Study links patient characteristics with the likelihood of bypassing the nearest surgical center for breast cancer treatment

By Pooja Toshniwal PahariaReviewed by Danielle Ellis, B.Sc.Jan 10 2024

In a recent study published in Cancer, researchers investigated hospital quality and patient factors associated with treatment location for breast cancer surgery.

Background

Countries are implementing policies to improve patient-centered health systems by allowing patients to choose their hospitals for treatment. However, studies show that up to one in three patients bypass their nearest surgical center due to being younger, fitter, and affluent, improving access to advanced technologies but may not result in the best disease-specific outcomes. Understanding patient mobility is crucial for matching demand with supply.

About the study

In the present national study, researchers investigated the mobility patterns of breast cancer patients who underwent primary surgical resections in the English NHS.

The team used the National Cancer Registration and Analysis Service (NCAS) data in linkage with the National Health Service (NHS) Hospital Episode Statistics (HES) data to identify women diagnosed between 2 January 2016 and 31 December 2018 undergoing breast-conserving surgeries (BCS) or mastectomies followed by immediate breast reconstruction (IBR) or without it. They used geographic data systems (ArcGIS) to investigate the extent of patients bypassing nearby hospitals for treatment.

The HES database provided data on patient factors such as age, residence, sex, ethnicity, comorbidities, and socioeconomic status. In addition, the researchers obtained data on the treating hospitals, BCS date, and type, such as autologous reconstruction, mastectomy, and breast re-excisions following BCS. They included six patient factors: age, ethnicity, comorbidities, socioeconomic deprivation, tumor stage, and residence for analysis.

The team identified seven hospital-based factors that increase hospital attractivity to physicians and patients for surgical treatment. The hospital factors were treatment availability, media reputation, performance ratings, research activities, tumor waiting times, and re-excision rates. They identified 49 cancer centers with multidisciplinary teams, 45 hospitals performing ≥20 breast reconstructions post-mastectomy using expander-based methods or autologous non-implants annually, 11 hospitals having good media reputations for employing top breast tumor specialists in the United Kingdom, 12 hospitals providing insufficient care, and 31 hospitals engaged in research activities. They also identified 33 cancer hospitals with the most tumor re-excisions following elective breast cancer surgery.

Population-based centroids for the Lower-Layer Super Output Areas (LSOAs) represented patients' residential locations. The team categorized the hospitals based on their performance rating system. They used the ESRI ArcGIS data system to determine mean travel times in the day by car. They classified patients who did not receive treatment at the nearest hospital as bypassers. They performed multivariate conditional-type logistic regressions to determine the odds ratios (ORs) for the relationships between travel times, patient and hospital characteristics, and surgery location. They also assessed the effect of travel duration and hospital factors, adjusting for confounders (age, ethnicity, comorbidity, socioeconomic status, residence, and cancer stage).

Results

The study analyzed 101,750 patients who underwent BCS with curative intent, of whom 69,153 received elective BCS and 33,686 underwent elective mastectomy. Of 69,153 individuals undergoing elective BCS, 33% (n=22,622) bypassed their nearby cancer hospital, and out of 23,536 individuals undergoing mastectomy, 31% (n=7,179) avoided their nearby hospital. Individuals undergoing BCS (OR, 1.9) or mastectomy procedures (OR, 1.5) showed a higher likelihood of receiving treatment from specialized centers for breast reconstruction.

Individuals receiving IBR and mastectomy showed a higher likelihood of traveling to hospitals having cancer specialists with a good media reputation (odds ratio, 2.4). Individuals undergoing BCS showed a lower likelihood of traveling to hospitals having short surgical waiting periods (OR, 0.7). For women receiving BCS, the probability of patients commuting to hospitals other than the nearest one reduced with increasing commuting times. For example, the probability of patients undergoing mastectomies (without breast reconstruction) commuting to hospitals ≤10 minutes away from the nearest hospital was considerably lower (OR, 0.3).

The team found no associations between the chances of patients commuting to specific hospitals and the United Kingdom Care Quality Commission hospital ratings, research activities of the hospitals, or whether the hospitals were multidisciplinary. Older patients, those belonging to ethnic minorities, and those with comorbidities and advanced disease showed a lower likelihood of traveling to hospitals apart from the nearest one for treatment. Additional travel times showed less strong associations with the probability of commuting to a specific hospital for rural patients than those living in urban areas.

Conclusion

Overall, the study findings showed that one out of three individuals with breast cancer bypass their most proximal hospital for surgery, with travel time being the primary factor. Younger patients, those with fewer comorbidities, white ethnic backgrounds, and those in rural regions showed a higher likelihood of traveling to alternative hospitals. Specialist breast reconstruction centers have a higher likelihood of treating patients undergoing breast cancer surgery. Improving the disconnect between perceived and actual cancer treatment quality is crucial to prevent perverse incentives and improve patient outcomes.