Simulation of Quality Death Spirals based on Human Resources Dynamics.

Although the hospital managers always try to improve the quality of the medical services, sometimes their efforts might affect reversely and push the system in what is so commonly called as "the death spirals of quality." The most important reason of falling into these spirals is the lack of a systemic thought that considers the feedback relationships between the numerous effective variables in the system performance, such as human resources service capacity. In this regard, the purpose of the present research is to design and simulate a dynamic human resources service capacity-based model to demonstrate the death spirals of quality phenomenon based on the service time per service and the possibility of error generation along with identifying the policies to cope with them. The system dynamics simulation approach is used to show the dynamics of the capacity of service from the standpoint of human resources. A model is simulated for the services of a hospital clinic as a case study. The simulation results of the designed dynamic model express that applying the desired policies for the case study can provide a good basis for fighting these spirals in a dynamic situation.

Assessing the Relative Performance of Nurses Using Data Envelopment Analysis Matrix (DEAM).

Assessing employee performance is one of the most important issue in healthcare management services. Because of their direct relationship with patients, nurses are also the most influential hospital staff who play a vital role in providing healthcare services. In this paper, a novel Data Envelopment Analysis Matrix (DEAM) approach is proposed for assessing the performance of nurses based on relative efficiency. The proposed model consists of five input variables (including type of employment, work experience, training hours, working hours and overtime hours) and eight output variables (the outputs are amount of hours each nurse spend on each of the eight activities including documentation, medical instructions, wound care and patient drainage, laboratory sampling, assessment and control care, follow-up and counseling and para-clinical measures, attendance during visiting and discharge suction) have been tested on 30 nurses from the heart department of a hospital in Iran. After determining the relative efficiency of each nurse based on the DEA model, the nurses' performance were evaluated in a DEAM format. As results the nurses were divided into four groups; superstars, potential stars, those who are needed to be trained effectively and question marks. Finally, based on the proposed approach, we have drawn some recommendations to policy makers in order to improve and maintain the performance of each of these groups. The proposed approach provides a practical framework for hospital managers so that they can assess the relative efficiency of nurses, plan and take steps to improve the quality of healthcare delivery.