...
首页> 外文期刊>International Journal of Population Data Science >Under-coding of secondary conditions in coded hospital health data: impact of co-existing conditions, death status and number of codes in a record
【24h】

Under-coding of secondary conditions in coded hospital health data: impact of co-existing conditions, death status and number of codes in a record

机译:编码的医院健康数据中的二级条件编码不足:共存条件,死亡状况和记录中编码数量的影响

获取原文
           

摘要

ABSTRACTObjectivesAdministrative health data including hospital discharge abstract data have been widely collected and analyzed for various purposes, including disease surveillance, case-mix costing, tracking healthcare system performance, policy-making and research. This study examined the coding validity of hypertension, diabetes, obesity and depression related to the presence of their co-existing conditions, death status and number of diagnosis codes in hospital discharge abstract data (DAD). ApproachWe randomly selected around 4000 DAD records from four teaching hospitals in Alberta, Canada and reviewed their charts to extract 31 conditions listed in Charlson and Elixhauser comorbidity indices. Conditions associated with the four study conditions were identified through multivariable logistic regression. We examined the coding validity of the four study conditions related to whether their co-existing conditions were coded, whether the patient died in hospital and the total number of diagnosis codes recorded in a DAD record.Results Hypertension, diabetes, obesity and depression are generally secondary diagnosis and their validity are affected by the coding of their co-existing conditions. The sensitivity for the four conditions increased as the total number of diagnosis codes in the record increased. The impact of death status on coding validity for the four conditions was minimal.ConclusionThe coding validity of conditions is closely related to its clinical importance and complexity of patients’ case mix. We recommend mandatory coding of certain secondary diagnosis to meet the need of health research based on administrative health data.
机译:摘要目的已经广泛收集和分析了包括医院出院摘要数据在内的行政健康数据,并出于各种目的进行了分析,包括疾病监测,病例组合成本,跟踪医疗保健系统的绩效,决策和研究。这项研究检查了在出院摘要数据(DAD)中与高血压,糖尿病,肥胖和抑郁症的共存状况,死亡状况和诊断代码的数量有关的编码有效性。方法我们从加拿大艾伯塔省的四家教学医院中随机选择了约4000条DAD记录,并审查了他们的图表以提取Charlson和Elixhauser合并症指数中列出的31种疾病。通过多变量逻辑回归确定与四种研究条件相关的条件。我们检查了四种研究条件的编码有效性,这些条件与是否共存条件,患者是否在医院死亡以及DAD记录中记录的诊断代码总数有关。结果高血压,糖尿病,肥胖和抑郁症通常二级诊断及其有效性受其共存条件编码的影响。随着记录中诊断代码总数的增加,这四个条件的灵敏度也随之提高。死亡状况对这四个条件下编码有效性的影响微乎其微。结论条件编码的有效性与其临床重要性和患者病例组合的复杂性密切相关。我们建议对某些二级诊断进行强制编码,以满足基于管理健康数据的健康研究需求。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号