Prescription Cost Analysis and Economic Impact of Drug Treatment in Patients with Chronic Illness, Attending the Medicine Out-patient Department in a Tertiary Care Hospital at South Delhi

Prescription Cost Analysis and Economic Impact of Drug Treatment in Patients with Chronic Illness, Attending the Medicine Out-patient Department in a Tertiary Care Hospital at South Delhi | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Prescription Cost Analysis and Economic Impact of Drug Treatment in Patients with Chronic Illness, Attending the Medicine Out-patient Department in a Tertiary Care Hospital at South Delhi Nusrat Nabi, Ayushi Manghani, Azhar Uddin, Neha Dhillon, Dharmander Singh, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6086835/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Jun, 2025 Read the published version in Cost Effectiveness and Resource Allocation → Version 1 posted 8 You are reading this latest preprint version Abstract Objectives The prevalence of chronic diseases is rising globally along with the consumption of nutraceuticals. It is documented that 80% of the deaths due to chronic illnesses occur in low and middle-income countries, including India. In addition, chronic diseases not only affect the patients but also their family income. Besides Southeast Asia is also the fastest-growing market for nutraceuticals with less stringent cost regulation. Hence, this research primarily focuses on the financial impact of the drug treatment for chronic illness, extensively comparing the therapeutic and non-therapeutic drug (nutraceutical) costs. Methods This was a retrospective, cross-sectional study with a sample size of 7877 prescriptions of medicine outpatient clinic, extracted from the hospital information system after 5 level screening for their inclusion in the study. The cost of drugs prescribed to the patient for chronic illness was calculated per month and its impact on the monthly family income was evaluated. The data analysis was stratified into the cost of therapeutic drug treatment and non-therapeutic drug treatment which was correlated with various chronic diseases and demographic parameters. Results A total of 465 patients were enrolled after screening and a high prescription rate of 88% for non-therapeutic treatment was reported. The total average monthly cost of chronic illness treatment was INR 1879 (22.42 USD), with therapeutic drug treatment of INR 1319 (15.74 USD) and non-therapeutic drug treatment of INR 560 (6.68 USD). Comprising 36% of patients, males spent higher amount on therapeutic drug treatment (INR 1780 or USD 21.26), while women spent higher on non-therapeutic drug treatment (INR 593 or USD 7.08). A catastrophic 11% of patients from ‘lower’ socioeconomic spent ≥ 10% of family income on non-therapeutic treatment. Conclusion Our study highlights the financial strain that chronic illnesses impose on families, emphasizing the need for policymakers to improve access to specialized care and cost capping of nutraceuticals. Chronic illness cost analysis economic impact nutraceuticals non-therapeutic drug treatment prescription therapeutic drug treatment. Figures Figure 1 INTRODUCTION Chronic illnesses have become a significant healthcare issue globally ( 1 ). According to the World Health Organization (WHO), 80% of the deaths due to chronic illnesses occur in low and middle-income countries (LMICs), including India( 2 ). Significant morbidity and mortality due to chronic illnesses may lead to economic impoverishment, resulting in a fall of consumption levels below minimum needs( 3 ). From the national standpoint, chronic illnesses reduce work capacity and life span, thus affecting economic productivity.( 4 , 5 ) A wide variety of dietary supplements known as nutraceuticals are claimed to offer prevention and cure for numerous diseases. Although these claims often lack scientific support, they are used indiscriminately by patients with chronic illnesses( 6 ). Southeast Asia is the most rapidly growing market for the nutraceuticals with an estimated compound annual growth rate (CAGR) of 12% ( 7 ). Despite the bigger market size of nutraceuticals compared to pharmaceuticals, their regulations remain less stringent, which emphasizes an urgent need to explore their pattern of consumption and cost per prescription( 8 ). In India, the regulation of drug prices, including non-therapeutic drugs, comes under the Drugs Prices Control Order (DPCO), which is enforced by the National Pharmaceutical Pricing Authority (NPPA). However, India’s policy for non-therapeutic drug cost regulation under the DPCO allows manufacturers significant pricing freedom, which is capped at a 10% annual increase, with the NPPA stepping in only in exceptional cases.( 9 ) Several methods have been employed to understand the economic burden of chronic illnesses( 10 ). The expenses spent on these illnesses are distributed in three categories: direct, indirect, and intangible costs( 11 ). Direct costs represent the amount of household income allocated for medical care, including prevention, diagnosis, rehabilitation and treatment of the illness( 12 ). The indirect costs include diminution of labor productivity that is caused by morbidity and mortality arising from these diseases( 13 – 15 ). The intangible costs encompass the psychological effects attributed to disease, usually in the form of pain, distress, and bereavement. The cost of illness (COI) approach, focusing on the direct cost of drug treatment per prescription for chronic illness was considered for this study( 10 , 11 ). The household was selected as the unit of analysis as the financial burden of an illness is distributed among both the sick and other members of the household, and predominantly affects the overall budget of the household.( 12 ) There are notable gaps in India in the literature regarding the economic repercussions of chronic diseases among Indian population. To our knowledge no studies on evaluation and comparison of financial impact of non-therapeutic drugs with therapeutic drugs for a wide range of chronic diseases in the Indian population are available. Hence, this study was planned to primarily determine the average cost per prescription for treatment of chronic illnesses and further evaluate the economic burden imposed by non-therapeutic drug treatment (nutraceuticals). The secondary objective included exploring the association between the cost of drug treatment of chronic illnesses and the various demographic and disease parameters. MATERIALS AND METHODS Study Design & Setting: This was a retrospective, cross sectional, data mining study. A total of 7877 prescriptions of patients suffering from chronic illness, who attended the outpatient clinics of the Department of Medicine at Hamdard Institute of Medical Sciences & Research, New Delhi, during the months of July and August 2022, were processed for inclusion in the study after obtaining due approval from the institutional ethics committee (IEC). Sample selection: Prescriptions of patients with the following criteria were included: (i) patients aged 18 years and above, (ii) of any gender, (iii) with definitive diagnosis of at least one chronic illness, and (iv) having been on same treatment for their chronic disease for at least three months (so that the subjects would have experienced significant costs associated with managing their chronic illness). The exclusion criteria were as follows: (i) Duplicate follow-up prescriptions, (ii) prescriptions for simultaneous treatment of acute illness, (iii) patients enrolled in the government health scheme receiving free medications (iv) patients not able to be contacted and (v) patients not ready to give consent. Extensive screening of all medicine out-patient prescription files, was conducted by trained medical professionals at 5 levels; 1) Prescriptions of all patients with chronic illnesses were filtered in the first level; 2) Next, only patients continuing the same treatment for chronic illness, for a minimum of 3 months, were taken; 3) Further, patients enrolled in the government economically weaker section (EWS) health scheme were dropped out; 4) Prescriptions found with any treatment for simultaneous acute illness were excluded; and 5) Finally, the patients were contacted over the telephone for a structured interview and a total of 465 patients were included in the study after obtaining informed consent. Data Collection: To achieve uniform “prescription cost analysis” a skill exercise was organized for the team members for working on hospital information system (HIS) and conducting telephonic interviews. Prescriptions were pulled from the HIS in the form of excel sheets. The data was extracted in a structured case record form, designed after literature review of comparable studies, and approved by a senior internist and statistician for validity(16). The data was collected in 2 phases; 1) All information on patient demographic characteristics and prescribed drugs related information was collected from the prescription retrieved from the HIS. 2) Patient informed consent, personal history (smoking, alcohol intake), compliance with treatment and socio-economic data was obtained over the telephone. Data Analysis: Being a retrospective study, only the cost of drugs prescribed for the chronic illness in the Medicine outpatient clinics was calculated per month for a patient. For every patient, the average monthly cost of drug treatment was calculated by taking into account the number of drugs prescribed (brand or generic), and the respective number of drug units (tablets, capsules) consumed in a month as per the prescription dosing schedule. The maximum retail prices (MRP) of the drugs as obtained from our hospital pharmacy was used for cost analysis. Throughout the analysis, the data was stratified into 2 specific categories: 1) Cost of Therapeutic Drug Treatment and 2) Cost of Non-therapeutic Drug Treatment (nutraceuticals), for a comprehensive comparison and correlation. Analysis of socio-economic status was done based on the latest modified Kuppuswamy scale(17) and the ‘average family income per month’ was used for analysis. To calculate average family income per month, total family income for a month as disclosed by the family was added and then divided by the number of family members. To calculate family income per month, total monthly income details were asked from the patient and the accompanying relative, as India still has a trend of extended families, so where the patient and accompanying person were not aware of the income, it was asked via a telephonic conversation with other family members. Where monthly income was not fixed for a member in the family, then average monthly income was calculated using total income in the last financial year for that person and then divided by twelve to get the average monthly income for that individual. To further assess the financial implications of the chronic illness the data was categorized into 2 groups namely, patients spending 10% of their monthly family income on drug treatment. The cost of treatment was presented in Indian Rupees (INR) as well as US Dollars (USD) for comparison with international studies. “Chronic Illness” for this prescription cost analysis study was defined as per WHO, wherein, chronic diseases or non-communicable diseases (NCDs), are of long duration and the result of a combination of genetic, physiological, environmental and behavioral factors(18). Statistical Analysis: All data was analyzed using Statistical Package for the Social Sciences [SPSS] (IBM Corp., Armonk, NY) version 16 software. The categorical variables of demographic characteristics were presented as frequency and percentage. In descriptive statistics, mean and standard deviations were calculated for continuous variables. The two sample, independent t-tests for continuous variables was used for significant difference between the cost of therapeutic and non-therapeutic drug treatment. The chi-square test was performed for categorical variables to verify association between the two groups of; <10% and ≥10% of family income spent on therapeutic and non-therapeutic drug treatment. The odds ratio was also calculated by performing the logistic regression in Table 3. The level of statistical significance was set at < 0.05. RESULTS A total of 7877 outpatient prescriptions from the medicine department were screened and 465 patients were enrolled in the study based on the eligibility criteria. Among these, 410 patients were prescribed non-therapeutic drug treatment for chronic illness amounting to 88% prescription rate. From the demographic data we observed that the elderly comprising only 23% of patients had the highest average monthly cost of therapeutic drug treatment (INR 1839 or USD 21.97). Highest cost of therapeutic treatment (INR 1780 or USD 21.26) was observed among males, whereas highest cost of non-therapeutic treatment (INR 593 or USD 7.08) was observed among females making 64% of patients. Table 2 captured both the prevalence and cost burden of chronic illnesses. CKD, with a prevalence of 6%, had the highest cost of therapeutic treatment (INR 6665 ± 5501 or USD 79.36 ±65.50) as well as non-therapeutic treatment (INR 1010 ± 948 or USD 12.03 ± 11.29), which was highly statistically significant. We observed from table 3 that > 10% of their family income was spent on both therapeutic and non-therapeutic treatment by elderly patients, males and lower SES group. While analyzing the cost of drug treatment as a function of socio-economic status (table 4), the lower SES class recorded the highest cost of non-therapeutic treatment among the elderly, females, patients with > 2 chronic illnesses and duration of > 10 years of illness. On the other hand, table 5 data reflected that the lower SES group had the lowest cost of therapeutic treatment for hypertension and diabetes, with contrasting highest cost of non-therapeutic treatment for hypertension and CAD. DISCUSSION Drug therapy plays a critical role and accounts for a large proportion of direct costs in managing chronic illnesses(10). It has been shown in many studies that more is spent on medication by families affected by chronic disease than matched control families which are unaffected by chronic illnesses(19). Our study reported 88% prescription rate of non-therapeutic drugs, which is similar to another study conducted in India(20) and other studies from Nepal (81.2%) and Malaysia (8,21). Although nutraceuticals are prescribed frequently, most studies have shown no clinical evidence supporting their role in treatment or prevention of chronic diseases(22,23). Our data revealed that the total average monthly cost of drug treatment for chronic illness was INR 1879 (22.42 USD), with an average monthly cost of therapeutic drug treatment of INR 1319 (15.74 USD) and average monthly cost of non-therapeutic drug treatment of INR 560 (6.68 USD). A study conducted in Nigeria documented the mean direct cost to be $137.72, and the household monthly income to be $318.01 with 43.3% of the household income spent on health(5). An Indian study focusing on the cost of nutraceuticals showed comparable results (Rs 357.45 or USD 4.26 per month)(24). Correlating the demographic variables with the cost of treatment for chronic diseases (table 1), we observed that that the men although comprising 36% of the patients, spent higher amount on the therapeutic drug treatment as well as overall drug treatment indicating the tendency to favor the healthcare needs of male members over females. The urgent need for universal health coverage (UHC) is a critical step in ensuring equitable access to health and eliminating this gender gap(18). On the other hand, we observed that women spent higher amount on non-therapeutic drug treatment which may be attributed to being more socially influenced. We also observed that the cost of therapeutic drug treatment for chronic illness increased with increasing age, however, the cost of non-therapeutic drug treatment was comparable among different age groups, which is similar to the findings of previous studies(25,26). On studying the impact of smoking and alcohol intake on cost of drug treatment, we found an increase in average cost of therapeutic treatment as well as total drug treatment. The cost burden of chronic illness, both therapeutic and non-therapeutic treatment, showed a positive association with the increase in family size, this is in line with other studies(25,27). Healthcare policy makers need to prioritize the vulnerable circumstances of low-income population and facilitate their access to medications for chronic diseases. Regarding the family SES we observed a contrasting pattern, showing an increased cost of therapeutic treatment with higher family SES, while an increased cost of non-therapeutic treatment was seen with lower family SES. Various studies have reported that due to increased awareness of health problems and financial stability, patients with higher education(14) and socioeconomic status(27) tend to spend more on therapeutic treatment. Evaluating the proportion of family income spent on chronic illness (table 3), we recorded that the patients spending > 10% of their family income on total drug treatment was 20%, therapeutic treatment 13% and non-therapeutic treatment 4%. Once again, we observed that the highest number of patients spending > 10% of their family income on both therapeutic treatment (27%) and non-therapeutic treatment (11%) were from the lower SES with highly significant statistical p-values (chi-square) of 0.000 and 0.024 respectively. Results comparable to ours have been reported by a reference study(5). It is noteworthy that some studies indicate healthcare expenses surpassing 10% of the family income as financially devastating(13,28) whereas others identify 40% as a threshold for catastrophic expenses(29). Hence, we can infer that a household should maintain their healthcare expenses below 10% of the total income, to circumvent substantial financial stress. This brings to notice the alarming 11% of our patients from lower SES, spending > 10% of their family income on non-therapeutic treatment. We did a comprehensive analysis of the impact of various demographic variables on the cost of treatment with a special focus on the socio-economic status of our patients (table 4). The data revealed an interesting observation that the patients of lower SES bore the highest cost of non-therapeutic treatment, throughout all demographic variables. The high consumption of nutraceuticals may be attributed to misconceptions and false beliefs regarding the curative potential of nutraceuticals, due to lack of education among the lower SES patients. In addition, the poor nutritional status and laborious work profile among the lower SES patients, are some of the important elements leading to use of nutraceuticals as a solution to chronic ailments. We also reported that with the increase in number of chronic illnesses (>2) the number of patients spending > 10% of their family income on therapeutic treatment (33%) was significantly higher (table 3; p-value=0.000). It is an established fact that the cost of illness varies with the type of disease. We reported the highest cost of both total drug treatment and therapeutic treatment in patients with CKD followed by COPD and patients with hypertension, diabetes and dyslipidemia concomitantly, which was found to be statistically significant (table 2). However, the highest cost for non-therapeutic treatment was borne by patients with followed by patients with dyslipidemia and diabetes. These findings highlight the use of costly injectable drugs in CKD and use of inhalers and nebulization in treatment of COPD. Other studies have also indicated that chronic kidney disease (CKD), chronic liver disease (CLD) and diabetes result in relatively high direct costs(5,25,26). The economic burden in terms of direct expenditures, imposed by hypertension and diabetes, two of the most impactful or ‘Big four’ NCDs, is also emphasized by the World Health Organization(25). Our study data shows a substantial economic impact even though we did not capture any direct costs besides the cost of drug treatment, neither did we include the indirect costs, including the intangible costs. These findings emphasize the need for LMICs such as India, to enhance health insurance penetration and coverage, as implemented by countries like Thailand(5,25,30). The government of India through its national public health insurance policy, the Ayushman Bharat Yojana, is trying to cater to health needs of the underprivileged population. However, the policy must include all out-patient services under its umbrella to protect the lower SES households from the catastrophic financial burden of chronic diseases. Additionally, the high prescription rate of nutraceuticals in our patient population calls attention towards the overestimation of nutraceutical safety among the physicians(22). Reports of toxicity and potential for congenital abnormalities due to excessive consumption of fat-soluble vitamins(8) further demand for judicious use of nutraceuticals and consideration of their potential interactions and adverse effects. Consequently, the development of nutraceuticals must be backed by scientific evidence and stringent legislation should be put in place to curb their misuse. Promoting evidence-based research and dissemination of authentic information concerning nutraceuticals should be taken on priority at national level, to ensure their judicious use by both consumers and physicians. Strengths and limitations: This is the first study in the country that has attempted to compare the cost burden of therapeutic drug treatment with non-therapeutic drug treatment in patients with chronic illness. The study provides insights into the non-therapeutic treatment of chronic illnesses, and its burden on a family by calculating the proportion of average monthly family income spent on the same. This will also guide policymakers to develop strategies to reduce healthcare costs in this segment. However, the study has some limitations; a) the study focuses only on the cost of prescribed medications and not any other direct or indirect treatment cost which may lead to underestimated treatment cost of chronic illness, (b) one of the major limitations encountered include difficulty in estimating the actual household monthly income (especially for non-salary earners), c) besides, the study was carried out in a particular patient population hence our results may not be generalized at the national level. CONCLUSION The findings of our study revealed a catastrophic financial strain of chronic disease treatment on the patient’s family income especially among the low SES group. Since, there are no stringent regulations in India governing the prices of the non-therapeutic drugs, our findings underscore the need for policy enhancements within frameworks of government national health insurance policies like Ayushman Bharat Yojana to include outpatient care coverage, cap nutraceutical prices, and enforce evidence-based regulations to alleviate economic strain and ensure equitable healthcare access. Abbreviations CAGR - Compound Annual Growth Rate CKD - Chronic Kidney Disease CLD - Chronic Liver Disease COI - Cost of Illness COPD - Chronic Obstructive Pulmonary Disease DPCO - Drugs Prices Control Order EWS - Economically Weaker Section HAHCH - Hakeem Abdul Hameed Centenary Hospital HIMSR - Hamdard Institute of Medical Sciences and Research HIS - Hospital Information System IEC - Institutional Ethics Committee INR - Indian Rupees LMICs - Low and Middle-Income Countries MRP - Maximum Retail Price NCDs - Non-Communicable Diseases NPPA - National Pharmaceutical Pricing Authority SES - Socio-Economic Status SPSS - Statistical Package for the Social Sciences UHC - Universal Health Coverage USD - United States Dollar WHO - World Health Organization Declarations • Ethics approval and consent to participate: Ethical approval was obtained prior to conception of study from institutional ethics committee and appropriate consent was taken from patients for inclusion in study. • Consent for publication: Not applicable. • Availability of data and materials: The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. • Competing interests: The author(s) declared no potential competing interests with respect to the research, authorship, and/or publication of this article. • Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article. • Authors' contributions: Conceptualization, title and design selection: NN, VJ, DS. Data collection: AM, ND. Data analysis: AU, KC, RJ. Data interpretation: AU, NN, DS. Article writing: NN, VJ, AM. Article review and finalization: VJ, RA, SK. • Acknowledgements: The authors have great gratitude to the participants for their positive attitude and willingness to participate in the study. The authors would especially like to acknowledge the support provided by the IT section during data collection. References World Health Organization. Global status report on noncommunicable diseases. World Heal Organ. 2010;53(9):1689–99. Organization WH. Preventing chronic diseases : a vital investment : WHO global report. World Health Organization; 2005. p. 182 p. Russell S. Illuminating cases: understanding the economic burden of illness through case study household research. Health Policy Plan [Internet]. 2005 Sep 1 [cited 2024 Nov 19];20(5):277–89. Available from: https://dx.doi.org/10.1093/heapol/czi035 Dom TNM, Ayob R, Abd Muttalib K, Aljunid SM. National Economic Burden Associated with Management of Periodontitis in Malaysia. Int J Dent [Internet]. 2016 [cited 2024 Nov 18];2016. Available from: https://pubmed.ncbi.nlm.nih.gov/27092180/ Okediji PT, Ojo AO, Ojo AI, Ojo AS, Ojo OE, Abioye-Kuteyi EA. The Economic Impacts of Chronic Illness on Households of Patients in Ile-Ife, South-Western Nigeria. Cureus [Internet]. 2017 Oct 7 [cited 2024 Nov 18];9(10). Available from: https://pubmed.ncbi.nlm.nih.gov/29226046/ Mahmood NA, Hassan MR, Ahmad S, Mohd Nawi H, Pang NTP, Syed Abdul Rahim SS, et al. Nutraceutical Use among Patients with Chronic Disease Attending Outpatient Clinics in a Tertiary Hospital. Evid Based Complement Alternat Med [Internet]. 2020 [cited 2024 Nov 18];2020:9814815. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC7673927/ https://www.fortunebusinessinsights.com/industry-reports/infographics/southeast-asia-dietary-supplements-market-101943 [Internet]. 2023. No Title. Available from: https://www.fortunebusinessinsights.com/industry-reports/infographics/southeast-asia-dietary-supplements-market-101943 Shrestha R, Shrestha S, Badri KC, Shrestha S. Evaluation of nutritional supplements prescribed, its associated cost and patients knowledge, attitude and practice towards nutraceuticals: A hospital based cross-sectional study in Kavrepalanchok, Nepal. PLoS One [Internet]. 2021 Jun 1 [cited 2024 Nov 19];16(6):e0252538. Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0252538 DPCO/NPPA | Department of Pharmaceuticals [Internet]. [cited 2025 Apr 11]. Available from: https://pharma-dept.gov.in/dpconppa Suhrcke M, Alliance OH. Chronic Disease: An Economic Perspective [Internet]. Oxford Health Alliance; 2006. Available from: https://books.google.co.in/books?id=VlFuYgEACAAJ Russell S. Ability to pay for health care: concepts and evidence. Health Policy Plan [Internet]. 1996 Sep 1 [cited 2024 Nov 19];11(3):219–37. Available from: https://dx.doi.org/10.1093/heapol/11.3.219 Russell S. The Economic Burden of Illness for Households in Developing Countries: A Review of Studies Focusing on Malaria, Tuberculosis, and Human Immunodeficiency Virus/Acquired Immunodeficiency Syndrome. 2004 [cited 2024 Nov 18]; Available from: https://www.ncbi.nlm.nih.gov/books/NBK3768/ Wingfield T, Boccia D, Tovar M, Gavino A, Zevallos K, Montoya R, et al. Defining catastrophic costs and comparing their importance for adverse tuberculosis outcome with multi-drug resistance: a prospective cohort study, Peru. PLoS Med [Internet]. 2014 [cited 2024 Nov 19];11(7). Available from: https://pubmed.ncbi.nlm.nih.gov/25025331/ You X, Kobayashi Y. Determinants of out-of-pocket health expenditure in China: analysis using China Health and Nutrition Survey data. Appl Health Econ Health Policy [Internet]. 2011 [cited 2024 Nov 19];9(1):39–49. Available from: https://pubmed.ncbi.nlm.nih.gov/21174481/ Sturm R. The Effects Of Obesity, Smoking, And Drinking On Medical Problems And Costs. https://doi.org/101377/hlthaff212245. 2017 Aug 17; Jeon YH, Essue B, Jan S, Wells R, Whitworth JA. Economic hardship associated with managing chronic illness: A qualitative inquiry. BMC Health Serv Res [Internet]. 2009 Oct 9 [cited 2024 Nov 18];9(1):1–11. Available from: https://bmchealthservres.biomedcentral.com/articles/10.1186/1472-6963-9-182 Kumar G, Dash P, Patnaik J, Pany G. SOCIOECONOMIC STATUS SCALE-MODIFIED KUPPUSWAMY SCALE FOR THE YEAR 2022. Int J Community Dent [Internet]. 2022 Jun 10 [cited 2024 Nov 18];10(1):1–6. Available from: https://www.editorialmanager.in/index.php/ijcd/article/view/26 Murphy A, Palafox B, Walli-Attaei M, Powell-Jackson T, Rangarajan S, Alhabib KF, et al. The household economic burden of non-communicable diseases in 18 countries. BMJ Glob Heal [Internet]. 2020 Feb 11 [cited 2024 Nov 18];5(2). Available from: https://pubmed.ncbi.nlm.nih.gov/32133191/ Pallegedara A. Impacts of chronic non-communicable diseases on households’ out-of-pocket healthcare expenditures in Sri Lanka. Int J Heal Econ Manag [Internet]. 2018 Sep 1 [cited 2024 Nov 18];18(3):301–19. Available from: https://www.researchgate.net/publication/322368095_Impacts_of_chronic_non-communicable_diseases_on_households’_out-of-pocket_healthcare_expenditures_in_Sri_Lanka Sharma A, Adiga S, Ashok M. Knowledge, attitude and practices related to dietary supplements and micronutrients in health sciences students. J Clin Diagn Res [Internet]. 2014 [cited 2024 Nov 19];8(8). Available from: https://pubmed.ncbi.nlm.nih.gov/25302213/ R N, Rai M, Ravindran A. Awareness And Practices Towards Nutraceuticals Among Medical Practitioners of A Tertiary Care Teaching Hospital in South India - A Pilot Study. IOSR J Dent Med Sci. 2017 May;16(05):12–6. Ronis MJJ, Pedersen KB, Watt J. Adverse Effects of Nutraceuticals and Dietary Supplements. Annu Rev Pharmacol Toxicol [Internet]. 2018 Jan 6 [cited 2024 Nov 19];58:583–601. Available from: https://pubmed.ncbi.nlm.nih.gov/28992429/ Teoh SL, Ngorsuraches S, Lai NM, Bangpan M, Chaiyakunapruk N. Factors affecting consumers’ decisions on the use of nutraceuticals: a systematic review. Int J Food Sci Nutr [Internet]. 2019 May 19 [cited 2024 Nov 19];70(4):491–512. Available from: https://pubmed.ncbi.nlm.nih.gov/30634867/ Gosavi S, Subramanian M, Reddy R, Shet BL. A Study of Prescription Pattern of Neutraceuticals, Knowledge of the Patients and Cost in a Tertiary Care Hospital. J Clin Diagn Res [Internet]. 2016 Apr 1 [cited 2024 Nov 18];10(4):FC01. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC4866122/ Almalki ZS, Alahmari AK, Alqahtani N, Alzarea AI, Alshehri AM, Alruwaybiah AM, et al. Households’ Direct Economic Burden Associated with Chronic Non-Communicable Diseases in Saudi Arabia. Int J Environ Res Public Heal 2022, Vol 19, Page 9736 [Internet]. 2022 Aug 8 [cited 2024 Nov 18];19(15):9736. Available from: https://www.mdpi.com/1660-4601/19/15/9736/htm Chua KP, Lee JM, Conti RM. Out-of-Pocket Spending for Insulin, Diabetes-Related Supplies, and Other Health Care Services Among Privately Insured US Patients With Type 1 Diabetes. JAMA Intern Med [Internet]. 2020 Jul 1 [cited 2024 Nov 18];180(7):1012. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC7265118/ Makinen M, Waters H, Rauch M, Almagambetova N, Bitran R, Gilson L, et al. Inequalities in health care use and expenditures: empirical data from eight developing countries and countries in transition. Bull World Health Organ [Internet]. 2000 [cited 2024 Nov 18];78(1):55. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC2560608/ Noncommunicable diseases [Internet]. [cited 2024 Nov 18]. Available from: https://www.who.int/news-room/fact-sheets/detail/noncommunicable-diseases Xu K, Evans DB, Kawabata K, Zeramdini R, Klavus J, Murray CJL. Household catastrophic health expenditure: a multicountry analysis. Lancet (London, England) [Internet]. 2003 Jul 12 [cited 2024 Nov 19];362(9378):111–7. Available from: https://pubmed.ncbi.nlm.nih.gov/12867110/ Almalki ZS, Karami NA, Almsoudi IA, Alhasoun RK, Mahdi AT, Alabsi EA, et al. Patient- centered medical home care access among adults with chronic conditions: National Estimates from the medical expenditure panel survey. BMC Health Serv Res [Internet]. 2018 Sep 27 [cited 2024 Nov 18];18(1):1–11. Available from: https://bmchealthservres.biomedcentral.com/articles/10.1186/s12913-018-3554-3 Tables Tables 1 to 3 are available in the Supplementary Files section Additional Declarations No competing interests reported. Supplementary Files Tables.docx Cite Share Download PDF Status: Published Journal Publication published 20 Jun, 2025 Read the published version in Cost Effectiveness and Resource Allocation → Version 1 posted Editorial decision: Accepted 21 Apr, 2025 Reviews received at journal 19 Apr, 2025 Reviews received at journal 15 Apr, 2025 Reviewers agreed at journal 12 Apr, 2025 Reviewers agreed at journal 12 Apr, 2025 Reviewers invited by journal 11 Apr, 2025 Submission checks completed at journal 11 Apr, 2025 First submitted to journal 11 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6086835","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":442035076,"identity":"39a11f5f-4cf6-46ee-8e89-06f12c52cb89","order_by":0,"name":"Nusrat Nabi","email":"","orcid":"","institution":"Hamdard Institute of Medical Sciences and Research","correspondingAuthor":false,"prefix":"","firstName":"Nusrat","middleName":"","lastName":"Nabi","suffix":""},{"id":442035077,"identity":"9f96ebf2-5b3b-4e7d-b2f7-d1251b9f80d0","order_by":1,"name":"Ayushi Manghani","email":"","orcid":"","institution":"Hamdard Institute of Medical Sciences and Research","correspondingAuthor":false,"prefix":"","firstName":"Ayushi","middleName":"","lastName":"Manghani","suffix":""},{"id":442035078,"identity":"643a7d6a-2016-4c19-96a2-3536443b859e","order_by":2,"name":"Azhar Uddin","email":"","orcid":"","institution":"Hamdard Institute of Medical Sciences and Research","correspondingAuthor":false,"prefix":"","firstName":"Azhar","middleName":"","lastName":"Uddin","suffix":""},{"id":442035079,"identity":"b892cde7-606a-420a-a7e3-51672007ac22","order_by":3,"name":"Neha Dhillon","email":"","orcid":"","institution":"Hamdard Institute of Medical Sciences and Research","correspondingAuthor":false,"prefix":"","firstName":"Neha","middleName":"","lastName":"Dhillon","suffix":""},{"id":442035080,"identity":"3f1df078-277b-4da3-bdce-0ad9c9a5bd51","order_by":4,"name":"Dharmander Singh","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYDCCAwwM0lCmAQNDBZBiZm4gRcsZkBZGUrQwtoFoAlr4bh9gvF1Qcy+af3bzxseV82qj+duBWn5UbMOpRfJcArP1jGPFuTPuHCs2PLvteO6Mw4wNjD1nbuPUYnCGgU2ahy0ht+FGjplk47ZjuQ1ALcyMbYS0/EvInX8jx/xn45xjufOJ0sLblpC7AWgLY2NDTe4GQlokzzA2W/P2JeRuvJFWLNlw7EDuRqCWg/j8wneG+eBtnm8JufNuJG/82FBTlzvv/OGDD35U4NaCHguHweQBPOoxQB0pikfBKBgFo2CEAACL2l7O8TYMnQAAAABJRU5ErkJggg==","orcid":"","institution":"Hamdard Institute of Medical Sciences and Research","correspondingAuthor":true,"prefix":"","firstName":"Dharmander","middleName":"","lastName":"Singh","suffix":""},{"id":442035081,"identity":"457e76dd-97c2-45ad-ae72-3c3b0aaa7f3c","order_by":5,"name":"Kailash Chandra","email":"","orcid":"","institution":"Hamdard Institute of Medical Sciences and Research","correspondingAuthor":false,"prefix":"","firstName":"Kailash","middleName":"","lastName":"Chandra","suffix":""},{"id":442035082,"identity":"27ed5d7a-692d-4e41-8985-c93434e9b52e","order_by":6,"name":"Vineet Jain","email":"","orcid":"","institution":"Hamdard Institute of Medical Sciences and Research","correspondingAuthor":false,"prefix":"","firstName":"Vineet","middleName":"","lastName":"Jain","suffix":""},{"id":442035083,"identity":"b3f362f6-3eb2-4bcf-90fc-60cfe617770b","order_by":7,"name":"Riyan Jain","email":"","orcid":"","institution":"Illinois Mathematics and Science Academy","correspondingAuthor":false,"prefix":"","firstName":"Riyan","middleName":"","lastName":"Jain","suffix":""},{"id":442035084,"identity":"ffd86539-2e25-41e4-9b41-1595ae91c44d","order_by":8,"name":"Razi Ahmad","email":"","orcid":"","institution":"Hamdard Institute of Medical Sciences and Research","correspondingAuthor":false,"prefix":"","firstName":"Razi","middleName":"","lastName":"Ahmad","suffix":""},{"id":442035085,"identity":"b5058b9e-6c10-4584-b782-0a4bf9804814","order_by":9,"name":"Sunil Kohli","email":"","orcid":"","institution":"Hamdard Institute of Medical Sciences and Research","correspondingAuthor":false,"prefix":"","firstName":"Sunil","middleName":"","lastName":"Kohli","suffix":""}],"badges":[],"createdAt":"2025-02-22 17:38:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6086835/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6086835/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12962-025-00628-6","type":"published","date":"2025-06-20T15:57:06+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80801139,"identity":"09cb3799-c17b-4a85-b4ae-d94f31315af3","added_by":"auto","created_at":"2025-04-17 08:37:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":281484,"visible":true,"origin":"","legend":"\u003cp\u003eclearly depicted that overall, the number of drugs prescribed for therapeutic treatment was higher than those prescribed for non-therapeutic treatment across all chronic diseases except for hypertension and dyslipidemia.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6086835/v1/5e0e0648ae62ea365d34c233.png"},{"id":85231441,"identity":"41180831-62e0-4807-beec-ca38bd4727c2","added_by":"auto","created_at":"2025-06-23 16:08:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":938185,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6086835/v1/1a5e21ff-c75f-4bfd-abaf-2ab9997f51c1.pdf"},{"id":80802010,"identity":"d1eba4af-2582-451f-a417-2312f838c3b3","added_by":"auto","created_at":"2025-04-17 08:45:27","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":56030,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-6086835/v1/600813c44f59d1b0b3c141aa.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003ePrescription Cost Analysis and Economic Impact of Drug Treatment in Patients with Chronic Illness, Attending the Medicine Out-patient Department in a Tertiary Care Hospital at South Delhi\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eChronic illnesses have become a significant healthcare issue globally (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). According to the World Health Organization (WHO), 80% of the deaths due to chronic illnesses occur in low and middle-income countries (LMICs), including India(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Significant morbidity and mortality due to chronic illnesses may lead to economic impoverishment, resulting in a fall of consumption levels below minimum needs(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). From the national standpoint, chronic illnesses reduce work capacity and life span, thus affecting economic productivity.(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eA wide variety of dietary supplements known as nutraceuticals are claimed to offer prevention and cure for numerous diseases. Although these claims often lack scientific support, they are used indiscriminately by patients with chronic illnesses(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Southeast Asia is the most rapidly growing market for the nutraceuticals with an estimated compound annual growth rate (CAGR) of 12% (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Despite the bigger market size of nutraceuticals compared to pharmaceuticals, their regulations remain less stringent, which emphasizes an urgent need to explore their pattern of consumption and cost per prescription(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). In India, the regulation of drug prices, including non-therapeutic drugs, comes under the Drugs Prices Control Order (DPCO), which is enforced by the National Pharmaceutical Pricing Authority (NPPA). However, India\u0026rsquo;s policy for non-therapeutic drug cost regulation under the DPCO allows manufacturers significant pricing freedom, which is capped at a 10% annual increase, with the NPPA stepping in only in exceptional cases.(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eSeveral methods have been employed to understand the economic burden of chronic illnesses(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). The expenses spent on these illnesses are distributed in three categories: direct, indirect, and intangible costs(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Direct costs represent the amount of household income allocated for medical care, including prevention, diagnosis, rehabilitation and treatment of the illness(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). The indirect costs include diminution of labor productivity that is caused by morbidity and mortality arising from these diseases(\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). The intangible costs encompass the psychological effects attributed to disease, usually in the form of pain, distress, and bereavement. The cost of illness (COI) approach, focusing on the direct cost of drug treatment per prescription for chronic illness was considered for this study(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). The household was selected as the unit of analysis as the financial burden of an illness is distributed among both the sick and other members of the household, and predominantly affects the overall budget of the household.(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThere are notable gaps in India in the literature regarding the economic repercussions of chronic diseases among Indian population. To our knowledge no studies on evaluation and comparison of financial impact of non-therapeutic drugs with therapeutic drugs for a wide range of chronic diseases in the Indian population are available. Hence, this study was planned to primarily determine the average cost per prescription for treatment of chronic illnesses and further evaluate the economic burden imposed by non-therapeutic drug treatment (nutraceuticals). The secondary objective included exploring the association between the cost of drug treatment of chronic illnesses and the various demographic and disease parameters.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStudy Design \u0026amp; Setting:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eThis was a retrospective, cross sectional, data mining study. A total of 7877 prescriptions of patients suffering from chronic illness, who attended the outpatient clinics of the Department of Medicine at Hamdard Institute of Medical Sciences \u0026amp; Research, New Delhi, during the months of July and August 2022, were processed for inclusion in the study after obtaining due approval from the institutional ethics committee (IEC).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSample selection:\u003c/em\u003e\u003c/strong\u003e Prescriptions of patients with the following criteria were included: (i) patients aged 18 years and above, (ii) of any gender, (iii) with definitive diagnosis of at least one chronic illness, and (iv) having been on same treatment for their chronic disease for at least three months (so that the subjects would have experienced significant costs associated with managing their chronic illness). The exclusion criteria were as follows: (i) Duplicate follow-up prescriptions, (ii) prescriptions for simultaneous treatment of acute illness, (iii) patients enrolled in the government health scheme receiving free medications (iv) patients not able to be contacted and (v) patients not ready to give consent.\u003c/p\u003e\n\u003cp\u003eExtensive screening of all medicine out-patient prescription files, was conducted by trained medical professionals at 5 levels; 1) Prescriptions of all patients with chronic illnesses were filtered in the first level; 2) Next, only patients continuing the same treatment for chronic illness, for a minimum of 3 months, were taken; 3) Further, patients enrolled in the government economically weaker section (EWS) health scheme were dropped out; 4) Prescriptions found with any treatment for simultaneous acute illness were excluded; and 5) Finally, the patients were contacted over the telephone for a structured interview and a total of 465 patients were included in the study after obtaining informed consent.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData Collection:\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eTo achieve uniform \u0026ldquo;prescription cost analysis\u0026rdquo; a skill exercise was organized for the team members for working on hospital information system (HIS) and conducting telephonic interviews. Prescriptions were pulled from the HIS in the form of excel sheets. The data was extracted in a structured case record form, designed after literature review of comparable studies, and approved by a senior internist and statistician for validity(16). The data was collected in 2 phases; 1) All information on patient demographic characteristics and prescribed drugs related information was collected from the prescription retrieved from the HIS. 2) Patient informed consent, personal history (smoking, alcohol intake), compliance with treatment and socio-economic data was obtained over the telephone.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData Analysis:\u003c/em\u003e\u003c/strong\u003e Being a retrospective study, only the cost of drugs prescribed for the chronic illness in the Medicine outpatient clinics was calculated per month for a patient. For every patient, the average monthly cost of drug treatment was calculated by taking into account the number of drugs prescribed (brand or generic), and the respective number of drug units (tablets, capsules) consumed in a month as per the prescription dosing schedule. The maximum retail prices (MRP) of the drugs as obtained from our hospital pharmacy was used for cost analysis. Throughout the analysis, the data was stratified into 2 specific categories: 1) Cost of Therapeutic Drug Treatment and 2) Cost of Non-therapeutic Drug Treatment (nutraceuticals), for a comprehensive comparison and correlation. Analysis of socio-economic status was done based on the latest modified Kuppuswamy scale(17) and the \u0026lsquo;average family income per month\u0026rsquo; was used for analysis. To calculate average family income per month, total family income for a month as disclosed by the family was added and then divided by the number of family members. To calculate family income per month, total monthly income details were asked from the patient and the accompanying relative, as India still has a trend of extended families, so where the patient and accompanying person were not aware of the income, it was asked via a telephonic conversation with other family members. Where monthly income was not fixed for a member in the family, then average monthly income was calculated using total income in the last financial year for that person and then divided by twelve to get the average monthly income for that individual. To further assess the financial implications of the chronic illness the data was categorized into 2 groups namely, patients spending \u0026lt;10% and \u003cu\u003e\u0026gt;\u003c/u\u003e10% of their monthly family income on drug treatment. The cost of treatment was presented in Indian Rupees (INR) as well as US Dollars (USD) for comparison with international studies. \u0026ldquo;Chronic Illness\u0026rdquo; for this prescription cost analysis study was defined as per WHO, wherein, chronic diseases or non-communicable diseases (NCDs), are of long duration and the result of a combination of genetic, physiological, environmental and behavioral factors(18).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStatistical Analysis:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eAll data was analyzed using Statistical Package for the Social Sciences [SPSS] (IBM Corp., Armonk, NY) version 16 software. The categorical variables of demographic characteristics were presented as frequency and percentage. In descriptive statistics, mean and standard deviations were calculated for continuous variables. The two sample, independent t-tests for continuous variables was used for significant difference between the cost of therapeutic and non-therapeutic drug treatment. The chi-square test was performed for categorical variables to verify association between the two groups of; \u0026lt;10% and \u0026ge;10% of family income spent on therapeutic and non-therapeutic drug treatment. The odds ratio was also calculated by performing the logistic regression in Table 3. The level of statistical significance was set at \u0026lt; 0.05.\u0026nbsp;\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eA total of 7877 outpatient prescriptions from the medicine department were screened and 465 patients were enrolled in the study based on the eligibility criteria. Among these, 410 patients were prescribed non-therapeutic drug treatment for chronic illness amounting to 88% prescription rate.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFrom the demographic data we observed that the elderly comprising only 23% of patients had the highest average monthly cost of therapeutic drug treatment (INR 1839 or USD 21.97). Highest cost of therapeutic treatment (INR 1780 or USD 21.26) was observed among males, whereas highest cost of non-therapeutic treatment (INR 593 or USD 7.08) was observed among females making 64% of patients. Table 2 captured both the prevalence and cost burden of chronic illnesses. CKD, with a prevalence of 6%, had the highest cost of therapeutic treatment (INR 6665 \u0026plusmn; 5501 or USD 79.36 \u0026plusmn;65.50) as well as non-therapeutic treatment (INR 1010 \u0026plusmn; 948 or USD 12.03 \u0026plusmn; 11.29), which was highly statistically significant. We observed from table 3 that \u003cu\u003e\u0026gt;\u003c/u\u003e10% of their family income was spent on both therapeutic and non-therapeutic treatment by elderly patients, males and lower SES group.\u003c/p\u003e\n\u003cp\u003eWhile analyzing the cost of drug treatment as a function of socio-economic status (table 4), the lower SES class recorded the highest cost of non-therapeutic treatment among the elderly, females, patients with \u0026gt; 2 chronic illnesses and duration of \u0026gt; 10 years of illness. On the other hand, table 5 data reflected that the lower SES group had the lowest cost of therapeutic treatment for hypertension and diabetes, with contrasting highest cost of non-therapeutic treatment for hypertension and CAD.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eDrug therapy plays a critical role and accounts for a large proportion of direct costs in managing chronic illnesses(10). It has been shown in many studies that more is spent on medication by families affected by chronic disease than matched control families which are unaffected by chronic illnesses(19). Our study reported 88% prescription rate of non-therapeutic drugs, which is similar to another study conducted in India(20) and other studies from Nepal (81.2%) and Malaysia (8,21). Although nutraceuticals are prescribed frequently, most studies have shown no clinical evidence supporting their role in treatment or prevention of chronic diseases(22,23). Our data revealed that the total average monthly cost of drug treatment for chronic illness was INR 1879 (22.42 USD), with an average monthly cost of therapeutic drug treatment of INR 1319 (15.74 USD) and average monthly cost of non-therapeutic drug treatment of INR 560 (6.68 USD). A study conducted in Nigeria documented the mean direct cost to be $137.72, and the household monthly income to be $318.01 with 43.3% of the household income spent on health(5). An Indian study\u0026nbsp;focusing on the cost of nutraceuticals showed comparable results (Rs 357.45 or USD 4.26 per month)(24).\u003c/p\u003e\n\u003cp\u003eCorrelating the demographic variables with the cost of treatment for chronic diseases (table 1), we observed that that the men although comprising 36% of the patients, spent higher amount on the therapeutic drug treatment as well as overall drug treatment indicating the tendency to favor the healthcare needs of male members over females. The urgent need for universal health coverage (UHC) is a critical step in ensuring equitable access to health and eliminating this gender gap(18). On the other hand, we observed that women spent higher amount on non-therapeutic drug treatment which may be attributed to being more socially influenced. We also observed that the cost of therapeutic drug treatment for chronic illness increased with increasing age, however, the cost of non-therapeutic drug treatment was comparable among different age groups, which is similar to the findings of previous studies(25,26). On studying the impact of smoking and alcohol intake on cost of drug treatment, we found an increase in average cost of therapeutic treatment as well as total drug treatment. The cost burden of chronic illness, both therapeutic and non-therapeutic treatment, showed a positive association with the increase in family size, this is in line with other studies(25,27). Healthcare policy makers need to prioritize the vulnerable circumstances of low-income population and facilitate their access to medications for chronic diseases.\u003c/p\u003e\n\u003cp\u003eRegarding the family SES we observed a contrasting pattern, showing an increased cost of therapeutic treatment with higher family SES, while an increased cost of non-therapeutic treatment was seen with lower family SES. Various studies have reported that due to increased awareness of health problems and financial stability, patients with higher education(14) and socioeconomic status(27) tend to spend more on therapeutic treatment. Evaluating the proportion of family income spent on chronic illness (table 3), we recorded that the patients spending \u003cu\u003e\u0026gt;\u003c/u\u003e10% of their family income on total drug treatment was 20%, therapeutic treatment 13% and non-therapeutic treatment 4%. Once again, we observed that the highest number of patients spending \u003cu\u003e\u0026gt;\u003c/u\u003e10% of their family income on both therapeutic treatment (27%) and non-therapeutic treatment (11%) were from the lower SES with highly significant statistical p-values (chi-square) of 0.000 and 0.024 respectively. Results comparable to ours have been reported by a reference study(5). It is noteworthy that some studies indicate healthcare expenses surpassing 10% of the family income as financially devastating(13,28) whereas others identify 40% as a threshold for catastrophic expenses(29). Hence, we can infer that a household should maintain their healthcare expenses below 10% of the total income, to circumvent substantial financial stress. This brings to notice the alarming 11% of our patients from lower SES, spending \u003cu\u003e\u0026gt;\u003c/u\u003e10% of their family income on non-therapeutic treatment. We did a comprehensive analysis of the impact of various demographic variables on the cost of treatment with a special focus on the socio-economic status of our patients (table 4). The data revealed an interesting observation that the patients of lower SES bore the highest cost of non-therapeutic treatment, throughout all demographic variables. The high consumption of nutraceuticals may be attributed to misconceptions and false beliefs regarding the curative potential of nutraceuticals, due to lack of education among the lower SES patients. In addition, the poor nutritional status and laborious work profile among the lower SES patients, are some of the important elements leading to use of nutraceuticals as a solution to chronic ailments. We also reported that with the increase in number of chronic illnesses (\u0026gt;2) the number of patients spending \u003cu\u003e\u0026gt;\u003c/u\u003e10% of their family income on therapeutic treatment (33%) was significantly higher (table 3; p-value=0.000).\u003c/p\u003e\n\u003cp\u003eIt is an established fact that the cost of illness varies with the type of disease. We reported the highest cost of both total drug treatment and therapeutic treatment in patients with CKD followed by COPD and patients with hypertension, diabetes and dyslipidemia concomitantly, which was found to be statistically significant (table 2). However, the highest cost for non-therapeutic treatment was borne by patients with followed by patients with dyslipidemia and diabetes. These findings highlight the use of costly injectable drugs in CKD and use of inhalers and nebulization in treatment of COPD. Other studies have also indicated that chronic kidney disease (CKD), chronic liver disease (CLD) and diabetes result in relatively high direct costs(5,25,26). The economic burden in terms of direct expenditures, imposed by hypertension and diabetes, two of the most impactful or \u0026lsquo;Big four\u0026rsquo; NCDs, is also emphasized by the World Health Organization(25).\u003c/p\u003e\n\u003cp\u003eOur study data shows a substantial economic impact even though we did not capture any direct costs besides the cost of drug treatment, neither did we include the indirect costs, including the intangible costs. These findings emphasize the need for LMICs such as India, to enhance health insurance penetration and coverage, as implemented by countries like Thailand(5,25,30). The government of India through its national public health insurance policy, the Ayushman Bharat Yojana, is trying to cater to health needs of the underprivileged population. However, the policy must include all out-patient services under its umbrella to protect the lower SES households from the catastrophic financial burden of chronic diseases. Additionally, the high prescription rate of nutraceuticals in our patient population calls attention towards the overestimation of nutraceutical safety among the physicians(22). Reports of toxicity and potential for congenital abnormalities due to excessive consumption of fat-soluble vitamins(8) further demand for judicious use of nutraceuticals and consideration of their potential interactions and adverse effects. Consequently, the development of nutraceuticals must be backed by scientific evidence and stringent legislation should be put in place to curb their misuse. Promoting evidence-based research and dissemination of authentic information concerning nutraceuticals should be taken on priority at national level, to ensure their judicious use by both consumers and physicians.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStrengths and limitations:\u003c/strong\u003e This is the first study in the country that has attempted to compare the cost burden of therapeutic drug treatment with non-therapeutic drug treatment in patients with chronic illness. The study provides insights into the non-therapeutic treatment of chronic illnesses, and its burden on a family by calculating the proportion of average monthly family income spent on the same. This will also guide policymakers to develop strategies to reduce healthcare costs in this segment. However, the study has some limitations; a) the study focuses only on the cost of prescribed medications and not any other direct or indirect treatment cost which may lead to underestimated treatment cost of chronic illness, (b) one of the major limitations encountered include difficulty in estimating the actual household monthly income (especially for non-salary earners), c) besides, the study was carried out in a particular patient population hence our results may not be generalized at the national level.\u0026nbsp;\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThe findings of our study revealed a catastrophic financial strain of chronic disease treatment on the patient\u0026rsquo;s family income especially among the low SES group. Since, there are no stringent regulations in India governing the prices of the non-therapeutic drugs, our findings underscore the need for policy enhancements within frameworks of government national health insurance policies like Ayushman Bharat Yojana to include outpatient care coverage, cap nutraceutical prices, and enforce evidence-based regulations to alleviate economic strain and ensure equitable healthcare access.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003col\u003e\n \u003cli\u003eCAGR - Compound Annual Growth Rate\u003c/li\u003e\n \u003cli\u003eCKD - Chronic Kidney Disease\u003c/li\u003e\n \u003cli\u003eCLD - Chronic Liver Disease\u003c/li\u003e\n \u003cli\u003eCOI - Cost of Illness\u003c/li\u003e\n \u003cli\u003eCOPD - Chronic Obstructive Pulmonary Disease\u003c/li\u003e\n \u003cli\u003eDPCO - Drugs Prices Control Order\u003c/li\u003e\n \u003cli\u003eEWS - Economically Weaker Section\u003c/li\u003e\n \u003cli\u003eHAHCH - Hakeem Abdul Hameed Centenary Hospital\u003c/li\u003e\n \u003cli\u003eHIMSR - Hamdard Institute of Medical Sciences and Research\u003c/li\u003e\n \u003cli\u003eHIS - Hospital Information System\u003c/li\u003e\n \u003cli\u003eIEC - Institutional Ethics Committee\u003c/li\u003e\n \u003cli\u003eINR - Indian Rupees\u003c/li\u003e\n \u003cli\u003eLMICs - Low and Middle-Income Countries\u003c/li\u003e\n \u003cli\u003eMRP - Maximum Retail Price\u003c/li\u003e\n \u003cli\u003eNCDs - Non-Communicable Diseases\u003c/li\u003e\n \u003cli\u003eNPPA - National Pharmaceutical Pricing Authority\u003c/li\u003e\n \u003cli\u003eSES - Socio-Economic Status\u003c/li\u003e\n \u003cli\u003eSPSS - Statistical Package for the Social Sciences\u003c/li\u003e\n \u003cli\u003eUHC - Universal Health Coverage\u003c/li\u003e\n \u003cli\u003eUSD - United States Dollar\u003c/li\u003e\n \u003cli\u003eWHO - World Health Organization\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Declarations","content":"\u003cp\u003e•\u0026nbsp; \u0026nbsp;\u0026nbsp;Ethics approval and consent to participate: Ethical approval was obtained prior to conception of study from institutional ethics committee and appropriate consent was taken from patients for inclusion in study.\u003c/p\u003e\n\u003cp\u003e•\u0026nbsp; \u0026nbsp;\u0026nbsp;Consent for publication: Not applicable.\u003c/p\u003e\n\u003cp\u003e•\u0026nbsp; \u0026nbsp;\u0026nbsp;Availability of data and materials: The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e•\u0026nbsp; \u0026nbsp;\u0026nbsp;Competing interests: The author(s) declared no potential competing interests with respect to the research, authorship, and/or publication of this article.\u003c/p\u003e\n\u003cp\u003e•\u0026nbsp; \u0026nbsp;\u0026nbsp;Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.\u003c/p\u003e\n\u003cp\u003e•\u0026nbsp; \u0026nbsp;\u0026nbsp;Authors' contributions: Conceptualization, title and design selection: NN, VJ, DS. Data collection: AM, ND. Data analysis: AU, KC, RJ. Data interpretation: AU, NN, DS. Article writing: NN, VJ, AM. Article review and finalization: VJ, RA, SK. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e• \u0026nbsp; \u0026nbsp;Acknowledgements: The authors have great gratitude to the participants for their positive attitude and willingness to participate in the study. The authors would especially like to acknowledge the support provided by the IT section during data collection.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eWorld Health Organization. Global status report on noncommunicable diseases. World Heal Organ. 2010;53(9):1689\u0026ndash;99.\u003c/li\u003e\n \u003cli\u003eOrganization WH. Preventing chronic diseases : a vital investment : WHO global report. World Health Organization; 2005. p. 182 p.\u003c/li\u003e\n \u003cli\u003eRussell S. Illuminating cases: understanding the economic burden of illness through case study household research. Health Policy Plan [Internet]. 2005 Sep 1 [cited 2024 Nov 19];20(5):277\u0026ndash;89. Available from: https://dx.doi.org/10.1093/heapol/czi035\u003c/li\u003e\n \u003cli\u003eDom TNM, Ayob R, Abd Muttalib K, Aljunid SM. National Economic Burden Associated with Management of Periodontitis in Malaysia. Int J Dent [Internet]. 2016 [cited 2024 Nov 18];2016. Available from: https://pubmed.ncbi.nlm.nih.gov/27092180/\u003c/li\u003e\n \u003cli\u003eOkediji PT, Ojo AO, Ojo AI, Ojo AS, Ojo OE, Abioye-Kuteyi EA. The Economic Impacts of Chronic Illness on Households of Patients in Ile-Ife, South-Western Nigeria. Cureus [Internet]. 2017 Oct 7 [cited 2024 Nov 18];9(10). Available from: https://pubmed.ncbi.nlm.nih.gov/29226046/\u003c/li\u003e\n \u003cli\u003eMahmood NA, Hassan MR, Ahmad S, Mohd Nawi H, Pang NTP, Syed Abdul Rahim SS, et al. Nutraceutical Use among Patients with Chronic Disease Attending Outpatient Clinics in a Tertiary Hospital. Evid Based Complement Alternat Med [Internet]. 2020 [cited 2024 Nov 18];2020:9814815. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC7673927/\u003c/li\u003e\n \u003cli\u003ehttps://www.fortunebusinessinsights.com/industry-reports/infographics/southeast-asia-dietary-supplements-market-101943 [Internet]. 2023. No Title. Available from: https://www.fortunebusinessinsights.com/industry-reports/infographics/southeast-asia-dietary-supplements-market-101943\u003c/li\u003e\n \u003cli\u003eShrestha R, Shrestha S, Badri KC, Shrestha S. Evaluation of nutritional supplements prescribed, its associated cost and patients knowledge, attitude and practice towards nutraceuticals: A hospital based cross-sectional study in Kavrepalanchok, Nepal. PLoS One [Internet]. 2021 Jun 1 [cited 2024 Nov 19];16(6):e0252538. Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0252538\u003c/li\u003e\n \u003cli\u003eDPCO/NPPA | Department of Pharmaceuticals [Internet]. [cited 2025 Apr 11]. Available from: https://pharma-dept.gov.in/dpconppa\u003c/li\u003e\n \u003cli\u003eSuhrcke M, Alliance OH. Chronic Disease: An Economic Perspective [Internet]. Oxford Health Alliance; 2006. Available from: https://books.google.co.in/books?id=VlFuYgEACAAJ\u003c/li\u003e\n \u003cli\u003eRussell S. Ability to pay for health care: concepts and evidence. Health Policy Plan [Internet]. 1996 Sep 1 [cited 2024 Nov 19];11(3):219\u0026ndash;37. Available from: https://dx.doi.org/10.1093/heapol/11.3.219\u003c/li\u003e\n \u003cli\u003eRussell S. The Economic Burden of Illness for Households in Developing Countries: A Review of Studies Focusing on Malaria, Tuberculosis, and Human Immunodeficiency Virus/Acquired Immunodeficiency Syndrome. 2004 [cited 2024 Nov 18]; Available from: https://www.ncbi.nlm.nih.gov/books/NBK3768/\u003c/li\u003e\n \u003cli\u003eWingfield T, Boccia D, Tovar M, Gavino A, Zevallos K, Montoya R, et al. Defining catastrophic costs and comparing their importance for adverse tuberculosis outcome with multi-drug resistance: a prospective cohort study, Peru. PLoS Med [Internet]. 2014 [cited 2024 Nov 19];11(7). Available from: https://pubmed.ncbi.nlm.nih.gov/25025331/\u003c/li\u003e\n \u003cli\u003eYou X, Kobayashi Y. Determinants of out-of-pocket health expenditure in China: analysis using China Health and Nutrition Survey data. Appl Health Econ Health Policy [Internet]. 2011 [cited 2024 Nov 19];9(1):39\u0026ndash;49. Available from: https://pubmed.ncbi.nlm.nih.gov/21174481/\u003c/li\u003e\n \u003cli\u003eSturm R. The Effects Of Obesity, Smoking, And Drinking On Medical Problems And Costs. https://doi.org/101377/hlthaff212245. 2017 Aug 17;\u003c/li\u003e\n \u003cli\u003eJeon YH, Essue B, Jan S, Wells R, Whitworth JA. Economic hardship associated with managing chronic illness: A qualitative inquiry. BMC Health Serv Res [Internet]. 2009 Oct 9 [cited 2024 Nov 18];9(1):1\u0026ndash;11. Available from: https://bmchealthservres.biomedcentral.com/articles/10.1186/1472-6963-9-182\u003c/li\u003e\n \u003cli\u003eKumar G, Dash P, Patnaik J, Pany G. SOCIOECONOMIC STATUS SCALE-MODIFIED KUPPUSWAMY SCALE FOR THE YEAR 2022. Int J Community Dent [Internet]. 2022 Jun 10 [cited 2024 Nov 18];10(1):1\u0026ndash;6. Available from: https://www.editorialmanager.in/index.php/ijcd/article/view/26\u003c/li\u003e\n \u003cli\u003eMurphy A, Palafox B, Walli-Attaei M, Powell-Jackson T, Rangarajan S, Alhabib KF, et al. The household economic burden of non-communicable diseases in 18 countries. BMJ Glob Heal [Internet]. 2020 Feb 11 [cited 2024 Nov 18];5(2). Available from: https://pubmed.ncbi.nlm.nih.gov/32133191/\u003c/li\u003e\n \u003cli\u003ePallegedara A. Impacts of chronic non-communicable diseases on households\u0026rsquo; out-of-pocket healthcare expenditures in Sri Lanka. Int J Heal Econ Manag [Internet]. 2018 Sep 1 [cited 2024 Nov 18];18(3):301\u0026ndash;19. Available from: https://www.researchgate.net/publication/322368095_Impacts_of_chronic_non-communicable_diseases_on_households\u0026rsquo;_out-of-pocket_healthcare_expenditures_in_Sri_Lanka\u003c/li\u003e\n \u003cli\u003eSharma A, Adiga S, Ashok M. Knowledge, attitude and practices related to dietary supplements and micronutrients in health sciences students. J Clin Diagn Res [Internet]. 2014 [cited 2024 Nov 19];8(8). Available from: https://pubmed.ncbi.nlm.nih.gov/25302213/\u003c/li\u003e\n \u003cli\u003eR N, Rai M, Ravindran A. Awareness And Practices Towards Nutraceuticals Among Medical Practitioners of A Tertiary Care Teaching Hospital in South India - A Pilot Study. IOSR J Dent Med Sci. 2017 May;16(05):12\u0026ndash;6.\u003c/li\u003e\n \u003cli\u003eRonis MJJ, Pedersen KB, Watt J. Adverse Effects of Nutraceuticals and Dietary Supplements. Annu Rev Pharmacol Toxicol [Internet]. 2018 Jan 6 [cited 2024 Nov 19];58:583\u0026ndash;601. Available from: https://pubmed.ncbi.nlm.nih.gov/28992429/\u003c/li\u003e\n \u003cli\u003eTeoh SL, Ngorsuraches S, Lai NM, Bangpan M, Chaiyakunapruk N. Factors affecting consumers\u0026rsquo; decisions on the use of nutraceuticals: a systematic review. Int J Food Sci Nutr [Internet]. 2019 May 19 [cited 2024 Nov 19];70(4):491\u0026ndash;512. Available from: https://pubmed.ncbi.nlm.nih.gov/30634867/\u003c/li\u003e\n \u003cli\u003eGosavi S, Subramanian M, Reddy R, Shet BL. A Study of Prescription Pattern of Neutraceuticals, Knowledge of the Patients and Cost in a Tertiary Care Hospital. J Clin Diagn Res [Internet]. 2016 Apr 1 [cited 2024 Nov 18];10(4):FC01. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC4866122/\u003c/li\u003e\n \u003cli\u003eAlmalki ZS, Alahmari AK, Alqahtani N, Alzarea AI, Alshehri AM, Alruwaybiah AM, et al. Households\u0026rsquo; Direct Economic Burden Associated with Chronic Non-Communicable Diseases in Saudi Arabia. Int J Environ Res Public Heal 2022, Vol 19, Page 9736 [Internet]. 2022 Aug 8 [cited 2024 Nov 18];19(15):9736. Available from: https://www.mdpi.com/1660-4601/19/15/9736/htm\u003c/li\u003e\n \u003cli\u003eChua KP, Lee JM, Conti RM. Out-of-Pocket Spending for Insulin, Diabetes-Related Supplies, and Other Health Care Services Among Privately Insured US Patients With Type 1 Diabetes. JAMA Intern Med [Internet]. 2020 Jul 1 [cited 2024 Nov 18];180(7):1012. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC7265118/\u003c/li\u003e\n \u003cli\u003eMakinen M, Waters H, Rauch M, Almagambetova N, Bitran R, Gilson L, et al. Inequalities in health care use and expenditures: empirical data from eight developing countries and countries in transition. Bull World Health Organ [Internet]. 2000 [cited 2024 Nov 18];78(1):55. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC2560608/\u003c/li\u003e\n \u003cli\u003eNoncommunicable diseases [Internet]. [cited 2024 Nov 18]. Available from: https://www.who.int/news-room/fact-sheets/detail/noncommunicable-diseases\u003c/li\u003e\n \u003cli\u003eXu K, Evans DB, Kawabata K, Zeramdini R, Klavus J, Murray CJL. Household catastrophic health expenditure: a multicountry analysis. Lancet (London, England) [Internet]. 2003 Jul 12 [cited 2024 Nov 19];362(9378):111\u0026ndash;7. Available from: https://pubmed.ncbi.nlm.nih.gov/12867110/\u003c/li\u003e\n \u003cli\u003eAlmalki ZS, Karami NA, Almsoudi IA, Alhasoun RK, Mahdi AT, Alabsi EA, et al. Patient- centered medical home care access among adults with chronic conditions: National Estimates from the medical expenditure panel survey. BMC Health Serv Res [Internet]. 2018 Sep 27 [cited 2024 Nov 18];18(1):1\u0026ndash;11. Available from: https://bmchealthservres.biomedcentral.com/articles/10.1186/s12913-018-3554-3\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 3 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":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cost-effectiveness-and-resource-allocation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cera","sideBox":"Learn more about [Cost Effectiveness and Resource Allocation](http://resource-allocation.biomedcentral.com)","snPcode":"12962","submissionUrl":"https://submission.nature.com/new-submission/12962/3","title":"Cost Effectiveness and Resource Allocation","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Chronic illness, cost analysis, economic impact, nutraceuticals, non-therapeutic drug treatment, prescription, therapeutic drug treatment.","lastPublishedDoi":"10.21203/rs.3.rs-6086835/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6086835/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eObjectives\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe prevalence of chronic diseases is rising globally along with the consumption of nutraceuticals. It is documented that 80% of the deaths due to chronic illnesses occur in low and middle-income countries, including India. In addition, chronic diseases not only affect the patients but also their family income. Besides Southeast Asia is also the fastest-growing market for nutraceuticals with less stringent cost regulation. Hence, this research primarily focuses on the financial impact of the drug treatment for chronic illness, extensively comparing the therapeutic and non-therapeutic drug (nutraceutical) costs.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis was a retrospective, cross-sectional study with a sample size of 7877 prescriptions of medicine outpatient clinic, extracted from the hospital information system after 5 level screening for their inclusion in the study. The cost of drugs prescribed to the patient for chronic illness was calculated per month and its impact on the monthly family income was evaluated. The data analysis was stratified into the cost of therapeutic drug treatment and non-therapeutic drug treatment which was correlated with various chronic diseases and demographic parameters.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eA total of 465 patients were enrolled after screening and a high prescription rate of 88% for non-therapeutic treatment was reported. The total average monthly cost of chronic illness treatment was INR 1879 (22.42 USD), with therapeutic drug treatment of INR 1319 (15.74 USD) and non-therapeutic drug treatment of INR 560 (6.68 USD). Comprising 36% of patients, males spent higher amount on therapeutic drug treatment (INR 1780 or USD 21.26), while women spent higher on non-therapeutic drug treatment (INR 593 or USD 7.08). A catastrophic 11% of patients from \u0026lsquo;lower\u0026rsquo; socioeconomic spent\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;10% of family income on non-therapeutic treatment.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003eOur study highlights the financial strain that chronic illnesses impose on families, emphasizing the need for policymakers to improve access to specialized care and cost capping of nutraceuticals.\u003c/p\u003e","manuscriptTitle":"Prescription Cost Analysis and Economic Impact of Drug Treatment in Patients with Chronic Illness, Attending the Medicine Out-patient Department in a Tertiary Care Hospital at South Delhi","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-17 08:37:22","doi":"10.21203/rs.3.rs-6086835/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Accepted","date":"2025-04-21T20:37:30+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-19T18:06:27+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-15T05:48:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"207135719473947717856568722115865774896","date":"2025-04-12T12:01:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"92048425554647473993712006961560831835","date":"2025-04-12T05:04:08+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-12T02:39:35+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-12T02:35:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cost Effectiveness and Resource Allocation","date":"2025-04-11T05:12:10+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cost-effectiveness-and-resource-allocation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cera","sideBox":"Learn more about [Cost Effectiveness and Resource Allocation](http://resource-allocation.biomedcentral.com)","snPcode":"12962","submissionUrl":"https://submission.nature.com/new-submission/12962/3","title":"Cost Effectiveness and Resource Allocation","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a390b9b9-b0d9-4a92-b583-4ea92c2cf434","owner":[],"postedDate":"April 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-06-23T16:04:11+00:00","versionOfRecord":{"articleIdentity":"rs-6086835","link":"https://doi.org/10.1186/s12962-025-00628-6","journal":{"identity":"cost-effectiveness-and-resource-allocation","isVorOnly":false,"title":"Cost Effectiveness and Resource Allocation"},"publishedOn":"2025-06-20 15:57:06","publishedOnDateReadable":"June 20th, 2025"},"versionCreatedAt":"2025-04-17 08:37:22","video":"","vorDoi":"10.1186/s12962-025-00628-6","vorDoiUrl":"https://doi.org/10.1186/s12962-025-00628-6","workflowStages":[]},"version":"v1","identity":"rs-6086835","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6086835","identity":"rs-6086835","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}