A Fuzzy Decision Making for Healthcare Administration

Decision making in a healthcare environment is challenging, especially during a period of uncertainty; equally important, healthcare administration leaders are expected to decide in a fuzzy environment. While decision making support systems have improved significantly, most of the support systems are multifaceted, complex, and disadvantageous (Bulut, Duru, Keçeci, & Yoshida, 2012). According to Bulut, Duru, Keçeci, and Yoshida (2012), decision supports systems have some flaws that affect decision-making process, including: “underestimation, optimism and limited capacity for concurrent analysis of multi-factor problems” (p. 1911). Accurately, making decisions that are unbiased and favorable in sequential decision making is complicated (Bulut, Duru, Keçeci, & Yoshida, 2012). Thus, support systems are insufficient for decision making.

Proper disposal of healthcare waste (HCW) is problematic for public sectors globally (Liu, Wu, & Li, 2013). HCW is increasing because of high demand for healthcare, population growth, and excessive availability of expendable medical device (Liu, Wu, & Li, 2013). HCW applies to population and animal-related waste in HSOs. Therefore, inappropriate discarding of HCW contributes to health problems that are detrimental to the environment and wellbeing (Liu, Wu, & Li, 2013). For example, healthcare leaders must ensure that HCW is appropriately discarded in appropriate containers to prevent wastes from HSO posing health hazards to patients, employees, and community. Likewise, healthcare leaders can use fuzzy decision making to help the organization decide which evidence-based treatment approach for disease condition are well-suited for standardization. Liu, Wu, and Li (2013) point out that Fuzzy theory is sufficient for addressing problems that are: “uncertain, imprecise, unspecific and fuzzy situation” (p. 2746). In essence, fuzzy decision making can help healthcare leaders streamline and optimize decision making during uncertainty.

References

Bulut, E., Duru, O., Keçeci, T., & Yoshida, S. (2012). Use of consistency index, expert prioritization and direct numerical inputs for generic fuzzy-AHP modeling: A process model for shipping asset management. Expert Systems with Applications, 39(2), 1911- 1923. doi:10.1016/j.eswa.2011.08.056

Liu, H., Wu, J., & Li, P. (2013). Assessment of health-care waste disposal methods using a VIKOR-based fuzzy multi-criteria decision making method. Waste Management, 33(12), 2744-2751. doi:10.1016/j.wasman.2013.08.006