Real-life data are data obtained in everyday practice, outside a strict experimental framework. These data reflect the effect of a procedure or a health product in real life, freeing us from the highly categorized populations of clinical trials. They can be a major leverage for improving practices, for continuous progress in collective knowledge, and for regulation through the quality and relevance of care.
The SKEZIA solution and the SKEZIA+ service enables the collection of different types of real-life data, including (but not limited too), PROMs, PREMs, and satisfaction.
What are PROMs ?
PROMs (Patient-Reported Outcome Measures) refer to data collected from patients without intervention from any medical experts. These data are collected through validated standardised questionnaires that aim to provide a more informed decision during drug prescription. Apart from drug prescriptions, they can be used to analyse the quality of life (QoL) of patients. The questionnaires are customisable and can be catered to patients with different needs and diseases.
For instance:
- Quality of life by EQ-5D or AQoL
- Symptoms such as pain (Measure of adult pain) or tiredness (Fatigue Severity scale)
- Disease severity, e.g. depression (K10°, Patient health questionnaire-2) or anxiety (GAD°)
- Functional capacity by WHODAS 2.0 or Owestry Disability Index
- Self-efficacy assessment by GSE
- 1.Patrick DL, Burke LB, Powers JH, et al. Patient-reported outcomes to support medical product labeling claims: FDA perspective. Value Health 2007;10(Suppl. 2):S125–37
- 2.Porter ME et al, Standardizing Patient Outcomes Measurement, NEJM, 2016
- 3.U.S. Department of Health and Human Services FDA Center for Drug Evaluation and Research, Guidance for industry: patient-reported outcome measures: use in medical product development to support labeling claims: draft guidance. Health Qual Life Outcomes 2006
There are two types of PROMs :
1. Generic PROMs can be administered to the general patient population. Commonly used surveys to measure QoL are SF-36 and the EQ-5D.
2. Specific PROMs focus on either a disease (e.g., depression, asthma, etc.), a patient group (e.g., children, cancer patients, etc.), or impairment to activities of daily living (e.g., pain, mobility, etc.).
For example:
- Disease severity, such as depression (K10, PHQ2) or anxiety (GAD7)
- Functional capacity by WHODAS 2.0 or ODI
Why measure PROMS ?
During clinical practice
Les données de vie réelle sont des données qui ne sont pas collectées dans un cadre expérimental strict (lien page recherche clinique), mais qui sont générées dans la pratique courante, notamment à l’occasion des soins réalisés en routine. Elles peuvent provenir d'un certain nombre de sources, par exemple :Des bases de données administrativesDes dossiers médicauxDe registres de produits et de maladiesDe données générées par les patients, y compris dans le cadre de l'utilisation à domicileDe données recueillies à partir d'autres sources pouvant fournir des informations sur l'état de santé, comme les dispositifs mobiles.
(source : https://www.fda.gov/science-research/science-and-research-special-topics/real-world-evidence)
PROMs encourage patient-centred care and improve communication between both clinician and patient. PROMs have a major impact when they are integrated into patient follow-up. In clinical consultations, they allow to:
On the patient's side:
· Help them share their concerns with their clinician
· Help identify symptoms that may require further investigation and management.
· Help patients regain control of their personal health
On the caregiver's side:
· Facilitate tracking of health outcomes over time.
· Enable comparison of a patient's results to those of other patients with the same health conditions.
· Promote shared decision making on treatments.
· Improve patient-perceived health outcomes.
In quality improvement and research
PROMs are used in research, clinical registries and quality improvement activities. They can provide information about on:
· Comparative effectiveness of non-drug treatments or interventions
· The effectiveness of quality improvement practices
· Variations in care practices, costs and outcomes among health care providers.
Les données de vie réelle sont des données qui ne sont pas collectées dans un cadre expérimental strict (lien page recherche clinique), mais qui sont générées dans la pratique courante, notamment à l’occasion des soins réalisés en routine. Elles peuvent provenir d'un certain nombre de sources, par exemple :Des bases de données administrativesDes dossiers médicauxDe registres de produits et de maladiesDe données générées par les patients, y compris dans le cadre de l'utilisation à domicileDe données recueillies à partir d'autres sources pouvant fournir des informations sur l'état de santé, comme les dispositifs mobiles.
(source : https://www.fda.gov/science-research/science-and-research-special-topics/real-world-evidence)
In health policy
The collection of PROMs at the national health system level is growing (link to Areas of Expertise / VBHC). These PROMs can be used by:
· Patients to inform their choice of health care providers (when PROMs information is made public).
· Regulatory agencies and manufacturers to refine the risk benefit balance of medical devices, surgical procedures or pharmaceutical products.
· Policy makers to move the health care system towards a system based on the quality of care provided ("Value Based Healthcare")
Les données de vie réelle sont des données qui ne sont pas collectées dans un cadre expérimental strict (lien page recherche clinique), mais qui sont générées dans la pratique courante, notamment à l’occasion des soins réalisés en routine. Elles peuvent provenir d'un certain nombre de sources, par exemple :Des bases de données administrativesDes dossiers médicauxDe registres de produits et de maladiesDe données générées par les patients, y compris dans le cadre de l'utilisation à domicileDe données recueillies à partir d'autres sources pouvant fournir des informations sur l'état de santé, comme les dispositifs mobiles.
(source : https://www.fda.gov/science-research/science-and-research-special-topics/real-world-evidence)
In quality improvement and research
PROMs can help make care more patient-centered and improve communication between clinician and patient. PROMs have a major impact when integrated into patient follow-up. In clinical consultations, they allow to:
On the patient's side:
·Assist in sharing concerns with their clinician.
· Help identify symptoms that may require further investigation and management.
· Become a true actor of your health.
On the caregiver's side:
· Facilitate tracking of health outcomes over time.
· Enable comparison of a patient's results to those of other patients with the same health problems.
· Promote shared decision making on alternative treatments.
·Improve patient-perceived health outcomes.
PROMs are used in research, clinical registries and quality improvement activities. They can provide information on:
- Comparative effectiveness of non-drug treatments or interventions
·The effectiveness of quality improvement practices
·Variations in care practices, costs and outcomes among health care providers.
The collection of PROMs at the national health system level is growing (link to Areas of Expertise / VBHC). These PROMs can be used by :
·Patients to inform their choice of health care providers (when PROMs information is made public).
·Regulatory agencies and manufacturers to refine the benefit-risk balance of medical devices, surgical techniques or pharmaceutical products.
·Policy makers to move the health care system towards a system based on the quality of care provided ("Value Based Healthcare")
On the patient's side:
·Assist in sharing concerns with their clinician.
· Help identify symptoms that may require further investigation and management.
· Become a true actor of your health.
On the caregiver's side:
- Facilitate tracking of health outcomes over time - Enable comparison of one patient's outcomes with those of other patients with the same health problems - Promote shared decision-making on alternative treatments - Improve patient-perceived health outcomes
Dans la pratique clinique
Les PROMs peuvent contribuer à centrer les soins sur le patient et à améliorer la communication entre le clinicien et le patient. Les PROMs ont un impact majeur lorsqu'ils sont intégrés dans le suivi des patients. Dans les consultations cliniques, ils permettent de :
Du côté du patient :
· Aider à partager ses préoccupations avec son clinicien.
· Contribuer à l'identification de symptômes qui pourraient nécessiter des examens et une prise en charge plus poussés.
· Devenir un véritable acteur de sa santé
Du côté du soignant :
· Faciliter le suivi des résultats de santé dans le temps.
· Permettre de comparer les résultats d'un patient à ceux d'autres patients souffrant des mêmes problèmes de santé.
· Favoriser la prise de décision partagée sur des traitements alternatifs.
· Améliorer les résultats de santé perçus par les patients.
Dans la pratique clinique
Les PROMs sont utilisés dans la recherche, dans les registres cliniques et dans les activités d'amélioration de la qualité. Ils peuvent apporter des informations sur :
· L'efficacité comparative de traitements ou d’interventions non-médicamenteuses
· L'efficacité des pratiques d'amélioration de la qualité
· Les variations des pratiques de soins, de coûts et de résultats entre les prestataires de soins de santé.
Dans la pratique clinique
La collecte de PROMs au niveau du système de santé national tend à s’accroitre (lien vers Domaines de compétences / VBHC). Ces PROMs peuvent être utilisés par :
· Les patients pour éclairer leur choix de prestataires de soins de santé (lorsque les informations PROMs sont rendues publiques).
· Les organismes de réglementation et les fabricants pour affiner la balance bénéfice-risque des dispositifs médicaux, des techniques chirurgicales ou des produits pharmaceutiques.
· Les décideurs pour orienter le système de santé vers un système basé sur la qualité des soins fournis (« Value Based Healthcare »)
Examples of PROMs collection initiatives in France
Recherche
· La plateforme de recherche publique ComPaRe (https://compare.aphp.fr/) de l’AP-HP permet à des patients atteints de maladies chroniques de participer de façon volontaire à des questions de recherche en répondant à des questionnaires en ligne PROMs.
Associations de patients
· Des associations de patients comme Renaloo et sa plateforme Moi Patient (https://www.moipatient.fr/) proposent des questionnaires types PROMs.
Research
· The public research platform ComPaRe of the AP-HP allows patients with chronic diseases to voluntarily participate in research questions by answering online PROMs questionnaires.
Les données de vie réelle sont des données qui ne sont pas collectées dans un cadre expérimental strict (lien page recherche clinique), mais qui sont générées dans la pratique courante, notamment à l’occasion des soins réalisés en routine. Elles peuvent provenir d'un certain nombre de sources, par exemple :Des bases de données administrativesDes dossiers médicauxDe registres de produits et de maladiesDe données générées par les patients, y compris dans le cadre de l'utilisation à domicileDe données recueillies à partir d'autres sources pouvant fournir des informations sur l'état de santé, comme les dispositifs mobiles.
(source : https://www.fda.gov/science-research/science-and-research-special-topics/real-world-evidence)
Patient Associations
· Patient associations such as Renaloo offer PROMs-type questionnaires.
Les données de vie réelle sont des données qui ne sont pas collectées dans un cadre expérimental strict (lien page recherche clinique), mais qui sont générées dans la pratique courante, notamment à l’occasion des soins réalisés en routine. Elles peuvent provenir d'un certain nombre de sources, par exemple :Des bases de données administrativesDes dossiers médicauxDe registres de produits et de maladiesDe données générées par les patients, y compris dans le cadre de l'utilisation à domicileDe données recueillies à partir d'autres sources pouvant fournir des informations sur l'état de santé, comme les dispositifs mobiles.
(source : https://www.fda.gov/science-research/science-and-research-special-topics/real-world-evidence)
Routine care
Les données de vie réelle sont des données qui ne sont pas collectées dans un cadre expérimental strict (lien page recherche clinique), mais qui sont générées dans la pratique courante, notamment à l’occasion des soins réalisés en routine. Elles peuvent provenir d'un certain nombre de sources, par exemple :Des bases de données administrativesDes dossiers médicauxDe registres de produits et de maladiesDe données générées par les patients, y compris dans le cadre de l'utilisation à domicileDe données recueillies à partir d'autres sources pouvant fournir des informations sur l'état de santé, comme les dispositifs mobiles.
(source : https://www.fda.gov/science-research/science-and-research-special-topics/real-world-evidence)
· The public research platform ComPaRe of the AP-HP allows patients with chronic diseases to voluntarily participate in research questions by answering online PROMs questionnaires.
·Patient associations such as Renaloo offer PROMs-type questionnaires.
What are PREMs?
PREMs (Patient-Reported Experience measures) are objective measures of patient's experience. Unlike PROMs, PREMs are focus in how the patient perceives their care, in the description of the events that took place: PREMs make it possible to understand the whole patient's interaction with the care system.
There are two types of PREMs:
1. Generic PREMs are design for all patients. For example:
· Time spent waiting for a consultation
· Access to care (distance from health facilities, difficulty finding the right doctor, etc.)°.
· Patient involvement in medical decisions°.
· The quality of communication
2. Specific PREMs focus on the patient experience for particular diseases. For example:
· Knowledge of the diabetes treatment plan and care pathway
· Support to manage long-term patient follow-up
Why measure PREMS ?
PREMs are used to measure the quality of care. They allow to:
For the health care system
· Identify areas for improvement in the organization of care
· Better quantitation evaluation of health professionals' practices
· Measure resource allocation needs for public health decision makers
For customers
· Emphasize the dimensions that really matter to them
· Get the feed back from previous customers when they face the same need
For the health care system
- Identify areas for improvement in the organization of care
·Better quantitative evaluation of health professionals' practices
- Measure the needs in terms of resource allocations fore santé publique
For users
· Emphasize the dimensions that really matter to them
- Know the experience of other users before them for the same need
Examples of PREMs collection initiatives in France
In France, the e-Satis system allows for the collection of patient-perceived quality (PREMs). It has been implemented since 2016 by the French National Authority for Health on a national scale, in patients who have been hospitalized. The e-Satis indicators mainly measure the satisfaction and experience of hospitalized patients. They do not measure clinical outcomes or the health status felt by the patient.
Satisfaction
What is satisfaction?
Patient satisfaction reflects the degree of agreement between the patient's expectations of care and the perception of the quality of care provided. It depends on the patient's preferences, level of health, characteristics and culture, in addition to the quality and outcome of care. Patient satisfaction is different from experience in that satisfaction is considered more subjective. For example, despite negative experiences, patients may be satisfied with their care; the opposite is also possible.
Why collect it?
The study of satisfaction is an important step in the adaptation of a service offer such as care. Satisfaction surveys ask individuals about various important points to improve the quality of the service provided. Patient satisfaction is measured by instruments such as self-administered questionnaires. Difficult to apprehend on an individual basis because it is very subjective, it provides a comprehensive view of the quality of care when combined with PROMs and PREMs.
What is satisfaction?
Patient satisfaction reflects the degree of agreement between the patient's expectations of care and the perception of the quality of care provided. It depends on the patient's preferences, level of health, characteristics and culture, in addition to the quality and outcome of care. Patient satisfaction is different from experience because satisfaction is considered more subjective. For example, despite negative experiences, patients may be satisfied with their care; the reverse is also possible.
Why collect it?
The study of satisfaction is an important step in the adaptation of a service offer such as care. Satisfaction surveys ask individuals about various important points to improve the quality of the service provided. Patient satisfaction is measured by instruments such as self-administered questionnaires. Difficult to apprehend on an individual basis because it is very subjective, it provides a complete view of the quality of care when combined with PROMs and PREMs.
Other real-life data
What other data can be collected?
Patients can add medical reports (consultation, complementary examination, prescription...). This allows a comprehensive approach of his environment and context. Data from IOT (watch, smartphone...) or biosensors can also be collected. These newly generate health data can be useful, especially when evaluating physical activity.
Real-life data
What are they and where do they come from?
Real-life data are data that are not collected in a strict experimental setting (link to clinical research page), but are generated in the course of routine practice, including routine care. They can come from a number of sources, for example: administrative databases, medical records, product and disease registries, patient-generated data, including home use, data collected from other sources that can provide information on health status, such as mobile devices°.
Why collect them?
To generate real-life evidence: this is clinical evidence about the use and potential benefits or risks of a medical product derived from the analysis of real-life data. Real-life evidence can be generated by different types of studies or analyses, including, but not limited to, randomized trials, pragmatic trials, or observational studies (prospective and/or retrospective)°. This makes it possible, for example:
- to observe the extent to which the conditions of the trials are verified in real life
- to highlight effects that cannot be identified in clinical trials (due to the limited number of participants and time horizons)
- to confirm or invalidate the results in terms of efficacy in populations that have actually been exposed to the treatment
To improve the quality of care: the challenge of real
-life data, and in particular data collected directly from patients, goes beyond simply demonstrating the efficacy or tolerance of a product:
they can constitute a major lever for improving practices, for continuous progress in collective knowledge, and for regulation through the quality and relevance of care°.
Les données de vie réelle sont des données qui ne sont pas collectées dans un cadre expérimental strict (lien page recherche clinique), mais qui sont générées dans la pratique courante, notamment à l’occasion des soins réalisés en routine. Elles peuvent provenir d'un certain nombre de sources, par exemple :Des bases de données administrativesDes dossiers médicauxDe registres de produits et de maladiesDe données générées par les patients, y compris dans le cadre de l'utilisation à domicileDe données recueillies à partir d'autres sources pouvant fournir des informations sur l'état de santé, comme les dispositifs mobiles.
(source : https://www.fda.gov/science-research/science-and-research-special-topics/real-world-evidence)
In France, a rich and dynamic ecosystem: the SNDS
The National Health Data System (SNDS) was created in 2016 to expand the use of health data. It's a significant step forward in analyzing and improving population health. It includes:
- Health insurance data (the national health insurance information system - SNIIRAM)
- Hospital data (the medicalization of information systems program - PMSI) historically matched to SNIIRAM
- Databases on medical causes of death (database of the Epidemiology Center on Medical Causes of Death of the National Institute of Health and Medical Research- Inserm's CépiDC)
- Data on disability (from the Departmental Houses for the Disabled - MDPH - data from the National Solidarity Fund for Autonomy - CNSA).
Les données de vie réelle sont des données qui ne sont pas collectées dans un cadre expérimental strict (lien page recherche clinique), mais qui sont générées dans la pratique courante, notamment à l’occasion des soins réalisés en routine. Elles peuvent provenir d'un certain nombre de sources, par exemple :Des bases de données administrativesDes dossiers médicauxDe registres de produits et de maladiesDe données générées par les patients, y compris dans le cadre de l'utilisation à domicileDe données recueillies à partir d'autres sources pouvant fournir des informations sur l'état de santé, comme les dispositifs mobiles.
(source : https://www.fda.gov/science-research/science-and-research-special-topics/real-world-evidence)
What are they and where do they come from?
Why collect them?
In France, a rich and dynamic ecosystem: the SNDS
Real-life data are data that are not collected in a strict experimental setting (link to clinical research page), but are generated in everyday practice, particularly during routine care. They can come from a number of sources, for example:
- Administrative databases
· Medical records
·Product and disease registries
· Patient-generated data, including in-home use
· Data collected from other sources that can provide information on health status, such as mobile devices.°
To generate real-life evidence: this is clinical evidence about the use and potential benefits or risks of a medical product derived from the analysis of real-life data. Real-life evidence can be generated by different types of studies or analyses, including, but not limited to, randomized trials, pragmatic trials, or observational studies (prospective and/or retrospective).°
This allows for example:
- To observe to what extent the test conditions are verified in real life
- To highlight effects that are not detectable in clinical trials (due to limited numbers and time horizons)
- To confirm or invalidate the results in terms of effectiveness on the populations actually exposed to the treatment.
To improve the quality of care: the challenge of real-life data, and in particular data collected directly from patients, goes beyond simply demonstrating the efficacy or tolerance of a product: they can be a major lever for improving practices, for continuous progress in collective knowledge, and for regulation through the quality and relevance of care °
The National Health Data System (NHDS) was created in 2016 to expand the use of health data and is a significant step forward in analyzing and improving population health.
It includes:
- Health insurance data (database of the national health insurance interregime information system - SNIIRAM)
- Hospital data (information systems medicalization program - PMSI) historically matched to Sniiram
·Databases on medical causes of death (database of the Centre for Epidemiology of Medical Causes of Death of the National Institute of Health and Medical Research - CépiDC of Inserm)
·Data on disability (from the departmental houses for the disabled - MDPH - data from the national solidarity fund for autonomy - CNSA).
What is done at the international level
International initiatives such as ICHOM (International Consortium for Health Outcome Measurements) or PROMIS (Patient-Reported Outcomes Measurement Information System) standardize the collection of PROMsPREMs promote their global use.
HAS has compared 13 selected systems (England, Wales, the United States of America, Canada, Australia, New Zealand, Sweden, Netherlands, Norway, Germany, Denmark, Belgium, and France)°.
