Comparison of physician referral and insurance claims data-based risk prediction as approaches to identify patients for care management in primary care: an observational study
Comparison of physician referral and insurance claims data-based risk prediction as approaches to identify patients for care management in primary care: an observational study
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DOI：
10.1186/1471-2296-14-157
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发表时间：
2013-10-20
影响因子：
2.9
通讯作者：
Szecsenyi, Joachim
中科院分区：
文献类型：
--
作者：
Freund, Tobias;Gondan, Matthias;Szecsenyi, Joachim
背景：以基层护理为基础的护理管理（CM）可以减少高危患者的住院率。由于CM的资源有限，需要确定最有可能受益的患者。本研究的目的是比较确定为CM无论是治疗初级保健医生（PCP）或住院风险（PM）的预测建模软件的患者住院和死亡率：方法：在2009年，一个队列的6,026名受益人的德国法定健康保险作为一个样本，患者识别CM的PCP或商业PM（CSSG 0.8，Verisk健康）。比较了2010年和患者选择前两年的住院率和死亡率。没有CM干预交付，直到2010年底和PCP盲住院率的评估rate.Results：在2010年，PM确定的患者的住院率为80%，高于PCP确定的患者。如果与PCP确定的患者相比，PM确定的患者的死亡率也高8%（10% vs. 2%）。由PM和PCP独立确定的患者的住院率在数值上介于PM和PCP确定的患者之间。2007年至2010年的时间趋势显示，PM确定的患者的住院率下降（每年-15%），而PCP确定的患者的住院率增加（每年+34%howlesshollows.Conclusions：PM确定的患者的住院率和死亡率高于PCP转诊患者。但后者显示随着时间的推移，住院率增加，从而表明PCP可能能够预测目前健康状况相对良好的患者未来的恶化。这些患者可能最有可能受益于CM等预防服务。
Background: Primary care-based care management (CM) could reduce hospital admissions in high-risk patients. Identification of patients most likely to benefit is needed as resources for CM are limited. This study aimed to compare hospitalization and mortality rates of patients identified for CM either by treating primary care physicians (PCPs) or predictive modelling software for hospitalization risk (PM).Methods: In 2009, a cohort of 6,026 beneficiaries of a German statutory health insurance served as a sample for patient identification for CM by PCPs or commercial PM (CSSG 0.8, Verisk Health). The resulting samples were compared regarding hospitalization and mortality rates in 2010 and in the two year period before patient selection. No CM-intervention was delivered until the end of 2010 and PCPs were blinded for the assessment of hospitalization rates.Results: In 2010, hospitalization rates of PM-identified patients were 80% higher compared to PCP-identified patients. Mortality rates were also 8% higher in PM-identified patients if compared to PCP-identified patients (10% vs. 2%). The hospitalization rate of patients independently identified by both PM and PCPs was numerically between PM-and PCP-identified patients. Time trend between 2007 and 2010 showed decreasing hospitalization rates in PM-identified patients (-15% per year) compared to increasing rates in PCP-identified patients (+34% per year).Conclusions: PM identified patients with higher hospitalization and mortality rates compared to PCP-referred patients. But the latter showed increasing hospitalization rates over time thereby suggesting that PCPs may be able to predict future deterioration in patients with relatively good current health status. These patients may most likely benefit from preventive services like CM.