Fulton Lawrence, Kruse Clemens Scott
Department of Health Administration, Texas State University, San Marcos, United States.
J Med Internet Res. 2019 Oct 29;21(10):e14609. doi: 10.2196/14609.
Hospital-based back surgery in the United States increased by 60% from January 2012 to December 2017, yet the supply of neurosurgeons remained relatively constant. During this time, adult obesity grew by 5%.
This study aimed to evaluate the demand and associated costs for hospital-based back surgery by geolocation over time to evaluate provider practice variation. The study then leveraged hierarchical time series to generate tight demand forecasts on an unobserved test set. Finally, explanatory financial, technical, workload, geographical, and temporal factors as well as state-level obesity rates were investigated as predictors for the demand for hospital-based back surgery.
Hospital data from January 2012 to December 2017 were used to generate geospatial-temporal maps and a video of the Current Procedural Terminology codes beginning with the digit 63 claims. Hierarchical time series modeling provided forecasts for each state, the census regions, and the nation for an unobserved test set and then again for the out-years of 2018 and 2019. Stepwise regression, lasso regression, ridge regression, elastic net, and gradient-boosted random forests were built on a training set and evaluated on a test set to evaluate variables important to explaining the demand for hospital-based back surgery.
Widespread, unexplained practice variation over time was seen using geographical information systems (GIS) multimedia mapping. Hierarchical time series provided accurate forecasts on a blind dataset and suggested a 6.52% (from 497,325 procedures in 2017 to 529,777 in 2018) growth of hospital-based back surgery in 2018 (529,777 and up to 13.00% by 2019 [from 497,325 procedures in 2017 to 563,023 procedures in 2019]). The increase in payments by 2019 are estimated to be US $323.9 million. Extreme gradient-boosted random forests beat constrained and unconstrained regression models on a 20% unobserved test set and suggested that obesity is one of the most important factors in explaining the increase in demand for hospital-based back surgery.
Practice variation and obesity are factors to consider when estimating demand for hospital-based back surgery. Federal, state, and local planners should evaluate demand-side and supply-side interventions for this emerging problem.
从2012年1月至2017年12月，美国以医院为基础的背部手术增加了60%，然而神经外科医生的数量相对保持稳定。在此期间，成人肥胖率增长了5%。
本研究旨在按地理位置和时间评估以医院为基础的背部手术的需求及相关成本，以评估医疗服务提供者的实践差异。该研究随后利用分层时间序列对一个未观察的测试集生成精确的需求预测。最后，研究财务、技术、工作量、地理和时间因素以及州一级的肥胖率等解释性因素，将其作为以医院为基础的背部手术需求的预测指标。
使用2012年1月至2017年12月的医院数据生成地理时空地图以及以数字63开头的现行手术操作术语编码索赔的视频。分层时间序列建模为每个州、人口普查区域和全国的一个未观察测试集提供预测，然后再次为2018年和2019年的未来年份提供预测。在一个训练集上构建逐步回归、套索回归、岭回归、弹性网络和梯度提升随机森林模型，并在一个测试集上进行评估，以评估对解释以医院为基础的背部手术需求重要的变量。
使用地理信息系统（GIS）多媒体映射可以看到随着时间推移广泛存在的、无法解释的实践差异。分层时间序列对一个盲数据集提供了准确的预测，并表明2018年以医院为基础的背部手术增长了6.52%（从2017年的497,325例手术增加到2018年的529,777例）（到2019年增长至13.00%[从2017年的497,325例手术增加到2019年的563,023例手术]）。预计到2019年支付增加3.239亿美元。极端梯度提升随机森林在一个20%的未观察测试集上击败了有约束和无约束回归模型，并表明肥胖是解释以医院为基础的背部手术需求增加的最重要因素之一。
在估计以医院为基础的背部手术需求时，实践差异和肥胖是需要考虑的因素。联邦、州和地方规划者应评估针对这一新兴问题的需求侧和供给侧干预措施。
