The effect of physician density on colorectal cancer stage at diagnosis: causal inference methods for spatial data applied on regional-level data.

IF 3 2区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Dajana Draganic, Knut Reidar Wangen
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引用次数: 0

Abstract

Background: The early detection of colorectal cancer (CRC) through regular screening decreases its incidence and mortality rates and improves survival rates. Norway has an extremely high percentage of CRC cases diagnosed at late stages, with large variations across municipalities and hospital catchment areas. This study examined whether the availability of physicians related to CRC primary diagnosis and preoperative investigations, or physician density, contributes to the observed geographical differences in late-stage incidence rates.

Method: Municipality-level data on CRC stage at diagnosis were obtained from the Cancer Registry of Norway for the period 2012-2020. Physician density was calculated as the number of physicians related to CRC investigations, general practitioners (GPs) and specialists per 10,000 people, using physician counts per municipality and hospital areas from Statistics Norway. The relationship was examined using a novel causal inference method for spatial data-neighbourhood adjustment method via spatial smoothing (NA approach)-which allowed for studying the region-level effect of physician supply on CRC outcome by using spatially referenced data and still providing causal relationships.

Results: According to the NA approach, an increase in one general practitioner per 10,000 people will result in a 3.6% (CI -0.064 to -0.008) decrease in late-stage CRC rates. For specialists, there was no evidence of a significant correlation with late-stage CRC distribution, while for both groups, GPs and specialists combined, an increase of 1 physician per 10,000 people would be equal to an average decrease in late-stage incidence rates by 2.79% (CI -0.055 to -0.001).

Conclusion: The study confirmed previous findings that an increase in GP supply will significantly improve CRC outcomes. In contrast to previous research, this study identified the importance of accessibility to both groups of physicians-GPs and specialists. If GPs encounter insufficient workforces in hospitals and long delays in colonoscopy scheduling, they will less often recommend colonoscopy examinations to patients. This study also highlighted the efficiency of the novel methodology for spatially referenced data, which allowed us to study the effect of physician density on cancer outcomes within a causal inference framework.

Abstract Image

Abstract Image

医生密度对结肠直肠癌诊断分期的影响:应用于地区级数据的空间数据因果推理方法。
背景:通过定期筛查及早发现结直肠癌(CRC)可降低其发病率和死亡率,提高存活率。挪威晚期确诊的 CRC 病例比例极高,各市和医院服务区之间的差异很大。本研究探讨了与 CRC 初诊和术前检查相关的医生的可用性或医生密度是否导致了所观察到的晚期发病率的地域差异:方法:从挪威癌症登记处获得了2012-2020年期间各市的CRC诊断阶段数据。医生密度是根据挪威统计局(Statistics Norway)提供的每个城市和每个医院地区的医生人数计算得出的,即每10,000人中与CRC调查相关的医生、全科医生(GP)和专科医生的人数。使用一种新颖的空间数据因果推断方法--通过空间平滑的邻里调整方法(NA方法)--对两者之间的关系进行了研究,该方法允许使用空间参考数据研究区域层面的医生供应对CRC结果的影响,同时仍能提供因果关系:根据 NA 方法,每 10,000 人中增加一名全科医生将导致晚期 CRC 发病率下降 3.6% (CI -0.064 至 -0.008)。对于专科医生而言,没有证据表明其与晚期 CRC 的分布有显著相关性,而对于全科医生和专科医生这两组人而言,每 10,000 人中增加 1 名医生将相当于晚期发病率平均下降 2.79% (CI -0.055 至 -0.001):这项研究证实了之前的研究结果,即增加全科医生的数量将显著改善儿童癌症的治疗效果。与之前的研究不同的是,这项研究指出了两类医生--全科医生和专科医生--可及性的重要性。如果全科医生遇到医院人手不足、结肠镜检查排期拖延时间过长等问题,他们就会减少向患者推荐结肠镜检查的次数。这项研究还凸显了新方法在空间参考数据方面的效率,使我们能够在因果推理框架内研究医生密度对癌症结果的影响。
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来源期刊
International Journal of Health Geographics
International Journal of Health Geographics PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH -
CiteScore
10.20
自引率
2.00%
发文量
17
审稿时长
12 weeks
期刊介绍: A leader among the field, International Journal of Health Geographics is an interdisciplinary, open access journal publishing internationally significant studies of geospatial information systems and science applications in health and healthcare. With an exceptional author satisfaction rate and a quick time to first decision, the journal caters to readers across an array of healthcare disciplines globally. International Journal of Health Geographics welcomes novel studies in the health and healthcare context spanning from spatial data infrastructure and Web geospatial interoperability research, to research into real-time Geographic Information Systems (GIS)-enabled surveillance services, remote sensing applications, spatial epidemiology, spatio-temporal statistics, internet GIS and cyberspace mapping, participatory GIS and citizen sensing, geospatial big data, healthy smart cities and regions, and geospatial Internet of Things and blockchain.
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