Frequently asked questions

The global healthcare sector is overburdened for several reasons. In many countries, the population is aging, and requires more medical care. At the same time, there is an overall shortage of physicians. In the Netherlands, a general practitioner (GP) or family doctor is the “gatekeeper” for almost all medical care, expanding the demand for their services. However, people may seek acute healthcare when their GP is unavailable, sometimes in non-urgent cases. Medvice aims to reduce this burden in two ways:

1) By providing patients with the accurate, personalized, always-available medical information they need, calming their concerns and ensuring that acute healthcare is only sought out when it is medically necessary.

2) By supporting physicians, clinics, and urgent care centres with improved patient flow and efficiency. The Medvice MIA Suite improves data collection and management, saving staff time, while Medvice.Ai helps screen for alarming symptoms and reach a differential diagnosis more quickly.

Medical reasoning is necessary when finding the proper diagnosis or carrying out a medical decision. The basis for medical reasoning is mostly associative, where risk factors such as lifestyle and epidemiology play an important role. In practice, patients rarely present the full scale of classical symptoms (“textbook symptoms”), and may present with atypical symptoms. Often, medical history or symptom information is simply incomplete. This puts physicians at risk of basing their diagnosis and treatment plans on incomplete or unclear data.

Using Machine Learning algorithms trained by real patient data, Medvice.Ai is able to predict a list of possible diagnoses (“differential diagnosis”) based on even incomplete information or on an atypical combination of symptoms. In the long run, using Machine Learning technology can function as a proper screening tool to pick up clinical associations missed by the GP.

Current existing triage protocols, like the NTS (Dutch) or MTS (UK) presently give an indication about the level of urgency of a certain physical problem. Unfortunately, these standards only prioritize on the basis of urgency, but do not gather any other necessary medical information which could later be useful for the consulting physician. Medvice not only integrates these validated triage standards, but also digitally and interactively initiates the general part of the medical history taking process. This saves time for the patient, since they can complete the information while they are waiting, and saves time for physicians and clinical staff, since they don’t need to spend crucial time with the patient simply gathering and recording this data.

Machine-learning systems rely on training data to increase their accuracy. In some sectors, such as the automotive sector, relevant datasets are readily available as they are being generated by automotive companies themselves. However, the healthcare sector relies on either third party, unclean and free text data, or “textbook” datasets (also called synthetic data). Accurate data is crucial for proper analysis, yet these datasets are not easy nor cheap to obtain.

Medvice is a pioneer in medical dataset creation, engineering our medical history taking software (MIA) so that, with patient consent, we can securely and pseudonymously store standardized, structured, labeled, and clean datasets. This clean data will be used to train the Medvice.AI ML systems and for further analysis. There is no limit to uses around this form of data gathering, and increasing the rate of data acquisition during the upscaling stage has the potential to improve differential diagnoses and upgrade the world of healthcare.

Medvice offers unparalleled medical software and services. We offer the only suite of services designed to meet the needs of patients, doctors, and clinics with our simple, intuitive data gathering and comprehensive set of in-clinic and mobile applications. Being founded by conscientious doctors, we adhere to the strictest medical standards. As such, we use next-generation technology to keep medical data accessible, controlled, and secure. Our machine learning algorithm improves constantly, enriched by anonymized, voluntary data shared by our patients and validated by physicians.

Medvice is uniquely designed to relieve the strain on our healthcare systems by:

• Providing patients with the accurate, affordable medical information they need to seek medical care only when necessary, and enjoy peace of mind about their healthcare decisions
• Streamlining information gathering for physicians and assisting them in more quickly arriving at a diagnosis and at treatment options
• Reducing waiting times and workload pressure in clinics and urgent care centres by expediting patient flow and improving data collection.

As a patient using the Medvice Interactive Anamnesis, or MIA, you will be asked to share certain data after you have filled out the details of your medical complaint. The data is only shared after your informed consent. This data includes purely medical information; no names or addresses are included.

The General Data Protection Regulation (GDPR) explicitly encourages organisations to consider pseudonymisation as a security measure, which provides advantages. It can allow organisations to satisfy their obligations of "privacy by design" and "privacy by default" and it may be used to justify processing that would otherwise be deemed "incompatible" with the purposes for which the data were originally collected.

As it is nearly impossible to ensure 100% real anonymous data, Medvice follows the latest GDPR guidelines and works with pseudonymous data. This means that data can be amended so that no individuals can be identified from the data (whether directly or indirectly) without a "key" that allows the data to be re-identified. A good example of pseudonymous data is coded data sets used in clinical trials. With Medvice, pseudonymous data is coded medical datasets obtained from the patient after using the MIA app or stand. Pseudonymous data are still treated as personal data because they enable the identification of individuals (albeit via a key). However, provided that the "key" that enables re-identification of individuals is kept separate and secure, the risks associated with pseudonymous data are much lower. In this way, we take two essential steps to minimize any risk against your personal security.