Category Archives: Healthcare
With this 2014 holiday season rolling into full swing, Americans will spend more than $600 Billion, a 4.1% increase from last year. According to the Credit Union National Association, a poll showed that 45% of credit and debit card users will think twice about how they shop and pay given the tens of millions of shoppers impacted by breaches. Stealing identities is a lucrative pastime for those with ulterior motives. The Black Market pays between $10-$12 per stolen record. Yet when enriched with health data, the value is as high as $50 per record because it can be used for insurance fraud.
Are the thieves getting smarter or are we getting sloppy?
With ubiquitous access to technology globally, general acceptance to online shopping, and the digitization of health records, there is more data online with more opportunities to steal our data than ever before. Unfortunately for shoppers, 2013 was known as ‘the year of the retailer breach’ according to the Verizon’s 2014 data breach report. Unfortunately for patients, Healthcare providers were most noted for the highest percentage of losing protected healthcare data.
So what can we do to be a smarter and safer consumer?
No one wants to bank roll the thieves’ illegal habits. One way would be to regress 20 years, drive to the mall and make our purchases cash in hand or go back to completely paper-based healthcare. Alternatively, here are a few suggestions to avoid being on the next list of victims:
1. Avoid irresponsible vendors and providers by being an educated consumer
Sites like The Identify Theft Resource Center and the US Department of Health and Human Services expose the latest breaches in retail and healthcare respectively. Look up who you are buying from and receiving care from and make sure they are doing everything they can to protect your data. If they didn’t respond in a timely fashion, tried to hide the breach, or didn’t implement new controls to protect your data, avoid them. Or take your chances.
2. Expect to be hacked, plan for it
Most organizations you trust with your personal information have already experienced a breach. In fact, according to a recent survey conducted by the Ponemon Group sponsored by Informatica, 72% of organizations polled experienced a breach within the past 12 months; more than 20% had 2 or more breaches in the same timeframe. When setting passwords, avoid using words or phrases that you publicly share on Facebook. When answering security questions, most security professionals suggest that you lie!
3. If it really bothers you, be vocal and engage
Many states are invoking legislation to make organizations accountable for notifying individuals when a breach occurs. For example, Florida enacted FIPA – the Florida Information Protection Act – on July 1, 2014 that stipulates that all breaches, large or small, are subject to notification. For every day that a breach goes undocumented, FIPA stipulates $1,000 per day penalty up to an annual limit of $500,000.
In conclusion, as the holiday shopping season approaches, now is the perfect time for you to ensure that you’re making the best – and most informed – purchasing decisions. You have the ability to take matters into your own hands; keep your data secure this year and every year.
To learn more about Informatica Data Security products, visit our Data Privacy solutions website.
The Rising CFO is Increasingly Business Oriented
At the CFO Rising West Conference on October 30th and 31st, there were sessions on managing capital expenditures, completing an IPO, and even managing margin and cash flow. However, the keynote presenters did not spend much of time on these topics. Instead, they focused on how CFOs need to help their firms execute better. Here is a quick summary of the suggestions made from CFOs in broadcasting, consumer goods, retail, healthcare, and medical devices.
The Modern CFO is Strategic
The Broadcasting CFO started his talk by saying he was not at the conference to share why CFOs need to move from being “bean counters to strategic advisors”. He said “let’s face it the modern CFO is a strategic CFO”. Agreeing with this viewpoint, the Consumer Goods CFO said that finance organizations have a major role to play in business transformation. He said that finance after all is the place to drive corporate improvement as well as business productivity and business efficiency.
CFOs Talked About Their Business’ Issues
The Retailer CFO talked like he was a marketing person. He said retail today is all about driving a multichannel customer experience. To do this, finance increasingly needs to provide real business value. He said, therefore, that data is critical to the retailer’s ability to serve customers better. He claimed that customers are changing how they buy, what they want to buy, and when they want to buy. We are being disrupted and it is better to understand and respond to these trends. We are trying, therefore, to build a better model of ecommerce.
Meanwhile, the Medical Devices CFO said that as a supplier to medical device vendors “what we do is compete with our customers engineering staffs”. And the Consumer Goods CFO added the importance of finance driving sustained business transformation.
CFOs Want To Improve Their Business’ Ability To Execute
The Medical Devices CFO said CFOs need to look for “earlier execution points”. They need to look for the drivers of behavior change. As a key element of this, he suggested that CFOs need to develop “early warning indicators”. He said CFOs need to actively look at the ability to achieve objectives. With sales, we need to ask what deals do we have in the pipe? At what size are these deals? And at what success rate will these deals be closed? Only with this information, can the CFO derive an expected company growth rate. He then asked CFOs in the room to identify themselves. With their hands in the air, he asked them are they helping to create a company that executes or not. He laid down the gauntlet for the CFOs in the room by then asserting that if you are not creating a company that executes then are going to be looking at cutting costs sooner rather than later.
The retailer CFO agreed with this CFO. He said today we need to focus on how to win a market. We need to be asking business questions including:
- How should we deploy resources to deliver against our firm’s value proposition?
- How do we know when we win?
CFOs Claim Ownership For Enterprise Performance Measurement
The Retail CFO said that finance needs to own “the facts for the organization”—the metrics and KPIs. This is how he claims CFOs will earn their seat at the CEOs table. He said in the past the CFO have tended to be stoic, but this now needs to change.
The Medical Devices CFO agreed and said enterprises shouldn’t be tracking 150 things—they need to pare it down to 12-15 things. They need to answer with what you measure—who, what, and when. He said in an execution culture people need to know the targets. They need measurable goals. And he asserted that business metrics are needed over financial metrics. The Consumer Goods CFO agreed by saying financial measures alone would find that “a house is on fire after half the house had already burned down”. The Healthcare CFO picked up on this idea and talked about the importance of finance driving value scorecards and monthly benchmarks of performance improvement. The broadcaster CFO went further and suggested the CFO’s role is one of a value optimizer.
CFOs Own The Data and Drive a Fact-based, Strategic Company Culture
The Retail CFOs discussed the need to drive a culture of insight. This means that data absolutely matters to the CFO. Now, he honestly admits that finance organizations have not used data well enough but he claims finance needs to make the time to truly become data centric. He said I do not consider myself a data expert, but finance needs to own “enterprise data and the integrity of this data”. He said as well that finance needs to ensure there are no data silos. He summarized by saying finance needs to use data to make sure that resources are focused on the right things; decisions are based on facts; and metrics are simple and understandable. “In finance, we need use data to increasingly drive business outcomes”.
CFOs Need to Drive a Culture That Executes for Today and the Future
Honestly, I never thought that I would hear this from a group of CFOs. The Retail CFO said we need to ensure that the big ideas do not get lost. We need to speed-up the prosecuting of business activities. We need to drive more exponential things (this means we need to position our assets and resources) and we need, at the same time, to drive the linear things which can drive a 1% improvement in execution or a 1% reduction in cost. Meanwhile, our Medical Device CFO discussed the present value, for example, of a liability for rework, lawsuits, and warranty costs. He said that finance leaders need to ensure things are done right today so the business doesn’t have problems a year from today. “If you give doing it right the first time a priority, you can reduce warranty reserve and this can directly impact corporate operating income”.
CFOs need to lead on ethics and compliance
The Medical Devices CFO said that CFOs, also, need to have high ethics and drive compliance. The Retail CFO discussed how finance needs to make the business transparent. Finance needs to be transparent about what is working and what is not working. The role of the CFO, at the same time, needs to ensure the integrity of the organization. The Broadcaster CFO asserted the same thing by saying that CFOs need to take a stakeholder approach to how they do business.
In whole, CFOs at CFO Rising are showing the way forward for the modern CFOs. This CFO is all about the data to drive present and future performance, ethics and compliance, and business transparency. This is a big change from the historical controller approach and mentality. I once asked a boss about what I needed to be promoted to a Vice President; my boss said that I needed to move from a technical specialist to a business person. Today’s CFOs clearly show that they are a business person first.
Solution Brief: The Intelligent Data Platform
CFOs Move to Chief Profitability Officer
CFOs Discuss Their Technology Priorities
The CFO Viewpoint upon Data
How CFOs can change the conversation with their CIO?
New type of CFO represents a potent CIO ally
Competing on Analytics
The Business Case for Better Data Connectivity
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?
In my last blog, I talked about the dreadful experience of cleaning raw data by hand as a former analyst a few years back. Well, the truth is, I was not alone. At a recent data mining Meetup event in San Francisco bay area, I asked a few analysts: “How much time do you spend on cleaning your data at work?” “More than 80% of my time” and “most my days” said the analysts, and “they are not fun”.
But check this out: There are over a dozen Meetup groups focused on data science and data mining here in the bay area I live. Those groups put on events multiple times a month, with topics often around hot, emerging technologies such as machine learning, graph analysis, real-time analytics, new algorithm on analyzing social media data, and of course, anything Big Data. Cools BI tools, new programming models and algorithms for better analysis are a big draw to data practitioners these days.
That got me thinking… if what analysts said to me is true, i.e., they spent 80% of their time on data prepping and 1/4 of that time analyzing the data and visualizing the results, which BTW, “is actually fun”, quoting a data analyst, then why are they drawn to the events focused on discussing the tools that can only help them 20% of the time? Why wouldn’t they want to explore technologies that can help address the dreadful 80% of the data scrubbing task they complain about?
Having been there myself, I thought perhaps a little self-reflection would help answer the question.
As a student of math, I love data and am fascinated about good stories I can discover from them. My two-year math program in graduate school was primarily focused on learning how to build fabulous math models to simulate the real events, and use those formula to predict the future, or look for meaningful patterns.
I used BI and statistical analysis tools while at school, and continued to use them at work after I graduated. Those software were great in that they helped me get to the results and see what’s in my data, and I can develop conclusions and make recommendations based on those insights for my clients. Without BI and visualization tools, I would not have delivered any results.
That was fun and glamorous part of my job as an analyst, but when I was not creating nice charts and presentations to tell the stories in my data, I was spending time, great amount of time, sometimes up to the wee hours cleaning and verifying my data, I was convinced that was part of my job and I just had to suck it up.
It was only a few months ago that I stumbled upon data quality software – it happened when I joined Informatica. At first I thought they were talking to the wrong person when they started pitching me data quality solutions.
Turns out, the concept of data quality automation is a highly relevant and extremely intuitive subject to me, and for anyone who is dealing with data on the regular basis. Data quality software offers an automated process for data cleansing and is much faster and delivers more accurate results than manual process. To put that in math context, if a data quality tool can reduce the data cleansing effort from 80% to 40% (btw, this is hardly a random number, some of our customers have reported much better results), that means analysts can now free up 40% of their time from scrubbing data, and use that times to do the things they like – playing with data in BI tools, building new models or running more scenarios, producing different views of the data and discovering things they may not be able to before, and do all of that with clean, trusted data. No more bored to death experience, what they are left with are improved productivity, more accurate and consistent results, compelling stories about data, and most important, they can focus on doing the things they like! Not too shabby right?
I am excited about trying out the data quality tools we have here at Informtica, my fellow analysts, you should start looking into them also. And I will check back in soon with more stories to share..
Regardless of the industry, new regulatory compliance requirements are more often than not treated like the introduction of a new tax. A few may be supportive, some will see the benefits, but most will focus on the negatives – the cost, the effort, the intrusion into private matters. There will more than likely be a lot of grumbling.
Across many industries there is currently a lot of grumbling, as new regulation seems to be springing up all over the place. Pharmaceutical companies have to deal with IDMP in Europe and UDI in the USA. This is hot on the heels of the US Sunshine Act, which is being followed in Europe by Aggregate Spend requirements. Consumer Goods companies in Europe are looking at the consequences of beefed up 1169 requirements. Financial Institutes are mulling over compliance to BCBS-239. Behind the grumbling most organisations across all verticals appear to have a similar approach to regulatory compliance. The pattern seems to go like this:
- Delay (The requirements may change)
- Scramble (They want it when? Why didn’t we get more time?)
- Code to Spec (Provide exactly what they want, and only what they want)
No wonder these requirements are seen as purely a cost and an annoyance. But it doesn’t have to be that way, and in fact, it should not. Just like I have seen a pattern in response to compliance, I see a pattern in the requirements themselves:
- The regulators want data
- Their requirements will change
- When they do change, regulators will be wanting even more data!
Now read the last 3 bullet points again, but use ‘executives’ or ‘management’ or ‘the business people’ instead of ‘regulators’. The pattern still holds true. The irony is that execs will quickly sign off on budget to meet regulatory requirements, but find it hard to see the value in “infrastructure” projects. Projects that will deliver this same data to their internal teams.
This is where the opportunity comes in. pwc’s 2013 State of Compliance Report[i] shows that over 42% of central compliance budgets are in excess of $1m. A significant figure. Efforts outside of the compliance team imply a higher actual cost. Large budgets are not surprising in multi-national companies, who often have to satisfy multiple regulators in a number of countries. As an alternate to multiple over-lapping compliance projects, what if this significant budget was repurposed to create a flexible data management platform? This approach could deliver compliance, but provide even more value internally.
Almost all internal teams are currently clamouring for additional data to drive ther newest application. Pharma and CG sales & marketing teams would love ready access to detailed product information. So would consumer and patient support staff, as well as down-stream partners. Trading desks and client managers within Financial Institutes should really have real-time access to their risk profiles guiding daily decision making. These data needs will not be going away. Why should regulators be prioritised over the people who drive your bottom line and who are guardians of your brand?
A flexible data management platform will serve everyone equally. Foundational tools for a flexible data management platform exist today including Data Quality, MDM, PIM and VIBE, Informatica’s Virtual Data Machine. Each of them play a significant role in easing of regulatory compliance, and as a bonus they deliver measureable business value in their own right. Implemented correctly, you will get enhanced data agility & visibility across the entire organisation as part of your compliance efforts. Sounds like ‘Buy one Get One Free’, or BOGOF in retail terms.
Unlike taxes, BOGOF opportunities are normally embraced with open arms. Regulatory compliance should receive a similar welcome – an opportunity to build the foundations for universal delivery of data which is safe, clean and connected. A 2011 study by The Economist found that effective regulatory compliance benefits businesses across a wide range of performance metrics[ii].
Is it time to get your free performance boost?
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.
According to a recent article in the LA Times, healthcare costs in the United States far exceed costs in other countries. For example, heart bypass surgery costs an average of $75,345 in the U.S. compared to $15,742 in the Netherlands and $16,492 in Argentina. In the U.S. healthcare accounts for 18% of the U.S. GDP and is increasing.
Michelle Blackmer is an healthcare industry expert at Informatica. In this interview, she explains why business as usual isn’t good enough anymore. Healthcare organizations are rethinking how they do business in an effort to improve outcomes, reduce costs, and comply with regulatory pressures such as the Affordable Care Act (ACA). Michelle believes a data-driven healthcare culture is foundational to personalized medicine and discusses the importance of clean, safe and connected data in executing a successful transformation.
Q. How is the healthcare industry responding to the rising costs of healthcare?
In response to the rising costs of healthcare, regulatory pressures (i.e. Affordable Care Act (ACA)), and the need to better patient outcomes at lower costs, the U.S. healthcare industry is transforming from a volume-based to a value-based model. In this new model, healthcare organizations need to invest in delivering personalized medicine.
To appreciate the potential of personalized medicine, think about your own healthcare experience. It’s typically reactive. You get sick, you go to the doctor, the doctor issues a prescription and you wait a couple of days to see if that drug works. If it doesn’t, you call the doctor and she tries another drug. This process is tedious, painful and costly.
Now imagine if you had a chronic disease like depression or cancer. On average, any given prescription drug only works for half of those who take it. Among cancer patients, the rate of ineffectiveness jumps to 75 percent. Anti-depressants are effective in only 62 percent of those who take them.
Organizations like MD Anderson and UPMC aim to put an end to cancer. They are combining scientific research with access to clean, safe and connected data (data of all types including genomic data). The insights revealed will empower personalized chemotherapies. Personalized medicine offers customized treatments based on patient history and best practices. Personalized medicine will transform healthcare delivery. Click on the links to watch videos about their transformational work.
Q. What role does data play in enabling personalized medicine?
Data is foundational to value-based care and personalized medicine. Not just any data will do. It needs to be clean, safe and connected data. It needs to be delivered rapidly across hallways and across networks.
As an industry, healthcare is at a stage where meaningful electronic data is being generated. Now you need to ensure that the data is accessible and trustworthy so that it can be rapidly analyzed. As data is aggregated across the ecosystem, married with financial and genomic data, data quality issues become more obvious. It’s vital that you can define the data issues so the people can spend their time analyzing the data to gain insights instead of wading through and manually resolving data quality issues.
The ability to trust data will differentiate leaders from the followers. Leaders will advance personalized medicine because they rely on clean, safe and connected data to:
1) Practice analytics as a core competency
2) Define evidence, deliver best practice care and personalize medicine
3) Engage patients and collaborate to foster strong, actionable relationships
Take a look at this Healthcare eBook for more on this topic: Potential Unlocked: Transforming Healthcare by Putting Information to Work.
Q. What is holding healthcare organizations back from managing their healthcare data like other mission-critical assets?
When you say other mission-critical assets, I think of facilitates, equipment, etc. Each of these assets has people and money assigned to manage and maintain them. The healthcare organizations I talk to who are highly invested in personalized medicine recognize that data is mission-critical. They are investing in the people, processes and technology needed to ensure data is clean, safe and connected. The technology includes data integration, data quality and master data management (MDM).
What’s holding other healthcare organizations back is that while they realize they need data governance, they wrongly believe they need to hire big teams of “data stewards” to be successful. In reality, you don’t need to hire a big team. Use the people you already have doing data governance. You may not have made this a formal part of their job description and they might not have data governance technologies yet, but they do have the skillset and they are already doing the work of a data steward.
So while a technology investment is required and you need people who can use the technology, start by formalizing the data stewardship work people are doing already as part of their current job. This way you have people who understand the data, taking an active role in the management of the data and they even get excited about it because their work is being recognized. IT takes on the role of enabling these people instead of having responsibility for all things data.
Q. Can you share examples of how immature information governance is a serious impediment to healthcare payers and providers?
Sure, without information governance, data is not harmonized across sources and so it is hard to make sense of it. This isn’t a problem when you are one business unit or one department, but when you want to get a comprehensive view or a view that incorporates external sources of information, this approach falls apart.
For example, let’s say the cardiology department in a healthcare organization implements a dashboard. The dashboard looks impressive. Then a group of physicians sees the dashboard, point out erroes and ask where the information (i.e. diagnosis or attending physician) came from. If you can’t answer these questions, trace the data back to its sources, or if you have data inconsistencies, the dashboard loses credibility. This is an example of how analytics fail to gain adoption and fail to foster innovation.
Q. Can you share examples of what data-driven healthcare organizations are doing differently?
Certainly, while many are just getting started on their journey to becoming data-driven, I’m seeing some inspiring examples, including:
- Implementing data governance for healthcare analytics. The program and data is owned by the business and enabled by IT and supported by technology such as data integration, data quality and MDM.
- Connecting information from across the entire healthcare ecosystem including 3rd party sources like payers, state agencies, and reference data like credit information from Equifax, firmographics from Dun & Bradstreet or NPI numbers from the national provider registry.
- Establishing consistent data definitions and parameters
- Thinking about the internet of things (IoT) and how to incorporate device data into analysis
- Engaging patients through non-traditional channels including loyalty programs and social media; tracking this information in a customer relationship management (CRM) system
- Fostering collaboration by understanding the relationships between patients, providers and the rest of the ecosystem
- Analyzing data to understand what is working and what is not working so that they can drive out unwanted variations in care
Q. What advice can you give healthcare provider and payer employees who want access to high quality healthcare data?
As with other organizational assets that deliver value—like buildings and equipment—data requires a foundational investment in people and systems to maximize return. In other words, institutions and individuals must start managing their mission-critical data with the same rigor they manage other mission-critical enterprise assets.
Q. Anything else you want to add?
Yes, I wanted to thank our 14 visionary customer executives at data-driven healthcare organizations such as MD Anderson, UPMC, Quest Diagnostics, Sutter Health, St. Joseph Health, Dallas Children’s Medical Center and Navinet for taking time out of their busy schedules to share their journeys toward becoming data-driven at Informatica World 2014. In our next post, I’ll share some highlights about how they are using data, how they are ensuring it is clean, safe and connected and a few data management best practices. InformaticaWorld attendees will be able to download presentations starting today! If you missed InformaticaWorld 2014, stay tuned for our upcoming webinars featuring many of these examples.
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!
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:
- Over 100 breakout sessions: Customers from other industries, including financial services, insurance, retail, manufacturing, oil and gas will share their data driven stories.
- 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.
- Data Driven Healthcare Roundtable Breakfast on Wednesday, May 14th. Customer led roundtable discussion.
- 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.
- Informatica Pavilion and Partner Expo: Interact with the latest Informatica and our partners provide.
- 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!
According to Health IT Portal, “Having an integrated health IT infrastructure allows a healthcare organization and its providers to streamline the flow of data from one department to the next. Not all health settings, however, find themselves in this situation. Either through business agreements or vendor selection processes, many a healthcare organization has to spend considerable time and resources getting their disparate health IT systems to talk to each.”
In other words, you can’t leverage Health Information Exchanges (HIEs) without a sound data integration strategy. This is something I’ve ranted about for years. The foundation of any entity-to-entity exchange, health, finance, or other, is that all relevant systems freely communicate, and thus able to consume and produce information that’s required by any information exchange.
The article cites the case of Memorial Healthcare, a community health care system in Owosso, MI. Memorial Healthcare has Meditech on the hospital side and Allscripts in its physician offices. Frank Fear, the CIO of Memorial Healthcare, spent the last few years working on solutions to enable data integration. The resulting solution between the two vendors’ offerings, as well as within the same system, is made up of both an EHR and a practice management solution.
Those in the world of healthcare are moving headlong into these exchanges. Most have no clue as to what must change within internal IT to get ahead of the need for the free flow of information. Moreover, there needs to be a good data governance strategy in place, as well as security, and a focus on compliance issues as well.
The reality is that, for the most part, data integration in the world of healthcare is largely ad-hoc, and tactical in nature. This has led to no standardized method for systems to talk one-to-another, and certainly no standard ways for data to flow out through exchanges. Think of plumbing that was built haphazardly and ad hoc over the years, with whatever was quick and easy. Now, you’ve finally turned on the water and there are many, many leaks.
In terms of data integration, healthcare has been underfunded for far too long. Now clear regulatory changes require better information management and security approaches. Unfortunately, healthcare IT is way behind, in terms of leveraging proper data integration approaches, as well as leveraging the right data integration technology.
As things change in the world of healthcare, including the move to HIEs, I suspect that data integration will finally get a hard look from those who manage IT in healthcare organizations. However, they need to do this with some sound planning, which should include an understanding of what the future holds in terms of information management, and how to create a common infrastructure that supports most of the existing and future use cases. Healthcare, you’re about 10 years behind, so let’s get moving this year.