WK3discussion(due by midnight)

Required Resource 

Text

Davenport, T. H. (Ed). (2014). Analytics in healthcare and the life sciences: Strategies, implementation, methods, and best practices. Upper Saddle River, NJ: International Institute for Analytics, Pearson Publisher. ISBN 13: 9780133407334

· Part III: Healthcare Analytics Implementation Methods – this section of the text covers in-depth descriptions and assessments of several methods used in executing healthcare data. These textbook readings will provide assistance with the CSBI exam, the discussion question, and the assignment.

Website

Healthcare Financial Management Association (Links to an external site.)Links to an external site.. (n.d.). Retrieved from http://www.hfma.org/

· The Healthcare Financial Management Association is an organization of healthcare finance leaders that builds and supports coalitions with other healthcare associations and industry groups to face the challenges the U.S. healthcare system faces today. This website will provide assistance with your CSBI exam preparation and your assignment.   Accessibility Statement does not exist Privacy Policy (Links to an external site.)Links to an external site.

Recommended Resources

Articles

Bates, D. W., Saria, S., Ohno-Machado, L., Shah, A., & Escobar, G. (2014). Big data in health care: Using analytics to identify and manage high-risk and high-cost patients. Health Affairs, 33, (7), 1123-1131. Retrieved from http://search.proquest.com/

· This article discusses the U.S. health care systems adoption of the Electronic Health Records system and how it has increased the availability of clinical data. The outcome of clinical data in conjunction with analytics is opportunities to reduce costs incorporating big data: high-cost patients, readmissions, triage, decompensation (when a patient’s condition worsens), adverse events, and treatment optimization for diseases affecting multiple organ systems (2014).

Bresnick, J. (2014). Decoding 10 more top healthcare big data analytics buzzwords. (Links to an external site.)Links to an external site. HealthIT Analytics. Retrieved from http://healthitanalytics.com/news/decoding-the-top-10-buzzwords-of-healthcare-big-data-analytics

· The article provides terminology relevant to healthcare analytics focusing on care coordination, data warehouse management, descriptive analytics, prescriptive analytics, and patient-generated health data.

Morse, S. (2016). CMS, America's health insurance plans set unified healthcare quality measures (Links to an external site.)Links to an external site.. Healthcare Finance. Retrieved from http://www.healthcarefinancenews.com/news/cms-americas-health-insurance-plans-set-unified-healthcare-quality-measureshttp://www.healthcarefinancenews.com/news/cms-americas-health-insurance-plans-set-unified-healthcare-quality-measures

· The Centers for Medicare and Medicaid Services (CMS) and America’s Health Insurance Plans have initiated a plan that incorporates health care providers and patients to identify core sets of quality measures that payers have committed to using for reporting. The goal is to provide clinical quality measures (analytics) to help get insurers on the same page.

Multimedia

HealthIt.gov. (2013, September 18). The path to interoperability (Links to an external site.)Links to an external site. [Video file]. Retrieved from https://www.youtube.com/watch?v=PaWcU7rqqyA

· This video provides information about the path to interoperability and will assist you in your Healthcare Analytics: Regulations, Clinical Quality, and Patient Safety discussion this week. Accessibility Statement (Links to an external site.)Links to an external site. Privacy Policy (Links to an external site.)Links to an external site.

Healthcare analytics provides the HCO with a process rather than transactions to evaluate the organizations level of quality in respect to care delivery. Patients, such as the boomer generation provide an increasingly educated base seeking answers to their questions as they participate in the continuum of care and demanding proof of quality care and positive outcomes (Davenport, 2014). Health care leaders must provide an evidence-based platform of clinical quality analytics.

How many physicians or clinicians embrace the knowledge that the patient comes in with, usually information obtained through the Internet.  How many patients self-diagnosis based on this information obtained?   No longer do patients take the stand of not asking any questions and just doing what the physician recommends.  Today's patients come in loaded with information that they use to ask thought-provoking questions.  Many patients want a holistic view of their care and bring in many forms of treatment that are not traditional.  How can healthcare organizations turn a potentially negative situation into a positive encounter?

Healthcare analytics provides the information needed to help at the beginning of patient care and throughout the care process, helping to improve the quality of care provided.  Meaningful use has been one of the key drivers to the growth and implementation of electronic health records (EHRs), and making progress towards health information exchange (HIE) (Ahier, n.d.).  The purpose behind meaningful use is for providers to use the EHRs in a “meaningful” way.  In order to demonstrate the EHR use, there are reporting requirements established by Medicare and Medicaid.  Medicare and Medicaid developed programs to provide financial incentive to eligible professionals (EP), eligible hospitals (EH) and critical access hospitals (CAH) for use of an EHR (Electronic Health Record) (Ahier, n.d.).  Since the point of meaningful use was to increase the quality of patient care, clinical analytics are being used to help provide the information needed to satisfy the reporting requirements. 

Regulations in healthcare drive many of the processes for the care of patients.  Compliance with these regulations often require new resources that could result in additional money outflow.  For example, to fully understand what is happening in the patient care areas, the data that is collected throughout the care of the patient needs to be captured and turned into information.  Through the information, analysis can happen and studied so decisions for improvement can be made.  The purchase of a system to handle the data analytics can be very expensive, particularly if all of the features are not used.  However, improvements in patient care may also result in a decrease in costs.  For example, there may be a supply used in patient care that yields the same quality results, but at a much lower price.  The beneficial changes can continue to happen over time, as more data is gathered and analyzed, and turned into information for decisions to be made.

When using analytics to improve patient care, there are many ways that the information may be used.  For example, grouping patients by gender, by diagnosis, by vitals, by treatments, by readmissions, secondary diagnosis, age, clinicians, and any other combination of data elements.  Analytics will show any trends, negative and positive.  These trends can be used to make process improvements, staff or scheduling changes, encourage preventive measures, schedule follow up appointments or procedures more timely, and other ways.  One of the exciting things about being in leadership is being able to analyze the data to report useful information.  Healthcare providers are constantly under scrutiny by the governmental regulations and the public for improving patient care quality while decreasing costs.  Analytics will provide the needed information in order to make the decisions to improve the overall value and quality of healthcare.

References

Aiher, B. (n.d.). Keeping Up With Meaningful Use: Clinical Analytics Are Key.  (Links to an external site.)Links to an external site.Retrieved from https://www.healthcatalyst.com/meaningful-use-to-meaningful-analytics