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In the last couple of years, the federal government has cut Medicare funding because of the increased adoption of cost-savings measures. For example, it has reduced funding to the aged care and health workforce by more than $1 billion this financial year (Herman, 2015). Herman (2015) adds that most doctors could experience a 20% reduction in Medicare reimbursements in 2016. This trend has worried stakeholders in the medical field because many people still depend on Medicare to cater for their medical expenses. In this regard, there have been suggestions to reduce the financial burden of diseases under the Medicare program by minimizing their occurrence through the adoption of preventive measures to cope with the declining funding (Herman, 2015). A long-term solution could be identifying the most common types of diseases diagnosed and treated under the Medicare plan and improving their management to reduce the burden on Medicare expenses. This strategy requires researchers to understand the incidence of diseases covered under the Medicare program. The findings of Data.CMS.gov (2011) could support a research problem that seeks to find out how to reduce the financial burden on the Medicare program in America. The supporting research questions would be to determine which diseases are most expensive to treat under the Medicare plan and to find out the diseases that most doctors treat under the Medicare plan.
The first research question seeks to understand the most expensive treatments under the Medicare plan. Analyzing the average Medicare payments would provide an accurate understanding of the most expensive treatments. Therefore, the main variable in the first research question would be the average Medicare payments. The second research question seeks to find out the most commonly treated diseases under the Medicare plan. The types of diagnoses made under the Medicare plan and the total discharges in the program would be the main variables. The confounding variables that could affect the outcomes of the relationships in the first and second research questions are the types of health care service providers and state variations in Medicare payments. These confounding factors reflect varying health care costs across American states and service providers. They could affect our understanding of the types of expenses under the Medicare plan.
When investigating how to reduce the incidence of diseases covered by the Medicare program, as a strategy of coping with reductions in Medicare funding, two more confounding variables emerge in this study. They are Medicare payments from out-of-network caregivers and Medicare payments through private health care plans. The statistics presented in Data.CMS.gov (2011) may fail to capture such data because they mainly focus on hospital-specific charges and in-patient prospective payment systems. Relying on such statistics alone to solve the research problem and failing to include Medicare payments from out of network caregivers and Medicare payments through private health care plans could prevent us from having a holistic understanding of the most expensive treatments under the Medicare plan and understanding the most commonly treated diseases under the same plan (Baum, 1995). My suggestion is that, based on the possible effects of the confounding variables, the findings that emerge from such an analysis should only be an indicator of possible strategies for reducing the financial burden of diseases under the Medicare plan and not finality of the same. In my experience, I have had access to inaccurate data from studies that recommend strategies for developing public health programs without considering the impact of confounding factors on the internal validity of the findings used to develop the recommendations in the first place. Such mistakes are avoidable. However, noting the importance of doing so, is it not also essential to measure the impact of the confounding variables to have a more accurate assessment of their impact on the findings?
References
Baum, F. (1995). Researching public health: Behind the qualitative-quantitative methodological debate. Social Science and Medicine, 40(4), 459468.
Data.CMS.gov. (2011). Inpatient prospective payment system (IPPS) provider summary for the top 100 diagnosis-related groups (DRG)FY2011 [Data file]. Web.
Herman, B. (2015). Obamas 2016 budget cuts Medicare but eliminates sequestration.
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