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U.S Healthcare Data and Analytics Pipeline

The demand for healthcare analytics professionals has exceeded all expectations, and is driven by the big data tidal wave.


Healthcare Big Data and Analytics

Big data†has been around for many years; not new to any industry. Itís a term commonly applied to large data sets where volume, variety and velocity all meet, and data complexity is beyond the ability of commonly used software tools to efficiently capture, manage, and process efficiently.

An organizationís and its data is one of the most valuable assets within most organizations. Therefore, being able to process and generate data using a proprietary automation process so that data can not only be stored, but also be fully analyzed, is an important strategic decision that must be made within an establishment. The knowledge and vision of applying strong analytics and capabilities to entire data will pave the path for true innovation within different segments of the Healthcare industry.†††

Healthcare Segments:

†* Medical & Diagnostic laboratories

* Outpatient care centers

* Physicianís offices

* Home health care

* Health practitioners

* Hospitals

* Nursing & residential care facilities

* Ambulatory services

* Dentistís offices

While Health Care administration costs are consuming 361 billion dollars for the U.S. health care system, tackling these excessive administrative costs offers a promising opportunity for integration of strong analytics, data management, data storage, predictive tools, and other management tools. Although, no one system could possibly handle such complexity, the many organizations adopting and investing in tools, and in very smart professionals, can agree that the cost of care and improvement of quality care, are two driving forces in the U.S. healthcare industry. †

Much of the movement hints that the U.S. healthcare industry will move from a mostly fee-for-service, volume-based system, to a value-based system. A good indicator is the strong analytics capabilities and data that have emerged within the past several years in the industry. While many other industries have experienced this type of innovation, the healthcare industry is poised to receive reconstructive surgery, and minimally invasive surgery, throughout different areas of the industry.

Provider Scoring and Algorithms

Implementation of scoring algorithms is not new and has been heavily used since the dot-com bubble burst in the year 2000 throughout different industries. The capabilities of algorithms scoring different products and services within the finance industry has innovated and transformed many sectors in that particular industry. With that said Ė scoring patterns and ranking programs such as the finance industry can be modeled using complex relevant algorithms. Thatís right, FICO = credit score, Altman Z-score = bankruptcy, StarMine† = investments decisions, just to name a few †risk assessment scoring products. ††

Knowledge + Analytics = Power x SOLUTIONS !

For the most part a typical medical providerís (MD) profile is actually very comprehensive and includes a significant amount of data criteria. However, the depth of data is largely depended upon the aggregation methods used, quality of data, relevancy of data, knowledge of data scientists & developers, and the strategic vision of the organization. For example, if you were to lookup Dr. John Dough, who is a Neurologist, there is a good chance that data on Dr. Dough vastly varies. Below is a partial example of some of the fields and elements in a physicianís profile and does not nearly constitute as a complete model, however by looking at some of the fields, it gives you a general idea of how aggregation of data and quality matters within the data set.††

a) Dr. John N. Dough
Specialty: Neurologic Surgery
Internship: UCLA, Los Angeles, CA
Residency: Neurological Surgery, Harbor View Medical Center, 1982
Fellowship: Harbor View Medical Center, Palo Alto, CA,

b) Dr. John Nathan Dough
Board Certification: Neurology, Issue Date: 6/19/1989
Internship: Mt. Sinai, Los Angeles, CA, 1980-1981
Residency: General Surgery, Neurology, Harbor View Medical Center, Palo Alto, CA, 1982-1985
Fellowship: Spine Surgery, Harbor View Medical Center, Palo Alto, CA, 1986-1987
Malpractice Judgment(s): 1 Judgment, Location. Arizona, Payment Amount: $475,000, Details: Settlement
Special Interest: Skull Base Surgery, Minimally Invasive Spinal Surgery, Disc Degenerative Disease, Spinal Fusion, Lumbar Spinal Surgery, Decompression.†

As seen in the partial descriptions (a,b), the depth within just a few fields varies for the same provider. More importantly, a complete profile, with all fields filled with proper data, would not only provide strong analytic capabilities, but a scoring in standard deviation would apply throughout profile as well. Thereís more on implementation of scoring methodologies that can be integrated into a scoring algorithm.

Surgeon Ratings Methodologies

Collaboration amongst surgeons and the ability to rate a peerís procedure technical skills, is not only an efficient method, but would prove to be a reliable assessment of a surgeonís skill. This methodology would need to be systematically integrated into a system for further processing, and a possible algorithm implementation. Today, many Healthcare quality models exist while using different methodologies. These indicators of quality often rely on patient feedback by accessing websites where consumers can review and rate a doctor with a numerical score. Websites offering ratings on physicians are popular and most will probably be around for years to come. However, because the accurate assessment of quality is very subjective on many levels, I believe advancements in quality measures, methodologies, and implementation of system tools will largely decrease the highly subjective evaluations that currently exist when rating a providerís performance.††

Methods of assessments for purposes of scoring a medical providers experience, training, education, and performance in a specialty field is very difficult to measure. Some of the critical implementation factors of designing an MD scoring system are a) Quality data, b) Strong analytics, c) Methodologies, d) Algorithms.†

Healthcare Procedure Pricing

With the government literally having 1,000ís of data sets in a vault, just sitting there, for the first time (April 2013) Medicare and inpatient/outpatient pricing data was released at Although this data dwarfs in comparison to the quality of data that exists in this government data vault, itís a start. Look for more of this type of data to be released in the near future. Meanwhile, sites with data on procedure costs are flourishing and are aggregating their own procedure costs data. †

Your medical procedure and/or treatment cost, whether or not youíre insured is an important factor when it comes to making a healthcare decision. Imagine a time when you will be able to search the cost of procedures and treatments by typing the surgery/treatment and city, and immediately access a comprehensive list of nearby hospitals, medical groups, or clinics, and information about quality and cost metrics for each. With an additional view, comprehensive data on your doctorís complete credential report, that also includes his/her score based on quality measurements. That time is here and has come to fruition. Look for pricing comparisons of treatments and procedures to get more in depth, and for consumers to take advantage and gain the benefits.


 healthcare big data
 healthcare analytics
 surgeon ratings methods
 procedure pricing
 hugo gallegos

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