The slideshare is the first lecture in a series on Managing Information in Health by the Author at Kingston University London on the MSc Course. The topic of the first lecture was the management of information and the way data is presented.

1. Royston E Morgan
BHM 303 Managing Information in Health
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2. Module Objectives
 to develop an ability to understand and use information as a
strategic resource in supporting the delivery of health and social
care services.
 to provide students with an understanding of the changing role of
information and communications technology (ICT) in the light of
structural changes in the NHS and social care.
 to examine the enabling role of IT in facilitating communication
and collaboration among professionals and patients in the health
and social care sectors.
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3. Session objectives
 Outline the module and rationale
 Discuss the use of information as a strategic resource in health
 Evaluate the role of information and related systems in health
services
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4. Can we distinguish Data Information or Knowledge?
 Data as a collection of facts
 Information as facts used to plan
or to take an action
 Knowledge?
Can it be also?
 Gossip?
 Intuition?
 Spreadsheets?
 Surveys?
 News reports?
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5. Why do we need information?
 Advances our understanding of complex situations
 Provides warning signs
 Reduces uncertainty
 Helps us to provide appropriate solutions
 Offers historical evidence
 Aids communication
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6. Reflect: what is meant when we say data is useful?
Is it
Can we discuss
 accurate, some examples of
 reliable, when these things
do/don’t happen
 relevant, and what the impact
is?
 timely,
 Accessible,
 etc?
Let’s consider different perspectives on
data…
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7. Much of the information managed by professionals
is contextualised
 In the specific context of use
In the actual case or problem being addressed
The same terms in a different context can carry a different meaning
In the specific mode of practice (can vary across countries for example)
 In the use of assumed (implicit) knowledge of the creator and user of the
information
Much recorded data by professionals assumes a background knowledge by the reader
so that comprehensive exposition is not needed
This can mean the use of the data is local to the situation and it can be difficult to use
the same data for other things
 By using a constrained (understood) vocabulary
Seen by acronyms or codes which can be very localised
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8. Much of the information needed by IT
professionals is specified
 Must be as far as possible generic
Covering a broad spectrum of uses
The same terms must be used in the same way (may imply practice change) but …
…Different modes of treatments must be acknowledged
 The use of assumed knowledge by users makes ‘its’ use in systems
complex
For interpretation or use outside the specific clinical context the assumed knowledge
may have to be declared
Data must be comparable across the organisation so that meaningful analysis and
comparison can be made (so how and who?)
 By using a open (codified) vocabulary
Data elements (codes) are defined in data dictionaries for example to avoid ambiguity
Generic free-text entries are a ‘no-no’ to most IT developments
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9. Much of the information managed by large
organisations created at A is needed at B
 Health Care workers create and manage information for their use
at the point of use
Managing the clinical trajectory through diverse departments (for
example using the Patient Record)
To coordinate the professional task…
…and is heavily contextualised and collective
 For other consumers of the information
Supplemental data is needed to make ‘it’ understandable and useable
Information can only be added at front end by people who may find
no value from doing so
 A core issue in managing information in organisations is getting
ownership of data
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10. So what do we think is information in Health
Care?
 Lets first discuss and draw-up a
list
in two groups first then plenary.
 You are a clinical practitioner or a
manager at an acute hospital
What information do you think
you might need to manage care?
What information do you think
you need to manage the
organization?
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11. Benchmarking in the health sector is a structured
approach to sharing and comparing practice….
 Figures on their own are often not informative
 How good or bad are we compared with others?
 If others are doing better, can we find out why?
 If we are doing really badly relative to others, can we change?
 What might inhibit us from improving further?
 National standards may seem ‘imposed’ but mostly aim to
improve quality
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12. A benchmarking process
1. Agree focus
2. Set baseline
3. Describe best practice
4. Assess current position
5. Compare (and share to
reach consensus on target)
6. Determine Action Plan
1. Review and revise
7. Tell ‘everyone’
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13. SCORING A BENCHMARK
WORST BEST
PRACTICE PRACTICE
Worst STEPS TOWARDS Best
Practice BEST PRACTICE Practice
E D C B A
1 2 3 4 5
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14. But where did the information come from?
 Accuracy and precision of data sources?
 How up to date is the data?
 Are the samples similar to your organisation?
 Are different types of organisation benchmarked or is it across the
board?
 Is there sufficient information about data collection, sampling
etc., for you to know?
 Are other sources and/or references cited?
 Who has assessed data quality?
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15. National Service Frameworks – information only
part of the story
Information
Expectations through
& skills Role of care technology
Attitudes to professions
private care
Older Older
People NSF People
2001 2011
Public Medical Assistive
attitudes Developments technologies
to age
Government
policies
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16. Is presenting (or collecting) data a neutral act?
Presentation of data is concerned with three parts:
 Selection of relevant data
 Representation of data
 Purpose of presentation
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17. Example: CHD NSF information processes
 Obligation is for (virtual) registers
established CHD
evidence of non-cardiac arterial disease
Heart failure plus
CHD risk factors
 Information Strategy addresses
patients, carers and the public
health professionals delivering care
clinical governance, performance mgt, service planning, public health
CHD NSF : national service framework for coronary heart disease
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18. Primary Care Trusts (now GP’s I think) and CHD
 What information do GP’s need?
 What do they need to know about CHD?
 From where can they get this information?
 How do they know if it is reliable?
 http://www.chd.org.uk/intro-nsf-intro.htm
 And why is it needed what is the purpose?
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19. Dental Survey Statistics 2007 versus 2006
 12% brush 'a few times a week'
or 'never'
 Only 30% say they brush for two
minutes
 17% 'can't remember' when
they last changed their brush
 60% of people would share their
brush with their partner, child,
friend or favourite celebrity
… And13% of respondents from Newcastle
from East Enders compared to 76% in Nottingham brush for the
2 mins recommended!
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20. And the strange things people floss with:
 Drill bit
How should
 Saw you interpret
 Shoelaces this?
 Hammer
 Fish bones
 Fork
 Twig
 Safety pin
 Toe nails
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21. Survey concerns include
 Response rates
 Sample and respondent bias
 Validity
 Reliability
 Imposing concepts on to the subject
 Assumptions around participant interpretation
 Their desire to find meaning and either help or outfox the researcher
 Scales and measurements
 The power of reporting statistics…
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22. Validity in surveys
 Construct validity vital (do we really measure what we mean to)
 Wording (avoidance of leading, loaded, double-barrelled or
confusing questions)
 Response bias
 Social desirability
 Respondent interpretation of questions
 ‘Face’ Validity also important for responses
 Ordering of questions (can randomise with online versions)
 Predictive validity – hardly every discussed!
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23. Reliability in surveys
 Pilots (with full feedback and modify) are vital
 Test-retest (but, time and experience of previous survey may have
changed)
 Split half (can only be done with some types of instruments).
 Internal scales (Cronbach’s alpha) but remember this only means
that each scale is measuring a similar thing…
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24. Beware of how data is presented
70
60
50
40 East
30 West
North
20
10
0
1st Qtr 2nd Qtr 3rd Qtr 4th Qtr
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25. Check the scales etc.
70
65
60
55
50
East
45
West
40
North
35
30
25
20
1st Qtr 2nd Qtr 3rd Qtr 4th Qtr
What else is wrong with this chart?
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26. Be aware of relevant propositions
Consider the statement ‘Chimpanzee DNA is
99.7% the same as Human DNA’
What does this statement mean what
inferences can be drawn?
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27. Be aware of relevant propositions
Do chimpanzees make cars/houses/PCs/ or give lectures in
Information Management that are 99.7% as good as those made
by humans?
 Or…
A lot of DNA is not involved in the development process and this is
being included in measurements
 Or …
A small change in DNA has a large impact on what is produced
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28. Be very aware of Statements of the form:
A is the greatest cause of B
 In the UK car crashes are the single greatest cause of deaths
among males in their 20s and 30s
 This is meaningless as there is no reference with which the scale
the statement
 The purpose of the statement is to create an atmosphere of
severity – and something must be done!
 It is at best not justified or at worst incorrect
 The Data…
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29. What does the data tell us?
The underlying life expectancy data shows that young people have very little chance of dying
and death rates are uniformly very low after the first year of life until about age 50.
So a statement such as ‘Car crashes are the greatest cause of deaths among males in their
20s and 30s will inevitably be true because nothing else really kills young males. Death due
to illness is uncommon among this group so any other cause will dominate.
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With acknowledgement to Alan McSweeney alan@alanmcsweeney.com Slide 29

30. When thinking about how data is presented in the
form of statistics
 Correlation is not causality
Number of drunks in a town and number of Conservative Party
members
 Significance tests generally flawed
 Look carefully at sampling and method
 You will learn much more about this in research methods too –
but it is not only about your own research – we are bombarded
with statistics these days…critique them carefully and remember
our session on risk!
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