Key concepts

What is actionable knowledge?

Actionable knowledge involves processing and packaging knowledge into decision-ready formats that can be acted upon to solve problems.  In the health and social care context this often means decision-ready tools that support decisions about patient care and improving services.

Examples might include mobile apps, clinical guidelines presented as visual pathways, shared decision aids, prompts and reminders in electronic care record systems, risk scoring tools and calculators, evidence summaries with action-focused recommendations, infographics.

‘Actionable knowledge is not only relevant to the world of practice, it is the knowledge that people use to create that world.' (Argyris, 1993). 

ARGYRIS, C., 1993, Knowledge for Action: A Guide to overcoming barriers to organizational change. San Francisco, Calif.: Jossey-Bass Inc.

How do I provide evidence of competency in this area? 

Can you...

• Analyse, evaluate and produce a range of types of actionable knowledge examples - could include infographics, data visualisation which makes recommendations for action clear, as well as more familiar forms of decision support - (e.g. concise recommendations for action based on validated evidence, presented in web or mobile format; prompts embedded in EHR systems)? 

What are digital knowledge resources?

Digital knowledge resources includes all sources where the information is available in digital formats and accessible with a help of computers. Examples include library resources published in digital format, such as e-journals,  e-books, and PDF reports as well as webs pages, blogs, digital video and audio recordings.

Importantly, digital knowledge resources are human-readable - i.e. they can be easily read and understood by humans. This is in contrast to machine-readable knowledge, which is structured so that computers can process it. Computable knowledge, described in the competency below, is based on machine-readable knowledge. 

Decision support tools exist in both formats.  Digital knowledge resources such as web pages providing guidelines, pathways and formularies are decision support tools.  Machine-readable knowledge such as calculators and scoring tools are also forms of decision support.

How do I provide evidence of competency in this area? 

Can you...

• Analyse, evaluate and create a variety of human-readable, computer-based decision support products and materials, working within and leading teams throughout the knowledge into action cycle? 

• Work with data whether unstructured, semi-structured or coded to analyse and evaluate ways in which that data might be translated into human-readable computerised knowledge? 

What’s Computer-executable knowledge?

Computer-executable  knowledge is structured in a format that can be reasoned with or processed by a computer to carry out a task. It is sometimes called computable or computational knowledge.

‘Computer-executable knowledge’ is held in a way that can be used by a computer when it is working on a task. (Wyatt and Scott, 2020)

WYATT, J. and SCOTT, P., 2020. Computable knowledge is the enemy of disease, BMJ Health Care Inform, 27(2)

Translating narrative clinical knowledge such as guidelines, recommendations and evidence summaries into computable knowledge such as executable code or models is a key goal of decision support. Computer-executable knowledge requires:

1) Knowledge to be written in a format that can be read by computers - usually as computer code or a model.

2) A software application to read and process the knowledge and deliver outputs. For example, this could be a drug dosage calculator, a risk scoring tool, or a system that delivers prompts and alerts in electronic care record systems. 

How do I provide evidence of competency in this area?

Can you...

• Analyse, evaluate and create computer-executable knowledge-based applications, support products and materials, working within and leading teams throughout the knowledge into action cycle? 

What is the relationship between decision support and artificial intelligence (AI)?

Decision support uses two main types of artificial intelligence:

1) Knowledge –based expert systems 

These are a long-established form of AI, dating back to the 1950s. They are still widely used in healthcare, in calculators, scoring tools and prompts and reminders and electronic care record systems. Knowledge-based expert systems are:

• Created by humans based on well-defined knowledge structures.
• Often based on algorithms derived from validated and transparent evidence. 

2) Machine learning

• Machine learning is less structured and controlled than knowledge-based AI. In simple terms, machine learning involves feeding data into a computer and seeing what insights the computer provides. Machine learning can provide insights beyond human analysis of data, however it can be less transparent and harder to validate.

The Right Decision Service currently uses knowledge-based expert systems - for example, for calculators, scoring tools and prompts within electronic care record systems.  It is exploring use of machine learning and in time it is likely to make more use of machine learning as well. 

How do I provide evidence that I understand the relationship between decision support and artificial intelligence?

Can you...

• Analyse, evaluate and create DSS applications, support products and materials, working within and leading teams throughout the knowledge into action cycle? 

• Within the Scottish context – show detailed knowledge of the RDS, definitions, applications etc.? 

What are algorithms and decision trees – knowledge-based and computer-generated?

How do I provide evidence of competency in this area?

Can you...

• Design, develop and deploy: a) algorithms created by domain experts or based on validated guidance and evidence; and b) algorithms generated automatically by computation of large datasets? 

• Produce algorithmic systems that underpin a range of different types of decision support - from human-readable clinical and care pathways to structured rules that process patient data in standalone apps or in electronic health record systems? 

What are knowledge-based expert systems?

An expert knowledge-based system is a computer system which emulates the decision-making ability of a human expert. These systems:

• Use a form of artificial intelligence
• Are based on structured knowledge created by humans, often  in the form of algorithms and decision trees.
• Are derived from a body of explicit, validated knowledge.

In healthcare, knowledge-based expert systems may include calculators, risk scoring tools and screening tools, interactive question and answer systems, and patient-specific prompts in electronic health record systems.  The Right Decision Service provides many 

How do I provide evidence of competency in this area? 

Can you...

• Analyse, evaluate and produce expert systems, working with and leading teams throughout the knowledge into action cycle? 

What are neural networks and machine learning?

Machine learning is one type of artificial intelligence (AI). It creates computer systems that are able to learn and adapt without following explicit instructions. It achieves this by using computer-generated algorithms and statistical models to analyse and draw inferences from patterns in data. 

A neural network uses a particular type of machine learning process to process data in a way that is inspired by the connections between neurons in the human brain. The term "deep learning" refers to machine learning processes that use multiple layers within a neural network. 

IBM, 2023a-last update, IBM. Available: https://www.ibm.com/topics/machine-learning#:~:text=Machine%20learning%20is%20a%20branch,rich%20history%20with%20machine%20learning. [Dec 11, 2023]

IBM, 2023b-last update, IBM. Available: https://www.ibm.com/topics/neural-networks#:~:text=Neural%20networks%2C%20also%20known%20as,neurons%20signal%20to%20one%20another [Oct 31, 2023]

How do I provide evidence of competency in this area? 

Can you...

• Have a working knowledge of machine learning, neural networks and deep learning operate, and of the relationships between these concepts? 

• Participate in and lead machine-learning projects throughout the development lifecycle, to develop applications, support products and materials? 

What is natural language processing?

Natural language processing (NLP) is a machine learning technology that gives computers the ability to interpret, manipulate, and comprehend human language. Common examples include:

• Email filters. 
• Smart assistants.
• Search engines such as Google
• Predictive text.
• Automated language translation tools

IBM, 2023-last update, IBM. Available: https://www.ibm.com/topics/natural-language-processing#:~:text=Natural%20language%20processing%20(NLP)%20refers,same%20way%20human%20beings%20can [Oct 31, 2023]

How do I provide evidence of competency in this area? 

Can you...

• Have a working knowledge of natural-language programming and ability to analyse, evaluate and create applications, support products and materials using these skills?