Health Economics and Big Data Analytics Specjalność na studiach II stopnia Master in Economy, 2-letnie, uzyskany tytuł: magister

Health Economics 

Europe is currently the oldest continent in the world and is expected to hold this record at least until 2060. The old age dependency ratio (people aged 65 or above relative to the working age population) reaches almost 25% in Europe, while it remains below 20% in other regions (Northern America at around 20%, Asia and Latin America slightly above 10%, while Africa remains below 10%). More (pdf)

Health economics is a new but dynamically developing science. It is the discipline of economics applied to the topic of health care. Health economics provides a set of methods and analytical approaches  to study the effectiveness, efficiency and value of health technologies with the ultimate objective of optimal allocation of healthcare resources.

The emergence of health economics dates back to 1963, the year when Kenneth Arrow published his article "Uncertainty and the Welfare Economics of Medical Care". However, it was not until the 1980s that it started flourishing as a separate discipline of science, in response to the emergence of the first academic works related to health economics. The research activities in the field of health economics was triggered by the creation of Journal of Health Economics by Joe Newhouse and Tony Culyer in 1981. From then on, a steady growth of scientific output by the experts from the discipline can be observed, with a yield of 2.000 publications per annum.

Investigating the reasons for the exponential growth in interest in health economics it is worth drawing attention to the escalating financial problems that the healthcare systems face, and which in turn forces the need to ensure the objective and transparent distribution of financial resources. It is increasingly challenging to meet the healthcare needs of all the patients. Frequently in order to reimburse the treatment for a particular group of patients, the access to a new, innovative therapy has to be denied to another group. It is a problem that can have its roots in the uninterrupted progress of medicine and in the limited public resources allocated to healthcare. While life expectancy in OECD countries increased on average by more than 12 years in the last half a century, the public healthcare budgets grew by as little as 2% of GDP within the last 15 years.

As the result of such challenges, the study of economic consequences of the introduction of new health technology to the clinical practice have been introduced in the decision-making process in the healthcare in many jurisdictions. According to the most recent estimates, as many as 22 out of  34 studied OECD countries have already implemented the requirement of health economics data in  the evaluation of need for reimbursement of a new health technology (Barnieh, 2014).

The fast development of health economics can also be exemplified by the increasing number of pricing & reimbursement specialists joining the International Organization of Pharmacoeconomics and Outcomes Research (ISPOR). In the last 20 years it grew over 30 times (ISPOR, 2016).

According to the most popular business networking portal Linkedin, there were more than 7587 vacanies posted with respect to the pricing & reimbursement specialization of health technologies on October 20th 2018. Więcej 

 

Why Big Data? 

Today’s discussion about the healthcare sector in the EU region is mainly driven by concerns of the sustainability of public budgets resulting from the growing life expectancy and medical needs of our aging population. The EU Commission acknowledges that the ability to meet such challenges requires adaptation of cost-effective solutions. A number of potential areas for improvement are highlighted which include: strengthening health promotion and disease prevention; moving healthcare out of the hospital sector towards more cost-effective primary and ambulatory care services; and promoting integrated care. The EU Commission indicates that new solutions using digital technologies can support implementation of such reforms. Innovative technologies include eHealth, telemedicine and other digital technologies such as 4G/5G mobile communications, artificial intelligence and supercomputing all of which offer new opportunities to transform our healthcare systems .

Digital health solutions offer opportunity for more patient-centered healthcare, emphasizing prevention and closer individual monitoring, whilst improving healthcare efficiency by reducing unnecessary consultations.

What is BIG DATA?

1. Hospital data support hospital organization
Hospitals in Paris are trialling Big Data and machine learning systems designed to forecast admission rates – leading to more efficient deployment of resources and better patient outcomes. The experimental project was carried out at four of AP-HP’s facilities, with plans to eventually roll it out to all 44 if it proves successful. As well as the hospital’s internal data, several external datasets such as weather, public holidays and flu patterns were tapped.
The result is a web browser-based interface designed to be used by doctors, nurses and hospital administration staff – untrained in data science – to forecast visit and admission rates for the next 15 days. Extra staff can be drafted in when high numbers of visitors are expected, leading to reduced waiting times for patients and better quality of care.


2. Patient history of disease to support treatment outcome
A 2013 survey shows that 75% of European hospitals have some type of electronic health records (EHR) system in place. enhanced patient safety, reduced clinical risk, increased continuity of care and improved productivity.

3. Mobile app or social media support to better control of treatment
There are more than 97,000 mHealth apps available on the market with new mHealth apps arriving every month. More than mobile apps to control sugar level, pulse …or smart pill that dissolves in the stomach and  the sensor is activated and transmits data to a wearable patch on the outside of the body and on to a smartphone app.

Example of the use of social media (twitter account):
Study Design
Tweet2Quit - peer-to-peer support and accountability for maintaining commitment to quit smoking: (1) discussion questions based on tobacco treatment clinical practice guidelines and (2) individualized autofeedback based on past-day participation.
In a two-group randomized controlled trial with 160 tobacco smokers, Tweet2Quit was combined with a web guide (smokefree.gov) and nicotine patch. The comparison group received the web guide and nicotine patches without the Twitter support group. Tobacco abstinence was reported at 60 days follow-up.
Study findings
Tweet2Quit participants reported significantly greater sustained tobacco abstinence compared with control subjects: 40% vs. 20%; Engagement was high, with participants averaging 57 tweets over an average of 47 days. More tweeting was associated with quitting.

4. Social media
Set up early warning system for adverse drug effects and interactions.
Millions of posts were first analyzed based on defined hashtags with the relevant drug names across social media channels such as Instagram, Facebook, or Twitter etc.
Connections were searched on how drugs interact with each other, and how people are describing them, also looking for clusters of symptoms at a scale not previously possible.
https://www.datapine.com/blog/big-data-examples-in-healthcare/

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