FAQ 1: What you need to know about Health Data

Health Data is information about your state of health – this includes both physical Health Data and mental Health Data. 

Examples of Health Data are your height and weight, lifestyle information such as the type and duration of your daily exercise, smoking habits or alcohol consumption. Health Data also includes past illnesses or treatments carried out, such as an operation, results of medical examinations such as blood values and X-rays, or genetic information such as illnesses in the family. Finally, Health Data also includes information about mental health and personal well-being.

All information in this FAQ relates to Switzerland, as the legal situation may be different in other countries.

There are different types of Health Data. The most common types of Health Data are as follows:

• Diagnostic data: Information about diseases, health conditions or disorders that an individual has been diagnosed with and the dates of diagnosis.

• Treatment data: Data about medical treatments a person has received, including surgeries, medications, therapies and other medical interventions.

• Laboratory results: Results of laboratory tests, such as blood tests, urinalysis, tissue samples and other diagnostic tests.

• Imaging examinations: Data from imaging procedures such as X-rays, MRI scans, CT scans and ultrasound examinations that are used to diagnose diseases or monitor the course of a disease.

• Medication data: Information about prescribed medications, dosages, intake schedules and possible side effects.

• Family history and genetic data: Information about family health history and genetic information that may indicate hereditary diseases or genetic risk factors.

• Vital signs: Measurements of vital signs such as blood pressure, pulse, body temperature, respiratory rate and other physiological parameters.

• Lifestyle and behavioral data: Information on dietary habits, physical activity, smoking habits, alcohol consumption and other lifestyle factors that can affect health.

• Mental Health Data: Data about mental health conditions, psychological evaluations, therapies and psychiatric treatments.

• Health Data trackers: Information from applications such as fitness trackers, smartwatches and health apps that collect measurements such as steps, sleep patterns, heart rate and other health indicators.

Together, these different types of Health Data provide a comprehensive picture of a person’s state of health.

Health Data comes from a variety of sources. Most Health Data is collected during a visit to a doctor’s surgery or hospital. 

• Healthcare professionals: Doctors, hospitals and other healthcare professionals collect Health Data during medical care. This includes the above-mentioned diagnoses, treatments or imaging procedures such as X-rays as well as lifestyle information. 

• Laboratories: Additional information necessary for diagnosis or treatment is usually obtained in specialized laboratories when the attending physician orders diagnostic tests such as a blood sample or urinalysis.

Every time you are examined in a doctor’s surgery or hospital, data is generated – your Health Data! For example, blood pressure and blood values or all descriptions of your well-being and complaints – they are evaluated by the doctors and used to make a diagnosis.

Pharmacies also store data, for example about your medication. If you use health and tracking apps, you collect various information about your state of health or perhaps even your sleep via a wearable such as a smartwatch or a smartphone. However, the data is generated in different contexts and is therefore not systematically collated. You could benefit from having all your Health Data in one place and thus avoid unnecessary examinations, for example.

In the case of cancer treatment, the majority of all Health Data that is recorded is collected during daily patient care at the hospital. The rest are, for example, laboratory reports, reports from follow-up examinations, data collected by patients themselves via apps or wearables or by telemedicine services. The enormous wealth of knowledge that this data could represent for research is extraordinary. Unfortunately, however, this data collection is rarely used as a source of information – so its full potential cannot be exploited. One reason for this is that we still lack the framework conditions in Switzerland to collate and analyze large volumes of data.

It is not the data of individual patients that is particularly interesting, but the summary of all the data, the big picture, so to speak. Only when researchers link thousands of data sets together do patterns become recognizable that are important for research as well as for individual diagnoses and treatment decisions.

Your Health Data is primarily useful for you and for people who treat you. With little effort, you can check which vaccinations you have received and which childhood illnesses you have survived – and which examinations do not need to be repeated. Your Health Data can be used further – but only with your consent – and help to improve healthcare for everyone. But how does this work? For example, when Health Data is used for medical research. If researchers are allowed to use Health Data, they can identify patterns, causes and trends and find out how diseases spread in the population. Or they can use this data to develop new medicines and therapies. All of this improves patient care – including your own healthcare.

((Example 1))

A concrete example: A few years ago, a biomarker was discovered in the human body that tells researchers whether someone has an increased risk of suffering a stroke. A biomarker – which can be a protein or a change in a gene – is a sign that acts as a warning signal for doctors because it indicates a certain problem. The research team was able to find the biomarker that indicates an increased risk of stroke by using artificial intelligence to analyze huge amounts of data from tissue samples taken from stroke patients. These tissue samples were taken – after obtaining the patient’s consent - during medical examinations, operations or autopsies and made available for research. Researchers recorded what information they obtained when examining these tissue samples and entered this information into a specially created database. By comparing the information, it became clear that patients whose bodies contain this particular biomarker are more likely to suffer a stroke. This is enormously helpful, as it means that those affected can protect themselves better and in a targeted manner, for example through more frequent check-ups or preventative treatments.

Whether or not you want to share your Health Data is your personal decision and can depend on many factors. 

Sharing Health Data can be very valuable for various reasons:

• If doctors from different specialties and nurses are involved in your diagnosis and treatment, sharing your Health Data can give them a better overview of your health status. For example, your blood lipid values and ECG can – with your consent – be viewed by your ear, nose and throat specialist, even though they were recorded by your internist. In this way, more comprehensive decisions can be made much more quickly, and all medical aspects as well as your medical history or that of your family are taken into account in the diagnosis. This can improve your treatment and make it safer. 

• Have you ever been asked by your doctors for certain blood values, vaccinations or X-rays and because you didn’t have them to hand, a new admission had to be made or a new sample taken? This should no longer happen in future, because such information can be stored in a central location such as the electronic patient record (EPR)

  • and retrieved by the relevant people at any time if you grant them access. This also makes medical care more efficient. This means that they can plan treatment better and ensure that neither money nor time is wasted. This is important so that everyone gets the best healthcare.

  • If more Health Data is shared, this will advance research. By analyzing a lot of Health Data, researchers can find out how diseases develop, they can develop more effective treatments and carry out studies to improve healthcare and enable the early detection of diseases. In this way, new ideas in medicine can be implemented better and faster with the help of Health Data.

  • Health Data helps to detect diseases at an early stage. This is particularly important to stop the spread of infections as some diseases are notifiable, such as the highly contagious measles. This also reduces the risk of you becoming infected and falling ill. 

  • The use of Health Data can make medicine as a whole more inclusive. In the past, for a variety of reasons, clinical trials were conducted primarily with men from industrialized countries – so the results were sometimes not as transferable to women or people from other regions of the world. By sharing data from different populations, we can identify these research gaps and do something about them.

  • Every person is unique, and so are their diseases – for example, every tumor is different. Thanks to extensive Health Data and advanced analytical methods, we can offer treatments that are better tailored to an individual. This individualized medicine uses real-time data and artificial intelligence to find the most effective therapy for each person.

According to surveys, over 70 percent of the Swiss population are willing to share Health Data in anonymized form with medical research – and thus contribute to a greater social benefit. Unfortunately, the possibilities are still limited. Here are a few examples: 

• Every medical examination or treatment by doctors, therapists, hospitals, nursing homes, Spitex, physios and so on generates new Health Data. In rare cases, you will be asked at the hospital whether your data may be used anonymously for research purposes.

• If you take part in a research study, your data will be as a rule used anonymously for this study. The researchers use your Health Data to find out how effective a drug or therapy is. This data is very valuable for developing new, more effective treatments. You can also share important data about your health by answering surveys, for example from doctors, pharmaceutical companies or health authorities.

• Acute hospitals, rehabilitation clinics, psychiatric clinics, nursing homes and maternity clinics as well as medical practices newly licensed from 2022 are obliged to join the Electronic Patient Record (EPR).

  • If you have set up an EPR, these institutions must store certain information there (a hospital discharge report, Spitex care report, medication list, X-ray findings or vaccinations). You can share these documents and others that you have uploaded yourself (such as previous X-ray or laboratory findings, a self-managed pain diary, blood pressure values from an app, a prescription for glasses, your living will or an organ donation card) with healthcare professionals of your choice. 

  • Many people share Health Data via wearables (smartwatch, fitness tracker) with the provider of the device (e.g. Apple, Samsung, Fitbit or Xiaomi), in some cases you can also share this data with your health insurance provider or your doctor. 

The digitalization of Health Data primarily benefits patients: They benefit from earlier detection of diseases and better medicines and therapies – in addition, society as a whole benefits because medical care becomes more efficient and cost-effective.

• Public health: Health Data makes it possible to better understand patterns, causes and trends of diseases and to find out how diseases spread in the population.

• Early detection: Thanks to Health Data, diseases can be detected earlier. Today, patients go to the doctor’s surgery because they have symptoms. A diagnosis is then made there. Diseases may already be at an advanced stage. There are now many ways to analyze Health Data and predict, for example, kidney failure before severe symptoms occur. Researchers have been able to prove the effectiveness of such programs with electronic patient dossiers from the USA and Israel. Patients’ chances of survival and recovery are significantly improved, at the same time, such methods can prevent high medical and care costs. This is a major step forward for those affected, their milieu and society as a whole.

• Researchers have new opportunities to use anonymized and standardized data to investigate diseases in greater depth and develop more effective therapies.

• Health policy and health authorities can use the data to make the healthcare system more transparent, qualitatively better, more efficient and ultimately more cost-effective. A meta-analysis of around 600 scientific publications on cost savings through digital health applications showed that savings of 6.5 to 10.8 percent can be achieved.

Essentially, you decide who you give access to your Health Data and who you do not. For example: If you have consented to the electronic patient record (EPR),healthcare professionals, hospitals, clinics and pharmacies can access the data that you have expressly authorized them to access. 

Even if Health Data is collected from you as part of studies or medical examinations, researchers can only access this data with your consent – or must at least inform you. In addition, all personal identification features are removed or encrypted so that no conclusions can be drawn about you and only the released anonymized Health Data can be used to gain insights for research.

In Switzerland, your personal Health Data is protected by various laws and ordinances. The Swiss Data Protection Act (DSG)contains rules that must be observed when processing personal data. Personal data within the meaning of the DSG is all information relating to a specific person. Health Data and genetic data of a specific person are particularly sensitive data. In rare cases, the disclosure of certain data to the state is required to protect public health, e.g., data on tuberculosis cases. In these special cases, the legislator weighs the protection of the general public higher than the protection of an individual person. Apart from these few exceptions, the disclosure of Health Data without consent is prohibited.

When passing on data – for example from the hospital to the family doctor – certain security measures must be observed.  For example: If healthcare professionals send patient data by email, the transmission must be encrypted. A well-known encryption system is “HIN,” which was founded by the Swiss Medical Association (FMH) and the “Ärztekasse” (Doctor’s Insurance Fund). If you receive such an encrypted email from your family doctor, you must identify yourself in order to open the email.

Digitalization in the healthcare sector is progressing internationally, but Switzerland is lagging behind in various respects compared to other European countries. There are currently problems in the following areas:

1. Health Data is not collected at many points in the healthcare system in such a way that it could be easily analyzed. In Switzerland, for example, there are currently no regulations on how Health Data is collected – because there are no corresponding regulations. For example, there is no standardized definition of how the gender of patients is recorded in digital documents – whether female is represented with “w” (weiblich: the German word for female), “f” (for féminin, femminile or female) or “2.” 

2. Many of the foundations for the further use of Health Data in research are lacking: for example, hospitals or doctors’ surgeries are not technically equipped accordingly, and there is a lack of software in which the data can be securely stored and shared. In addition, the laws that allow the further use of data (secondary use) are not always clear. 

3. It is also difficult to network all stakeholders in the healthcare system – for example, doctors, therapists, hospitals, nursing homes, home care, health insurance companies, universities and so on – i.e., to motivate them to consistently record data in the correct digital form and to use tools with which this data can be shared.

Specific federal projects include the electronic patient record (EPR), which was introduced in 2020, and the DigiSanté project to promote digital transformation in the healthcare sector. Both projects are moving in the right direction and form a good basis for the development of a networked healthcare data system. 

The digital transformation of the healthcare system must be driven forward quickly with clear political will and leadership. This requires:

• An integrated infrastructure. Data must be recorded uniformly, securely encrypted and shared.

• Common technical and ethical standards for data collection.

• Trust and acceptance of the system.

• Skilled professionals and specialists.

• A constructive legal framework.

• Financial resources.

The electronic patient record(EPR) is a collection of personal data and documents containing information relating to a patient’s health. This includes, for example, a hospital discharge report, a Spitex care report, a medication list, X-ray findings or a vaccination record. This information can be accessed at any time via a secure internet connection by both the patient and the responsible healthcare professionals: on a computer, smartphone, at home or on the move. Each patient decides for themselves who can view which documents and when. The medical information in the EPR belongs to the patient. They decide what happens to it.

In an emergency – for example, if you are admitted to hospital unconscious after an accident – the EPR can provide vital information, such as whether you are suffering from illnesses or allergies, whether you are allergic to certain medications or whether you are taking medication. 

As the dissemination of the EPR is currently still very low, a comprehensive revision is being carried out in order to make the EPR more user-friendly and to improve its functionality. However, in order to maintain the structure created to date, Parliament decided on transitional funding in spring 2024. Ultimately, the aim is to make the EPR even better and more efficient for the future.

The federal government aims to catch up with Switzerland in the digitalization of the healthcare system by 2034 with the DigiSanté project,and increase the quality and efficiency of the healthcare system. One of the goals is to make Health Data, for example from clinical studies, more easily and securely accessible for research. The authorities are currently working on a standard to record these large data streams and exchange them between the various players in the healthcare system. At the same time, data protection, informational autonomy and cybersecurity must be guaranteed, and access to healthcare data must be clearly regulated by law. The solutions developed are to be implemented between 2025 and 2034.

A networked ecosystem for healthcare data will help to tackle pressing challenges in the healthcare system such as high costs, improving quality, transparency and sustainability.

By comparison, Estonia is a frontrunner in digital healthcare.The Eastern European country relies on comprehensive digital healthcare services such as e-prescriptions, electronic patient records and a national healthcare portal. All of these services are made possible by a standardized national infrastructure. Estonia has been pursuing a consistent digitalization strategy in all public areas, including e-health, since 1991. E-prescriptions and electronic patient records have been mandatory for over a decade, video consultations and remote diagnoses are permitted by law and are well accepted by the general public. The ENHIS network links doctors and pharmacies across the country and enables citizens to access their Health Data via the digilugu.ee portal. Citizens retain control over their data, with the option of deciding for themselves at any time who has access or not.

As Roche, we are committed to advancing Switzerland’s digitalization at all levels of politics and society. In close cooperation with all stakeholders, we see it as our shared responsibility to make the public healthcare system even better equipped for the future. Roche has developed the Precision Oncology Program (POP)together with the University Hospital and the University of Zurich, among others. The joint goal of the project is to find out how oncology patients in Switzerland can benefit from a comparison with larger and personalized data sets in the clinical setting. We want to find out how data from hospitals and medical practices can be structured and transformed into useful reports. 

Focus on patients: In the future, there should be a greater focus on patients in the healthcare system.

In patient-centered healthcare, what counts for patients is the outcome at the end of treatment – not how many treatments were carried out. Money should be spent where it brings the greatest benefit for patients. Patients will be better informed and more involved in decision-making. Treatment is coordinated across different specialist areas so that the treatment steps are better coordinated and the same services are not provided more than once. 

Patient centricity is important to Roche. Currently, the focus in the Swiss healthcare system is too much on the services provided (quantity) instead of the treatment results (quality). Today, there is too little transparency as to what results or quality a patient receives for the services paid for. In most cases, the treating physicians or clinics along the patient pathway are not sufficiently networked. The lack of networking leads to redundant examinations, such as multiple laboratory tests, which in turn generates costs that could be avoided.

Roche is committed to ensuring that treatment outcomes collected along the patient pathway are taken into account in treatment and reimbursement decisions.

Example Basel: The University Hospital Basel (USB) and Roche want to jointly define a Swiss-wide standard for the implementation of patient-oriented healthcare in everyday clinical practice in Switzerland. The parties have joined forces to assess and investigate patient benefit and the efficiency of resource use as part of a pilot project using lung care as an example.

Pharmaceutical companies are not interested in which person’s health data originates from – they are interested in comparing a large amount of data in order to recognize patterns. They therefore use anonymized data in their research studies. Roche therefore does not collect personal information from people, as it is not important for the research and development of medicines to draw conclusions about an individual person. In addition, pharmaceutical companies work with hospitals and laboratories to obtain information about patients – but only if they agree or are informed. You can find out more about the anonymization of data under “What is the difference between unencrypted, encrypted and anonymized data?” 

For medicines that have already been approved, Health Data on diagnosis, treatment, medication use and laboratory tests of patients are important for identifying problems. It is particularly important to analyze all this data over a longer period of time to learn more about the long-term effects of medications, identify changes in the patient’s disease progression and adjust treatment in a timely manner. For this reason, patients are sometimes asked to fill out questionnaires about their state of health (so-called Patient-Reported Outcome Measures).

Much of our knowledge about illnesses, treatments and individual treatment successes comes from general practitioners, specialists, hospitals and so on. However, this so-called real-world data is not recorded in such a way that it can be analyzed effectively. Its potential is therefore hardly used, which is highly unfortunate.

The Health Data required by a pharmaceutical company always depends on the company’s  current research priorities. Roche wants to improve the quality of life of patients by researching and developing new medicines. 

Every person is unique, and so are their illnesses – for example, every tumor is different. Thanks to extensive Health Data and advanced analytical methods, we can offer treatments that are precisely tailored to an individual. This individualized medicine uses real-time data and artificial intelligence to find the most effective therapy for each person. Roche is strongly committed to this area of research. We want to accelerate the development of innovative medicines and personalize patient care. Our goal is to make medical research and treatment faster, more efficient and safer. We attach great importance to data protection and handle the data entrusted to us respectfully and in accordance with the highest ethical standards.

No, currently private individuals cannot share Health Data with Roche on their own initiative. Roche mainly needs information about the health of patients who are taking new medicines in clinical trials, for example. If you have any questions or would like to get in touch with us, please contact us via our social media channels or via the contact formon our website.

Roche does not wish to collect personal information about individuals. It is not important for the research and development of medicines to draw conclusions about individuals. This is why Health Data is mostly anonymized, i.e., modified in such a way that it can no longer be linked to individual persons. You can find out more about this under “What is the difference between unencrypted, encrypted and anonymized data?”Sometimes data is also pseudonymized, i.e., encrypted in such a way that it can only be decrypted using a special code. This code is stored securely and is not accessible to Roche.

Roche works closely with health authorities such as the Federal Office of Public Health(FOPH) to ensure that your data is protected. The right to privacy is very important and Roche is subject to clear rules (such as the Swiss Data Protection Act(DSG) or the rules of the EU Data Protection Regulation) to ensure that personal Health Data is particularly protected and used responsibly. Roche recognizes that behind every data point is a human being and treats your data with the highest level of integrity and care. You can find more on this topic in the Roche Principles on the Ethical Use of Data.