Applying interactive process mining to discover and optimise real clinical pathways, fostering a collaborative change to Value-Based Health Care

All health systems are faced with the challenge of managing increasing cases of chronic conditions among the populations they serve. This can put the sustainability of current systems at risk.[1]

Value-Based Health Care (VBHC) proposes an approach to care providers to deliver healthcare services providing value to patients, while keeping healthcare sustainable.[2]

VBHC establishes four key principles to transform healthcare:

•            Improvement of the patient experience

•            Improvement of staff satisfaction

•            Reduction of per capita cost of health care

•            Increasing the healthy population.[3]

VBHC aims to improve patient experience and staff satisfaction while reducing health expenditure. It does so by using a reimbursement model according to the effectiveness of the care interventions.

A successful implementation of VBHC will ultimately result in a more sustainable future healthcare system.[4] A system which cares for citizens throughout the care continuum, contributing to a better cared for, healthier population.

Digital transformation is needed to implement VBHC models. Digital tools help health professionals access and analyse data more effectively, aiding collaborative decision-making.

However, this transformation is not simple, and there are problems of acceptance on the part of the actors involved. These problems come from difficulty in the usability of the solutions.[5]

Solutions often use language that is unfamiliar to healthcare professionals, limiting their collaboration. And many have a black-box approach that does not explain the steps carried out, an issue of particular importance in the clinical field.[6]

VALUE to enable real collaborative transformations

The VALUE solution is a new framework, designed to support clinical, technical, and management staff to adopt VBHC approaches. It includes new technology and a new method. It involves health professionals from the beginning and fosters discussion among all the actors that participate in healthcare delivery.

The solution uses innovative interactive process mining techniques to advise on the real steps that patients should take. The VALUE dashboard provides easy-to-use interactive controls that report the issues according to performance or clinical indicators in an understandable way.

The solution can be customised by the health professionals that use it. This helps improves usability and allows decision making to be mapped in an intuitive and transparent way.

The definition of indicators, and later analysis, is performed interactively and iteratively with the clinical or management staff. This ensures real control and understating of what is the solution doing every time, avoiding the black-box effect.

The adoption of the VALUE solution by hospitals will boost a VBHC transformation overcoming most of the current barriers. It promises to provide a healthcare system focused on patients’ health as the key indicators.

VALUE and EIT Health: the right partnership to promote better healthcare

The EIT Health-supported VALUE initiative joins prominent clinical, industry, and academic and technical partners to support clinical pathway optimisation. A required step to change to a value-based healthcare model.

The initiative is aligned with EIT Health’s goal of promoting better health of citizens as it is focused on transforming health outcomes through the adoption of VBHC approaches. By improving the way health professionals collaborate, this transformation has the potential to improve patients’ experience of healthcare delivery and their quality of life.

Testimonials

“The potential of interactive process mining is its capability to empower health experts in the real understanding of the health process, allowing them to actually know their patients behaviour and measure the value chain of their decisions”. Carlos Fernandez-Llatas. Head of Interactive process mining for Health Lab (Universitat Politècnica de València, SP)

“We have huge databases but after understanding IPM, I consider we are at the Bronze Age”. Martin Holzmann. Function of Emergency care (Karolinska University Hospital, SE)

“It is the best solution to improve and understand the healthcare patient workflow”. Angeles Celda. Nurse, Emergency Medicine (Hospital General de València, SP)

“Learning IPM should be a must for all the Portuguese cardiologists”. Lino Gonçalvez. Cardiac Service Chief (Centro Hospitalar e Universitário de Coimbra, PT)

“Interactive process mining will be a key element for clinical pathway optimization. With the participation in VALUE project Medtronic will be one step ahead in the value-based healthcare transformation”. Rebeca Basurto. Head of Iberia consulting in Integrated Health solutions (Medtronic, SP)

“VALUE project offers us the possibility of enriching our digital transformation solution by integration new added value services for the healthcare domain”. Blanca Jordán. Health Sector Manager at Research and Innovation (ATOS, SP))

External Partners

• Erasmus Universitair Medisch Centrum Rotterdam
• Instituto de Investigacion Biomedica de Salamanca (IECSCYL-IBSAL)
• Stockholms Läns Landsting
• Agencia de Qualitat i Avaluació Sanitàries de Catalunya (AQuAS)
• Mysphera S.L.

References

[1] Who.int. 2021. Ageing and health. [online] Available at: <https://www.who.int/news-room/fact-sheets/detail/ageing-and-health> [Accessed 1 December 2021].

[2] Blackstone, E. and Fuhr, J., 2021. Redefining Health Care: Creating Value-Based Competition on Results.

[3] Hbs.edu. 2021. [online] Available at: <https://www.hbs.edu/ris/Publication%20Files/20050627%20IHI%20Impact%20Meeting%2006272005%20Final-NV_c5acc589-9f69-48db-9c64-75df74dc30a5.pdf> [Accessed 1 December 2021].

[4] Taylor & Francis. 2021. Insights on value-based healthcare implementation from Dutch heart care. [online] Available at: <https://www.tandfonline.com/doi/abs/10.1080/20479700.2017.1397307> [Accessed 1 December 2021].

[5] Shortliffe, E., 2021. Medical Expert Systems—Knowledge Tools for Physicians. [online] PubMed Central (PMC). Available at: <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1307157/> [Accessed 1 December 2021].

[6] Rudin, C., 2021. Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead. [online] Nature. Available at <https://www.nature.com/articles/s42256-019-0048-x> [Accessed 1 December 2021].