Abstract

The Overkill case study discusses issues around low-value care and ways of minimizing healthcare costs while increasing the quality of output. Low-value care is the administration of health interventions whose costs or harms exceed benefits. It arises from information asymmetry between the doctor and their patient. The doctor has a lot of knowledge on treatment plans, while the patient has little knowledge and relies fully on the doctors recommendations. The doctors decision to offer low-value care is a form of moral hazard. All the same, the inclination to offer low-value care could be minimized through adopting capitation compensation systems to replace fee-for service systems. The latter encourage physicians to focus on the quantity of care rather than the quality of care, thus heightening the need to offer low-value care. This assignment uses the information in the case to answer questions on why people receive low-value care, issues associated with overdiagosis, and the different forms of health management organizations.

Case Study: The Overkill Case

Introduction of Topic and Facts of the Case

The Overkill case study addresses the moral hazard of low-value care, which is the unfortunate idea that millions of patients are forced to pay for operations, drugs, and tests that will not make them any better. The author provides several examples of low-value care cases in which medical personnel prescribed one or more of twenty-six useless treatments and tests that added healthcare costs to patients but had no impact on health improvement. Medicare patients are the most likely victims of low-value care, with studies indicating that on average, 25 to 42 percent of patients receive some form of test or treatment that pushes costs up but has little effect on health improvement. Unfortunately, some of these decisions could harm patients in the long-run. For instance, frequent CT scans expose patients to the risk of developing cancer.

The author attributes the tendency to offer low-value to information asymmetry. Medical professionals know more about tests and medical plans than their patients, who have little knowledge and fully trust their doctors decisions. Medical professionals thus take advantage of the patients lack of information to enhance their incomes by prescribing unnecessary tests and medications. Insurers attempt to address this moral hazard by refusing to pay for costs that seem unnecessary. However, it is challenging to differentiate between the necessary costs and the exaggerated ones. Coverage limitations could cause death if patients are unable to access crucial healthcare services. Large organizations such as Wal-Mart have come up with more creative ways to foster quality healthcare for their employees at low costs. The company works with specific trustworthy healthcare providers in an accountable care organization to increase employees access to quality, affordable healthcare.

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A summary of the Areas Pertinent to the Course

The case study demonstrates three concepts discussed in the course text: moral hazard, adverse selection, and information asymmetry. Information Asymmetry is a situation in which one party in a transaction has more information or knowledge than the other (Lee, 2019). The Overkill case demonstrates information asymmetry between doctors and patients. Doctors have more information on treatment plans than patients, who have little knowledge and fully rely on their doctors diagnoses and treatment plan recommendations.

A Moral hazard exists when a party takes advantage of information asymmetry to benefit itself at the expense of the other party because it enjoys protection and the other party will bear the burden. In the Overkill case, insured patients engage in moral hazard when they fail to seek a second opinion from another doctor and instead opt to take up tests and costly procedures immediately they are prescribed because the insurer covers the cost. At the same time, doctors engage in moral hazard when they impose more expensive treatment plans on Medicare patients than they would if patients were not covered. The author mentions that 25 to 42 percent of Medicare patients receive some form of overtreatment or over-testing that pushes costs up but has little effect on health improvement. Doctors also engage in moral hazard when they prescribe unnecessary treatment plans and tests, thus benefiting themselves at the expense of the patients. In some cases, these unnecessary treatment plans can be harmful to patients. For instance, regular CT scanning increases the risk of developing cancer.

The moral hazard problem then gives rise to adverse selection, which occurs when organizations cannot distinguish between low-risk and high-risk clients, leading them to take action that disadvantages all parties (Lee, 2019). The course book discusses adverse selection in the context of insurance coverage in chapter three. Since insurance companies cannot distinguish between low-risk and high-risk clients, they charge everyone a higher premium. In the Overkill case, adverse selection arises when insurance companies impose limits on coverage and decline to cover some costs because they cannot tell which costs are necessary and which ones are exaggerated.

A Detailed Case Discussion

What is low-value care?

Low-value care is the administration of health interventions whose costs or harms exceed benefits (Chua, 2022). An example of low-value care is sending a suspected thyroid cancer patient for an MRI after they have had an ultrasound. An MRI is not as effective...…on the quantity of care they gave and thus. Thus, the doctors operated on a profit-maximization culture, notwithstanding that they owned some of the imaging centers and healthcare agencies where patients were sent for healthcare services. Since the passage of the Affordable Care Act, per-capita Medicare costs have flattened out. The countys Medicare costs per patient reduced by $3,000 between 2009 and 2012 as a result of the policy change. Hospital admissions reduced by 10 percent while ambulance rides, initially the highest in the country, reduced by 40 percent.

How did inputs to care change? The county reported a reduction in inputs to care, which are the resources needed to access care. The shift from the fee-for-service reimbursement model meant that physicins compensation was no longer attached to the quantity of care offered. As such, physicians no longer had to get patients to pay more

How did outputs to care change? Outputs to care, as measured by the number of discharges and quality output, increased due to the policy change. Physicians began to focus on offering quality care rather than care in huge quantities, which reduced the number of unnecessary procedures, waiting times, and referrals. At the same time, it increased the number of patients as care was more affordable.

Conclusion

The Overkill case demonstrates how patients receive low-value care and what policymakers could do to increase quality and decrease healthcare costs. Low-value care ranges from simple actions such as prescribing antibiotics for common cold to conducting unnecessary surgeries. Fee-for-payment systems are at the heart of low-value care as they make physicians operate like business people focused on generating as much profit as possible from their patients. The bottom line is that to reduce costs and increase the quality of care, there is a need to shift from fee-for-payment compensation models to the capitation model, where physicians reimbursement is a fixed amount pegged on the number of patients they are allocated, whether or not the patients seek treatment. Further, organizations could reduce insurance costs by organizing accountable care organizations or hiring physician staff to offer quality and affordable healthcare services to employees. The key takeaways from this case are:

Fee-for-service systems increase the risk of low-value care while capitation systems help to reduce healthcare costs and increase the quality of care. It is important that medical personnel remain focused on the quality of care rather than the quantity of care

Overdiagnosis could help uncover illnesses that may never have come to light but is harmful in the long-run if it leads to the diagnosis of a serious illness

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