Impact of the COVID-19 pandemic on hospital-based heart failure care in New South Wales, Australia: a linked data cohort study.

IF 2.7 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES
Daniel McIntyre, Desi Quintans, Samia Kazi, Haeri Min, Wen-Qiang He, Simone Marschner, Rohan Khera, Natasha Nassar, Clara K Chow
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引用次数: 0

Abstract

Background: Healthcare policy implemented during the COVID-19 pandemic may have impacted the health of patients with heart failure. Australian data provide a unique opportunity to examine service disruption independent of significant COVID-19 burden. This study aimed to examine heart failure care during the pandemic in New South Wales (NSW).

Methods: Analysis of hospital utilisation among patients aged ≥ 18 years with a primary diagnosis of heart failure conducted using linked administrative health records from hospital admission, emergency department, non-admitted services, and mortality data collections. Health service utilisation and outcomes were compared "Pre-pandemic" (PP): 16th March 2018 - 28th August 2019 and "During pandemic" (DP): 16th March 2020 - 28th August 2021. Mortality data were available until December 2021.

Results: Heart failure-related ED presentations and hospital admissions were similar between the periods (PP = 15,324 vs DP = 15,023 ED presentations, PP = 24,072 vs DP = 23,145 hospital admissions), though rates of admission from ED were lower DP (PP = 12,783/15,324 (83.4% [95% CI 82.8-84.0]) vs DP = 12,230/15,023 (81.4% [95% CI 80.8-82.0%]). There was no difference according to age, sex, rurality, or socioeconomic status. Outpatient volume reduced DP (PP = 44,447 vs DP = 35,801 occasions of service), but telehealth visits increased nearly threefold (PP = 5,978/44,447 (13.4% [95% CI 13.1-13.8%]) vs DP = 15,901/35,801 (44.4% [95% CI 43.9-44.9%]) with highest uptake among the wealthy and those in major cities. Time to heart failure-related ED presentation, hospitalisation or all-cause mortality following index admission was longer DP (PP = 273 [IQR 259, 290] days, DP = 323 [IQR 300, 342] days, HR 0.91 [95% CI 0.88, 0.95]).

Conclusions: Policies implemented DP had minimal impact on volumes of inpatient heart failure care in NSW hospitals, but there were fewer admissions from ED and reduced volumes of publicly funded outpatient care. A rapid shift from patient-facing to remotely delivered care enabled compliance with restrictions and was associated with increased time to heart failure-related adverse events, but access was not afforded equally across the socio-demographic spectrum.

COVID-19 大流行对澳大利亚新南威尔士州医院心力衰竭护理的影响:一项关联数据队列研究。
背景:COVID-19 大流行期间实施的医疗保健政策可能会影响心力衰竭患者的健康。澳大利亚的数据为我们提供了一个独特的机会,来研究与 COVID-19 的重大负担无关的服务中断情况。本研究旨在考察新南威尔士州(NSW)大流行期间的心力衰竭护理情况:方法:利用入院、急诊科、非入院服务和死亡数据收集中的关联行政健康记录,对年龄≥ 18 岁、主要诊断为心力衰竭的患者的医院使用情况进行分析。对 "大流行前"(PP):2018 年 3 月 16 日至 2019 年 8 月 28 日和 "大流行期间"(DP)的医疗服务利用率和结果进行了比较:2020 年 3 月 16 日至 2021 年 8 月 28 日。死亡率数据截至 2021 年 12 月:不同时期心衰相关的急诊室就诊人数和入院人数相似(PP = 15,324 对 DP = 15,023 急诊室就诊人数,PP = 24,072 对 DP = 23,145 入院人数),但急诊室入院率低于 DP(PP = 12,783/15,324 (83.4% [95% CI 82.8-84.0])对 DP = 12,230/15,023 (81.4% [95% CI 80.8-82.0%])。年龄、性别、乡村或社会经济地位没有差异。门诊量减少了远程医疗的使用率(PP = 44,447 vs DP = 35,801 次服务),但远程医疗的使用率增加了近三倍(PP = 5,978/44,447 (13.4% [95% CI 13.1-13.8%])vs DP = 15,901/35,801 (44.4% [95% CI 43.9-44.9%]),其中富人和大城市人群的使用率最高。指数入院后,心衰相关的急诊室就诊、住院或全因死亡时间均长于DP(PP = 273 [IQR 259, 290] 天,DP = 323 [IQR 300, 342] 天,HR 0.91 [95% CI 0.88, 0.95]):DP政策的实施对新南威尔士州医院心衰住院治疗量的影响微乎其微,但急诊室入院人数减少,公费门诊治疗量也有所下降。从面向患者到远程提供医疗服务的快速转变使人们能够遵守相关限制,并延长了心力衰竭相关不良事件的发生时间,但不同社会人口群体获得医疗服务的机会并不平等。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
BMC Health Services Research
BMC Health Services Research 医学-卫生保健
CiteScore
4.40
自引率
7.10%
发文量
1372
审稿时长
6 months
期刊介绍: BMC Health Services Research is an open access, peer-reviewed journal that considers articles on all aspects of health services research, including delivery of care, management of health services, assessment of healthcare needs, measurement of outcomes, allocation of healthcare resources, evaluation of different health markets and health services organizations, international comparative analysis of health systems, health economics and the impact of health policies and regulations.
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