Productivity Analysis in Healthcare System Essay

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Productivity analysis is important in any industry but is arguably critical in healthcare. Whereas low productivity of a single company may lead to its stagnation, decline, and bankruptcy, low productivity of the healthcare system may result in dire consequences for the whole nation. Productivity in healthcare can be expressed through various public health-related and financial metrics — health expenditures per capita, return on assets or live births and hospital beds per certain number of residents. However, regardless of selected methods and metrics, analyzing healthcare productivity is essential for several reasons.

Firstly, productivity analysis makes it possible to evaluate the effectiveness and benefits of reforms in healthcare. For example, a quantitative study by Chai et al. (2020) revealed that the overall productivity of the Chinese healthcare system deteriorated after the launch of nationwide healthcare reform in 2009. Only nine provinces became more productive, while twenty-two experienced a decline in productivity (Chai et al., 2020). In this regard, the productivity analysis showed an actual ineffectiveness of healthcare reform. Such feedback is especially valuable since it prevents the false sense of accomplishment from emerging. On the other hand, productivity analysis can confirm the benefits from certain changes in the healthcare system. Wang et al. (2018) analyzed 3266 unique hospital observations in the United States and demonstrated the direct positive influence of IT investments in healthcare. On average, a $1 million increase in operating IT investments resulted in a $130,339 increase in net income (Wang et al., 2018). In such cases, financial benefits confirmed by productivity analysis can become a decisive argument for technological modernization in healthcare.

Secondly, productivity analysis may also assist with revealing fundamental issues in the healthcare system. For instance, Chai et al. (2020) managed to establish a connection between the negative influence of Chinese healthcare reform on productivity and the decline in the scale of technological change. Only the rich and technologically advanced provinces — Beijing, Shanghai, and Tianjin achieved substantial growth in productivity (Chai et al., 2020). Furthermore, the authors confirmed the negative consequences of the formal health technology assessment (HTA) absence (Chai et al., 2020). Without the HTA in place, the Chinese healthcare industry was flooded with new technologies of questionable effectiveness. In addition, the researchers pointed at the inefficiency of resource concentration on tertiary hospitals (Chai et al., 2020). Overall, the productivity analysis provided quantitative data, necessary for highlighting the reasons that led to unexpected negative results of nationwide reform.

Lastly, productivity analysis can uncover potential areas for further improvement in the healthcare system. For example, Xenos et al. (2017) confirmed the leading role of technological advancement in Greek public hospitals’ recovery from the 2009-2012 economic crisis. Technology change during the managerial and financing healthcare reforms led to a noticeable increase in productivity. However, Xenos et al. (2017) also pointed at the fact that certain Greek hospitals operated under decreasing returns to scale. In this case, productivity analysis offered a potential solution of reducing capacity for achieving better efficiency rates.

In summary, one can claim that the advantages provided by the productivity analysis in healthcare make it a beneficial, if not a mandatory practice. Most importantly, it helps in making an informed judgment whether the healthcare system is developing in the right direction. Consequently, productivity analysis uncovers malfunctioning elements that may thwart healthcare reforms. Finally, the practice of productivity analysis serves as a source of insights into potential steps for the future development of successful reforms.

References

Chai, P., Zhang, Y., Zhou, M., Liu, S., & Kinfu, Y. (2020). . Health Policy and Planning, 35(3), 257-266.

Wang, T., Wang, Y., & McLeod, A. (2018). International Journal of Accounting Information Systems, 28, 1-13.

Xenos, P., Yfantopoulos, J., Nektarios, M., Polyzos, N., Tinios, P., & Constantopoulos, A. (2017). . Cost Effectiveness and Resource Allocation, 15(1), 1-12.

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