Healthcare & Technology

Healthcare Analytics: Principles of Healthcare Clinical Intelligence

Link: Health reform, meaningful use drive demand for BI

A recent article in Healthcare IT News described an industry trend to take clinical data captured at the point of care and use it to determine how providers and hospitals can best meet requirements for meaningful use, and decisions regarding participation in ACOs. In technology circles, this trend is described as "Business Intelligence (BI)" or "Knowledge Management (KM)."

I prefer to describe uses of BI or KM software as "Clinical Intelligence" that can be used to analyze patient trends using data collected at the bedside and data contained in the Patient's EMR. Reported trends in the HIT News article describe reasons to collect and analyze data including: 

• "Pay for Performance" or bundled payment models that require efficient delivery of high quality healthcare services that result in improved health outcomes, and 
• An exciting move into the world of "Predictive Analytics" (within reasonable levels of confidence).

In 2008 I read a post by Tom Davenport, Harvard Business Review, about 10 Principles of the New Business Intelligence that included ideas that are relevant not only to Business Intelligence but can also form the basis for Principles of Healthcare Clinical Intelligence.. I loosely paraphrase:

• Healthcare decisions are made based upon objective and subjective reports by patients.
• Just like other industries, access to data isn't enough if the goal is improved health outcomes.
• Provide the right data in a clinically intuitive manner that supports the user's need for the right information, at the right time, for the right patient

Tom speaks to the "loosely coupled" relationship of information and decisions that are efficient enough to provide information for more than one question. He says that the provision of information supports decision making, but doesn't always "lead to better decisions."

I read this and considered that the most important factor in achieving clinical intelligence is the "human factor" ... Technology in and of itself does not change the way healthcare is delivered. Physicians, Clinicians, Nurses, Therapists, et. al. make decisions based on the data they - or computers - collect from and about the patient. He continued by saying that business intelligence results will increasingly be achieved by IT solutions that are specific to particular industries and decisions within them."

Interestingly, Tom commented about my post and recommended another post from his HBR blog, What Medicine Can Teach Us About Decision-Making. In this post Davenport mentioned Jerome Groopman, a distinguished doctor in Boston and a writer for The New Yorker (and the author of several books, including the recent How Doctors Think). "... many medical errors result from "poor thinking"--incorrect diagnoses, unreliable heuristics, and so forth... CEO's and other senior executives make similar errors. The difference is that "hospitals convene regular meetings where all faculty and trainees--from the chief to the beginning medical student--revisit cases that had poor outcomes." Needless to say, such self-examination is rare in the corporate boardroom.

Consider that business performance management is a "close cousin" to clinical outcomes management, healthcare analytics, predictive analytics, or any other name du jour. Three simple concepts can form the basis of an intelligent data platform upon which sound clinical decisions can be made.

• Capture: Is data captured in a format that is flexible enough to be used for decision making? With timely updates, accuracy, and availability with appropriate security from any mobile device?
• Analyze: Does the software tool provide an easy to use capability that searches, categorizes, slices, and dices data? Does it also save reports and recommend similar searches?
• Predict: Am I able to discern .. of the X number of patients admitted to the ICU each month over the past year, how many exhibited clinical factors indicating risk of Sepsis? What interventions were used to prevent progression?

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Healthcare Analytics: Capture, Analyze, Predict FRAUD

Link: CMS partners to move beyond 'pay and chase' anti-fraud efforts | Government Health IT

"The Centers for Medicare and Medicaid Services revealed intentions to tap predictive modeling to root out Medicare fraud last month and now has announced the technology and vendors that will make that happen."

After spending 11 years as an IT Director in the Financial Services market and a Champion of Data Warehousing, I might have guessed that fraud would be one of the first implementations of healthcare predictive analytics.

There have been many reports of healthcare fraud in recent weeks. Patients, providers, clinics, hospitals, pharmacies, laboratories, CMS, and payers are all interested in the same thing... The Clinical Record. 

Now that healthcare providers and hospitals have migrated from paper to electronic records, the data captured by these systems that are reported to CMS and private payers makes it easy to analyze the data for potential fraudulent claims and trends as well as the patient's clinical status. 

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To stay current on the HITECH Act and its quickly changing regulatory scheme visit the HITECH Survival Guide website and/or sign up for their free monthly compliance newsletter. Also, check out a FREE EHR Checklist.

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Survey on the benefits of EMR Software

Link: 2011 Physician Survey

An increasing number of Eligible Providers (EP) and Critical Access Hospitals (CAH) have attested to Meaningful Use 2011 Criteria. So now, what are the actual benefits received from using electronic medical records? Take the survey above and contribute your experiences with the group..

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To stay current on the HITECH Act and its quickly changing regulatory scheme visit the HITECH Survival Guide website and/or sign up for their free monthly compliance newsletter. Also, check out a FREE EHR Checklist.

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Healthcare Analytics: The VA Health Care System

The VA Health Care System

An interesting but previously unknown fact was that the Veterans Health Information Systems and Technology Architecture, VistA, is actually a bundle of nearly 20,000 software programs originally written in the 70’s by physicians for physicians. Interestingly, the author reports that many of the big EMR vendors today benefitted from the Open Source VistA EMR software – such as Epic and Cerner.

VA Health Care can be looked upon as a standard for future medical successes. The author spoke to an analogy of comparing the VA System with Accountable Care Organizations.. He writes, “we don’t need, and don’t have time for, endless studies and pilot programs to show how it could be done. With only a few tweaks, the VA can provide us with a proven model because it was an ‘accountable care organization’ long before most health-care wonks had any such concept.”

As a former VHA Staff RN I can relate to the many examples of quality care given to veterans in Longman's book. How, as a nation, do we care for our military and their families? They put their lives on the line, the ultimate sacrifice, and deserve the best care possible. As a nurse, I witnessed care of an Army Veteran mother who gave birth to an 11 lb. baby without requiring a C-Section. Due to his size, was born with distocia in his shoulder but fortunately without damage to his upper brachial plexus nerves. Mother and baby were fine, Physical Therapy (PT) and time healed the wound. Another example is a veteran who experienced shoulder pain after dislocation and a compressed vertebral disk. Again, PT was provided with pain management and without surgical intervention; his pain was virtually gone in a short while. He now serves with the Army’s Airborne Elite.

As an RN educated in the style of western medicine and therapeutics, I would have thought an OB/Gyn provider would have quickly performed a Cesarean Section for a fetus that size. I also would have expected that the man with the shoulder and compressed disk problem would have undergone some type of orthopedic surgery.

These examples are shared with their possible alternatives because the private health system is incented to provide interventions for which they are paid (fee-for-service). In contrast, the VA is incented to keep veterans healthy over their lifetime, though preventative care, education, patient involvement, and at lower healthcare costs.

1. Through use of VistA for the past 20+ years, the VHA has access to longitudinal records of veterans that can be used to study what works and what doesn’t work for patients with specific conditions, given certain treatments.
2. These records provide excellent insight into evidence based medicine. In comparison to private health plans, VHA and clinical guidelines are developed using this data. that support the benefit of long term relationships between veterans and the VHA.
3. Considering the aging population, the progression and high incidence of chronic diseases, coordinated and continuous care is required. Unfortunately, with the multitude of software systems for the healthcare market (clinics, CAHs, etc.), the ability for Clinicians to view longitudinal care received by patients is not available.
4. In our current state of EMR adoption, lack of free-flowing data from provider-provider or hospital-provider, hinders accumulation of medical knowledge that educates and informs clinicians in the practice of medicine.

This brief commentary on the book and use of medical data by the VHA is an exemplar of how health data collected over a long period of time, when analyzed in the context of disease and health conditions has the potential to predict which evidence becomes medical best practices. 

Healthcare Analytics: Capture, Analyze, Predict

Link: Analytics hold promise for proactive healthcare delivery

Years ago, as an IT Director, I was a “Ralph Kimball cheerleader” for business intelligence, data warehousing and analytics. OK, I wasn’t really a cheerleader, and even had my wings clipped, but the promise of improved knowledge and capabilities enabled by data analytics in business was a key factor for success.

In this new world of HITECH, it comes as no surprise that BI and analytics is a rapidly growing field in healthcare. The focus over the past two years has been to select, purchase, install, and train clinicians on use of EMRs and its implications for workflow changes. We are in the stage of Capture.

Many providers and hospital complexes are making progress with installation, training and use of EMRs and have received their first dose of incentive monies. So what is the next step?

In addition to future Meaningful Use phases and incentives, Clinicians are becoming familiar with the power of analytics for data contained in the EMR. Software tools such as QlikView, Cognos, Microstrategy, Anvita, and others are guiding us to the next step, Analyze.

The combination of a treasure mine of clinical data contained in an EMR system with future capabilities of HIEs and Clinical Registries, the ability to identify key performance factors not only for financial and operational assessments, but also key performance indicators for patient safety and health is a growing area of interest. Articles have recently been published about trends and concerns for chronic patient conditions and diseases, lifestyle changes for wellness and a plethora of other topics of interest to both patients and clinicians.

There is sufficient medical and scientific literature online to assess risk factors and patient data trends that suggest high risk or potential risks for chronic disease management, as an example. As clinicians become more knowledgeable and comfortable using the technology there may well be a growing area of interest to to analyze risk factors and/or possible outcomes for individual patients. The next step: Predict.

In the coming posts, I will share some ideas and my experience in the "world" of data analytics and healthcare intelligence with a series of posts on the topic: Healthcare Analytics: Capture, Analyze and Predict.

In a word... Predictive Analytics. One of the key benefits of healthcare analytics is for clinicians to become more proactive in care delivery with a focus on prevention and early treatments. These tools and this enhanced focus can and will lead to improved patient outcomes if used properly. 

 

Managing Process Variation to improve quality and reduce cost?

Link: Process Variation Podcast

As more Physicians and Hospitals strive to meet requirements for Meaningful Use incentives, the topic of process variation comes to mind. Generally speaking, Nurses observe variation in all patient encounters. Some variations represent downward trends in patient stability or condition, while others trend upward with improved conditions and wellness. Often negative variations cause immediate clinical action, interventions and/or treatments. 

I had not given much thought to the topic of process variation and its management as a tool to reduce costs and improve care until I heard this podcast from Hospitals & Health Networks. The ability to manage, recognize and act upon patient status trends in real-time has the potential to improve the quality of health care delivery and to lower cost of care. An interesting thought..

Click on this link to read a recent article from BMJ 2011 on the topic: The meaning of variation to healthcare managers, clinical and health-services researchers, and individual patients.

Looking for a best of breed HIPAA Compliance Software?

To stay current on the HITECH Act and its quickly changing regulatory scheme visit the HITECH Survival Guide website and/or sign up for their free monthly compliance newsletter. Also, check out a FREE EHR Checklist.

If you need tools that will help with your compliance initiatives then check out the HSG Store.