Abstract

Background: administrative healthcare data are among main components of hospital information system. Such data can be analyzed and deployed for a variety of purposes. The principal aim of this research was to depict trends of administrative healthcare data from HIS in a general hospital from March 2011 to March 2014. Methods: data set used for this research was extracted from the SQL database of the hospital information system in Razi general hospital located in Marand. The data were saved as CSV (Comma Separated Values) in order to facilitate data cleaning and analysis. The variables of data set included patient’s age, gender, final diagnosis, final diagnosis code based on ICD-10 classification system, date of hospitalization, date of discharge, LOS(Length of Stay), ward, and survival status of the patient. Data were analyzed and visualized after applying appropriate cleansing and preparing techniques. Results: morbidity showed a constant trend over three years. Pregnancy, childbirth and the puerperium were the leading category of final diagnosis (about 32.8 %). The diseases of the circulatory system were the second class accounting for 13 percent of the hospitalization cases. The diseases of the digestive system had the third rank (10%). Patients aged between 14 and 44 constituted a higher proportion of total cases. Diseases of the circulatory system was the most common class of diseases among elderly patients (age≥65). The highest rate of mortality was observed among patients with final diagnosis of the circulatory system diseases followed by those with diseases of the respiratory system, and neoplasms. Mortality rate for the ICU and the CCU patients were 62% and 33% respectively. The longest average of LOS (7.3 days) was observed among patients hospitalized in the ICU while patients in the Obstetrics and Gynecology ward had the shortest average of LOS (2.4 days). Multiple regression analysis revealed that LOS was correlated with variables of surgery, gender, and type of payment, ward, the class of final diagnosis and age. Conclusion: this study presents trends in administrative health care data residing in hospital information system of a general public hospital. Patterns in morbidity, mortality and length of stay can inform decision making in health care management. Mining trends in administrative healthcare data can add value to the health care management.

Key words: Pattern, Administrative healthcare data, Hospital Information System