Saturday, August 17, 2013

Written Assignment 8: Data Mining


 

 

 

 

 

 

Written Assignment 8: Data Mining

Alanna M. Schauer

Thomas Edison State College

 

 

 

 

 

 

 

 


Written Assignment 8: Data Mining

Information Technology Manager Interview

The writer interviewed the Clinical Application Manager called B.K. to gather the information needed to answer the following questions. The author was surprised to receive the answers given because the hospital has such foresight when it comes to Information technology and yet this was not the case as it pertained to data mining

 AMS- "What software are we currently using for data mining?

B.K. - "We do not have great data mining tools established currently but we are working on it. We are rolling out some new projects that will address the data mining issue but we are at the beginning stages. We are focusing on the Quality Core Measures initiatives and utilizing software called Focus by SpectraMD USA, Inc. (Are you maximizing, 2012). This program has dashboards that allow monitoring of the information and the ability to see trending. This software focuses on the value based purchasing initiatives and allows you to drill down to specific data points to see where there is missing information. This allows the hospital to increase performance across the continuum of care and gain financial incentives."

 AMS- "Who is currently using the Focus program?"

 B.K. -"We are really targeting the quality issues and CHF readmissions so the quality assurance department is the primary users of this new software program. We will build this over our Siemens Decision Support System (DSS). K.A. the VP of Quality Assurance is the person who really decides what data targets we need to focus on. Our Congestive Heart Failure (CHF) readmission rates are high, higher than the administration wants and we need to work fast to reduce them."

AMS- "What are they trying to predict with the collection of the data; the CHF values?"

B. K. -"The Focus program uses predictive and analytic statistical techniques as a primary tool for data mining core measure information. When they created this program, they created a panel of cardiologists for their input so they could capture the necessary data points for a successful program. For example, with the CHF measure, the ejection fraction is a good indicator of cardiac muscle function but they need a clean data point. When the echocardiogram calculates the ejection fraction, there is one value.  In contrast, when the cardiologists over read the echocardiogram they often report a percentage of forty-fifty percent and that is not a clean data point. Cores measure reporting can cause significant financial burdens on the organization if handled incorrectly. CHF is one of the data mining concerns but so are myocardial infarction (MI), pneumonia, VTE, and stroke. There is also the idea of providing quality patient care which makes this program vital to the viability of the organization."

            "We are trying to predict or evaluate where we are the weakest so an action plan can be instituted and our values can be superior. We are attempting to preemptively determine where to focus our efforts for positive quality outcomes. "

 AMS- "What data are they using in this data mining program?"

B.K. - With CHF, we are looking at the length of stay per admission, the ejection fraction of the echocardiogram, the comorbidities that exist for the patient, like diabetes or hypertension, the B-type Natriuretic Peptide (BNP) blood test value, to mention a few. With the stroke patient, we are also looking for the length of time for CAT scan or door- to CT scan time and the thirty-minute window for tissue plasminogen activase (TPA) administration if warranted.

AMS-"What do you see as the advantages and disadvantages of the institution's approach

 to data mining?"

B.K. - "We are at an important crossroad at this institution because we have to make a decision to adopt a hybrid approach to data mining or wait and try to implement a global system using Siemens. Siemens DSS is moving toward this global data mining system and this would be an advantage because we predominantly utilize Siemens Soarian and their DSS platform is quite robust. The new upgrade we performed in June has added many data mining features so we are contemplating waiting to see what they come up with in the future. I am not sure there are advantages except we are familiar with Siemens and have a good working relationship. The disadvantages would be we are implementing this data mining initiative somewhat late compared to local area hospitals so we are under the gun, so to speak."  

AMS- "What are the issues with the institution's approach to data mining?

B. K. -"SpectraMD USA, Inc. is a new company and their premium program concerns value based purchasing and CMS Cores Measures. This is their flagship data-mining program but they intend to expand to be the premiere data mining company. They do have a program for Physician Quality Reporting System Compliance but we use Crimson Continuum of Care program so we do not need their program (Crimson continuum of, 2013). We needed to get the core measures under control so we implemented this program. We are not sure that we want to explore their other programs at this time. We have to consider that if we use their program for other data mining projects they may be appropriate for some clinical areas but inappropriate for other clinical areas. This is why we have nineteen clinical systems in our hospital because no one system fully understands the electronic medical record documentation system of every clinical area. These are big issues to tackle and we are investigating, researching and evaluating the best way to move forward.

AMS-"Thinking of what this institution is trying to do with data mining, what criteria 

would you want to use in evaluating data mining software.

B. K. - "We look for many things when evaluating data mining software. The number one item I look for is functionality because that determines the adaptability of the program and how it can meet the challenges that may occur with data mining. Performance is another category because there is going to be many different interfaces and data sources and this demonstrates the efficiency of the product. Another category is the ease of use or user friendly capability of the data mining software. It has to be easy to learn or there can be errors or incorrect documentation. Are there different levels in this program that would affect learning is another question to consider. This software also has to have other functions that will facilitate report production and data manipulation. The data needs to be capable of filtering, randomizing, and potentially deleting outliers. The data needs to be clean for the finished product to be accurate and truly reflect the subject in which we are looking to mine data."

            "We looked at these features with Focus but we were ready to purchase because of time constraints and their program had acceptable criteria. That is why we are taking more time with our decision to adopt hybrid or global system for data mining."

AMS-" What role do you see the nurse playing regarding data mining, including a 

discussion of the uses of data mining to improve nursing practice?"

B. K. - "Nurses are key players in documentation in electronic medical records and information technology as it pertains to patient care. We have the IT meeting monthly to have nurses input with the various projects that we are implementing. Nurses have a different approach to IT systems and documentation and their thoughts and opinions are valued. "Program developers look for nurses to be involved in the development of nursing documentation," (Lyden, 2008, pg.9).  We have restructured Case Management to have Care Coordinators and Clinical Data Informatics specialists that review charts, round on the floors and input the data into Focus."

            "In the future as data mining expands here there will be more jobs that will be necessary to collect, clean and input the data. With the capability of Soarian currently to run reports on your individual patients or your assignment, you can structure your nursing practice and look for trends.  The increased use of technology can improve nursing practice especially when we convert to hand held devices. We have one more upgrade to convert Soarian software to the hand held device capability and then we will begin introducing the devices in certain clinical areas. All of these initiatives will change and improve nursing care toward their patients."

                                                                Conclusion

            The interviewer was helpful and provided great insight into the world of data mining at the writer's institution. The nurse informaticist uses science, nursing, evidence based theory, and nursing care to provide quality patient care (Shuler, 2011) . From a patient outcomes perspective there are informatics tools that help "shared decision-making and risk communication from the perspective of patient safety: (1) interactive education to improve risk comprehension; (2) multiple, individualized formats for conveying risk; (3) individualized risk calculations; (4) application of decision analysis methods to calculate options with the highest expected value; (5) automated updates of evidence to support shared decision making; and (6) utilization of different preference elicitation techniques and formats," Data mining is also another tool for improving patient outcomes," (Bakken, 2006, pg 233).

            The increased use of data mining can improve patient safety with shared decision-making,
 
increased communication, identifying potential risks and interactive education (Shuler, 2011). There
 
will be greater roles in data input, analyzing and collecting data so patient outcomes can be improved.

 
References

Are you maximizing data to avoid financial penalties?. (2012). Retrieved from https://www.spectramd.com/userfiles/File/FOCUS Actionable Analytics.pdf

Bakken, S. (2006). Informatics for patient safety: a nursing research perspective. Annual Review of Nursing Research, 24. Retrieved from http://resources.njstatelib.org/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=mdc&AN=17078416&site=ehost-live
End of citation-->

Crimson continuum of care. (2013). Retrieved from http://www.advisory.com/Technology/Crimson

Lyden, C. (2008). From Paper to Computer Documentation: One easy step? Online

            Journal of Nursing Informatics (OJNI), 12 (3). Available at

            http:ojni.org/12_3/Lyden.htm

Shuler, G. K. (2011). Role of nursing informatics for leadership. Nursing Advance, Retrieved from
 
 
            Leadership.aspx

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