India has a progressive shortage of 600,000 doctors and two million nurses. For a country that's a billion strong (and counting), this is not sufficient. Currently, we have a lamentable doctor-patient ratio of 1:1457, and nurse-patient of 1:475 ratio. With such a massive workload, doctors don't have more than 2-5 minutes per patient - considered just enough to execute a basic triage and issue a prescription. Unlike family general physicians who would be acutely aware of one's medical history, doctors these days are unable to spend time understanding thorough clinical history of patients. This leads to medical errors, misdiagnosis and needless emotional strain. 

One of the most crucial aspects of patient diagnosis is clinical history, sometimes given credence even more than a physical exam and thorough lab investigations. When comprehensively captured, it leads to a faster, accurate and well-informed diagnosis in almost 80% of medical cases, and can help in ensuring evidence-based recommendations for lab investigations. In resource-constrained countries like ours where majority cannot afford expensive medical tests, capturing detailed clinical history becomes paramount. 

Bangalore based startup HealthCloudAI, founded by Dr. Preeti Bhargava & Nitesh Shroff, is building Point-of-Care assistive AI solutions that shares a physician's workload by enabling clinical assistants to capture patient’s comprehensive history before consultation, and generate clinical insights based on the patient's history to facilitate faster and more accurate diagnosis. HealthCloudAI is building Arintra, the first assistive AI solution that enables the doctor’s assistants to capture patient’s comprehensive and chronological medical history, which include chief complaints, present symptoms, risk factors, medication history, family history, drug allergies, past surgeries etc, prior to medical consultation. A physician assistant or paramedic uses Arintra at point-of-care or remotely to utilize a patient's wait time to capture comprehensive and precise clinical history. Arintra is akin to a resident doctor conducting a medical interview. It uses medical AI to intelligently dive deep into a patient's history based on chief complaints and previous responses. This profile is presented to the doctor remotely or when a patient enters the doctor's chamber. Arintra ensures no critical medical information about the patient is missed. It presents the patient’s medical history to the doctors in a visually intuitive format that they can easily comprehend and interpret. This facilitates faster and more accurate diagnosis, patient screening and triage leading to better patient outcome.

An AI-Driven Personal Health Record 

By maximising the capacity of doctors by shifting some of their efforts on a paramedic, the app enables a doctor to engage with a patient meaningfully, allowing them to provide better quality care to a higher number of patients. Being armed with an exhaustive medical history of patients with better documentation and presentation, doctors are in control of improving the speed and accuracy of diagnosis and treatment. Arintra also helps reduce the doctors’ workload by presenting an accurate aggregated medical history to the doctor when patients appear for a follow up. Not only doctors, patients too benefit as Arintra will store and maintain their medical history, doctor generated prescriptions and treatment plans over several visits which will help track and monitor their health over a period of time. Their Arintra profile will effectively function as a Personal Health Record (PHR) and provide a continuum of care. Assistants and paramedics benefit because Arintra upskills them to provide better patient care at a fraction of cost (in terms of both time and money) of traditional methods such as extensive medical training.

Other benefits of working with Arintra include zero doctor-effort NABH compliant documentation, upskilling medical assistants at no additional cost, generating PHR for patients aggregated over multiple visits, proprietary medical AI models trained to address diseases specific to India and zero cost deployment with no extra equipment.

Some of the key features of Arintra include: 

• Clinical insights such as provisional diagnosis, lab recommendations (optimized for cost and convenience of patients), and drug interactions.
• Patient triage in order to prioritize them for being seen by the doctor
• Recommending the right specialization of the doctor to patients based on their chief complaints and symptoms (in a hospital setup)
• Insights into patients’ medical conditions based on patient’s cumulative clinical history - this will help improve patient outcomes
• Insights on epidemiology and healthcare statistics of different parts of the country, which will enable state agencies to formulate appropriate policies

An India-First Product With Local Data: 

While there are some companies in USA and Europe with products similar to Arintra, like Ada, Babylon Health, Buoy Health and Suki, however, they work with datasets originating from these regions and tuned to health challenges commonly seen there such as call center triages and clinical documentation for medical insurance claims. Arintra is a Point of Care Assistive AI solution trained on Indian healthcare data and is more attuned to Indian patients. 

The company is currently running more than 30 pilots in different hospitals, SHCOs and clinics across Karnataka, Andhra Pradesh, Telangana, Gujarat, Tamil Nadu, Kerala and Maharashtra covering multiple specializations, and has helped more than 8,500 patients. Doctors using Arintra include a pulmonologist at Apollo Hospital in Hyderabad, two cardiologists in Rajkot and Bangalor, two neurologists in Hyderabad and Hosur, one rheumatologist in Hyderabad and physician in Aurangabad. in addition, Healthcloud AI is also a technology partner to organizations such as YouSee and Trinity Care Foundation, with its solution deployed at six medical camps. 

The response from the medical community has been very encouraging as this solution helps save time, provided a detailed patient history and could prove to be a viable AI-guided option in establishing a Personal Health Records (PHR) platform.