How an AI Tool is Quietly Fixing Prescription Errors

A free flow of over-the-counter medicines at pharmacy stores in India often complicates medical cases. Painkillers, antibiotics and antihistamines are sold without any questions. In a country where self-medication is a norm, this practice often leads to adverse drug reactions, particularly when mixed with prescriptions from qualified doctors. 

Amid such a scenario, Artificial Intelligence (AI) is beginning to tackle one of clinical medicine’s most persistent dangers – drug interactions. This happens when two or more prescribed medications create a harmful or even fatal response in a patient’s body. 

At Amala Institute of Medical Sciences in Thrissur, Kerala, an AI-driven initiative called SafeRx is helping doctors write prescriptions. The hospital has partnered with Bengaluru-based healthtech company DoctorAssist.ai to deploy SafeRx, an intelligent drug interaction checker and clinical decision support tool for doctors.

“Most drug interactions are unintentional,” said Dr V K  Prathibha, head of pharmacology at Amala. “A patient might be under a cardiologist, nephrologist and neurologist simultaneously, each giving separate prescriptions. If one doctor doesn’t know what the other has prescribed, reactions can happen. And if the patient forgets to carry their older records, it gets riskier.”

SafeRx helps mitigate this risk. 

Flagging Potential Risks

While Amala already has a pharmacovigilance centre that tracks adverse reactions, SafeRx enables doctors to flag possible drug interactions in real-time, before any harm is done. Integrated with the hospital’s Electronic Medical Records (EMRs), SafeRx uses AI to cross-check prescriptions with up-to-date drug guidelines and known contraindications.

When a healthcare provider prescribes medication digitally through the EMR, SafeRx can automatically review the prescription in real time, cross-referencing it with the patient’s current medication, medical history and known allergies. The tool identifies any potential drug interactions, contraindications or dosage issues and instantly alerts the doctor.

The system evaluates patients’ age, gender, known medical conditions and runs checks across drug databases to alert the physician about possible harmful combinations or excessive antibiotic use. It also supports antimicrobial stewardship by warning when an antibiotic from the “reserve” category is prescribed without justification or when therapy exceeds the recommended duration. 

“Earlier, we would track adverse reactions after they occurred,” Dr Prathibha explains. “But AI is helping us flag risky combinations beforehand, especially with antibiotics and high-risk drugs.”

Father Antony Mannummel, associate director at the Amala Institute, drew an analogy between SafeRx and the stethoscope. Anyone can use one, but only a doctor knows what they’re listening for, he said, concluding: “This is not about replacing doctors, it’s about helping them make more informed decisions.” 

Data Privacy and Sanitising

The intelligence behind SafeRx is built using open-source large language models like LLaMA 3.5, Mistral and Phalcon, said Abilash Raghunandanan, founder and CTO of DoctorAssist.ai.

“We’ve fine-tuned the model based on geography-specific usage patterns,” he said. “In Kerala, doctors might prefer certain drugs over others. Hospitals have their own standard protocols. SafeRx understands that context.”

While many tech-health platforms raise red flags for privacy, Raghunandanan insisted that data is stored on their own servers, ensuring no third-party access.

“The model doesn’t require identifiable information,” he said, adding, “The data is fully sanitised before training. Only age, sex and medical condition are used.”

This aligns with India’s National Digital Health Mission (NDHM) guidelines under the Ayushman Bharat Digital Mission (ABDM), which call for consent-based, secure health data systems (ABDM Health Data Policy).

Other similar interventions backed by AI are improving medical practice across the world. Another AI-powered medical knowledge platform, Pathway is a fully integrated drug reference and drug interaction checker, where clinicians can access comprehensive medication information for over 2,000 drugs and screen for interactions within the same interface they already use for clinical guidance.

In Canada, the AI platform MedSafer has been deployed in senior care settings to identify potentially inappropriate medications (PIMs), reducing medication overload and preventing adverse events. 

‘As Good As The Data It Receives’

In India, the risk from drug interactions is not hypothetical. A 2016 study found that up to 12% of hospital admissions in India were drug-related, with adverse drug reactions (ADRs) being a major contributor. 

This is further complicated by the country’s fragmented healthcare delivery, where patients often visit multiple specialists without a centralised EMR. In this scenario, AI-backed decision-support tools can stitch together the gaps in patient care.

“It’s about tech with real value addition,” Raghunandanan reiterated. “We’re not just digitising healthcare, we’re making it safer for the patients in all possible ways.”

Despite its promise, AI in medicine is not without its critics. Some doctors remain wary of automation intruding into clinical judgement. Others worry about the lack of formal AI regulation in India’s health sector, beyond the broad strokes of the National Digital Health Mission (NDHM).

Moreover, smaller clinics lacking robust digital infrastructure may find it challenging to adopt AI tools effectively. “AI is only as good as the data it receives,” cautioned Dr Prathibha. “When patient records are incomplete or poorly maintained, even the most advanced algorithms can fall short.”

The post How an AI Tool is Quietly Fixing Prescription Errors appeared first on Analytics India Magazine.

Generated by RSStT. The copyright belongs to the original author.

Source