Muratov Sergei, Lee Justin, Holbrook Anne, Paterson J Michael, Guertin Jason R, Mbuagbaw Lawrence, Gomes Tara, Khuu Wayne, Pequeno Priscila, Tarride Jean-Eric
Department of Health Research Methods, Evidence, and Impact (Muratov, Lee, Holbrook, Mbuagbaw, Tarride) and Divisions of Geriatric Medicine (Lee) and Clinical Pharmacology and Toxicology (Holbrook), Department of Medicine, McMaster University, Hamilton, Ont.; ICES (Paterson, Gomes, Khuu, Pequeno), Toronto, Ont.; Département de médecine sociale et préventive (Guertin), Faculté de médecine, and Centre de recherche du Centre hospitalier universitaire de Québec (Guertin), Axe Santé des populations et pratiques optimales en santé, Université Laval, Québec, Que.; Li Ka Shing Knowledge Institute (Gomes), St. Michael's Hospital, Toronto, Ont.; Centre for Health Economics and Policy Analysis (Tarride) and Department of Family Medicine (Paterson), McMaster University, Hamilton, Ont.
CMAJ Open. 2019 Aug 25;7(3):E537-E545. doi: 10.9778/cmajo.20180185. Print 2019 Jul-Sep.
Most health care spending is concentrated within a small group of high-cost health care users. To inform health policies, we examined the characteristics of index hospital admissions and their predictors among incident older high-cost users compared to older non-high-cost users in Ontario.
Using Ontario administrative data, we identified incident high-cost users aged 66 years or more and matched them 1:3 on age, gender and Local Health Integration Network with non-high-cost users aged 66 years or more. We defined high-cost users as patients within the top 5% most costly high-cost users during fiscal year 2013/14 but not during 2012/13. An index hospital admission, the main outcome, was defined as the first unplanned hospital admission during 2013/14, with no hospital admissions in the preceding 12 months. Descriptively, we analyzed the attributes of index hospital admissions, including costs. We identified predictors of index hospital admissions using stratified logistic regression.
Over half (95 375/175 847 [54.2%]) of all high-cost users had an unplanned index hospital admission, compared to 8838/527 541 (1.7%) of non-high-cost users. High-cost users had a poorer health status, longer acute length of stay (mean 7.5 d v. 2.9 d) and more frequent designation as alternate level of care before discharge (20.8% v. 1.7%) than did non-high-cost users. Ten diagnosis codes accounted for roughly one-third of the index hospital admission costs in both cohorts. Although many predictors were similar between the cohorts, a lower risk of an index hospital admission was associated with residence in long-term care, attachment to a primary care provider and recent consultation by a geriatrician among high-cost users.
The high prevalence of index hospital admissions and the corresponding costs are a distinctive feature of incident older high-cost users. Improved access to specialist outpatient care, home-based social care and long-term care when required are worth further investigation.
大部分医疗保健支出集中在一小部分高成本医疗保健使用者身上。为了为卫生政策提供信息，我们研究了安大略省新出现的老年高成本使用者与老年非高成本使用者相比，指数住院的特征及其预测因素。
利用安大略省的行政数据，我们确定了66岁及以上的新出现的高成本使用者，并将他们与66岁及以上的非高成本使用者按年龄、性别和地方卫生整合网络进行1:3匹配。我们将高成本使用者定义为在2013/14财政年度但不在2012/13财政年度中成本最高的前5%的患者。主要结局指数住院被定义为2013/14期间的首次非计划住院，且在之前12个月内无住院记录。描述性地，我们分析了指数住院的属性，包括费用。我们使用分层逻辑回归确定指数住院的预测因素。
所有高成本使用者中超过一半（95375/175847[54.2%]）有非计划的指数住院，而非高成本使用者中这一比例为8838/527541（1.7%）。与非高成本使用者相比，高成本使用者的健康状况较差，急性住院时间更长（平均7.5天对2.9天），出院前被指定为替代护理级别的频率更高（20.8%对1.7%）。在两个队列中，十个诊断代码约占指数住院费用的三分之一。尽管两个队列中的许多预测因素相似，但高成本使用者中指数住院风险较低与长期护理居住、与初级保健提供者的联系以及最近老年医学专家的会诊有关。
指数住院的高患病率及相应费用是新出现的老年高成本使用者的一个显著特征。改善专科门诊护理、家庭社会护理以及在需要时的长期护理的可及性值得进一步研究。
