Elizabeth A. Cooke , Nadia A.S. Smith , Donna Chung , Ben Goretzki , Spencer A. Thomas , Adrienne Flanagan , Craig Gerrand , Neal Navani , Prabhakar Rajan , Ashoke Roy , Clare Schilling , Ellie Smyth , Paul Stimpson , Sandra J. Strauss , Derralynn Hughes
{"title":"提高北伦敦医院癌症护理效率的分析框架","authors":"Elizabeth A. Cooke , Nadia A.S. Smith , Donna Chung , Ben Goretzki , Spencer A. Thomas , Adrienne Flanagan , Craig Gerrand , Neal Navani , Prabhakar Rajan , Ashoke Roy , Clare Schilling , Ellie Smyth , Paul Stimpson , Sandra J. Strauss , Derralynn Hughes","doi":"10.1016/j.health.2025.100406","DOIUrl":null,"url":null,"abstract":"<div><div>We use mathematical and statistical techniques on operational data to examine the impact of different factors on the time to treatment for cancer patients in North London hospitals. Understanding the factors which prolong the time between referral and treatment starting for cancer patients on pathways which cross healthcare providers is imperative to improved patient care. We analyse three tumour pathways which involve transfer of patients between hospitals: sarcoma, urological, and head and neck cancers. Several factors impact on the time to first treatment including demographic characteristics, day of the week first seen and method of communicating the cancer diagnosis. In particular, we found that head and neck patients from lower socioeconomic areas were more likely to have longer times from referral to treatment. Patients with sarcoma who were first seen on a Sunday are more likely to breach the 28-day faster diagnosis standard. This analysis is an important first step in highlighting where focus is needed to improve cancer care pathways. Understanding and mitigating the factors influencing the length of time between referral and treatment could enhance the efficiency of cancer care pathways and, consequently, patient outcomes.</div></div>","PeriodicalId":73222,"journal":{"name":"Healthcare analytics (New York, N.Y.)","volume":"8 ","pages":"Article 100406"},"PeriodicalIF":0.0000,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An analytical framework for enhancing cancer care efficiency in North London hospitals\",\"authors\":\"Elizabeth A. Cooke , Nadia A.S. Smith , Donna Chung , Ben Goretzki , Spencer A. Thomas , Adrienne Flanagan , Craig Gerrand , Neal Navani , Prabhakar Rajan , Ashoke Roy , Clare Schilling , Ellie Smyth , Paul Stimpson , Sandra J. Strauss , Derralynn Hughes\",\"doi\":\"10.1016/j.health.2025.100406\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>We use mathematical and statistical techniques on operational data to examine the impact of different factors on the time to treatment for cancer patients in North London hospitals. Understanding the factors which prolong the time between referral and treatment starting for cancer patients on pathways which cross healthcare providers is imperative to improved patient care. We analyse three tumour pathways which involve transfer of patients between hospitals: sarcoma, urological, and head and neck cancers. Several factors impact on the time to first treatment including demographic characteristics, day of the week first seen and method of communicating the cancer diagnosis. In particular, we found that head and neck patients from lower socioeconomic areas were more likely to have longer times from referral to treatment. Patients with sarcoma who were first seen on a Sunday are more likely to breach the 28-day faster diagnosis standard. This analysis is an important first step in highlighting where focus is needed to improve cancer care pathways. Understanding and mitigating the factors influencing the length of time between referral and treatment could enhance the efficiency of cancer care pathways and, consequently, patient outcomes.</div></div>\",\"PeriodicalId\":73222,\"journal\":{\"name\":\"Healthcare analytics (New York, N.Y.)\",\"volume\":\"8 \",\"pages\":\"Article 100406\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Healthcare analytics (New York, N.Y.)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2772442525000255\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Healthcare analytics (New York, N.Y.)","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772442525000255","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An analytical framework for enhancing cancer care efficiency in North London hospitals
We use mathematical and statistical techniques on operational data to examine the impact of different factors on the time to treatment for cancer patients in North London hospitals. Understanding the factors which prolong the time between referral and treatment starting for cancer patients on pathways which cross healthcare providers is imperative to improved patient care. We analyse three tumour pathways which involve transfer of patients between hospitals: sarcoma, urological, and head and neck cancers. Several factors impact on the time to first treatment including demographic characteristics, day of the week first seen and method of communicating the cancer diagnosis. In particular, we found that head and neck patients from lower socioeconomic areas were more likely to have longer times from referral to treatment. Patients with sarcoma who were first seen on a Sunday are more likely to breach the 28-day faster diagnosis standard. This analysis is an important first step in highlighting where focus is needed to improve cancer care pathways. Understanding and mitigating the factors influencing the length of time between referral and treatment could enhance the efficiency of cancer care pathways and, consequently, patient outcomes.