HAS-15, Do I Attend or Not?

If you are like me, the more information that I can internalize the better. However, we can become bombarded by too much information, too much time dedicated to personal education, and too much time away from the things that are most important in our lives. Finding the balance between learning more, and finding the areas that will play a meaningful part of your life can be difficult. When you throw in the fact that a concept may seem intriguing to you, but may be better saved for another more appropriate time in your life, you must weigh the pros and cons. This is a dilemma that many may face in the next few months as anticipation and information is released from the Healthcare Analytics Summit 2015 (HAS’15) presented by Health Catalyst.

image courtesy of HealthCatalyst.com
image courtesy of HealthCatalyst.com

To help break past doing the pros and cons list, it is necessary to understand what the Summit is all about, and if the materials to be presented will fit into the appropriate category for you. For those of you who attended last year’s rousing success Summit, this may be a rehash because you already have a true grasp of who can benefit and what roles they play within an organization. For the others that were not able to attend, did not know about the Summit, or let the chance slip by you, I have located a good comprehensive list that details many facts.

Analytical strategies are not a new tool within an arsenal of a healthcare organization, however, the prominence has grown in popularity due to the ability to find data-driven planning and solutions. If you are tasked with understanding an array of data sources and analytical tools, yet you find yourself on the outside or scouring the internet to find ways to create meaningful reports, you are a good candidate to significantly grow in your position. The analytical strategies that will be addressed will include far-reaching clinical, operation, financial and administrative reporting demands. Contained within is an organized way of identifying, prioritizing, measuring and tracking financial changes as a means of reducing waste and overages.

As most of know, changes in life, especially in a well-established routine, can be difficult to make. There are some individuals who take to this task better than others, yet changes are necessary for the betterment of all involved. Sometimes it is vital that adoption of analytical strategies is accelerated as a means of moving away from inefficiencies and losses to a single-system version software that provides all mandatory and optional insights into how the organization is doing. When there are stragglers to the party, it makes it difficult to find comprehensive and accurate data. Correlations between data points requires all possible inputs to prove relationships (positive or negative).

It is possible that you are on the other end of the argument and already have a system in place, but have reached a limit to the system’s scope. When a ceiling has been hit, it makes it challenging to find valuable data, to track complex data, and to make data-driven decisions. At one point, your system worked wonders, provided all the insight you may have needed, but when that system no longer works for you, getting out of that frustrating routine into a system that is ample enough for current and future needs can be make-it-or-break-it answer for your organization.

Adversely, organizations that are in the implementation stage with electronic medical records (EMR) are not candidates for these advanced approaches. It is the age-old adage that you must walk before you run, and is very applicable in this situation. If you are looking ahead to the future and wanting to employ a progressive system to your organization, make sure your foundational policies and procedures are established.

Furthermore, there are organizations that have gone well beyond the basics of analytical strategies and are working on a more predictive method of managing. These companies are not going to benefit from the information that will be presented at the Summit due to the fact that they have already applied the tactics. Although, there might be small aspects or qualities that would be new and helpful, overall, the Summit may be seen as remedial.

image courtesy of flickr.com/PhilippaMckinlay
image courtesy of flickr.com/PhilippaMckinlay

As a whole, there are many people within a single organization that would greatly benefit attendance at this year’s HASummit. To see a more complete list of the ideas and fundamental backgrounds that will be addressed at the Summit, please refer to the “Who Should Attend” page of the HAS-’15 conference. Also included within the HAS-’15 site is a recap of the highly-successful launch of the HAS-’14 conference, which you can browse.

You are the best one to assess your position and the demands that you have. If you fall into the criteria presented above, you may want to dive in more deeply to the specifics and register for the Summit before this passes you by once again.

Shifting from Fee-for-Service to Value-Based Healthcare

Value-based healthcare is being or will be implemented in all hospitals and healthcare organizations soon. The healthcare industry is facing rising costs, and often worsening outcomes, and this needs to stop. Too many organizations are stuck in their old ways and moving along without changing or improving, without getting better outcomes or lowering costs. Why not make the healthcare industry more efficient and cost-effective for everyone?

image courtesy of freedigitalphotos.net/VichayaKiatying-Angsulee
image courtesy of freedigitalphotos.net/VichayaKiatying-Angsulee

To understand the old path, it is necessary to grasp fee-for-service healthcare. This is pretty much just what it sounds like: healthcare experts are paid for each service they provide, whether it is an visit in the office, specialty treatment, tests or other procedures. This would open the doors for excessive testing, and referrals for outside treatment that might not be necessary. To change how some healthcare providers were ordering excessive assessments on patients, requirements from the government are starting to reflect the value-based method of payments to make the doctors more responsible for what they are asking of their patients, and the vast diversity in costs from office to office.

Hence the switch to value-based healthcare. This switch won’t necessarily be easy or smooth, but implementing this switch based on data and analysis can hopefully make the process less painful. Rather than switch a whole system haphazardly, an organization should first understand the end goals and how they would like to get there. This makes it possible to look into the demands they will have from a system, and this is crucial because in the value-based model, the healthcare organizations are at a higher risk of not getting reimbursed.

Crystal Run Healthcare is a great example of an Accountable Care Organization (ACO) switching to the value-based model. One tool they are using to ensure improved care, better professional and specialist coverage of the city’s population, and controlling of costs for everyone involved revolves around Population Health Management (PHM). PHM is the understanding of the people and communities that are being cared for.

image courtesy of flickr.com/BillOhl
image courtesy of flickr.com/BillOhl

Taking control of the rising cost of providing healthcare doesn’t have to be as large of an issue as many in the healthcare industry might make it out to be. A change to the point of view from which these professionals are going about the duties is a huge step in the right direction. The move from fee-for-service to value-based care may not seem logical, yet with the right tools and awareness of short- and long-term goals will put you on the right path. In the end, value-based treatment should not be the ugly step-child that is shunned and never understood, but an innovative way to move into the future of healthcare.

Does CIO Have the Right Idea about Clinical Data Warehousing

It isn’t much of a secret that the healthcare industry as a whole is playing a game of catch-up when it comes to certain technological implementations. One of the areas where there is not only a need but also an outright demand for technology is in data warehousing. Due to the vast amount of information being generated every day, and the requirement to change those saved data points into valuable data-driven details is essential. As explained in the CIO article, evidence-based content must guide quality improvements in healthcare.

image courtesy of flickr.com/TristanSchmurr
image courtesy of flickr.com/TristanSchmurr

Data warehousing has gone from a haphazard storing of data that usually was insufficient, and lacked the ability to produce complex company reports or provide analytical insights. Today, clinical data warehousing is much more agile, with the capability of integrating information from all departments, yet restricting access to appropriate personnel into their proper responsibilities. This agility allows for complex reporting with many factors and filters to reach decisive answers into how the organization is working.

Due to the financial and time investments that are necessary to implement something as large and involved as a data warehouse requires an understanding into what you are really investing your money. It would be amazing to employ a new technological tool and see dividends paid out immediately. However, this is rarely the case in any business of industry, and applies to this situation, too. As seen with Texas Children’s Hospital, there was an initial three-month trial period, and then a nine-month timetable established to bring everything together. Now, they are able to pool and pull from 12 different systems within their framework, and produce data that isn’t stale or out-of-date.

Since implementing the clinical data warehouse, Texas Children’s Hospital has seen a significant reduction in costs, including the ability to reallocate resources to other initiatives the hospital has. Additionally, they have seen an improvement to patient outcomes and overall patient satisfaction, which cannot be quantified financially.

image courtesy of freedigitalphotos.net/Praisaeng
image courtesy of freedigitalphotos.net/Praisaeng

Implementing a clinical data warehouse is not a simple decision, nor one that fixed in place quickly, the long-term effects for both organization and patient will be improved drastically. CIO truly does have it correct that data warehousing is not just a fly-by-night idea that will fizzle out, but a standard to which many healthcare establishments must rely on to provide better care and to keep costs as low as possible.

Healthcare Analytics Takes Giant Step into the Future with Newly Named Collaboration

The recent announcement that partners up Health Catalyst and Allina Health has a completely new feel in the healthcare industry. Health Catalyst is one of leading providers of data warehousing and clinical analytics, and drives quality improvements by managing inefficiencies in order to lower costs but not at the expense of patient satisfaction.

This $108 million deal has two very unique elements that may become the new model for business practices in the future:

  • Allina will send Health Catalyst all of their data warehousing, analytics and performance improvement technology, along with specific personnel
  • Allina will receive access the Health Catalyst’s technology rich software with content and deployment expertise to ensure accelerated outcome improvement

What this translates to is the fact that as healthcare companies move away from fee-for-service based payments and the margin of running inefficiently becomes impossible, a new archetype for performance is required. As a means of proving that Health Catalyst can provide this process, they have staked part of their fees with Allina to the ability to show improvement to quality and outcomes. Each year, a committee of representatives will assess results and progress towards short- and long-term goals.

Due to the fact that Allina works within 12 hospitals, almost 100 clinics, and other healthcare services, the opportunity to see the real-world findings “via [a] living laboratory” may be the perfect ongoing evidence that the traditional relationships between vendor and healthcare provide should be reexamined.

Risk Management in Healthcare

There is a level of expectation when you enter a hospital, clinic or doctor’s office that you will be made better at some point down the road. Obviously, there are some instances when this expectation can’t be met, however, the objective to heal is still at the forefront. From the point of view of healthcare professionals, meeting this objective doesn’t start when someone walks through the door, but long before that in ways that may be somewhat astounding.

image courtesy of freedigitalphotos.net/Praisaeng
image courtesy of freedigitalphotos.net/Praisaeng

A very conscious effort is being made on a daily basis when it comes to reducing the possibility of loss, whether of life, mobility, thought or feeling of security. The healthcare industry walks a fine line when understanding risk and managing that risk to each individual patient. The strategy to decrease risk begins with a methodic gathering and utilization of essential data. The activities of the past shed light on what will happen in the future; use history to teach you what to expect.

What this compiled mass of data gives is answers to most common and rare human conditions, instead of relying upon the more limited experience or research of a single or group of healthcare professionals. Now, doctors can turn to tried-and-tested data to diagnose and treat patients. This information is a more proactive approach to medicine in the hopes of making someone better before conditions worsen and to also prevent medical catastrophes before they ever occur.

There are times, though, that no matter how much effort is put into preventing adverse events, and the only response left is to be reactive. This is not a negative characteristic because we know that accidents happen and tell-tell signs are missed or never surface. In these kinds of situations, the response to adverse effects comes down to four stages of care:

  • Diagnosis (identify the risks or potential risks that might occur)
  • Assessment (calculate the probability of adverse effects)
  • Prognosis (estimate the impact of adverse effects)
  • Management (control the risks and adverse effects)

There is a long list of reasons why managing risk is an essential tool within the healthcare industry. However, most everything falls under two major categories:

  • Provide the most positive outcome
  • Avoid medical malpractice

To better describe these items, it is necessary to delve deeper and to understand the implications for both patient and professional. To judge an outcome as positive isn’t black and white due to the fact that every person and every event is unique. However, an easily assessed situation might be a young child with a severe ear infection is given antibiotics and within a few days is back to his or her own self. Yet, a family that is taking care of end-of-life needs for one of its members isn’t expecting a full recovery but a management of pain and a dignified passing. The expectations and satisfaction of patients depends a great deal upon recognition to his or her circumstances.

On the other side of the coin lie the medical aspects of treatment. The majority of all healthcare professionals do not seek to cause harm or aggravate patients, but events occur that lend themselves to seeking out arbitration or a malpractice suit. Some of the events that lead down this sort of path include loss of patient’s life, mobility or ability, negligence, misdiagnosis, further injury or damage, or unconsented incursion of person or privacy.

As a matter of risk management, it is necessary to reduce malpractice episodes, decrease the avoidable adverse events, and keep record of patients and their satisfaction/dissatisfaction in each medical experience. In addition, a helpful tool is to know the statistics for surrounding facilities as this will give insight comparisons. This information, known as population health, helps to identify problematic issues within a community or region, which can be addressed more specifically and lead to more positive conclusions.

image courtesy of freedigitalphotos.net/imagerymajestic
image courtesy of freedigitalphotos.net/imagerymajestic

Another beneficial understanding for medical experts is to know factors that lead to heightened risk and can contribute to comorbidities, such as a patient’s risky behaviors, being young or elderly, family history, readmissions for previous ailments, or current prescriptions/medications.

To manage risk and truly to improve the quality of care received, one of the greatest tools the healthcare industry has at their disposal is information. Information in the form of individualized medical records for the patient, and gathered data from years of other patients’ experiences. Added together with the skilled hands and intelligence of doctors and other professionals will make for the best circumstantial outcomes.

Measuring Quality Improvement in Healthcare

At one point or another, all of us become uses of healthcare, whether it is a routines check-up, on slot from illness or injury. Without much thought or research, it is very easy to understand and explain the quality of care that you received; medical professionals assessed your situation, medicine or medical services are prescribed, and follow-up care is explained. We can see the results, sometimes immediate; other instances require time for internal healing. In worst-case scenarios, quality is measured by helping life to end with less distress.

photo courtesy of imagerymajestic/freedigitalphotos.net
photo courtesy of imagerymajestic/freedigitalphotos.net

The question then arises: Is quality in healthcare a black or white picture? The answer is unequivocally no. There are many straightforward and easily identifiable situations where quality in care is obvious. When recuperation is recognized or health is restored, and the patient is satisfied with the road to recovery or end result, quality can be quantified. However, is all care linked only with renewal and contentment?

From the point of view of those working within the healthcare system, there are many other facets that attribute to the improvement of quality and the ability to measure such advances. Without droning through a list of all possible departments and sectors along with the areas where improvements are sought, a more overall structure has been defined that can carry across many divisions. Three fields to measurement are:

  • Structural (equipment, facilities, etc.)
  • Processes (how the system functions)
  • Outcome (final product or result)

As helpful as this information can be, these are only the things to measure, but not the steps to take in order to produce results. Duke University Medical Center has formed a very organized illustration called the FADE Model of quality improvement. This outline identifies the steps that need to taken and how to explore the most effectual processes to improve standards. The FADE Model includes:

  • Focus – define/verify what needs to be improved
  • Analyze – collect and analyze data to find the root cause of problems and possible solutions
  • Develop – use analyzed data to develop a plan to:
    • improve
    • implement
    • communicate
    • measure or monitor
  • Execute – implement the development stage
  • Evaluate – install monitoring processes to validate improvements

Understanding where improvements need to be made and analyzing data are both very complicated steps. Most any business would consider a reduction in costs and errors to be stating the obvious. However, finding the inefficiencies may not be as obvious. Outside and unbiased recognition comes in the form of dedicated software, which eliminates guess work by taking collected data from as many sources as possible to produce a complete picture of procedures and events.

image courtesy of cooldesign/freedigitalphoto.net
image courtesy of cooldesign/freedigitalphoto.net

This picture defines the areas in need of improvement, and may also provide the answers to questions of root-causes. As much as we might like to believe that problems should be apparent, the truth is some improvements are complex with several outlying factors that contribute to the performance. With analytical data in hand, more quality information is present and the ability to attain better results is achievable.

Why We Need Healthcare Data Analysts

There will always be careers in health care for persons with a desire to help and care for others. Aside from abilities relative to basic patient care, anyone beginning a health care career now and in the future will need more than basic computer skills. The increasing use of technology in health data management adds a new dimension to the skill set required just a few decades ago.

Healthcare Data Analysts
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The next new high demand specialty in the health care field may be the Healthcare Data Analyst. As more information about patient care is entered into digital databases, more complex processes will be needed to retrieve the information and use it in ways to improve hospital efficiency and patient care.

Knowing how to query the database to pull out the relevant information and use it effectively will require skill with statistical analysis. This is in addition to knowing what relevant information to look for.

There are a number of software platforms available for health care institutions to choose from for their clinical data storage and retrieval. Designers of those systems are often physicians themselves, or have strong ties to the medical field. They often have a problem to solve, and data management is the fist step in finding a solution.

Armed with a repository full of data, hospital decision makers can direct resources to specific health treatments and programs that will have the greatest impact on their patient population.

A clinical analytics application with completely integrated data from a large health care enterprise can identify and reduce gaps in patient care and resource management. By “aggregating data from the health system’s Electronic Health Record (EHR) and other critical IT systems,” a skilled healthcare data analyst can tailor a query to evaluate readmission rates for instance. Then she can work with physicians and hospital staff to develop a strategy to lower the numbers. Along with saving the hospital valuable resources, insurance providers and the patients will also see savings.

Saving Money with Analytics
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Development of software that allows the patient to take a more active role in his own health care is gaining in popularity. An approach known as telemedicine is expected to save the health care industry and its clients up to six billion dollars per year.

With telemedicine, patients and physicians can communicate via telephone or video and can often resolve issues without needing an office visit. In addition, nurses and other hospital staff are often able to answer questions that don’t involve diagnosing conditions or prescribing medications.

Research is an area where electronic health records can have a tremendous impact. Studies can be designed to analyze disease trends within the hospital’s own patient population or on a global scale. There can be problems, though, when clinicians ask information technology workers for sets of data.

Health Care Data Analysts
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Applying clinical analytics to disordered data sets may be more time consuming than a busy physician would like to deal with. IT workers may not understand all the ramifications of the data they generate in response to requests from researchers. Healthcare data analysts can bridge many of these communications gaps by having a foot in each world.

Healthcare has a compelling need to use more information, better. Software engineers who can help medical enterprises achieve that goal will not lack for work for the foreseeable future.


Healthcare Data in Action

When you are making a big decision in your life, you usually don’t turn to the Magic 8 Ball or local newspaper’s horoscope predictions.  More often than not, research, other people’s experiences, and common available knowledge are gathered together and weighed against doubts or other insights.  This is not much different than the information that comes out when visiting a doctor or hospital.  The collected data and experience from years of research, trial and error, and patient’s encounters are weighed against current signs and symptoms.  This total gathering of healthcare data makes it possible to receive more precise treatment on an individual basis, eliminate unnecessary testing and wait times, and also prevent future diseases and outbreaks.

Healthcare data saves lives
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In this day and age, we are not satisfied with simply taking a pill for everything that ails us; we want and expect that cures are being pursued, and that our communities and nation are being protected from epidemics.  These leaps in expectations are warranted, however don’t come without years of exploration into healthcare data.  Found within all that data that has been generated, and is still being generated, are patterns that contain answers.

However, there are billions and billions of bytes of data already created, with more being added each moment.  In fact, the healthcare industry is one of the top producers of data each year, and thus serves to benefit the most from all that stockpiled information.  The thought that someone or a group of people could sit down and begin to decipher any significant patterns is impossible.  That is why the business of healthcare has turned to big data solutions.

When comparing all the information manufactured in the realm of healthcare, not many industries stack up to the complexity and privacy issues.  Not only do treating doctors and nurses need access, but billing departments and insurance representative and even government offices need some of the information stored within the data warehouses.  Thus the need for efficiency and effectual extraction of information is in high demand.

The gathering and storing of such significant and immense amount of information is not a project that is tackled with something as straightforward and simple as an Excel spreadsheet.  The need to have a model and progressive goals to eliminate errors, produce more meaningful outputs and ultimately to reduce expenses for everyone involved is crucial.  This healthcare analytics adoption model lays out the steps that lead down a path of better utilization of the collected healthcare data.  As the steps are perfected, and as technology also provides further aid to analyze stored information, goals for producing advances in treatment and reduction of costs will truly be met.

Data collection in healthcare
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As much as I am glad that my doctor doesn’t turn to a Magic 8 Ball to determine the best course of action with my healthcare, I see the benefits that combining the processing of such large amounts of health data and the analytical tools to understand and find significant information held within can open the doors to more cures, better care and an overall superior knowledge to such a vast and necessary industry.  And, having a plan of action will make it possible to reach the highest potential.

8 Levels of the Healthcare Analytics Adoption Model

Accountable Care Organizations (ACO’s) across the country are discovering every day just how useful and effective healthcare analytics can be. In today’s marketplace, data management is becoming an integral part of providing quality service to the general public.

According to an article published by Health Catalyst, there are 8 levels of analytics adoption in which an ACO can find itself. As you read through this summary, see if you can figure out how your own personal provider is doing in adopting this technology into their practice.

Level 0: Little to no analytics integration

What is an ACO?
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– This provider has a self-contained information system that doesn’t share with or draw from a larger pool of data
– Inconsistent and incomplete data sets cause confusion and wasted time and resources
– Reporting is labor-intensive and less helpful
– There is virtually no data governance

Level 1: Integrating the Enterprise Data Warehouse (EDW)
– This provider has begun to use a data warehouse to collect data on HIMSS EMR Stage 3 data, the revenue cycle, financial information, supply chains, and the patient experience
– There is a searchable metadata repository that can be accessed across the enterprise
– The EDW is updated within one month of source system changes
– The CIO of the organization receives reports from the EDW

Level 2: Standardized Vocabulary & Patient Registries
– Various, disparate source system content is identified and standardized in the EDW
– Local standards define the naming, definition and types of data
– Patient registries are defined by ICD billing data
– The governance of data forms around the definition and evolution of patient registries

Level 3: Automated Internal Reporting for consistent and efficient production
– Analytics are consistent and efficient, and are focused on supporting basic management and operation of the ACO
– KPI’s are accessible from the executive level to front-line management
– Data analysts are regularly involved in order to collaborate and guide the EDW
– The governance of data is being managed in a way to steer the ACO towards constant improvement

Level 4: External reporting integration
– Analytics are focused on consistency, efficient reporting and accreditation requirements, payer incentives and specialty society databases
– Industry-standard vocabularies are adhered to
– Clinical data content is searchable with simple key word targeting
– Data governance is centralized  for review and approval of externally released data

Level 5: Reduction of waste and care variability
– Analytics are focused on measuring clinical best practices, waste reduction, and eliminating variability
– Data is used to support teams focusing on improving the health of patient populations, not just individuals
– Population-based analytics are implemented in order to improve individual-level care
– Teams are in place that continuously and regularly look for ways to improve care quality while reducing risks and costs
– Data is improved by incorporating information from labs, pharmacies and clinical observations
– Content from the EDW is organized into evidence-based and standardized data streams that simultaneously manage clinical and cost data associated with patient registries
– Insurance claims and HIE data feeds are included in data content
– EDW updates happen within one week of source system changes

health analytics and data management
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Level 6: Population health management
– The ACO shares in the financial risks as well as the rewards tied to clinical outcomes
– Acute care cases are managed under bundled payments at a level of 50% or higher
– Data content is expanded to incorporate bedside devices, home monitoring data, external pharmacies and activity based costs
– Data governance is factored into the metrics of quality-based compensation plans for clinicians and executives
– EDW updates happen within one day of source system changes
– C-level executives accountable for balancing cost of care with quality of care receive EDW reports

Level 7: Risk prevention and predictive analysis
– Diagnosis-based, fixed-fee per capita reimbursement models are addressed by the analytic motives
– Predictive modeling, forecasting and risk stratification are used to support outreach, triage, escalation and referrals, expanding focus from management of cases to collaboration with clinician and payer partners for management of episodes of care
– Risks and rewards are shared through collaboration between physicians, hospitals, employers, payers, and members/patients
– Patients who are unwilling or unable to participate in care protocols are flagged in the registries
– Data is expanded to incorporate home monitoring data, long term facility care data, and protocol-specific patient reported outcomes
– EDW updates occur within one hour of source system changes

Level 8: Personalized medicine & prescriptive analysis
– Data management is used to influence wellness management, physical and behavioral health and mass customization of care
– Analytics are expanded to include NLP of text, prescriptive analytics, and intervention support
– Patient-specific outcomes are improved at the point of care, based upon population outcomes
– Data content is expanded to incorporate biometric data, genomic data and familial data
– Updates in the EDW occur within a few minutes of changes in the source systems

What type of provider would you prefer? Healthcare analytics can transform our current model into a data-driven process, which serves the population as a whole as well as individuals. As more and more ACO’s integrate the EDW into their processes, the better the service will be across the spectrum of providers. As consumers, we can aid in the process by learning about the process and participating in the discussion.


Application of Business Healthcare Intelligence

Business intelligence (BI) is a general term used across many different industries of businesses that helps to explain utilization of stored data.  A more specific definition is the extracting, identifying and analyzing of computerized business data to provide current and predictive view of operations.

When integrating BI into the demands of healthcare the possibilities are almost limitless.  However, the need for a data warehouse coupled with BI is integral to uncovering the potential of the stored data.  How these work together is that the data warehouse is the efficient and effective way to store the collected information, which can then be accessed by all the necessary personnel.

The BI tools look at all that data and are able to dive down to find problem or red-flagged areas that should be looked over. Imagine sitting in a very important financial meeting where everyone has their own statistical data to backup their opinion for changes.  One department shows there is a surplus and demands more spending power, but according to your numbers, that same department is showing a significant loss and should be cutting back severely.  So, who is right?  Both parties have evidence that supports their point of view, and both consider the other to be incorrect.

Situations like this happen all too often because two or more groups are extracting their numbers differently, possibly from different sources, and basing decisions with far reaching consequences on that data.  If everyone was on the same page, with the same numbers, the same conclusions and all of it being accurate, more appropriate and effectual decisions could be made.

This is the importance of the data warehouse: everyone is pulling from the same information, and interpreting it the same way.  Thus better assessments can be made with everyone in agreement. Another typical situation that comes up can be that everyone sees that a department is losing money, everyone has settled on that fact, but the no one can explain how, where or why it is happening.  Sort of like looking at an Excel worksheet with all the numbers plugged in, the totals summed and yet no better understand of what is going on than before you looked at it.

How can you make changes if you don’t know where to start?  What if the changes you believe you should make don’t aid in the health of the company? All the stored data is in one location, the necessary people can access it to help draw current and future decisions, but what does this do if there is no analysis tool that makes meaningful use and presentable layouts that let you know what all the numbers really mean?

BI might be divided up just a little further to seen for the ultimate usability and also the end strategy that you want to meet.  You can have all the graphs, reports and summaries you can handle, but if you don’t know what your end-game is, than you are left with a very expensive data system. Obviously, more often than not, cutting costs and inefficiencies is at the top of everyone’s list.  There is nothing wrong with that in the field of healthcare, and in most cases, this would help with patient safety, treatment and overall cost.

To be more specific though: what if you wanted to cut down on the number of habitual patients seeking pain medicine.  This would mean understanding the fundamentals that go into a patient coming to a hospital or clinic on a regular basis.  This isn’t found within the vast array of numbers, but is found within notations and other information that can be housed in a data warehouse.  By having a strategy, you can see where you are headed and why. There are other pitfalls to be aware of that can bring down any giant of the business world.

In one word, let me say Segway.  Just because you build it, you hype it, you cover it in mystery and you launch to a national audience doesn’t mean that everyone will flock to buy it.  The same goes with business intelligence: just because you install it, instruct everyone and toot your own horn doesn’t mean everybody will support the decision or utilize it to the fullest potential.  Change is required and you need to understand that all your problems won’t be solved just because you instituted new software.

Additionally, no matter how much of a perfect fit BI software may be for you, if data quality isn’t an enforced concept for everyone involved, the old adage, “GIGO (garbage in, garbage out)” will always ring true.  A simple example of this could be if a health professional consistently entered a wrong spelling for medicine administered to patients, the information wouldn’t be pulled out for statistical reporting or other pertinent accounting.  This simple action could lead to eventually falling behind in having that medicine purchased or slightly skewing expenditures.  Without consistent checks to make sure that all information being entered is reliable, the conclusions made could be biased in one direction or another, but never completely accurate.

Healthcare business intelligence may be of the most complex of any known industry, but also may yield more long-lasting answers no matter your part in the healthcare system.  However, be ready to know the inner workings of the business and the strategies that will help to accomplish whatever goals may be requested or required of you.