Drive Healthcare Transformation with a Strategic Analytics Framework and Implementation Plan

Drive Healthcare Transformation with a Strategic Analytics Framework and

Implementation Plan

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Contents Covered in This Session

• Chpt 3 of your textbook

• Templates, Artifacts and Samples provided in the Course Content of Blackboard

• Sample Analytics Interview Questions

• Sample Analytics Use Cases

• BI Analytics Strategy Plan Presentation

• BI Analytics Strategy Plan and Roadmap

• Business Justification Document Sample

• Data Assessment Templates

• Chpts 1 – 3 of Healthcare Data Warehouses provided in the Reference Books Section of the Course Content

2HCAD 6635 Health Information Analytics Copyright © 2016 Frank F. Wang

Problem Domain

• Healthcare organizations (HCOs) are facing increasing quality, financial, and regulatory pressures, and must transform to achieve sustainability.

• The three fundamental information needs of healthcare improvement are to identify:

• What quality/performance/safety aspects need to improve?

• What processes must change to result in improvement?

• What change (if any) has occurred?

HCAD 6635 Health Information Analytics Copyright © 2016 Frank F. Wang 3

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What is an Analytics Strategy?

• A strategy that ensures analytics development and capabilities are in alignment with enterprise quality and performance goals Avoids the “all dashboard, no improvement” syndrome

• Helps to achieve optimal use of analytics Can mean the difference between a “collection of reports”

versus a high-value information resource

• Analytics Strategy should align with other relevant strategies including: Business Intelligence (BI) strategy

Information Technology (IT) strategy

Quality Improvement (QI) strategy


Building and Executing a Successful Framework

• Understand requirements Review strategy components with stakeholders

Identify how analytics are currently used

Determine what capabilities will be needed (short & long term)

• Identify gaps and mitigate risks List known/potential gaps and their mitigation approaches

Prioritize gap mitigation based on impact, effort, & cost

• Execute plan Assign task owners and target implementation deadlines

Monitor progress and apply mid-course corrections


Analytics System

Business & Quality Context

Stakeholders & Users

Processes & Data

Tools & Techniques

Team & Training

Technology & Infrastructure

HCAD 6635 Health Information Analytics 6

Strategic Analytics System Framework

An effective analytics system is more than simply a reporting/BI tool layered on top of a data source.

Copyright © 2016 Frank F. Wang 6

Strategic Planning and Development

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FiltersCurrent State Details

Assessment and Strategy Development

Business Drivers

Technical Landscape

Executive Summary

Data readinessassessment

Information Architecture

Organization Architecture

Project Management

Analysis and documentation Information gathering

Current State

Summary

Gaps Summary

Planning Documents

Strawman Vision

Program Analysis and

Planning

Analytical Processes

Needs Assessment

Technical Architecture

Functional Requirements

Best Practices

Relevant Client Experiences

Applicable Industry Trends

HCAD 6635 Health Information Analytics Copyright © 2016 Frank F. Wang



Analytics Strategy



Processes & Data

Tools & Techniques

Team & Training


Copyright © 2016 Frank F. Wang

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Business Context: Enterprise Goals, Objectives, and Strategy

• What are the Organizational Goals and Objectives? Are what the organization is aiming to achieve.

Define the performance and quality targets of the organization

Answer “why” the organization is (or should be) engaging in certain activities

• What are the Organizational Strategies? Outlines how the organization expects to achieve its goals

• Analytics must provide insight into past, current, and anticipated future progress towards meeting the enterprise goals.


Analytics Stack

Presentation

Visualization Dashboards Reports

Alerts Mobile Geospatial

Quality & Performance Management

Processes Indicators Targets

Improvement strategy Evaluation strategy

Analytics

Tools Techniques Team

Stakeholders Requirements

Deployment Management

Data

Quality Management Integration

Infrastructure Storage

Business Context

Objectives Goals Voice of patient

Focus on the BusinessAn abstracted Business Intelligence and Analytics stack helps maintain focus on key components of analytics required to address business and clinical goals.


Use Business Intelligence, Data Warehousing and Analytics to achieve the goals:

• Drive Member Value• Drive Patient Volume and Revenue Growth• Drive Clinical Excellence

Services will be consistent with the organization’s vision and mission and will:• Drive a growing base of patients

and revenues for members

• Build an environment that facilitates members’ future success

• Continuously reinforce a “value” message to the members

• Complement corporate values, goals, and long term objectives of our members

Aligning Business Objectives and Analytics Objectives (Example)


Key Business Objectives & Goals – Goal Alignment

Strategic Objectives Business Intelligence and Helps By…Increase Operational Efficiencies

• Minimizing FTE growth while increasing volume of referrals and cases

−Simplified data access to all data−Automation of processes (Reforecasting)

• Increases Margin & Contribution−Enable larger case loads

Improve Predictive Models • Improve Pricing/Budgeting of individual contracts−Simplified data access to all data−Improved Risk identification and mitigation

Scale an Increase in Business Volume

• Increase prospects, referrals & revenues−Quantitative/Benchmark analyses depicting value

• Identify/Support new products−Informatics Products−Identify market niches and opportunities

Increase Market Penetration & Open Up New Markets

Perform Clinical Data Analysis & Studies

• Improve clinical efficiency −Benchmark analysis (clinical and financial)−Identify Risks and mitigations

Improve Customer Satisfaction

• Improved response to customer inquiries−Simplified data access to all data

• Backlash from large “winner” contracts

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• Use Business Intelligence/Analytics to help us…

Why

BI?


Adding SWOT to Strategy

• Traditional “SWOT” analysis can be layered onto the components (and sub-components) of analytics strategy.

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Strengths Weaknesses Opportunities Threats



Data & Processes

Tools & Techniques

Team & Training



SWOT Analysis Brainstorming Example

Services will be Consequence

Services will be • Unprepared to determine impact and prepare for consumer driven healthcare

• Incapable of efficiently managing “pay for performance” on a widespread basis

• Unable to respond to bundled payment and ACO models

Services will be • Not leveraging the clinical value of our physician/patient relationships

• More time shepparding care data than analyzing it

Services will be • No proactive monitoring and remediation of contract and payment terms

• Limited understanding of network-wide customer base and how to get the most of our relationships

Services will be • Difficult to:– Determine the efficacy of programs and services– Forecast and plan based historical performance and trends

SWOT Analysis Brainstorming Example

• Organization is seen as the connective tissue between in/outpatient patient experience and the hospitals and medical staffs. Organization is best positioned to provide an integrated view of:

PatientsPayersProvidersProduct & ServiceEmployer

Migrate from reactive and ad-hoc to proactive and systematic Less data, more information and furthermore, predictive and

prescriptive analytics Intuitive access (ease of use and quality) Informed decision making (data correlation and timeliness) Use information to do more with less (or same) Protect physician and patient privacy Safeguard intellectual property Do unto Payers as they do unto us

Payment Care Delivery Outcomes


Aligning Strategic and Tactical Quality Objectives

• Analytics is the “glue” which ties strategic objectives and tactical activities together.

• Objectives of unit- or department-based improvement initiatives should, where possible, align with the quality objectives of the organization as a whole.

• Prevents misdirected/wasted activity

• Enables the HCO to monitor progress and evaluate outcomes

Strategic Level Strategic Objectives

Analytics Metrics Indicators Targets

Tactical Level Tactical Objectives

A reminder that the customer (“the patient”) is the ultimate reason for the work we’re doing.

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Voice of the customer


Business Goals: Strategic and Tactic

Strategic Objectives Tactic GoalsIncrease Operational Efficiencies

• Maintain sub-linear scalability in Operations while increasing volume of referrals and cases

• Increase Margin & ContributionImprove Predictive Models • Improve Pricing/Budgeting of individual

contracts through the use of existing cases informatics

Scale an Increase in Business Volume

• Increase revenues by four-fold within 48 months

• Deploy new products/services through acquisition and new product developmentIncrease Penetration of

Existing Market & Open Up New Markets

Perform Clinical Data Analysis & Studies

• Improve clinical efficiency through the ability to use improved BI, (i.e., use of trends, benchmarks, and predictive analysis techniques to identify opportunities, plan interventions and measure outcome results)

Improve Customer Satisfaction • Through all of the above

17Copyright © 2016 Frank F. WangHCAD 6635 Health Information Analytics

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Quality Strategy / Improvement Approach

• Quality Strategy outlines the steps and approach the organization is going to be taking to achieve quality goals/objectives.

• Which QI approaches are utilized (i.e., Lean, Six Sigma) will impact what data is required, how it is analyzed, and how it is communicated.

• Analytics development teams and quality improvement teams must work closely together

to ensure that information requirements of users and the delivery by via analytics are in sync.

• When executing the analytics strategy, always ask “are we taking appropriate and necessary steps towards achieving the organization’s quality and performance goals?”


HCAD 6635 Health Information Analytics


Analytics Strategy



Processes & Data

Tools & Techniques

Team & Training



Stakeholder Analysis

• A stakeholder is a person (or group of persons) that are: impacted by, users of, or otherwise have a concern (or interest

in) the development and deployment of analytical solutions throughout the healthcare organization.

• When developing an analytics strategy, it is important to understand what each of the likely analytics stakeholders will require, and develop approaches to ensure they are getting what they need.


HCO Stakeholder Types

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Stakeholder DescriptionPatient The person whose health an healthcare experience

we’re trying to improve with the use of analytics

Sponsor The person who supports and provides financial resources for the development and implementation of the analytics infrastructure

Influencer A person who may not be directly involved in the development or use of analytics, but who holders considerable influence over support of analytics initiatives.

Customer / User A person in the HCO who accesses analytical tools, or uses the output of analytical tools, to support decision making and to drive action.


Source: HealthIT Analytics, "EHRs Don't Do Enough for Care Coordination, Docs Say," Jennifer Bresnick, January 19, 2015 http://healthitanalytics.com/news/ehrs-dont-do-enough-for-care-coordination-docs-say/

83% of physicians are frustrated by EHR usability, interoperability and integration.

If We Do Not Listen to Our Stakeholders


http://healthitanalytics.com/news/ehrs-dont-do-enough-for-care-coordination-docs-say/

Source: Accenture, "2015 Healthcare IT check-up shows progress (and some pain)--Infographic"https://www.accenture.com/us-en/insight-2015-healthcare-it-check-up-shows-progress-pain-infographic.aspx

Interoperability: 51% of US doctors in 2015 routinely access clinical data of a patient who has been seen by a different health organization, slightly up from 45% in 2012.

Then We Can Not Expect Higher Adoption Rate


https://www.accenture.com/us-en/insight-2015-healthcare-it-check-up-shows-progress-pain-infographic.aspx

Barriers to Physician Engagement

A McKinsey report highlights four key concerns and barriers:• Physicians feel overwhelmed and ill-equipped to

effect change. They lack an understanding of their part in healthcare waste and inefficiency.

• Hospitals and payers believe that employing physicians is the primary means of securing alignment.

• Organizations have the misconception that compensation is one of the most important drivers for physicians.

• Physicians have a poor understanding of the risk-based payment model along with being risk-averse.


http://healthcare.mckinsey.com/sites/default/files/MCK_Hosp_MDSurvey.pdf

Steps to Gain Physician Buy-in

The Institute for Healthcare Improvement put together a framework of six elements to encourage physician buy-in for a shared quality agenda:• Discover a common purpose

• Adopt an engaging style and talk about rewards

• Reframe values and beliefs

• Segment the engagement plan and provide education

• Use “engaging” improvement methods

• Show courage and provide backup


http://www.ihi.org/resources/Pages/IHIWhitePapers/EngagingPhysiciansWhitePaper.aspx

Who We Spoke To (Stakeholder Interview)

Area ResourcesAccount Management ABC

Clinical Services MD ……

Company Overview StuartController MichelleFinance KevinHuman Resources ErinOperations SethProduct Development StuartProvider Administration StuartSales, New Business Development

Tom

QA/Corporate Compliance SharenIT Russell

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Interview Key Stakeholders: Common Themes (Example)• Data is not centralized; rather it is distributed across multiple systems and

requires multiple tools. Switching tools takes a lot of time.

• Significant time is spent manually consolidating data before it can be

effectively utilized/analyzed.

• The current tools do not readily provide the query capabilities users want.

• Some datasets are stale and don’t reflect the most recent data.

• Some clinical data is still only captured as unstructured data which can only

be searched as free text.

• Lack of clear and consistent definitions of common business terms and data

labels.

• New analyses/reports are funneled through 1-2 very busy individuals. No “self service” capability for creating new analyses.

• Lack of “benchmarks” in providing quantifiable benefits of services. Such

benchmarks are not readily available in the marketplace.27

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Analytics Use Cases

• A use case is a brief description of how analytics will be used by a stakeholder. Analytics use cases can help to: identify any gaps in analytics capabilities, and

reduce the likelihood that critical analytics needs will be missed.

• Analytics use cases help identify: what data elements are most important and what indicators will

be necessary to calculate, and

what types of usability and presentation factors (such as dashboards, alerts, and mobile access) need to be considered.

• Develop high-level use cases when outlining the analytics strategy, and drill down in more detail as new analytical applications are designed and built.


Analytics Use Cases Example

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Customer / user

Sample use case(s)

Physician Uses personalized performance report to adjust care practices.

Unit manager Determine which patients are likely to exceed length of stay targets.

QI team leader Identify bottlenecks in patient flow.Evaluate outcomes of QI initiatives.

Healthcare executive

Evaluate and monitor overall performance of the organization.


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Financial Analytics Business Needs Assessment and Use Cases Example

Typical Business Questions

• What are the utilization rates for a given procedure?

• Are the service lines making a higher margin this year than last?

• Which services have a high or low profit margin? Do we have unprofitable procedures that act as ‘loss leaders’?

• What is the cost/reimbursement (actual or estimated) ratio by procedure or diagnosis? By payer?

• What variability in volume, reimbursements, revenue or cost do we see between physician, by specialty, by patient demographics, by patient diagnosis or by procedures provided over time?

Primary Business Functions EnabledService line optimization Facilities planningStaff planning Profit optimizationInvestment prioritization

Primary Metrics and KPIs• Percent growth in net revenue• Increase in Service Line Market

Share• Revenue• Operating Expenses• Operating / Total Margin• Supply Expenses• Salaries and Benefits / Labor

Costs• Purchased Services• Utilities, Repair & Maintenance• Insurance & Rent• Miscellaneous Expense• Depreciation/Amortization• Interest Expense• Hospital (Entity) Allocation

EBIDA %• Total Operating Expense per

Adjusted Patient Day • Net Patient Revenue per

Adjusted Admission

Metric/KPI Context• Date / Time• Month / Year • Visit (ambulatory) / Encounter

(acute)• Episode (Ambulatory only)• Procedure• Payer / Payer Type• Patient Population• Patient Type (IP, OP)• Physician / Nurse / Care Giver• Group / Care System / Entity /

Dept• Diagnosis / Condition• Service Code / Charge Code /

Service Type• Service Line

Typical Business Questions

• What are the utilization rates for a given procedure?

• Are the service lines making a higher margin this year than last?

• Which services have a high or low profit margin? Do we have unprofitable procedures that act as ‘loss leaders’?

• What is the cost/reimbursement (actual or estimated) ratio by procedure or diagnosis? By payer?

• What variability in volume, reimbursements, revenue or cost do we see between physician, by specialty, by patient demographics, by patient diagnosis or by procedures provided over time?

Primary Business Functions EnabledService line optimization Facilities planningStaff planning Profit optimizationInvestment prioritization

Primary Metrics and KPIs• Percent growth in net revenue• Increase in Service Line Market

Share• Revenue• Operating Expenses• Operating / Total Margin• Supply Expenses• Salaries and Benefits / Labor

Costs• Purchased Services• Utilities, Repair & Maintenance• Insurance & Rent• Miscellaneous Expense• Depreciation/Amortization• Interest Expense• Hospital (Entity) Allocation

EBIDA %• Total Operating Expense per

Adjusted Patient Day • Net Patient Revenue per

Adjusted Admission

Metric/KPI Context• Date / Time• Month / Year • Visit (ambulatory) / Encounter

(acute)• Episode (Ambulatory only)• Procedure• Payer / Payer Type• Patient Population• Patient Type (IP, OP)• Physician / Nurse / Care Giver• Group / Care System / Entity /

Dept• Diagnosis / Condition• Service Code / Charge Code /

Service Type• Service Line


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With Financial Analytics, We Are Able to …

TO SYNTHESIZETO GATHER TO ANALYZE TO ACT TO INFLUENCE

USE THESE INPUTS

RESULTING IN

• I:Manage• Avega• EPIC• Master Data / Reference Data

• Monthly trended financial results

• Service line financial scorecards

• Standard Financial Reports

• Ad-Hoc queries• Data Mining

• Variance analysis results

• Revenue opportunities and challenges

• Long-term revenue opportunities

• Investment opportunities

• Service line investments / divestitures

• Capital investment strategies

• Revenue and costs• Budgeted results

• To optimize revenue potential of service line components

• To optimize resource allocation

• By managing spending

• Revenue loss root cause• Underperforming service lines

• Underperforming care systems

• Changes in cash flow

• Resources focused on growing service areas

• Targeted cost reduction projects

• Staff redeployment• Practice interventions

• Focused strategic growth

• Leverage of capital investments

• Variance to Budget• Identified deviations from expected results

• Identification of significant revenue changes

• Gross Revenue• Gross Margin• Total Margin• Income and expense against budget

• Income statements by service line

• Balance sheets • Reference data normalization

• Variance root cause analysis

• Isolating improvement opportunities

• Identification of growth opportunities or cost savings

TO SYNTHESIZETO GATHER TO ANALYZE TO ACT TO INFLUENCE

USE THESE INPUTS

RESULTING IN

• I:Manage• Avega• EPIC• Master Data / Reference Data

• Monthly trended financial results

• Service line financial scorecards

• Standard Financial Reports

• Ad-Hoc queries• Data Mining

• Variance analysis results

• Revenue opportunities and challenges

• Long-term revenue opportunities

• Investment opportunities

• Service line investments / divestitures

• Capital investment strategies

• Revenue and costs• Budgeted results

• To optimize revenue potential of service line components

• To optimize resource allocation

• By managing spending

• Revenue loss root cause• Underperforming service lines

• Underperforming care systems

• Changes in cash flow

• Resources focused on growing service areas

• Targeted cost reduction projects

• Staff redeployment• Practice interventions

• Focused strategic growth

• Leverage of capital investments

• Variance to Budget• Identified deviations from expected results

• Identification of significant revenue changes

• Gross Revenue• Gross Margin• Total Margin• Income and expense against budget

• Income statements by service line

• Balance sheets • Reference data normalization

• Variance root cause analysis

• Isolating improvement opportunities

• Identification of growth opportunities or cost savings


Organizational Assessment

• Recently embraced and embarked on a strategy for BI/Analytics Executive sponsorship exists at VP and Sr. Director level

A data warehouse is under development

• Does not yet have a formal BI/Analytics Executive Steering Committee Broad and formal representation should exist

• No formal Data Governance or BI/Analytics Competency Center Focus is on providing analyses – Not on providing users with tools and training to be self-sufficient

Lacks direction toward a single, consolidated approach to business metrics

Lacks formal data governance and data quality (data stewards) roles and processes

• No dedicated Development team with needed analytics skills/experience Existing Applications Development team doing all development

Existing team has little or no experience in data warehousing and BI/Analytics

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Processes & Data

Analytics Strategy



Processes & Data

Tools & Techniques

Team & Training



Data Considerations

• Data is the “raw material” of analytics.

• Modern computerized clinical systems (such as electronic medical records) contain dozens if not hundreds of individual data elements. The potential exists for thousands of possible data items from which to

choose for analytics.

• An analytics strategy must consider: how to determine which data is necessary for quality and

performance improvement

how the data is managed and its quality assured

how data links back to business processes for necessary context.


Data Issue ExampleData Sources • What are the sources of data?

• What data is necessary to address key business issues?

Data Quality • How good is the quality of available data?• Is the data “good enough” for analytics?• What gaps in data exist?• Does metadata exist?

Data governance • Who is responsible for data management, governance, and stewardship?

• What policies and procedures exist?

Business Processes • What business processes and procedures align with important quality issues?

• What data is available for measuring processes? Are proxy measures available?

Data Considerations for Analytics Strategy

35Copyright © 2016 Frank F. WangHCAD 6635 Health Information Analytics

Data Assessment

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• Data is not complete, integrated or organized for the enterprise Multiple versions of the data exist on

different platforms Multiple sources of data & tools to answer

a single question Common definitions of terms are not

defined or widely understood

• Users spend too much time as data gatherers and integrators, rather than as analysts No reuse leads to redundant effort and

inconsistent results High risk of errors

• Little or no data quality processes No audit, balance and control No formal Master Data Management (e.g.,

Provider)

• No metadata management Business terms are not standardized and

shared Business rules are not standardized and

shared

many “data domains”no single trusted source inefficient redundancy

no data integrationno data governance

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Allergic asthma 389145006

Aspirin-induced asthma 407674008

Acute asthma 304527002

Drug-induced asthma 93432008

Work aggravated asthma 416601004

Allergic bronchitis 405720007

Chemical-induced asthma 92807009

Brittle asthma 225057002

Sulfite-induced asthma 233688007

Millers' asthma 11641008

Asthma attack 266364000

Asthma night-time symptoms 95022009

Etc.

SNOMED CT

Asthma 95967001

Asthma, Unspecified Type, unspecified 493.90

ICD9CM

Metadata is Data of DataMetadata is a set of data that describes and gives information about other data.


Business Processes

• Business processes provide essential context to the data.

• Most quality improvement methodologies monitor progress and evaluate performance and outcomes using indicators based on process data. Requires a strong alignment between key business processes

and the data that measures those processes.

• As part of the analytics strategy, consider: if and how current business processes are documented, and

how data items are mapped to these documented business processes.

stacks of Visio charts becomes unmanageable very quickly!


• Using appropriate indicators that align between tactical and strategic levels are necessary.

Tactical-level sub-indicators should align with strategic indicators

Some tactical-level-specific indicators might be necessary for initiatives that are important at a program, department, or unit level, but don’t directly align with strategic goals.

Indicator

Sub-Indicator 1

Sub-Indicator 2

Sub-Indicator 3

Strategic Level

Tactical Level

Tactical Indicator 1

Using Appropriate Indicators

39HCAD 6635 Health Information Analytics Copyright © 2016 Frank F. Wang 39

Strategic and Tactical Indicator Alignment Example

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95% of patients admitted from ED achieve EDLOS < 8hrs

Time to physician

assessment

Time to consult

answered

Time to consult decision

Strategic Level

Tactical Level

Time to inpatient bed

assigned

Time to patient left ED


Analytics Tools and Techniques

Analytics Strategy



Processes & Data

Tools & Techniques

Team & Training



Common Analytical Applications

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Analytical Application DescriptionStatistical • Used for deeper statistical analysis not available in

“standard” business intelligence or reporting packages

Visualization • Used for developing interactive, dynamic data visualizations that aid with analysis

Data Profiling • Helps to understand and improve the quality of an HCO’s data.

Data Mining • Analysis of large data sets to uncover unknown or unsuspected relationships.

Text Mining • Analysis of unstructured, text-based data to extract high-quality information.

Online Analytical Processing • Allows analysts to interactively explore data by drilling-down, rolling up, or “slicing and dicing” data.

Copyright © 2016 Frank F. WangHCAD 6635 Health Information Analytics

Inventory of Existing Analytical Tools

• Analytical tools must meet the requirements of analysts building analytics solutions/applications, and the end-users who will rely on the resultant information and insight.

• Conduct an inventory of existing analytics tools to

determine if: Capability is missing that will be required

Existing capability exists that may not be widely known

• Identify viable best-of-breed vendor solutions that meet requirements; custom-build from scratch if necessary or if participating in research.


Analytics Tools Assessment Example

• HCO recently started down the road to BI/Analytics Development of DW, strategy, processes, and standards underway

Consider evaluation of Information Delivery tools (e.g. SAS, Cognos)

• Current and targeted hardware is appropriate Size of data and organization does not warrant more powerful hardware

• Current software direction is appropriate Crystal Reports not fully utilized

Microsoft BI Tool suite is a good fit

Already invested in Microsoft technology (SQL Server, SharePoint, CRM, etc.)

Existing licensing will cover expected needs for near-term

“best of class” tools are overkill with unjustifiable ROI

SAS licenses are not current and tool is not currently in use

Additional software needed

• Data modeling – a more formal tool/process should be adopted

• Metadata – no good tool on the market 44

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Team and Training

Analytics Strategy



Processes & Data

Tools & Techniques

Team & Training



Team Development Considerations

• People are a critical consideration when developing or expanding an analytics capability within a healthcare organization

• Although having the best tools are nice, having the best (and right) people is critical to achieving the goals and objectives of the HCO

• An analytics strategy must consider: What kinds of people (and the skills they bring) are necessary

The optimal size and composition of the team

Roles and degree of specialization

What gaps in skills exist, and what training is required

How to attract the best analytical talent

How to retain the analytic talent within your HCO

Optimal organizational structure


Providing Analytics Training as part of Physician Engagement Plan

• Achieving improvements in today’s world of value-based care requires physician buy-in because their decisions drive the majority of quality and cost outcomes.

• Provide administrative support, data analytics and reporting, and the training needed for improvement.

• Listen to and address physician’s concerns to gain their trust and get buy-in and enthusiasm for quality improvement efforts.



Technology and Infrastructure

Analytics Strategy



Processes & Data

Tools & Techniques

Team & Training




• Analytics and reporting are the tip of the iceberg in the business intelligence stack.

• The current, near-term, and long-term analytics needs of the HCO must drive how analytics-related technological capabilities are acquired. The exact complement of tools will depend on the overall needs of the HCO.

• The analytics strategy is an important input to IT hardware and infrastructure strategies and planning as hardware and other system upgrades are considered.


Healthcare BI and Analytics Technology and Infrastructure

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Source:

Evelson, B. It's Time to Reinvent your BI Strategy. Forrester Research, Inc.

Reporting and analytics are the “tip of the iceberg” regarding the business intelligence technology stack.


Organizational Considerations

• Different resource management models exist for analytics teams: “centralized” analytics office

“distributed” analytics resources

“virtual” center of excellence / competency center (combines best aspects of centralized and distributed models)

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Virtual Business Intelligence / Analytics Competency Centre

Senior Management

Decision Support Services

(Analytics)

Central (“Core”) Analytics Analysts

Surgery Program

Program Analytics Resource

Medicine Program


Emergency Program



Strategy Implementation

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Strategy Execution Summary

• It is important to implement and adhere to the analytics strategy

• Plan for and schedule activities to address identified gaps

Establish a selection criteria to determine what projects will get emphasis in light of needs of the business and analytics strategy

Prioritize activities and desired capabilities to balance resources as new (possibly conflicting) work arises

• Monitor progress towards achieving goals of the analytics strategy

• Ensure that the strategy is a living document that serves as a roadmap for guiding action and doesn’t become “shelfware”

Copyright © 2016 Frank F. WangHCAD 6635 Health Information Analytics53

Implementation Challenges

Program Needs Healthcare ChallengeExecutive Support Executives have to manage organization’s staff to

get their cooperation and buy-in.

Well-Defined Business Challenge

Business challenges are everywhere. The real problem is prioritizing which one to address first.

Lots of Data There’s lots of data but a lot of it is locked in departmental silos which ultimately makes all the data useless.

Right Team The challenge will be finding qualified people in an already scarce resource pool and getting them to accept the lower wage healthcare may pay. Outsourcing might need to be an option. Bottom Line: GET HELP!

Integral Part of Organization Everyone must buy-in to the results of the analytics program including clinical, finance and operational staff.

Track Results and Update Models

With the right team in place this should not be an issue.

Copyright © 2016 Frank F. WangHCAD 6635 Health Information Analytics 54

Strategic Planning and Development

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FiltersCurrent State Details

Assessment and Strategy Development

Business Drivers

Technical Landscape

Executive Summary

Data readinessassessment

Information Architecture

Organization Architecture

Project Management

Analysis and documentation Information gathering

Current State

Summary

Gaps Summary

Planning Documents

Strawman Vision

Program Analysis and

Planning

Analytical Processes

Needs Assessment

Technical Architecture

Functional Requirements

Best Practices

Relevant Client Experiences

Applicable Industry Trends


Gap Analysis

• Identify important gaps between current and future state, what the corrective action(s) will be, who owns the actions, and what the due date for corrective actions is.

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http://www.mindtools.com/pages/article/gap-analysis.htm

Category Current State Target State Corrective Action Priority Owner Due Date



Data & Processes

Tools & Techniques

Team & Training



http://www.mindtools.com/pages/article/gap-analysis.htm

Prioritizing Gap Corrective Actions

• Use the Impact / Effort matrix to help quantitatively determine priority for addressing analytics gaps.

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Q1

Impa

ct (i

ncre

asin

g)

Effort/Resources Required (increasing)

Q4

Q2 Q3

Low impact, Low effort“Consider”

High impact, Low effort“Immediate”

High impact, High effort“Evaluate”

Low impact, High effort“Avoid”


Assessing Business Value and Process and Data Readiness

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Score Profile Ranking

0.0

1.0

2.0

3.0

4.0

5.0Clinical Quality (In Setting)

Patient Experience / Satisfaction

System Performance Analysis

Cost Tracking & Variance Analysis

Safety Tracking

Patient Flow Optimization

Clinical Quality (Out of Setting)

Corporate Top Level KPI's

Physician Demand Management

Patient Demand ManagementRevenue Cycle / Charge Integrity DNFBRevenue Cycle / Patient Access

Staffing Management / Utilization(at department/low level)

Service Design / Redesign

Strategic Workforce Planning

Materials Management

Engagement

Payer Analysis; Contract Negotiation; Pricing Analytics

Revenue Cycle / Patient Financial Services'

Clinical Trial Inception and Monitoring

Research Grant Application and Tracking

Expected Business ValueProcess… ReadinessData Readiness


59

Prioritizing Data Subject Areas Example

Sales /Acct Mgmt

Clinical

Claims

Financial

Network Mgmt

Provider

Contracts

Lower HigherImplementation Readiness

Higher

Lower

Bus

ines

s Va

lue

Business Value: qualitative, mission-based assessment Readiness: ease of data integration, given quality, number of sources, completeness, etc.

• Incrementally delivering BI value begins with an understanding of data readiness and its value to the business

Case Mgmt

Impl

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oadm

ap

1

3

2


At the End of a Strategy Planning, Detailed Documents and Presentation Are Prepared to Obtain Management Buy-in

• Project Objectives & Approach

• Current Environment Assessment Data Organization Technology

• Future State Recommendations Business Process & Data Gaps Architecture Organization

• Implementation Roadmap Recommended Priorities Recommended Phasing Resource & Budget Estimates

• Why BI/Analytics? Benefits & ROI Considerations

• Summary & Next Steps to Success


Current Environment Assessment

62

Overall BI and Analytics Assessment – Where we are Now

Data

Organization

Technology

Best inClass

Cur

rent

Ass

essm

ent


63

Assessment Summary – Using the Analytic Maturity Model

STAGE 1REPORTING

WHAT happened?

Primarily Batchwith Pre-defined Queries

STAGE 2ANALYZING

WHY did it happen?

Increase inAd Hoc Queries

STAGE 3PREDICTING

WHAT will happen?

Analytical Modeling

Grows

STAGE 4OPERATIONALIZING

What IS happening?

Continuous Update & Time Sensitive Queries

Gain Importance

STAGE 5ACTIVE

Analytics

How do we MAKE it happen?

Event Based Triggeringtakes hold

Batch Continuous Update / Short Queries

Event-Based TriggeringAd Hoc Analytics

You are here

Cur

rent

Ass

essm

ent


Current Assessment: Data Assessment Findings

• Implement New Accounting Method

• Evaluate and Deploy Enhanced Accounting System

• Employer Industry Coding – SIC/NAICS Codes

• Contract Reject Reason Codes

• Claims OCR and Pending Claims

• Service Code Mapping Update

• Revised Reforecasting

• Obtain Industry Benchmarks

• Fully deploy Customer Relationship Management

• “Other” Clinical Data

• Data Product Strategy Definition

64

Futu

re S

tate

Rec

omm

enda

tions


65

Current Landscape BI/Analytics Architecture (AS IS Sample)

Source

Systems

Existing

Planned

Retiring

External

Data Flows Existing Planned Manual

Serve Excel and/or

Access

Store(RDB/ODS/DW/DM)

Siemens

Cred File

QuestLabs

Hoovers

Ecare Online

EPIC

CHSClaims

PMMC ContractPro

ECHO

CareScience

Web Server

PayerMaster

EmployerDatabase

MemberInvoicing Tool

AgreementSummary

Transplant

Great Plains

Fee Schedule

Colon CancerScreening

Medassets

Cost DataEligibility

Acct PayableFixed Asset

GL / Invoicing

Physician,Clinical,

&Fin. Data

Find aDoctor(Web)

Hosp ClinicalAnd Financial

Data

ClinicalPerformance

Inits

Transplant/Distribution

Invoicing/Receivables

EmployerRelationsReporting

ReinsuranceRecovery

Meditech

PatientRegistry

Lab Data

Central BenefitVerification Planned

CentralBenefit

VerificationUnit

Employer(Access)

Reference & Ad Hoc(Access)

PatientCharts

PMMC Physician Pro (CDR)

DW

Various Physician AppFeeds (Medisoft, Misys, etc.)

Lab Data

Transplant(Access)

Clarity

UHC

Med Labs


Process and Data

Future State & Recommendations

Future State and Recommendations – Data Example• Implement New Accounting Method• Evaluate and Deploy Enhanced Accounting System

Issue Action• Change in accounting method

impacts requirements for Finance data

• Current process/tools for creating financial (GAAP) results:

− Are not efficient or timely− Do not readily support BI &

integration to a Data Warehouse

• Select and fully implement new accounting method before integrating this data with a BI solution

• Evaluate project-based accounting systems as these support business activities for:

− Contracting for a defined body of work/services (a project)

− Budgeting for delivery of products and services

− Defining project tasks and track status− Assigning resources to a project/task− Collection of expenditures (i.e. Claims)

for the delivery of products and services− Invoicing of customers− Revenue recognition based on project

activities (using various methods)

Result• More efficient and timely accounting close cycle• Robust data source of financial results for use in BI

67

Futu

re S

tate

Rec

omm

enda

tions


• Employer Industry Coding – SIC/NAICS Codes

Issue Action• NAICS Industry codes are not

currently being captured even though ARCH supports this

• Industry information is needed to support Contracts Analytics

• Implement processes to ensure collection of Industry codes via:

− Employer contact− Web-base service− D&B service

Result• More complete demographics information to support industry-based

analysis (i.e., Marketing)Futu

re S

tate

Rec

omm

enda

tions


Future State and Recommendations – Data Example

• Contract Reject Reason Codes

69

Issue Action• Reject reasons are not currently

captured accurately for all declined contracts

− 50% of rejected contracts since the beginning of 2006

− $13,000,000 of contracts• Limits Client’s ability to analyze

rejected contracts and forming strategies to increase conversion rates

• Implement process and system changes to require a Reject Reason be specified when a contract is rejected

Result• Basis for understanding why contracts are rejected• Definition of goals and processes to reduce specific types of rejects• Increase conversion rate and revenue

Reject Reasons By Contract Value

No Reason

Cost

Carrier to Manage

Noncompensable

Rescinded Contract

Employer Request

Other

Futu

re S

tate

Rec

omm

enda

tions



• “Other” Clinical Data

Issue Action• Valuable clinical data is currently

being captured as “Other Data” (free text in CATS)

• Hinders BI support of clinical analyses

− Manual searches of clinical records for conditions and risk factors not predefined in CATS

• Assess the benefits of capturing this data as structured data

• Weigh against the costs of implementation options:

− Replacing InfoPath forms to enable capture of structured data at point of care

− Implement new processes (CATS) to identify and structure (with user input) such “Other data” after the point of initial entry

− Deploy Knowledge Management or search tools to enhance search-ability of clinical records

Result• Codification of all diagnoses, treatments, etc. for a case• Enhanced clinical analysis• Improved risk identification/mitigation and treatment plans

70

Futu

re S

tate

Rec

omm

enda

tions



• Data Product Strategy Definition

Issue Action• Data products generally utilize

industry standard coding schemes (i.e., CPT, HCPCS, ICD, etc.)

• Not all Client data is collected using such standards:

− Clinical assessments (CATS)− Contract budgets and

classifications (ARCH)• Only Claims data is captured

using such standards

• In defining a product strategy based on Client’s existing data, weigh the costs to:

− Convert existing to appropriate industry standards (at a sufficient level of detail)

− Modify processes and systems to capture data in accordance with such standards

Result• Viable product strategy (including all costs to deliver)

71

Futu

re S

tate

Rec

omm

enda

tions



Future Technical Architecture Recommendation Example

• Current and targeted hardware is appropriate Size of data and organization does not warrant more or different

• Current software is appropriate, but should be augmented Microsoft BI Tool suite is the right size and fit for Paradigm

Already licensed for SQL Server, and SharePoint (incl. SSIS, SSAS, SSRS, and Excel

Services)

Given analytics maturity and size, growing with Microsoft BI solutions makes sense

Probable upgrade to Enterprise Edition of SQL Server

Adopt SAS (or equivalent tool) on limited basis where/when needed (i.e., with Clinical data)

• Data modeling – a more formal tool/process should be adopted

(Microsoft or ERwin)

• Metadata Management

72

Futu

re S

tate

Rec

omm

enda

tions


Organization


74

Enterprise Business Intelligence/Analytics Governance

• Ensures EDW/BI/Analytics projects align with the business vision so that

Right projects done at the right time, driving optimum business benefit

Data standards are followed Data integrity and quality Facilitate data ownership

issue resolution An enterprise-wide ‘business’

perspective is taken into account

Development Team

• Define, Design, Build, Test, & Deploy

• Tool Evaluation and Support• Technical Support• BI Architecture and Infrastructure

Data Governance Team(Data Stewards)

• Develops Business Rules• Enforces data policies in terms

of data validity, accuracy, ownership

BI and AnalyticsExecutive Committee

• Strategic Direction & Business Alignment

• Sets Policy• Proposes Funding• Meets quarterly

• Business & IT Leaders• Tactical Direction & Cultural

Change Agents• Resolves cross-functional Issues• Presents recommendations to

Executive Committee• Meets monthly

Advisory Committee

Competency Center (Analytic Stewards)

• End-user Support• Tips & Techniques• Exchange Successes• Usability Feedback• Standard Measures • Liaisons to customers

Futu

re S

tate

Rec

omm

enda

tions


Architecture


TECHNOLOGY – HIGH LEVEL LANDSCAPE (VISION STATE)

SatisfySource

UHC

Store

Cred File

QuestLabs

Hoovers

eCare Online

CHSClaims

PMMC ContractPro

ECHO

CareScience

Web Server

Eligibility

Meditech

Med Labs

PatientCharts

PMMC Physician Pro (CDR)

DW

Various Physician AppFeeds (Medisoft, Misys, etc.)

Stage

Web SiteEnterprise

BI Tool

Executive Dashboards

EnterpriseReports

Ad hoc & OLAPReports

Data Mining/Modeling

Organization, Stewardship and GovernanceData Quality and Meta Data Management

Systems

Existing

Planned

External

Data FlowsExistingPlannedManualData Back to Sources

EDWAnalytics

Master & RefData

EPIC

Lab Data

Data StewardsMatch/Merge

Data GovernanceMaster Data Management

MedAssets



EDW and Analytics System Hosting Options

77

With this model, the vendor connects your data sources to a secure, HIPAA-compliant environment in the cloud.

Vendor-Hosted Solution in the Cloud

The vendor purchases the base hardware, customizes it, and installs the appropriate software offsite.

Vendor Appliance Hosted by Client

Many clients acquire the hardware and software licenses required and the system is set it and hosted in their own data center.

Client-Hosted Solution (On-Premise)

Benefits of outsourcing EDW/Analytics • No need buy, manage, maintain, or

worry about hardware and software assets residing in your own data center.


Implementation Roadmap And Resources

An Consultant’s Approach

79

Implementation Roadmap & Timeline

Legend:

20xx 20xx 20xx

Q3 Q4Q1 Q2 Q2Q4Q3

“Other” Clinical Data

DataTools XLS’s

Industry Coding

Q1

Reject Reasons

Prerequisite Process & Data Enhancements

Deploy Subject Area/ Functionality

Sunset Existing Tool/Process

Deploy Architectural Component

Data Architecture & Modeling Tools

ETL (SSIS) Architecture

Information Delivery (SSRS) Architecture

Data Governance & Stewardship

Phase 1: Contracts

Industry Standard Coding

SAS Access(as needed)

Phase 2: Clinical Phase 6: Clinical V2

Data Product Strategy

Phase 3: Claims & Providers

Claims OCR & Pending Claims

Service Code Mapping Update

Revised Reforecasting

Phase 4: Sales, Account Mgmt, Referrals & Benchmarks

Fully Deploy CRM

Industry Benchmarks

Scorecard(as needed)

Phase 5: Finance

New Accounting Method Implemented

Evaluate/Deploy Accounting System

DataTools XLS’s

WC_ Reporting

Crystal Reports(Claims)

Finance MDB’s

Future Phases

Prerequisite Data

PRN Integrated into ARCH

Meta Data

OLAP Tools(as needed)

Continuous Refinement

Master Data Management(Provider, Customer, etc.)

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Phase 1

80

SourceServeStore

Stage(SSIS) Enterprise

ID Tool(SSRS, AS)

Functional Scope:• Contracts (ARCH)

& Pending Contracts• Non-GAAP Contract

Performance

Organization, Stewardship and Governance

Data and Metadata Management

EnterpriseReports

Ad hocReports

P_Central

ReferralComplex

Kwiktag

ARCHPRNCRM CFMS

CATS

SQL

NuView(HR)

Hosted

Access DBs

EBS(Payroll)

Health-eSystems(Rx)

Access DBsWC_Reporting

RPT

CS Stars(Paid Claims)


Systems

Existing

Planned

Retiring

External

DWAnalytics

Data Steward

Match/Merge Data Governance

Tasking

Various Access DBs(Arch, Tools, etc.)

CATS_ReportingSQL

Excel

Access

Crystal(Contract& Claims)

Excel

Access

MasterDataIW Addr

• Mentor Client Team in full “life cycle” BI/Analytics development methodology

• Implement basic data & metadata management (KPIs & governance)• Provide initial ad hoc reporting as pilot (rapid prototype)• Begin to build out reports with EBI tool to replace existing tools

Impl

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Phase 2

81

ServeStore

Source

Stage(SSIS)

EnterpriseBI Tool

(SSRS, AS)

Functional Scope:• Clinical (CATS)• “Other Data” as-is• Link to Contracts

P_Central

ReferralComplex

Kwiktag

ARCHPRNCRM CFMS

CATS

NuView(HR)

Hosted

Access DBs

EBS(Payroll)

Health-eSystems(Rx)

Access DBsWC_ReportingCS Stars

(Paid Claims)

• Continue mentoring with Clinical Data from CATS, demonstrating conformation of metrics and dimensions, and data cleansing

• Expand on Data and Metadata Management capabilities with MDM (Provider), data lineage, and more mature/complete KPIs.

• Mature data stewardship and governance processes.• Introduce OLAP into ID solutions suite.

DWAnalytics

OLAP

Ad hocReports

EnterpriseReports

Data Stewards

Match/Merge Data Governance

Tasking

Excel

Access

Crystal(Contract& Claims)

MasterDataIW Addr

Impl

emen

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Organization, Stewardship and GovernanceHCAD 6635 Health Information Analytics Copyright © 2016 Frank F. Wang

Systems

Existing

Planned

Retiring

External

Systems

Existing

Planned

Retiring

External


Phase 3

82

Source

SatisfyStoreFunctional Scope: • Claims (CFMS Feed)• Service Code Maps• Provider Master

(PRN & Claims)• Provider Analysis• Link Claims to

Contracts & Clinical P_Central

ReferralComplex

ARCHPRN CFMS

Kwiktag

CRM

CATS



BasicScorecards

OLAP

Ad hocReports

EnterpriseReports

Data Stewards

Match/Merge Master Data Management

• Continue mentoring with Claims data from CS Stars & Health-eSys.

• Expand on Data and Metadata Management capabilities.

• Continue to mature data stewardship and governance processes.

• Prototype defined KPIs for score-carding solutions.

NuView(HR)

Hosted

Access DBs

EBS(Payroll)

Health-eSystems(Rx)

WC_ReportingCS Stars

(Paid Claims)

Access DBs

Stage(SSIS)

DWAnalytics

CFMS

SAS

ClientWeb SiteEnterprise

BI Tool(SSRS)

SAS

Tasking

Crystal(Claims)

MasterData

Provider

IW Addr

Impl

emen

tatio

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ap



Systems

Existing

Planned

Retiring

External

Phase 4

83

Source

SatisfyStore

Stage(SSIS)

Functional Scope:• Sales/Acct Mgmt

(CRM)• Referrals • Benchmarks

(External)

P_Central

ReferralComplex

ARCHPRN CFMS

Kwiktag

CRM

Hosted

EBS(Payroll)

Health-eSystems(Rx) CS Stars

(Paid Claims)

NuView(HR)

CATS



DWAnalytics

Match/MergeMaster Data Management

• Continue with Sales & Account Management data. Ensure standard ETL approach and dimensional conformity.

• Expand on Data and Metadata Management capabilities.

• Complete stewardship and governance processes maturity path.

Benchmark

Web SiteEnterprise

BI Tool(SSRS)

SAS

Tasking

etc.Provider

IW AddrMasterData

CFMS

Scorecards

OLAP

Ad hocReports

EnterpriseReports

Data Stewards

SAS

Impl

emen

tatio

n R

oadm

ap



Systems

Existing

Planned

Retiring

External

Phase 5

84

Source

SatisfyStore

Stage(SSIS)

Functional Scope:• Financial (GAAP)

Results• Link to Contracts

P_Central

ReferralComplex

ARCHPRN CFMS

Kwiktag

CRM

Hosted

EBS(Payroll)


(Paid Claims)

NuView(HR)

CATS



DWAnalytics

FinancialSystems

• Ensure ETL & dimensional conformity.

• Complete core Data and Metadata Management capabilities (MDM, Lineage, Quality, KPIs, etc.).

• Continue to leverage stewardship and governance to perfect B/Analytics Competency Center thru user and web-site support, and training.

ParadigmWeb Site

&Enterprise

BI Tool(SSRS)

SAS

Benchmark

Tasking

Match/MergeMaster Data Management

Scorecards& Dashboards

OLAP

Ad hocReports

EnterpriseReports

Data Stewards

SAS

Impl

emen

tatio

n R

oadm

ap



Systems

Existing

Planned

Retiring

External

Phase 6+

85

Source SatisfyStore

Stage(SSIS)

Functional Scope:• Clinical “Other”

Data

P_Central

ReferralComplex

ARCHPRN CFMS

Kwiktag

CRM

Hosted

EBS(Payroll)


(Paid Claims)

NuView(HR)

CATS

DWAnalytics

FinancialSystems

• Bring in remaining clinical data using all established process and tool infrastructure.

• Expand on Data and Metadata Management capabilities, and well as overall Governance, to ensue long term sustainable solutions.

MasterData

Match/Merge

Master Data Management

Paybase

Benchmark

Tasking

ParadigmWeb Site

&Enterprise

BI Tool(SSRS)

SAS



Scorecards& Dashboards

OLAP

Ad hocReports

EnterpriseReports

Data Stewards

SAS

Impl

emen

tatio

n R

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ap



Systems

Existing

Planned

Retiring

External

Resource Requirements Estimate

NOTE: The Paradigm FTE includes ~.5 FTE of non "Core Team" personnel such as:

~.2 FTE for Executive Sponsors~.2 FTE for Data Stewards.~.1 FTE for IT Support (i.e., DBA, SysAdmin)

86

Impl

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FTE Per Roadmap Phase

7.25

5.91

2.57

- -

4.68

5.91

6.03

7.527.23

6.28

0.36

3.60

3.09

6.03

4.143.92

5.92

-

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

1 2 3 4 5 6Phases

FTE

Total FTEHP FTEParadigm FTE

Consulting Analytics Team

Client Analytics Team

Client and Consultant

FTE


Resource Allocation & Cost By Phase

87

Budget estimates provided in this presentation should be considered estimates to provide Board with a budget range for planning purposes

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Phase 1 Phase 2 Phase 3 Phase 4 Phase 5 Phase 6 TOTAL

Internal Resources 315,300$ 275,000$ 280,100$ 340,900$ 272,600$ 258,000$ 1,741,900$

Professional Services (wt Expenses) 968,400$ 719,900$ 641,800$ 101,000$ -$ -$ 2,431,100$

Hardware & Software 7,000$ 5,000$ -$ 42,000$ 20,000$ -$ 74,000$

Total By Phase 1,290,700$ 999,900$ 921,900$ 483,900$ 292,600$ 258,000$ 4,247,000$

Capitalized Dollars 1,148,200$ 906,800$ 798,500$ 422,900$ 262,200$ 234,200$ 3,772,800$

Expense Dollars 142,500$ 93,100$ 123,400$ 61,000$ 30,400$ 23,800$ 474,200$

• Estimates do not include any resource space costs• Consulting costs are based on 20xx standard rates with a 5% discount applied• Consulting work week is based upon 45 hours

• Internal Resources are at a $55-$76 / hour• Existing hardware is sufficient for the

duration of this roadmap

Cost Assumptions


Value Proposition and ROI Analysis

A Consultant’s Approach

DRIVING MEMBER VALUE

Initiative Revenue Management Member Dashboard Portfolio Management

Capabilities Proactive surveillance of claims underpayment and systematic billing and collections issues

Member operational measures for problem “Early Warning” and best practices identification

Network wide analytics and modeling of payer volume, revenue contribution and service issues. Systematic “Threat Level Assessment”

Contribution to Organizational Excellence

• Ensures equitable member reimbursement

• Enables monitoring of contract terms compliance

• Reduced work for practices and hospitals

• Proactive identification of issues and root cause analysis

• Identification of future contract protections

• Achievement of contract value

• Identification and remediation of sub-optimal contract performance

• Optimization of contract portfolio value over time

• Sophisticated information based contract negotiations

Value to Others Members:

• Decreased revenue loss

• Decreased time to resolution

Patients:

• Fewer billing issues

• Better patient experience

Members:

• Operational improvement opportunities based on best practices identification

• Greater understanding of the customer base

Members:

• Better contract terms

• Increased operational efficiencies

• Increased patient volume and revenue

Market:

• Predictability/stability


DRIVING PATIENT VOLUME, REVENUE GROWTH

Initiative Patient Referral Catchment Eligibility & Benefits

Capabilities Patient source, treatment sought and referral-out analytics

Patient, employer, payer and practice profiling

Eligibility and benefits verification analytics


• Physician outreach and feedback programs

• Direct patient and employer outreach and education

• Disease management

• Targeted marketing opportunity identification

• Enriched employer relationships

• Directed patient volume growth

Deeper understanding of:

•Trends in benefit products

•Covered services

•Bad debt allocation guidelines

Enhances contracting and employer relations efforts


• Increased patient and revenue bases from “new” and existing markets

• Input into service and network design

Patients/Employers:

• Continuity of care

Members:

• Increased patient and revenue bases from “new” and existing markets

• Input into service and network design

Employers:

• Customized services based on need

Members:

• Improved patient registration guidelines, collection of co-payment at time of service

Patients/Employers:

• Awareness of benefits and payment expectations

• Fewer service issues


DRIVING CLINICAL EXCELLENCE

Initiative Performance Indicators

Physicians Dashboard Product Modeling Patient Continuum of Care

Capabilities Encounter based P4P and Bundled payment measure benchmarking

Measure clinical quality & outcomes by clinical integration program, case mix and disease state

Design new products & services to grow organization’s network and quality

Episodic based quality and outcome measure benchmarking


Provides systematic performance feedback

Helps develop advanced population-based care and provides tools for change

Enables employer-sponsored health improvement program innovation

Differentiates organization in quality and patient outcome


• Demonstrated performance under contracts

• Clinical leadership as Clinical Integration and ACO initiatives evolve and expand

Members:

• Increased understanding of patient base

• More timely feedback, and guidance for change

Patients/Employers:

• Reduced cost of care

• Better care and outcome

Members:

• Increased patient and revenue bases from “new” markets

Employers:

• Focus on improving employee health

• Customized services based on need

Members:

• Highest reputation in market

• Patient loyalty to brand

Patients/Employers:

• Best value in health care


92

Client’s Improvement Opportunities

Minimize Headcount as Revenue Grows

• Use BI & Analytics to integrate data and provide faster access to more complete data for more efficient: Budget creation for Referrals Responses to customer inquiries Research of provider/claim issues Reforecasting

• Assumptions If revenue increases four-fold, DCS FTE

would increase from 9 to 36 (27 new FTE) Process and BI changes would enable case

load to increase 50% Eliminates 14 of 27 new FTE at $135K/yr

Potential ImpactPhase 1 – 3:

2 FTE @ $135K/Yr

$270K/YrPhase 3 onward:

14 FTE @ $135K/Yr

$1.9M/Yr

NOTE: Does NOT include reduced FTE for the DCS Administrative Team

Currently 2+ FTE per DCS (28 FTE total)

Why

BI?

Ope

ratio

nal

Effi

cien

cies

Cus

tom

er

Sat

isfa

ctio

n

Clin

ical

A

naly

sis

Pre

dict

ive

Mod

ellin

g

Mar

ket

Pen

etra

tion


Client Improvement Opportunities

93

Enhance Pricing Accuracy

• Use BI/Analytics to reduce the risk of additional outlier or “losing” contracts by: Simplifying access to complete contract/ case

history during pricing Deeper analysis of clinical history to determine

key Risk Factors (and related treatment and cost impacts) for use in pricing

• Assumptions Client enjoys a 99.5% budgeting accuracy rate

(across all contracts) Negative outliers total $13.5M (18 mos)

15 contracts over budget by > $500K ($750K average)

3 contracts are over budget by > $1M ($1.5M average)

$9M/yr impact at current contract volume

Why

BI?

Ope

ratio

nal

Effi

cien

cies

Cus

tom

er

Sat

isfa

ctio

n

Clin

ical

A

naly

sis

Pre

dict

ive

Mod

ellin

g

Mar

ket

Pen

etra

tion

Potential Impact

− Phase 2 onward − Total potential:

$9M/Yr

− 50% increase in accuracy of negative outliers (at current volumes):

$4.5M/Yr


94


Improve Conversion Rate / Reduce Rejects

• Utilize BI/Analytics with combined datasets with benchmarks to support Sales and Marketing efforts, including: Quantitative analyses supporting Client’s

value proposition Marketing and brand awareness Customer/Case specific Referral or

Opportunity Identify market niches and opportunities not

previously identified which contribute to new products/services.

• Assumptions $26M of rejected contracts (from 1/06) $11M (or more) rejected due to “Cost” or

“Carrier to Manage”

Potential Impact

Phase 2 & Phase 4

Assume 20% of $11M could be converted

$1.5M/Yr

Why

BI?

Ope

ratio

nal

Effi

cien

cies

Cus

tom

er

Sat

isfa

ctio

n

Clin

ical

A

naly

sis

Pre

dict

ive

Mod

ellin

g

Mar

ket

Pen

etra

tion

Reject Reasons By Contract Value

No Reason

Cost

Carrier to Manage

Noncompensable

Rescinded Contract

Employer Request

Other



Potential Impact of BI/Analytics

$8-12M/Yr potential savings

versus

$4M BI investment

Payback period would be under 2 years

95

Why

BI?


Data & Analytics

Drive Healthcare Transformation with a Strategic Analytics Framework and Implementation Plan