Healthcare is increasingly becoming expensive for patients to afford. Despite a consistent use of healthcare products, the amount that patients have to pay for products have risen. Over the period of 2014 to 2018, Gary Claxton et al. of the Kaiser Family Foundation found that “inpatient prices for patients with private insurance rose about 13 percent compared to only 3 percent for patients with public insurers” (Claxton et al. 2018). Since the average price increase was isolated against the inflation in the US over this period, the implication of their analysis is that private insurance companies are driving up prices so that they can earn a higher profit. In addition, as private insurance companies continue to hike prices, Zack Cooper et al. also noted that market structure drives an even more exorbitant price difference where “hospital mergers are associated with even higher prices” (Cooper et al. 2014). The rise in prices not only decreases a patient’s access to necessary healthcare, like diagnostics, but it also makes evident a form of corruption in private insurance companies.
However, while the rise in healthcare prices are rampant and apparent, the mechanism is not yet clear as to exactly how insurance companies increase the prices that patients have to pay out-of-pocket. For these reasons, I have decided to study the relationship between current insurance policies in the Bay Area and the access to diagnostic tools by at-risk patients. This field of research is rich for exploration and will hold a wealth of information about how insurance and healthcare companies treat the Bay Area community. This ultimately leads me to my research question: Are coding defects a mechanism to the rise of healthcare prices in the Bay Area? What is the correlation between the number of coding defects and customer debt or satisfaction? Focusing on the specific perspective of healthcare providers, I hope to construct a clear narrative that discusses this complex relationship through the use of anecdotal evidence from Bay Area doctors and quantitative analysis in a controlled environment.