During the COVID-19 pandemic, the bidirectional relationship between policy and data reliability has been a challenge for researchers of the local municipal health services. Policy decisions on population specific test locations and selective registration of negative test results led to population differences in data quality. This hampered the calculation of reliable population specific infection rates needed to develop proper data driven public health policy. https://doi.org/10.1007/s12508-023-00377-y
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Background Ethnic differences in colon cancer (CC) care were shown in the United States, but results are not directly applicable to European countries due to fundamental healthcare system differences. This is the first study addressing ethnic differences in treatment and survival for CC in the Netherlands. Methods Data of 101,882 patients diagnosed with CC in 1996–2011 were selected from the Netherlands Cancer Registry and linked to databases from Statistics Netherlands. Ethnic differences in lymph node (LN) evaluation, anastomotic leakage and adjuvant chemotherapy were analysed using stepwise logistic regression models. Stepwise Cox regression was used to examine the influence of ethnic differences in adjuvant chemotherapy on 5-year all-cause and colorectal cancer-specific survival. Results Adequate LN evaluation was significantly more likely for patients from ‘other Western’ countries than for the Dutch (OR 1.09; 95% CI 1.01–1.16). ‘Other Western’ patients had a significantly higher risk of anastomotic leakage after resection (OR 1.24; 95% CI 1.05–1.47). Patients of Moroccan origin were significantly less likely to receive adjuvant chemotherapy (OR 0.27; 95% CI 0.13–0.59). Ethnic differences were not fully explained by differences in socioeconomic and hospital-related characteristics. The higher 5-year all-cause mortality of Moroccan patients (HR 1.64; 95% CI 1.03–2.61) was statistically explained by differences in adjuvant chemotherapy receipt. Conclusion These results suggest the presence of ethnic inequalities in CC care in the Netherlands. We recommend further analysis of the role of comorbidity, communication in patient-provider interaction and patients’ health literacy when looking at ethnic differences in treatment for CC.
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It is important for caregivers and patients to know which wounds are at risk of prolonged wound healing to enable timely communication and treatment. Available prognostic models predict wound healing in chronic ulcers, but not in acute wounds, that is, originating after trauma or surgery. We developed a model to detect which factors can predict (prolonged) healing of complex acute wounds in patients treated in a large wound expertise centre (WEC). Using Cox and linear regression analyses, we determined which patient- and wound-related characteristics best predict time to complete wound healing and derived a prediction formula to estimate how long this may take. We selected 563 patients with acute wounds, documented in the WEC registry between 2007 and 2012. Wounds had existed for a median of 19 days (range 6-46 days). The majority of these were located on the leg (52%). Five significant independent predictors of prolonged wound healing were identified: wound location on the trunk [hazard ratio (HR) 0·565, 95% confidence interval (CI) 0·405-0·788; P = 0·001], wound infection (HR 0·728, 95% CI 0·534-0·991; P = 0·044), wound size (HR 0·993, 95% CI 0·988-0·997; P = 0·001), wound duration (HR 0·998, 95% CI 0·996-0·999; P = 0·005) and patient's age (HR 1·009, 95% CI 1·001-1·018; P = 0·020), but not diabetes. Awareness of the five factors predicting the healing of complex acute wounds, particularly wound infection and location on the trunk, may help caregivers to predict wound healing time and to detect, refer and focus on patients who need additional attention.
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