increasing adoption of EMDL across the country, along with the continuous expansion of various Essential Medicines Lists (EMLs), including the National EML, likely contributes to this trend.\u003c/p\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eCompleteness and legibility of prescriptions\u003c/h2\u003e \u003cp\u003eWe examined the completeness of prescriptions in terms of critical information such as diagnosis, frequency of dosage, strength, and dosage forms, and follow-up visits. The analysis indicates that half of the sample prescriptions were incomplete in different respects. One of the studies from Central India reported that only 19% of prescriptions mentioned proper dose, duration, and frequency (DDF) of prescribed drugs [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Moreover, about half (47%) of the prescriptions were also found to be not legible. Prescription audit studies show that legibility improves with more complete prescriptions but decreases when more brand names are used and as the number of prescribed drugs increases [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Unlike in our study, the percentage of illegible prescriptions was found to be less than 20% in Saudi Arabia (19.8%) and Eritrea (14.1%) [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e This study highlights significant shortcomings in enforcing prescription guidelines, as evidenced by the high number of incomplete and illegible prescriptions. To improve compliance, monitoring capacity should be enhanced within the public health system. Additionally, efforts must be made to significantly improve the doctor-patient ratio, which can help reduce physicians' workload, foster better doctor-patient interactions, and ultimately lead to improved patient outcomes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eRelationship between prescribing of antibiotics, injections, FDCs etc. and quantity of drugs prescribed per prescription\u003c/h2\u003e \u003cp\u003eAside from legibility, incompleteness and branded drug use issues, prescribing indicators reveal polypharmacy as a prevalent prescription practice, which is a matter of great concern. According to this study, the proportion of prescriptions with antibiotics, injections, fixed dose combinations and vitamins is positively related to the number of drugs per prescription. Likewise, a study conducted in Ethiopia also found that the number of medications prescribed was significantly associated with the prescription of antibiotics [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Another study reveals that patients prescribed three to four medicines are two times more likely to be prescribed an antibiotic compared to those prescribed one to two medicines per encounter [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Responsible use of antibiotics and FDCs are essentially important to reduce prescription cost, enhance treatment adherence, improved health outcomes and confine AMR nationally and internationally.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eOur analysis draws attention to unsatisfactory prescribing practices in public health facilities. This highlights that some interventions, such as dissemination of the guidelines for writing legible prescriptions to all public health facilities, writing complete prescriptions with patient signs and symptoms, complete medical history, rational selection of medicines, diagnosis and follow-up assistance, are needed. In addition, institutions such as the NMC should review the current regulations to address the aforementioned concerns and especially the public health issue of inappropriate polypharmacy and formulate approaches that can lead to appropriate medicine usage in all levels of health care settings.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eMaharashtra State EML: Maharashtra State Essential Medicine List\u003c/p\u003e\n\u003cp\u003ePMBJP list: Pradhan Mantri Bhartiya Jan Aushadhi Pariyojan list\u003c/p\u003e\n\u003cp\u003eUPA: United Progressive Alliance\u003c/p\u003e\n\u003cp\u003eNDA: National Democratic Alliance\u003c/p\u003e\n\u003cp\u003ePMBI: Pharmaceuticals \u0026amp; Medical Devices Bureau of India\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSAP: Strategic Action Plan\u003c/p\u003e\n\u003cp\u003eFDC: Fixed-dose combination\u003c/p\u003e\n\u003cp\u003eWHO: World Health Organization\u003c/p\u003e\n\u003cp\u003eOPD: Out Patient Department\u003c/p\u003e\n\u003cp\u003eIPD: Patient Department\u003c/p\u003e\n\u003cp\u003ePHCs: Primary Health Centres\u003c/p\u003e\n\u003cp\u003eRH: Rural Hospital\u003c/p\u003e\n\u003cp\u003eSDH: Subdistrict Hospital\u003c/p\u003e\n\u003cp\u003eAMR: Antimicrobial resistance\u003c/p\u003e\n\u003cp\u003eSTGs: Standard Treatment Guidelines\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAll participants gave their verbal informed consent before the interviews. The study protocol\u0026nbsp;\u003c/strong\u003ewas approved by the School of Health Systems Studies, Tata Institute of Social Sciences, Mumbai. Additionally, the permission to conduct the study was obtained from\u0026nbsp;Pharmaceuticals \u0026amp; Medical Devices Bureau of India (PMBI), Department of Pharmaceuticals, Government of India, The Department of Public Health, Mumbai and the District Collectorate of Palghar district\u0026nbsp;\u003cstrong\u003eAll methods were performed in accordance with the relevant guidelines and regulations.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data used and or analysed during the current study are not publicly available. The datasets can be obtained from the corresponding author on reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe have not received any funding for this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSG was involved in the conception and design of the study as well as drafting, analysis, interpretation and editing. SL was involved in the study conception, data acquisition, analysis, interpretation and drafting the manuscript. Both authors read and approved the final version of the manuscript to be considered for publication.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWorld Health Organization. The pursuit of responsible use of medicines: Sharing and learning from country experiences [Internet]. Geneva, Switzerland; 2012 [cited 2021 May 31]. Available from: https://apps.who.int/iris/bitstream/handle/10665/75828/WHO_EMP_MAR_2012.3_eng.pdf?sequence=1\u003c/li\u003e\n\u003cli\u003eAccess to Medicines Foundation. Access to Medicines Index, 2022 [Internet]. 2022 [cited 2025 Apr 6]. Available from: https://accesstomedicinefoundation.org/resource/2022-access-to-medicineindex\u003c/li\u003e\n\u003cli\u003eTefera BB, Getachew M, Kebede B. 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Prescribing pattern and associated factors in community pharmacies: A cross-sectional study using AWaRe classification and WHO antibiotic prescribing indicators in Dire Dawa, Ethiopia. Drugs Real World Outcomes. 2023;10(3):459\u0026ndash;469. Available from: https://doi.org/10.1007/s40801-023-00367-1\u003c/li\u003e\n\u003cli\u003eAmaha ND, Weldemariam DG, Abdu N, Tesfamariam EH. Prescribing practices using WHO prescribing indicators and factors associated with antibiotic prescribing in six community pharmacies in Asmara, Eritrea: A cross-sectional study. Antimicrob Resist Infect Control. 2019;8:163. Available from: https://doi.org/10.1186/s13756-019-0620-5\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 9 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Jan Aushadhi scheme, essential medicines, prescription pattern, prescribing indicators, polypharmacy, generics, rational drug practices","lastPublishedDoi":"10.21203/rs.3.rs-6830661/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6830661/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground:\u003c/h2\u003e \u003cp\u003eIrrational prescribing practices, inappropriate use of medicines, and the high cost of essential medications are significant health policy concerns in India. To address the issue of accessibility, a generic medicine scheme called \u003cem\u003eJan Aushadhi (JA translates to People\u0026rsquo;s Medicine)\u003c/em\u003e was revamped and expanded in 2015. Additionally, physicians were advised to comply with the erstwhile Medical Council of India\u0026rsquo;s regulation of prescribing medicines by their salt names. This is the first study which not only assessed the quality of prescriptions in public health facilities, but also examined whether the doctors' prescribing behaviours in public facilities are in sync with the government\u0026rsquo;s intent to improve access to medicines through promotion of generics.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA survey was conducted at JA pharmacies near 11 public healthcare facilities in Mumbai and Palghar. Prescription slips written by doctors from the public healthcare system were collected from all patients who visited the JA pharmacies. After excluding prescriptions with illegible handwritings and incomplete data, a total of 330 prescriptions were included in the analysis.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e \u003cp\u003eThe mean number of drugs per prescription was 2.7 and 4 for outpatients and inpatients, respectively. More than 53% of the outpatient prescription slips had no diagnosis on them, nearly 60% were devoid of patients\u0026rsquo; signs and symptoms, and listed branded medicines instead of generics. Among outpatient prescriptions, 1% contained injectable, while 32% included antibiotics. However, for those hospitalised, 82% of their prescriptions included injectable, and 64% contained antibiotics. Nearly 78% of the medicines prescribed came from the JA list. A total of 85% of drugs were prescribed from the Maharashtra State essential medicine list (EML) with 86% of OPD drugs and 83% of IPD drugs falling under this category.\u003c/p\u003e\u003ch2\u003eConclusion:\u003c/h2\u003e \u003cp\u003eThe analysis reveals highly unsatisfactory prescribing practices in public health facilities. This underscores the urgent need to review the current laws regulating the practice of medicines, particularly those concerning the requirements for writing legible prescriptions, documenting patients' signs and symptoms, recording complete medical histories, selecting appropriate medications, making accurate diagnoses, and providing proper follow-up care. Equally important is to arm the public health authorities to ensure the implementation of these prescription regulations.\u003c/p\u003e","manuscriptTitle":"Prescribing trends-branded versus unbranded generics and rational use of medicine at public health facilities in Maharashtra, India","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-24 11:14:02","doi":"10.21203/rs.3.rs-6830661/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-11T03:01:34+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-27T07:05:10+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-17T08:12:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"101101637344424540570268902512101537345","date":"2025-11-07T14:22:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"188036755992074798299763683853969561686","date":"2025-11-07T07:35:40+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-12T10:14:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"277587645838378359076992294806963037442","date":"2025-10-05T09:14:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"337943262229268796949750186963346657185","date":"2025-10-03T09:50:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"45337018765842468338764046242448767706","date":"2025-08-19T05:27:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"136443199664113346544346350327521547125","date":"2025-08-14T05:44:48+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-20T06:56:25+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-20T05:57:01+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-06-19T16:53:34+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-18T13:01:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Health Services Research","date":"2025-06-18T11:39:56+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a1ae2d06-d004-4d9e-b42d-3270c9a8252f","owner":[],"postedDate":"June 24th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-10T18:08:41+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-24 11:14:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6830661","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6830661","identity":"rs-6830661","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}