The ACT@Scale project responds to the need for a deeper look into the results and conclusions that came out of the previous project, Advancing Care Coordination and Telehealth Deployment (2013-2015) and it follows the strategic lines proposed by the European Association on Active and Healthy Ageing (EIP on AHA).
This new project, ACT@Scale, began in March 2016 within the framework of the Horizon 2020 programme which was financed by the European Union. The aim is on transforming health processes and the provision of services related to integrated care and telemonitoring.
How have we done all this?
Different regions in Europe, the industry and innovative academic institutions have worked in collaboration over these past few years. The Agency for Health Quality and Assessment of Catalonia (AQuAS) has been one of the partners in this consortium leading the work-package Change Management, Stakeholder Management and Staff Engagement.
With 15 partners, in association, from 8 countries of the European Union and with the coordination of Phillips Healthcare we have worked collaboratively in order to consolidate and scale up the best practices identified in integrated care and telemonitoring so that they can be transferred to other European regions.
The Basque Country, The Netherlands, Scotland, Germany and Catalonia have contributed with a total of 15 programmes of integrated care, both innovative and of reference, regarding best practices in health. In particular, Catalonia has participated with five reference programmes of good practices in integrated care: Programme of Chronic Care, of the Badalona Serveis Assistencials; Nursing Homes, of MUTUAM; Frail Care for Older People, of the Parc Sanitari Pere Virgili; Complex Case Management, of the Hospital Clínic de Barcelona and the Promotion of Physical Activity, also of the Hospital Clínic de Barcelona.
ACT@Scale has developed a framework of assessment based on experience, practice and evidence using the Donabedian theoretical framework. To assess the implementation of the programmes, a collaborative methodology (Plan-Do-Study-Act) has been used. Thus, in order to assess processes of implementation and scalability, research has been done within four work packages:
What have we learnt in relation to Change Management, Stakeholder and Staff Engagement?
In relation to Stakeholder Management, the leaders of the programmes that completed the questionnaires agreed that participative and co-creation strategies need to be introduced to improve the quality of integrated care and to reduce the resistance of stakeholders to change, where all identified stakeholders feel part of the process.
In terms of Change Management, regarding leadership, new communication strategies need to be incorporated which should be based on a collaborative methodology so as to detect and prioritise needs, implement them and monitor and assess them within the processes of change initiated.
In terms of Staff Engagement, we can confirm that the implementation of programmes of integrated care is a dynamic process in which potential risks need to be identified and therefore, assessment and redesign need to be ongoing..
Integrated care contributes to the creation of new health scenarios, some in a state of change and others as yet unknown. These new scenarios should make us think about defining new professional profiles, new areas of expertise and identify new actors and “actresses”.
The Catalan Health Department deserves many congratulations on the launch of the website Shared decisions to help patients make decisions about their care. Nowadays the internet makes it possible to find vast quantities of information about health and healthcare, but this can be confusing and some of it is misleading and unreliable. So it is especially important to ensure that people are given access to trustworthy information to help them make decisions about their health.
We all want healthcare to be responsive to our needs and wishes. We want to be listened to, to be given clear explanations and to have our values and preferences taken seriously. Many of us want to be able to influence any decisions that affect us, including treatment decisions.
The key questions that we want answers to are as follows:
What are my options?
What are the benefits and possible harms?
How likely are these benefits and harms?
How can you help me make a decision that’s right for me?
Shared decision making is central to a patient-centred approach. It involves clinicians and patients working together to select tests, treatments, management or support packages, based on clinical evidence and the patient’s informed preferences. It requires the provision of evidence-based information about options, outcomes and uncertainties, together with decision support counselling and a systematic approach to recording and implementing patients’ preferences.
Shared decision making is recommended in many common situations – for people facing major treatment decisions where there is more than one feasible option, for decisions about screening tests and preventive strategies, for maternity care choices, for choosing care and support packages for long-term conditions, for advance care planning for mental health problems and for end-of-life care.
Provision of reliable, balanced evidence-based information has been shown to improve people’s knowledge and ability to participate in decisions about their care, improving the quality and appropriateness of clinical decision making. And as part of a collaborative approach to care planning for long-term conditions it can lead to improved health outcomes.
Information provision is only the first step. As well as providing facts and figures to help people consider their options, doctors, nurses, and other clinicians must engage patients in a process of deliberation to determine their preferred course of action. This demands good conversations where both parties communicate well and share information. Effective risk communication, preference elicitation and decision support are essential skills for clinicians. And then of course there must be a commitment from both clinician and patient to act on the mutually agreed decisions.
Implementing shared decision making is challenging. It is very different from the traditional approach in which clinicians view themselves as experts and sole decision makers and patients’ knowledge, expertise and preferences are unacknowledged or undervalued.
Patients used to be expected to play a passive role and follow doctors’ orders, but this old-fashioned view is beginning to give way to demands for a more collaborative approach. This is very good news! Patients have grown up and health systems must now adapt to meet their expectations, helping them to become knowledgeable, skilled and confident co-producers of health.
Today we continue the interview with Maria Bodí (@mariabodi23), doctor at the Intensive Medicine Service, and Josep Gómez (@JosepGomezAlvarez), doctor in Biotechnology at the Hospital Universitari de Tarragona Joan XXII, experts in clinical management and aspects of quality and safety in healthcare.
Josep Gómez, María Bodí
In your opinion, what are the conclusions of the so-called Real World Data studies which were carried out using real data in terms of benefits and risks related to patient safety?
Benefits? Everything. Information derived from a real healthcare environment is necessary to take decisions. Randomised clinical trials which have defined the effectiveness and safety of therapeutic interventions have served till now as a Gold Standard of the best scientific evidence. But they are very costly, and what is more, they are aimed at very selective groups of patients. Studies and analyses derived from the real world, known as Real World Data, mean it is possible to know the effectiveness and safety of interventions in groups of patients which are usually excluded from trials (pregnant women, older people, patients with many comorbidities who are the majority, etc…).
There is a series of limitations and obstacles that prevent Real World Data from substituting clinical trials. On the one hand, legal and ethical aspects and those concerning the guarantee of the quality of data. On the other, it is not possible to accept the bias that there is when not randomising Real World Data. Before taking decisions, we need to ensure that there are no confusing factors.
Real World Data complements the information obtained from clinical trials in routine clinical practice.
Some weeks ago we received the visit of Lucian Leape in Barcelona, author of the extremely famous book “To Err is Human”. We were fortunate to be able to listen to him in a talk at AQuAS – were you able to listen to him?
No, unfortunately we were not able to attend. It is a pity because we were told that it was a good review of what we have learnt in the past two decades in the field of clinical safety and that some good recommendations were made for the future.
In your opinion, what contributions did the To Err is Human report, published 20 years ago, make?
It revolutionised the field of safety. It was a paradigm shift which is still in place today.
The To Err is Human report denounced the thousands of deaths in the United States resulting from adverse events which could have been avoided! People who were dying in hospitals for reasons unrelated to the disease for which they had been admitted. The most important thing is that those events, those deaths, could have been avoided. Better training, better work organisation, knowing and analysing risks and teamwork, among other factors, have been shown to be key elements that contribute to reducing the amount of events and their severity.
In 2016, MIMIC-II was published, a huge set of de-identified data of ICU patients of the Harvard Medical School. It was created and has been maintained by researchers at the Massachusetts Institute of Technology. They published this dataset with the aim of democratising research. The idea is that after attending a training course on the treatment of data for research, you are certified as a practising researcher and you sign a document of usage: ultimately, to enable a researcher to have access to a large data base to carry out research. In addition, it encourages researchers to share the code (data processing methodology) that they have applied to data to obtain the results they publish. Altogether, it makes studies more transparent and repeatable which in turn increases the excellence of scientific production.
As a result of our experience in extracting data from the clinical information system to develop our management tool of the unit, we took on the challenge of generating our own data base to carry out research. Once created, we contacted the PADRIS programme so they could advise us regarding data anonymisation protocols and methodologies to get access to the programme in order to carry out research. They showed great interest in our project at all times and they helped us see it to fruition and thus the role of the PADRIS programme was decisive in making the Datathon Tarragona 2018 possible. We are in fact still in contact with them to define future strategies about how to make this data available for research projects without infringing any data protection law and how to broaden the database with data from other ICUs in the Catalan territory.
If you could make a recommendation to other researchers who wish to do research, what would it be?
We recommend they collaborate with experts in other fields, especially those related to data and statistical technology. We are now reaching a level of sophistication and volume of data that obliges us to work in multidisciplinary teams in order to make the most of data and to understand it the best we can. The datathons are a great example of this; the role of the clinician is decisive in defining aims and in validating the results that appear when cutting edge algorithms are applied by data scientists. At the same time, the role of data scientists is also decisive when suggesting and applying complex methodologies which are far removed from traditional statistics applied within a clinical context.
What professional challenge would you like to succeed with in 2019?
The ultimate professional challenge for 2019 is the same as each year: improving the care given to patients which are admitted to an ICU. To achieve this, we have some very specific challenges in our unit. On the one hand, to continue developing our tool to exploit data which enables us to analyse processes and the results obtained in our day to day and in this way become aware of where we need to place our attention to make improvements. On the other hand, taking advantage of the secondary use of data to carry out research and to generate algorithms for automatic learning which are able to help a doctor take the most accurate and appropriate decisions based on the profile of each disease.
(You can read the first part of this interview here)
The PADRIS programme contributes to the improvement of people’s health by making anonymised health information available for re-use by researchers in Catalan research centres, in compliance with the current legal framework and established principles.
Is this seen in practice based on a professional’s experience?
Today we interview Maria Bodi (@mariabodi23), doctor of the Intensive Care Medicine service in the Hospital Universitari de Tarragona Joan XXII, expert in clinical management and aspects of quality and safety in healthcare. Like many health professionals, she combines healthcare practice with research.
María Bodí
What is your day to day like?
As head of the Intensive Care Medicine Service at the hospital, in my day to day my basic task focuses on managing the service and organising the care for critical patients by coordinating the work of the professionals involved. More than 150 people work in the service including medical professionals (specialists in intensive medicine, resident intern doctors), nurses, nurse aids, ancillary staff, physiotherapists and secretaries. In addition, it is a service which participates and collaborates in the teaching of medical, nursing and physiotherapy degrees or certifications.
I try to facilitate the participation of professionals in the strategy of the service. This requires articulating and coordinating all efforts made with a clear objective in mind, which is providing quality care to our patients. To a greater or lesser degree, it is necessary to encourage and coordinate the participation of professionals in care-giving, management, teaching and research. This will guarantee the commitment of a worker in the service’s strategy and its organisation.
If we focus on medical professionals, each member of the team is in charge of a specific area of our speciality and we therefore provide ongoing training for the entire team, assess results and commit ourselves to carrying out actions which derive from the analysis of our results.
What do you think about the format that was used for the Datathon?
The Datathon was the result of a series of developments over recent years within the field of secondary use of data in patients’ clinical records for management and for research at a top level. The experience was very good. Pure science, with doctors, technicians and technology all at the service of real-life data analysis in order to find the best scientific evidence.
In the last three years, our group has delved deeper into the study of data and also into the assessment of the quality and safety of data for secondary use. Our progress has allowed us to collaborate with other leading teams such as the team of Dr Leo Celi of the Massachusetts Institute of Technology with whom we organised this event.
In your opinion, how can the quality of care be improved in intensive care units?
We have to aim for excellence. We need to tackle all the dimensions regarding quality of care. We need to improve effectiveness, safety and efficiency. But when talking about good and efficient results, we are not referring to the number of actions done at a particular cost. We are talking about bringing value to the patient, to the work team, the organisation, the health system and society. How is this achieved?
Our team has worked on developing a methodology which enables us to have automatic indicators of quality. This has been possible because all of a patient’s bedside devices (mechanical ventilation, monitoring, dialysis machines, etc.… ) are connected to the system of clinical information and this information, from the hospital’s clinical records, from laboratories and imaging tests, is integrated. This information is incorporated by professionals in an ordered manner.
By means of these indicators designed with innovative technology, it is possible to assess the processes of care and their results. If the professional participates in the design of a process of care, in its planning, and knows how things are being done and what results there are, they get involved and commit themselves to the aims of the service and the organisation.
Likewise, one needs to move from a reactive to predictive medicine, preventive and personalised. We have data with which to start working along these lines. Nevertheless, the scale and complexity of this data makes it difficult for methods of artificial intelligence to easily translate it into relevant clinical models. The application of cutting-edge predictive methods and data manipulation require collaborative skills between professionals who are medical and technology experts, as well as new models in the treatment and analysis of data.
We have read that it is possible to assess risk in an intensive care unit in real time. It seems difficult to imagine this. What can you tell us about it?
It can indeed. We work on the assumption that we have access to the data stored from all patients that have been admitted to an ICU, or in more than one ICU. If the combination of a group of variables (demographic, clinical, laboratory results) leads to a complication or an adverse event, a trained computer model using this data can predict the risk of the same complication or event occurring if it detects the combination of this group of variables. This is the basis of predictive medicine.
Understood, but in practical terms, what is purpose of assessing the possibility of a risk?
It can range anywhere from analysing a risk or predicting the appearance of a complication in the course of a disease, a problem of safety, an adverse event, the need for or an increase in dosage of a specific drug, to a specific therapy. It can predict the probability of an improvement or worsening and even the risk of death for a patient as a result of their disease.
Medicine already has calculators to assess a risk of death due to a disease based on data bases created by professionals using manual registers. But these days, with the automation of data registration- an example of this being the Clinical Information Systems in our ICUs – today’s methodology based on big data and artificial intelligence allows us to have much more detail when assessing risks.
When there is talk of moving towards a health model based on value, what does this mean exactly?
It is about organising work around the specific conditions of a patient which optimises their cure. It is a question of paying organisations and hospitals for the value they bring. Their results and their costs are the key components of the value which a health system and its professionals offer patients. But if we are talking about results, we are not only interested in whether a patient survives the ICU or not. Results are measured in terms of quality, their capacity of going back to their normal lives, their jobs, etc…
Therefore, to push efforts for improvement, we need to base ourselves on multidisciplinary work and a health model based on value; this means changing an organisation’s business model and investing in systems of measurement, analysis of clinical results and costs.
What importance do you attribute to the fact that data is obtained automatically and not manually?
It means data can be analysed using one source only, errors are minimised and a professional’s time is not required for the task of inputting the data.
How is the data included automatically?
In the ICU, clinical information systems now enable all information to be integrated. Apart from the data which professionals input in an ordered manner during the process of care of a critical patient, laboratory results, imaging tests, clinical records and the data from all a patient’s bedside devices are integrated too (mechanical ventilation, monitoring, dialysis machines, etc…).
What does “secondary use of data” mean?
Primary use is that which is used on a day to day basis, at the patient’s bedside, to take decisions relating to diagnosis, treatment and the planning of the process of care. For example, a decision is made whether to increase the dosage of a drug based on laboratory results.
We talk about secondary use when we refer to using data for management or for research. Obviously, the end aim is still the improvement of care for a patient.
