Children's Hospital of Eastern Ontario (CHEO) Inflammatory Bowel Disease Centre, Division of Gastroenterology, Hepatology and Nutrition, CHEO, Ottawa, Ontario, Canada; School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada.
SickKids Inflammatory Bowel Disease Center, Division of Gastroenterology, Hepatology and Nutrition, The Hospital for Sick Children, Toronto, Ontario Canada; Child Health Evaluative Sciences, SickKids Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada.
J Clin Epidemiol. 2022 Sep;149:23-35. doi: 10.1016/j.jclinepi.2022.05.006. Epub 2022 May 20.
Compare meta-analysis in a distributed network to individual-level analysis for assessment of time trends of health services utilization with health administrative data.
We used administrative data from Ontario, Canada to analyze temporal trends in pediatric inflammatory bowel disease health services use. Beta coefficients were obtained using negative binomial, logistic, and Cox proportional hazards regression models. We replicated the individual-level analyses in each Ontario Local Health Integration Network (LHIN), then meta-analyzed aggregate trends using both fixed and random effects meta-analysis. We compared the pooled estimates of effect with individual-level analysis.
Beta coefficients, summary effect estimates, and 95% confidence intervals (CIs) from the meta-analysis of data from distributed networks were not different than those from individual-level data, regardless of meta-analytic approach used. For example, the 5-year odds ratio of colectomy in ulcerative colitis using individual-level analysis was 0.978 (95% CI 0.950 to 1.007) compared to distributed network fixed effects meta-analysis: 0.982 (95% CI 0.950 to 1.015), and random effects meta-analysis: 0.982 (95% CI 0.950 to 1.015).
Meta-analysis of multi-jurisdictional estimates were similar to estimates obtained from individual-level analysis. This method is a valid alternative for analysis of multi-jurisdictional data when individual-level data cannot be shared.
将分布式网络中的荟萃分析与个体水平分析进行比较，以评估利用健康管理数据评估卫生服务利用的时间趋势。
我们使用来自加拿大安大略省的管理数据来分析儿科炎症性肠病卫生服务使用的时间趋势。使用负二项式、逻辑和 Cox 比例风险回归模型获得β系数。我们在每个安大略省当地卫生整合网络 (LHIN) 中复制个体水平分析，然后使用固定和随机效应荟萃分析对汇总趋势进行荟萃分析。我们将荟萃估计的效果与个体水平分析进行了比较。
无论使用何种荟萃分析方法，来自分布式网络的荟萃分析数据的β系数、汇总效果估计值和 95%置信区间 (CI) 与个体水平数据没有差异。例如，使用个体水平分析溃疡性结肠炎 5 年结肠切除术的 5 年odds 比为 0.978 (95%CI 0.950 至 1.007)，而与分布式网络固定效应荟萃分析相比：0.982 (95%CI 0.950 至 1.015)，随机效应荟萃分析：0.982 (95%CI 0.950 至 1.015)。
多司法管辖区估计的荟萃分析与个体水平分析得出的估计值相似。当无法共享个体水平数据时，这种方法是分析多司法管辖区数据的有效替代方法。
