Queensland Health, Nutrition & Dietetics, Princess Alexandra Hospital, Australia; University of Queensland, School of Human Movement and Nutrition Sciences, Australia.
University of Queensland, School of Human Movement and Nutrition Sciences, Australia.
Clin Nutr ESPEN. 2021 Feb;41:193-197. doi: 10.1016/j.clnesp.2020.11.012. Epub 2020 Dec 24.
During conversion from paper to electronic documentation at a tertiary hospital, the Malnutrition Screening Tool was embedded into the electronic health record (e-HR) with nursing staff's completion continued as part of admission procedures with dietetic referrals automated. Currently, the impact of e-HR implementation on malnutrition identification is unknown. Consequently, this retrospective pre-test post-test study compared one year of malnutrition coding in a tertiary teaching hospital two years before and after e-HR implementation automating malnutrition screening referrals to dietitians with subsequent malnutrition assessment completion.
Eligibility included adults (≥18yrs) admitted overnight or longer during the 2013/2014 and 2017/2018 financial years. Requested hospital data included demographics, admission data and coding for malnutrition and dietitian intervention. Eligible admissions prior to e-HR implementation were classified as pre-e-HR group, with admissions after classified as post-e-HR. Descriptive, Fisher's exact, Mann-Whitney U and independent samples t-tests were used to compare groups.
Patient admissions pre-e-HR (n = 37,143) and post-e-HR (n = 36,625) implementation were clinically similar in age, gender and length of stay (57 ± 19 years, 60% male, 3 (1-918) days). However, the numbers of admissions coded annually with malnutrition increased by 47% from 1436 to 2116 following e-HR implementation (p < 0.001). The proportion of eligible patients who were malnourished on admission and not seen by a dietitian during admission decreased one third from 6.5% to 4.8% (p = 0.042).
Malnutrition coding increased by 47% after an e-HR implementation with an embedded malnutrition screening tool that automated referrals to dietitians impacting the identification of care to optimize nutritional status.
在一家三级医院从纸质文档向电子文档转换的过程中,营养不良筛查工具嵌入到电子健康记录(电子病历)中,护理人员的完成情况继续作为入院程序的一部分,同时自动向营养师转介饮食建议。目前,电子病历实施对营养不良识别的影响尚不清楚。因此,这项回顾性预-后测试研究比较了在电子病历实施前两年(2013/2014 财年和 2017/2018 财年)和之后两年(2017/2018 财年和 2019/2020 财年),对一家三级教学医院的一年营养不良编码进行了比较,在此期间,电子病历实现了对营养师的营养不良筛查建议的自动化,随后完成了营养不良评估。
纳入标准包括在 2013/2014 财年和 2017/2018 财年期间过夜或更长时间住院的成年人(≥18 岁)。要求医院提供的数据包括人口统计学、入院数据以及营养不良和营养师干预的编码。在电子病历实施前符合条件的入院患者被归类为电子病历实施前组,而实施后符合条件的入院患者被归类为电子病历实施后组。采用描述性、Fisher 精确检验、Mann-Whitney U 检验和独立样本 t 检验对组间进行比较。
电子病历实施前(n=37143)和实施后(n=36625)的患者入院时在年龄、性别和住院时间方面临床相似(57±19 岁,60%为男性,3(1-918)天)。然而,电子病历实施后,每年被编码为营养不良的患者数量增加了 47%,从 1436 例增加到 2116 例(p<0.001)。在入院时营养不良且在入院期间未接受营养师诊治的合格患者比例从 6.5%下降到 4.8%(p=0.042),下降了三分之一。
电子病历实施后,营养不良编码增加了 47%,嵌入了营养不良筛查工具,该工具自动向营养师转介,从而提高了识别护理的能力,以优化营养状况。