THE DEFINITIVE GUIDE FOR

Health Data

basis for individual therapy approaches and new findings

 

Patient Monitors and Data Supported Solutions

Clinical trials and scientific evidence are essential in healthcare and prevention. However, this compiled knowledge is rarely optimally tailored to the individual through keyword individualization. The solution to this problem is "real-world data" – information based on personalized data from patients, accumulated from a wide variety of sources taken from "real life" scenarios.

 

Temedica collects these health insights, links them together and evaluates them - using the company's own applications and the Permea platform - and draws on scientific data sources for an all-encompassing analysis. The goal: to create patient-generated therapy approaches and gain invaluable new insights.

What does real-world evidence mean?

The term real-world evidence (RWE) is a conceptual combination of facts and relevant information stemming from real world situations. RWE includes any evidence obtained outside the settings of classic clinical trials and is therefore a hugely valuable addition to this data pool.

The advantage of real-world data lies in its particular benefit for the patients themselves and, not least, for the pharmaceutical industry, physicians and all stakeholders in the healthcare and prevention sectors.

For example, real-world evidence provides effective support for drug development by incorporating real therapeutic successes documented by patients. Physicians can adjust their treatment methods and decisions on the basis of this, thereby individually extracting the maximum for the patient or a group of patients.

Pharmaceutical companies are also in a much better position to assess potential treatment outcomes, as research departments can come into contact with each other with new knowledge and unprecedented perspectives for their work.

 

What is the added value of personalized health data?

Real-world data provides insights that often don’t emerge in full from medical studies. They differ from established data sources in that they are not derived exclusively from official observations and research on small groups in the context of clinical trials, but often come from patients themselves and their wealth of experience or are the result of practice routines.

The added value of this approach is obvious: Scientists, physicians, health authorities and other experts can use real-world health data to support hypotheses based on studies that have been conducted within the confines of a clinical trial setting. The pharmaceutical industry is able to detect any anomalies, side effects or other patterns and tailor drug development accordingly - however, it’s essential that the patient ultimately benefits from this analyzed health data.

 

What are the sources of digital health data?

Relevant health data can be accessed in a variety of different ways. In the digital environment, it can be collected both via social media and in the context of anonymized surveys among specific population or patient groups. Additionally, wearables - which are being used by an ever-increasing number of people - also serve to collect relevant information, usually not only recording information on the wearer’s heart rate, but also their physical activity and sleep data.

Healthcare data from "real-world" contexts can also come from the mobile devices of private users, for example, from apps in which the user enters corresponding data. Temedica is using this promising approach, for example, with a special application for patients suffering from the chronic disease multiple sclerosis.

 

Big data in healthcare: What does it mean?

The term Big Data generally stands for a large amount of data. Particularly in the area of data for healthcare - i.e., health data - this information holds almost immeasurable potential and brings extraordinary benefits for the healthcare sector.

The Big Data in Healthcare category brings together a wide range of information. These concern, for example:

  • Disease history
  • medical history
  • Blood counts and other laboratory data
  • Genetic data
  • X-ray, CT or MRI images
  • Medication schedules
  • Health insurance data
  • Sleep and activity records

This all-encompassing collection of data can be used, for example, to analyze promising approaches to therapies for which no background experience is available. Disease patterns and possible treatment methods can be defined and analyzed at the same time and recommendations made as a result.

From a business perspective, big data acts as an optimization tool in the context of billing processes in clinics or medical practices, in logistics, communication, and purchasing and marketing policy, for example. Computers analyze the immense volumes of data and, with the help of artificial intelligence, break down the data to identify patterns that can then help prevent diseases or treat them in the best possible way.

This way, unnecessary and possibly unpleasant and financially demanding additional examinations can be avoided, potential complaints can be diagnosed at an early stage, and targeted therapies can be planned accordingly.

 

Real World Data and data protection: How does it work?

The pooling of medical data undoubtedly has the potential to take the healthcare system to a new technological level. However, since most of this information is personal and highly sensitive, data protection is an issue of the utmost importance.

It is therefore important to make the flow of data as transparent as possible – a substantial but achievable challenge. Above all, under no circumstances can these data be misused, and economic interests must never collide with the needs of the individual.

Both the Permea analysis platform and all apps of the digital health company Temedica GmbH comply with current data protection standards (in accordance with the General Data Protection Regulation (DSGVO)). This applies on a national as well as on an international level.

 

The benefits of healthcare data analytics in a nutshell

First and foremost, merging and analyzing patient data aims to provide more efficient and better health care. In addition to this, obvious benefits lie in the:

  • Prevention of disease
  • Possibility of obtaining new knowledge for research and clinical studies
  • Optimization of treatment processes
  • Cost savings Digitalization of processes
  • Acceleration of administrative processes
  • Better understanding of health data

 

Conclusion: Digital health is the present and the future

Continuous technological progress doesn’t stop at the healthcare sector, and the foundation for revolutionizing the system within the medical field has long since been laid. Today, digital health doesn’t just mean the digitization of medical records or laboratory data - rather, the connection between people and technology should result in a simplification and improvement of the healthcare system,both in terms of pre- and post-operative care and in the development and implementation of therapeutic approaches.

The objective of digitization is incontrovertible: the patient and his or her health are the highest good and will be satisfied by all available means. In order to ensure this, it’s essential to join forces and harness the power of the potential of these innovative concepts.

 

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Patient Monitors and

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Patient Monitors and Data Supported Solutions