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.

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.

 (To be continued …)

Indicators for assessing care for chronicity

10 Nov

In a previous post we discussed the advantages of using indicators in the assessment of health services. At AQuAS we have been applying indicators to assess different care processes and areas, with care for patients suffering from chronic conditions being one of the principal areas of interest in terms of new care models and programs assessment. Interventions in the field of care for chronicity are extremely complex given that by their very nature, they tend to involve multiple actors and many different levels of care concurrently, as well as different elements utilising therapeutic instruments and technology with very variable intensity. Moreover, their effectiveness is often linked to contextual factors, making it difficult to attribute an outcome to a particular component of the program. So, given this level of complexity, the question remains, why should we be using indicators in this area? The answer is that these indicators may provide us with several benefits compared to other assessment approaches, such as:

  • Incorporating professional opinion and consensus
  • The possibility of including structural and procedural indicators allows us to obtain an understanding of the environment and the reality in which the initiative is being implemented
  • Providing a type of assessment that is more accessible and understandable for professionals
  • Greater simplicity and speed in evaluation and obtaining results
  • Possibility of defining standards
  • Allowing comparisons to be established and objectifying trends
  • Identifying successful characteristics and factors that can define which models are most effective, for which groups of chronic patients, in what context and at what cost

The first project in which AQuAS began using quality of care indicators for assessing chronicity got underway in 2012 with the commission by the Program for Prevention and Care for Chronicity (PPAC) to define a set of indicators to assess the quality of integrated care programs for chronicity within the health sector, where an ‘integrated program’ is understood as those programs involving the coordinated participation of different levels of care. Following the methodology described in the previous post (review of literature, establishing a theoretical framework and expert opinions) a total of 18 indicators were obtained, mainly from intermediate and final results, which experts considered relevant and feasible for assess these types of programs and which are currently being implemented (see table 1 and web).

Table 1: Indicators assessed as relevant and feasible for evaluating integrated care programs for chronicity

indicadors-2-en-1

From this experience, AQuAS developed a proposal for indicators, published recently to, assess chronic care as part of the strategy for tackling chronicity within the National Health System. As a result of this work, a set of indicators considered to be crucial for evaluation emerged, which included several previously prioritized indicators which are repeated such as polymedication, avoidable readmissions and hospitalisations, but which incorporates new factors which are more closely associated with the patients’ experience, such as the assessment of the patients’ and carers’ quality of life, or patients’ lifestyles (see Table 2).

Table 2: Proposal for prioritized indicators for promoting more uniform measurement of the entire National Health System for evaluating of chronicity care strategies

indicadors-2-en-2

Later, from 2014 onwards, the Catalan Institute of Healthcare and Social Services (ICASS – Dpt. Social Welfare and Family) and the PPAC (Health Dept.), commissioned extensive work to be carried out in evaluating collaborative social and health care models in Catalonia. These models not only consider the different levels of care in the health system but also include social services, a crucial aspect in caring for patients in this category. The objectives of the project were to outline the organization and operations of these collaborative experiences, identify barriers and facilitators, propose a conceptual framework for assessment and define a set of well-founded indicators based on feedback from participants and the expertise acquired from previous assessment studies. The proposed indicators continue to take into account traditional indicators while consolidating assessment that includes the views of those involved, not just the patient, but also the caregivers and professionals, and placing special emphasis on the evaluation of the coordinated actions of healthcare and social services, for example considering the avoidance of duplicate processes or carrying out joint social and healthcare initiatives.

We must also highlight in this line of work the efforts undertaken by the ITES FORUM (Forum of innovation, transformation and excellence in health and social services) to define a joint health and social services evaluation framework with a proposal of indicators (line L6) and in which AQuAS is also involved jointly with professionals from different fields. The Forum is a tool to facilitate the necessary conceptual debate required for transforming existing social services and healthcare in favour of a new model of integrated care.

Finally, and to continue discussing the area of assessing the integration of health and social services, since 2015 AQuAS has been involved in the Horizon2020 SUSTAIN (Sustainable tailored integrated care for older people in Europe) project. This European project aims to compare, assess and implement strategies to improve integrated care experiences aimed at non-institutionalized elderly individuals, in other words, those living in their own homes. The project has an additional goal, which is to seek to ensure that the best integrated care initiatives in this area are applicable and adaptable to other European health systems and regions. The project involves seven European countries working simultaneously on the basis of the definition and implementation of a set of indicators pending definition, tailored to this type of population and integrative approach.

Indicators, therefore, are useful tools for assessing an area as large and as complex as chronicity and they can be applied from a broader or narrower perspective, in other words, taking into account not only the different levels of care in the health system, but also including social services. The results obtained from the implementation of these indicators will provide professionals with objective criteria regarding the quality of their interventions, by facilitating the identification of the strengths of chronic care programs, as well as areas with scope for improvement.

Post written by Noemí Robles, Laia Domingo i Mireia Espallargues. Àrea d’Avaluació, AQuAS.

The “perfect” health system

20 Oct
Joan MV Pons
Joan MV Pons

Mark Britnell is an international expert in health systems having held several senior positions in the NHS and currently provides consulting services for several countries. With this wealth of experience, Britnell wrote a book in 2015 with the inspiring title of, In search of the perfect health care system (1). In it, Britnell examines the dilemmas facing governments, the global challenges such as demographic, epidemiological, technological and economic transitions, as well as the more specific cases facing each country.

A significant portion of the book, more than half, is dedicated to examining individual countries grouped by continent: the Asian region including Australia (with large countries from Japan, China and India, to small densely populated enclaves such as Singapore and Hong Kong) Africa and the Middle East (just three very different examples such as Qatar, Israel and South Africa), Europe (from Portugal to Russia via the Nordic countries, Germany, Italy, France and the English) and the Americas (from the north; Canada, USA and Mexico and the south, such as Brazil). Too bad that the section on the Iberian Peninsula only speaks of our western neighbours (the eastern side but a general walk through).

There is no questioning that Britnells’ knowledge has been acquired first hand, given his worldwide expertise in conferences and consultancy. As the author mentions, he is often asked which country has the best health care system? Since the WHO report, Health systems: Improving performance (2), published in 2000, several country rankings have been published according to the assessment of their health systems using a variety of methodologies and outcomes. The table below serves as an example.

pons-comparison-health-systems

Nowadays, rankings proliferate as can be seen in universities and research institutions/centres. The indicators may be different, but it seems that one may always end up finding the most favourable ranking for them. Catalan public universities are a good example, given that centre advertises their position – besides that of excellence in comparison to other universities which are not necessarily British –  in the ranking system which makes it stand out to a greater degree that other Catalan universities.

Britnell, getting back to our point, after so many rankings, lectures and consulting, make a proposal on what the best health system might be by taking the best areas from the different countries. If the world could have a perfect health system, it would have to possess the following characteristics:

–    Universal healthcare values (UK)
–    Primary health care (Israel)
–    Community services (Brazil)
–    Mental health and welfare (Australia)
–    Promoting health (Scandinavian countries)
–    Empowerment of patients and communities (certain African nations)
–    Research and development (USA)
–    Innovation and new ways of doing things (India)
–    IT and Communication technologies (Singapore)
–    The capacity of choice (France)
–    Funding (Switzerland)
–    Care for the elderly (Japan)

References

(1) Britnell M. In Search of the Perfect Health System. London (United Kingdom): Palgrave Macmillan Education; 2015.

(2) The World Health Report 2000. Health systems: improving performance. Geneva (Switzerland): World Health Organization (WHO); 2000.

(3) Where do you get the most for your health care dollar?. Bloomberg Visual Data; 2014.

(4) Davis K, Stremikis K, Squires D, Schoen C. 2014 Update. Mirror, mirror on the wall. How the performance of the U.S. Health Care System Compares Internationally. New York, NY (US): The Commonwealth Fund; 2014.

(5) Health outcomes and cost: A 166-country comparison. Intelligence Unit. The Economist; 2014.

Post written by Joan MV Pons.

Real Time Delphi relating to chronicity

2 Jun
Monguet JM 2015
Josep Maria Monguet

The Real Time Delphi method, which implements the functionality of the Internet to make the Delphi Method more flexible, efficient and transparent, has been used by the Agency for Health Quality and Assessment of Catalonia (AQuAS as per the Catalan synonym) to identify the indicators for evaluating chronicity care and for the management of the areas of improvement in this field.

¿What is the Delphi method? It is a structured communication technique which is based on a panel of experts who answers questionnaires in two or more rounds. After each round, a facilitator provides a summary of what the experts have said in the previous round. Successive rounds are intended to reach a consensus on the subject. The Delphi method is applied to make predictions about the future and, in general, for any issue when a scientific approach is not possible. When the Delphi method is online (Real Time Delphi) the responses of the participants are calculated automatically and many variants of the method can be entered in a controlled way.

Health Consensus

The Health Consensus application that facilitates the participation of professionals through a methodology of online consensus developed by the company Onsanity from research done at the Universitat Politècnica de Catalunya (UPC) in Barcelona was used to identify the most appropriate indicators.

The work was carried out in the years 2013-2014, the first prototype of the system was applied twice, first in Catalonia, and a second version in the context of all the Spanish health system. The Health Consensus application for the selection of indicators allowed for the collecting of contributions from more than 800 health professionals, including clinical profiles of management and planning. An initial list of 215 indicators was progressively reduced through successive rounds of consensus until it was reduced to 18.

Not only did this experience allow the the identification of indicators, but it also showed various aspects that are interesting for research  and innovation:

  1. It is possible to pool the tacit knowledge of a fairly large group of professionals, putting together experiences and different points of view.
  2. The professionals underscore their perception that the contributions that are made, are highly valuable in the construction of the model subjected to consensus.
  3. The online system is accepted by the professionals who expressed a high satisfaction level during the participation process.

The experience was published: Monguet JM, Trejo A, Martí T, Espallargues M, Serra-Sutton V, Escarrabill J. Assessment of chronic health care through and Internet consensus tool. IGI Global; 2015.

Post written by Josep Mª Monguet (@JM_Monguet), UPC Professor.

Indicators for the health services assessment

4 Feb

What are indicators and how to set them?

In the clinical evaluation field, specifically for health care, an indicator in an instrument used to measure or assess specifici aspects of quality of care, and ultimately, the improvement of quality: assessment to improve.

The methodology used for creating or developing health indicators is distinct in that it combines different methodologies. In the first place, when elaborating indicators, the standard and most recommended procedure is to begin with a conceptual framework of reference, as this provides the premise for reflecting aspects of assessment, dimension, attributes, key areas of care specific to the field of study, as well as the target population. Moreover, the process of defining indicators takes into consideration two sources: scientific evidence experience and expert opinion.

A literature review enables authors to take into consideration scientific evidence and experience in the use of the indicator. A review of the scientific evidence ensures the validity of both the construct, (the indicator measures the intended target), as well as the guidelines (there is close correlation between an indicator and the outcome or another measure considered the gold standard). In addition, previous experience in the application of an indicator provides some basis as to its acceptability or use thereof. Generally, users find an indicator helpful if variations in the values it presents are ​​due to changes in the quality of care, and vice versa.

As far as expert opinion is concerned, it is important to highlight the advantages to using consensus methods during the process of identification and selection of indicators, a highly participative course of action. In general, the process is based on a consensus-centred approach (i.e., a group of professional experts which may, in addition, incorporate opinions from a group of patients and users), which is subsequently extended to a larger body of associated groups. Thus, the involvement of a significant number of participants in reaching a consensus on indicators reinforces the embeddedness of the assessment strategy and collective responsibility, furthering the eventual adoption and implementation of the indicators.

Figure 1. Combination of methodologies for developing indicators

Methodologies Developing Indicators

How to implement indicators?

Once the indicators have been defined, there are several different approaches to their implementation. These include performance analysis and comparison between units of analysis, or benchmarking, whether this refers to organizations, centres, services, teams or professionals. The first approach seeks to analyse the relationship between health outcomes (in quantity and quality) and the resources utilized, in other words, the value of health care. The objective is to identify the gap between what might be achieved using existing technology and resources (efficiency, the maximum achievable potential), and what is actually being achieved (effectiveness), adjusted due to the available resources and other variables which impact the outcome.

Figure 2. An example of mapping indicators used to analyse performance. In this case, the graph maps the ratio of observed/expected cases for the indicator subject to the study for Basic Healthcare Areas (ABS, as per the Catalan acronym).

Mapping

Source: Metodologia dels atles de variacions en la pràctica mèdica del SISCAT. Atles de variacions del SISCAT, número 0. Barcelona: Agència de Qualitat i Avaluació Sanitàries de Catalunya. Departament de Salut. Generalitat de Catalunya; 2014.

Finally, if the process is taken to the next level, we find ourselves in the realms of benchmarking, which allows us to make a comparative assessment. Basically, this involves using any product, service or work process within an organisation and which manifest best practises in the area of interest and using it as “comparator” or benchmark. The objective of this process is to transmit information regarding best practices and their implementation.

Figure 3. Sample mapping of an indicator used to make comparisons between units of analysis (benchmarking)

Comparisons

Source: Metodologia dels atles de variacions en la pràctica mèdica del SISCAT. Atles de variacions del SISCAT, número 0. Barcelona: Agència de Qualitat i Avaluació Sanitàries de Catalunya. Departament de Salut. Generalitat de Catalunya; 2014.

Post written by Mireia Espallargues, Noemí Robles and Laia Domingo.