In a world where new terminology emerges every day to describe some new technology on the market, it is almost impossible to grasp a full understanding of what a name or title represents. Luckily, something as straightforward as Physician Engagement is self-explanatory. However, applying the principle to daily practice within a healthcare organization isn’t as simple, in fact, it is about as easy to engage physicians in some companies as it is to not have a teenager roll their eyes during a serious conversation.

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No healthcare establishment can say they have reached a pinnacle of perfection, where clinical quality is improved, and clinical costs are under control. Physicians are at the forefront of the decision-making processes as a natural consequence to their position. When quality changes are either required or requested, one of the most important steps should be to make the physicians a part of the development and implementation. Fostering a sense of ownership not only builds trust between administrators and physicians, but also creates a partnership where everyone is invested. Back and forth discussions are seen as constructive, and allow for strategizing and prioritization. As long as this tool is utilized early in the process, it can effectually motivate and encourage.

The thought of being able to personally champion quality improvement ideas to each physician would be ideal, it is also impossible. This is when delegation can have a farther reach. Finding leaders among leadership helps to promote a trickle-down effect. With the endorsement of changes coming down from heads of department or other leader, who are seen more as colleagues, and questions being answered on a more personal level, the full weight of carrying a program doesn’t fall on one small group of individuals. Instead, largely organized groups have a spokesman who can convey information in both directions. Most people are going to follow a leader they know and can interact with, rather than a perceived out-of-touch bureaucrat.

Most established organizations are made up of many different departments, specialties, locations and other diversities that makes implementation of any quality improvements an enormous task. As the old saying goes: How do you eat an elephant? One bite at a time. This is also applicable to carrying out changes: Choose one are of focus. Not only do the modifications happen in a more manageable fashion, but this also allows for providing proof to other departments as to the validity of the changes.

To perpetuate orderliness, teams and leaders must be structured. This doesn’t mean everyone’s roles are reorganized and redefined, however, the necessity to have designated experts to whom a team or department can turn will alleviate errant projects. More importantly, it will breed commitment and oversight to drive and motivate physicians to stay the course. To a small extent, this is related to having a spokesman who is able to communicate for a group to the administrators.

Any great plan is only as good as its results. Thus, putting the plan into action is also a key ingredient to implementation and reaching a goal. Nevertheless, it is easy to become discouraged when the plan loses momentum. Many people take this as a sign to give up and move on to something else, when it is the opposite that is true; by sticking to the plan and trudging through the challenges of quality improvements, you are showing your physicians that you have faith in the plan and that it is worth any bumps in the road. You are also demonstrating that a plan may need outside input and insight that may only be available through the physicians that know the underbelly of the system. Working together to fine-tune a plan will reinstill enthusiasm for the end results.

Improvements, no matter what kind, are measurable by some comparison. Physicians, like any true scientist, are curious and methodical to their core. As such, they want to see that improvements are happening, whether it be in overall performance, reduction in errors and waste, or increase to financial achievements. Simply saying that everything is getting better is not sufficient. Data-driven evidence communicates where changes have occurred, if they are positive or negative, and if goals are being met. Evidence of this sort doesn’t come without having collected, grouped and analyzed data. Many healthcare organization utilize enterprise data warehouses (EDW) to store data in a unified database setup, that allows access company-wide, and can be analyzed for planning purposes. When you are able to create reports that show progress and improvement, physicians are more likely to remain steadfast.

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It almost goes without saying that none of really like change, especially changes to routines that may be very well established. Change can be a positive thing, and prove to be helpful in many respects. You must be an advocate for change at all times. When you don’t fight the battles, no matter how small, resistance and outright resentment can creep in, and all the work for physicians to actually be engaged will have been for nothing. It may be as simple as walking through the above steps again, or just letting someone vent frustrations for a while.

Having everybody on the same ship, headed the same direction, with the same intent will go a long way to moving forward more quickly. Even though this is more a perfect scenario situation, there is nothing to say that you can’t help everyone to make the move forward. Your physicians are a strong driving force within your organization, and they need to be utilized to their fullest potential.

As businesses and industries grow at almost record pace, it is not hard to see how anyone of everyone isn’t utilizing any technology to understand what makes their business tick. The inner workings of any good organization must be realized at all levels to enable improvements, uncover waste and make better decisions for forward progress. These aspects are only discovered by utilizing tools that expose patterns and trends not visibly recognized with human efforts alone. One of the tools that provides revelation within the gathered information is data mining.

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Data mining is somewhat self-defining, but to bring us onto the same page, it is described in most IT realms as the process of finding useful relationships in the midst of large volumes of data. These relations are found by digging down into complex data, with the help of analytics, in order to show correlations between data sets. The reason that this isn’t considered humanly possible is because of the vast amounts of data that would have to be sifted through, understanding diverse associations and to do this in a timely fashion.

Many business types rely upon revealed trends as a means of providing better services and products, while controlling costs. This is no different within the healthcare industry; providing better care and managing expenses for all involved is not only advantageous, but is also part of the regulations passed down from the federal government. This doesn’t simply happen because it is willed into place or by finding less expensive materials and machinery to work with. Understanding where inefficiencies are occurring will benefit patient and professional.

If you are wondering where all the data is coming from that enables the experts to offer improved care, you don’t have to look very far due to the fact that we are all contributing to the greater picture. Each time that we visit a healthcare provider, whether it be for illness, accident or preventative care, information is recorded in our electronic health records (EHR), which allows our information to be shared across different providers to facilitate more accurate, personal care, but also to provide information within our specific communities or populations.

A trend that already being pushed upon those within healthcare is the change from a fee-for-service based pay to a value-based pay. This means that doctors are moving away from billing for every service they provide to proving that performance for reimbursement. This puts more risk for treatment in the professional’s court, but also demands more efficient treatment with less waste, such as duplicate testing, unnecessary testing, and unproductive appointments.

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In lockstep with the movement away from fee-for-service based payments, comes better decision-making requirements. Data-driven decisions are much more effectual and long-term compared to other less reliable methods of rendering decisions. Crystal Run Healthcare of New York has implemented better practice determinations with how their organization moves forward. With data mining tools and the ability to evaluate patient trends, understand where future needs might be, explore internal and external risks, and other general processes, they are able to identify the current and future needs for patients and their organization as a whole.

Data mining truly is a self-definable term that holds a wealth of conclusions that not only benefit those working inside a healthcare organization, but also those that seek out and rely upon assistance that healthcare professional offer. Although the immediate effects may not blatantly obvious every time we are in a doctor’s office or hospital, the truth is the products received as a result of data mining are fundamental and foundational, thus are not always apparent. Sometimes, it is these sorts of developments that make it easier to put our faith and health into a doctor’s hands.

In the healthcare industry, demands for better services at lower costs are at the forefront of many conversations both within and without the walls. Many of the mandates that government sets forth also stipulate this. How are organizations supposed to make changes to a business that is dealing with accidents and ailments that have their own unique circumstances? There is a particular tool that these groups now have at their disposal, which provides a better understanding of the community where they are located and the needs of the people found within; this is Population Health Management software. Healthcare providers can make data-driven decisions, plan for the future and improve care all while containing costs.

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Population Health Management is defined as the outcomes and distribution of healthcare within a specified group. These groups may be as large as a nation, or a particular community; they may be more exact by selecting persons with disabilities or financial difficulties. However, when a healthcare organization is providing services in a defined area, they want to know the types of services that are most needed, where are the best locations for hospitals and clinics to serve the most number of patients, and where specialty treatments physicians would most conveniently located.

The task of tracking down all this kind of information, creating a report that details the population that is being helped, and doing it in a timely manner is almost impossible. Educated guesses are still just based on making a decision without all the information in hand. This is where and why Population Health Management (PHM) software is crucial in changing decisions from guesses to fact-based and data-driven.

We all participate in adding information to healthcare data systems every time we visit the doctor or end up in the hospital; statistics and notes go into our electronic health record (EHR), which enables the treating expert to know our health history and to add to it. This health information is not only collected for our own personal benefit, but is pulled out and used to understand everyone around us. In other words, when you get the flu and end up in the doctor’s office, information is saved and analytics applied to bring to light health patterns in your area. With a picture of patterns that have occurred over years, and your input, it is easy for decision makers within a healthcare organization to predict when cold and flu season will probably start next year. This is a small example, but the ability to prepare, yet not over prepare, aids in the effort to provide better care and not have waste or overages on the financial side.

The predictive and preparative knowledge gained by understanding and applying population health management strategies also has an effect on managing patients’ risks and reducing negative consequences. As seen in this Becker’s Hospital Review article, PHM turns previously time consuming tasks into much more time sensitive reports and data, which translate directly into effective and efficient care.

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PHM isn’t simply loaded onto a bunch of computers and it is ready to use. There is a lot of time, changes and other investments that are required to implement the system. With as much data that is being created and saved, the need for an Enterprise Data Warehouse (EDW) is a must. Along with knowing that implementation isn’t a series of single projects that once completed provide a new, self-contained system. Part of this is due to the fact that every organization has different requirements and unique obligations that must be met. These must be understood so as to integrate them into the system as a whole, and ultimately reach a point where efficiencies are more the norm.

Truly, it is quite amazing that each one of us is contributing to a huge picture that improves health services down the road. We all live as part of a community and many of the regularities found within communities are repeated. These repeats of patterns and the understanding of how to prevent, prepare and predict health issues is exactly what Population Health Management is all about.

For anyone who doesn’t know what big data is, you’d better get caught up quickly, because it is the direction many industries and companies within large industries are headed. A basic definition, as stated in a Forbes articles defines big data as: “…a collection of data from traditional and digital sources inside and outside [a] company that represents a source for ongoing discovery and analysis.” So, how do mainstream industries use big data compared to how the healthcare industry uses it?

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Big data is the means by which business practices can truly measure what is happening at every level and department in the organization. The ability to measure provides a fundamental understanding, which leads to better and more accurate decisions. Within the retail market, this kind of familiarity leads to enhanced responses to customers’ wants and needs in a timelier manner than traditionally discovered with analytics.

This is much the same when looking at big data in healthcare: measuring the positive results with patients, working to raise patient satisfaction levels, and meeting/exceeding resolutions to departmental budget shortcomings become transparent. When you have knowledge about what needs to change, you can thus make the changes necessary, and provide a better care environment for patients.

Many companies seek to understand actions their customers take, especially while on the internet. This does not simply tie a customer to his or her purchases, but also includes other items they clicked on, the different pages visited on the website and promotions or reviews that may have influenced their navigations throughout. With this data and the firm understanding of what the customers may be looking for, a company can then offer advertising directed specifically for each customer. Much of this individualized attention happens in real-time while the consumer is still online.

The concept of real-time assessment is happening more and more in a healthcare situation: doctors have access to a patient’s electronic health record (EHR), which provides a comprehensive explanation as to what the patient has been through. Being able to coordinate current care with previous events will better ensure that adverse events are avoided. Customer actions aren’t followed by clicks, but by visits within a healthcare organization, and include all medical notations. Doctors are then able to present the most advantageous approach to helping the patient.

Technology is moving ahead at breakneck speed for every industry. Data systems and analytics that were sufficient and may have been considered cutting edge five years ago are now far from adequate for the amount of data being collected or the demand for that data to be utilized to promote customer experiences. The need to have ample room to store and access the data means moving up to a database or in many cases a data warehouse. Additionally, software to manage the data is part of the package required to handle all the information that is being saved.

One of the largest industries for data production is healthcare. We are all contributing to the growing knowledge base within a healthcare system, and that information is substantial. When you think about the different kinds of data that is being gathered, you might begin to understand the sheer depth of fact and images that stored. Most of the data comes in three different forms:

  • Billing and clinical transactions
  • Digital capture of diagnostic images
  • Documentation and notations
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Obviously, the type of data being stored and accessed is quite different between most businesses and a healthcare organization. However, the amount of information being generated can be considered comparable to these other fields and in some respects must be managed much more securely due to the fact that personal, medical and financial information is being cached.

Although healthcare requires a different type of big data system, the fact that big data is a key component to helping care specialists improve medical treatment and to do so in a timelier and more efficient manner shows that both business and healthcare benefit from rendered information uncovered. Big data is a broad-spectrum word that has many implications in any field to which it is applied.

This may have come out of left field and not seem like the most conventional partnering in the healthcare industry, but this may prove to be the new model for making healthcare a safer and more efficient industry.

If you haven’t heard, MedCity News recently announced the combining of technologies with the partnering of Allina Health and Health Catalyst. The Minnesota-based Allina Health has more than 90 clinics and 12 hospitals that will benefit from the one of the highest rated data warehousing and analytics companies in the realm of healthcare software.

What makes this collaboration unique and thus newsworthy is the fact that this is a shared-risk deal with Allina sending its data warehousing, clinical analytics and specific personnel to Health Catalyst. Then Health Catalyst must prove measurable and significant reductions to inefficiencies and manage both financial and patient risk levels, which translates to money saved for patient and organization and improved patient satisfaction with overall care.

This ten-year contract will enable Allina to become a front-runner to a new model at a time when fee-for-services payments with insurance companies are going away, and the need to locate wasteful spending and practices delivers a more robust and enhanced system of business. If Health Catalyst doesn’t meet data-driven improvements, they risk upwards of 20 percent of their fees that they could collect. Thus achieving specified objectives will demonstrate their ability to handle this new structure to a business relationship.

Have you ever had to answer the question: On a scale of one to ten, what is your pain level? Maybe at admission to the hospital or new patient paperwork they ask what medications and current/prior health issues you’ve had. There is a lot of insight that can be gleaned from just those two groupings of questions. This insight, along with other pertinent information can help health professionals to better diagnose, assess and treat. What you might not know is that this practice is called risk stratification.

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To understand better how risk can be lessened or controlled in a health care environment, each patient must be evaluated to see what is happening. This occurs whether the visit is to a doctor’s office, clinic or emergency room. The immediate pressure to gauge a situation may not be as pressing outside of the emergency room, but stratifying the risk to each patient aids in the overall healthcare needs, services and coordination needed both in the short- and long-term circumstances. So, how do doctors go about assessing the risk a patient is under?

Identifying risk levels comes down to knowledge, history and communication. Knowledge is the professional understanding of the human body and how it both functions and can be fixed/healed. The history is our own point of view of what has happened to us, whether it be passing events or ongoing issues. What I mean by a point of view is that when prior diagnoses and treatments have transpired, if we remember the sequence of even differently or erroneously, this may play a part in future health management. This may also be the case when recalling family history of disease; if we misunderstood what someone suffer with or never knew the medical account.

Communication may be one of the most important steps or tools that is used to realize what is happening. Both the doctor and patient need to be willing to listen, disclose details and follow up with any additional questions as required for full perspective. When one or both parties miss out on vital components within a conversation, the likelihood of mistakes escalates dramatically. For instance, when a patient hasn’t divulged all current symptoms, critical elements to a quick conclusion may be passed over and the length of treatment greatly extended.

Once all information is collected, and a specific assessment can be made on the patient, this is where a better understanding of risk stratification comes into play. Sensitivity to factors that affect the overall risk level that a patient is categorized into includes:

  • comorbidities
  • mental health
  • poverty
  • social changes
  • inability to self-manage
  • likelihood of readmission
  • tendency to frequently seek out medical support

The higher the risk level, the more likely that patient requires personalized managed with his or her care so as to prevent adverse outcomes. To explain further, many individuals have a tendency to become overwhelmed with changes to lifestyles and routines, and as such either purposefully or unknowingly mismanage his or her own care. The need to monitor, regulate and follow up on care must be seen as essential. Within the confines of a hospital, these steps are supervised and recorded. However, when home care is called for, patients and procedures can fall through the cracks. It may be as simple as forgetting to take prescribed medicine at specified times, or as disastrous as introducing unsterile equipment to a susceptible patient.

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By managing the amount of risk patients are subjected to, and allocating appropriate resources when they are needed and to whom, the probability of negative outcomes is lessened. This management can be proactive, reactive or a combination of both. A proactive approach is to get ahead and prevent problems from aggravating a situation, while a reactive approach is situationally driven and require putting finger in the dike instead of preventing the leaks in the first place. However, it is impossible to prevent incidents from happening, especially when dealing with a high-risk patient. Thus, being able to prevent the manifestation of some symptoms while managing others as they surface is critical.

As much as we may not want to correlate managing the cost of healthcare and providing improved care, it is a very real subject within risk management. In a day and age of lowering overall costs yet increased expectations of positive results and technological advances, the resulting fall out can include malpractice lawsuits and increased cost to insurance. When proactive and even predictive methods are implemented, the ability to control risks to patients and financial losses broadly speaks to the need of risk stratification techniques being openly utilized.

It goes without saying that when you make certain purchases or research particular products the reputation and quality of such are factored into your decision. Yet, within the realm of healthcare, we take for granted that our doctor or local hospital meet and exceed quality standards around the nation. Unfortunately, this may not be the case, but not necessarily because of the professionals within the businesses. Quality within a service industry may very well come down to the overall standards established as an individual entity.

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By no means does this imply that any healthcare professional seek to have a lesser model to work towards or endanger patient health and privacy, yet the quality controls practiced within the organization may unintentionally lead to this result. An overall picture of the positives and negatives may only be painted when there is sufficient data collected, and compiled so as to reveal reality without biases.

The collection and compilation of information seems like it should be straightforward, especially in a world amassed with computer records. An unfortunate characteristic within the healthcare industry is that software programs dedicated to these dynamic needs has not been at the forefront of progress as it has been within other businesses and industries. This game of catch-up has many players and is providing a wide variety of programs, which take in all the necessary details and can generate an image, whether literal or by means of reports that indicates many different answers to questions of how to run a business better. Some of these more clarified images include:

• Inefficiencies
• Loss in timely actions
• Errors in diagnoses and/or treatments
• Poor performance at any level or department
• Need for continuity of further services
• Increase costs to facility due to duplications or lost information

Though this list could be much greater and finely detailed, the general idea that many areas of interest are at stake for losses of time and money. Thus, there is a basis for making changes to combat problematic situations and to be truly productive. Implementing aspects such as data warehousing and identifying process improvement will begin the fine-tuning that will lead to true, provable change.

Obviously, this doesn’t happen overnight, nor does it come about without challenges. Some obstacles that can be predicted before any implementation has occurred include:

• Resistance to change as a general attribute
• Changes require time to implement and to learn
• Processes can be initially slower
• Concerns for privacy may be expressed

However, these may not be all the struggles that are revealed. Other problems may include:

• Easier detection of poor performance
• Individuals who struggle with new technology
• Change of duties or responsibilities
• Changes in business emphases
• Resistance from outside sources (e.g. insurance providers)
• In significant changes, patient feedback may be affected

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In a day and age of technological advances and greater need for analytics within healthcare data, the improvements that have been made and are continuing to be made are astounding. To manage or control the quality of care received, it is necessary to employ unbiased knowledge as a means to a better end. This end is a better overall treatment for patients at a lower cost for all involved. Quality control in healthcare equals enhanced medical healing.

To understand what business intelligence (BI) is, we should start by choosing an industry first, and and then dig into application. defines BI as an umbrella term that includes the applications, infrastructure and tools, and best practices that enable access to and analysis of information to improve and optimize decisions and performance.

Healthcare Business Intelligence

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BI isn’t a stand-alone concept or practice, especially when employed within the healthcare industry.  There are three main components that when utilized alongside BI to provide the most effectual data.  The first component is the data storage technology, or the enterprise data warehouse (EDW).  This is a system that converts stored data, past or present, into meaningful or useful information enabling better decision making.

Once all the data is organized in a manner that can be extracted, the second component is called upon.  The need to change the aggregated details into a visual format is known as data visualization and is one of the more powerful tools available.  Most of us can’t look at a spreadsheet with its rows and columns of information and truly make sense of it all.  However, when translated into a graph, chart or diagram, the comparisons become easy to digest and diagnose.  A visual analysis allows decision makers to begin to answer questions such as:

  • What happened?
  • How often did it happen?
  • What is the problem?
  • What do I need to do to fix the problem?

Now that a picture has been created regarding what has already occurred, the third component is then put into action.  Being able to drill down and apply discovery methods is where information about the future is contained.  Many refer to this as business analytics, which is the predictive aspect to intelligence.  When you are able to use the answers from the questions from the past to find out what the future might hold, you are moving into a realm of better business making decisions.  Answering questions along the lines of:

  • Why is this happening?
  • What happens if we keep moving in the same direction as a company?
  • What are the possible outcomes and financial benefits?

Many healthcare professionals will draw upon dashboards, which provide a high-level view of the organization.  This other visual component is part of the business analytics side of the equation because it can supply answers to the any different “why” questions, and thus leads to projections in potential understanding of the business as a whole.

IT in the Business of Healthcare

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There is a natural progression that strengthens the course of healthcare, both within and outside the walls of a doctor’s office, clinic or hospital.  When you know what has happened, you can create reports.  When you know what is happening right now, you can monitor and make real-time changes and decisions.  When you know why something has happened, you can analyze it for better awareness.  And, when you know what is possible in the future, you can predict when time, money and resources should be accurately dedicated.  Business Intelligence is the process that makes it all possible.

Have you ever put off buying something you knew you needed, and you had every excuse in the book?  They were really good excuses, but there usually comes a point where either out of necessity or emergency the purchase is made, and then you wonder why you didn’t do it sooner.  This seems to be the case of investing in and implementing healthcare information systems (IS) into clinics and hospitals.  Many of the excuses given by practitioners and other health professionals include a financial burden, the old ways still work well, changes – especially this large – can take up too much time and resources, and the flat out rejection of new technology.

Managing Healthcare Information

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Whether it is realized by decision makers or not, a functional information system can be the tool that should be purchased sooner rather than later, and it shouldn’t be entered into lightly.  The goals and focus of your practice have to be understood so as to utilize any software to its fullest potential.  Just because there are the best of intentions for better business actions does not mean that installing and employing an IS will smooth sailing.  In fact, there are many challenges that should be addressed and not overlooked or swept under the rug.  The adaptation of new technology isn’t an all or none scenario, but has levels of usage.  For example, a physician may prefer not to carry around a tablet to access medical research and records, not because he or she is not comfortable with the tablet, but the tablet may be cumbersome or be a distraction when meeting with a patient.  However, the nursing staff may find that a tablet is very convenient and aids in time management.

Some practitioners are accustomed to turning to journals and published work to find new guidelines and medical results; moving to an Internet-based search may be too much out of the norm.  When you take into consideration that many of the medical journals have decades of study and investigation behind the findings.  Changing an age-old, accepted method of progression for one that is much more instantaneous can prove to be a big hurdle to jump.

Managing Healthcare Information

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Another barrier that can impede implementation is the fear of litigation.  Unfortunately, our society is so quick to skip any sort of negotiations and run to a lawyer when medical mistakes occur.  So, the tried and tested ways of past are much easier to rely on over those that are technology-based.

One of the modern moves that medicine is making is towards personalized medicine.  This is the use of a patient’s physiological makeup and medical history to provide a more effective and exacting treatment.  The direct correlation between having up-to-the-minute information and analytical capability provided within an IS is crucial.  This is also the case when moving to a more evidence based medicine (EBM) means of treatment.  EBM relies finding links between common treatments  and large scale proven treatments.  The commonality is sometimes only found with the help of software that can recognize patterns within vast numbers of cases.

Modern Healthcare Information Systems

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Having the technology of an IS has been shown to relate directly with the rise in quality of care provided and patient satisfaction.  The patient doesn’t need to see that a medical professional is carrying around a tablet or some other piece of technology, but as practitioners are able to more specifically provide needed care, avoid errors or prolong hospital stays, everyone’s best interests are accounted for: patient is helped along quicker and healthcare professionals reduce expenses.  Although adaptation isn’t a one size fits all case, the steps taken to implement and utilize a healthcare information system will prove to be beneficial for all involved.

A very basic definition of data mining is the searching through large amounts of computerized data to find useful trends or patterns.  At one point this might have been plotted on a simple Excel sheet or graph, but in the realm of today’s standards, the amount of data and nuances involved far exceed minimal plotting.  Especially in an industry as large and data-rich as healthcare, the discovery of patterns requires a lot more processing power.

Clinical analytics means examining vast amounts of information in order to uncover recurring trends, which in turn produce predictive or future forecast data.  Just as when watching a weather forecast, the computers that make the predictions for five or ten days out take into account the patterns in the highs and lows currently happening, and then find previous models that held similar flows and calculates what should happen.  Though this is quite simplified, this example shows the value of data mining from years of previously stored and analyzed information.

clinical analytics and data management

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Being able to predict the future of patients and their healthcare opens the doors to being able to identify and deal with high-risk patients more appropriately, rather than continually admitting them into costly hospital beds.  Also, being able to ascertain the patients with severe or chronic illnesses who might be susceptible to readmissions can be headed off with other preventative measures instead of another hospital stay.  Armed with the ability to distinguish when patients fall into certain patterns, doctors and other health professionals would be able to manage staff, space, resources and the overall costs expended due to effective and efficient planning.

Healthcare and the many different fields of medicine are one of the larger industries creating a majority of data generated each day.  This data is compiled together and shared as part of the information exchange that takes into account demographics, such as age, gender and zip code, along with patient’s needs, and plots out general and diverse patterns, especially within communities or populations.  These patterns are then applied by professionals when treatment is sought in order to categorize the patient into a more personalized course of healing.

Data mining in healthcare doesn’t benefit just one group of people, but works to help everyone that is involved at the many different levels of treatments; doctors and other staff have more information at their fingertips to correctly and quickly diagnose a patient.  The patients may not be subjected to unnecessary testing or periods of unknowing because of the actionable data.  Hospitals can run more efficiently due to the fine-tuned productivity found within the patterns.  Even the prevention of fraud and fraudulent behavior can be identified from previously recognized trends.

clinical data management and healthcare analytics

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The most unfortunate aspect in all of this is the healthcare industry is playing a game of catch up within the realm of data mining.  Most other businesses and industries have fewer points for which they are trying to model.  The sheer complexity of data that is kept in healthcare has been a hindrance to making or finding the right software to implement.  Additionally, the privacy that needs to be upheld on medical files has slowed the adaptation of data mining technology.  But, persistence and a better working knowledge of restrictions and requirements that needed to be respected, a breakthrough for the healthcare industry.

The basic definition of data mining helps to describe the minimal possibilities for any business that utilizes it.  However, the enormous possibilities available when implemented to its fullest potential, there is almost limitless growth.  This isn’t just within healthcare but for anyone, yet healthcare may be the spheres in which data mining might have the most significant ability.  At one time or another all of us will be a patient, whether for that yearly physical or for something much more dire.  If you are like me, I want all those who are helping me to have as much knowledge available to them, and if that includes previous patterns determined from data collected over many years and patients, I am happy to a beneficiary.  Even if we think we are absolutely unique, there are some features that make us ordinary under the hood (so to speak).