John Brower

CS875

Introduction

Attached is a copy of my unit 4 assignment. The cost of healthcare increases annually with significant federal and personal funds spent on hospitalizations (Baicker & Goldman, 2011). While this reference is outdated, it shows the concern expressed over a decade ago regarding the growth of medical expenses. The escalating costs are not a consequence of bed scarcity. In fact, the annual inpatient occupancy rate is 65% (Ravaghi et al., 2020). Most of the expense is related to pharmaceuticals, labor, and research and occurs in the latter years of life (Hosseini, 2015).

Scope

            Many in the healthcare industry believe more care will take place in the home and this socio-technology plan details an approach to in-home care with monitoring device technology. The are three domains required for complete integration. First are devices such as glucometers, smart scales, wearable devices. Second is the communication technology and the infrastructure of message transmission. Finally, the technology to analyze high-dimensional biometric data.

            There are several challenges associated with this integration. The biggest obstacle is the acceptance by healthcare providers to receive and act upon the information (Kuo, 2011). In an industry where legal jeopardy is one decision away, few providers will accept this data without legal protection and compensation.

Purpose

            The Affordable Care Act promised to control costs through a strategy of cost sharing between people with a low chance of requiring healthcare and higher risk and uninsured members of the community (Yang, 2013). Despite this law, the cost of health care continued to escalate with increasing costs of inpatient care and expensive pharmaceuticals leading the charge (Currin, 2020). In home monitoring technology and real time analysis offer the potential to act upon changes in care before a healthcare crisis emerges. Often the patient is left to their own care and self-report healthcare concerns. With the use of smart technologies in the home and machine learning algorithms, many of those hospitalizations are preventable.

 

References

Baicker, K., & Goldman, D. (2011). Patient Cost-Sharing and Healthcare Spending Growth. The Journal of Economic Perspectives, 25(2), 47-68. https://doi.org/10.1257/jep.25.2.47

 

Currin, L. L. (2020). The Rising Costs of Hospital Pharmaceutical Shortages and the Impact on Patient Care: Exploring the Use of Predictive Analytics in New York Area Hospitals.

 

Hosseini, H. (2015). Aging and the Rising Costs of Healthcare in the United States: Can There be a Solution? [Article]. Ageing International, 40(3), 229-247. https://doi.org/10.1007/s12126-014-9209-8

 

Kuo, A. M.-H. (2011). Opportunities and challenges of cloud computing to improve health care services. Journal of medical Internet research, 13(3), e67-e67. https://doi.org/10.2196/jmir.1867

 

Ravaghi, H., Alidoost, S., Mannion, R., & Bélorgeot, V. D. (2020). Models and methods for determining the optimal number of beds in hospitals and regions: a systematic scoping review. BMC health services research, 20(1), 186-186. https://doi.org/10.1186/s12913-020-5023-z

 

Yang, J. G. S. (2013). What is the Affordable Care Act of 2010? James G.S. Yang explains some details of the Patient Protection and Affordable Care Act of 2010 and offers tax planning strategies to alleviate the new tax burdens. Taxes (Chicago, Ill.), 91(12), 39.