1 Decision Support Systems Knowledge Management HA 608 - Lecture 6 Janet Guptill – HA 608 – October 1, 2007
1 Decision Support Systems Knowledge Management HA 608 - Lecture 6 Janet Guptill – HA 608 – October 1, 2007.
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1
Decision Support SystemsKnowledge Management
HA 608 - Lecture 6
Janet Guptill – HA 608 – October 1, 2007
2
MAJOR TYPES OF SYSTEMS
EXECUTIVE SUPPORT SYSTEMS (ESS)[Strategic Level]
MANAGEMENT INFORMATION SYSTEMS (MIS) DECISION SUPPORT SYSTEMS (DSS)
[Management Level] KNOWLEDGE WORK SYSTEMS (KWS) OFFICE AUTOMATION SYSTEMS (OAS)
[Knowledge Level] TRANSACTION PROCESSING SYSTEMS (TPS)
[Operational Level]
3
Key Terms
Decision Support – analyzing data, often from different sources, to make better decisions
Decision Support Systems (DSS) automate decision support
Expert Systems automate decision-making Executive Information Systems (EIS) provide
“dashboards” to assess operational performance Clinical Decision Support Systems (CDSS)
enhance patient care decision-making Knowledge Management (KM) incorporates
evidence- and experience-based information
4
Decision Support - A Possible Definition:
Decision Support - an organization’s use of data in order to improve its managerial and clinical decision-making effectiveness.
NOTE: Above definition makes NO mention of computers!
5
Steps in Using Data to Make Decisions:
Formulate the Decision Problem Obtain Appropriate Data Summarize Data Create a Model Use Model to Evaluate Alternatives Choose an Alternative Implement the Alternative
6
Approaches to IncorporatingData in Decision Making
Manual – collect data and logically organize it to support decision process
Spreadsheets, Statistical Software, etc. Request “IT Department” to generate a
report Use Decision-Support System (DSS) that
integrates needed data and provides analysis framework
7
A Sample Decision Making Problem
You are the Executive Director of a 21-physician multi-specialty clinic.
You currently purchase MRI services on a discounted fee-for-service basis from a local hospital.
You have begun to think about building the capability of providing these services in-house.
8
A Sample Decision Making Problem (Cont’d)
You are trying to decide when to begin installing the necessary MRI equipment and when to start a search for a radiologist with expertise in this area.
You realize that this decision should be based on data.
How do you make this decision? What data do you need?
9
Test the feasibility of a freestanding centerMap forecasted procedures by zipcode,
overlay existing imaging provider sitesEstimate demand based on 3-5 mile
radius and realistic market share targets“Reality test” the demand numbers to be
certain sufficient volumes are attainableCreate the financials, staffing plans, and
marketing strategies
10
St Louis 2001 Major Imaging Procedures by site of care
0
20,000
40,000
60,000
80,000
100,000
120,000
140,000
160,000
180,000
MRI CT PET SPECT MISC
Hospital OP
Freestanding
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Major Imaging Procedures expected to grow over next 5 years in St Louis due to greater adoption of imaging technology in the market
0
50,000
100,000
150,000
200,000
250,000
300,000
350,000
400,000
MRI CT PET SPECT MISC
2002
2007
12
St Louis area map—Focus on St Charles County
13
St Charles County - Existing Imaging Centers - 2001
14
What volumes are needed to be worthwhile? What are realistic start-up volumes?
(assumes 260 days/year)
Breakeven Volume/Day
Year 1 Volume/Day
Year 2 Volume/Day
Year 3 Volume/Day
MRI 7 10 15 20
CT 5 10 15 20
PET 4 4 6 8
SPECT 5 5 7 10
15
What decisions would you make with these data?
Mkt 1:
63301
63303
63304
63376
Mkt 2:
63385
63366
63367
2007 Proc
Forecast
Breakeven
Mkt Share
Capacity
Mkt Share
Market 1 CT 25,319 5% 21%
MRI 14,277 13% 36%
PET 529 196% 392%
SPECT 5,022 26% 52%
Market 2 CT 11,225 12% 46%
MRI 6,329 29% 82%
PET 232 448% 896%
SPECT 2,191 59% 119%
16
Desirable Attributes of a Decision Support System
Easy Interaction With the System Executives Can Retrieve Data
Themselves Data are Displayed in a Meaningful
Format System has Modeling Capability System Generates Clear Reports
17
First, a look at Database Management Systems (DBMS)
Describe How Database Management Systems Organize Data
Identify 3 Database Models, Principles Of Database Design
Discuss Database Trends
18
Two Definitions:
Database - collection of data carefully organized to be of value to a user
Database Management System (DBMS) - software used to manipulate the database
19
Example Database
Employee Name
Date of Hire
Social Security #
Language Fluency
Ken L. Watt 03/03/86 111-23-3223 None
Jane Sargent 11/10/90 356-29-0588 German
Mary Smith 05/05/97 334-44-9876 Spanish
.
.
.
.
.
.
.
.
.
.
.
.
Robert Cardin 09/12/92 056-88-4848 French
Record
Field
File
20
An Overview of Database Models
Hierarchical Data Model - stores data as nodes in a tree structure
Department
Employees Equipment
TechnicianMaintenance Records
ROOT
FIRSTCHILD
2nd CHILD
21
Use of “Pointers” to connect recordsField In One Record Is Address Of
Next Record In Sequence
POINTERRECORD 1
POINTERRECORD 2
POINTERRECORD 3
22
Types Of RelationshipsFound in a Hierarchical Data Model
ONE-TO-ONE: Department Employees
ONE-TO-MANY:Equipment
Technician MaintenanceRecords Supervisor
23
An Overview of Database Models
Network Data Model - stores data as nodes in a network
Department
Employees Equipment
Technician
Maintenance Records
24
NETWORK DATA MODEL
Variation Of Hierarchical ModelUseful For Many-to-Many RelationshipsExample: Student Class Schedules -
Many Students in many classes
MANY-TO-MANY:
STUDENTA
STUDENTB
STUDENTC
CLASS1
CLASS2
25
An Overview of Database Models
Data In Table Format – each record is an event with a standard set of event characteristics
Relation: Table Tuple: Row (Record) In Table Field: Column (Attribute) In Table
Relational Data Model - stores data in individual files, or tables
26
Relational Data Model
27
Comparison of the Models
Network Models - seem to have little application in health care; some
research applications reportedHierarchical Models - appropriate
where data form a natural hierarchy; radiology reporting system; data on individual patients
Relational Models - emerging as the most popular and widely used; supports ad hoc queries
28
Healthcare example of relational databasesHospital Patient ID
Patient Age DRG Attending Physician ID
Admit Date Discharge Date
Discharge Disposition
1234509 42 465 1389 6-05-06 6-10-06 Home
3445676 75 110 3409 5-16-06 6-10-06 SNF
5678932 22 322 6704 6-07-06 6-08-06 Home
7890111 6 201 3422 6-10-06 6-11-06 Transfer
Physician ID
Physician Name
Physician Specialty
Physician Practice Name
Physician Office Zipcode
Medical Staff Activation Date
Physician Date of Birth
1389 Jones OB/GYN Jones PC 63144 11-1996 5-12-1959
3409 Richards Internal Medicine
Medical Specialists
63106 5-1987 2-22-1947
6704 Jackson Orthopedics Sports Medicine
63118 6-2000 4-25-1977
3422 Craig Pediatrics Family Health 63105 6-2004 8-16-1980
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Comparison of the Models
Processing
Efficiency
Flexibility
User
Friendly
Program
Complexity
Medium High Medium
Medium Low High
Low Low High
High High Low
Network Hierarchical Relational
30
Database Management System (DBMS)
Software To Create & Maintain DataEnables Business Applications To
Extract DataIndependent Of Specific Computer
Programs
31
Database Management Systems
Data Definition Language (DDL) - used to define and describe the data elements in the database
Data Manipulation Language (DML) - used to access, edit, and extract information from the data contained in the database
Data Dictionary - used to store a detailed description of the data
32
Two Views Of Data
Physical View: Where are Data Physically? Software Application or other data source Drive, Disk, Surface, Track, Sector, Record Tape, Block, Record Number
Logical View: What Data are Needed By Application? Information needed to make the decision(s) Name, Type, Length Of Field Ability to link or relate to other needed data
elements
33
Data Definition Language
Creates a link between the “User View” of the data and the Physical View of the data
User defines a schema, or view of the database
Schema includes file description, record description, and information about fields
34
Data Manipulation Language
Provides ease of interaction between the user and the database
Allows user to add new data; sort, delete, edit, or display data; generate reports
Two methods for interacting: “Embedded Statements” Direct Interaction (Query Languages)
35
Query Languages
Natural Language Queries - English-like statements
“Please give me the number, name and department name of all pieces of equipment that are associated with the department having the number 19.”
36
Query Languages
Query-by-Example (QBE) – Microsoft Access
37
Query Languages
Structured Query Language (SQL) - developed in the 1970s and adopted as a standard relational language in 1986
SELECT EQUIP_NO, EQUIP_NAME, DEPT_NAME FROM EQTABLE, DEPTABLEWHERE DEPTABLE.DEPT_NO=EQTABLE.DEPT_NOAND DEPT_NO=19
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Data Dictionary
File that stores detailed information about the data elements used in a database -- name type (numeric, alphanumeric, logical ...) storage allocation person authorized to change date of last change
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Creating A Database
Conceptual DesignPhysical Design
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CREATING A DATABASECONCEPTUAL DESIGN:
Abstract Model, Business PerspectiveHow Will Data Be Grouped?Relationships Among ElementsEstablish End-User Needs
41
Creating A DatabasePhysical Design:
Detailed Model By Database Specialists Entity-Relationship Diagram (ERD)
Documents the conceptual data model Normalization - Process of making the
database structure efficient
Physician Fills OutMedication
Order
42
Elements Of Database Environment
DATABASE MANAGEMENT
SYSTEM
DATAADMINISTRATION
DATABASETECHNOLOGY & MANAGEMENT
USERS
DATA PLANNING & MODELING
METHODOLOGY
43
DATABASE TRENDS
Object- Oriented: Data and Procedures Stored Together; Can be Retrieved, Shared
Hypermedia: Nodes Contain Text, Graphics, Sound, Video, Programs; Organizes Data as Nodes
Linking DatabasesVia The Web
44
DATABASE TRENDS
Distributed Databases - a set of “smaller” databases into which an organization might choose to store its data. Benefits include: data are closer to user;
multiple copies exist; data access is moreefficient; applications are morebalanced.
Disadvantages: more complex;potential for loss of synchronization.
45
3 Final Concepts
Data Warehouse - enables the collection and organization of disparate data sources, both internal and external, to an enterprise
Clinical Data Repository Master Patient Index (MPI) Standardization of Terminology & Data
Format Data Mart
Meets the demands of specific department(s) or decision types
46
Standardization Issues
Health Level-7 (HL7) – a set of standards designed to develop a cost-effective
approach to system connectivity SNOMED (Systematized Nomenclature of
Medical Reference Terminology) – a standard vocabulary of clinical terms
EMPI (Enterprise-wide master person index) – a relational database containing IDs of all
patients seen anywhere in the system
47
DATABASE ADMINISTRATION
Defines & Organizes DatabaseStructure And Content
Develops Security Procedures Develops Database
Documentation Maintains DBMS
Conceptual Model of a Decision-Support System
ReportWriter
ClinicalSystems
ExternalDatabases
FinancialDatabases
ModelLibrary
DBMS
ModelManager
User Interface
User
OtherData Sources
DSSDatabase(s)
49
General Uses of a DSSand the System to Support Each Use
General Use: Retrieve Data Item Perform Ad Hoc
Analysis Present Aggregated
Data Determine Impact of a
Proposed Decision Propose Decisions to
Management Make Decisions
According to a Rule
Type of System: Simple DBMS Generic Statistical
Package Executive Information
System DSS with “What-If”
Modeling Capability DSS with Optimization
Modeling Capability Expert System; DSS with
Artificial Intelligence
50
Sources of Information forDecision Support
Internal Transaction Processing Systems (e.g., ADT systems)
Specially Constructed Databases (e.g., medical staff roster)
External Data Sources (e.g., market demographics data)
51
Storing the Information forDecision Support
DatabasesExample: Lab Data in a Single HospitalMany Databases throughout the SystemOften Represent Disparate SystemsCritical to have a key field to link
disparate databases together, e.g., patient ID, procedure code, etc.
52
Storing the Information forDecision Support
Data RepositoriesExample: Clinical Data Drawn from Multiple
Hospitals Related to Day-to-Day PracticeVirtual vs. Physical RepositoryBJC Clinical Desk-Top (ClinDesk) System is
a Physical Clinical Data RepositoryEMR would be a real-time data repository
53
Storing the Information forDecision Support
Data WarehousesMore Information than RepositoryUsed for Retrospective ResearchAvoids “Bogging Down” Operating
Information SystemsOften “Interrogated” With Data MiningClassic example is risk-adjusted patient
discharge data for outcomes analysis
54
Information Needed forDecision Support
Information to Support Strategic Planning Information to Support Marketing Information to Assist in Resource Allocation Information to Support Enhancement of
Productivity and Operating Efficiency Information to Support Outcomes
Assessment Information to Support Contract Negotiation
56
Approaches to Developing a DSS
Write the necessary programs from scratch in a suitable language
Use tools such as spreadsheets, database tools, data “cubes,” etc.
Customize a package Purchase a turnkey system
What are examples of healthcare turnkey systems?
57
Expert Systems automate the decision-making process
Expert System: “A system capable of reproducing “the reasoning process a human decision maker would go through in reaching a decision, diagnosing a problem, or suggesting a course of action.”
Mallach, E.G. 1994. Understanding Decision Support Systems and Expert Systems. Burr Ridge, IL.: Irwin
58
Components of an Expert System
Knowledge Base (Rule Base) - contains expertise of the system
Database - Information which knowledge base is matched against
Inference Engine - generates conclusions User Interface - facilitates interaction
between system and user Workspace - where system stores facts about
a situation
59
UserInterface
InferenceEngine
Knowledge Base
Workspace
Database
User
Conceptual Model of an Expert System
60
Typical Applications of Expert Systems
Program to find “fraud and abuse” in insurance claims
Program to support hospital bed assignment
Program to handle scheduling of outpatient procedures
Program to check drug interactions or inappropriate dosages
61
Executive Information Systems (EIS)
Definition - “An information system which draws from multiple applications and multiple data sources, internal and external, to provide executives and other decision makers with the necessary information to monitor and analyze the performance of the organization.”
Hoven, J. van den. 1996. “Executive Support Systems and Decision Making.” Journal of Systems Management 47(2):48-55.
62
Typical Areas of Interest to the Executive
Financial Performance Clinical Outcomes Human Resource Utilization Access and Continuity Customer Satisfaction Market Share
63
Getting the Executive to Use the EIS
Executive Participates in the Design EIS Must Provide Relevant and
Desired Information Output of EIS Must be Pleasing with
High-Quality Graphics System Should be Relatively Easy
to Use
64
Comparison of DSS & EIS
Both Integrate Clinical and Financial Information from a Variety of Sources
Both Enhance Management Decision Making
DSS Supports Greater Depth of Analytical Probing & Modeling
EIS provides performance indicators at a glance, similar to a scorecard
65
Clinical Decision Support Systems (CDSS)
Broad Definition: Any automated tool that helps clinicians improve the delivery or management of patient care
Ideal Definition: A set of knowledge-based tools fully integrated with both the “physician component” of the computerized patient record and a repository of complete and accurate clinical data and test results
66
The Two Erroneous Extremesin DSS Design
Overly Simplistic - System is able to merely collect and aggregate data rather than to serve as a DSS
Overly Sophisticated Computing Technology - Clever “bells and whistles,” but limited ability to interface with operational systems and to provide the executive with needed information
67
The Proper Balance
Executives must look upon the installation of a DSS in their organization as one of THEIR strategic projects, rather than a necessary activity to be delegated to the IT staff!
68
Knowledge Management and DSS
DSS contain information to make managerial decisions.
Data become Information; but to create
Knowledge one needs Experience. Knowledge Management links user
experience to data and information to enhance executive decision-making.
69
John Seely Brown: “Because information is not knowledge, data is not wisdom, bits are not experience. The difference is us: we make knowledge out of information together, in our communities of practice.”
The Social Life of Information
What is Knowledge Management?
70
Knowledge Management entails the use of “Online Communities”
What is a “community”?
Why are they moving “online”?
Why should this matter to you?
What is hard about it?What makes it easier?
71
Who has expertise inthis area?
Is anyone else working on this same problem?Is anyone else working on this same problem?
What ideas have been tried and
tested?
What ideas have been tried and
tested?
Who else faces similar challenges to mine?
Is there a recommended way to do this?
Is there a recommended way to do this?
How can I share what I have learned?
How can I share what I have learned?
Knowledge Management: people connecting through shared needs
72
Gained $1.5B in annual wafer manufacturing capacity by sharing “best practices”
More than $1 billion in documented bottom-line savings since 1995
Saved “tens of millions of dollars” by creating a worldwide repository of “best practices”
Saved over $150M in the first year of an initiative to identify and share marketing best practices
$50 million a year in travel cost avoidance and $6 million annually by finding information more quickly through its KM initiative
$1.5 million in savings from 2 of its communities of practice
Knowledge ManagementLessons Learned from Leading Business Managers
Define the desired performance outcomes – link knowledge transfer activities contributing to these results – APQC.org
73
What are communities of practice? Communities of practice are social networks
Online communities are supported by web technologies
They exist to solve problems
74
What are online communities in healthcare?
Consumer communities – Disease support groups, weight loss/stop
smoking, connect patients and families
Professional communities – Professional societies, physician networking,
hospital business alliances, software users
Employee communities – Best practice adoption, process improvement
teams, peer networking
75
Online communities are it!
MySpace Generation
Collaboration Expectations
Customer Interactions
Engagement
76
Virtual Communities are used across hospitals to:
Create relationships across time and space for peer learning and experience sharing
Identify successful practices, lessons learned, and critical success factors for achieving better results
Encourage and reward adoption of innovative practices and data-driven business processes
77
Virtual Communities are used within hospitals to:
Collaborate across roles, departments, or functions to solve operational problems
Simplify access to experts and expertise, encourage new ideas
Save time and money by re-using work done in another department or area
78
What are key building blocks for effective communities?
Value Add – both the individual and the organization have to see it as useful
Culture – a new way of working – inherently more open and collaborative
Infrastructure – making it look simple is hard work to begin with
Communicating Impact – stories drive changeIHI Profiles in Improvement Who's improving health care? People are. Listen to the story of Jennifer Dunscomb of Columbus Regional Hospital.Source: www.IHI.org
79
Examples of Knowledge Management Systems in Healthcare
CHCA 3 pronged approach to knowledge management:
Peer Networking Forums, Performance
Improvement Collaboratives, Race for Results
Awards Program
CHI Embedded knowledge transfer and learning:
Knowledge Communities, Practice in Action, Calls to
Learn, Relay Reports, LEARN
80
CHCA Case Study
Background of CHCAOverview of Forums, Collaboratives,
Race for ResultsStrategic Impact to dateLessons Learned
Improving the Performance of Children’s Hospitals
81
Knowledge Transfer to Improve Performance: A Case Study
42 non-competing hospitals US, Canada$14 billion combined revenue (1)Average per member revenue of $330 million If Fortune 500 would be ranked 142 IDN influence:
500,000 inpatients; 10 million outpatients (2) 102,000 employees (2) >20,000 pediatric physicians (5,162 medical specialists;1,985 surgical
specialists(2)Top 5 among U.S. health systems/IDNs
Sources: (1) Estimated from Goldman Sachs report to CHCA, July 2004; (2) Estimated from personnel report in AHA Guide 2003/ 2004
82
CHCA’s 3-pronged strategyPeer Networking Performance
ImprovementSpread
TECHNOLOGY Online communities Peer group meetings
Collaboratives
C, C, c
RACE for Results Juried annual award
PEOPLE & PROCESS
Teleconferences List serves Forum directors Special reports Benchmarking
PDSA approach Results reported to
peers and executives Dedicated PI staff
Awards process with external judges
Peer reviewed publication
Ambassador program External published
results Real time tools and
resources
STRATEGIC IMPACT
Individual employee improvement in productivity
Satisfaction + individual hospital improvement in results
Organization-wide improvement, e.g., cost reduction, error reduction, safety improvement
Accelerate improvement Safe, efficient and
effective
Focus on spread Knowledge available
when you need it Best practices Peer assistance
83
1 - Peer Networking Forums Internet site for Forum members only
Exclusivity, confidentiality, knowledge of colleagues Dedicated staff facilitator – Supports 3-5 Forums depending on
content knowledge and required expertise Share documents, post weblinks, initiate discussions, find resources
Technology combined with meetings keeps the group connected Teleconferences, webcasts, bi-annual meetings Ad hoc conversations, focused research, group
problem-solving Rapid response to posted questions Benchmarking and identifying variation
84
Peer Networking Forums are Highly Active
Ambulatory 22 Materials Management 33
Cardiac 28 OR Directors 31
CFO 40 PACT 34
CHAPs 17 Patient Financial Services
21
CIO 36 Payor Contracting 33
CNO 40 Pediatric Practice Exec.
22
COO 40 Pharmacy Buyers 40
Corporate Compliance 28 Pharmacy Directors 39
Customer Service 20 PHIS 37
Dietary 33 Physician Relations 22
Executive Dialogue 40 Quality and Safety Leaders
42
Facilities Management 33 Radiology Directors 33
Health Information Mgmt
33 Respiratory Directors 32
Home Care 17 Risk Managers 25
Human Resources 32 SMAC 30
JCAHO 35 Social Work Community
15
Lab Directors 32 SPBD 28
Overall 2006
satisfaction5.24 of 6.0
(87%)
2006 Hospital Participation in Forums
85
Peer Networking Forums webpage example
86
2 - Performance Improvement Collaboratives
Dedicated Performance Improvement staff and resources Trained in IHI improvement methodology Hospitals agree to share results, post data and publish results Use industry and hospital expert panels to validate clinical direction Combine research and rapid cycle - essential for academic engagement
Technology tools and partners integral to success Knowledge repository available real time
improvements, tool kits, lessons learned, comparative data, audios of webcasts and lessons learned
Strategic partners essential to spreading results and gaining credibility AHRQ Partnership for Quality Grant helped fund participation and training for all
42 hospitals Data-sharing agreements developed to expand comparative data sets (Vermont
Oxford Neonatal Network and others)
87
Performance Improvement CollaborativesExample: Reduced Adverse Drug Events
Hospital Teams:AtlantaBirminghamBuffaloCincinnatiColumbusCorpus ChristiDaytonFort WorthKansas CityMiamiNashvilleNew OrleansNew York/
Morgan-StanleyNew York/
Komansky CenterOrangePalo AltoPittsburghSt. Petersburg
16 teams (89%) had a reduction in ADE rate Average among teams with a reduction: 64% reduction Average for all teams: 49% reduction
11 teams (61%) had at least a 50% reduction in ADE rate
BE
TT
ER
Avg.
CHCA Hospitals with reduction in ADE rate
Goal
88
Collaboratives have own web-sharing spaces
89
Adverse Drug Event Collaborative webpage
90
Blood Stream Infection Collaborative webpage
91
Surgical Infection Prevention Collaborative
92
3 - Awards Program Encourages Spread Formal RACE for Results awards program
Formal application process with strict submission requirements External judges panel representing industry experts in quality and patient
safety Results announced at award ceremony during annual Quality
& Safety Meeting Winners required to serve as Ambassadors during subsequent year to teach
techniques and encourage adoption of proven practices
Formal marketing campaign to publicize event Emails, posters, web notices to promote the competition and publicize
winners Email-based Relay Report to report progress as proven practices are
replicated across the alliance Resources and contacts posted on the intranet to facilitate connections and
encourage adoption Benchmarking reports regularly published to document improvements Improve Today Webcasts connect colleagues
93
RACE for Results Awards Program
2004 2005 2006 2007
Little Rock: Reducing Catheter-Related Bloodstream Infections through Repeated Rapid Cycle Improvements
Cincinnati: Reducing Cost through Improving Quality
Palo Alto: Decreasing ADEs By Implementing Safety Best Practices
Washington DC: Using PHIS to Target Reducing Infections in VP Shunt Surgeries
Omaha: "Asthma Attack“
Dayton: Reducing Catheter-Associated Bloodstream Infections in Children
11 Entries 12 Entries 17 Entries 30 Entries
94
RACE Results in Performance Improvement
95
Conclusions for CHCAStrategy Drives Approach Informal peer networking builds a culture of sharing and collaboration Formal collaboratives are needed to create immediate results Systematic rewards and support are needed to spread initial results
Knowledge Transfer involves Technology, People/Process, and Strategy Technology enables information sharing and people directories People processes ensure productive interaction and knowledge exchange Strategy determines impact measures and ensures organizational momentum
CHCA Case Study Results: 42 children’s hospitals participate in 30 peer networking forums, regularly
sharing improvement tools and resources, exchanging best practices and learning from industry experts
18 children’s hospitals averted 13,478 adverse drug events (ADEs), representing $2.7 million in net savings, and reduced PICU blood stream infections (BSIs) by 57%
More than 60 intensive care units are working to sustain and spread improvements in ADEs and BSIs based on the initial collaboratives’ work
96
CHI Case Study
Background of CHIKT&L Strategy and ScopeRelay Report results to dateLessons Learned
97
CHI Fast Facts
Multi-institutional System of Catholic Healthcare Providers Dedicated to the healing ministry of the Catholic Church National Offices: Denver, Northern KY, and Minneapolis Market Based Organizations (MBOs)
19 states 68 rural and urban communities 71 hospitals (63 acute care, 5 behavioral, 2 rehabilitation, 1 long
term acute care) 43 long-term care, assisted living facilities and residential units 5 Community Health Services Organizations
Licensed acute care beds range from 15 to 1,546 $7.1 Billion in Annual Revenues 66,000 Employees (and growing)
98
Vision for CHI
Catholic Health Initiatives’ Vision is to live out its Mission by transforming health care delivery and by creating new ministries for the promotion of healthy communities.
99
CHI Strategic Plan: 2007 - 2011
100
Leveraging the Knowledge Within
“Our goal is for CHI to become known as an innovative organization. That will be our legacy for the future health care system – that CHI learns to leverage the wisdom of the whole, efficiently, effectively, and humanely.”
- Kevin E. Lofton, FACHE, CEO, Catholic Health Initiatives
101
Knowledge Leadership
Knowledge Leaders are Leaders who are effective at…
Embracing and driving change
Sharing experiences and applying learning
Modeling the expected behaviors grounded in the culture of the organization
… in order to tap into the intellectual capital of the organization and harness it to innovate and grow
102
Knowledge Transfer & Learning at CHI
StrategicPriority
Consulting
Knowledge Communities
Formal Education
Practice in Action
Communication& Collaboration
103
CHI’s KT&L StrategyCommunication & Collaboration
Knowledge Transfer
Integrated Learning
TECHNOLOGY Knowledge Communities Relay Report Live Meeting web-
conferencing List serves
Practice in Action - Proven Practices database
Pathfinders collection of expert resources
Calls to Learn Annual Events &
Conferences System-wide LMS -
LEARN
PEOPLE & PROCESS
Calls to Learn National office sponsors KC Chartering process KC metrics reports
Integrated into Annual Planning Budget Review process
Formal process to confirm a proven practice
KT&L staff support system-wide initiatives e.g., CHI Connect, service line development
Centralized calendar of Calls to Learn across the organization and beyond
LMS intended to address CHI-wide practices
Integration of organizational effectiveness research with delivery of new education
STRATEGIC IMPACT
Enable innovation Focus on strategic
priorities Defined and implemented
new standards of practice
Organization-wide improvement, e.g., cost reduction, error reduction, safety improvement
Accelerate improvement Safe, efficient and effective Strategic Priority Consulting
Compliance adherence Enable delivery of
education in support of strategic priorities across the system
104
Knowledge Communities: Collaborate and Innovate
An environment that enables innovation, supports the development and spread of new ideas and builds the organizational social network to save time and reduce costs.
Value of Pharmacist
as part of bedside
patient care team proved
and $53 Million saved
Value of Pharmacist
as part of bedside
patient care team proved
and $53 Million saved
105
Why CHI uses online communities
Connect peers and experts across CHI Common space across distance and time Supports the work of the Knowledge
Community: Enable and leverage knowledge sharing Learn before doing Problem solving: find, innovate, and accelerate
solutions Reduce costs, save time, and increase social fabric A strategic resource
106
Making it Easier to Connect with Knowledge Communities
107
Relay Report: Communicate, Connect, Celebrate
Improve connectivity, celebrate successes and increase awareness and utilization of KT&L resources.
Accelerate the
implementation of
clinical imaging
technology, resulting
in accelerated
NPSR of $1.5 - $3.0 M
Accelerate the
implementation of
clinical imaging
technology, resulting
in accelerated
NPSR of $1.5 - $3.0 M
108
Practice in Action: Transfer Critical Knowledge
Increase adoption of reliable, evidence based practices, identify organizational expertise, and recognize facilities that have achieved success.
Avoided medication
errors through
improved reconciliation
of home and hospital
medications.
Avoided medication
errors through
improved reconciliation
of home and hospital
medications.
109
Strategic Priority Consulting: Support Organizational Priorities
Accelerate achievement of strategic priorities by creating a plan to leverage available knowledge transfer and learning resources.
Accelerate the
implementation of
ERP technology
(Lawson) and the
realization of
projected savings
Accelerate the
implementation of
ERP technology
(Lawson) and the
realization of
projected savings
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Formal Education: Sustain Change
Coordinate and share system resources to insure that education and training help employees learn the skills, behaviors and competencies they need to move strategic priorities forward.
Avoid dangerous /
deadly events in OB
through a targeted
Advanced Fetal
Monitoring curriculum
Avoid dangerous /
deadly events in OB
through a targeted
Advanced Fetal
Monitoring curriculum
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Knowledge Transfer is both Organic AND Strategic
Practice in Action
StrategicPriority
Consulting
Knowledge Communities
Formal Education
Communication & Collaboration
Accelerate Learning & Enable Innovation through…
…leading to new models of care delivery and creative solutions…
…resulting in improved outcomes:
• Quality & Patient Safety
• Employee Satisfaction & Engagement
• Increased Operating Margins
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Conclusions for CHIKnowledge Leadership is at the core of CHI’s business strategy New Leadership competencies are based on collaboration & change Knowledge communities build a culture of sharing and innovation KT&L team has become core resource for national strategic initiatives
Knowledge Transfer has become the way CHI works Web tools support connectivity and facilitate communicating about key knowledge
resources and success stories New roles have evolved as collaboration has become embedded in the way CHI
works Strategic initiatives rely on knowledge tools to speed adoption
CHI Case Study Results: A total of 48 knowledge communities involve over 1600 associates across the
system Knowledge communities have yielded both “hard” and “soft” dollar savings,
impact patient outcomes through improved practices, increase reuse of proven practices
After 5+ years, CHI leadership expect KT&L resources to be utilized as part of strategic priority projects and leaders will be held accountable to Knowledge Leadership competencies
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Communities Are Here!
A 2001 best practice study (Using Communities of Practice to Drive Organizational Performance and Innovation) found:
“…strong evidence that communities are the next step in the evolution of the modern, knowledge-based organization. Communities … are a legitimate way to spend time, engage an amazing percent of employees, are held accountable for producing and stewarding business-critical knowledge (and often results), and are assuming a formal voice in the organization, based on the power of their knowledge, not their position.”
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Knowledge Management Building Blocks in Healthcare
Peer Networking
Performance Improvement
Spread
TECHNOLOGY Create MySpace for your employees, physicians, and customers
Create public campaigns for targeted improvement goals
Publish results on the hospital website – customize for each audience
PEOPLE & PROCESS
Create online people directories, create peer group moderator roles, highlight personal success stories
Develop a dedicated PI staff – this may incorporate Six Sigma, IHI Collaboratives, etc – or may be internally developed
Incorporate proven practice sharing into annual awards ceremonies, dept budget reviews, employee performance reviews
STRATEGIC IMPACT
Enhanced employee satisfaction and productivity, strong customer satisfaction scores
Focused improvement in targeted areas, e.g., patient safety, financial performance, wait times, turnover, etc.
Faster decisions, quicker adoption of proven practices, rapid innovation absorption
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Key Topics
Decision Support – analyzing data, often from different sources, to make better decisions
Decision Support Systems (DSS) automate decision support
Executive Information Systems (EIS) quickly assess performance and trends
Clinical Decision Support Systems (CDSS) enhance patient care decision-making
Knowledge Management (KM) incorporates evidence- and experience-based information
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