Managing information health
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Transcript of Managing information health
Slide 1 Crosslight Management
Royston E Morgan
BHM 303 Managing Information in Health
Slide 2 Crosslight Management
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.
Slide 3 Crosslight Management
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
Slide 4 Crosslight Management
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?
Slide 5 Crosslight Management
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
Slide 6 Crosslight Management
Reflect: what is meant when we say data is useful?
Is it
accurate,
reliable,
relevant,
timely,
Accessible,
etc?
Can we discuss
some examples of
when these things
do/don’t happen
and what the impact
is?
Let’s consider different perspectives on
data…
Slide 7 Crosslight Management
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
Slide 8 Crosslight Management
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
Slide 9 Crosslight Management
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
Slide 10 Crosslight Management
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?
Slide 11 Crosslight Management
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
Slide 12 Crosslight Management
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’
Slide 13 Crosslight Management
SCORING A BENCHMARK
WORST BEST
PRACTICE PRACTICE
STEPS TOWARDS
BEST PRACTICE
E D C B A
1 2 3 4 5
Worst
Practice
Best
Practice
Slide 14 Crosslight Management
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?
Slide 15 Crosslight Management
National Service Frameworks – information only part of the story
Older
People
2001
Older
People
2011 NSF
Expectations
& skills
Public
attitudes
to age
Attitudes to
private care
Medical
Developments
Role of care
professions
Assistive
technologies
Information
through
technology
Government
policies
Slide 16 Crosslight Management
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
Slide 17 Crosslight Management
CHD NSF : national service framework for coronary heart disease
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
Slide 18 Crosslight Management
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?
Slide 19 Crosslight Management
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 from East Enders
… And13% of respondents from Newcastle
compared to 76% in Nottingham brush for the
2 mins recommended!
Slide 20 Crosslight Management
And the strange things people floss with:
Drill bit
Saw
Shoelaces
Hammer
Fish bones
Fork
Twig
Safety pin
Toe nails
How should
you interpret
this?
Slide 21 Crosslight Management
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…
Slide 22 Crosslight Management
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!
Slide 23 Crosslight Management
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…
Slide 24 Crosslight Management
Beware of how data is presented
0
10
20
30
40
50
60
70
1st Qtr 2nd Qtr 3rd Qtr 4th Qtr
East
West
North
Slide 25 Crosslight Management
Check the scales etc.
20
25
30
35
40
45
50
55
60
65
70
1st Qtr 2nd Qtr 3rd Qtr 4th Qtr
East
West
North
What else is wrong with this chart?
Slide 26 Crosslight Management
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?
Slide 27 Crosslight Management
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
Slide 28 Crosslight Management
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…
Slide 29 Crosslight Management
What does the data tell us?
With acknowledgement to Alan McSweeney [email protected]
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.
Slide 30 Crosslight Management
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!