value-based – AQuAS Blog

Improving the quality of healthcare in intensive care units. The PADRIS programme in the Tarragona Datathon 2018 (part two)

14 Feb

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.

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.

What impact has the PADRIS programme had on your day to day?

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)

Improving the quality of healthcare in Intensive Care Units. The PADRIS programme in the Tarragona Datathon 2018 (part one)

7 Feb

Last November, the AQuAS played an important role by means of the PADRIS programme in the Critical Care Data analysis Summit and Tarragona Datathon 2018. Talking about it has been in the pipeline since then.

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.

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.

(To be continued …)

PIPPI project: community of practice in procurement based on value

13 Dec

Innovation has been present in the AQuAS blog with projects such as Antisuperbugs and Ritmocore but there are many more on the go right now. Today we put the focus on the purchase of innovation and on how this innovative methodology can have an impact on clinical practice.

We interview Ramon Maspons, engineer specialised in the management of innovation and technology, coordinator of innovation at AQuAS.

What tools does the health system at present have within its reach to add value to healthcare?

The public procurement of innovation is one of the facilitating instruments when adopting innovation and developing policies for technology and innovation. Due to the characteristics of the health sector this becomes a strategic element. There are other sectors where this does not happen because the public purchaser does not have market power.

In what way does innovation provide added value?

At a first level, we could say that if there is no application no value is generated. At a second level, I would say that the changes in the process are what add value. And at a third level, we could talk directly about the user.

A very brief article was published not long ago on this subject in the journal Annals de Medicina. Recently, in another context, the King’s Fund published a report on models of innovation.

Could you highlight an innovative project within the field of innovation?

Yes, the PIPPI project, coordinated by the Karolinska University Hospital in which AQuAS is involved, together with six other institutions in the hospital and university environment in Sweden, Holland, Italy, Austria, Spain, Finland and the United Kingdom. It is a platform made up of hospitals from the European Hospital Alliance, which is the network of the most relevant European hospitals, and then AQuAS. The focus of this work group is the new models of procurement based on value using digital technologies as an element to transform health services.

Have you considered changing the name of the project?

No, but in fact yes, because the name has curious meanings and connotations in different languages. This was one of the subjects that arose in the Kickoff meeting of the project.

Jokes aside, what is the involvement of AQuAS in the PIPPI project?

The expertise of AQuAS in assessment, innovation and the procurement of innovation is key. This project proposes an environment where the different stakeholders involved in change can come to an agreement and work together, both when revealing the needs of a health system, of hospitals, as well as when involving companies, technological centres, universities, patients and caregivers.

It is a very ambitious aim. What would you say is special about this project?

Its strategic focus of putting the different stakeholders involved in improving healthcare in the same project but having the support of the leadership of hospitals and an assessment agency. Identifying needs and solutions using this vast network of diverse expertise is one of the strengths of this project.

How will the PIPPI project work?

The project needs to develop a community of practice where challenges can be posed and solutions considered within an international framework.

Could you be a little more specific about which environments digital technologies will have an impact on in the health services?

By all means. We can include very different subjects such as co-creation with clinicians, telemedicine, data analytics, artificial intelligence, and so on. Some aspects are nearer on the horizon and others more distant. There exists a powerful reflection on digital technologies: it is said that everything that is digitalised is dematerialised and demonetised (it may be a subject too complex to go into here) and there are also those who say that, in the end, what is digitalised is democratised, but now that really would be going into other subjects.

Earlier you mentioned involving patients – who and what are we talking about exactly?

The patient is a key element in procurement based on value because the patient generates value and this is something difficult for other sectors to understand. When we talk of digital transformation, the involvement of patients is often as necessary as it is a sensitive issue and a certain methodology is therefore required, or specific game rules. We are talking about complex systems which require complex ways of working where, among other things, very diverse sensitivities, organisational models, governances, health systems or types of providers are involved. In short, what we are talking about is getting patients to become a part of identifying needs and taking decisions; we are talking about expert patient concepts, the participation of citizens and about health literacy.

And how are you going to achieve all this?

As members of this consortium, we have the experience, knowledge, methodologies and leadership to forge ahead with a project of this nature. I recommend looking at the presentation of Romualdo Ramos and Tanja Stamm of the Medical University of Vienna to know more about this project.

What is the aim of the PIPPI project in a few words?

Impossible in just a few words, but can I do it in nine? Facilitating the joint design of the best healthcare possible.