Capitalising on opportunities: Malnutrition coding in hospital before and after the introduction of electronic health records with an embedded malnutrition screening tool
Author(s)
Vivanti, A
Lee, HC
Palmer, M
Griffith University Author(s)
Year published
2021
Metadata
Show full item recordAbstract
Background and aims: 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 ...
View more >Background and aims: 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. Methods: 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. Results: 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). Conclusions: 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.
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View more >Background and aims: 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. Methods: 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. Results: 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). Conclusions: 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.
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Journal Title
Clinical Nutrition ESPEN
Volume
41
Subject
Health services and systems
Public health