the Department of Family Medicine and the Division of Primary Care, Department of Internal Medicine, Mayo Clinic, Rochester, MN.
J Am Board Fam Med. 2013 Nov-Dec;26(6):745-50. doi: 10.3122/jabfm.2013.06.120340.
Overweight and obese individuals have increased health risks. Clinical reminders positively affect health outcomes in diabetes and osteoporosis, but the effect of automated prompts on weight loss in obesity has not been studied. Our objective was to determine whether an automatic prompt for the clinician to recommend lifestyle changes to patients with a body mass index (BMI) >25 kg/m(2) led to greater weight loss over a 3- to 6-month interval compared with the absence of a clinical reminder.
We conducted a retrospective analysis of electronic medical records of obese adult patients with a BMI >25 kg/m(2) who were seen in 2009 and 2010, before and after implementation of an automated printed clinical reminder, respectively. We evaluated 1600 patients in each of the control and intervention groups. The primary outcome was the mean change in BMI between the control and intervention groups. Multiple linear regression was used to assess the effect of the clinical reminder on the change in BMI while adjusting for baseline BMI and potential confounding factors.
The reduction in BMI (mean ± standard deviation) in the group with the clinical reminder (-0.084 ± 1.56 kg/m(2)) was not significantly greater than the control group (-0.053 ± 1.49 kg/m(2); P = .56). A regression model incorporating the clinical reminder, age, baseline BMI, obesity diagnosis, diabetes, and hyperlipidemia found that baseline BMI (P < .001), obesity diagnosis (P < .001), age (P = .001), and hyperlipidemia diagnosis (P = .02) were significant predictors of weight loss, but the clinical reminder was not (P = .78). There was a significant interaction between the clinical reminder and baseline BMI (P = .005), as the prompt increased weight loss more in those with lower baseline BMI.
Automated clinical reminders alone do not improve weight loss in overweight and obese patients. Physician diagnoses of obesity or hyperlipidemia were associated with weight loss, suggesting that formally noting these diagnoses contributes to successful weight loss.
超重和肥胖个体的健康风险增加。临床提示可积极影响糖尿病和骨质疏松症的健康结果，但自动化提示对肥胖患者减肥的影响尚未得到研究。我们的目的是确定向 BMI（体重指数）>25kg/m²的患者自动提示建议生活方式改变是否会导致 3 至 6 个月的体重减轻比缺乏临床提示更大。
我们对 2009 年和 2010 年分别在实施自动化打印临床提示前后接受过治疗的肥胖成年患者进行了电子病历的回顾性分析。我们分别评估了对照组和干预组各 1600 名患者。主要结局是对照组和干预组之间 BMI 的平均变化。使用多元线性回归来评估临床提示对 BMI 变化的影响，同时调整基线 BMI 和潜在混杂因素。
临床提示组（-0.084±1.56kg/m²）的 BMI 降低幅度（均值±标准差）与对照组（-0.053±1.49kg/m²）相比没有显著差异（P=.56）。包含临床提示、年龄、基线 BMI、肥胖诊断、糖尿病和高脂血症的回归模型发现，基线 BMI（P<.001）、肥胖诊断（P<.001）、年龄（P=.001）和高脂血症诊断（P=.02）是体重减轻的显著预测因素，但临床提示不是（P=.78）。临床提示和基线 BMI 之间存在显著的交互作用（P=.005），提示提示在基线 BMI 较低的患者中更能促进体重减轻。
单独使用自动化临床提示并不能改善超重和肥胖患者的体重减轻。医生对肥胖或高脂血症的诊断与体重减轻相关，这表明正式记录这些诊断有助于成功减肥。
