Cargando…
The effect of physician density on colorectal cancer stage at diagnosis: causal inference methods for spatial data applied on regional-level data
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 catchm...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9850813/ https://www.ncbi.nlm.nih.gov/pubmed/36658603 http://dx.doi.org/10.1186/s12942-023-00323-w |
_version_ | 1784872267534041088 |
---|---|
author | Draganic, Dajana Wangen, Knut Reidar |
author_facet | Draganic, Dajana Wangen, Knut Reidar |
author_sort | Draganic, Dajana |
collection | PubMed |
description | 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12942-023-00323-w. |
format | Online Article Text |
id | pubmed-9850813 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-98508132023-01-20 The effect of physician density on colorectal cancer stage at diagnosis: causal inference methods for spatial data applied on regional-level data Draganic, Dajana Wangen, Knut Reidar Int J Health Geogr Research 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12942-023-00323-w. BioMed Central 2023-01-19 /pmc/articles/PMC9850813/ /pubmed/36658603 http://dx.doi.org/10.1186/s12942-023-00323-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Draganic, Dajana Wangen, Knut Reidar The effect of physician density on colorectal cancer stage at diagnosis: causal inference methods for spatial data applied on regional-level data |
title | The effect of physician density on colorectal cancer stage at diagnosis: causal inference methods for spatial data applied on regional-level data |
title_full | The effect of physician density on colorectal cancer stage at diagnosis: causal inference methods for spatial data applied on regional-level data |
title_fullStr | The effect of physician density on colorectal cancer stage at diagnosis: causal inference methods for spatial data applied on regional-level data |
title_full_unstemmed | The effect of physician density on colorectal cancer stage at diagnosis: causal inference methods for spatial data applied on regional-level data |
title_short | The effect of physician density on colorectal cancer stage at diagnosis: causal inference methods for spatial data applied on regional-level data |
title_sort | effect of physician density on colorectal cancer stage at diagnosis: causal inference methods for spatial data applied on regional-level data |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9850813/ https://www.ncbi.nlm.nih.gov/pubmed/36658603 http://dx.doi.org/10.1186/s12942-023-00323-w |
work_keys_str_mv | AT draganicdajana theeffectofphysiciandensityoncolorectalcancerstageatdiagnosiscausalinferencemethodsforspatialdataappliedonregionalleveldata AT wangenknutreidar theeffectofphysiciandensityoncolorectalcancerstageatdiagnosiscausalinferencemethodsforspatialdataappliedonregionalleveldata AT draganicdajana effectofphysiciandensityoncolorectalcancerstageatdiagnosiscausalinferencemethodsforspatialdataappliedonregionalleveldata AT wangenknutreidar effectofphysiciandensityoncolorectalcancerstageatdiagnosiscausalinferencemethodsforspatialdataappliedonregionalleveldata |