Web-Service for Pharmacists: How Data Science Can Help Pharmacists with Customer Care
Tags: Artificial Intelligence, Chatbots, Healthcare, Pharmaceutical, Data Science

People are known to shrink from bureaucratic procedures and get intimidated by the official hospital — or even GP office settings. In many cases, when they seek immediate relief, they go directly to local pharmacies where pharmacists face the need to offer prompt treatment based solely on described complaints. To reinforce the connection between a pharmacy and a patient, we created a system consisting of a pharmacist-oriented web-service and a patient bot service that are connected to a shared database.

Inna Ageeva, CEO at Sciforce, contemplates about the potential impact of the project on the pharmacy-level healthcare:

“In many countries people, when getting ill, go to pharmacies to seek for help. Pharmacists have to take decisions and to help their customers based on the described complains. Our project helps them use country-specific protocols via a web service to better understand the customer’s needs and take appropriate decisions. This product aims to improve health care services at the level of pharmacies and in might be of a big social impact for the countries with limited access to healthcare services”

Pharmacist’s web-service

The web service is based on the digitalized clinical practical guidelines for pharmacists. The database was populated from a variety of sources. For the Ukraine-based prototype, we collected information on medication and recommendations from pharmaceutical protocols approved by the Ministry of Healthcare of Ukraine. Then, we processed international guidelines and extracted information to an intermediate table. Then, we checked whether the medications are registered in Ukraine and whether they are the OTC drugs. We developed convenient algorithms to define symptom treatment and at present our web-service covers 15 symptoms of complete surveys, including online checking of life-threatening conditions.

From the user side, it requires several steps to obtain a recommendation. At first, a pharmacist chooses a symptom and fills in a questionnaire about life-threatening conditions. In case such condition is detected, a message appears suggesting that the patient should address a physician. In other cases, the pharmacist is redirected to the page to determine the symptomatic pharmacotherapy. After the patient’s interview, the system displays a result.

The result consists of several fields that might include patient state or a recommendation to contact a doctor, as well as recommended therapeutic groups and medications from each group and pharmaceutical care messages. Based on the results, a pharmacist can offer a better evidence-based solution, recommend the patient further examination at a healthcare facility, save the results as a medication history, or send a report on adverse effects.

Bot service for patients

The patient bot service we developed is a supplementary service connected to the pharmacist’s web-service that provides patients with information on their medication, including methods of administration and possible interactions. The aim of the service is to help patients with drug adherence and establish a connection between the patient and the pharmacist to enable further explanation and feedback. To get the information for online pharmaceutical care by a bot service, we executed a parsing of the ninth issue of Ukraine’s State Drug Formulary.

How it works

The under-the-hood the system is a multi-component. As a pharmacist fills in the online-survey based on the user’s complaints, the requests are sent to a back-end following by queries to a database to extract the information and record a user session. After that, a patient connects to the bot and inputs the resulting medication to obtain the basic info, causing next requests and queries to the same database.Technologically, we rely on Python and Django framework, and the relational database is developed with PostgreSQL.

According to Olha Marushchak, the author of the project, it is the strong connection between IT and pharmacy that made the project stand out among other outstanding ideas:

“We were the only one to present work that addresses pharmaceutical issues and the only one to work in the field of Information Technology. Most research was done on laboratory animals, especially in endocrinology and neurobiology. There was another girl from Odessa who had very strong statistics, but she did not present it as Data Science. I hope that with our project we raised Ukraine’s rating, showed that we have progressive ideas. We talked about the e-health system and about the medical reform and that our web-service can become a part of the nationwide reforms. We see that our project gets traction, so we plan to work harder and improve it and probably to publish a scientific paper — there is a good chance that it will be accepted by the academia.”

Viktor Kolchenko, who is responsible for the whole technical side of the project, also shares his impressions on being a software developer amid medical professionals: