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| Big data analysis of the disease spectrum characteristics in the patients with emergency admission: based on the home data of 5.91 million hospital medical records of 169 comprehensive hospitals from 2015 to 2017 |
| Ding Bin, Dai Zhi-qiang, Teng Chun-xia, Du Yu-lei, Xue Feng, Chen Xiao-hong, Wang Jing, Wei Ling, Wei Cong |
| Zhong Wei Yun Institute of Medical Data Analytics & Application Technology, Beijing 100055, China |
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Abstract Objective In this paper, the distribution characteristics of hospital patients with emergency approach to hospital were discussed with big data technology, which provided the reference for emergency quality control and management. Methods The home data of 26.9277 million hospital medical records (Health system 4-1) of 169 comprehensive hospitals for 3 years (2015~2017) were gathered through the Zhong Wei Yun Medical Data Platform Network. The first page data of patients admitted to the hospital by emergency treatment were collected, and the disease spectrum and related characteristics were analyzed. Results The total number of patients emergency admitted to the hospital was 5.9181 million in the 169 hospitals, accounting for about 21.98%. The spectrum of patients with emergency admission was characterized by the following characteristics: ①The amount of data: There were obviously more patients admitted to the tertiary hospital than the secondary hospitals. However, the emergency admission ratio of the secondary hospital was higher than that in the tertiary hospital. The number of patients with emergency admission to the tertiary hospital was increasing year by year. But the emergency admission ratio in the proportion of total hospitalization of the secondary hospital presented an unstable trend and was slightly decreasing yearly. ②Number of diseases: The total coverage of disease spectrum reached the national requirements in the tertiary hospitals and secondary hospitals. The numbers and proportions of emergency treatment were slightly decreasing. ③The distribution of disease systems: The top five were circulatory disease(21.53%), some other consequences of injury and poisoning and external causes(14.27%), respiratory disease(11.70%), digestive diseases(10.74%), childbirth and puerperium(9.23%). ④The distribution of major diseases in patients with emergency admission: In the 13 major diseases associated with emergency care, acute myocardial infarction, acute stroke, adult pneumonia and acute pancreatitis were increased yearly. Half of the major diseases accounted for nearly 50% of total inpatients. ⑤Patient outcome: The fatality rate of patients with emergency admission was higher than that of total inpatients, no matter in secondary hospital or in tertiary hospital. The mortality rate of patients in tertiary hospital was higher than that in secondary hospital. The proportion of death emergency patients in the death hospitalized patients in the same period was about 50% and it was higher in secondary hospital. Conclusion The data volumes and the number of diseases and distribution of disease system of patients in tertiary hospital were better than that in secondary hospital. The mortality rate of patients in tertiary hospital was higher than that of secondary hospital. It indicated that state of illness is more difficult and serious in tertiary hospital in one aspect. And the proportion of death emergency patients in the death hospitalized patients in the same period was higher in secondary hospital. It suggested that the comprehensive treatment ability of secondary hospitals is inferior to that of tertiary hospital. The disease epidemiology investigation and analysis was carried out through the first page data of inpatient medical records, which had real and objective advantages. The establishment of medical big data platform lays the technical foundation for carrying out the investigation and analysis of epidemiology, enhancing emergency quality control and management.
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Corresponding Authors:
Chen Xiao-hong, E-mail: cxh70@126.com
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