Medical coding is an important activity as far as it is used for the proper evaluation of medical data. The two most common mistakes include over-coding or under-coding. Over-coding presupposes the insertion of information in such a way that it will result in a higher payment. When over-coding occurs, data are overrated. Over-coding is a kind of fraud aimed at receiving a better profit without doing the corresponding amount of work. Over-coding may be conducted in two possible ways — upcoding or unbundling. When the provider misrepresents the level and amount of work for the particular service or procedure, the upcoding occurs. Unbundling is the method of reimbursement that presupposes the provision of bills for all services separately. It is easier to increase the payment by asking to pay for two unilateral procedures instead of one bilateral (Hicks par. 9).
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Although under-coding is not a fraud, it is also negative for the organization. Under-coding is the wrong presentation of data that does not demonstrate all scope of already done work. If the amount of work is diminished, the revenue will be less too. Consequently, the under-coding leads to the loss of profit. However, some health care providers practice intentional under-coding to avoid inspections of insurance companies. Such an approach is not right as well.
DRG is an abbreviation for diagnostic-related grouping. DRG is a system used to categorize the type of illness and overall cost of hospitalization for health insurance companies. Under DRG, health insurance companies pay a set amount of money for the treatment of a particular disease. In case the hospital manages to treat patients using not all payment, the profit is made. However, a hospital may need to pay more for treatment in particular instances. As a result, a loss of revenues occurs. Such a system is rather controversial. On the one side, it should encourage hospitals to avoid over-treating of patients. On the other, health care providers may try to discharge people even they are not healthy enough to make a profit (Davis par. 12).
Discussion of items
Impact of over-coding and under-coding
As has been already mentioned, over-coding is a fraud that aims to increase revenues. The over-coding influences the length of patients’ stay significantly. Fred Schulte and David Donald have investigated the problem of the intentional insertion of incorrect data to make more profits. The researchers have found out that the hospitals’ fees for patient treatments increased drastically after the implementation of the medical coding systems. The increase in required financial support for treatment is especially vivid among older patients. Schulte and Donald state, “Doctors steadily billed Medicare for longer and more complex office visits between 2001 and the end of the decade even though there’s little hard evidence they spent more time with patients or that their patients were sicker and required more complicated — and time-consuming — care” (par. 8). This fact demonstrates that over-coding may result in a limited length of stay that will negatively influence the patient’s health.
Over-coding may be directly connected to the unnecessary diagnostic results. The primary aim of health care providers is to make a profit from patients’ treatment. The best way to retain a patient is to make him undergo unnecessary diagnostic tests. While patient takes particular useless tests, the provider may bill for more complicated and expensive procedures. Gawande writes about the practice of sending patients to make EEG for the headache examination while this test is used to diagnose seizure disorders (par. 2). According to the author’s findings, over-coding results in taking unnecessary diagnostic tests for almost thirty percent of patients.
Also, over-coding impacts the use of unnecessary medication. Healthcare providers may prescribe unnecessary medications to receive more financial resources for hospitals from the insurance company. The following picture demonstrates the estimated increase of the spending amounts for drugs (PwC 9).
Monitoring of the length of stay is another aspect that is influenced negatively by the over-coding. The actual length of stay may not be the same as documented in the system. Health care providers may insert incorrect data to increase payment but the discharge of patients sooner. The problem is that the short length of stay is considered to be a positive index while patients’ outcomes are negative. Jones writes, “most would view the length of stay as a continuously decreasing measure, reflecting the increasing efficiency” (248). In such a way, providers negatively affect large-scale monitoring of LOS. Numbers may show that the situation is becoming better while health disparities will increase.
The under-coding may have a negative impact on medication errors. The systems of electronic sharing of various diagnoses and patients’ health conditions are extremely useful for the avoidance of medical errors (Agrawal 681). The number of death because of medical errors is shocking. For example, almost two million people die because of medical errors in the US. In the UAE, medical claims concerning fatal errors increase annually as well (Bell par.1). An efficient coding system is crucial for proper diagnosis and prevention of unknown consequences of treatment. Under-coding decreases the possibility of avoiding medical errors by limiting the available information.
Under-coding may influence unnecessary diagnostic tests. Most doctors practice under-coding due to the fear to be reviewed by insurance companies or making some mistakes. As a result, they do not include information about all tests that have been done. When the person comes to the other doctor, he or she is asked to take the same tests (which were not coded) that may be harmful to health.
The same is the impact of the under-coding on the monitoring of the length of stay. When hospitals practice under-coding, they follow their particular purposes. Some of the providers believe that government monitors over-coding only. However, the government checks instances of improper coding which includes under-coding as well. The problem is that while under-coding, hospitals provide governmental institutions with limited information about LOS monitoring. It may affect the choice of national health care programs and policies (“Undercoding. Is it Worth it?” 2).
Under-coding in the DRG system has an adverse effect on the length of stay of patients in hospitals in some cases. As it has been already mentioned, hospitals are given a particular sum of money for the treatment of diseases. One of the objectives of DRG implementation is to avoid over-treatment of patients. However, if hospitals manage to treat patients quickly, they will have a profit in the form of the remaining part of the money for treatment. Thus, some providers are ready to discharge patients as soon as possible and make a profit. In such cases, health care providers use under-coding to minimize necessary treatment and shorten the length of stay of patients in hospitals. This fraudulent experience is harmful to patients’ health and safety because of the lack of treatment and professional support. The following table demonstrated the impact of DRG on the length of stay in hospitals.
Application of Diagnosis Related Groups (DRG’s) and Cost Weight methodology
Under DRG, ten thousand diseases may be divided into approximately seven hundred groups. One group includes similar illnesses with almost the same cost of treatment. A treatment of one patient is equal to one DRG. Data from DRG are used to estimate the necessary funding for one patient. The application of DRG may be divided into several steps. First, the patient with the medical history should be discharged. Then, health manager reviews the treatment and inserts the information into the computer system. This information is sent to the Department of Health. Correct codes from DRG are crucial for the hospital to receive funding, which is also known as casemix funding (“DRG and Casemix Funding” par. 3-5).
A cost weight methodology is used to calculate the required funding for one Diagnosis-Related Group and compare it to other DRGs. The cost weight is measured by checking the correlation between the funding for DRG and the LOS. Weighted Inlier Equivalent Separation is the name of the process employed for the identification of cost weight. Such methodology is employed to increase the efficient division of funding (“DRG and Casemix Funding” par. 8-10).
Impact of incomplete documentation on health record
The insufficient documentation may be a sign of a poor clinical care, possible fraud, or lack of responsibility for the medical documentations. As a result, the health record of the particular patient does not contain all necessary information about previous symptoms, diagnoses, treatment options, and prescriptions.
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The incomplete health record may negatively influence the further treatment of the patient. Not relevant care information may result in the choice of the wrong treatment by other healthcare providers. In such a way, the improper documentation may have a devastating impact on patient’s health and result in medical errors, unnecessary treatment, and wrong diagnosis (“The consequences of an incomplete medical record” par. 2).
Unnecessary medications and management of healthcare funding
Healthcare providers may use prescription of unnecessary medication as a means to increase the funding for the hospital. The US is the most vivid example in this respect. The state spends the most money on the health care system in the world. However, numerous researchers find out that immense amounts of money can be saved. One of the examples is “overuse of antibiotics for respiratory infections, with potential savings of $1.1 billion” (Delaune and Everett 1). Thus, health providers may make use of prescribing unnecessary medications to increase the inflow of financial resources to the hospital. This issue is extremely controversial for two reasons. First, the government cannot refuse to provide the amount of requested money. Otherwise, people will come to the conclusion that the state tries to save resources at the cost of nation’s health. Second, the governmental institutions should monitor the efficiency of spending of provided financing due to the numerous claims concerning malfeasance in office.
Medication error and risk management
The proper evaluation of medical errors contributes significantly to the risk management in hospitals. Medical errors comprise an important concern for healthcare providers. However, as far as numerous errors are made, these data should be used for the potential prevention. Thus, medical errors may be classified according to their frequency, places when they occur, or types of procedures with most medication errors. Such data should be used for the prediction and prevention of possible errors. It is a direct way to the improvement of patient safety which, in its turn, belongs to the scope of risk management (Pietra et al. 340).
The implementation of various strategies has demonstrated that there are challenges related to the improvement of the efficiency of medical coding. The principal concern refers to the fact that health care providers may use over-coding and under-coding for fulfilling individual aims. Also, some mistakes in medical coding are caused due to the lack of professional training and skills.
The first recommendation is to promote the education about medical coding. Personnel should be given basic training concerning the proper way to insert data. It is advisable to provide hospital’s staff with opportunities to train how to use medical coding in their practice. A more important factor refers to the realization of the consequences of any kind of fraud or mistakes. While most providers know the results of over-coding, under-coding is considered to be a safe way to avoid examinations from insurance companies. However, under-coding is also a violation of the principles of medical coding. The second recommendation is to establish a system of mandatory checks of coding within the particular time frame to avoid attempts to make profit or mistakes.
Over-coding is a way to make a profit of payments provided by insurance companies via overestimating services and procedures that have been provided to the patient. Under-coding is a method of diminution of what has been done for patients to avoid inspections. DRG is a system of categorization of illnesses in various classes. Both over-coding and under-coding have a negative influence on medication errors, monitoring of LOS, unnecessary medications, and unnecessary diagnostic tests. Also, some of these indicators may be used to manage hospital financing and conduct risk management. The idea of medical coding is crucial for the successful development of health care services. However, it is necessary to educate health care providers and perform constant inspections.
Agrawal, Abha. “Medication errors: prevention using information technology systems.” British Journal of Clinical Pharmacology 67.6 (2009): 681-686. Print.
Bell, Jennifer. More than 500 medical complaints made in Dubai last year. 2014. Web.
Davis, Elizabeth. DRG 101: What is a DRG & How Does It Work. n.d. Web.
Delaune, Jules and Wendy Everett. Waste and Inefficiency in the U.S. Healthcare System. 2008. PDF file. Web.
DRG and Casemix Funding n.d. Web.
“DRG with Great Impact on Reducing Length of Stay (LOS) —2010” n.d. JPEG file.
Gawande, Atul. Overkill. 2015.
Hicks, Joy. Two Coding Mistakes You Must Avoid. n.d. Web.
Jones, Rod. “Benchmarking Length of Stay.” British Journal of Healthcare Management 16.5 (2010): 248-250. Print.
“Medical Error Graph” n.d. GIF file. 2016.
Pietra, Raymond, Laura Calligalis, Ludvig Moldenini, Richard Quattrin, and Silvio Brusaferro. “Medical Errors and Clinical Risk Management: state of the art.” Acta Otorhinolaryngologica Italica 25.6 (2005): 339-346. Print.
PwC. Medical Cost Trend: Behind the Numbers 2015. PDF file. Web.
Schulte, Fred and David Donald. How Doctors and Hospitals Have Collected Billions in Questionable Medicare Fees. 2012.
The consequences of an incomplete medical record 2005. Web.
Undercoding. Is it Worth it? n.d. PDF file. Web.