Prescription Cost Dynamics in Chronic Disease Management: The Role of PMBJP-Scheme in Enhancing Affordability in India
Author(s)
Kavya Surimilli1, Hemanth K. Nambari, PharmD2, Kavita Kachroo, MBA, MHA2, Jitendra Sharma, Ph.D2;
1Kalam Institute of Health Technology ( KIHT), Senior Fellow, Visakhapatnam, India, 2Kalam Institute of Health Technology, Visakhapatnam, India
1Kalam Institute of Health Technology ( KIHT), Senior Fellow, Visakhapatnam, India, 2Kalam Institute of Health Technology, Visakhapatnam, India
OBJECTIVES: The main objective of this study is to assess the cost dynamics of prescription medications in chronic disease management by comparing the out-of-pocket expenditure between medicines available in Jan Aushadhi and Tertiary-care corporate hospitals by assessing monthly prescription cost.
METHODS: We conducted a cross-sectional study for 98 prescriptions to compare the prescription cost burden, where paired t-test used to assess the statistical significance of cost difference and ANOVA was conducted to examine the cost variation across different age groups and clinical departments. Multiple linear regression was employed to identify prescription cost. Analysis performed by using SPSS software.
RESULTS: The mean difference per 30-day prescription between two groups is ₹1,616.08 (95% CI: ₹1,338.45-₹1,893.71). On average, Jan Aushadhi medicines were 78.11% low priced than their branded counterparts (95% CI: 75.23%-80.99%). This difference was statistically significant (paired t-test: t (96)=11.54, p<0.001) with a large effect size (Cohen's d=1.17). According to department, average savings per 30-day prescription in cardiology is 81.62%, 80.36% in General medicine and 77.74% In neurology. ANOVA showed no significant difference in savings percentage across departments (F (3, 93)= 1.32, p=0.273). ANOVA for age related 30-day prescription cost indicated a significant difference in branded prices across age groups (F(3,93)= 3.27, p=0.025). Post-hoc analysis (Tukey HSD) revealed a significant difference between the 18-30 and 66+ age groups (p=0.018). Multiple linear regression analysis revealed that age and being prescribed medications from the Cardiology department were significant predictors of higher prescription costs (R²=0.142, F(5, 91)=3.01, p=0.014).
CONCLUSIONS: PMBJY-scheme seen as cost-effective alternative for better healthcare accessibility and medication adherence in chronic disease management and this study plays an important role in healthcare policy. The absence of intermediaries, elimination of marketing expenses, and a low-profit margin, all while maintaining high-quality standards certified by WHO-GMP, allow Jan Aushadhi medicines to remain affordable for the public without compromising on quality.
METHODS: We conducted a cross-sectional study for 98 prescriptions to compare the prescription cost burden, where paired t-test used to assess the statistical significance of cost difference and ANOVA was conducted to examine the cost variation across different age groups and clinical departments. Multiple linear regression was employed to identify prescription cost. Analysis performed by using SPSS software.
RESULTS: The mean difference per 30-day prescription between two groups is ₹1,616.08 (95% CI: ₹1,338.45-₹1,893.71). On average, Jan Aushadhi medicines were 78.11% low priced than their branded counterparts (95% CI: 75.23%-80.99%). This difference was statistically significant (paired t-test: t (96)=11.54, p<0.001) with a large effect size (Cohen's d=1.17). According to department, average savings per 30-day prescription in cardiology is 81.62%, 80.36% in General medicine and 77.74% In neurology. ANOVA showed no significant difference in savings percentage across departments (F (3, 93)= 1.32, p=0.273). ANOVA for age related 30-day prescription cost indicated a significant difference in branded prices across age groups (F(3,93)= 3.27, p=0.025). Post-hoc analysis (Tukey HSD) revealed a significant difference between the 18-30 and 66+ age groups (p=0.018). Multiple linear regression analysis revealed that age and being prescribed medications from the Cardiology department were significant predictors of higher prescription costs (R²=0.142, F(5, 91)=3.01, p=0.014).
CONCLUSIONS: PMBJY-scheme seen as cost-effective alternative for better healthcare accessibility and medication adherence in chronic disease management and this study plays an important role in healthcare policy. The absence of intermediaries, elimination of marketing expenses, and a low-profit margin, all while maintaining high-quality standards certified by WHO-GMP, allow Jan Aushadhi medicines to remain affordable for the public without compromising on quality.
Conference/Value in Health Info
2025-05, ISPOR 2025, Montréal, Quebec, CA
Value in Health, Volume 28, Issue S1
Code
EE55
Topic
Economic Evaluation
Topic Subcategory
Budget Impact Analysis, Cost/Cost of Illness/Resource Use Studies, Value of Information
Disease
SDC: Cardiovascular Disorders (including MI, Stroke, Circulatory), SDC: Diabetes/Endocrine/Metabolic Disorders (including obesity), SDC: Geriatrics, SDC: Neurological Disorders, STA: Biologics & Biosimilars