Multimorbidity characteristics in elderly inpatients and their associated factors in complex networks: a cross-sectional study (preprint)

Background Multimorbidity of chronic diseases has become an increasingly serious public health problem. However, the research on the current situation of multimorbidity in the elderly in Jiangsu, China is relatively lacking. Methods We surveyed a total of 229,926 inpatients aged above 60 and with two or more chronic diseases in the First Affiliated Hospital with Nanjing Medical University from January 1, 2015 to December 31, 2021. The Apriori algorithm was used to analyze the association rules of the multimorbidity patternsin old adults. Results The mean age of these patients was 72.0±8.7 years, and the male-to-female ratio was 1:1.53. These patients during the COVID-19 period(from 2020 to 2021) displayed younger, higher male rate, shorter median length of hospital stay, higher ≥6 multimorbidities rate and lower median cost than those not during the COVID-19 period (from 2015 to 2019). In all of these patients, the top 5 chronic diseases were "Hypertensive diseases(I10-I15)", "Other forms of heart disease(I30-I52)", "Diabetes mellitus(E10-E14)", "lschaemic heart diseases(I20-I25)" and "Cerebrovascular diseases(I60-I69)". The complex networks of multimorbidity showed that Hypertensive diseases had a higher probability of co-occurrence with multiple diseases in all these patients, followed by Diabetes mellitus, Other forms of heart disease, and lschaemic heart diseases(I20-I25). Conclusion In conclusion, the patterns of multimorbidity among the aged varied by COVID-19. Our results highlighted the importance of control of hypertensive diseases, diabetes, and heart disease in gerontal patients. More efforts to improve the understanding of multimorbidity patterns would help us develop new clinical and family care models.

AI based satisfaction survey of patients in fever clinics during the outbreak of COVID-19 (preprint)

Background: We assessed patient by automated survey method in understanding and satisfaction with the use of fever clinic, and observed the effectiveness of this method. Methods: Total 873 patients in fever clinc at Jiangsu Province Hospital (JSPH) from 20 January 2019 to 18 June 2020 were investigated by an antomated survey method conbined by Wechat, Short Message Service (SMS) and AI voice call. Responses were assessed for overall positivity or negativity and further compared according to patients types (isolated patients and non-isolated patients). Responses were also described and compared for each type of survey. Results: A total of 379 patient surveys were returned, for a total response rate of 43.4%. Isolated and non-isolated patients responses were similar and all with more than 90% satisfaction. Most isolated patient represent that the medical staff had explained to them the reason for the isolation and know that can helps prevent COVID-19. AI voice calls had the highest percentage of all response types, followed by WeChat and SMS. Conclusion: The patient has a positive response to the use of fever clinic. The automated survey method combine by different survey types can bring great convenience to the investigation while ensuring good investigation efficiency.