The Future of RCM in Healthcare OrganizationsCitiusTech
This document / whitepaper talks about how healthcare technology companies can leverage emerging technologies to derive insights to improve their Revenue Cycle Management process.
Master Data Management - Aligning Data, Process, and GovernanceDATAVERSITY
Master Data Management (MDM) can provide significant value to the organization in creating consistent key data assets such as Customer, Product, Supplier, Patient, and the list goes on. But getting MDM “right” requires a strategic mix of Data Architecture, business process, and Data Governance. Join this webinar to learn how to find the “sweet spot” between technology, design, process, and people for your MDM initiative.
Data-Ed Slides: Best Practices in Data Stewardship (Technical)DATAVERSITY
In order to find value in your organization's data assets, heroic data stewards are tasked with saving the day- every single day! These heroes adhere to a data governance framework and work to ensure that data is: captured right the first time, validated through automated means, and integrated into business processes. Whether its data profiling or in depth root cause analysis, data stewards can be counted on to ensure the organization's mission critical data is reliable. In this webinar we will approach this framework, and punctuate important facets of a data steward’s role.
Learning Objectives:
- Understand the business need for a data governance framework
- Learn why embedded data quality principles are an important part of system/process design
- Identify opportunities to help drive your organization to a data driven culture
RPA (Robotic Process Automation) promises to automate various complex tasks for healthcare organizations – payers and providers – to improve member experience, lower costs and relieve employees from rising pressure of work. But when it comes to actual applications of RPA, most companies are having a difficult time. This brief eBook outlines the benefits, challenges, tools and key healthcare use cases of RPA that can help healthcare organizations boost their productivity.
The Analytics CoE: Positioning your Business Analytics Program for SuccessCartegraph
This Loras College Business Analytics Symposium breakout session presentation by Kiran Garimella, Ph.D., president and founder of XBITALIGN, explored the analytics center of excellence (CoE).
A business analytics program is more than the application of data science and Big Data technology to data. Success should be measured not only by the valuable insights the program delivers, but also by how well it is sustained and how much the ‘analytics mindset’ becomes part of the company’s DNA. The journey is not only from data to information, but also from information to knowledge, and from knowledge to intelligence. The foundation for making this happen is a well-structured Analytics Center of Excellence (CoE).
Customer Journey Analytics: Cracking the Patient Engagement Challenge for PayersHealth Catalyst
Customer journey analytics uses machine learning and big data to track and analyze when and through what channels customers interact with an organization, with an aim to influence behavior (e.g., buying behaviors among retail customers). Similarly, healthcare organizations want to influence health-related behaviors, such a taking medication as prescribed and not smoking, to improve outcomes and lower the cost of care. In a partnership with an analytics services provider, a payer organization is leveraging customer journey analytics among healthcare consumers to identify the best opportunities and channels for patient outreach. With this analytics-driven engagement strategy, the payer has found an opportunity to significantly improve patient engagement—a predicted overall increase from 18 percent to 31 percent.
As the strategic importance of data has increased, new approaches to customer analytics have emerged as well. As customer interactions with companies grow and diversify, the need to integrate data faster and deliver real-time insights is critical. This presentation explores the underlying trends driving companies to become more data-driven and invest in customer analytics. And, it outlines three types of approaches to capturing, managing, analyzing, and activating customer knowledge and insights.
The Future of RCM in Healthcare OrganizationsCitiusTech
This document / whitepaper talks about how healthcare technology companies can leverage emerging technologies to derive insights to improve their Revenue Cycle Management process.
Master Data Management - Aligning Data, Process, and GovernanceDATAVERSITY
Master Data Management (MDM) can provide significant value to the organization in creating consistent key data assets such as Customer, Product, Supplier, Patient, and the list goes on. But getting MDM “right” requires a strategic mix of Data Architecture, business process, and Data Governance. Join this webinar to learn how to find the “sweet spot” between technology, design, process, and people for your MDM initiative.
Data-Ed Slides: Best Practices in Data Stewardship (Technical)DATAVERSITY
In order to find value in your organization's data assets, heroic data stewards are tasked with saving the day- every single day! These heroes adhere to a data governance framework and work to ensure that data is: captured right the first time, validated through automated means, and integrated into business processes. Whether its data profiling or in depth root cause analysis, data stewards can be counted on to ensure the organization's mission critical data is reliable. In this webinar we will approach this framework, and punctuate important facets of a data steward’s role.
Learning Objectives:
- Understand the business need for a data governance framework
- Learn why embedded data quality principles are an important part of system/process design
- Identify opportunities to help drive your organization to a data driven culture
RPA (Robotic Process Automation) promises to automate various complex tasks for healthcare organizations – payers and providers – to improve member experience, lower costs and relieve employees from rising pressure of work. But when it comes to actual applications of RPA, most companies are having a difficult time. This brief eBook outlines the benefits, challenges, tools and key healthcare use cases of RPA that can help healthcare organizations boost their productivity.
The Analytics CoE: Positioning your Business Analytics Program for SuccessCartegraph
This Loras College Business Analytics Symposium breakout session presentation by Kiran Garimella, Ph.D., president and founder of XBITALIGN, explored the analytics center of excellence (CoE).
A business analytics program is more than the application of data science and Big Data technology to data. Success should be measured not only by the valuable insights the program delivers, but also by how well it is sustained and how much the ‘analytics mindset’ becomes part of the company’s DNA. The journey is not only from data to information, but also from information to knowledge, and from knowledge to intelligence. The foundation for making this happen is a well-structured Analytics Center of Excellence (CoE).
Customer Journey Analytics: Cracking the Patient Engagement Challenge for PayersHealth Catalyst
Customer journey analytics uses machine learning and big data to track and analyze when and through what channels customers interact with an organization, with an aim to influence behavior (e.g., buying behaviors among retail customers). Similarly, healthcare organizations want to influence health-related behaviors, such a taking medication as prescribed and not smoking, to improve outcomes and lower the cost of care. In a partnership with an analytics services provider, a payer organization is leveraging customer journey analytics among healthcare consumers to identify the best opportunities and channels for patient outreach. With this analytics-driven engagement strategy, the payer has found an opportunity to significantly improve patient engagement—a predicted overall increase from 18 percent to 31 percent.
As the strategic importance of data has increased, new approaches to customer analytics have emerged as well. As customer interactions with companies grow and diversify, the need to integrate data faster and deliver real-time insights is critical. This presentation explores the underlying trends driving companies to become more data-driven and invest in customer analytics. And, it outlines three types of approaches to capturing, managing, analyzing, and activating customer knowledge and insights.
This webinar will focus on the technical and practical aspects of creating and deploying predictive analytics. We have seen an emerging need for predictive analytics across clinical, operational, and financial domains. One pitfall we’ve seen with predictive analytics is that while many people with access to free tools can develop predictive models, many organizations fail to provide a sufficient infrastructure in which the models are deployed in a consistent, reliable way and truly embedded into the analytics environment. We will survey techniques that are used to get better predictions at scale. This webinar won’t be an intense mathematical treatment of the latest predictive algorithms, but will rather be a guide for organizations that want to embed predictive analytics into their technical and operational workflows.
Topics will include:
Reducing the time it takes to develop a model
Automating model training and retraining
Feature engineering
Deploying the model in the analytics environment
Deploying the model in the clinical environment
Building an Effective BI Governance ProgramDATAVERSITY
“Through 2025, 80% of organizations seeking to scale digital business will fail because they do not take a modern approach to data and analytics governance.” – Gartner
If you are in the process of building a governance initiative or responsible for governance initiatives today, you can’t afford to be in the 80%. This webinar will ensure you deliver a successful program, by providing you tools and recommendations and will run you through a practical example from start to finish.
The following will be covered:
- Define clear objectives & gain buy-in
- Involve the right stakeholders
- Define Scope
- Set clear roles and responsibilities
- Create an effective workflow
- Monitor impact
Planning the implementation of an EMR or EHR, then you need to understand the basics of defining your clinical workflow. This presentation was made at a variety of medical conferences
Interoperability is one of the most critical issues facing the health care industry today. A universal exchange language is needed to assist health care providers in sharing health information in order to coordinate diagnosis and treatment, while maintaining privacy and security of personal data. Health Information Exchanges (HIE) allow for the movement of clinical data between disparate systems; they enable providers to electronically share health records through a network. This presentation provides an overview of HIE and the Meaningful Use requirement related to the exchange of clinical information as well as information about standards of exchange and the recommended "next steps" for providers.
Improving IT services by implementing best practices. Strategic approval with clear RACI. Details plan covering entire process to improve the efficiency of IT team.
How a Semantic Layer Makes Data Mesh Work at ScaleDATAVERSITY
Data Mesh is a trending approach to building a decentralized data architecture by leveraging a domain-oriented, self-service design. However, the pure definition of Data Mesh lacks a center of excellence or central data team and doesn’t address the need for a common approach for sharing data products across teams. The semantic layer is emerging as a key component to supporting a Hub and Spoke style of organizing data teams by introducing data model sharing, collaboration, and distributed ownership controls.
This session will explain how data teams can define common models and definitions with a semantic layer to decentralize analytics product creation using a Hub and Spoke architecture.
Attend this session to learn about:
- The role of a Data Mesh in the modern cloud architecture.
- How a semantic layer can serve as the binding agent to support decentralization.
- How to drive self service with consistency and control.
Presentation winning strategies for shared services in the public sectorChazey Partners
Phil Searle, Founder and CEO of Chazey Partners, shared his view on what it takes shared services to be successful in the public sector. In this presentation, he has also highlighted the very essential basics of shared services and analyzed the lessons that he has learned through the years' of implementation in the public sector.
resentation of use cases of Master Data Management for Customer Data. It presents the business drivers and how Talend platform for MDM can adress them.
A hybrid approach to data management is emerging in healthcare as organizations recognize the value of an enterprise data warehouse in combination with a data lake.
In this SlideShare, we discuss data lakes in healthcare and we:
Provide an overview of a Hadoop-based data lake architecture and integration platform, and its application in machine learning, predictive modeling, and data discovery
Discuss several key use cases driving the adoption of data lakes for both providers and health plans
Discuss available data storage forms and the required tools for a data lake environment
Detail best practices for conducting data lake assessments and review key implementation considerations for healthcare
Reference models a case study for healthcareReal IRM
This presentation is focused on the Healthcare Reference Framework which The Norwegian Healthcare Authority is sponsoring. Sarina looks at the Healthcare vision and business motivation driving the development and adoption of industry reference models and includes the business case for increased South African participation.
Meet our speakers and download this presentation(and more) at http://www.realirm.com/about-us/speakers-forum
POV Healthcare Payer Medical Informatics and AnalyticsFrank Wang
Health Insurance / Payer Analytics
Medical Informatics
Fraud Detection
Care Management
Utilization Management
Business Performance Management
Clinical Outcome Measures
This webinar will focus on the technical and practical aspects of creating and deploying predictive analytics. We have seen an emerging need for predictive analytics across clinical, operational, and financial domains. One pitfall we’ve seen with predictive analytics is that while many people with access to free tools can develop predictive models, many organizations fail to provide a sufficient infrastructure in which the models are deployed in a consistent, reliable way and truly embedded into the analytics environment. We will survey techniques that are used to get better predictions at scale. This webinar won’t be an intense mathematical treatment of the latest predictive algorithms, but will rather be a guide for organizations that want to embed predictive analytics into their technical and operational workflows.
Topics will include:
Reducing the time it takes to develop a model
Automating model training and retraining
Feature engineering
Deploying the model in the analytics environment
Deploying the model in the clinical environment
Building an Effective BI Governance ProgramDATAVERSITY
“Through 2025, 80% of organizations seeking to scale digital business will fail because they do not take a modern approach to data and analytics governance.” – Gartner
If you are in the process of building a governance initiative or responsible for governance initiatives today, you can’t afford to be in the 80%. This webinar will ensure you deliver a successful program, by providing you tools and recommendations and will run you through a practical example from start to finish.
The following will be covered:
- Define clear objectives & gain buy-in
- Involve the right stakeholders
- Define Scope
- Set clear roles and responsibilities
- Create an effective workflow
- Monitor impact
Planning the implementation of an EMR or EHR, then you need to understand the basics of defining your clinical workflow. This presentation was made at a variety of medical conferences
Interoperability is one of the most critical issues facing the health care industry today. A universal exchange language is needed to assist health care providers in sharing health information in order to coordinate diagnosis and treatment, while maintaining privacy and security of personal data. Health Information Exchanges (HIE) allow for the movement of clinical data between disparate systems; they enable providers to electronically share health records through a network. This presentation provides an overview of HIE and the Meaningful Use requirement related to the exchange of clinical information as well as information about standards of exchange and the recommended "next steps" for providers.
Improving IT services by implementing best practices. Strategic approval with clear RACI. Details plan covering entire process to improve the efficiency of IT team.
How a Semantic Layer Makes Data Mesh Work at ScaleDATAVERSITY
Data Mesh is a trending approach to building a decentralized data architecture by leveraging a domain-oriented, self-service design. However, the pure definition of Data Mesh lacks a center of excellence or central data team and doesn’t address the need for a common approach for sharing data products across teams. The semantic layer is emerging as a key component to supporting a Hub and Spoke style of organizing data teams by introducing data model sharing, collaboration, and distributed ownership controls.
This session will explain how data teams can define common models and definitions with a semantic layer to decentralize analytics product creation using a Hub and Spoke architecture.
Attend this session to learn about:
- The role of a Data Mesh in the modern cloud architecture.
- How a semantic layer can serve as the binding agent to support decentralization.
- How to drive self service with consistency and control.
Presentation winning strategies for shared services in the public sectorChazey Partners
Phil Searle, Founder and CEO of Chazey Partners, shared his view on what it takes shared services to be successful in the public sector. In this presentation, he has also highlighted the very essential basics of shared services and analyzed the lessons that he has learned through the years' of implementation in the public sector.
resentation of use cases of Master Data Management for Customer Data. It presents the business drivers and how Talend platform for MDM can adress them.
A hybrid approach to data management is emerging in healthcare as organizations recognize the value of an enterprise data warehouse in combination with a data lake.
In this SlideShare, we discuss data lakes in healthcare and we:
Provide an overview of a Hadoop-based data lake architecture and integration platform, and its application in machine learning, predictive modeling, and data discovery
Discuss several key use cases driving the adoption of data lakes for both providers and health plans
Discuss available data storage forms and the required tools for a data lake environment
Detail best practices for conducting data lake assessments and review key implementation considerations for healthcare
Reference models a case study for healthcareReal IRM
This presentation is focused on the Healthcare Reference Framework which The Norwegian Healthcare Authority is sponsoring. Sarina looks at the Healthcare vision and business motivation driving the development and adoption of industry reference models and includes the business case for increased South African participation.
Meet our speakers and download this presentation(and more) at http://www.realirm.com/about-us/speakers-forum
POV Healthcare Payer Medical Informatics and AnalyticsFrank Wang
Health Insurance / Payer Analytics
Medical Informatics
Fraud Detection
Care Management
Utilization Management
Business Performance Management
Clinical Outcome Measures
Are open platforms necessary for generative phenomena? Is the Internet threatened by Apple? What does it mean to claim that the Open Web is under threat? What does it actually mean to claim that a system is Open?
How to Use Open Source Technologies in Safety-critical Medical Device PlatformsShahid Shah
There is a great deal of fear and angst in the medical device vendor community about the use open source in safety-critical products. This presentation provides advice on why the fear is misplaced and how to proceed with using open source in safety-critical medical devices.
The affordable care act presents a massive growth opportunity for every healthcare payer and provider. With millions of potential subscribers at stake, companies that use their call centers to efficiently enroll individuals will immediately see the benefits with increased market share. Many payers and providers use the excellent Salesforce.com platform to manage their call center but find that training staff to consistently interact with subscriber prospects is a challenge.
The webinar will feature a leading healthcare advocacy group that will illustrate how Cloud Extend is helping them optimize the efficiency of their business-to-consumer (B2C) outreach. In addition, Informatica will present an in depth overview of Informatica Cloud Extend. Finally, Informatica will also demonstrate a payer-based Cloud Extend Affordable Care Act scenario.
MMIS/HealthCare Payer Applications depend upon traditional data base models and structured data analytics to fulfill their needs. These approaches, while adequate in the past, will not suffice to address future requirements. They lack the processing capability to load and query multi-terabyte datasets in a timely fashion and the flexibility to effectively manage unstructured and semi-structured data. Adapting “Big Data” platform to MMIS application will resolve above issues.
Healthcare Payers are increasingly looking for advanced solutions to lower overall healthcare cost and provide a better patient experience. A payer that puts the customer at the center requires seamless integration across communication channels and functions, and a holistic view of the enterprise.
Bodhtree is a global IT consulting, services and software solutions company, with strong competency in Product engineering, Analytics, Cloud and Enterprise services, serving clients in the US, India, APAC and MENA regions. Leveraging strong partnerships with global technology giants such as SAP, Oracle, Salesforce.com, Informatica, etc., we offer world class solutions to fortune listed organizations and SMBs across industries.
Application Outsourcing (AO) in the Healthcare Provider Industry - Annual ReportEverest Group
This report provides an overview of the ITO market for the healthcare provider industry. Analysis includes key trends in market size & growth, demand drivers, adoption & scope trends, emerging themes, key areas of investment, and implications for key stakeholders. The report also provides specific insights on the importance of technology enablement across the healthcare provider value-chain and how both, reforms and digitization, are becoming paramount for driving key strategic initiatives in this industry
2015 athenahealth PayerView Report and ReviveHealth Trust Index WebinarReviveHealth
ReviveHealth and Catalyst Healthcare Research, along with special guest athenahealth, reveal the findings from our 9th Annual ReviveHealth National Payor Survey of health system executives and discuss how those findings compare and contrast with the 10th Annual athenahealth PayerView report.
In this 60-minute webinar, athenahealth Payer Operations Manager Laurie Graham, ReviveHealth CEO Brandon Edwards, and Catalyst Healthcare Research President Dan Prince will address the following essential questions:
How do payors stack up against each other in terms of trust, reliability, honesty, and fairness?
How does a payor’s denial rate and claims speed inform provider trust?
What strategies are providers and health systems implementing for continued success in the changing healthcare environment?
What are the major trends in the healthcare industry?
Healthcare ito in healthcare payer - annual report - preview deck - july 2013Everest Group
This report provides an overview of the ITO market for the healthcare payer industry. Analysis includes key trends in market size & growth, demand drivers, adoption & scope trends, emerging themes, key areas of investment, and implications for key stakeholders. The report also provides specific updates on the readiness of the various stakeholders from the perspective of payer reform mandates
En presentation om IBM MessageSight som erbjuder skalbar konnektivitet.
Läs mer om Utveckling och sammankoppling för mobila enheter (http://www-03.ibm.com/software/products/sv/category/SWL00)
Introduction to DCAM, the Data Management Capability Assessment ModelElement22
DCAM is a model to assess data management capability within the financial industry. It was created by the EDM Council. This presentation provides an overview of DCAM and how financial institutions leverage DCAM to improve or establish their data management programs and meet regulatory requirements such as BCBS 239.
To view recording of this webinar please use the below link:
https://wso2.com/library/webinars/2015/02/connected-health-reference-architecture/
The key focus areas of this session are
Overview of healthcare IT landscape
Standards and protocols widely used in healthcare platforms
SOA is healthcare domain
Quality of services in healthcare platforms
A connected healthcare reference model
Three Keys to a Successful Margin: Charges, Costs, and LaborHealth Catalyst
How can cost management and complete charge capture protect and enhance the margin?
In this webinar, we will look at 2024 margin pressures likely to impact your organization’s financial resiliency. This presentation will also share how organizations can move from Fee-for-Service to Value; bringing Cost to the forefront.
The Foundations of Success in Population Health ManagementHealth Catalyst
From hospital systems to large employers, organizations are increasingly taking on financial risk for the health of populations. Drivers of this trend include the update to the MSSP model, the recent CMS Primary Cares Initiative announcement, the increasing prevalence of the Medicare Advantage model, innovative partnerships in the self-insured employer space, and the proliferation of Medicaid ACOs. Yet while market pressures push organizations toward population risk, they don't necessarily help them succeed: most organizations are struggling to attain or sustain the dual imperatives of high-quality care and cost containment. A primary reason? Short-sighted and tactical approaches that don't provide the flexible data infrastructure and tools to adapt to emerging trends in population health—or to support short-term contractual requirements while building toward long-term success.
View this launch webinar to learn about Health Catalyst’s Population Health Foundations solution, a data and analytics-first starter set aimed at optimizing performance in value-based risk arrangements and providing the data ecosystem that will flex and adapt to complex needs of risk-bearing organizations. Solution services ensure that the strategic value of data is maximized to improve performance in risk contracts—and provide side-by-side subject matter expert partnership for establishing short- and long-term goals for population health management (PHM).
Built on Health Catalyst’s foundational technology and supported by the nationwide experience and perspective of its experts, the Population Health Foundations solution helps organizations leverage multiple data sources to understand their patient populations and create meaningful views of financial and clinical quality performance. As a starter set that organizations can build on based on their needs, the solution is designed to compensate for the known limitations of “black box” population health applications that fail to reveal the “why” of analytic insights and exacerbate the challenges of transforming quality, cost, and care. The Population Health Foundations solution delivers the essential analytic tools needed for success under value-based risk arrangements.
In these slides you can expect to:
- Review recent changes to the field of value-based care, and reactions and insights from the market
- Discover how the Population Health Foundations solution can act as a comprehensive, data-first analytics solution to support your population stratification and monitoring needs
- Understand how this solution functions as a foundational starter set for value-based care success, enabling clients to leverage all their data and other relevant population health tools
2023 — Focus on the Margin (Vitalware by Health Catalyst)Health Catalyst
In this webinar, we will look at pressures exerted in 2023 on the margin and explore how cost management and complete charge capture can protect and enhance the margin. We will provide details on patient activity costing versus the cost-to-charge ratio (CCR), looking at common themes for lost charges and providing an example of where patient activity cost management was able to provide insight into cost containment and practice patterns of a system provider.
Surviving Value-Based Purchasing in Healthcare: Connecting Your Clinical and ...Health Catalyst
Reducing healthcare costs is a major driving force in bundled payments, home-centered medical care, and accountable care organizations. But each new delivery model is built on the premise of reducing revenue per patient. So how can a health system win? Find out what you can do financially survive in today’s environment.
Population Health Management: Enabling Accountable Care in Collaborative Prov...Salus One Ed
This document provides the reader information about population health management (PMH), how it relates to incentive payments for healthcare providers and their health insurance partners (commercial and government). See details about required transformation of care delivery methods, typical accountable care payment models, how to achieve incentives, partnerships between state government (public health) and community shared services needs and necessary technology and data to achieve it.
Workplace productivity is an estimate of how efficiently organizations utilize their resources to accomplish business objectives. Improving productivity is important because increasing it can increase revenue using the same or fewer resources.
in order to meet cost reduction targets, CMOs
* Share patient data across ecosystems
* Embed shared organizational intelligence
* Establish guidance for quality & cost within physician workflows
* Prepare physician leaders to create a culture of continual improvement
Streamlining Your Medical Practice for Profitability and SuccessConventus
Conventus webinar video providing key success strategies and tactics for improving productivity, profitability, and patient care. The one-hour video features host Susan Lieberman of Conventus and Stevie Davidson of Health Informatics Consulting.
Overview of an Open-Platform Health Plan that Lowers Costs and Improves Perfo...Mark Gall
It's hard to gauge how well a health plan is performing. Do our employees understand and get the most out of their benefits? How effective is our wellness program? Are we paying too much for services? These are typical questions. An Open-Platform Health Plan is a self-funded health plan with unique features that allow an employer to establish, track and review performance benchmarks and reduce their exposure to risk.
HLU Consultants, Inc. is a privately held, independent consulting firm based out of Cincinnati, OH since 1961. The consultants at HLU successfully bring together a tremendous amount of industry expertise, valued partners and innovative technologies to design a better, cost-efficient health plan around a customer’s workforce. They help employers establish meaningful benchmarks so they can gauge the success of their plan with a focus on reducing costs, improving outcomes and helping employees successfully navigate the complex healthcare system.
Introduction to Population Health Analytics, Predictive Analytics, Big Data a...Frank Wang
UNH HCAD 6635 Healthcare Analytics Session 12, the last session of Health Information Analytics. Details of the topics of this session will be covered in HCAD 6637 "Advanced Analytics and Health Data Mining"
Population Health Management, Predictive Analytics, Big Data and Text AnalyticsFrank Wang
HCAD 6635 Health Information Analytics session 12
Population Health Management Analytics
Predictive Analytics
Big Data and its potential applications in Healthcare
Text Analytics
Public Health Analytics
Information Management In Pharmaceutical IndustryFrank Wang
Pharmaceutical Industry Information Management Opportunities and Challenges in Research, Development, Clinical, Sales, Marketing, Managed Markets, Manufacturing, Supply Chain and Distribution
2. 2
THE FACES OF HEALTHCARE
Anatomy of a medical transaction
Emotional… Complex… Fragmented… Paper-based
Source: Life Magazine
3. 3
Healthcare Client Needs are Changing to Address Drivers
Cost Reduction
Consumer
Engagement
Interoperability
Business
Intelligence
Management
Data
Management
• Pressure to reduce operating costs due to restrictions on Medial Loss Ratios
• Health Exchange-enabled Individual market requires a low cost structure
• Health plans will need to re-allocate capital to new product and growth initiatives
• Claims processing system modernization becomes increasingly important
• Consumerism and Individual Markets are shifting the business model
• Increased number of Medicare and Medicaid membership
• Multi-channel customer engagement is needed
• Cloud CRM
• Accountable Care Organizations will require new partnerships with providers
• Greater alignment of incentives among pharma, health plans and health providers
requires collaboration
• Global Network Infrastructure expansion to support growing business needs and
industry interconnectivity
• Health plans and their partners will need to manage significantly more health data
• Dashboards and other insight tools can reduce operational costs
• Social network analytics is emerging
• Real Time Data/Knowledge in support of Strategic Decision Making
• ICD-10 is impacting critical applications and infrastructure
• Individuals moving between plans increase demand for data security and integrity
• Connectivity with individual end-point devices (tablets, smart phones) require
increased data security
• New healthcare delivery models in support of evidence-based medicine and
personalize medicine yield data types unfamiliar to most payers
4. 4
BUSINESS VALUE ANALYSIS OF INFORMATION MANAGEMENT IN
HEALTHCARE
ULTIMATE BUSINESS
GOAL
Speed Innovation to Practice Improve Quality of CareImprove Operational Efficiencies
COST CONTAINMENT
---------------------------
Cut Operating Expense
QUALITY OF CARE
----------------------------
Minimizing Medical Errors
COMPLIANCE
----------------------------
100% compliance
(HIPAA, HITECH etc.)
PATIENT THROUGHPUT
---------------
Increase: 10% per year
ULTIMATE BUSINESS
GOAL
EXECUTIVE
KPIs
(Direction)
COST x Claim
-------------
Decrease
ERROR RATE
---------------
Errors: 0% in
5 years
In-patients per
bed per year
------------------------
----
Increase
COST x Bill
-------------
Decrease
CORE KPIs
(Direction)
LENGTH OF STAY
-------------------------
---
Decrease
BUSINESS
INITIATIVES
(Strategy/Priority
Language)
Improve efficiency of
Clinical decision making and
Emergency services
Improve quality of healthcare
services while reducing costs
Manage information for
efficiency and compliance
Improve diagnostic process
efficiency and patient data
integration
OPERATING
KPIs
--------------------
PROCESS/
FUNCTION
Reduce time frame of medical
service delivery and emergency
Patient response.
--------------
Improve clinical decision support
and information sharing among
healthcare stakeholders
Reduce diagnostic imaging/
data complexity
------------------
Improve access to diagnostic
information across clinical
department
SAMPLE
SOLUTION
Enable new care management
and risk modeling applications
------------------
Improve access to patient
information from disparate
sources
Design, develop and deliver a
web-based interface for
information sharing
Implement cost effective storage
optimization and scalable data
protection
Construct a single data ware-
house to enable leveraging of
information as a corporate asset
Implement cost effective
PACS/RISS integration
Mitigate potential data loss
without a cost increase
--------------
Optimize storage capacity while
protecting ‘business critical’ data
ROA(Asset
Utilization)
---------------
Increase
5. 5
The journey to accountable care requires a Healthcare IT
Transformation across the entire community of care
Integrated
Health
System
Optimized
Healthcare
IT System
Physician
Office
Hospitals
and
Clinics
Lab
Facilities
Long
Term
Care
Facility
Government/
Commercial
Payors
Imaging
Center
Home
Health
Outpatient
Surgery
Center
Pharmacy/
PBMs
Healthcare Transformation IT
Requirements
• Upgrade, automate and connect healthcare
IT systems across acute, ambulatory,
clinic and home settings
• Deliver an integrated clinical and financial
view of a patient on demand
• Deploy “collaborative” systems to enable
“team” based community care
• Establish Business intelligence platforms
for reporting, outcomes measurement and
disease management
• Accelerate standardization and cost take
out activities ahead of new system installs
6. 6
The 8 Building Blocks of Successful Accountable HealthcarePayforReportingPayforOutcomes
EHR/PMS/
E-Prescribing 2. Automating and Integrating Fragmented Stakeholders
Information
Exchange
(HIE)
3. Sharing Clinical, Operations and Financial Information
Aggregation &
Analytics 4. Aggregating Siloed Data and Gaining Insight
Decision
Support 5. Transforming collected data into clinical knowledge
Healthcare
Portals and
Medical Homes
6. Making clinical information accessible and “team-based” care
possible
Outcomes
Measurement &
Reporting
7. Establishing Core Measures and Reporting Outcomes
Risk
Sharing 8. Enabling Population Based Management and Risk Sharing
Models
Converged
Medical
Infrastructure
1. Establishing Standardized and Optimized IT Platforms
7. 7
Healthcare Payer Solution Landscape
Unique
Individual -
Member,
Provider,
Agent, etc.
Claims
Fees
Lab
Member
Premium
Eligibility
EBM
Groupers
CM/WM
Program
EMR
Risk
Care Management / Medical Management
Program
Effectivenes
s
Outcomes
Analytics
Population
Analysis
CM/DM/WM
Analysis
Case
Management
Outcomes
Member
Engagement
HEDIS
Pay 4
Performance
Bundled Pmt
Analytics
Shared
Savings
Cost Trends
Market
Analytics
Employer
Engagement
Provider
Engagement
ACO
HIE
HIX
Sales Forces
Analytics
NCQA
many more…
Account
Management
CMS
State
Reporting
8. 8
Cost and Revenue Analytics
Understand your financial metrics and trend analysis
Multi-
faceted
• Fraud, underwriting, MLR,
clinical and coding guideline
Timely
• Reporting at the time of
processing claims or claim
submission
What-if
Scenario
• Leverage “what-if” analysis to
identify effective responses to
cost drivers
9. 9
Supporting the BI needs of Healthcare Payers as they engage members in ongoing care
management along the health continuum
Care Management Model
Evaluate
Measure outcomes and
adjust performance
Intervene
Targeted, evidence
based methods to
impact the
member’s
condition and
health
Enroll
Incentivize and engage
members to participate
Identify & Target
Right member; right program
1
2
3
4
10. 10
Care Management Portal
Member-
centric
• Member-centric view tracking and reporting members’ health
conditions, goals, recommended interventions and outcomes
so that care managers can assess overall program
effectiveness
Integration
• Integrates with claims data to identify members with existing
or developing chronic diseases, calculates treatment plan
cost savings, and track results
Easy to use
• An easy to use care management portal
11. 11
Care management to reduce hospital readmission rates
Care Management
– Fraud, underwriting, cost trending, general
admin costs; clinical and coding guidelines
– Identify and analyze your cost drivers
– Reporting at the time of processing claims or
claim submission
– What do you do next?
– Leverage ‘what-if’ analysis to identify effective
responses to cost drivers
– Analyze fraud patterns pre-payment and
streamline response; early intervention
Comprehensive
• From prevention to long-
term chronic disease
maintenance
Predictable
• Predictive modeling at
patient and population
levels to reduce hospital
readmission rates
Multiple data
sources
• Leverage many different
data sources
12. 12
Use Case: Stratification for Care
Intervention
Mr. HP1 – 20 years, blood pressure 120 / 80
Mr. HP2 – 30 years, blood pressure 140 / 90, 15 lbs
overweight, borderline high fasting blood sugar (115 mg/dl)
Mr. HP3 – 40 years, blood pressure 155 / 110, 50 lbs
overweight, repeated high fasting blood sugar (140 mg/dl )
Is at risk of developing a chronic condition
that can be minimized through better
understanding and improved self care. He
has a medium risk score. He is placed into
a Disease Management program to
optimize blood pressure control, achieve
moderate weight reduction, and incorporate
dietary modification.
Has a chronic condition that puts him at
high risk for getting progressively worse.
In this case, preventing or slowing
progression is the goal. He is placed in a
Case Management (CM) program.
The challenge is to correctly assess who is at risk, quantify the risk,
then match the individual with the best care intervention.Is healthy and thus has a very low
risk score. Based on this, he is
directed to the Wellness program.
13. 13
Use Case – Case Management
– Identifying High Risk High Cost (HRHC) Members
• Identify members who are at high risk for experiencing
decreased health or likely to incur high dollar cost for treatments.
• Separate long-term HRHC members (advanced chronic disease
suffers) from one time high cost members (trauma)
• Stratify long-term HRHC members in order to assign appropriate
intervention by Case Management (CM)
– Benefit
• Lower immediate costs
• Much lower long term cost (bend the trend)
• Target intervention by Case Mangement to improve member
health, keep the member healthier for longer period of time,
delay the worsening of health.
14. Insurance Performance – Case
Management
Member
ID
First
name
Last
Name
Age Total Cost
Expected Amount
Year 2
1 De-ID De-ID 60 $10,565 $109,051.00
2 De-ID De-ID 61 $27,013 $78,934.00
3 De-ID De-ID 50 $28,805 $51,971.00
4 De-ID De-ID 59 $8,372 $66,154.00
5 De-ID De-ID 86 $17,674 $65,604.00
6 De-ID De-ID 61 $420,318 $14,575.00
7 De-ID De-ID 55 $29,925 $48,609.00
8 De-ID De-ID 54 $4,828 $55,133.00
9 De-ID De-ID 87 $5,161 $55,062.00
10 De-ID De-ID 5 $620,887 $5,570.00
One time event
(Blue)
• Little impact for future
• Goal: encourage healthy behavior
Continued
progression
(Yellow)
• Slow progression, moderate affect long term
costs
• Goal: Extend time the member feels healthy
Sudden change
for the worse
(Red)
• Rapid progression into disease, large affect
on long-term costs
• Goal: Stop or moderate descent into disease
15. 15
Utilization Management (UM)
Appropriateness
• Reviews prior authorization, eligibility, benefits
limits and services limits
Necessity
• Provides concurrent and retrospective reviews
based on evidence-based guidelines, clinical
criteria (InterQual, Milliman, Solucient)
Efficiency
• Proactively manages therapeutic duplication,
level of care and length of services
16. 16
Disease Management and Wellness Managemen
Segment
and Predict
• Segments and predicts specific
illness such as heart conditions,
diabetes and depression
Wellness
Plan
• Member centric wellness
management including health risk
assessment, patient education
Cost
Containment
• Develop short- and long-term cost
control machnism
17. 17
Cost Containment Findings
Provider
#
Count Provider Name Specialty Total $
1 4836 Bing, Mark Family Practice $160,833
2 4342 Yahoo, Charles Psychiatry $143,490
3 2732 East End Urgent Care URGENT Family Practice $90,479
4 2602 Place, First MD General Practice $63,892
5 1724 Swat, Edward MD Anesthesiology $56,696
6 4312 Smith, Gregory E DPM Podiatry $54,597
7 3836 Man, Super G DPM Podiatry $49,796
8 1615 Riley, James R MD Plastic Surgery $37,970
9 3243 Avian, Bird DPM Podiatry $37,327
10 2513 Copper, Metal H DPM Podiatry $32,668
Reduce costs by identifying and eliminating un-necessary procedures
Necessity
• Is the procedure necessary
Savings
• How large is the potential saving and what
is the estimated cost/benefit ratio?
Nail
Debridement
•Nail debridement clinical guidelines. Only 2 of 5 are directly tied to a
disease
•Relief of pain
•Treatment of infection (bacterial, fungal and viral)
•Temporary removal of an anatomic deformity …
•Exposure of subungal condition …
•Prophylactic measure to prevent further problems …
18. Fraud and Abuse Detection
Additional investigation needed
Provider
#
Count Provider Name Specialty Total $
1 4836 Bing, Mark Family Practice $160,833
2 4342 Yahoo, Charles Psychiatry $143,490
3 2732 East End Urgent Care
URGENT
Family Practice $90,479
4 2602 Place, First MD General Practice $63,892
5 1724 Swat, Edward MD Anesthesiology $56,696
6 4312 Smith, Gregory E
DPM
Podiatry $54,597
7 3836 Man, Super G DPM Podiatry $49,796
8 1615 Riley, James R MD Plastic Surgery $37,970
9 3243 Avian, Bird DPM Podiatry $37,327
10 2513 Copper, Metal H DPM Podiatry $32,668
Provider1
• Charges significantly higher
than his peers
Provider 2
• Specialized in psychiatry, and is
not generally associated with
nail debridement
Provider 5
• Practised in a specialty that is
not generally associated with
the nail debridement procedure
19. 19
Fraud and Abuse (F&A) Detection by Profiling Providers
Ranking Top 5 Codes by Quantity for Provider: GR0000000 – ABC Medical Group, Inc
6 Months of Service xx/xx-yy/yy, Paid in Months xx/xx-yy/yy
GR0000000
Qty Rank and % Compared to
OB/GYN Groups
6 Month Peer
Averages
Code Code Desc
Total Dollars
Paid
Total
Qty
Adj Rank
% of
Total
Qty
Total #
Provs
Peer Avg
Dollars Paid
Peer
Avg
Qty
81025-TC Urine pregnancy test $12,560.60 2,710 #1 or 19% 65 $1,022.93 220
Z9752
Family planning counseling (15
minutes) $33,086.45 1,735 #1 or 21% 55 $2,778.90 149
Z6410
Perinatal education, individual,
each 15 minutes $9,511.71 1,131 #9 or 3% 91 $3,657.38 435
Z6204
Follow-up antepartum nutrition
assessment, treatment and/or
intervention; individual, each 15
minutes $7,569.00 900 #5 or 4% 96 $2,074.14 247
Z1034 Antepartum follow-up visit $48,625.92 804 #16 or 2% 195 $11,996.08 203
Outlier detection based on Provider profiles. Highlighted cells suggest
further investigation.
20. 20
Health Information Exchange
Singular
• Houses data from many clinical data
sources in a secure central structure
Enabling
• Enables key functions that reduces costs
(reduced repeated testing, reduced risk of
adverse events) and improves
coordination of care
Payer
• Some HIE use cases have focus on
sending ADTs (admissions, discharges,
transfers) and discharge summaries to the
health plans in lieu of manual processing
21. 21
HIE DISTRIBUTION LAYER BUILT FOR GROWTH
Collaborate regionally and cross- border with
other states
Offer clear guidance and flexible access to
consumers, employers, payers pharmas
22. 22
Timely
• Analyze compliance data
ahead of time to highlight
problems before submission
Streamlined
• Easier to locate, access and
report; new reports can be
added quickly to increase
regulatory adherence
Actionable
• Provide further drilldowns to
identify root-causes in order
to take actions to rectify the
issues
Compliance Streamlining
23. 23
Transform readily available, everyday data into actionable
knowledge
Healthcare Payer Medical Informatics
Eligibility
– Clinical expertise
– Statistical tools
– Data mining
– Predictive analytics
– Research methods
– Database
technologies
– Published papers
Optimize
Quality
Medical
Inpatient &
Outpatient
Pharmacy
Data Sources
(Structured and
Unstructured)
Labs
Demographics
Medical
Records
Surveys
Health Risk
Assessments
Seamless
Information
Exchange
Enhance
Collaborative
Care
Cost
Containment
Enhance
Health
Outcomes
Population
Health
Analysis
Prevent
Fraud
Medical
Informatics
Possible Actions
to Take
24. 24
Predictive Modeling
Turning Data into Knowledge – Example
We have 35,000
individuals in
our population
with diabetes.
The patients
cost us $7,000
this year, a 15%
increase over
last year.
The national
prevalence rate
for diabetes is
8.3%; ours is
12%.
Hypertension is
a major co-
morbidity for
diabetes.
Assign patient-
level risk scores
using a
statistical model
to predict which
diabetics will be
hospitalized
next year.
Efficiently
allocate care
management
resources to
help reduce
avoidable
hospitalizations
for at-risk
patients.
Wisdom
–actionable
info
5
Knowledge
–goals
–targets
4
Information
–benchmarks
–trends
3
Secondary
Data
–averages
–rates
2
Primary
Data
–counts
–sums
1
HP Confidential
25. 25
Turning Data into Knowledge – Examples
2
5
Wisdom
(actionable info)
5Knowledge
(goals, targets)
4Information
(benchmarks, trends)
3Secondary Data
(averages, rates)
2Primary Data
(counts, sums)
1
A total of 10,000
Medicaid enrollees
received mental health
services in SFY 2010.
We have 35,000
individuals in our
population with
diabetes.
Medicare patients
cared for by our
physicians have an
average cost of $8800
per year.
The procedure for
internal fetal monitoring
was billed multiple
times for the same
pregnancy.
Mental health services
expenditures averaged
$400 pmpm in 2009.
The patients cost us
$7,000 this year, a 15%
increase over last year.
The No. 1 DRG for our
hospitalized Medicare
patients is chronic
heart failure.
This amount has
increased by 2% in
each of the past three
years.
Payments for mental
health services to
provider X have risen
20% YOY whereas the
Statewide average is
5%.
The national prevalence
rate for diabetes is
8.3%; ours is 12%.
Hypertension is a major
co-morbidity for
diabetes.
The number of heart
failure patients
compared to
benchmark data is high.
This is not medically
justified as the
procedure is only
performed during active
labor to monitor fetal
heart rate and uterine
activity.
Applying data mining to
large data sets, we can
automatically detect
more fraudulent
providers and increase
our ROI.
Assign patient-level risk
scores using a
statistical model to
predict which diabetics
will be hospitalized next
year.
Medicare patients with
Class 4 heart failure
without a cardiac
specialist cost over
$50,000.
This procedure was
controlled solely by
diagnosis, which did not
prevent misuse and
coding errors.
We will proactively ward
off complex sets of
fraudulent claims using
predictive analytics.
Efficiently allocate care
management resources
to help reduce
avoidable
hospitalizations for at-
risk patients.
Early referral to a “Heart
Failure Specialty Clinic”
may lower the Medicare
cost profile.
Update medical policy
to reimburse fetal
internal monitoring in an
inpatient setting and
establish limits for
reimbursement
consistency.
HP Confidential
26. 26
Client A Client B Client C
Use Cases
– Client concern
• Vendor proposes device for
chronic wound care claiming
substantial cost effectiveness
• Need to due diligence
– We researches
• Device
• Medical literature for wound
care
• Develops assessment study
– Our study reveals
• potential for significant savings
based on prevalence of wounds
– We recommends
• Pilot of new treatment
– Client concern
• Is mental health utilization
below norms?
• If so, what financial penalty risk
– We examines
• HEDIS methods
• Reviews medical literature for
benchmarks
– We executes study
• co-morbidities
• utilization trends
• confidence intervals
– Our study reveals
• Client in full compliance
• At national norms
• No penalties incurred
– Client concern
• Children receiving dangerous
and costly anti-psychotic drugs
with no evidence of approved
diagnosis
– Our study reveals
• Similar disturbing patterns
– We recommends
• Physician education,
• Care management for patients
• Consideration for a prior
authorization program
HP Confidential
30. 30
Decision Support Services Data Inputs
ADVANCED ANALYTICS
Data Warehouse
• Weekly Load
• Claims Star Schema
Data Warehouse
• Weekly Load
• Claims Star Schema
Member
• Base
Information
• Eligibility
• Lock-In
Member
• Base
Information
• Eligibility
• Lock-In
Claims
• Paid and
Denied
• FFS and
Encounters
Claims
• Paid and
Denied
• FFS and
Encounters Provider
• Base
Information
• Enrollment on
Review
• Group
Assignment
Provider
• Base
Information
• Enrollment on
Review
• Group
Assignment
Financial
• A/ Rs
• Expenditures
• Cash Receipts
Financial
• A/ Rs
• Expenditures
• Cash Receipts
Managed Care
• Capitation
Payments
• Recip PCP
Assignment
• Provider MCO
Enrollment
Managed Care
• Capitation
Payments
• Recip PCP
Assignment
• Provider MCO
Enrollment
Other
• Prior
Authorization
• Drug Rebate
• Reference
• TPL
Other
• Prior
Authorization
• Drug Rebate
• Reference
• TPL
Data Warehouse
• Weekly Load
• Claims Star Schema
Data Warehouse
• Weekly Load
• Claims Star Schema
Member
• Base
Information
• Eligibility
• Lock-In
Member
• Base
Information
• Eligibility
• Lock-In
Claims
• Paid and
Denied
• FFS and
Encounters
Claims
• Paid and
Denied
• FFS and
Encounters Provider
• Base
Information
• Enrollment on
Review
• Group
Assignment
Provider
• Base
Information
• Enrollment on
Review
• Group
Assignment
Financial
• A/ Rs
• Expenditures
• Cash Receipts
Financial
• A/ Rs
• Expenditures
• Cash Receipts
Managed Care
• Capitation
Payments
• Recip PCP
Assignment
• Provider MCO
Enrollment
Managed Care
• Capitation
Payments
• Recip PCP
Assignment
• Provider MCO
Enrollment
Other
• Prior
Authorization
• Drug Rebate
• Reference
• TPL
Other
• Prior
Authorization
• Drug Rebate
• Reference
• TPL
31. 31
Healthcare Payer
Reference Architecture
Reporting Findings
Collecting and
Examining the
Evidence (aka the
Data)
Testing and Analyzing
Preserving Data and
Information
Alternative Computing
Models – e.g. Cloud
32. 32
From Healthcare (“Sickcare”) to Integrated Health Management
Converging and Transforming…
– Empowered
consumers and
expert patients
– Coaching and
advocacy
– Integrated budget,
benefits and health
management
– Aligned
incentives/rewards
– Wellness & prevention
– Diagnosis & treatment
– Care coordination
– Quality and outcomes
– Pay 4 Performance
– Bundled Payment
– Analytics for improved decision
making
– Accountable Care Organization
Provider
Engagement
Consumer
Engagement
Health Plans
Engagement
IHM
Transparency & Choice