Medicine, medicine, who’s got the medicine? According to the World Health Organization (WHO), 68 percent of the world’s population lacks access to essential medicines. India is no different, with only 3000 public health centres in Karnataka having limited supplies of essential medicines.
Since medicine procurement is a state-level activity in India, in this study, four states have been selected. These are the largest Indian states with the largest populations in India. The chosen states are, Tamil Nadu, Kerala, Odisha, and Punjab. The study focuses on issues that are identified in the procurement process of essential medicines. The medicine procurement data and contract information from the four states are central to the current study.
A normative model is used to study how suppliers would/should respond to orders from multiple states in the current order fulfillment part of the system. The motivation of the study is to capture the reality to provide deeper insights that are viable for implementation from a policy-making perspective, while maintaining the parsimony of the mathematical models.
Essential medicine procurement in the Indian Public health system is undertaken by the state-level medical service corporations (MSC). Some states, like Kerala, follow a centralized system, while others like Punjab. Tamil Nadu and Odisha follow a decentralized system, that is a mix of the two. The following are the issues in state-level medicine procurement:
1. Capacity issues at suppliers:
Pharmaceutical companies have many issues with operational and infrastructural issues such as shortage of power, logistical and raw material procurement challenges. Also, they are unable to make a profit because of the stiff competition in the market.
2. Batching of orders:
Large bulk orders of essential medicines are done in states. The same supplier may supply for other states as well.
3. Penalties and blacklisting by states:
A percentage of the price of the orders is done if essential medicines are delivered on time. If there is repeated delay, the supplier is blacklisted by that state and can’t do business with the state again for a certain fixed time period. Firms are in agreement that this is a harsh move and they tend to lose business.
4. Transportation and inventory costs:
Transportation and inventory costs are important with regard to the supply chains.
To propose policy recommendations, the following situations were studied:
1. Variation in capacity allocation by suppliers:
The non-fulfillment of orders by suppliers due to capacity constraints is a major issue faced by states. Suppliers only allocate a subset of their actual production capacities to government orders in order to be business-viable.
Capacity allocation was done as follows: capacity allocation less than or equal to 30 percent as low, factor between 50 percent to 79 percent as medium, and allocation factor greater than or equal to 80 percent as high.
It was observed that for medium and high allocation factor worked out quite successfully in all four states, but for the low allocation factor it was not very successful.
2. Staggered ordering versus batching:
Staggering was implemented as opposed to batching. It was thought that instead of giving a few bulk orders at once, why not order smaller supplies of essential medicines at regular time intervals? Thus staggering orders was found to be better in terms of delivery results. Timing of the order is crucial. It is suggested that a combination of staggering and batching be done. Given the advantages seen with staggered ordering, successful delivery of essential medicines can be achieved at the intra-state level through the use of framework agreements or umbrella contracts where-in long term contracts for small repeat orders in a given time frame. The government also benefits from lower prices from larger orders through demand aggregation.
3. Penalties and blacklisting:
The penalty structure implemented by the states is based on the start time of the penalty period, and the duration of the penalty period and amount.
States are classified as stricter, when starting the penalty period earlier, like Kerala, or lenient, when starting the penalty period later and imposing fewer fines, like Odisha.
It is found that suppliers prefer strict states over lenient. For example, Kerala over Odisha.
It is suggested that penalties and blacklisting should be done in a gradual manner. Though such a change does not affect the current order fulfillment cycle, it can impact future orders and is crucial.
4. Transportation and inventory costs:
The total transportation cost depends on the distance between the supplier and the state, as well as the standard freight rates.
Proximity to a supplier provides a marginal advantage through improved fill rates and reduced delays for a state. For example, if the suppliers are located in Baddi, Himachal Pradesh, a neighbouring state of Punjab (distance of less than 100 kilometres.), while Tamil Nadu, Odisha, and Kerala are 1500 kilometres away from Baddi, some improvement in the order fulfillment in Punjab is seen.
Some states do prioritize in-state sourcing, but only for limited medicines. But in-state sourcing of essential medicines hardly affects the total price from the supplier. Therefore, locational zoning of suppliers can be undertaken, and suppliers from closer zones should be prioritized for sourcing by states.
Thus from this study it is evident that despite the operational, logistic, and infrastructural challenges which exist in the current system, several measures can be undertaken to considerably ease the system and address medicine shortage.
Increased capacity allocation at suppliers for state orders, staggering of orders at the state level, stricter, but gradual penalties and blacklisting at state level, and sourcing from suppliers closer to the state have been recommended in this study.
Using this study, and upon implementation, the fill rates over all the states was at 53 percent as compared to an average fill rate of 30.95 percent.
There are still some shortcomings in spite of the model used and changes implemented. Several other factors can affect procurement, and can be studied further such as, pricing issues, payment conditions, quality control benchmarks, essential drug list composition, and legal requirements. Conversely, the current model may result in instances of under- or over-filling of orders. Furthermore, penalties and blacklisting are not as common in a commodity focused supply chain. Thus this study leaves future research in this area open.
Dr. Girija Vaidyanathan, former Chief Secretary of Tamil Nadu, appreciated the efforts of the authors, Prof. Vijaya C. Subramanian from the Department of Operations Management, IFMR-GSB, Krea University, and Prof. Rangaraja Sundarraj P. from the Department of Management Studies, IIT Madras, and gave the following statement: “I find this paper both interesting and relevant in the Indian context. It is interesting that the entire research and modeling have been done based on data available in the public domain. The comparison of the drug procurement policies of four different states has thrown up some practical recommendations for improving the process by ensuring increased capacity allocation for government orders, by staggering state level purchases, stricter but gradual penalties for delayed supply and by purchasing from suppliers nearer to the state.
Some of the additional aspects that can be added for future study include the role of packaging and printing which is one of the major causes for delayed supply of drugs for the public system as well as how quality control is implemented in various states and its impact on fill rate and timely supply. For high volume drugs, the licensed capacity of various suppliers and how they are determined may also need to be studied and recommendations made on how they can be optimized.
All in all, it is a very useful piece of research especially for the State Health Departments. It would be very useful to have a virtual discussion with state level health department personnel who are in charge of the drug procurement process to see how they respond to these suggestions.”
Article by Akshay Anantharaman
Here is the original link to the scientific paper: