Michelle Blackmer

Michelle Blackmer

Optimizing Supply Chain with Data Governance

Optimizing Supply Chain with Data Governance

Optimizing Supply Chain with Data Governance

Last week I met with a customer who recently completed a few data fueled supply chain projects. Informatica data integration and master data management are part of the solution architecture. I’m not going to name the client at this early stage but want to share highlights from our Q&A.

Q: What was the driver for this project?

A: The initiative fell out of a procure-to-pay (P2P) initiative.  We engaged a consulting firm to help centralize Accounts Payable operations.  One required deliverable was an executive P2P dashboard. This dashboard would provide enterprise insights by relying on the enterprise data warehousing and business intelligence platform.

Q: What did the dashboard illustrate?

The dashboard integrated data from many sources to provide a single view of information about all of our suppliers. By visualizing this information in one place, we were able to rapidly gain operational insights. There are approximately 30,000 suppliers in the supplier master who either manufacture, or distribute, or both over 150,000 unique products.

Q: From which sources is Informatica consuming data to power the P2P dashboard?

A: There are 8 sources of data:

3 ERP Systems:

  1. Lawson
  2. HBOC STAR
  3. Meditech

4 Enrichment Sources:

  1. Dun & Bradstreet – for associating suppliers together from disparate sources.
  2. GDSN – Global Data Pool for helping to cleanse healthcare products.
  3. McKesson Pharmacy Spend – spend file from third party pharmaceutical distributor Helps capture detailed pharmacy spend which we procure from this third party.
  4. Office Depot Spend – spend file from third party office supply distributor.  Helps capture detailed pharmacy spend.
  5. MedAssets – third party group purchasing organization (GPO) who provides detailed contract pricing.

Q: Did you tackle clinical scenarios first?

A: No, well we certainly have many clinical scenarios we want to explore like cost per procedure per patient we knew that we should establish a few quick, operational wins to gain traction and credibility.

Q: Great idea – capturing quick wins is certainly the way we are seeing customers have the most success in these transformative projects. Where did you start?

A: We started with supply chain cost containment; increasing pressures on healthcare organizations to reduce cost made this low hanging fruit the right place to start. There may be as much as 20% waste to be eliminated through strategic and actionable analytics.

Q: What did you discover?

A: Through the P2P dashboard, insights were gained into days to pay on invoices as well as early payment discounts and late payment penalties. With the visualization we quickly saw that we were paying a large amount of late fees. With this awareness, we dug into why the late fees were so high. What was discovered is that, with one large supplier, the original payment terms were net 30 but that in later negotiations terms were changed to 20 days. Late fees were accruing after 20 days. Through this complete view we were able to rapidly hone in on the issue and change operations — avoiding costly late fees.

Q: That’s a great example of straight forward analytics powered by an integrated view of data, thank you. What’s a more complex use case you plan to tackle?

A: Now that we have the systems in place along with data stewardship, we will start to focus on clinical supply chain scenarios like cost per procedure per patient. We have all of the data in one data warehouse to answer questions like – which procedures are costing the most, do procedure costs vary by clinician? By location? By supply? – and what is the outcome of each of these procedures? We always want to take the right and best action for the patient.

We were also able to identify where negotiated payment discounts were not being taken advantage of or where there were opportunities to negotiate discounts.

These insights were revealed through the dashboard and immediate value was realized the first day.

Fueling knowledge with data is helping procurement negotiate the right discounts, i.e. they can seek discounts on the most used supplies vs discounts on supplies rarely used. Think of it this way… you don’t want to get a discount on OJ and if you are buying milk.

Q: Excellent example and metaphor. Let’s talk more about stewardship, you have a data governance organization within IT that is governing supply chain?

A: No, we have a data governance team within supply chain… Supply chain staff that used to be called “content managers” now “data stewards”. They were doing the stewardship work of defining data, its use, its source, its quality before but it wasn’t a formally recognized part of their jobs… now it is. Armed with Informatica Data Director they are managing the quality of supply chain data across four domains including suppliers/vendors, locations, contracts and items. Data from each of these domains resides in our EMR, our ERP applications and in our ambulatory EMR/Practice Management application creating redundancy and manual reconciliation effort.

By adding Master Data Management (MDM) to the architecture, we were able to centralize management of master data about suppliers/vendors, items, contracts and locations, augment this data with enrichment data like that from D&B, reduce redundancy and reduce manual effort.

MDM shares this complete and accurate information with the enterprise data warehouse and we can use it to run analytics against. Having a confident, complete view of master data allows us to trust analytical insights revealed through the P2P dashboard.

Q: What lessons learned would you offer?

A: Having recognized operational value, I’d encourage health systems to focus on data driven supply chain because there are savings opportunities through easier identification of unmanaged spend.

I really enjoyed learning more about this project with valuable, tangible and nearly immediate results. I will keep you posted as the customer moves onto the next phase. If you have comments or questions, leave them here.

FacebookTwitterLinkedInEmailPrintShare
Posted in B2B, Data First, Data Governance, Retail | Tagged , , , | Leave a comment

10 Insights From The Road To Data Governance

10 Insights From The Road To Data Governance

10 Insights From The Road To Data Governance

I routinely have the pleasure of working with Terri Mikol, Director of Data Governance, UPMC. Terri has been spearheading data governance for three years at UPMC. As a result, she has a wealth of insights to offer on this hot topic. Enjoy her top 10 lessons learned from UPMC’s data governance journey:

1. You already have data stewards.

Commonly, health systems think they can’t staff data governance such as UPMC has becauseof a lack of funding. In reality, people are already doing data governance everywhere, across your organization! You don’t have to secure headcount; you locate these people within the business, formalize data governance as part of their job, and provide them tools to improve and manage their efforts.

2. Multiple types of data stewards ensure all governance needs are being met.

Three types of data stewards were identified and tasked across the enterprise:

I. Data Steward. Create and maintain data/business definitions. Assist with defining data and mappings along with rule definition and data integrity improvement.

II. Application Steward. One steward is named per application sourcing enterprise analytics. Populate and maintain inventory, assist with data definition and prioritize data integrity issues.

III. Analytics Steward. Named for each team providing analytics. Populate and maintain inventory, reduce duplication and define rules and self-service guidelines.

3. Establish IT as an enabler.

IT, instead of taking action on data governance or being the data governor, has become anenabler of data governance by investing in and administering tools that support metadata definition and master data management.

4. Form a governance council.

UPMC formed a governance council of 29 executives—yes, that’s a big number but UPMC is a big organization. The council is clinically led. It is co-chaired by two CMIOs and includes Marketing, Strategic Planning, Finance, Human Resources, the Health Plan, and Research. The council signs off on and prioritizes policies. Decision-making must be provided from somewhere.

5. Avoid slowing progress with process.

In these still-early days, only 15 minutes of monthly council meetings are spent on policy and guidelines; discussion and direction take priority. For example, a recent agenda item was “Length of Stay.” The council agreed a single owner would coordinate across Finance, Quality and Care Management to define and document an enterprise definition for “Length of Stay.”

6. Use examples.

Struggling to get buy-in from the business about the importance of data governance? An example everyone can relate to is “Test Patient.” For years, in her business intelligence role, Terri worked with “Test Patient.” Investigation revealed that these fake patients end up in places they should not. There was no standard for creation or removal of test patients, which meant that test patients and their costs, outcomes, etc., were included in analysis and reporting that drove decisions inside and external to UPMC. The governance program created a policy for testing in production should the need arise.

7. Make governance personal through marketing.

Terri holds monthly round tables with business and clinical constituents. These have been a game changer: Once a month, for two hours, ten business invitees meet and talk about the program. Each attendee shares a data challenge, and Terri educates them on the program and illustrates how the program will address each challenge.

8. Deliver self-service.

Providing self-service empowers your users to gain access and control to the data they need to improve their processes. The only way to deliver self-service business intelligence is to make metadata, master data, and data quality transparent and accessible across the enterprise.

9. IT can’t do it alone.

Initially, IT was resistant to giving up control, but now the team understands that it doesn’t have the knowledge or the time to effectively do data governance alone.

10. Don’t quit!

Governance can be complicated, and it may seem like little progress is being made. Terri keeps spirits high by reminding folks that the only failure is quitting.

Getting started? Assess the data governance maturity of your organization here: http://governyourdata.com/

FacebookTwitterLinkedInEmailPrintShare
Posted in Data First, Data Governance, Data Integration, Data Security | Tagged , , , | Leave a comment

Optimizing Outcomes for Medicare Advantage

 Optimizing Outcomes for Medicare Advantage

Optimizing Outcomes for Medicare Advantage

In anticipation of attending RISE California Summit: Best Practices for Successfully Managing Risk and Driving Accountable Care next week, I had the opportunity to interview my colleague Noreen Hurley and our partner Saeed Aminzadeh, CEO, Decision Point Healthcare Solutions to get their perspectives on hot topics at the show. Specifically we spent quite a bit of time talking about the role of data in improving CMS STARS which is important in optimizing the outcomes for any Medicare Advantage population.

Saeed, what does Decision Point do?

We are a healthcare engagement analytics company…essentially we help clients that are “at risk” organizations to improve performance, including STAR ratings. We do this by providing data driven insights to more effectively engage members and providers.

What type of data do you use to make these recommendations?

Well, taking better care of members is about emotionally involving them in their care. Information to help do this resides in data that plans already have available, i.e. utilization patterns, distance to doctors, if they are compliant with evidence based guidelines, do they call into the call center. We also seek to include information about their behavior as a consumer. such as their lifestyles, their access to technology, and so forth.

Claims data makes sense, everyone has that but the other data you mentioned, that can be harder to capture. Why does non-claims oriented data matter?

We develop predictive models that are unique for each client – specifically based on the demographics and variables of their population. Variables like exercise and technology access matter because — for example, exercise habits influence mood and access to technology demonstrates a way to contact them or invite them to participate in online communities with other members like themselves.

The predictive models then determine which members are at most risk?

Yes, yes they do but they can also determine a member’s barriers to desired behavior, and their likelihood of responding to and acting on health plan communications. For example, if we identified a diabetic member as high risk of non-compliance, found their primary barrier to compliance as health literacy, and determined that the member will likely respond positively to a combination of health coaching and mobile health initiatives, we would recommend outreach that directly addresses these findings..

Noreen, when you were working on the payer side of the house, how were you going about determining which members were in your at risk population?

We had teams of people doing mining of claims data and we were asking members to complete surveys. This made for more data but the sheer volume of data made it complex to accurately review and assess which members were at highest risk. It was very challenging to take into consideration all of the variables that impact each member. Taking data from so many disparate sources and bringing it together is a big challenge.

What made it (and continues to make it) it so challenging, specifically to STARS?

So much of the data is collected as surveys or in other non-standard formats. Members inherently are unique which creates a lot of variability and it is often difficult to interpret the relationships that exist between members and primary care physicians, specialists, facilities and the rest of their care team. Relationships are important because they can provide insights into utilization patterns, potential overlaps or gaps in care and how we can most effectively engage those members in their care.

What are Informatica and Decision Point doing together?

To optimize the predictive models, as Saeed described, it’s imperative to feed them as much data and as accurate of data as possible. Without data, insights will be missed… and insights are the path to discovery and to improving CMS STARS ratings. Informatica is the data integration company — we ensure that data is reliable), connected (from any source to any target) and safe (avoiding data breaches or HIPAA violations). Informatica is delivering data to Decision Point efficiently and effectively so that clients have access to the best data possible to derive insights and improve outcomes. Our technology also provided the Star team with a member profile which brings together that disparate data and organizes it into the 360 degree view of that member. In addition to fueling Decision Point’s powerful algorithms, this is a tool that can be used for ongoing insights into the members.

Excellent, how can readers learn more?

They can meet with us next week – email Noreen or Saeed to arrange time.
Decision Point Healthcare Solutions

FacebookTwitterLinkedInEmailPrintShare
Posted in Healthcare, Vertical | Tagged | Leave a comment

Health Plans, Create Competitive Differentiation with Risk Adjustment

improve risk adjustmentExploring Risk Adjustment as a Source of Competitive Differentiation

Risk adjustment is a hot topic in healthcare. Today, I interviewed my colleague, Noreen Hurley to learn more. Noreen tell us about your experience with risk adjustment.

Before I joined Informatica I worked for a health plan in Boston. I managed several programs  including CMS Five Start Quality Rating System and Risk Adjustment Redesign.  We recognized the need for a robust diagnostic profile of our members in support of risk adjustment. However, because the information resides in multiple sources, gathering and connecting the data presented many challenges. I see the opportunity for health plans to transform risk adjustment.

As risk adjustment becomes an integral component in healthcare, I encourage health plans to create a core competency around the development of diagnostic profiles. This should be the case for health plans and ACO’s.  This profile is the source of reimbursement for an individual. This profile is also the basis for clinical care management.  Augmented with social and demographic data, the profile can create a roadmap for successfully engaging each member.

Why is risk adjustment important?

Risk Adjustment is increasingly entrenched in the healthcare ecosystem.  Originating in Medicare Advantage, it is now applicable to other areas.  Risk adjustment is mission critical to protect financial viability and identify a clinical baseline for  members.

What are a few examples of the increasing importance of risk adjustment?

1)      Centers for Medicare and Medicaid (CMS) continues to increase the focus on Risk Adjustment. They are evaluating the value provided to the Federal government and beneficiaries.  CMS has questioned the efficacy of home assessments and challenged health plans to provide a value statement beyond the harvesting of diagnoses codes which result solely in revenue enhancement.   Illustrating additional value has been a challenge. Integrating data across the health plan will help address this challenge and derive value.

2)      Marketplace members will also require risk adjustment calculations.  After the first three years, the three “R’s” will dwindle down to one ‘R”.  When Reinsurance and Risk Corridors end, we will be left with Risk Adjustment. To succeed with this new population, health plans need a clear strategy to obtain, analyze and process data.  CMS processing delays make risk adjustment even more difficult.  A Health Plan’s ability to manage this information  will be critical to success.

3)      Dual Eligibles, Medicaid members and ACO’s also rely on risk management for profitability and improved quality.

With an enhanced diagnostic profile — one that is accurate, complete and shared — I believe it is possible to enhance care, deliver appropriate reimbursements and provide coordinated care.

How can payers better enable risk adjustment?

  • Facilitate timely analysis of accurate data from a variety of sources, in any  format.
  • Integrate and reconcile data from initial receipt through adjudication and  submission.
  • Deliver clean and normalized data to business users.
  • Provide an aggregated view of master data about members, providers and the relationships between them to reveal insights and enable a differentiated level of service.
  • Apply natural language processing to capture insights otherwise trapped in text based notes.

With clean, safe and connected data,  health plans can profile members and identify undocumented diagnoses. With this data, health plans will also be able to create reports identifying providers who would benefit from additional training and support (about coding accuracy and completeness).

What will clean, safe and connected data allow?

  • Allow risk adjustment to become a core competency and source of differentiation.  Revenue impacts are expanding to lines of business representing larger and increasingly complex populations.
  • Educate, motivate and engage providers with accurate reporting.  Obtaining and acting on diagnostic data is best done when the member/patient is meeting with the caregiver.  Clear and trusted feedback to physicians will contribute to a strong partnership.
  • Improve patient care, reduce medical cost, increase quality ratings and engage members.
FacebookTwitterLinkedInEmailPrintShare
Posted in B2B, B2B Data Exchange, Business Impact / Benefits, Business/IT Collaboration, CIO, Customer Acquisition & Retention, Data Governance, Data Integration, Enterprise Data Management, Healthcare, Master Data Management, Operational Efficiency | Tagged , , | Leave a comment

Why Healthcare Data Professionals belong at Informatica World 2014

This year, over one dozen healthcare leaders will share their knowledge on data driven insights at Informatica World 2014. These will be included in six tracks and over 100 breakout sessions during the conference. We are only five weeks away and I am excited that the healthcare path has grown 220% from 2013!

Informatica-World-Healthcare

Join us for these healthcare sessions:

  • Moving From Vision to Reality at UPMC : Structuring a Data Integration and Analytics Program: University of Pittsburgh Medical Center (UPMC) partnered with Informatica IPS to establish enterprise analytics as a core organizational competency through an Integration Competency Center engagement. Join IPS and UPMC to learn more.
  • HIPAA Validation for Eligibility and Claims Status in Real Time: Healthcare reform requires healthcare payers to exchange and process HIPAA messages in less time with greater accuracy. Learn how HealthNet tackled this challenge.
  • Application Retirement for Healthcare ROI : Dallas Children’s Hospital needed to retire outdated operating systems, hardware, and applications while retaining access to their legacy data for compliance purposes. Learn why application retirement is critical to the healthcare industry, how Dallas Children’s selected which applications to retire and the healthcare specific functionality that Informatica is delivering.
  • UPMC’s story of implementing a Multi-Domain MDM healthcare solution in support of Data Governance : This presentation will unfold the UPMC story of implementing a Multi-Domain MDM healthcare solution as part of an overall enterprise analytics / data warehousing effort.  MDM is a vital part of the overall architecture needed to support UPMC’s efforts to improve the quality of patient care and help create methods for personalized medicine. Today, the leading MDM solution developer will discuss how the team put together the roadmap, worked with domain specific workgroups, created the trust matrix and share his lessons learned. He will also share what they have planned for their consolidated and trusted Patient, Provider and Facility master data in this changing healthcare industry. This will also explain how the MDM program fits into the ICC (Integration Competency Center) currently implemented at UPMC.
  • Enterprise Codeset Repositories for Healthcare: Controlling the Chaos: Learn the benefit of a centralized storage point to govern and manage codes (ICD-9/10, CPT, HCPCS, DRG, SNOMED, Revenue, TOS, POS, Service Category, etc.), mappings and artifacts that reference codes.
  • Christus Health Roadmap to Data Driven Healthcare : To organize information and effectively deliver services in a hypercompetitive market, healthcare organizations must deliver data in an accurate, timely, efficient way while ensuring its clarity. Learn how CHRISTUS Health is developing and pursuing its vision for data management, including lessons adopted from other industries and the business case used to fund data management as a strategic initiative.
  • Business Value of Data Quality : This customer panel will address why data quality is a business imperative which significantly affects business success.
  • MD Anderson – Foster Business and IT Collaboration to Reveal Data Insights with Informatica: Is your integration team intimidated by the new Informatica 9.6 tools? Do your analysts and business users require faster access to data and answers about where data comes from. If so, this session is a must attend.
  • The Many Faces of the Healthcare Customer : In the healthcare industry, the customer paying for services (individuals, insurers, employers, the government) is not necessarily the decision-influencer (physicians) or even the patient — and the provider comes in just as many varieties. Learn how, Quest, the world’s leading provider of diagnostic information leverages master data management to resolve the chaos of serving 130M+ patients, 1200+ payers, and almost half of all US physicians and hospitals.
  • Lessons in Healthcare Enterprise Information Management from St. Joseph Health and Sutter Health St. Joseph : Health created a business case for enterprise information management, then built a future-proofed strategy and architecture to unlock, share, and use data. Sutter Health engaged the business, established a governance structure, and freed data from silos for better organizational performance and efficiency. Come hear these leading health systems share their best practices and lessons learned in making data-driven care a reality.
  • Navinet, Inc and Informatica – Delivering Network Intelligence, The Value to the Payer, Provider and Patient: Today, healthcare payers and providers must share information in unprecedented ways to reduce redundancy, cut costs, coordinate care, and drive positive outcomes. Learn how NaviNet’s vision of a “smart” communications network combines Big Data and network intelligence to share proactive real-time information between insurers and providers.
  • Providence Health Services takes a progressive approach to automating ETL development and documentation: A newly organized team of BI Generalists, most of whom have no ETL experience and even fewer with Informatica skills, were tasked with Informatica development when Providence migrated from Microsoft SSIS to Informatica. Learn how the team relied on Informatica to alleviate the burden of low value tasks.
  • Using IDE for Data On-boarding Framework at HMS : HMS’s core business is to onboard large amounts of external data that arrive in different formats. HMS developed a framework using IDE to standardize the on-boarding process. This tool can be used by non-IT analysts and provides standard profiling reports and reusable mapping “templates” which has improved the hand-off to IT and significantly reduced misinterpretations and errors.

Additionally, this year’s attendees are invited to:

  1. Over 100 breakout sessions: Customers from other industries, including financial services, insurance, retail, manufacturing, oil and gas will share their data driven stories.
  2. Healthcare networking reception on Wednesday, May 14th: Join your healthcare peers and Informatica’s healthcare team on Wednesday from 6-7:30pm in the Vesper bar of the Cosmopolitan Resort for a private Healthcare networking reception. Come and hear firsthand how others are achieving a competitive advantage by maximizing return on data while enjoying hors d’oeuvres and cocktails.
  3. Data Driven Healthcare Roundtable Breakfast on Wednesday, May 14th. Customer led roundtable discussion.
  4. Personal meetings: Since most of the Informatica team will be in attendance, this is a great opportunity to meet face to face with Informatica’s product, services and solution teams.
  5. Informatica Pavilion and Partner Expo: Interact with the latest Informatica and our partners provide.
  6. An expanded “Hands-on-Lab”: Learn from real-life case studies and talk to experts about your unique environment.

The Healthcare industry is facing extraordinary changes and uncertainty — both from a business and a technology perspective. Join us to learn about key drivers for change and innovative uses of data technology solutions to discover sources for operational and process improvement. There is still time to Register now!

FacebookTwitterLinkedInEmailPrintShare
Posted in Big Data, Business/IT Collaboration, Data Integration, Healthcare, Informatica World 2014, Master Data Management | Tagged , , , | 2 Comments

Data is the Key to Value-based Healthcare

The transition to value-based care is well underway. From healthcare delivery organizations to clinicians, payers, and patients, everyone feels the impact.  Each has a role to play. Moving to a value-driven model demands agility from people, processes, and technology. Organizations that succeed in this transformation will be those in which:

  • Collaboration is commonplace
  • Clinicians and business leaders wear new hats
  • Data is recognized as an enterprise asset

The ability to leverage data will differentiate the leaders from the followers. Successful healthcare organizations will:

1)      Establish analytics as a core competency
2)      Rely on data to deliver best practice care
3)      Engage patients and collaborate across the ecosystem to foster strong, actionable relationships

Trustworthy data is required to power the analytics that reveal the right answers, to define best practice guidelines and to identify and understand relationships across the ecosystem. In order to advance, data integration must also be agile. The right answers do not live in a single application. Instead, the right answers are revealed by integrating data from across the entire ecosystem. For example, in order to deliver personalized medicine, you must analyze an integrated view of data from numerous sources. These sources could include multiple EMRs, genomic data, data marts, reference data and billing data.

A recent PWC survey showed that 62% of executives believe data integration will become a competitive advantage.  However, a July 2013 Information Week survey reported that 40% of healthcare executives gave their organization only a grade D or F on preparedness to manage the data deluge.

value-based healthcare

What grade would you give your organization?

You can improve your organization’s grade, but it will require collaboration between business and IT.  If you are in IT, you’ll need to collaborate with business users who understand the data. You must empower them with self-service tools for improving data quality and connecting data.  If you are a business leader, you need to understand and take an active role with the data.

To take the next step, download our new eBook, “Potential Unlocked: Transforming healthcare by putting information to work.”  In it, you’ll learn:

  1. How to put your information to work
  2. New ways to govern your data
  3. What other healthcare organizations are doing
  4. How to overcome common barriers

So go ahead, download it now and let me know what you think. I look forward to hearing your questions and comments….oh, and your grade!

FacebookTwitterLinkedInEmailPrintShare
Posted in Data Governance, Data Integration, Data Warehousing, Healthcare, Master Data Management | Tagged , , , | Leave a comment

Improving CMS Star Ratings… The Secret Sauce

Many of our customers are Medicare health plans and one thing that keeps coming up in conversation is how they can transform business processes to improve star ratings. For plans covering health services, the overall score for quality of those services covers 36 different topics in 5 categories:

1. Staying healthy: screenings, tests, and vaccines

2. Managing chronic (long-term) conditions

3. Member experience with the health plan

4. Member complaints, problems getting services, and improvement in the health plan’s performance

5. Health plan customer service

Based on member feedback and activity in each of these areas, the health plans receive a rating (1-5 stars) which is published and made available to consumers. These ratings play a critical role in plan selection each Fall. The rating holds obvious value as consumers are increasingly “yelp minded,” meaning they look to online reviews from peer groups to make buying decisions. Even with this realization though, improving ratings is a challenge. There are the typical complexities of any survey: capturing a representative respondent pool, members may be negatively influenced by a single event and there are commonly emotional biases. There are also less obvious challenges associated with the data.

For example, a member with CHF may visit north of 8 providers in a month and they may or may not follow through on prescribed preventative care measures. How does CMS successfully capture the clinical and administrative data on each of these visits when patient information may be captured differently at each location? How does the health plan ensure that the CMS interpretation matches their interpretation of the visit data? In many cases, our customers have implemented an enterprise data warehouse and are doing some type of claims analysis but this analysis requires capturing new data and analyzing data in new ways.

We hear that those responsible for member ratings, retention and acquisition routinely wait >6 months to have a source or data added to a reporting database. The cycle time is too great to make a quick and meaningful impact on the ratings.

Let’s continue this discussion next week during your morning commute.

Join me as I talk with Frank Norman a Healthcare Partners at Knowledgent.

During this “drive time” webinar series, health plans will learn how to discover insights to improve CMS Star ratings.

Part 1 of the webinar series: Top 5 Reasons Why Improving CMS Star Ratings is a Challenge

Part 2 of the webinar series: Using Your Data to Improve CMS Star Ratings

Part 3 of the webinar series: Automating Insights into CMS Star Ratings

FacebookTwitterLinkedInEmailPrintShare
Posted in Application Retirement, Big Data, CIO, Customers, Data Warehousing, Enterprise Data Management, Healthcare | Tagged , , | Leave a comment

National Health IT Week 2013

As we head into National Health IT Week … like any good writer faced with a blank sheet, I was battling writers block by perusing Facebook. Coincidentally, I came across this HBR article. Healthcare — on the front page of the Harvard Business Review; so main-stream!

I implemented a Radiology Information System in 2000 and an electronic Medication Administration Record (MAR) in 2002. Back in the day, healthcare IT was the underdog, only the geekiest of geeks were up all night comparing paper MARs to electronic MARs, working side by side with the nurses and HIM to iron out bugs and taking delivery of new code into the wee hours of the morning.

Then I thought about previous National Health IT Week events. I remember gathering in DC with a bunch of other healthcare IT geeks  professionals, discussing the importance of health IT. Many may not realize the type of advocacy and awareness that occurs during this week – it’s pretty impactful. We had the unique experience of walking to the office of Senator Dick Durbin, meeting with him and requesting his assistance in making healthcare IT top of mind.

We’ve come a long way. But. We have a long way to go.

In the recent past healthcare has invested heavily in applications and infrastructure; EMR adoption is up, people are commonly using the words “healthcare analytics” and “data” is everyone’s favorite four letter word.  As data surfaces to the top of minds, gaining access to it, improving the quality of it and making sure that everyone trusts it has to be the next step for healthcare providers and payers. Hand coding interactions between systems is time intensive and error prone, information in aggregate magnifies data inconsistencies and data quality errors – for example, it’s always surprising to learn how many different ways a single enterprise can document marital status.

The reason to drill into this data is that locked in this data are the keys to value driven healthcare. To derive value from data, a commiserate investment in data is necessary.  I hope that this year’s National Health IT week includes a focus on and discussion of the data itself – making it accessible and trustworthy — and the types of tools required to do this.  Becoming data-driven is the only way to succeed in this value based model we are moving to. The three pillars of data driven healthcare are 1) Accessing and Using Data as an Asset, 2) Having Knowledge of All Participants and Actors and 3) Taking Action on What you Know.

FacebookTwitterLinkedInEmailPrintShare
Posted in Healthcare | Leave a comment

ROI via Application Retirement

ROI = every executive’s favorite acronym and one that is often challenging to demonstrate.

In our interactions with provider clients and prospects we are hearing that they’ve migrated to new EMRs but aren’t receiving the ROI they had budgeted or anticipated. In many cases, they are using the new EMR for documentation but still paying to maintain the legacy EMR for access to historical data for billing and care delivery. If health systems can retire these applications and still maintain operational access to the data, they will be able to realize the expected ROI and serve patients proactively.

My colleague Julie, Lockner wrote a blog post about how Informatica Application Retirement for Healthcare is helping healthcare organizations to retire legacy applications and realize ROI.

Read her blog post here or listen to a quick overview here.

FacebookTwitterLinkedInEmailPrintShare
Posted in Application ILM, Application Retirement, Healthcare | Tagged , , | Leave a comment

Why an EMR is Not Enough Part II

A lesson learned from other industries, like retail and financial services, is that while analytics and data warehouses are critical components to delivering big results from data — neither is easy. Gartner reported that 80% of data warehousing initiatives fail to meet expectations, often running over budget and failing to deliver a ROI.

  • Executives are often frustrated because responses to their requests for new reports and edited reports take too long
  • Misunderstood requirements and costly rework are the result of a lack of collaboration between stakeholders and IT
  • BI consumers lose confidence in data; they don’t trust it because they lack transparency into its lineage and don’t understand why it appears differently after being aggregated with data from other applications

 

Expecting value from data without making a commiserate investment in data results in unmet expectations. Accessing data is hard, each request requires new effort, establishing enterprise standards for data quality are an enormous effort and transforming data to fit into a heterogeneous intelligence environment is complicated and time consuming.

 

Introducing multiple sources of data across organizational boundaries creates a need for an environment that supports effective collaboration between stakeholders and the information technology team implementing solutions to manage data. To be genuinely useful, data must be verifiable and trustworthy since only then will stakeholders have the confidence to make data-driven decisions.  To realize the value of data, from Epic and beyond, IT leaders must implement business intelligence and data warehousing best practices that:

  • bring data together across applications including clinical and financial data
  • foster collaboration between clinicians, IT and business stakeholders
  • establish trust and confidence in business intelligence and decision making.
FacebookTwitterLinkedInEmailPrintShare
Posted in Healthcare | Tagged , , , | Leave a comment