Developing An Analytical Model of Organizational Accountability for Healthcare Organizations

Background : Past studies on organizational accountability have has similar limitations. First, empirical evidence of organizational accountability is rare as the majority of research takes a conceptual approach of the topic. Next, only a few of these studies are applicable to health care organizations(HCOs). Last, even fewer studies can be applied to those in other countries from the US, as these countries have different healthcare delivery systems. To fill these gaps, we attempted to develop an analytical model of organizational accountability for HCOs.

Methods : Multiple methods, including (1) a systematic review of the literature on organizational accountability in the areas of policy, politics, and health administration, (2) focus group interviews with managers of HCOs in Korea, and (3) consultations from advisory committees were all used for our model building process.

Results : Hospitals accountability was conceptualized by two axes: answerability(X, horizontal) and value-creating(Y, vertical). Our concept building could relieve competing accountability mechanism which past studies stressed. Four elements of accountability(legal, economical, social, and clinical) were applied to specify each of the two features of organizational accountability. And then four types of accountability behavior were coordinated by this x-y axis: high A/high VC, high A/low VC, low A/high VC, low A/low VC. Next, a multidimensional model of HCOs' accountability, enabling an empirically testable multi-level analysis, was proposed. Finally, results of in-depth interviews suggested that Korean hospitals' efforts to create economical and clinical accountability were unsatisfying with respect to those for enhancing legal or community accountability.

Conclusion : Experts and the participants of the interviews provided supports for the applicability and practicability of our framework. Future studies to empirically test the relationships among the variables of the model we proposed are highly recommended.