Use of an electronic metabolic monitoring form in a mental health service - A retrospective file audit

Brenda HAPPELL, Chris PLATANIA-PHUNG, CADEYRN GASKIN, R Stanton

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

Background: People with severe mental illness have poorer physical health, experience disparities in physical health care, and lead significantly shorter lives, compared to the general population. Routine metabolic monitoring is proposed as a method of identifying risk factors for metabolic abnormalities. Efforts to date suggest routine metabolic monitoring is both incomplete and ad-hoc, however. This present study reports on the recent implementation of a routine metabolic monitoring form at a mental health service in regional Australia. Methods: A retrospective file audit was undertaken on 721 consumers with electronic health records at the mental health service. Descriptive statistics were used to report the frequency of use of the metabolic monitoring form and the range of metabolic parameters that had been recorded. Results: Consumers had an average age of 41.4 years (SD = 14.6), over half were male (58.4 %), and the most common psychiatric diagnosis was schizophrenia (42.3 %). The metabolic monitoring forms of 36 % of consumers contained data. Measurements were most commonly recorded for weight (87.4 % of forms), height (85.4 %), blood pressure (83.5 %), and body mass index (73.6 %). Data were less frequently recorded for lipids (cholesterol, 56.3 %; low density lipoprotein, 48.7 %; high density lipoprotein, 51.7 %; triglycerides, 55.2 %), liver function (alanine aminotransferase, 66.3 %; aspartate aminotransferase, 65.5 %; gamma-glutamyl transpeptidase, 64.8 %), renal function (urea, 66.3 %; creatinine, 65.9 %), fasting blood glucose (60.2 %), and waist circumference (54.4 %). Conclusions: The metabolic monitoring forms in consumer electronic health records are not utilised in a manner that maximises their potential. The extent of the missing data suggests that the metabolic health of most consumers may not have been adequately monitored. Addressing the possible reasons for the low completion rate has the potential to improve the provision of physical health care for people with mental illness.
Original languageEnglish
Article number109
Pages (from-to)1-8
Number of pages8
JournalBMC Psychiatry
Volume16
Issue number1
DOIs
Publication statusPublished - 2016

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Electronic Health Records
Mental Health Services
Delivery of Health Care
gamma-Glutamyltransferase
Health
Waist Circumference
HDL Lipoproteins
Aspartate Aminotransferases
Alanine Transaminase
LDL Lipoproteins
Mental Disorders
Blood Glucose
Urea
Fasting
Creatinine
Schizophrenia
Triglycerides
Body Mass Index
Cholesterol
Blood Pressure

Cite this

HAPPELL, Brenda ; PLATANIA-PHUNG, Chris ; GASKIN, CADEYRN ; Stanton, R. / Use of an electronic metabolic monitoring form in a mental health service - A retrospective file audit. In: BMC Psychiatry. 2016 ; Vol. 16, No. 1. pp. 1-8.
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abstract = "Background: People with severe mental illness have poorer physical health, experience disparities in physical health care, and lead significantly shorter lives, compared to the general population. Routine metabolic monitoring is proposed as a method of identifying risk factors for metabolic abnormalities. Efforts to date suggest routine metabolic monitoring is both incomplete and ad-hoc, however. This present study reports on the recent implementation of a routine metabolic monitoring form at a mental health service in regional Australia. Methods: A retrospective file audit was undertaken on 721 consumers with electronic health records at the mental health service. Descriptive statistics were used to report the frequency of use of the metabolic monitoring form and the range of metabolic parameters that had been recorded. Results: Consumers had an average age of 41.4 years (SD = 14.6), over half were male (58.4 {\%}), and the most common psychiatric diagnosis was schizophrenia (42.3 {\%}). The metabolic monitoring forms of 36 {\%} of consumers contained data. Measurements were most commonly recorded for weight (87.4 {\%} of forms), height (85.4 {\%}), blood pressure (83.5 {\%}), and body mass index (73.6 {\%}). Data were less frequently recorded for lipids (cholesterol, 56.3 {\%}; low density lipoprotein, 48.7 {\%}; high density lipoprotein, 51.7 {\%}; triglycerides, 55.2 {\%}), liver function (alanine aminotransferase, 66.3 {\%}; aspartate aminotransferase, 65.5 {\%}; gamma-glutamyl transpeptidase, 64.8 {\%}), renal function (urea, 66.3 {\%}; creatinine, 65.9 {\%}), fasting blood glucose (60.2 {\%}), and waist circumference (54.4 {\%}). Conclusions: The metabolic monitoring forms in consumer electronic health records are not utilised in a manner that maximises their potential. The extent of the missing data suggests that the metabolic health of most consumers may not have been adequately monitored. Addressing the possible reasons for the low completion rate has the potential to improve the provision of physical health care for people with mental illness.",
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Use of an electronic metabolic monitoring form in a mental health service - A retrospective file audit. / HAPPELL, Brenda; PLATANIA-PHUNG, Chris; GASKIN, CADEYRN; Stanton, R.

In: BMC Psychiatry, Vol. 16, No. 1, 109, 2016, p. 1-8.

Research output: Contribution to journalArticle

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T1 - Use of an electronic metabolic monitoring form in a mental health service - A retrospective file audit

AU - HAPPELL, Brenda

AU - PLATANIA-PHUNG, Chris

AU - GASKIN, CADEYRN

AU - Stanton, R

PY - 2016

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N2 - Background: People with severe mental illness have poorer physical health, experience disparities in physical health care, and lead significantly shorter lives, compared to the general population. Routine metabolic monitoring is proposed as a method of identifying risk factors for metabolic abnormalities. Efforts to date suggest routine metabolic monitoring is both incomplete and ad-hoc, however. This present study reports on the recent implementation of a routine metabolic monitoring form at a mental health service in regional Australia. Methods: A retrospective file audit was undertaken on 721 consumers with electronic health records at the mental health service. Descriptive statistics were used to report the frequency of use of the metabolic monitoring form and the range of metabolic parameters that had been recorded. Results: Consumers had an average age of 41.4 years (SD = 14.6), over half were male (58.4 %), and the most common psychiatric diagnosis was schizophrenia (42.3 %). The metabolic monitoring forms of 36 % of consumers contained data. Measurements were most commonly recorded for weight (87.4 % of forms), height (85.4 %), blood pressure (83.5 %), and body mass index (73.6 %). Data were less frequently recorded for lipids (cholesterol, 56.3 %; low density lipoprotein, 48.7 %; high density lipoprotein, 51.7 %; triglycerides, 55.2 %), liver function (alanine aminotransferase, 66.3 %; aspartate aminotransferase, 65.5 %; gamma-glutamyl transpeptidase, 64.8 %), renal function (urea, 66.3 %; creatinine, 65.9 %), fasting blood glucose (60.2 %), and waist circumference (54.4 %). Conclusions: The metabolic monitoring forms in consumer electronic health records are not utilised in a manner that maximises their potential. The extent of the missing data suggests that the metabolic health of most consumers may not have been adequately monitored. Addressing the possible reasons for the low completion rate has the potential to improve the provision of physical health care for people with mental illness.

AB - Background: People with severe mental illness have poorer physical health, experience disparities in physical health care, and lead significantly shorter lives, compared to the general population. Routine metabolic monitoring is proposed as a method of identifying risk factors for metabolic abnormalities. Efforts to date suggest routine metabolic monitoring is both incomplete and ad-hoc, however. This present study reports on the recent implementation of a routine metabolic monitoring form at a mental health service in regional Australia. Methods: A retrospective file audit was undertaken on 721 consumers with electronic health records at the mental health service. Descriptive statistics were used to report the frequency of use of the metabolic monitoring form and the range of metabolic parameters that had been recorded. Results: Consumers had an average age of 41.4 years (SD = 14.6), over half were male (58.4 %), and the most common psychiatric diagnosis was schizophrenia (42.3 %). The metabolic monitoring forms of 36 % of consumers contained data. Measurements were most commonly recorded for weight (87.4 % of forms), height (85.4 %), blood pressure (83.5 %), and body mass index (73.6 %). Data were less frequently recorded for lipids (cholesterol, 56.3 %; low density lipoprotein, 48.7 %; high density lipoprotein, 51.7 %; triglycerides, 55.2 %), liver function (alanine aminotransferase, 66.3 %; aspartate aminotransferase, 65.5 %; gamma-glutamyl transpeptidase, 64.8 %), renal function (urea, 66.3 %; creatinine, 65.9 %), fasting blood glucose (60.2 %), and waist circumference (54.4 %). Conclusions: The metabolic monitoring forms in consumer electronic health records are not utilised in a manner that maximises their potential. The extent of the missing data suggests that the metabolic health of most consumers may not have been adequately monitored. Addressing the possible reasons for the low completion rate has the potential to improve the provision of physical health care for people with mental illness.

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