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Posts Tagged ‘BI’

3 Components for a Successful Hybrid Environment in Healthcare

It is no secret that healthcare organizations are collecting more information today than ever before. They’re collecting information about their own operations, their patients and the communities they serve. The challenge for healthcare organizations isn’t collecting the information, but analyzing the data and efficiently and securely storing it. Healthcare organizations that can overcome the data challenges and gain faster, fuller data insights will have the tools to positively impact patient care and overall business.3 Keys to a Successful Hybrid Environment in Healthcare

When it comes to data storage, healthcare organizations struggle with finding a balance between “on premise” and the cloud. Many CIOs recognize the need to expand beyond the home port and are quickly moving information to public clouds. However, they aren’t completely abandoning their data centers for fear they won’t have control or access to timely information. The hybrid IT solution helps to solve the data storage problem but it also brings a unique set of concerns in regards to data control, data access and data compliance.

Data Control
Data is much easier to control when it is housed in one central location. With a hybrid IT solution, however, you do not have that luxury. Data stored in multiple locations must be seamlessly connected, able to securely and efficiently move between locations and allow you to maintain full control across all platforms.

Data Access
The key to collaboration and improved patient outcomes is ensuring everyone who needs access to data has it. On the flip side, broad data access needs to be secure and only available to authorized users. With a hybrid IT solution integrated data supports collaboration beyond the walls of the healthcare facility.

Data Compliance
Changing regulations are putting added pressure on healthcare organizations. Keeping up with the evolving regulatory landscape is a challenge in itself and having information stored in multiple locations only adds to this complexity. Developing a strategy to protect data and manage it to ensure it meets regulatory requirements is critical to a hybrid IT solution.

Hybrid IT environments provide the best of both worlds when it comes to data storage and analysis. Leveraging a hybrid environment will lead to timely and accurate analysis of data which will result in the delivery of actionable insights for improved collaboration, better patient outcomes and overall lower cost of care.

Considering implementing a hybrid IT environment or just want to learn more? Join Perficient and UnityPoint Health for a discussion on the benefits of Power BI and Office 365, and how one technology-savvy healthcare provider is leveraging its hybrid environment of Power BI, Excel-enabled dashboards and SharePoint 2013.

Sign up for the November 12th webinar

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No Easy Outs in Healthcare BI, but a New Approach

When you played baseball as a youngster, and stepped into the batter’s box, the last thing you wanted to be was an “easy out”. Ironically, today many healthcare organizations are looking for the “easy out” to rapidly develop the business intelligence reporting needed to address regulatory reporting demands, population health No easy outs with healthcare BI, but a new approachmanagement and chronic condition management, to name just a few.

The pressure to quickly stand-up an enterprise data warehouse, put data governance in place, start loading and cleaning data is intense just to get to the point of creating dashboards and offering mobile BI. Overloaded Healthcare IT teams are dealing with demands to compress traditional time-frames of 18-24 months to get the BI foundation in place down to as little as 4-5 months, start to finish.

This situation begs the old saying of “do you want it fast or do you want it right?” You can bet the answer today is both. Generally, healthcare organizations develop a BI strategy that examines the current state BI architecture, envision a future state BI architecture, document the gaps and create a time phased roadmap to build out the infrastructure, software and development required to meet the business needs. Just describing the process tells us that it will be complex and time consuming, right? Read the rest of this post »

Beyond the BI Strategy: 4 Steps to ROI

In a recent issue of PC Today (www.pctoday.com), there was a quote by Cindi Howson of BI Scorecard that really stuck in my mind: “There are far too many cases of companies having good data, good tools, but a culture that’s a barrier to using that data for action.” Frequently, outside Beyond the BI Strategy: 4 Steps to ROIconsultants are brought into an organization, especially in healthcare, to pull data out of silo’ed applications, cleanse it and land it in an enterprise data warehouse (EDW). Then the real fun begins as the organization tries to determine what their expectations are from this treasure trove of data. More importantly, this struggle to determine the value of the integration of clinical, operational and financial data can stall the return on investment for this important and difficult effort.

In conducting a business intelligence (BI) strategy, it is very important to investigate those silo’ed data sources to determine which elements can benefit which part of the organization and to notify internal groups of the new resources. In other words, the Enterprise Data Warehouse needs exploration and promotion to the key stakeholders or by the key stakeholders to gain new insights and derive the new value. Matching data to the right people is fundamental to success and deserves its own tracking mechanism in data governance. Moving beyond the original stakeholders and their requirements in a BI strategy and getting down to who really will use the data and how it is used helps drive stronger outcomes for the use of the integrated data. It truly isn’t just start with the end in mind, but exploring how the new integrated views of information can drive improved operational processes and solve daily problems in a real-time manner.

It is often frustrating to data warehouse builders because they understand the value stored inside but don’t know who needs the information to take action. It is worth educating and promoting this big investment! If a key data source is overlooked for real improvements in an important corporate process, then find it and add it. If data has moved past its useful life, then it should be moved to an archive to keep the enterprise data warehouse relevant and in step with the organization. Many organizations set up BI Competency Centers to help govern and develop the enterprise data warehouse, but my suggestion would be to make those centers a place for brainstorming, exploring and deriving value on an ongoing basis.

In healthcare, as we strive to lower costs and adopt a lean process improvement methodology, our process of using high-quality data should help identify new revenue opportunities, serve our communities more effectively and encourage us to explore possibilities. That exploration should start with the data that we work hard to acquire, extract, transform and load in our enterprise view. As data comes in faster, we need to respond quickly by connecting the data with the right users.

To summarize, in moving beyond the build stage of an enterprise data warehouse and gaining the return on investment, there are four key steps:

  1. Identify the “new” stakeholders that will use the EDW in their daily jobs
  2. Help the new stakeholders explore and learn what data is available to streamline clinical, operational or financial processes, possibly in a BI Competency Center to master tools
  3. Promote the success stories to create action from all parts of the organization
  4. Realize the return on investment from your EDW – celebrate!

How ProHealth is Innovating Population Health Management Webinar

The process of effectively managing population health while consistently measuring and reporting its outcomes can be a challenge for healthcare providers.

How ProHealth Care is Innovating Population Health ManagementWe will be having a conversation with Christine Bessler, CIO and VP of Information Technology at ProHealth Care and Juliet Silver, Director of Healthcare Advisory Services at Perficient on Wednesday, March 26. We will be discussing some of these issues as well as how ProHealth Care was the first healthcare system to produce reports and data out of Epic’s Cogito data warehouse in a production environment.

During the session, Christine will be answering the following questions:

  • How did they deliver clinically integrated insights to 460 physicians
  • How access to analytics allows their physicians to easily see which patients need important health screenings or care interventions, setting the stage for enhanced preventive care and better management of chronic diseases.
  • How ProHealth Care’ developed their strategy to integrate data from Epic with information from other EMRs and data sources to deliver clinically integrated BI
  • How ProHealth Care is positioning itself to deliver against an advanced self-service BI capability in the future.

Juliet will share insight into the methodology applied to establish data governance as a discipline at ProHealth Care, and how the Business Intelligence Competency Center came to be.

Christine Bessler will answer these questions and more during our free webinar on March 26th at 1:00pm CT.

To register for the webinar click here.

 

Why business intelligence isn’t the end game for health analytics

A few years ago, I transplanted my family from the south to Washington DC.  I love the Capital, for its history, its influence, but we quickly realized we had left Mayberry and arrived on Jupiter.  Horns honked and people moved around briskly.  Maybe it was us – our naiveté — or maybe it was the community we had arrived in.  But we quickly realized: “If you order french fries, you get french fries.” And only french fries. Months of dining out were spent, only to find that our presumed “condiments” were not standard with our order.  We would have to ask for them and specify the quantity.  French Fries and 2 ketchups, please.

Careful.Well I clicked my heels three times and eventually moved us back to our Mayberry.  It’s been three years and my son and I will still giggle together when we order french fries and see someone going out of his or her way to offer ketchup.  And when we say “Yes, Please”, we get several packets.

Consulting in Healthcare is no different. We’ve grown accustomed to the “build to spec” approach.  You get exactly what you asked for.

I’m thankful to be a part of Perficient and the Oracle Healthcare Business Intelligence team.  We share a common philosophy – understand what the customer wants to achieve, coach and advise available options, design and deliver a solution that fulfills their NOW problem and simultaneously prepared them for the next 5 years.  It’s not just a report – it’s Healthcare Analytics. Read the rest of this post »

Analyzing the healthcare industry tipping point using Therbligs

Do you remember therbligs from your Operations Management class? 

The word therblig was the creation of Frank Bunker Gilbreth and Lillian Moller Gilbreth, American industrial psychologists who invented the field of time and motion study. It is a reversal of the name Gilbreth, with ‘th’ transposed. Therbligs are 18 kinds of elemental motions used in the study of motion economy in the workplace. A workplace task is analyzed by recording each of the therblig units for a process, with the results used for optimization of manual labor by eliminating unneeded movements. (Wikipedia)

shutterstock_128890124I remember, and it was a lifetime ago.  But then again, the Gilbreth’s were turn-of-the-century industrial psychologists who invented the field of time and motion study.  I consider them the founding parents of Industrial Engineering.

So why are we talking about therbligs in Healthcare?

Ah, young Jedi, the time has come to learn our lessons much the same way that the industrial giants like Ford, Carnegie Steel and General Electric learned 100 years ago during Teddy Roosevelt’s administration.  These early lessons became the standards of the mid-century boom in manufacturing and production output.

So the healthcare technology space has finally gotten to its tipping point.  In order to survive, the healthcare industry will need to invest in Industrial Engineering principles and it will need to do product line, service line, episodic, acute and outpatient time and motion studies.

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Can you predict my future? Predictive analytics at #HIMSS14

While my interest is always in the convergence of technology like the Internet of Things and healthcare IT, the role of sensors in managing health and wellness is just exploding. 

“The most popular device functionality in the wearable tech market is heart rate monitoring, with nearly 12 million such devices shipped in 2013. Pedometers and activity trackers accounted for a combined 16 million shipments over the same period.” (According to a report released Thursday by ABI Research)

- Source: New report shows smartwatches and AR glasses have their work cut out.

the role of analytics, especially healthcare analytics, should be to inform, encourage and drive healthcare consumers to improve our behaviors or decisions without being intrusive.

“The role of analytics, especially healthcare analytics, should be to inform, encourage and drive healthcare consumers to improve our behaviors or decisions without being intrusive.”

You can’t turn anywhere without reading about the latest running gadgets, fitness bands, Bluetooth blood pressure cuffs, etc.  In the inevitable rush to wearable computing, one key idea can get lost: what are we doing with all of that data? 

The data produced by these devices and sensors has to be interpreted and turned into information that is actionable.  The fitness band that looks at your goal of 10,000 steps, sees that you are at 8,000 steps right after dinner and encourages you for one final walk around the neighborhood, will ultimately win out over all others.  In order to pull off that trick, we need analytics and, sometimes, predictive analytics.

Just as the sensors are working in the background without us even taking notice, the role of analytics, especially healthcare analytics, should be to inform, encourage and drive healthcare consumers to improve our behaviors or decisions without being intrusive.  The goal of healthcare analytics or informatics should be to create an environment for the healthcare consumer that makes life better, easier and more enjoyable.

An example is when the running app sees your pace slowing down towards the end of a run, then it kicks in a song with a faster pace to help you finish strong.  Today those apps require you to recognize that situation and take action of pressing a button.  It’s all there but it’s not automated.  What we need is that invisible intelligence that recognizes the situation and then takes action to assist us.

The Role of AnalyticsAt HIMSS 2014, we will be seeing this jump in interest in predictive analytics as it applies to healthcare, especially two distinct types of predictive analytics.

  1. One type is the traditional forecasting model of advanced analytics that trends past information to predict future states.
  2. The second type of predictive analytics is statistical models that encompass multiple feeds or variables to predict a future outcome.  This modeling is rapidly moving past the arena of data scientists who create the models and is moving more within the grasp of smart business analysts.  These models can predict your longevity based on multiple factors like your BMI, blood sugar readings for diabetics and other factors from your medical history.

Of course, we want to be able to predict health outcomes, especially when faced with several choices for changing our behaviors or lifestyle.  It will be exciting to see how healthcare application vendors are addressing this important next step in analytics.

The use of predictive analytics could really change the nature of a patient engagement with your doctor.  How will we react when we see the outcome of our current lifestyle?  Will we shut off Netflix bingeing and head to the gym? See you at HIMSS 2014 to find out!  Stop by Perficient’s booth #2035 and tell us what you found out!

himss14_top

 

Database inferencing to get to trusted healthcare data

A health insurance client of mine recently embarked on an initiative to truly have “trusted data” in its Enterprise Data Warehouse so that business leaders could make decisions based on accurate data.  However, how can one truly know if your data is trustable??   In addition to having solid controls in place (e.g., unique indexes on the primary AND natural key), it is also necessary to measure how the data compares to defined quality rulesWithout this measurement, trusted data is a hope – not an assured reality. 

shutterstock_71078161To enable this measurement, I designed a repository for storing

  • configurable data quality rules,
  • metadata about data structures to be measured,
  • and the results of data quality measurements.

I experienced the need to be able to perform a degree of “inferencing” in the relational database (DB2) being used for this repository.  Normally one thinks of inferencing as the domain of semantic modeling and semantic web technologies like RDF, OWL, SPARQL, Pellet, etc. – and these are indeed very powerful technologies that I have written about elsewhere.  However, using semantic web technologies wasn’t a possibility for this system.

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5 Reasons Big Data Improves Personalization of Medicine

I enjoyed an article today in IT Business Edge about the ways that Big Data is improving outcomes. We hear that all the time, right? But what does it really mean? Why does more (and better) patient data lead to improved healthcare for all? When business intelligence is leveraged properly to deliver insights to healthcare providers, we see the following:

  1. 5_waysLearning what we never knew before: 

    “Allowing for previously unknown factors involved in disease to be discovered and utilized as drug targets or disease biomarkers.”

  2. Comparing data points from various sources to individualize treatment plans, improving outcomes. 

    “We are able to align and compare multiple data points from various sources, tailoring individualized treatment plans for each patient.”

  3. A move from subjective interpretation to objective diagnosis.A coworker of mine said to me yesterday, “Can you imagine when our kids are older? They’ll be laughing at our stories of how doctors once said to us, ‘Based on your symptoms, I think you have [X disease].'”

    She’s right. Diagnoses vary from physician to physician based on his or her background and experience. Not any more! As this article states, we’re facing a “datafication” of patient samples.

    “A vast quantity of knowledge that can be statistically analyzed and quickly reviewed by multiple clinicians for solid diagnosis”

  4. Better – and faster – decisions about treatment as a result of more and better patient data
    “Clinicians can systematically extract more information from each patient without requiring multiple rounds of testing.”
  5.  More accurate diagnosis and more appropriate spending on treatments due to reproducible testing”Consistently reproducible test results are possible between clinicians and doctors for more accurate diagnosis and appropriate spending on therapy options.”

Two Keys to Success for Healthcare

Healthcare reform, ACA, Business Intelligence, Enterprise Portals, predictive analytics, pay for performance, the Triple Aim, total cost of care, patient safety….these, and many more,  are the buzzwords in healthcare and medicine these days.  Install this system, connect that system, run these reports, use this “intelligent program”… Do you ever wonder if we can solve all of these problems with just technology?

As a clinically oriented physician working in a technology world, I need to take a step back and look at behaviors and workflow.  How can we mentor the next generation of physicians, nurses and allied health professionals, teach them skills and foster their curiosity while encouraging them to be technologically savvy? I believe there are two twisted stethescopecritical keys to success: critical thinking and decision support.  Both are crucial and neither should exist without the other.  Here’s why.

Critical thinking is an essential tool for physicians.  Physicians who have this innate ability are often the most successful at diagnosing and treating their patients well. It is part art and part skill but ultimately, it affects patient safety and wellness.  I was pleased to see that medical school curriculums are now focusing on this as a fundamental skill. According to the recent Wall Street Journal article, “The Biggest Mistake Doctors Make,” the program at Dalhousie University “aims to help trainees step back and examine how biases may affect their thinking. Developed by Pat Croskerry, a physician known for his research on the role of cognitive error in diagnosis, it uses a list of 50 different types of bias that may lead to diagnostic error”.  Couple this with technology driven decision support at the point of care, which assists but never negates clinical judgment, and you have a winning combination.  These basic building blocks allow clinicians to concentrate on their craft: diagnosing and treating patients safely and effectively.

Healthcare reform is necessary but it does not have to undermine the knowledge and experience of our clinicians.  Adding technology, such as Natural Language Processing (NLP), real time decision support, predictive analytics, patient entered data via portals, mobile healthcare management apps and yes, even Watson, can only enhance and advance healthcare, streamline treatment and decrease costs.  Simple?  Let me know your thoughts!

Healthcare Analytics for the Patient Centered Medical Home

The patient centered medical home (PCMH) emphasizes care coordination and communication between various healthcare delivery systems. This coordinated care system can lead to better quality healthcare delivery as well as a better patient experience – but in order to achieve these benefits, providers must be able to see and interpret data from across the many entities the patient interacts with.

Leveraging clinical data from EMRs, HIEs and patient devices allows organizations to:

  • Enhance access and continuity
  • Identify and manage patient populations
  • Plan and manage care
  • Provide self-care support and resources
  • Track and coordinate care
  • Measure and improve performance

Join us October 29th for the webinar “Make the Most of Your ACO with Healthcare Analytics.”  You will learn how Oracle Enterprise Health Analytics (EHA), coupled with Oracle Business Intelligence and Oracle WebCenter, fulfills the ACO mandate for a patient centered medical home.

Click here to register for the webinar.

The Business Intelligence of Healthcare

Numerous industries incorporate core concepts and methodologies of business intelligence to capture and review processed information, develop trending metrics, implement projective analyses, and transform raw data to strategic information to enhance organizational operations. The core opportunity within the healthcare industry that will benefit all aspects of the organization is establishing high standards of care for patient quality and overall healthcare delivery system performance. The integration of hospital-leftbusiness intelligence has the ability to improve standards by implementing methodologies for the maintenance of current healthcare delivery systems while introducing innovative processes that will enable continual improvement.

The foundational categories that are required to integrate an effective business intelligence system will include the capture and data transfer from raw input data files into data that can be incorporated into analytic review, reporting, and graphing presentations to render future goals and strategy. Additionally, pre-defined goals must be established to focus on core competencies and objectives. In maintaining quality and performance, a quality parameter may include accurate diagnoses and follow-up treatment for an ER visit with a mapped performance indicator being time to service and subsequent ER revisits. The incoming ER visit submissions can be aggregated to present data sets to project risk assessment for future ER visits or missed diagnoses. The core methodologies of business intelligence can be utilized to improve on clinical and business aspects of healthcare systems with planning and determined goals.