System Structures Presentation
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system_structures_overview.docxSYSTEM STRUCTURES OVERVIEW 1
SYSTEM STRUCTURES OVERVIEW 4
An understanding of disease classification structures is paramount for easily studying various diseases. Therefore, numerous data collection on disease classification structures has been conducted for many purposes. This study will focus on the classification structures of a disease for purposes of reimbursement and epidemiological data collection as well as its description, reason, structure, benefits, and negative aspects.
The disease classification structures refer to a disease categorization system developed World Health Organization. This system classifies disease into International Classification of Disease (ICD) structures, ranging from ICD 6 to ICD 11 (Loscalzo et al, 2007). These classification structures are essential for data collection for reimbursement by the insurance and epidemiology, which is the study of health-related conditions and events in terms of distribution and determinants in a specific population.
Description of the Selected System
The information system structure needed for disease classification for reimbursement is both complex and user friendly at the same time. The information system must be able to recognize the ICD-10 codes. ICD-10 is the International Classification of Disease, tenth edition. If the staff was not able to understand how to use the information system, the correct information would not be entered and the organization would not receive correct reimbursement. ICD-10 codes identify the disease which then determines if the treatment is one that will be reimbursed by the payer; for example, an ICD-10 code of 496.0, would allow for a reimbursement of oxygen, however it would not allow for a reimbursement of a wheelchair, since the diagnosis is for COPD. The codes identify the disease which then identifies what reimbursable treatment has been used.
Reason for the Selected System
The Affordable Care Act of 2010 states that the Centers for Medicare and Medicaid Services must begin adding a value modifier under the Medicare Physician Fee Schedule by 2015. (Chapman, 2014) For the first time in health care physicians and hospitals are being reimbursed for the quality of care they provide rather than the services they render. With the implementation of ICD10, the description of the services provided will be in the coding.
Most hospitals are thinking about and preparing for ICD10. In addition, they are implementing EMR’s. Value based contracts, patient outcomes, and efficiency of patient care need to be added to the strategy. Applicable Structure for the Work Area
All health care organizations utilize specific codes and structures; which will assist in the reimbursement process and the collection of data. This particular system structure is applicable in the work area because it helps medical coders and those in the billing department, who may utilize the system, to process and send payments. These payments can be paid to private insurance companies or those who have plans such as PPO’s, HMO’s, or POS’s. Guidelines are taken for each company as it puts forth the best effort in helping the patient, client, or organization save money for services rendered. The “WHO” business plan states, “Given the advances in health information technology and health care systems, today we need to rethink the classification better suited for the purpose of data collection and capture different dimension and serve for more comparisons across the health care environment” (WHO, 2005).
Benefits of the Selected System
When it comes to the reimbursement, the underwriters require data concerning the disease classification structure of a particular disease, to estimate appropriate amount to indemnify the patient or any other claimant. In epidemiology, disease classification structure is necessary, because it offers a shared language for monitoring and reporting diseases. This permits a standard and a consistent way of sharing and comparing epidemiological data between hospitals across the world. It also helps to classify and code epidemiological information, for instance, health care administration, monitoring and evaluation, primary care, health research, control and treatment (Rothman et al, 2008). It offers a broad view of the health situation of nations and populations.
Negative Aspect of the Selected System
The problem with the shift to a model that reimburses based on quality metrics is that the “bonus” does not come immediately. When a contract that is value based is signed, it is usually 18 months before the benefits are reaped. According to United Healthcare, in 2013 more than $20 Billion of its reimbursements to hospitals, physicians, and other providers were linked in some way to cost efficiency and quality measures. (Chapman, 2014)
The implementation of ICD10 has been long awaited however once it actually comes to fruition; the estimates are that hospitals will experience a 50% to 70% slowdown in coder productivity at least initially. (Eramo, 2014) In addition, many hospitals do not have a denial management strategy in place to deal with the influx of denials based on improper coding.
Conclusion
It is important to understand different structures and the use of data collection in regards to diseases, treatment, and reimbursement. Individuals who are a part of the health care industry have major roles which keep organizations actively running properly. The selective system structure disease for purposes of reimbursement and epidemiological data collection is applicable in many health care environments and used by medical coders and billing specialist for many different reasons. Information technology systems will always be of importance in the health care industry.
References
Chapman, S. (2014, September). How to Succeed in a Value Based World. Retrieved from http://fortherecordmag.com/archives/0914p18.shtml
Eramo, L. (2014, February). Warning: Loss of Productivity Ahead. Retrieved from http://forthereocrodmag.com/archives/0214p10.shtml
Loscalzo, J., Kohane, I., & Barabasi, A. L. (2007). Human disease classification in the postgenomic era: a complex systems approach to human pathobiology. Molecular systems biology, 3(1).
Rothman, K. J., Greenland, S., & Lash, T. L. (Eds.). (2008). Modern epidemiology. Lippincott Williams & Wilkins.
WHO. (2005). Rethinking Clarification for our global village. Retrieved from http://www.who.int/classifications/BusinessPlan.pdf
