Analysis of Discharged Patients from the Urology Department of a Tertiary Hospital in Ningbo from 2015 to 2020
Objectives This study aims to analyze the main diseases and surgical procedures of inpatients in the Department of Urology of a tertiary hospital in Ningbo City to provide a reference for the development of urology and the rational allocation of medical and health resources.Methods 57,798 inpatients in the Urology department were collected from January 1,2015 to December 31,2020.SPSS 24.0 and EXCEL software were used to perform descriptive statistical analysis on the basic information data and Chi-square on the composition of major diseases and surgeries.Results The male-to-female ratio of hospitalized patients was 3.63∶1.86.12％of the patients were from Ningbo City,and there were 28,219 patients aged 60 and above,accounting for 48.82％.The top five diseases were urinary calculus(24.36％),endocrine therapy for prostate cancer(17.90％),excessive foreskin,phimosis(8.20％),prostatic hyperplasia(5.93％),and renal cyst(2.4％).The top five surgical procedures were percutaneous nephroscopy and ureteroscopy lithotripsy(37.27％),circumcision(17.55％),transurethral resection of the prostate(7.87％),and laparoscopic renal cyst removal(4.51％),transurethral resection of bladder lesions(3.30％).There were more male patients than female patients with the top five diseases and surgical procedures,and the difference was statistically significant(P＜0.001).There were statistically significant differences in age group composition among different types of diseases and surgeries(P＜0.05).Conclusions Early screening of urinary tract stones and prostate diseases in middle-aged and elderly people should be strengthened to achieve early detection,early diagnosis,and early treatment.For adolescents,hospitals should work with schools and communities to strengthen the popularization of physiological hygiene knowledge.In addition,hospitals should strengthen the construction of key disciplines and talent training in a targeted manner to further optimize resource allocation.
UrologyDominant diseaseClassification of diseasesConstituent analysis
NETL
NSTL
万方数据
