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Posts Tagged ‘big data’

10 Benefits of Enterprise Information Management in Healthcare

This month, we completed an interview with our healthcare analytics strategist, Juliette Silver. We wanted to understand how enterprise information management strategies can specifically optimize business performance, reduce costs, mitigate risks and improve quality of care.

From the interview, I take away at least 10 major benefits to establishing and leveraging an enterprise information management strategy in healthcare settings:

EIMAn EIM strategy can:

  1. Help manage access to enterprise information in a secure, HIPAA-compliant manner.
  2. Allow healthcare professionals to turn mountains of data into real-time decisions.
  3. Help focus people, process, policies, frameworks and foundational technologies toward how to best leverage enterprise data.
  4. Set forth the framework that will be used to provide the information delivery capability,whether the information is in the form of data (structured or unstructured) or unstructured content, or a combination of both.
  5. Help an organization respond to evolving regulatory requirements and reimbursement models.
  6. Define the information management model that will be used to harmonize the delivery of both content and data specific to a healthcare organization’s goals and objectives.
  7. Ensure the delivery of information in the form of a trustworthy source that can be interpreted, used and managed consistently across the enterprise.
  8. Give a clinician or healthcare knowledge worker the access they need to the many sources or types of information from which to make decisions.
  9. Ensure information is timely, accurate, valid, verified and generally fit for purpose.
  10. Produce a more holistic view of the patient, derived from structured data stored in an electronic health record and other clinical systems, as well as unstructured information or content made available in some of the forms previously stated.

Read the full interview 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.

Read the rest of this post »

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.

Read the rest of this post »

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.”

Social Meets Clinical Meets Research: Big Data in Medicine

I was intrigued immediately when I read that The Mount Sinai Medical Center in New York hired the former data scientist for Facebook, Jeff Hammerbacher, to develop and refine their predictive analytics capabilities.  It seems like a collision of the planets!  Is it possible that this social media data scientist could break the code of predictive analytics in medicine and introduce us to the wonders of big data AND really improve health and wellness in the process?

It is my hope that this collaboration, particularly with Joel Dudley, director of biomedical informatics at Mount Sinai’s medical school, will produce something great.  As a health_iconphysician, I look for the future of medicine to provide insights into the veiled depths of our core being.  Why do some patients respond to treatments while others don’t?  What factors blend together to allow some individuals to achieve wellness when others cannot?  How can we predict who is at risk for becoming “chronically ill” and how can we work to proactively reverse that?  Are these questions based on genomics, demographics, social interaction, environmental factors or something else?

Big Data is everywhere.  From the ever evolving social media space of Facebook, Twitter, LinkedIn and more, to the wealth of Patient Generated Data, to the heat maps of disease outbreaks and millions of patient EMR findings, to the developing genomic data, someone should surely be able to decipher the code and be able to predict wellness.  Maybe it’s a pipe dream, maybe not.  But I do think if great minds combine with great machines, perhaps it CAN happen.

Let me know your thoughts!

Top 5 Technology Trends in Healthcare – September 2013

The healthcare IT field is rapidly developing and changing. Emerging technology and updated regulations put pressure on healthcare providers and health plans to stay ahead of the curve. Perficient creates a monthly list that explores some of the current topics and issues in health IT. This list examines the most talked about issues and technologies that are currently affecting the industry.

HCBlog Top5 Trends

Obamacare Defunding

Under the Affordable Care Act, or Obamacare, over 48 million uninsured Americans will be eligible for enrollment in subsidized plans through state-run health insurance exchanges, with annually increasing fines for those who go uncovered. Currently, the US government is reviewing calls to defund Obamacare while Health Insurance Exchanges are set to open on October 1st.

Google Calico

Last week, Google announced it would be reentering the e-health game with its new product, Calico. The goal of Calico is to positively impact aging and associated diseases, while focusing on health and well-being. Initially, Calico will fun aging and preventable disease research projects.

Read the rest of this post »

A Low Cost Big Data Integration Option?

With all of the interest in big data in healthcare, it’s easy to get drawn in by the excitement and not realize that it’s not a silver bullet that’s going to address all your data and infrastructure problems.   Unless you are able to understand and integrate your data, throwing all the data onto a platform like Hadoop or Cassandra probably won’t provide the benefit you’re looking for. Of course, there really is benefit to leveraging a big data platform for the right kinds of use cases, such as increased scalability, performance, potentially lower TCO, etc.

Of course, there are many integration tools out on the market that perform well.   However, I’d like to propose consideration of Semantic Web technologies as a low cost alternative to traditional data integration.  Many are open sourced and are based on approved standards from W3C such as RDF (Resource Description Framework) and OWL (Web Ontology Language).

How_information_is_connecting_all_types_of_healthcare_data_to_make_a_difference_LRGUsing Semantic Web technologies to enable integration, for example the Open Link Data initiative for integrating data across the internet, can (besides being less expensive) provide significant advantages for automated inferencing of new data which would previously require specialized programming to derive.  Indeed, your Semantic Web environment can serve as the knowledge base for artificial intelligence.

Read the rest of this post »

The Coming “Big Data” Storm

As a technologist raised in Kansas as a child, I am used to examining the horizon for changes in the weather.  We could watch the large thunderstorms build up during the heat of the day into 40,000 foot monsters full of hail and tornadoes.  I was reading an Ars Technica article on how pervasive computing and cloud will change the nature of IT recently, and the article pointed out the coming “big data” storm.  The article argues that like the heat of a Midwestern day growing and driving the thunderstorm, key technologies have reached a tipping point to create the perfect “big data” storm.

Just like storms, big data includes three big trends of volume, velocity and variety.  Data sets were predicted to reach 1 petabyte (1 million gigabytes) and without recent advances in hardware and software, especially virtualization and cloud storage, would be unmanageable in terms of volume.  Velocity is especially evident in healthcare data stormwhere near real-time information is not just a goal but becoming a requirement.  Velocity demands very fast processing to analyze data, potentially aggregate it, and visualize results.  Variety of data is a challenge in healthcare as well, with new and unstructured forms like video, text and sensor readings. The proliferation of medical devices and sensors alone can create data that literally overwhelm the typical healthcare organization’s ability to analyze and take action based on the information, thus creating a dangerous storm.

Read the rest of this post »

Top 5 Technology Trends in Healthcare – August 2013

The healthcare IT field is rapidly developing and changing. Emerging technology and updated regulations put pressure on healthcare providers and health plans to stay ahead of the curve. Perficient creates a monthly list that explores some of the current topics and issues in health IT. This list examines the most talked about issues and technologies that are currently affecting the industry.

HCBlog Top5 Trends

Personalization of Medicine

Personalized analytics have the power to improve care outcomes for patients by drawing data from a complete view into their care coordination. Healthcare analytics and big data hold the key to being able to provide personalized care and prevention. By integrating personal health records with EMR data, providers have a 360 view into the history of the patient and the care they require.

Interoperability

Interoperability plays a key role in ensuring systems can communicate with each other to share information. It helps to reduce redundant data entry, speed access to information and create a real-time flow of information through an enterprise IT system. The key benefit of creating interoperability is to improve the visibility, sharing and re-use of data collection between disparate healthcare applications and devices.

Read the rest of this post »

Harnessing Hospital Data to Improve Healthcare

In the age of ACOs and value based payments, there is a constant pressure on the healthcare industry to reduce costs without damaging the quality of care provided. While there are many factors in this balancing act, hospital readmissions and  lack of medication adherence are two issues driving up costs that can be addressed and prevented. EMRs hold the data needed to created a prevention plan, but that data is often siloed from clinical, financial and operation data also necessary for an effective plan. Business intelligence and analytics tools allow providers to view and interpret the data, but even these systems often don’t communicate with other systems.

A Forbes article recently announced that IBM and Premier health alliance are teaming up to provide better data insights across a population. Using big data, this Data Alliance Collaborative (DAC) utilizes IBM technology to predict readmissions and medication compliance issues across the Premier collaboration of 200 hospitals. With over 70 different health care systems, Premier sees great value in using shared capabilities to leverage data analytics for population health.

“Partnering with Premier and  IBM to create the integrated view of clinical, financial and operational information in one data model will allow a clearer analysis of costed outcomes and improved decision support for healthcare organizations,” said Martin Sizemore, principal, healthcare strategic advisory services at Perficient. This real-time integrated view of the data will allow hospitals to make mid-course adjustments to meet federal regulations.

Perficient will be hosting a webinar, “Going Beyond the EMR for Data-driven Insights in Healthcare,” to further explore the role of data analytics in healthcare. Join us to learn how analytics is being used to measure and monitor performance and provide service-line directors and financial administrators with reporting and analysis that enhances clinical care processes and business operations.