An interview with Diagnostic Match who want to help family doctors to see hidden HIV+ patients and came up with an idea to make a decision-support tool for family doctors to detect hidden HIV+ patients with automatic HIV indicator disease algorithms. The Diagnostic Match algorithms analyse patient's health data and display reminders for a doctor to make a test if the patient is in the at-risk group.
Could you tell us a little about Diagnostic Match? The individuals behind the company?
The HIV epidemic shows no signs of easing in Estonia – with 24 new cases per 100,000 population each year, Estonia is first in Europe in HIV incidence rates. It is estimated that more than 2.3 million people are living with HIV in Europe.
But 1 in 3 doesn't know that they are infected and therefore enter HIV care too late. Diagnostic Match initiative was established because of the epidemic situation in Estonia and in Europe.
In May 2016, the head of the Estonia Family Doctors Association Diana Ingerainen and two IT experts Grete Kikas and Kristjan Krass got together and decided to participate in HIVdigital competition that was focusing on finding digital health solutions for HIV patients and their medical team. During the analysing phase we understood that existing IT solutions in Estonia are institution based and doctor's speciality centred or even document centred. For example, to get the patient's "whole picture of diagnosis" doctors must read summaries of the previous case histories and search for diagnosis that could be defined there - it is just too time consuming! And it's definitely not an Estonian specific problem.
Statistics show that Estonian family doctors perform only 5% of the HIV tests. The low level of tests isn't because of the lack of knowledge about the HIV epidemic or that patients never visited their family doctors. But the problem is that doctors don't know which patients potentially need HIV testing. The clinical guidelines for HIV testing are stating that HIV tests has to be recommended when the patient has the HIV indicator disease diagnosed. Example of HIV indicator diseases are sexually transmitted infections, herpes zoster or Hepatitis B or C. But there's around 400 different ICD-10 codes that can be associated with HIV and to know them all and more over to see them all, is practically called "mission impossible".
We wanted to help family doctors to see hidden HIV+ patients and came up with an idea to make a decision support tool for family doctors to detect hidden HIV+ patients with automatic HIV indicator disease algorithms. Our algorithms are analysing patient's health data and displaying reminders for a doctor to make a test if the patient is in the risk group.
What is Diagnostic Match’s mission?
The overall mission for Diagnostic Match is to detect hidden HIV+ patients as early as possible in the course of their infection. This will help to improve their lives and increase transmission rates.
With a disease such as HIV, early discovery can dramatically affect the outcome for a patient. Was this a motivating factor behind Diagnostic Match?
Yes, absolutely! By lowering the level of virus in the body, earlier diagnosis and treatment helps people with HIV live healthier and longer lives. Furthermore, it will help to lower the chances of transmitting the disease to others as well. Earlier diagnosis and treatment has so many benefits for patients with HIV and this is why it should be a key public health strategy. Public health strategies need new and innovative approaches for detecting hidden HIV+ patients and finding them using indicator disease algorithms, is definitely one of the novel and evidence-based approach that should be considered.
Diagnostic Match is involved in the discovery of HIV+ patients through connected ‘indicator’ diseases.
How does Diagnostic Match’s automated algorithm work? Both in terms of sourcing patient information and then subsequently indicating potential HIV+ patients.
Our solution is a digital decision support platform that helps to find HIV-positive patients through indicator diseases. The system analysis and looks for diseases that are co-morbid with HIV, such as hepatitis B and C, herpes zoster, tuberculosis and many others, and helps general practitioners to make a decision to whom they need to recommend HIV testing. Our solution is fully integrateble into already existing medical softwares and our algorithms are based on medical guidelines and validated by the medical professionals.
At what stage of development is Diagnostic Match, and at what stage can we expect it to be used by GP’s in Estonia and the rest of Europe and the world?
At the moment, a solution is being developed for the Estonian market, but the great amount of indicator diseases are overlapping from country to country. We started with primary care and GPs, but we’ve got to the point that there’s an actual demand for the product from other healthcare workers and specialities as well. We think that by the end it doesn't matter where and when the patient enters care - is it primary care or secondary care. Whenever a person has dealings with the healthcare system, the given doctor, nurse, occupational health physician, or gynaecologist should already see a notification if a patient has been diagnosed with specific indicator conditions and the treatment guidelines recommend that HIV testing be considered. In the future, we have plans to develop algorithms for foreign markets as well.
Are there any plans to branch out beyond HIV+ and use Diagnostic Match’s automated algorithm to match indicator health problems to other diseases and medical conditions?
Yes, soon we are trying to focus on other chronic diseases as well such as diabetes, hypertension or COPD.
What is coming up in 2017 and beyond for Diagnostic Match?
We have plans to expand our platform to other diseases and secondary care.
Could you tell us any insights into the wider Digital Health industry within Estonia?
Estonians tend to say that they are "front-runners" in e-Health sector. Our biggest success story is an e-Prescription. More than 95% of prescriptions in Estonia are issued digitally. A 2015 survey showed that the e-Prescription service was the most popular e-service among citizens. Our whole population's health data is stored in one database and about 10 000 healthcare professionals are using the database. Our health information system allows medical records to be exchanged between hospitals and family doctor's practices in a matter of minutes.
Connected Health Profile http://connectedhealth.ee/members/diagnostic-match/
Contact us at: E-mail: email@example.com
Phone: 0845 643 5375
Estonian Digital Health Series: Diagnostic Match interview first published on Company Connecting February 2017