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Saudi Ministry of Health sets global example with Ada’a performance measurement model

Effective performance management is essential in business, irrespective the size, type or industry in which it operates.  Yet few organizations can get performance measurement right; the slightest difference in methodology can produce huge differences, and rankings aren’t always consistent.

That was the challenge for the Saudi Ministry of Health, who wanted to rank more than 100 of its hospitals across the Kingdom based on more than 40 key performance indicators (KPIs). Assessing hospitals is a key element of Ada’a, the Ministry’s massive hospital digitization and transformation project – the first system-wide hospital transformation of this scale in the world.

The complexity of the challenge is even bigger, because the Ministry, and its decision makers, need the ranking to be fair to the unique characteristics of each hospital – whether a small 40-bed rural facility or giant 2,000-bed urban medical city. It also must address the different importance of each of more than 40 key performance indicators (KPIs) being collected about each hospital.

What’s more, the ranking must be able to explain to Ministry decision makers why a hospital gets a good or bad rank, and to do so in a way that allows them to take action to help lower-performing hospitals improve and help high-performing hospitals to keep doing well.

Solving such a challenge is as complicated as it sounds. The Ministry, with help from partners had tried to figure this out. But a project lead by GE Healthcare Partners suggested a novel approach.

They proposed using “stochastic multicriteria acceptability analysis,” a complex form of machine learning designed for multiple-criteria decision-aiding regarding problems with incomplete, imprecise or uncertain information.

With the involvement of Ministry officials, including authors Al Aama Tareef,Mohammed Alabdulaali, Mohammed AlHarbi and Abdulaziz Sawan, the research project was led by Ali Alessandro Ayach, a Senior Director at GE Healthcare Partners. It received critical research expertise and contributions from professors from the University of Siena and the University of Rome in Italy, as well as GE Healthcare Partners leadership in the region, which gave Ayach the resources, time and operational support to pursue this project to its successful outcome.

The result is an extremely sophisticated machine learning algorithm that, when tested using real data against 10 million scenarios, delivered a 90% success rate, reflecting an exceptionally strong performance, Ayach explained. The importance of the breakthrough is such that the research paper detailing the solution has already been presented at well-respected academic conference and accepted for publication in peer reviewed – high impact factor scholarly journals.

“The beauty of this methodology is that it leverages multi-criteria decision-making. The more criteria, the more complex the decision-making.  No healthcare system globally has ranked hospitals before in this way.  Saudi Arabia’s Ministry of Health has created a reliable model that is truly an example for the world to follow,” said Ayach, also a lecturer and researcher in the Department of Decision Science at the University of Rome, Faculty of Managerial and Industrial Engineering; a member of the European Decision Science Institute; and a scientific reviewer for the International Forum for Knowledge and Asset Management.

The significance of the results is such that the authors believe this is the first time globally that the SMAA approach has been used to solve for complex decision-making and ranking outside the field of nuclear energy.

The tool not only gives decision makers excellent information with high reliability, but does so in a way that coalesces the more than 40 KPIS into just six or eight “composite KPIs”. That kind of simplicity and clarity—and the model built—serves as an important decision-making tool for Ministry policy makers who look at resource allocation, branding to create competitive advantage, leadership and administration. In other words, it means the Ministry can know with high confidence that a decision to give support to various hospitals will not only help those hospitals but also deliver an overall improvement to healthcare Kingdom wide.

This latter point is one reason the tool has potential applicability in other aspects of healthcare and in many other industries as well.

That’s because, conventionally, in large complex organizations, overall organizational performance is incentivized by setting KPIs for each unit or division within the organization. Each unit does whatever it takes to meet its KPIs, irrespective of whether or not it’s good for other divisions or the overall organization.

This tool can help boards of directors and other strategic decision makers in these organizations identify such unintended consequences, and create better visibility into what each unit needs to achieve in order to ensure that not just the business unit, but the whole organization achieves better outcomes.

GE Healthcare Partners brings a wealth of global and local expertise to the collaboration, as it currently is supporting the Saudi Ministry of Health on its Ada’a program, a radical hospital culture and performance transformation initiative that is driving efficiency and productivity across more than 150 Ministry hospitals, more than 730 Primary Healthcare Centers, and 4 medical cities, then reinvesting the savings into patient care. The project is a strategic priority for the Ministry.

Business: Healthcare

Country: Saudi Arabia

Keywords: Ada’a, Machine Learning, Research

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