Introduction:
In India’s healthcare system, a single medical prescription can unlock a universe of confusion. For instance, a doctor prescribing ‘atorvastatin in the form of Atorvastatin 10mg’, a generic molecule, can lead to a patient being confused as to whether they should purchase the units of medicine: Ator, Lipitor, Storvas, or a dozen of the other options.
This situation presents the single absolute problem for Indian health tech product managers and developers. How should a single generic drug and its numerous brand variations be displayed in an efficiently constructed e-pharmacy, a clinic, or an app?
The answer, again, is not in the code, but rather in the data. A learning system that seeks to generate trust and confidence should base its foundation on a generic name and brand name user experience structure which is robust. This is a critical UX gap and can only be fulfilled with an Indian Drug Database.
The Great Indian Divide: Understanding the Generic vs. Brand Medicine Landscape
The UX cannot be solved without comprehending the problem. The divide posed by Generic vs Brand Medicine in India is a problem unique to the nation.
- Generic Name (Molecule): This is the active component of the drug which may be, “Paracetamol” or “Metformin”. This is the technical term that is assigned to the drug itself.
- Brand Name (Trade Name): This is the name that the company that manufactures the drug assigns to it, for instance “Crocin” for Paracetamol and “Glycomet” for Metformin.
There are many pharmaceutical companies in India that produce the same generic molecules but under different brand names and with a large variation in price. The government encourages generic prescription to and the Jan Aushadhi store, but it is a mixed bag of prescription habits. Physicians may write prescriptions that include generic medications, brand medications, or a mixture of the two.
This poses problems for developers of the platform. The search intent of the user is obscure. A patient may search for “Crocin” while a physician searches for “Paracetamol”. It is your platforms job to discern that both users are talking about the same thing and provide all the relevant options in an organized manner.
The User Experience (UX) Catastrophe: When Databases Fail
There is no doubt that without a strong, relationally mapped database, the user experience of your platform is destined to fail. The resultant failure from this has a number of outcomes, all of which lead to user frustration and the decreasing of trust that the user has in the platform.
Scenario 1: Absence of E-Pharmacy Search Capability
Upon typing “Dolo 650,” the user is only presented with the option “Dolo 650.” Your platform fails to educate the user that “Paracetamol 650mg” is the active ingredient of this “Dolo 650” brand and that there 15 others, available, and possibly cheaper, alternatives.
Result: Losing the most cost-effective alternate fulfilment option. Your platform is deemed to having ‘tiny’ and worse ‘hidden’ inventory of substitutes. This is a grave shortcoming in the Drug Database UX in India.
Scenario 2: The Pharmacist’s Inventory System Horror
Among the records in a pharmacy that uses your inventory system, a doctor’s prescription that states “Telma 40” as the brand name is being processed. The brand “Telma 40” is currently out of stock. The pharmacist has a mental model that the generic is “Telmisartan 40mg” which they have a stock of 5 other brands available; yet, due to a low quality ‘Medicine Dataset of India’ the pharmacist is incapable of sufficient relational searches. The system forces the pharmacist to complete the task of sifting through the stock manually, only to be met with disappointment.
Result: The endpoints of your software are misaligned, which leads to inefficient workflows and compromised service. The pharmacists’ databases and inventory records are bound to be frustrated.
Scenario 3: Developer’s Map Data Issues
As a developer, you try to build this logic yourself. You construct an online list of all the names of medicines in an excel document. You figure out the data is rubbish:
- ‘Paracetamol’ is also known as ‘Acetaminophen’
- Strengths are inconsistent: 500 mg, 500mg, 0.5g.
- Brand to molecule mapping is either non-existent or grossly incorrect.
The Result: You waste months of engineering time spent on data cleansing, which is entirely unrelated to your focus product. Data is still buggy, and information is always outdated the moment a search is launched.
Building the Bridge: How a Structured Medicine Dataset of India Solves UX
A Dataset of Medicines of India which is professionally done and structured is not merely a list, but a multifaceted complex relational database crafted to address the discipline’s primary pain points. It serves as the user experience ‘single source of truth’ the under serves.
The Core: Mapping Brand names to Molecules
The primary “one-to-many” mapping is a basic, pivotal high-quality feature of the Medicines Database of India. Expert database providers such as Data Requisite have primary keys for the generic molecule, i.e., MOLECULE_ID_1234 = “Atorvastatin 10mg” and maps it to every single brand name available in the market.
The foundational rudiments for optimal UX experience stems from this clean, relational architecture. It emphasizes the platform’s comprehension of the relationship whereby Crocin, Calpol and Dolo are grouped under the parent “Paracetamol.”
Powering Intelligent Search and Discovery
Having such a mapping enables the platform to perform sophisticated searches.
- A user searches “Paracetamol 500mg” (Generic): Instead of a generic entry, the platform displays a clean, grouped results page:
- “Showing results for Paracetamol 500mg”
- Generic Option: Jan Aushadhi Paracetamol 500mg (Price: ₹X)
- Popular Brands: Crocin (Price: ₹Y), Calpol (Price: ₹Z)
- [View all 25 brands]
- A user searches “Crocin 500mg” (Brand): The result is a lot richer where the platform:
- Displays the product page for “Crocin 500mg”.
- Super importantly, it’s appended with: “Contains Paracetamol 500mg. See 24 other brands with the same composition.”
This data-driven enhancement shifts the perception of the platform from a mere catalogue to an informative health companion.
Enabling Trustworthy Generic Substitution
This is the most critical UX factor for the Indian market. Accurate database is the confidence the platform needs to make substitution suggestions.
Picture the user flow:
- A user adds “Lipitor 10mg” (a relatively expensive brand) to the cart.
- Popup: “Claim a 70% discount! Purchase the same composition (Atorvastatin 10mg) under the name ‘Storvas 10mg’ for the price of ₹XX.”
- The platform confirms therapeutic equivalence of both products by displaying the generic name, strength, and manufacturer for both products, side-by-side.
This “generic substitution” is the single greatest method for establishing and maintaining user trust for the platform. It shows that the user is prioritized and that the platform is transparent. Access to a real-time, comprehensive list of Indian medicines containing brand names and their corresponding generic compositions is needed to perform these actions.
Beyond The Name: The Essential Metrics Your Database Should Feature
An effective and reliable Indian Drug Database should also incorporate critical parameters other than names. The strength of a healthtech platform stems from the depth of the dataset which outlines the integrated functionalities. The system will fail if it is constructed from the superficial and shallow list of the names of medicines from a simple database.
For better comprehension, consider the following:
- Precise Composition: A composition should never be referred to as the simple naming of individual ingredients. It should be “Paracetamol 500mg + Caffeine 30mg”
- Manufacturer: This is a key trust signal for users (e.g. “Cipla,” “Sun Pharma.”)
- Pack Size / SKU: For the more user-friendly Stripe of 10, Stripe of 15, and Bottle 60ml,.
- Updated MRP: Medicine prices change. An active price which is obsolete is a dread in e pharmacy. It results in cart abandonment and numerous complaints.
- High Quality images: A user experience confidence issue, duplicates and correct products, is the box and strip images, which should be visible and high quality, and both.
The complete, clean, and constantly updated Indian Medicine Data is the true backbone of a professional healthtech application.
The Implementation: API vs Excel – Which One Would You Prefer
Having made the decision of sourcing a professional database, there are two main implementation routes.
- The Excel / CSV Data Dump
Data Requisite and other providers typically provide the complete Medicine dataset of India as a downloadable file (Ex. Excel, CSV, SQL).
- Pros: Ideal for the first bulk upload, to fill in an internal inventory system, or to analyse data. It simplifies acquiring the relevant dataset because it is all in one document.
- Cons: You are in charge of manually importing the dataset. This includes keeping the data current (new drugs, MRP changes) changes, and so, it can be exhaustive.
- The Medicine Database API
This is the sophisticated, expandable answer to any user interconnected system that is live. The Indian medicine database API allows fluid interaction with the data.
- Benefits:
Current Information: Prices, launches, and changes in composition data are updated in real-time.
Predictive Text: Easily implement a search bar auto-suggest feature (“As you type…”).
Minimalist: You are serviced in a queried manner. There is no need, therefore, to keep a large multi-gigabyte database.
- Drawbacks: More implementation and development time is needed, but the accuracy and scalability are worth the time in the long run.
For most electronic pharmacies and digital prescription platforms, a hybrid model works best: a one-time bulk import using an all-medications list excel to set up the initial catalogue and then integrating a real-time searchable Medicine database API for continuous updates.
Conclusion:
The challenge every pharmacy in India battling generic vs brand medicine is not a challenge at all. It is, in fact, a data challenge and one that results in a deficit in UX.
Trying to “wing it” using incomplete data, scraped data, and even manually curated data is a false economy. The engineering hours, the number of complaints from users and the user’s lost trust is worth the cost of a professionally curated useful database.
A complex medicine database such as the one offered by Data Requisite is not simply expensive line-item data. For any digital healthcare platform in India, this is the base foundational investment. It is the centrepiece of the transformation of an India generic and brand clutter into an effortless and trustworthy user experience. Do not let a lack of data create a gap in your user experience.
Also Read: How Small Healthcare Startups Can Benefit from an Indian Medicine Database
