Wen Liu1, Jingcheng Shi1, Simin He1, Xi Luo1, Weijun Zhong2, Fang Yang1. 1. Xiangya School of Public Health, Central South University, Changsha, China. 2. Center for Information Statistics, Health Commission of Hunan Province, Changsha, China.
Abstract
AIM: Shortening the length of stay (LOS) is a potential and sustainable way to relieve the pressure that type 2 diabetes mellitus (T2DM) patients placed on the public health system. METHOD: Multi-stage random sampling was used to obtain qualified hospitals and electronic medical records for patients discharged with T2DM in 2018. A box-cox transformation was adopted to normalize LOS. Multilevel model was used to verify hospital cluster effect on LOS variations and screen potential factors for LOS variations from both individual and hospital levels. RESULT: 50 hospitals and a total of 12,888 T2DM patients were included. Significant differences in LOS variations between hospitals, and a hospital cluster effect on LOS variations (t = 92.188, P<0.001) was detected. The results showed that female patients, patients with new rural cooperative' medical insurance, hospitals with more beds, and hospitals with faster bed turnovers had shorter LOS. Conversely, elderly patients, patients with urban workers' medical insurance, patients requiring surgery, patients with the International Classification of Diseases coded complication types E11.1, E11.2, E11.4, E11.5, and other complications cardiovascular diseases, grade III hospitals, hospitals with a lower doctor-to-nurse ratio, and hospitals with more daily visits per doctor had longer LOS. CONCLUSIONS: The evidence proved that hospital cluster effect on LOS variation did exist. Complications and patients features at individual level, as well as organization and resource characteristics at hospital level, had impacted LOS variations to varying degrees. To shorten LOS and better meet the medical demand for T2DM patients, limited health resources must be allocated and utilized rationally at hospital level, and the patients with the characteristics of longer LOS risk must be identified in time. More influencing factors on LOS variations at different levels are still worth of comprehensive exploration in the future.
AIM: Shortening the length of stay (LOS) is a potential and sustainable way to relieve the pressure that type 2 diabetes mellitus (T2DM) patients placed on the public health system. METHOD: Multi-stage random sampling was used to obtain qualified hospitals and electronic medical records for patients discharged with T2DM in 2018. A box-cox transformation was adopted to normalize LOS. Multilevel model was used to verify hospital cluster effect on LOS variations and screen potential factors for LOS variations from both individual and hospital levels. RESULT: 50 hospitals and a total of 12,888 T2DM patients were included. Significant differences in LOS variations between hospitals, and a hospital cluster effect on LOS variations (t = 92.188, P<0.001) was detected. The results showed that female patients, patients with new rural cooperative' medical insurance, hospitals with more beds, and hospitals with faster bed turnovers had shorter LOS. Conversely, elderly patients, patients with urban workers' medical insurance, patients requiring surgery, patients with the International Classification of Diseases coded complication types E11.1, E11.2, E11.4, E11.5, and other complications cardiovascular diseases, grade III hospitals, hospitals with a lower doctor-to-nurse ratio, and hospitals with more daily visits per doctor had longer LOS. CONCLUSIONS: The evidence proved that hospital cluster effect on LOS variation did exist. Complications and patients features at individual level, as well as organization and resource characteristics at hospital level, had impacted LOS variations to varying degrees. To shorten LOS and better meet the medical demand for T2DM patients, limited health resources must be allocated and utilized rationally at hospital level, and the patients with the characteristics of longer LOS risk must be identified in time. More influencing factors on LOS variations at different levels are still worth of comprehensive exploration in the future.
Authors: S Manoukian; S Stewart; S Dancer; N Graves; H Mason; A McFarland; C Robertson; J Reilly Journal: J Hosp Infect Date: 2018-06-11 Impact factor: 3.926
Authors: Mamta Ruparel; Jose Luis López-Campos; Ady Castro-Acosta; Sylvia Hartl; Francisco Pozo-Rodriguez; C Michael Roberts Journal: ERJ Open Res Date: 2016-03-05