Identifying acute kidney injury in the community-a novel informatics approach

被引:5
作者
Xu, Gang [1 ,4 ]
Player, Paul [1 ]
Shepherd, David [2 ,3 ]
Brunskill, Nigel J. [1 ,4 ,5 ]
机构
[1] Univ Hosp Leicester NHS Trust, Leicester, Leics, England
[2] Univ Leicester, Dept Hlth Sci, Leicester, Leics, England
[3] Leicester City Clin Commissioning Grp, Leicester, Leics, England
[4] Univ Leicester, Dept Infect Immun & Inflammat, Leicester, Leics, England
[5] Leicester Gen Hosp, Dept Nephrol, Gwendolen Rd, Leicester LE54PW, Leics, England
关键词
Acute kidney injury; Primary care; Medical informatics; HOSPITALIZED-PATIENTS; RECEPTOR BLOCKERS; OUTCOMES; EPIDEMIOLOGY; RISK; DISEASE; AKI;
D O I
10.1007/s40620-015-0190-4
中图分类号
R5 [内科学]; R69 [泌尿科学(泌尿生殖系疾病)];
学科分类号
1002 ; 100201 ;
摘要
Background Acute kidney injury (AKI) is a serious and common problem that is associated with high mortality. Currently nearly all efforts at improving outcomes in AKI have been focused on secondary care. We now know that a large number of patients most likely develop the condition in primary care. To our knowledge there has been no previous attempts to approach this topic from the primary care perspective. Aim To test the utility of novel informatics software to identify patients with AKI in the community. Setting and method We carried out a retrospective audit of patients in one urban practice in Leicestershire using novel informatics software. The audit data was run on two occasions, once for high-risk patients between 4th July 2010 through until 30th September 2013, and once for low risk patients for the period of 27th October 2011 through until 21st January 2014. Results During the period of the data collection the average practice list size was 12,420, with 235 and 19 AKI episodes in the high and low risk groups respectively. The annual AKI incidence was 27.9/1000 in the high-risk group, 1.22/1000 in the low risk group, and 10.6/1000 overall. The most common associated factor was sepsis in 170 patients, followed by dehydration in 54 patients. Conclusion We have shown it is possible to identify patients with AKI in the community using informatics software. Our data suggests that AKI in the community is much more common than previously thought and demonstrates the need to better understand this condition from the primary care perspective.
引用
收藏
页码:93 / 98
页数:6
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