Using Data to Drive Health System Performance

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Using Data to Drive Health System Performance

• Lynn Talbot
• Sandra Dodgson
• Mike Finch
• Stanton Shanedling

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Using Data to Drive Health System Improvement

• Objectives
• To offer an opportunity for you to review where
  you are now in the use of your data
• To look at possibilities for using data
  differently to improve performance
• To increase individual and collective skills and
  knowledge
• To develop a plan to build local capacity

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Current NHS Structure
Secretary of State
Treasury
DOH
Chief Executive
Director of Finance
Chief Medical Officer
Chief Nurse
Etc
Strategic Health Authorities
28
PCTs
203 approx
Providing
Commissioning
Themselves

• Acute
• Mental Health
• Private Sector
• Voluntary Sector

• GPs
• Opticians
• Dentists
• Pharmacists etc

PATIENTS
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The Context

• Whole System

Comprehensive data
Poor data
Discrete services
5

National Requirements
Learning from Others
Resources/ Costs
Population Health Needs Patterns of Service
Usage
Service Design/ Redesign
Where want to be (Strategy)
Where are now
Detailed Service Specification
Commissioning Cycle
How get there (Transition Plan)
Review Impact and quality
Working with potential providers
Putting into operation
New contracts/ SLAs or changes to existing
agreements
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PROGRAMME
DAY 1
DAY 2
Where are we now?
How do we get there?
Review Impact/Quality
Putting into practice
Where do we want to be?
Case Study
Actions
Overview
Food for Thought
Group Work
Actions
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Session 1
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Knowledge ManagementUsing Data to Drive Strategy

• Knowledge derives from information as information
  derives from data.
• Unlike data and information, knowledge contains
  judgment.

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Data

• What are Data
• gt Sets of discrete, objective facts about events
• gt Structured records of transactions
• gt Essential raw material for the creation of
  information
• Data sets by themselves have little relevance or
  importance and no inherent meaning.

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Information

• Information has meaning, relevance and purpose.
• We transform data into information by adding
  value.
• Why was the data gathered?
• What units of analysis are used?
• How is the data analysed?
• How are errors removed?
• How is a summary created based on the data?

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Knowledge

• Knowledge is neither data nor information though
  it is related to both
• Data, information and knowledge are not
  interchangeable
• Knowledge is a mix of framed experience, values,
  contextual information, and expert insight that
  provides a framework for evaluating and
  incorporating new experiences and information.
• - Thomas H. Davenport, Laurence Prusak
• Working Knowledge How Organizations Manage What
  they Know

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Knowledge

• Knowledge has become a health care asset not only
  for the health provider, but for the patient as
  well.
• Health care now, more than ever before, requires
  quality, value, service, innovation, efficiency
  and effectiveness.

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Knowledge

• If information is to become knowledge, then
  people must do the work to accomplish meaning.
• How does this compare to others?
• What are the implications for decisions?
• How does this relate to others?
• What do others think?

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What is Knowledge Management

• The leveraging of collective wisdom to increase
  responsiveness and innovation. -The Delphi
  Group
• KM is intended to allow organisations to protect
  and develop their knowledge resource.
• - The Applied Knowledge Resource Institute

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What is Knowledge Management

• KM is a management discipline that focuses on
  enhancing knowledge production, integration and
  use in organisations.
• - Mark McElroy, Knowledge Management Consortium
• A cycle of knowledge creation, integration and
  dissemination.
• - Gerhard Fisher, Jonathan Ostwald, Univ. of
  Colorado

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Knowledge Management (KM)Knowledge the
Business Process Environment
Business Processes Reflect Mutually Held
Knowledge in Practice
Organisational Knowledge is Embodied in Agents
Artifacts
Business Process Environment
Business Process Behaviors of Interacting Agents
- Knowledge Use
Organisational Knowledge Containers - Artifacts
Codifications Individuals Teams
Internal/external events
Continuous exposure to events in the (Business)
environment to which organisations react adapt
by drawing on their mutually held knowledge
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Knowledge ManagementNot How First-Generation KM
has Seen It
Business Process Environment
Distributed Organisational Knowledge
Business Process Behaviors of Interacting Agents
- Knowledge Use
Organisational Knowledge Containers - Artifacts
Codifications Individuals Teams
Internal/external events
Begins with the convenient assumption that
valuable organisational knowledge simply exists
All we need to do is capture, codify, and share it
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An Expanded View
How to enhance knowledge production in an
organisation
People dont just use knowledge, they create it!
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Usually as Follows
How to enhance knowledge sharing and use in an
organisation?
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Knowledge Management10 Key Principles of Second
Generation KM

• 1. Learning and innovation is a social process,
  not an administrative one - strong affinity with
  organisational learning theory
• 2. Organisational learning and innovation is
  triggered by the detection of problems
• 3. Valuable organisational knowledge does not
  simply exist - people create it

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Knowledge Management10 Key Principles of Second
Generation KM

• 4. The social pattern of organisational learning
  and innovation is largely self-organising and has
  regularity to it.
• 5. KM is a management discipline that focuses on
  enhancing knowledge production and integration in
  organisations
• 6. KM is not an application of IT - rather, KM
  sometimes uses IT to help it have impact on the
  social dynamics of knowledge processing

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Knowledge Management10 Key Principles of Second
Generation KM

• 7. KM interventions can only have direct impact
  on knowledge processing outcomes, not business
  outcomes - impact on business outcomes is
  indirect
• 8. KMs value proposition? KM enhances an
  organisations capacity to adapt by improving its
  ability to learn, innovate, and to detect and
  solve problems

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Knowledge Management10 Key Principles of Second
Generation KM

• 9. If it doesnt address value, veracity, or
  context, its not knowledge management
• 10. Business strategy is subordinate to KM
  strategy, not the reverse, because business
  strategy is itself a product of knowledge
  processing - KM is not an implementation
  toll for strategy strategy follows from KP and
  is, therefore, downstream from KM.

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Knowledge Management versus Knowledge
Processing

• Knowledge Management
• is a management discipline that focuses on
  enhancing knowledge processing
• Knowledge Processing
• is what organisations do to produce and integrate
  their knowledge

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What Investments in KM Cannot Do

• KM cannot make decisions on behalf of people
  operating on the front lines.
• KM has direct impact on Knowledge Processing
  outcomes, but only indirect impact on business
  outcomes.

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But Most KM Strategies Are Only Supply-Side in
Scope
Supply-Side KM Strategies Are All About
Knowledge Capture, Sharing and Codification

• Knowledge Integration
• (Diffusion)
• Sharing
• Broadcasting
• Searching
• Teaching

Organisational Knowledge
Business Process Environment
Business Process Behaviors of Interacting
Agents (Knowledge Use)

• Organisational Knowledge
• Containers
• Artifacts Codifications
• Individuals Teams

Distributed Organisational Knowledge
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Also IT- Centric and Transaction Oriented

• Knowledge Integration
• (Diffusion)
• Sharing
• Broadcasting
• Searching
• Teaching

Tend to be Technology-Centric and Focus on
Getting The Right Info to the Right People at
the Right Time
Organisational Knowledge
Business Process Environment
Business Process Behaviors of Interacting
Agents (Knowledge Use)

• Organisational Knowledge
• Containers
• Artifacts Codifications
• Individuals Teams

Distributed Organisational Knowledge
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Critical Differences Between Information
Management and KM
KM concerns itself with the value, veracity, or
context of beliefs or claims. It also considers
the production of related claims (knowledge
claims) and ways they are integrated into an
organisation.
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Critical Differences Between Information
Management and KM

• Information Management tends to be aimed at
  managing work products and their content and/or
  attributes, but not beliefs or claims about their
  value, veracity, or context. In addition, it does
  not consider business processes and supporting
  systems that accompany the production and
  integration of related knowledge.
• IM can support KM strategies - but not the
  same as KM.

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Demand-Side KM

• Focus is on satisfying organisational demand for
  the production of new knowledge
• e.g., gt The resources needed to launch
  and sustain your program
• Emphasises knowledge creation from a bottom-up
  perspective
• Usually people and process-centric in its
  orientation (collaboration, organisational
  learning and innovation)

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Supply-Side KM

• Focus is onsupplying the right information to
  the right people at the right time
• Emphasises knowledge sharing from a top-down
  perspective
• Usually technology-centric in its orientation
  (capture, codify and share knowledge)

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Approach
Demand - Side KM
Supply - Side KM
Social Dimension (people and Processes)

• Individual Learning
• Group Learning
• Think Tanks
• Mgmt Planning
• Innovation

• Training Programs
• Operations Mgmt
• Knowledge Capture
• Storytelling
• KM Initiatives

Technology Dimension (IT)

• Knowledge Portals
• Innovation Mgmt
• tools
• Groupware
• Discussion groups

• InformationPortals
• Intranets
• Information Mgmt
• Content Mgmt
• Imaging

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Session 2
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National Requirements
Learning from Others
Resources/ Costs
Population Health Needs Patterns of Service
Usage
Where want to be (Strategy)
Where are now
Commissioning Cycle
How get there (Transition Plan)
Review Impact and quality
Putting into operation
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Understanding Where We Are Now Where We Want to
Be Make a Difference in Health Care Delivery
Broad Street Pump
John Snow 1883
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Strategic Planning for SHAsA blend of two
perspectivesMedicine/Public Health
Asklepios First physician Greek legend
Hygeia Daughter of Asklepios
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Knowledge Management

• 
  Social/Health
• 
  Indicators
• Evaluation
  Data Analysis
• Implementation
  Useful Information
• Operations Planning
  Knowledge Management
• 
  
• 
  Strategy
  

Planning Cycle
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Health System Program PlanningThe
PRECEDE/PROCEED FrameworkLawrence W. Green
Marshall W. Kreuter

• PRECEDE
• P predisposing
• R reinforcing
• E enabling
• C constructs
• E educational
• ecological
• D diagnosis
• E evaluation

• PROCEED
• P policy
• R regulatory
• O organizational
• C constructs
• E educational
• E environmental
• D development

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Hallmarks of thePRECEDE/PROCEED Framework

• Flexible, Comprehensive, and Scaleable
• Evidence-based and Easy to Evaluate
• Participatory Process
• Platform for Best Practice

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PRECEDE-PROCEED Framework
Formative evaluation baselines for outcome
evaluation
Genetics
Phase 6 Implementation
Phase 7 Process evaluation
Phase 8 Outcome evaluation
Phase 9 Impact evaluation
New in 4th ed., Green Kreuter, Health Promotion
Planning, An Educational and Ecological
Approach, 2005 .
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PRECEDE/PROCEEDNine Phases

• 1. Social Assessment Identify social problems
  that impact quality of life, health care and
  priorities of individuals or populations.
• e.g., unemployment, absenteeism, crime,
  crowding, overall population health
• 2. Epidemiological Assessment Determine health
  issues associated with the quality of life.
• e.g., morbidity, mortality, risk factors,
  education, disability, physiological risk
  factors,longevity, intensity, incidence,
  prevalence, culture

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Influences on the Population's Health
Place Time
Context
Community Attributes
Biological Characteristics Age Gender
Genetic makeup
Social Cohesion Social support Social change
Natural Environment Air quality Water
quality Contaminants
Built Environment Housing Workplace
School
The Populations Health Disease
Functional Status Well-being
Health Services Structure Cost Access
Quality
Cultural Context Race Culture Religion
Discrimination
Economic Employment Income Income
inequality Economic change Education
Political Context Public policies Health
policies Laws Participation
Lifestyles and Health Practices Smoking
Diet Physical Activity Safety Violence
Sexual Practices
Population-based Health Programs Water supply
Waste disposal Public health programs School
programs
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Nine Phases cont

• 3. Genetics, Behavioral Environmental
  Assessment Identify health practices linked to
  the health problems - vital indicators.
• e.g.,compliance, consumption patterns,preventive
  actions,utilization,
  self-care, frequency, lifestyle,
  economic, family, access, affordability, housing
• /-foods, high stress
  jobs,smoking in public places

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safety issues
literacy
values
economics
pollution
hygiene
parenting skills
infection control
cultural issues
health care
social policy
communication
waste disposal
approval
mental health issues
water
DESCENDANTS
food safety
ADAM
EVE
FAMILY
shelter
grief issues
love
contraception
access to healthcare
higher level communication negotiation skills
interpersonal skills
law and order
roads transport
food storage
food storage and transportation
education
larger quantities of food water
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Proportions of premature mortality attributable
to genetic predisposition, behavior, and
environment (social, physical, and health care).
Social circumstances15
Genetic predisposition 30
Physical environment5
Health care 10
Behavior 40
Source McGinnis JM, Russo PG, Knickman, JR.
Health Affairs, 21(2), April 2002.
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Epidemiology of COPD

• Previously more common in other countries than UK
• Over 3 million people in UK suffer from COPD
• Male mortality from COPD decreasing for 30 years
  while female mortality has been steadily rising
  for 30 years
• COPD responsible for 10 emergency admissions
• Emergency hospital admissions for exacerbations
  and home oxygen account for a large proportion of
  healthcare costs in the UK

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Epidemiology of COPD

• COPD responsible for gt30,000 deaths in UK yearly
• COPD care costs NHS an estimated 500
  million/year (2001)
• 6th leading cause of adult deaths worldwide
• 80-90 of all COPD cases can be directly
  attributed to smoking

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Groupwork

• Consider COPD
• What data (actual and tacit) do you have to
  determine where you are now?
• How do you source this data inside and outside
  your own organisation?
• How is information used in your patch?

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Using data

• What has this confirmed for you?
• What might you do differently
• As an individual?
• As a team?

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Session 3
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National Requirements
Learning from Others
Resources/ Costs
Population Health Needs Patterns of Service
Usage
Where want to be (Strategy)
Where are now
Commissioning Cycle
How get there (Transition Plan)
Review Impact and quality
Putting into operation
55
PRECEDE-PROCEED Framework
Formative evaluation baselines for outcome
evaluation
Genetics
Phase 6 Implementation
Phase 7 Process evaluation
Phase 8 Outcome evaluation
Phase 9 Impact evaluation
New in 4th ed., Green Kreuter, Health Promotion
Planning, An Educational and Ecological
Approach, 2005 .
56
Nine Phases cont

• 4. Educational/Ecological Assessment
• Predisposing factors e.g.,knowledge, attitudes,
  values,
  beliefs,perceptions
• Reinforcing factors e.g., attitudes and
  beliefs of others -
• Parents, teachers, employers, health
  professionals, legal, social services,
  etc.
• Enabling factors e.g., resources,
  accessibility, skills

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Nine Phases cont

• 5. Administrative and Policy Assessment
  Administrative organizational concerns prior to
  implementation.
• gt The organisational barriers that
  effect implementation
• gt Policies that support the program or
  need to be changed
• 6. Implementation of the Program
• e.g., gt Well thought out plan, budget,
  training, careful monitoring

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Nine Phases cont

• PRECEDE Evaluation Tasks
• Specifying measurable objectives baselines -
  Formative Process Evaluation
• PROCEED Evaluation Tasks
• Monitoring Continuous Quality Improvement -
  Process, Outcome Impact Evaluation
• 7. Process Evaluation
• 8. Outcome Evaluation Tomorrow!
• 9. Impact Evaluation

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PRECEDE/PROCEEDBehavioral Program Matrix
More Important Less Important
High priority Low priority for a
program except for
political reasons
More Changeable
Priority for No program
innovations assessment is crucial
Less Changeable
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Strategic PlanningWhat to Do Based on
Information Knowledge

• Notice that strategy is embedded in the
  Progress Pyramid.
• Unlike Vision Mission which are stable for
  many years, a typical strategy (especially in
  health care), is stable for 1-3 years.

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Strategic PlanningWhere are you with your
health care planning?
Outward Imagination Innovation
Forward Planning Goals
Backward History Experience
Inward Assessment Correction
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Strategic Planning

• Through a carefully aligned strategic plan,
  SHAs can
• 1. Examine the health care environment in which
  they exist and operate.
• 2. Explore health care factors (eg. COPD) and
  trends that affect the way SHAs provide care
  services and intervention from a medical and
  public health perspective.

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Strategic Planning

• 3. Seek to meet mandates and fulfill SHAs mission
  consistent with National, regional and locally
  identified needs.
• 4. Frame strategic issues creatively to drive
  health care delivery and prevention/health
  promotion initiatives.

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Diffusion of Innovations
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14
16
lt3
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Groupwork

• Consider COPD
• What are the drivers for service change/ health
  improvement interventions?

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Groupwork

• What do you think the service will look like
  should look like in 3/5 years and 10 years from
  now?
• What are your assumptions?

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Groupwork cont.

• What data/information do you need/have?

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Using data

• What has this identified for you?
• What might you do
• As an individual?
• For others in your patch?

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Session 4
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National Requirements
Learning from Others
Resources/ Costs
Population Health Needs Patterns of Service
Usage
Where want to be (Strategy)
Where are now
Commissioning Cycle
How get there (Transition Plan)
Review Impact and quality
Putting into operation
71
Identification of Key Data Sources

• Why is Data Important?
• As we have learned, the correct data will
  help you answer the key health questions you
  have. Data is key for determining
• What Problem
• Who Populations, how many people
• Where Locations, geography
• When Period of time
• Why Why is this an issue

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Identification of Key Data Sources

• Why is Data Collection Important?
• To track changes/stability of health over time
• What is influencing changes
• To evaluate the impact of prevention/health
  promotion, and health care interventions
• To monitor resource allocation

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Identification of Key Data SourcesApplications
Functions

• The major software application areas for
  information systems in modern health care
  organisations are
• Patient financial administrative systems
• Decision support systems
• General financial management systems
• Provider managed care systems
• Clinical systems
• Practice management systems
• Home health systems
• Enabling technologies

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Identification of Key Data SourcesPatient
Financial Administrative SystemsThese systems
are obtained from a health information system
supplier. They support the activities involved in
tracking inpatient and outpatient care.
Application Function
Data Required Data Uses

• Inpatient Admission, outpatient/clinic
  registration
• Patient Transfer
• Patient Discharge
• Census/bed control
• Preadmissions and insurance verification
  

• Patient demographic insurance data
• Current census info.
• Treating Physician Info.
• Patient clinical data
• Discharge planning
• LOS

• Population tracking, service, market analysis
• Census tracking/bed control
• Initiate, conclude services
• QI, cost control measures
• Utilization Review

Admission/Discharge/ Transfer Registration

• Multiple procedure, resource, facility support
• Conflict alert
• Surgical facility support

Scheduling

• Patient demographic/clinical data
• Test Requirements and procedures
• Resource availability/costs
• Surgical preference lists

• Cost Control
• Productivity measurement,improvement
• QA/UR
• Costing by patient group
• Conflict resource mgmt

• Patient demographic, clinical, insurance data
• Patient records number
• Deficiency types and stds.
• DRG Groupers
• Coding indices and edits
• Patient abstracting stds.

• Mgmt /physician reporting
• Provider profiling
• QA
• Patient trending

• Chart and deficiency tracking
• Coding
• Abstracting

Medical Records
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Identification of Key Data SourcesPatient
Financial Administrative Systems - cont
Application Function
Data Required Data Uses

• Estimated and actual LOS calculation

• Initial and final patient diagnosis procedures
  performed
• Patient demographic data

• Utilization control
• Patient trending
• Outcomes studies
• Management and regulatory reporting

UR
QA

• Potential quality problem alerts

• User defined quality and LOS stds.

• Quality control and risk mgmt
• Physician profiling
• Outcomes studies
• Mgmt and regulatory reporting

• Quality evaluation and maintenance
• Clinical Protocol Development
• Regulatory, state reporting

• Severity of illness classification
• Health status evaluation
• Aggregate data grouping for Quality Report Cards

• Patient financial, clinical and admin., data
• Internally or externally defined quality
  indicators

Scheduling
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Identification of Key Data SourcesDecision
Support SystemsThese systems are obtained
through a specialty group of HIS vendors.
Application Function
Data Required Data Uses
Budgeting

• Revenue/expense projections
• Volume-adjusted projections

• Historical revenue/expense data
• Case-mix data

• Budgeting

• Produce data for cost procedure, case, HRG,
  ambulatory visit grp.
• Determine per procedure, case, HRG costs

• Labor hours
• Supply costs
• Number, types of procedures performed

• Cost identification
• Budgeting
• Measure variable cost-control technique
  effectiveness

Cost Accounting

• Revenue
• Expense
• Case Mix
• Economic Modeling assumptions

• Establish appropriate funding
• Contract negotiation and mgmt

Reimbursement Modeling

• Project revenue expenses
• Compare actual/expected reimbursement
• Predict financial impact of changes

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Identification of Key Data SourcesDecision
Support Systems - cont
Application Function
Data Required Data Uses
Case-Mix Analysis

• Analyse patient service mix by point of
  service., department, physician, payer/contract,
  diagnosis

• Diagnosis procedure data from all depts and
  point of service
• Patient accounting and administrative data

• Population analysis
• UR
• Contract negotiation and mgmt
• Physician staffing recruiting
• Budget requirements by service line

Productivity Management

• Management of labor hours

• Labor hours and costs
• Patient acuity data

• Staffing requirements and projections
• Labor cost management

Clinical Process Improvement

• Rules base processing alerts to patient events
• Diagnostic and treatment prompts

• Patient clinical data
• External databases
• Critical paths and protocols

• QA
• Risk Management
• Cost Control
• Clinician education/ awareness

Critical Paths Protocols

• Std trmt procedures for cases
• Variance tracking and research

• Diagnosis procedure data
• Drug cost patient outcome data

• Physician profiling evaluation
• Clinical cost id, control, RM

Physician/Provider Profiling

• Treatment patterns case-mix
• Outcomes

• Diagnosis Procedure data
• Severity methods protocols

• Variance reports
• Clinical cost id and control

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Identification of Key Data SourcesClinical
SystemsClinical systems support the
documentation management for direct patient
care.
Application Function
Data Required Data Uses
Nursing Care Planning

• Clinical documentation
• Care planning
• Dosage calculation
• Acuity classification

• Patient clinical data
• Facility-defined care paths
• Dosage stds

• UR/QA
• Regulatory reporting and compliance
• Provider profiling.case management

Critical Paths Protocols

• Std trmt and procedures for similar cases
• Variance tracking and alerts
• Research support for clinical protocols

• Diagnosis and procedure data
• Procedure drug cost data
• Patient outcome data

• Physician profiling/ evaluation
• Clinical cost Identification and control
• RM

• Automated order verification
• Online inquires for orders
• Prompts for best practice
• Order set Maintenance
• Order explosion
• Automated results reporting

• Patient demographic and clinical information
• Ordering physician information
• Testing procedures, results
• Clinical protocols

• Management reporting
• Cost control
• RM
• QA/UR
• Medical records

Order Entry and Results Reporting
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Identification of Key Data SourcesClinical
Systems - cont
Application Function
Data Required Data Uses
Clinical Process Improvement

• Rules based processing alerts
• Diagnostic and treatment prompts

• Patient clinical data
• External databases
• Critical paths and protocols

• QA
• RM
• Cost Control
• Clinician education and awareness

Physician/Provider Profiling

• Treatment patterns
• Case-mix
• Outcomes

• Clinical diagnosis and procedure data
• Severity, risk adjustment methods
• Standard protocols

• Variance reports
• Clinical cost identification and control

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Identification of Key Data SourcesAncillary
Department Clinical SystemsAncillary systems
support the internal activities of a health care
organisations individual departments.
Application Function
Data Required Data Uses
Pharmacy

• Inventory tracking
• Regulatory compliance
• Medication risk management
• Order fulfillment

• Type of controlled substances
• Stock transfer data
• Rx transfer data
• Patient administrative and clinical data
• Location/expiration dates
• Rx service costs

• Regulatory reporting
• Inventory cost and space planning
• Patient/payer billing

Radiology

• Order fulfillment
• Film tracking
• Regulatory compliance

• Patient, clinical administrative data
• Location of films
• Radiology service costs

• Management reporting
• Patient/payer billing

Laboratory

• Type of controlled substances
• Lab ranges and values
• Pending orders
• Coding data, costs of orders

• Regulatory compliance
• Parameter definitions
• Worklists management
• Order fulfillment

• Patient /payer billing
• Order fulfillment
• Productivity management

Operating Room

• Scheduling, OR prep
• Inventory control

• Staffing costs
• Surgical supply preference

• Productivity
• Cost identification and control

81
Identification of Key Data SourcesPractice
Management SystemsThese systems support the
clinical and administrative activities relating
to physician practice.
Application Function
Data Required Data Uses
Scheduling

• Multiple procedure resource
• Conflict alert
• Recalls/reminders
• Variable time slots

• Patient demographic/clinical data
• Test requirements/procedures
• Resource availability and costs

• Cost control
• Productivity measurement,improvement
• QA/UR
• Resource/supply costing by patient group

Registration

• Inpatient admission or outpatient clinic
  registration
• Patient transfer or discharge
• Referral tracking

• Patient demographic insurance data
• Census information
• Treating physician information
• Patient clinical data
• Discharge instructions

• Population, census tracking
• Initiate and conclude services
• QI
• Cost control

Medical Records

• Chart deficiency tracking
• Coding
• Retention/evaluation

• Management reporting
• Patient/payer billing
• Provider deficiency profiling
• QA

• Patient demographic clinical, insurance data
• Patient medical records
• Deficiency types, HRGs
• Coding indices and edits

UR and Case Management

• Actual vs expected/contracted utilization

• Case mix by provider/contract
• Contract terms
• Patient diagnosis /procedures
• Patient demographic/Hx data

• Compliance with contract terms
• Provider profiling
• Utilisation control
• Contract profitability analysis

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Identification of Key Data SourcesSocial
Services/Mental HealthThese services support the
integrated health care spectrum surrounding
mental health and associated needs.
Application Function
Data Required Data Uses
Scheduling

• By patient, physician, resource
• Conflict alert
• Recalls/reminders
• Variable time slots

• Patient demographic/clinical data
• Visit requirements and procedures
• Resources
• Patient eligibility

• Cost control
• Productivity measurement
• QA/UR
• Resources
• Case Management

Clinical Documentation, Care Pathways/Plans/
Protocols

• Automated visit notes
• Assessments - ADL, SF-36
• Treatment and procedures for similar cases
• Severity adjust care plans
• Variance tracking
• Research support

• Clinical diagnosis (ICD-10, NANDA)- procedure
  visits
• Actual visits completed
• Drug cost data
• Outcome data,care paths
• Severity of illness measurement

• Clinician profiling and evaluation
• Clinical cost identification/control
• RM
• UR/QA
• Regulatory compliance reporting

Patient Management

• Patient demographics
• Registration/discharge
• Third party billing (UB-92)

• Patient demographics, medical Hx
• Required billing form data

• Case-mix
• Population studies
• Health status outcomes
• Patient tracking

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Identification of Key Data SourcesKey System
Focuses and Applications

System Focus Critical System
Applications

• Enterprise scheduling
• Enterprise patient index
• Enterprise capabilities for eligibility, benefit,
  utilization and protocols

Patient Administration Applications
Enterprise wide view uniform data accessible
across the System possibly uniform systems
support central business operations as required

• Clinical data repository
• Evolve toward electronic health record

Medical Records
Shift to single enterprise record
encounter-based longitudinal focus on patient

• Commissioning analysis
• Clinical case management/analysis
• Actuarial/risk-adjusted outcome analysis
• Patient satisfaction analysis
• Budgeting and productivity mgmt

Decision Support
Support multiple organisations and entities used
in pursuit of cost reduction, managed care
contracting, clinical continuum

• Common procedures, order protocols
• Computerized protocols
• Case management solutions
• Integrated ambulatory acute care
• Physician office result reporting

Clinical systems
Managing efficacy of care within contract
support continuum of care
84
Identification of Key Data SourcesEnabling
TechnologiesTechnologies have enabled providers
to utilize new and more efficient methods of data
communication.
Category What They Enable
Technologies

• Data warehouse clinical data repository
• Enterprise area networks
• Community health networks
• EDI

Networking and Telecommunications Technologies
More efficient, complete data storage and
communication. New ways to capture and store raw
data ability to communicate required data across
geography, facilities.

• Clinical workstation
• Data mining
• Graphical user interfaces

Networking and Telecommunications Technologies
Technologies that broaden the potential IT user
base, through more visual, intuitive presentation
and interpretation of data.

• Scheduling
• Case Management
• Protocol management
• Member health record
• Uniform eligibility database

Networking and Telecommunications Technologies
Work to integrate information - with associated
improvement in care quality and efficiency, cost
maintenance and control.

• Relational databases
• Interface tools,Query languages
• Graphical interfaces
• Open systems
• Client/server

Networking and Telecommunications Technologies
Technology available to develop and support new
applications. These technologies ease financial
and risk barriers to new development and shorten
application development timetables.
85
Groupwork

• You are building a transition plan for COPD.
  What would you need to know to
• identify success criteria, barriers and
  obstacles
• understand the different pressures across the
  system

86
Session 5
87

National Requirements
Learning from Others
Resources/ Costs
Population Health Needs Patterns of Service
Usage
Where want to be (Strategy)
Where are now
Commissioning Cycle
How get there (Transition Plan)
Review Impact and quality
Putting into operation
88
Program/Methods ForMonitoring/Influencing
Behavior of Physicians

• QUALITY IMPROVEMENT
• PRACTICE GUIDELINES
• DISEASE/CASE MANAGEMENT
• FEEDBACK/PROFILING

89
A Working Definition of Quality of Care

• Quality of care is the degree to which health
  services for individuals and populations increase
  the likelihood of desired health outcomes and are
  consistent with current professional knowledge.

90
Quality Improvement

• HMOs have an advantage in improving quality of
  care
• gtA defined population permits tracking
  population-based outcome measures.
• gtRelatively comprehensive benefit coverage.
• gtCommon medical record (group, staff models).
• gtCommon billing data

91

• Obstacles to Improving Quality of Care
• gtSkepticism of physicians and employers regarding
  organizational commitment to quality improvement.
• gtDifficulty in moving quality improvement efforts
  from the philosophical to the practical level.
• gtLack of MIS capacity needed to support quality
  improvement efforts.
• gtLack of expertise in evaluation of quality
  initiatives and their outcomes.

92
Physician Education

• Little evidence of effectiveness in changing
  behavior when used alone.
• Best employed in conjunction with more
  comprehensive efforts to alter practice patterns,
  such as clinical practice guidelines, profiling,
  and financial incentives.

93
Best Practices Aggregate Goals

• Define aggregate performance targets regarding
  clinical practice or patient outcomes
• Recruit a panel of physicians to develop strategy
  for achieving targets
• gtShare plan data
• gtCollect best practices of other managed care
  organizations
• Implementation
• gtFocus on what is best for patients rather than
  what is convenient for providers
• gtBe aware that change will generate fear of staff
  reductions and therefore resistance
• gtMake goals achievable under most circumstances

94
Quality ImprovementMajor Concerns

• Different explanations for poor plan performance
  can exist cookie-cutter responses are not likely
  to be appropriate.
• The problem is not always a clinical one health
  plan factors and community characteristics may be
  critical.
• Careful fact finding is necessary before data are
  released or corrective actions taken.

95
Clinical Practice Guidelines

• Premise if one can determine best practice for
  a clinical condition, and more physicians can
  learn to practice in this way, outcomes can be
  improved and costs reduced.
• At their best, guidelines represent the medical
  professions knowledge about how to best address
  a clinical problem
• Early clinical practice guidelines were not
  effective
• gtNot written for practicing physicians
• gtDistrust of guidelines written by experts - Not
  coordinated with physician financial incentives

96
Clinical Practice Guidelines(cont.)

• Recent generation of clinical guidelines hold
  greater promise
• gtStructured as tools to assist the physician
  clear that they are not intended to replace
  clinical judgment
• gtDevelopmental process involves local physicians
  and other health providers
• gtClear explanation of scientific basis
• gtEmphasis on implementation as well as
  development
• gtRecognition of need to continually revise and
  update guidelines
• gtCoordination with financial incentives remains
  an issue

97
Impact of Cystitis Clinical Practice Guideline on
Costs and Outcomes of Care

• Guideline developed to reduce variation and
  improve quality of care for women age 18 to 64
  with uncomplicated cystitis.
• Study involves sample of women with cystitis
  attending five primary care practices
• About half of all urinary tract infections seen
  in these practices were eligible for care under
  the guideline.
• Analysis compared 201 eligible cases seen before
  the guideline was implemented to 145 cases seen
  after the guideline was implemented.

98

Impact of Cystitis Clinical Practice Guideline
on Costs and Outcomes of Care

• Results
• gtUse of an antibiotic recommended by the
  guideline rose from 88 of cases to 95 of cases
• gtUse of 3 day course of the antibiotic rose from
  28 of cases to 52 of cases
• gtUse of a urine culture decreased from 69 of
  cases to 38 of cases
• gtVisits managed solely by physicians fell from
  65 of cases to 32 of cases.

99
Impact of Cystitis Clinical Practice Guideline
on Costs and Outcomes of Care

• Results
• gtProportion of cases coordinated primarily by the
  nurse rose from 19 to 57.
• gtSavings per case of 25.69 were 35 of total
  pre-guideline direct costs.
• Statistically significant

100
Feedback/Profiling Techniques

• Internal profiling
• External profiling

101
Feedback/Profiling Techniques

• General Issues
• Peer Comparison
• gtReport performance back to an individual
  physician or physician group along with
  comparative data from others
• gtMeaningful only if physicians agree that the
  comparison group is relevant
• Individual Feedback
• gtProvide an individual physician or physician
  group with data about own performance without
  comparative information. Meaningful only if there
  is an accepted norm or standard otherwise there
  is no anchor for the data

102
Feedback/Profiling Techniques

• Group or Aggregate Feedback
• gtProvide individual physicians with information
  on the performance of the larger group, but not
  on individual performance
• gtMeaningful only if individuals in the group can
  relate their performance to the groups
  performance

103
Retinal ScreeningTarget 90 - 5 points
104
COPDMax 45 points
105
Oxygen PrescribingItems per 1,000 Registered
106
J40-J44 - COPDNon-Elective Last FCEs XYZ PCT
discharge dates between January and December
2003 (Number of Discharges per 1000 List Size)
107
Experience with Feedback

• Individual feedback and peer comparison has been
  more effective than aggregate feedback because
  aggregate feedback has often been used with no
  norm for comparison
• Feedback is most useful in conjunction with other
  efforts
• Feedback is most effective when the objective is
  to increase utilization
• The effect of feedback is at its greatest when
• gtThere is a strong scientific base for
  comparative norms or goals
• gtThe data being fed back to physicians are
  relatively stable over time
• gtThere is case mix adjustment
• gtThere are clear actions physicians can take in
  response to the data (linkage to quality
  management)

108
Characteristics of a Potentially Effective
Profiling Approach

• Severity adjustments are essential.
• Outlier removal is desirable.
• Use more than one benchmark if possible (for
  example, for inpatient comparisons, length of
  stay and average charges).
• For each patient, calculate variance from
  comparison group average.
• gtVariance defined as (actual LOS-average LOS)
• Aggregate severity adjusted categories to
  meaningful service lines that approximate
  medical staff structures.
• Calculate average variance for each physician for
  each service line in which physician exceeds
  threshold volume of patients.
• Determine comparison groups
• gtPeer group at the hospital
• gtPeer group in local competitive area
• gtPeer group in region

109
Groupwork

• Consider COPD
• Which levers/incentives would be appropriate to
  your strategy from yesterday?
• What information/data do you need to access to
  support you in using these?

110
Session 6
111

National Requirements
Learning from Others
Resources/ Costs
Population Health Needs Patterns of Service
Usage
Where want to be (Strategy)
Where are now
Commissioning Cycle
How get there (Transition Plan)
Review Impact and quality
Putting into operation
112
Reviewing the Impact/Quality of Changes Put into
Place - Evaluation
Some Key Evaluation Terms
Acceptable Accessible Accomplishment Accountable
Accuracy Analysis Appropriate Available
Cohorts Comparison Content Context Control
Cost Data primary and secondary
Goals Judgment Metrics Norms
Objectives Outcomes Outputs Precision
Process Purpose
Quality Quantity Recording Reliability Reporting
Standards Synthesis Time Timelines
Validity Value Weighting Worth
113
PRECEDE-PROCEED Framework
Formative evaluation baselines for outcome
evaluation
Genetics
Phase 6 Implementation
Phase 7 Process evaluation
Phase 8 Outcome evaluation
Phase 9 Impact evaluation
New in 4th ed., Green Kreuter, Health Promotion
Planning, An Educational and Ecological
Approach, 2005 .
114
Evaluation

• PRECEDE Evaluation Tasks
• Specifying measurable objectives baselines -
  Formative Process Evaluation
• PROCEED Evaluation Tasks
• Monitoring Continuous Quality Improvement -
  Process, Outcome Impact Evaluation

115
Health Care Evaluation Measurement

• Things to Consider
• Comparing and contrasting various types of
  evaluation
• Identification of problems that may hinder an
  effective evaluation
• Reasons to conduct an evaluation
• The planning and conducting of an evaluation
• Defining metrics and methods to measure and
  report evaluation findings

116
Health Care EvaluationKey Ideas

• Evaluation is critical for all health care, and
  prevention/ health promotion initiatives.
• Evaluation must be designed early in the process
  of health care planning. Remember
  PRECEDE/PROCEED!
• The process of designing an evaluation must be a
  collaborative effort of all stakeholders.
• Evaluation ultimately becomes judgment. Who has
  the power to decide?
• Evaluation does not need to be a formal academic
  study
• Do you report successes, failures, strengths,
  weaknesses?

117
Health Care EvaluationPurposes

• 1. To determine achievement of objectives related
  to improved health status
• 2. To improve health program implementation
• 3. To provide accountability to funders
• 4. To increase community support
• 5. To contribute to the scientific base for
  community. public health interventions
• 6. To impact policy decisions

118
Health Care EvaluationDefinition

• Evaluation
• Determining the value or worth of the health
  care initiative against a standard of
  acceptability.
• To examine or judge.
• (The key is who establishes the standard and who
  judges!)

119
Health Care EvaluationElements

• Context What, when , where, and who
• Process How care is organized and
  delivered
• Content Program elements to be provided
  and why - available birdseed
• Output How many times did the bird flap
  its wings?
• Outcome Did the bird fly?
• Impact How high? How far? Where?

120
Health Care EvaluationTypes

• Process Evaluation Examines the procedures
  and tasks involved during the implementation of
  a program.

121
Health Care EvaluationTypes

• Process Evaluation
• When to use As soon as the health initiative
  begins
• What it shows How well a program is
  working as it goes
• Why is it useful Identifies early problems

122
Health Care EvaluationTypes

• Outcome Evaluation Used to obtain
  descriptive data on a project and to document
  short-term results. Focuses on an ultimate goal
  of a health care program or treatment. Generally
  measured by vital statistics in a population.

123
Health Care Evaluation Types

• Outcome Evaluation What you measure/count
• When to use For ongoing programs at appropriate
  intervals or for one time programs when program
  is complete
• What it shows Has program reached its ultimate
  goal.
• Why is it useful Learn from successes and for
  future funding.

124
Health Care Evaluation Types

• Impact Evaluation Is the most comprehensive
  type of evaluation because it focuses on the
  long-range results and the resultant improvements
  in health status.
• Impact evaluation is the most costly.
• Information obtained from an impact evaluation
  can include changes in e.g.,morbidity and
  mortality.

125
Health Care EvaluationTypes

• Impact Evaluation - What you want
• When to use After the health program has made
  contact with at least one person or a
  population
• What it shows Changes in knowledge, attitudes,
  and beliefs
• Why is it useful Allows management to modify
  resources effectively

126
Groupwork

• Using handout provided consider the following
• What data sources do you currently use?
• What would demonstrate that you are on track and
  achieving your goals?