Assignment is Literature Review

Reducing Evaluation and Management Coding Errors in Physician Practices.

Research Questions:

RQ1: What are the causes/drivers of evaluation and management coding errors in physician practices.

RQ2: How can we reduce evaluation and management coding errors in physician group practices.

Literature Review Process: Review 10-15 research papers that informs us of our current state of knowledge in your problem area. If you find no prior paper in this area, expand your search terms to extract 10-15 papers in related areas. Describe the process by which you selected papers for review (e.g., which databases were used, what keywords, etc.), how you filtered your search results, actual counts of papers extracted in each search, etc.

I performed a search in the OVID Health Journals database using the following keywords: physician coding, physician documentation, evaluation and management codes, medical coding accuracy, and upcoding. The initial search returned 186 articles. I repeated the search limiting the keywords to the abstract which then returned 16 articles. I selected 4 articles after a full text review.

Next, using the same keywords from the previous search, I performed a second search in the ABI/Inform Global, Academic Search Premier and Science Direct databases for peer reviewed scholarly journals. The search produced 331 results. I again refined the relevance by limiting the keyword search to the abstracts which then resulted in 41 articles. A review of the abstracts produced 9 relevant articles; I eliminated articles that either did not focus on physician practices (i.e. focused exclusively on hospitals) or was not relevant to physician CPT coding errors (i.e. focused on DRG or ICD-10 coding).

I found 25 relevant sources in the bibliographies of the selected articles, of which I selected 11 to include in the literature review, resulting in a final list of 24 articles.

Selection Criteria for Literature Review

TABLE 1: Key Issues and Implications of Evaluation & Management Coding Errors

TABLE 2: Factors that Cause Evaluation and Management Coding Errors

TABLE 3: Countermeasures to Reduce Evaluation and Management Coding Errors

TABLE 4: Possible Theories to Explain Coding Errors

Analysis (Gaps):

Medical Coding Scope and Definition

All outpatient encounters are coded using evaluation and management codes. This literature review focuses on coding errors for evaluation and management services because they represent nearly 30% of Medicare Outpatient payments and according to CMS, they are the most common type of medical billing error (Department of Health and Human Services, 2014).

There are five levels of evaluation and management codes. Level 1 codes reflects the least complex outpatient encounter and correspondingly the lowest level of reimbursement. Accordingly, level 5 codes represent the most complex patient encounter and the highest level of reimbursement. Undercoding is a term used to describe a situation where a physician bills a lesser code - and therefore receives less reimbursement – for services provided. Overcoding - which is the subject of medical coding fraud literature - occurs when a physician overcharges for the services provided (Bauder, Khoshgoftaar, & Seliya, 2017). Both overcoding and undercoding are considered medical coding errors (Varacallo, Wolf, & Martin, 2017) and subsequently are included in the literature review.

Key Issues and Implications

The literature supports a high rate of evaluation and management coding errors in physician practices. Numerous studies, spanning almost two decades, cite error rates ranging from 33% to 57% (Chao et al., 1998; Department of Health and Human Services, 2014; Holt, Warsy, & Wright, 2010; Varacallo et al., 2017). The persistent error rates raise concerns about its effect on health care policy (Lorence & Richards, 2002), the impact on national healthcare costs (Department of Health and Human Services, 2014), the financial viability of physician practices (Nguyen, O'Mara, & Powell, 2017) and the increasing criminal and civil penalties physicians face (Doan, 2011; Hyman, 2002).

A key theme in the literature is the apparent subjectivity of the coding guidelines. Zuber et al. (2000), found a 44% concordance rate between coding auditors. Kikano et al, (2009) noted similar results with 43% concordance rate among Family Physicians. These studies underscore a prevalent concern in the literature; physicians’ cannot correctly apply coding guidelines because the coding system is ambiguous and too complex to be uniformly applied(Kikano, Goodwin, & Stange, 2000; King, Lipsky, & Sharp, 2002; Zuber et al., 2000).

Causes of Evaluation and Management Errors

There is general agreement a knowledge deficit exists in physician coding and education. Results from survey instruments, self-assessments and coding tests, demonstrate a knowledge gap in understanding of basic coding principles (Andreae, Dunham, & Freed, 2009; Cohen, Marculescu, & Sa, 2001; Varacallo et al., 2017). Leaning on Bandura’s (1977) self-efficacy theory, Cohen et al. (2001), and Brennan et al, (2011) show that when physicians doubt their ability to accurately learn the system they do not put forth the effort thus they continue to make coding errors. Other causes of coding errors involve environmental factors such as time constraints and management pressures. Simon’s satisficing theory (Simon, 1956), and the theory of availability heuristics (Tversky & Kahnerman, 1982), form complementary conceptual frameworks for arguments that time pressures, limited knowledge and cognitive abilities are key contributing factors to coding errors (Cohen et al., 2001; King et al., 2002). Finally, the quality of the information used in the coding process is also a key contributor to coding errors. Since the physicians’ documentation forms the basis of selecting the medical codes, quality of the information documented is critical to accurate coding. Documentation which is incomplete, inaccurate or ambiguous will inevitably result in incorrect coding (Howard & Reddy, 2018; Varacallo et al., 2017).

Countermeasures Against Evaluation and Management Coding Errors

Prevention – There is widespread agreement that educational intervention is the best strategy to reduce coding errors. However, these recommendations are not scientifically tested. One study found significant improvement in knowledge after educational sessions, but this study did not measure long term retention and is not transferable to clinical practice (Varacallo et al., 2017). Nguyen et al, (2017) performed a similar study but found no impact on coding accuracy. Nonetheless, the literature calls for formal graduate education programs during residencies, fellowships and as a prerequisite to board certifications (Agrawal, Taitsman, & Cassel, 2013; Howard & Reddy, 2018). I did not find any studies that tested training program characteristics proven to improve coding accuracy or strategies physicians may employ (such as accounting control theory) to improve the quality of the information in their documentation. Further, the literature is also silent the use of information technology as a tool to prevent coding errors.

Detection – The government primarily relies on post and pre-payment audits to identify incidences of medical coding errors and improper payments (Department of Health and Human Services, 2014). This investigative approach is manual, resource intensive and therefore not cost effective. Datamining techniques, focused on the highest risk areas, are more accurate and effective in identifying patterns of coding errors which can then be handed over to investigative agencies to research and respond.

Response – While most concede regulatory enforcement is a necessary response to government fraud, others argue deterrence does nothing to address human and information errors (Doan, 2011; King et al., 2002). Undercoding occurs with equal frequency as overcoding, which suggest lack of training as a root cause and not motivations of financial profit (Chao et al., 1998; Holt et al., 2010; Kikano et al., 2000). Further, there is limited evidence that the legal interventions, ushered in by the Health Insurance Portability and Accountability Act of 1996, have been effective in deterring coding errors (Hyman, 2002; Rashidian, Joudaki, & Vian, 2012). Nonetheless, there remains concern the current system of reimbursement gives physicians financial incentives to upcode (Lorence & Richards, 2002). Resource dependency theory (Pfeffer & Salancik, 2003) for example, postulates that external influences, may lead physicians to intentionally upcode to maximize reimbursement.

It has been shown that the primary drivers of evaluation and management coding errors are inadequate knowledge and awareness. It follows then preventative measures such as physician documentation improvement, and coding education programs, are vital yet missing countermeasures against evaluation and management errors. Considering the dearth of research on the economic, financial and legal implications of medical coding errors, identifying and testing the effectiveness of educational and information technology interventions seem like logical extensions of the current body of work. My research will attempt to 1) test the effectiveness of training and education interventions to minimize evaluation and management coding errors 2) identify information technology interventions that are proven to improve information quality in physicians’ documentation and 3) further our understanding of evaluation and management coding errors.

References

Agrawal, S., Taitsman, J., & Cassel, C. (2013). Educating physicians about responsible management of finite resources. Jama, 309(11), 1115-1116. doi:10.1001/jama.2013.1013

Andreae, M. C., Dunham, K., & Freed, G. L. (2009). Inadequate training in billing and coding as perceived by recent pediatric graduates. Clinical Pediatrics, 48(9), 939-944. doi:10.1177/0009922809337622

Bauder, R., Khoshgoftaar, T., & Seliya, N. (2017). A survey on the state of healthcare upcoding fraud analysis and detection. Health Services and Outcomes Research Methodology, 17(1), 31-55. doi:10.1007/s10742-016-0154-8

Becker, D., Kessler, D., & McClellan, M. (2005). Detecting Medicare abuse. Journal of Health Economics, 24(1), 189-210. doi:10.1016/j.jhealeco.2004.07.002

Brennan, M., & Probe, R. (2011). Common errors in billing and coding for orthopaedic trauma care. Current Orthopaedic Practice, 22(1), 12-16. doi:10.1097/BCO.0b013e31820598bd

Brunt, C. S. (2011). CPT fee differentials and visit upcoding under Medicare part B. Health Economics, 20(7), 831-841. doi:10.1002/hec.1649