BackgroundHuman behavior is recognized as the main factor in the occurrence of accidents (70–90 percent), with human personality and problem solving ability as two related factors in the occurrence of medical errors (annually 42.7 million in the world). The objectives of this study were to investigate the relationship between personality factors, problem solving ability and medical errors.Material and methodsThis study was a questionnaire case control study. Information on 49 members of medical and nursing staff with medical errors (case group) and 46 without medical errors (control group) were analyzed. To collect the data, two Heppner problem solving questionnaires and the NEO-Five Factor Inventory were used, which were completed by the study population.ResultsThe results illustrate that individuals without medical errors showed higher scores in contentiousness, extraversion and agreeableness and lower scores in neuroticism than those with medical errors. Individuals without medical errors also showed higher scores in problem solving ability scales than those with medical errors.ConclusionResults of this study, suggest that personality factors and problem solving ability are related to medical errors and it may be possible for hospital authorities to use this knowledge when selecting capable medical staff.

PurposeThere is not enough comprehensive evidence on factors affecting hospital costs and revenue (HCR). The main objective of the current study is to identify and classify factors affecting HCR integrating experts' opinions and literature review.Design/methodology/approachFirst, a restricted literature review is conducted to identify the factors affecting HCR. In the second step, the targeted semi-structured interviews are conducted with 15 experts to identify, validate and classify the latent factors.FindingsIn addition to the factors identified through the literature review, 22 new important factors were added by the experts as the determinants of HCR, which were not pointed out in previous studies. The final model presented for the factors affecting HCR contains seven main groups, 22 subgroups and 70 variables.Originality/valueFactors affecting HCR will provide valuable contributions for hospital budgeting, and financial and strategic planning, and they will offer an effective horizon for future research on cost-cutting strategies.

A B S T R A C TNowadays, nurses scheduling is one of the most important challenges with which health care centers are encountered. The significance of nurses' work quality has led researchers to be concerned about scheduling problems, which have an impact on nurses' performance. Observing the interests of hospital and patients, providing their satisfaction, and meeting their needs are among the main objectives of scheduling, which are focused on in this research. For this end, goal programming is used for modeling and problem solving of the nurses scheduling process. Hence, a developed comprehensive model with 7 goals related to management aspects and nurses' interests have been designed considering emergency department characteristics of a large hospital in Tehran as a case study. Finally, the model was solved via GAMS software. The model resulted in an optimal pattern for nurses scheduling in a 28-days horizon. According to the definition presented in the modeling process, 3 goals associated with proportion, sequence, and isolation of working days were fulfilled. However, 4 goals of nurses' interests, number of working days, and isolate off days have illustrated a few deviations due to resource limitation. In addition, a comparison between the results and the current scheduling indicated a higher efficiency of optimal scheduling. Sensitivity analysis of the nurses scheduling also revealed that with an increase in the number of nurses, the goals would improve significantly. Implementation of this scheduling not only improves work justice and performance of the nurses but also increases their satisfaction from the scheduling process. NOMENCLATUREI Days index U The maximum working day for each nurse J Working shifts index d  Positive deviation from a goal K Nurses index d  Negative deviation from a goal N Number of days Q Minimum number of night shift for each nurse , , i j k X Binary decision variable to show kth nurse situation in jth shift of ith day W Maximum number of night shift for each nurse M Number of nurses Greek Symbols , i j D Nurses requirement for ith day and jth shift , , i j k  Random variable to show kth nurse preference to work in ith day and jth shift L The minimum working day for each nurse , i k  Random variable to show kth nurse preference to be off in ith day

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