Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked

An analysis of a rural hospital's investment decision under different payment systems

From an economic perspective, large investments in medical equipment are justifiable only when many patients benefit. Although rural hospitals play a crucial role locally, the treatments they can offer are limited. In this study, I characterize investment level that maximizes the total surplus, encompassing patients' welfare and producer surplus, and subtracting treatment costs. Specifically, I account for economic externalities generated by the investment in the rural hospital and for different utility losses that patients suffer when they cannot be treated locally. I demonstrate that the optimal investment level can be implemented if the Health Authority has the power to set specific prices for each disease. Additionally, I explore a decentralized situation wherein the investment decision lies with the rural hospital manager, and the Health Authority can only make a discrete decision between two payment systems: Fee-for-service, which covers all treatment costs, or Diagnosis-Related-Groups, which reimburses a price per patient based on the overall average cost. I find that the Diagnosis-Related-Groups system outperforms the Fee-for-service in terms of total surplus when the treatment cost at the rural hospital is lower. However, when the rural hospital has higher costs and the Health Authority seeks to incentivize investment, the Fee-for-service system is superior.

Upcoding in medicare: where does it matter most?

Upcoding in Medicare has been a topic of interest to economists and policy makers for nearly 40 years. While upcoding is generally understood as "billing for services at higher level of complexity than the service actually pro- vided or documented," it has a wide range of definitions within the literature. This is largely because the financial incentives across programs and aspects under the coding control of billing specialists and providers are different, and have evolved substantially over time, as has the published literature. Arguably, the primary importance of analyzing upcoding in different parts of Medicare is to inform policy makers on the magnitude of the process and to suggest approaches to mitigate the level of upcoding. Financial estimates for upcoding in traditional Medicare (Medicare Parts A and B), are highly variable, in part reflecting differences in methodology for each of the services covered. To resolve this variability, we used summaries of audit data from the Comprehensive Error Rate Testing program for the period 2010-2019. This program uses the same methodology across all forms of service in Medicare Parts A and B, allowing direct comparisons of upcoding magnitude. On average, upcoding for hospitalization under Part A represents $656 million annually (or 0.53% of total Part A annual expenditures) during our sample period, while up- coding for physician services under Part B is $2.38 billion annually (or 2.43% of Part B annual expenditures). These numbers compare to the recent consistent estimates from multiple different entities putting upcoding in Medicare Part C at $10-15 billion annually (or approximately 2.8-4.2% of Part C annual expenditures). Upcoding for hospitalization under Medicare Part A is small, relative to overall upcoding expenditures.

Analysis of Health Care Billing via Quantile Variable Selection Models

Fraudulent billing of health care insurance programs such as Medicare is in the billions of dollars. The extent of such overpayments remains an issue despite the emerging use of analytical methods for fraud detection. This motivates policy makers to also be interested in the provider billing characteristics and understand the common factors that drive conservative and/or aggressive behavior. Statistical approaches to tackling this problem are confronted by the asymmetric and/or leptokurtic distributions of billing data. This paper is a first attempt at using a quantile regression framework and a variable selection approach for medical billing analysis. The proposed method addresses the varying impacts of (potentially different) variables at the different quantiles of the billing aggressiveness distribution. We use the mammography procedure to showcase our analysis and offer recommendations on fraud detection.

Reducing administrative costs in US health care: Assessing single payer and its alternatives

OBJECTIVE

Excess administrative costs in the US health care system are routinely referenced as a justification for comprehensive reform. While there is agreement that these costs are too high, there is little understanding of what generates administrative costs and what policy options might mitigate them.

DATA SOURCES

Literature review and national utilization and expenditure data.

STUDY DESIGN

We developed a simulation model of physician billing and insurance-related (BIR) costs to estimate how certain policy reforms would generate savings. Our model is based on structural elements of the payment process in the United States and considers each provider's number of health plan contracts, the number of features in each health plan, the clinical and nonclinical processes required to submit a bill for payment, and the compliance costs associated with medical billing.

DATA EXTRACTION

For several types of visits, we estimated fixed and variable costs of the billing process. We used the model to estimate the BIR costs at a national level under a variety of policy scenarios, including variations of a single payer "Medicare-for-All" model that extends fee-for-service Medicare to the entire population and policy efforts to reduce administrative costs in a multi-payer model. We conducted sensitivity analyses of a wide variety of model parameters.

PRINCIPAL FINDINGS

Our model estimates that national BIR costs are reduced between 33% and 53% in Medicare-for-All style single-payer models and between 27% and 63% in various multi-payer models. Under a wide range of assumptions and sensitivity analyses, standardizing contracts generates larger savings with less variance than savings from single-payer strategies.

CONCLUSION

Although moving toward a single-payer system will reduce BIR costs, certain reforms to payer-provider contracts could generate at least as many administrative cost savings without radically reforming the entire health system. BIR costs can be meaningfully reduced without abandoning a multi-payer system.

Septic Revision Total Hip Arthroplasty Is Not Adequately Compensated by Work Relative Value Units

BACKGROUND

Performing revision total hip arthroplasty (rTHA) for periprosthetic joint infection is complex and may require greater time and resources than aseptic revision cases. Work relative value units (RVUs) assigned may not reflect the difference in actual work required for septic revision hip cases. The purpose of this study is to compare the work effort between aseptic and septic revision hip cohorts, and determine if physicians are appropriately compensated.

METHODS

Data were collected through the National Surgical Quality Improvement Program database for the years 2005 to 2018 to identify all aseptic rTHA cases and septic rTHA cases. Work RVU, operation time, RVU per minute, and dollars per minute were assessed between the aseptic and septic revision hip cohorts. Univariate and multivariate analyses were used for the study.

RESULTS

The mean operation times for aseptic and septic rTHAs were 146.12 and 173.24 minutes, respectively (P < .001). This resulted in an RVU per minute of 0.257 for the aseptic revision hip cohort compared to 0.212 for the septic cohort (P < .001). Aseptic rTHA cases were valued higher with a dollars per minute of 9.28, whereas septic rTHA cases were 7.65 (P < .001).

CONCLUSION

Although rTHA for infection is more complex and requires longer mean operative time than aseptic rTHA, physicians are not appropriately reimbursed for this challenging procedure. This inadequate RVU-based reimbursement for septic rTHA may deter physicians from performing these procedures, which could lead to decreased access to care for patients in need of rTHA for infection.

Do hospitals respond to changing incentive structures? Evidence from Medicare's 2007 DRG restructuring

In 2007, the Centers for Medicare and Medicaid restructured the diagnosis related group (DRG) system by expanding the number of categories within a DRG to account for complications present within certain conditions. This change allows for differential reimbursement depending on the severity of the case. We examine whether this change incentivized hospitals to upcode patients as sicker to increase their reimbursements. Using the National Inpatient Survey data from HCUP from 2005 to 2010 and three methods to detect the presence of upcoding, our most conservative estimate is an additional three percent of reimbursement is attributable to upcoding. We find evidence of upcoding in government, non-profit, and for-profit hospitals. We find spillover effects of upcoding impacting not only Medicare payers, but also private insurance companies as well.

Physician Behavior under Prospective Payment Schemes-Evidence from Artefactual Field and Lab Experiments

Recent experimental studies analyze the behavior of physicians towards patients and find that physicians care for their own profit as well as patient benefit. In this paper, we extend the experimental analysis of the physician decision problem by adding a third party which represents the health insurance that finances medical service provision under a prospective payment scheme. Our results show that physicians take into account the payoffs of the third party, which can lead to underprovision of medical care. We conduct a laboratory experiment in neutral as well as in medical framing using students and medical doctors as subjects. Subjects in the medically framed experiments behave weakly and are more patient orientated in contrast to neutral framing. A sample of medical doctors exhibits comparable behavior to students with medical framing.