Happell Brenda, Platania-Phung Chris, Gaskin Cadeyrn J, Stanton Robert
Synergy, Nursing and Midwifery Research Centre University of Canberra, Faculty of Health and ACT Health, Canberra, Australia.
School of Medical and Applied Sciences, Central Queensland University, Bruce Highway, North Rockhampton, QLD, 4702, Australia.
BMC Psychiatry. 2016 Apr 19;16:109. doi: 10.1186/s12888-016-0814-9.
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.
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.
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%).
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.
与普通人群相比，患有严重精神疾病的人身体健康状况较差，在获得医疗保健方面存在差异，并且寿命明显缩短。常规代谢监测被提议作为一种识别代谢异常风险因素的方法。然而，迄今为止的努力表明，常规代谢监测既不完整也不规范。本研究报告了澳大利亚地区一家心理健康服务机构最近实施常规代谢监测表的情况。
对该心理健康服务机构中721名拥有电子健康记录的消费者进行回顾性档案审核。使用描述性统计方法报告代谢监测表的使用频率以及所记录的代谢参数范围。
消费者的平均年龄为41.4岁（标准差=14.6），超过一半为男性（58.4%），最常见的精神疾病诊断是精神分裂症（42.3%）。36%的消费者的代谢监测表包含数据。测量记录最常见的是体重（占表格的87.4%）、身高（85.4%）、血压（83.5%）和体重指数（73.6%）。脂质（胆固醇，56.3%；低密度脂蛋白，48.7%；高密度脂蛋白，51.7%；甘油三酯，55.2%）、肝功能（谷丙转氨酶，66.3%；谷草转氨酶，65.5%；γ-谷氨酰转肽酶，64.8%）、肾功能（尿素，66.3%；肌酐，65.9%）、空腹血糖（60.2%）和腰围（54.4%）的数据记录较少。
消费者电子健康记录中的代谢监测表未得到充分利用，未能最大限度发挥其潜力。缺失数据的程度表明，大多数消费者的代谢健康可能未得到充分监测。解决完成率低的可能原因，有可能改善对精神疾病患者的身体健康护理。
