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.
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In today's post I share my Top 10 Best Mobile. Presentations. Mobile Database Spatial databases provide structures for storage and analysis of spatial data; Spatial ... quickest route to victim
Advanced Analytics Systems for Smarter Benefits, Claims, and Entitlement Mana...IBM Government
This IBM white paper introduces the field of analytics, and discusses how analytics can be utilized in claims and benefits processing systems. It also provides an example of an advanced analytics system developed for the U.S. Social Security Administration.
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This session was recorded in NYC on October 22nd, 2019 and can be viewed here: https://youtu.be/7h61dxKjhvg
Machine learning in finance—the promise and the peril
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Bio: Leading projects to apply machine learning and artificial intelligence across the firm. Evaluating opportunities to work with other organizations and consulting with clients.
There is a necessity of formal risk management. A formal risk management procedure gives numerous
profits to both the project group and the improvement association in general. Initially, it provides for them
an organized component to give conceivability into dangers to project triumph. By acknowledging the
potential effect of each one risk thing, we can concentrate on regulating the most intense risks first. We can
convey risk evaluation with project estimation to quantify a conceivable schedule slippage if certain risks
emerge into issues. Knowledge Management currently gets more considerations because of its assurance
that learning from the past will generally assist software engineers make good decisions in uncertainty.
This methodology helps the project supervisor creates sensible possibility supports. The point when data
requirements are different than actual requirements, either as a result of wrong SRS understandings or
mid-requirement changes to SRS as part of the requirement updating are occupied, excessively
troublesome to use, excessively challenging to decipher, or they essentially do not introduce of service or
significant data, chiefs should principally depend on experience and instinct for discriminating choice
making.
Data analysis has transformed the way organizations and individuals make decisions. As the volume of data continues to grow exponentially, the need for data-driven insights has become increasingly critical. However, raw data, no matter how extensive, can often be overwhelming and challenging to interpret. This is where the concept of data storytelling comes into play. In this comprehensive exploration, we will delve into the essence of data storytelling, its significance in data analysis, the key elements that constitute an effective data story, and practical tips for implementing data storytelling techniques.
Week Seven: Managing Knowledge
Information Resource Management
IT620
February 22, 2014
Running head: MANAGING KNOWLEDGE 1
MANAGING KNOWLEDGE 3
MANAGING KNOWLEDGE 2
Managing Knowledge
Chapter 14: Question 3. How do human capital, structural capital, and customer capital differ?
ANSWER.
Human capital, structural capital and customer capital are three basic fundamentals of any organization. They differ in their roles playing for that organization. Human capital is the efficiency of a human being on the basis of its skills; more the human is skilled and efficient results in more human capital. On the structural capital is the efficiency of the organizations to provide environment in which they can increase the efficiencies of humans working for them such as data, systems, knowledge and designs. The customer capital is the relationship bond with organization products, stronger the bond between the customer and the products results in a stronger customer capital.
Chapter 14: Question 8. What approach did the energy company take to encourage knowledge sharing among its 15 business units?
ANSWER.
The approach that the energy company took to encourage sharing among its 15 business units was establishing peer groups from various units. The idea was to have employees share his or her knowledge without the involvement of leadership to avoid political aspects. Since this was unsuccessful it was decided to provide a human portal for employees where they can ask questions regarding the problems they faced with their customers and employees from other business units provides a solution to them, its kind knowledge sharing between the organizations from different business units. They also gave a chance to their employees to meet with the other employees from different business unit so that they share their experience for the growth of their particular business unit.
Chapter 14: Question 10. What three questions does Stewart recommend be asked before launching a knowledge management project?
ANSWER
The three questions that Stewart recommends to be asked before launching a knowledge management project are listed as follows:
Listing out the group that will use this knowledge space and make them responsible for all the content they are going to post on that knowledge space.
The type of knowledge groups was going to share on the knowledge space and who will manage the context that the employees were discussed on the knowledge space.
He also raises the question of the culture that the organization is going to adopt, will that be composed of reusers or originators because he stated both are different because a repository of things promotes a reuse culture; an online chat room helps originators, but this is not going to happen opposite.
Week 7 - Managing Knowledge
Due Date: Sat, Feb 22, 2014 11:55 PM MST
Write answers to the following textbook questions located at the end of each chapter. Each answer should be approximately 70 words, or a total of appr.
Data literacy is now a sought-after ability for many workers. To begin, leaders must be aware of data literacy and develop a common language for learning.
How to Create a Big Data Culture in PharmaChris Waller
A talk presented at the Big Data and Analytics conference in Boston on January 28, 2014. Emphasis on data and information sharing cultures in companies.
Keynote by Charles Elkan, Goldman Sachs - Machine Learning in Finance - The P...Sri Ambati
This session was recorded in NYC on October 22nd, 2019 and can be viewed here: https://youtu.be/7h61dxKjhvg
Machine learning in finance—the promise and the peril
This talk will discuss how machine learning (ML) fits into the landscape of quantitative methods used in finance, and draw conclusions about application domains where ML is more promising versus domains where the perils are more acute. The talk will also discuss how to formulate a financial goal as an ML problem, and how to choose between solution approaches.
Bio: Leading projects to apply machine learning and artificial intelligence across the firm. Evaluating opportunities to work with other organizations and consulting with clients.
There is a necessity of formal risk management. A formal risk management procedure gives numerous
profits to both the project group and the improvement association in general. Initially, it provides for them
an organized component to give conceivability into dangers to project triumph. By acknowledging the
potential effect of each one risk thing, we can concentrate on regulating the most intense risks first. We can
convey risk evaluation with project estimation to quantify a conceivable schedule slippage if certain risks
emerge into issues. Knowledge Management currently gets more considerations because of its assurance
that learning from the past will generally assist software engineers make good decisions in uncertainty.
This methodology helps the project supervisor creates sensible possibility supports. The point when data
requirements are different than actual requirements, either as a result of wrong SRS understandings or
mid-requirement changes to SRS as part of the requirement updating are occupied, excessively
troublesome to use, excessively challenging to decipher, or they essentially do not introduce of service or
significant data, chiefs should principally depend on experience and instinct for discriminating choice
making.
Data analysis has transformed the way organizations and individuals make decisions. As the volume of data continues to grow exponentially, the need for data-driven insights has become increasingly critical. However, raw data, no matter how extensive, can often be overwhelming and challenging to interpret. This is where the concept of data storytelling comes into play. In this comprehensive exploration, we will delve into the essence of data storytelling, its significance in data analysis, the key elements that constitute an effective data story, and practical tips for implementing data storytelling techniques.
Week Seven: Managing Knowledge
Information Resource Management
IT620
February 22, 2014
Running head: MANAGING KNOWLEDGE 1
MANAGING KNOWLEDGE 3
MANAGING KNOWLEDGE 2
Managing Knowledge
Chapter 14: Question 3. How do human capital, structural capital, and customer capital differ?
ANSWER.
Human capital, structural capital and customer capital are three basic fundamentals of any organization. They differ in their roles playing for that organization. Human capital is the efficiency of a human being on the basis of its skills; more the human is skilled and efficient results in more human capital. On the structural capital is the efficiency of the organizations to provide environment in which they can increase the efficiencies of humans working for them such as data, systems, knowledge and designs. The customer capital is the relationship bond with organization products, stronger the bond between the customer and the products results in a stronger customer capital.
Chapter 14: Question 8. What approach did the energy company take to encourage knowledge sharing among its 15 business units?
ANSWER.
The approach that the energy company took to encourage sharing among its 15 business units was establishing peer groups from various units. The idea was to have employees share his or her knowledge without the involvement of leadership to avoid political aspects. Since this was unsuccessful it was decided to provide a human portal for employees where they can ask questions regarding the problems they faced with their customers and employees from other business units provides a solution to them, its kind knowledge sharing between the organizations from different business units. They also gave a chance to their employees to meet with the other employees from different business unit so that they share their experience for the growth of their particular business unit.
Chapter 14: Question 10. What three questions does Stewart recommend be asked before launching a knowledge management project?
ANSWER
The three questions that Stewart recommends to be asked before launching a knowledge management project are listed as follows:
Listing out the group that will use this knowledge space and make them responsible for all the content they are going to post on that knowledge space.
The type of knowledge groups was going to share on the knowledge space and who will manage the context that the employees were discussed on the knowledge space.
He also raises the question of the culture that the organization is going to adopt, will that be composed of reusers or originators because he stated both are different because a repository of things promotes a reuse culture; an online chat room helps originators, but this is not going to happen opposite.
Week 7 - Managing Knowledge
Due Date: Sat, Feb 22, 2014 11:55 PM MST
Write answers to the following textbook questions located at the end of each chapter. Each answer should be approximately 70 words, or a total of appr.
Data literacy is now a sought-after ability for many workers. To begin, leaders must be aware of data literacy and develop a common language for learning.
How to Create a Big Data Culture in PharmaChris Waller
A talk presented at the Big Data and Analytics conference in Boston on January 28, 2014. Emphasis on data and information sharing cultures in companies.
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Managing information health
1. Royston E Morgan
BHM 303 Managing Information in Health
Crosslight Management Slide 1
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.
Crosslight Management Slide 2
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
Crosslight Management Slide 3
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?
Crosslight Management Slide 4
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
Crosslight Management Slide 5
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…
Crosslight Management Slide 6
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
Crosslight Management Slide 7
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
Crosslight Management Slide 8
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
Crosslight Management Slide 9
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?
Crosslight Management Slide 10
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
Crosslight Management Slide 11
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’
Crosslight Management Slide 12
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
Crosslight Management Slide 13
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?
Crosslight Management Slide 14
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
Crosslight Management Slide 15
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
Crosslight Management Slide 16
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
Crosslight Management Slide 17
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?
Crosslight Management Slide 18
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!
Crosslight Management Slide 19
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
Crosslight Management Slide 20
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…
Crosslight Management Slide 21
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!
Crosslight Management Slide 22
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…
Crosslight Management Slide 23
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
Crosslight Management Slide 24
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?
Crosslight Management Slide 25
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?
Crosslight Management Slide 26
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
Crosslight Management Slide 27
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…
Crosslight Management Slide 28
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.
Crosslight Management
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!
Crosslight Management Slide 30