Module - Information and Knowledge Management (SBI125)

STP

Aim of this module

Trainees completing this module will be able to identify clinical concepts underlying the description of healthcare activity and represent them in a computable form. They will be able to represent a clinical decision in an appropriate formalism and be able to assess data quality. Students will understand what knowledge is, and how knowledge can be harnessed to improve the quality of clinical care. By the end of the module students will know the various forms in which clinical knowledge exists and can be accessed and shared, including the main principles underpinning clinical coding and the design of knowledge management systems. They will understand the ways in which knowledge is used in decision making, and how knowledge can be formally represented. In addition, trainees will have a sufficient understanding of the nature of health record information, and the ways in which such information might formally be represented and managed and shared electronically, to equip them to play an active role in the design, development, procurement, or adoption of electronic health record (EHR) systems in their future careers. Trainees will also know about the requirements for rich interoperability between EHR systems. This module will enable the trainee to identify clinical concepts underlying healthcare activity, including healthcare science and represent them in a computable form. They will represent a clinical decision in an appropriate formalism and assess the quality of the data. Trainees will apply their understanding of what knowledge is, and how knowledge can be harnessed to improve the quality and safety of clinical care. The trainee will formally represent information and knowledge and apply decision analysis techniques to the use of large NHS data sets to inform clinical and service decision making. 

Work-based learning outcomes

  1. Examine a work based related dataflow and review how data are collected, analysed and used to support care, research and healthcare management within the organisation, including a healthcare science service.
  2. Examine how large NHS data sets are created and used to support research and critical evaluation of practice, make funding decisions and contribute to the formulation and delivery of plans and strategies for meeting health and social care.
  3. Analyse the strengths and weaknesses, from a data perspective, of activity-based funding mechanisms.
  4. Assess the strengths and weaknesses of SNOMED CT, ICD 10 and OPCS5, and present the analysis and the findings in a written report.
  5. Review the challenges involved in coding clinical encounters; assess what kind of granularity of coding is practical and present at a team or departmental meeting.
  6. Represent a healthcare problem as a decision tree, including, where possible, the views of patients, and use the decision tree to inform the solution to the healthcare or healthcare science problem.

Work-based Competencies

Learning outcome Title Knowledge
1 1, 2, 3, 4, 5, 6

Apply information governance principles and best practice in the workplace, including confidentiality.
  • The legislation, regulatory guidance and NHS protocols regarding the security, confidentiality and appropriate sharing of patient identifiable information.
  • Role of the Caldicott Guardian.
  • The different arrangements and the associated responsibilities of clinical staff for security of all types of clinical information, especially electronically held, and for using such data for ‘secondary’ purposes.
2 1

Examine a dataflow and review how data are collected, analysed and used to support care, research and health and care management within the organisation.
  • Data flows in the NHS and social care and support landscapes.
  • Data and information (structured and unstructured) analysis methodologies and techniques.
  • National data sets and models.
  • Data collection methodologies.
  • Data reporting and presentation tools and techniques.
  • Quantitative outcomes measures and their application.
  • Management information systems.
  • Safety and security.
  • Links between data, information and insights.
3 1

Present your findings in a written report and verbally to your line manager and peers.
  • Critical appraisal techniques.
  • Knowledge representation.
  • Data visualisation techniques.
  • Predictive modelling techniques.
  • Knowledge management techniques and approaches.
4 2

Critically evaluate how large NHS data sets are created and used to support research and make funding decisions.
  • Data mining techniques.
  • Data warehousing.
  • Transparency: challenges and solutions.
  • Secondary uses of data.
  • Role of national data collection and analysis services.
  • Application of data in national commissioning strategy and planning.
  • Transparency – challenges.
  • Information governance and ethical considerations.
5 2

Work with a clinical team and discuss the perceived strengths and weaknesses of large NHS data sets.
  • Data mining techniques.
  • Data warehousing.
  • Transparency: challenges and solutions.
  • Secondary uses of data.
  • Role of national data collection and analysis services.
  • Application of data in national commissioning strategy and planning.
  • Transparency – challenges.
  • Information governance and ethical considerations.
6 2

Critically evaluate how data are used to support research and critical evaluation of practice.
  • Data mining techniques.
  • Data warehousing.
  • Transparency: challenges and solutions.
  • Secondary uses of data.
  • Role of national data collection and analysis services.
  • Application of data in national commissioning strategy and planning.
  • Transparency – challenges.
  • Information governance and ethical considerations.
7 2

Present your findings in a written report and verbally to your line manager and peers.
  • Presentation options for different audiences.
  • The characteristics of effective and high-quality health initiatives from a patient perspective.
8 3

Analyse the strengths and weaknesses, from a data perspective, of activity-based funding mechanisms.
  • Uses of data in activity-based funding.
  • Alternatives to activity-based funding.
  • Examples of activity-based approaches.
  • Pros and cons of activity-based mechanisms.
9 3

Propose changes to the use of data in activity-based funding mechanisms within your local health environment.
  • Uses of data in activity-based funding.
  • Alternatives to activity-based funding.
  • Examples of activity-based approaches.
  • Pros and cons of activity-based mechanisms.
10 4

Assess the relative strengths and weaknesses of SNOMED CT, ICD 10 and OPCS5.
  • The nature and purpose of different coding and classification systems in health.
  • Uses of coding and classifications systems.
  • Pros and cons of each.
11 4

Present the analysis and the finding in a written report, making judgements in relation to the strength of the evidence.
  • Data analysis techniques.
  • Presentation options for different audiences.
12 5

Review the challenges involved in coding clinical encounters and include an assessment of the kind of granularity provided by each coding system.
  • Coding and data quality issues.
  • Different approaches to coding practice.
  • The role of clinicians in coding and classification.
  • Uses of coded data.
13 5

Write a short report summarising your findings and present the key messages at a team or departmental meeting.
  • Report writing.
  • Presentation techniques.
  • How to respond to questions.
14 6

Represent a healthcare problem as a decision tree.
  • Decision support methodologies and their application.
  • Nature of decision trees.
  • Knowledge representation theory and practice.
  • Application of mathematical approaches to machine learning.
15 6

Use the decision tree to develop new guidelines to solve the healthcare problem.
  • Structure and content of clinical guidelines.
  • Uses of decision trees in health and care.

Work-based assessment

Complete 2 Case-Based Discussion(s)
Complete 3 of the following DOPS and/or OCEs
Type Title
DOPS Present the three main coding systems SNOMED CT, ICD 10 and OPCS 5 to a non coding scientific audience, with particular emphasis on the improvement of data quality and the uses of data
DOPS Present to healthcare professionals in your organisations the uses of healthcare data and why data quality is important.
DOPS Construct a decision tree to represent a healthcare problem
OCE Undertake some clinical coding from patient notes and compare your results to that of the professional coders