Addressing Palliative Sedation during Expert Consultation: A Descriptive Analysis of the Practice of Dutch Palliative Care Consultation Teams

Contains fulltext : 153544.PDF (publisher's version ) (Open Access)MAIN OBJECTIVE: Since palliative sedation is considered a complex intervention, consultation teams are increasingly established to support general practice. This study aims to offer insight into the frequency and characteristics of expert consultations regarding palliative sedation. METHODS: We performed a retrospective analysis of a longitudinal database. This database contained all patient-related consultations by Dutch Palliative Care Consultation teams, that were requested between 2004 and 2011. We described the frequency and characteristics of these consultations, in particular of the subgroup of consultations in which palliative sedation was addressed (i.e. PSa consultations). We used multivariate regression analysis to explore consultation characteristics associated with a higher likelihood of PSa consultations. MAIN RESULTS AND THEIR SIGNIFICANCE: Of the 44,443 initial consultations, most were requested by general practitioners (73%) and most concerned patients with cancer (86%). Palliative sedation was addressed in 18.1% of all consultations. Palliative sedation was relatively more often discussed during consultations for patients with a neurologic disease (OR 1.79; 95% CI: 1.51-2.12) or COPD (OR 1.39; 95% CI: 1.15-1.69) than for patients with cancer. We observed a higher likelihood of PSa consultations if the following topics were also addressed during consultation: dyspnoea (OR 1.30; 95% CI: 1.22-1.40), agitation/delirium (OR 1.57; 95% CI: 1.47-1.68), exhaustion (OR 2.89; 95% CI: 2.61-3.20), euthanasia-related questions (OR 2.65; 95% CI: 2.37-2.96) or existential issues (OR 1.55; 95% CI: 1.31-1.83). CONCLUSION: In conclusion, PSa consultations accounted for almost one-fifth of all expert consultations and were associated with several case-related characteristics. These characteristics may help clinicians in identifying patients at risk for a more complex disease trajectory at the end of life

Variation in treatment and outcome in patients with non-small cell lung cancer by region, hospital type and volume in the Netherlands

Background: Care processes for patients with NSCLC can vary by provider, which may lead to unwanted variation in outcomes. Therefore, in modern health care an increased focus on guideline development and implementation is seen. It is expected that more guideline adherence leads to a higher number of patients receiving optimal treatment for their cancer which could improve overall survival. Objective: The aim of this study was to evaluate variations in treatment patterns and outcomes of patients with NSCLC treated in different (types of) hospitals and regions in the Netherlands. Especially, variation in the percentage of patients receiving the optimal treatment for the stage of their disease, according to the Dutch national guideline of 2004, was analyzed. Methods: All patients with a histological confirmed primary NSCLC diagnosed in the period 2001–2006 in all Dutch hospitals (N = 97) were selected from the population-based Netherlands Cancer Registry. Hospitals were divided in groups based on their region (N = 9), annual volume of NSCLC patients, teaching status and presence of radiotherapy facilities. Stage-specific differences in optimal treatment rates between (groups of) hospitals and regions were evaluated. Results: In the study period 43 544 patients were diagnosed with NSCLC. The resection rates for stage I/II NSCLC patients increased during the study period, but resection rates varied by region and were higher in teaching hospitals for thoracic surgeons (OR 1.5; 95%CI 1.2–1.9, p = 0.001) and in hospitals with a diagnostic volume of more than 50/year (OR 1.3; 95%CI 1.1–1.5, p = 0.001). Also the use of chemoradiation in stage III patients increased, though marked differences between hospitals in the use of chemoradiation for stage III patients were revealed. Differences in optimal treatment rates between hospitals led to differences in survival. Conclusion: Treatment patterns and outcome of NSCLC patients in the Netherlands varied by region and the hospital their cancer was diagnosed in. Though resection rates were higher in hospitals training thoracic surgeons, variation between individual hospitals was much more distinct. Hospital characteristics like a high diagnostic volume, teaching status or availability of radiotherapy facilities proved no guarantee for optimal treatment rates

Disparities in quality of care for colon cancer between hospitals in the Netherlands

Background: Aim of this study was to describe treatment patterns and outcome according to region, and according to hospital types and volumes among patients with colon cancer in the Netherlands.\ud \ud Methods: All patients with invasive colon carcinoma diagnosed in the period 2001–2006 were selected from the Netherlands Cancer Registry. Logistic regression analyses were performed to examine the influence of relevant factors on the odds of having adequate lymph node evaluation, receiving adjuvant chemotherapy and postoperative mortality. Relative survival analysis was used to estimate relative excess risk of dying according to hospital type and volume.\ud \ud Results: In total, 39 907 patients were selected. Patients diagnosed in a university hospital had a higher odds (OR 2.47; 95% CI 2.19–2.78) and patients diagnosed in a hospital with >100 colon carcinoma diagnoses annually had a lower odds (OR 0.70; 95% CI 0.64–0.77) of having ≥10 lymph nodes evaluated. The odds of receiving adjuvant chemotherapy was lower in patients diagnosed in teaching hospitals (OR 0.85; 95% CI 0.73–0.98) and university hospitals (OR 0.56; 95% CI 0.45–0.70) compared to patients diagnosed in non-teaching hospitals. Funnel plots showed large variation in these two outcome measures between individual hospitals. No differences in postoperative mortality were found between hospital types or volumes. Patients diagnosed in university hospitals and patients diagnosed in hospitals with >50 diagnoses of colon carcinoma per year had a better survival.\ud \ud Conclusions: Variation in treatment and outcome of patients with colon cancer in the Netherlands was revealed, with differences between hospital types and volumes. However, variation seemed mainly based on the level of the individual hospital

Variation in treatment and outcome of patients with rectal cancer by region, hospital type and volume in the Netherlands

Background: Aim of this study was to describe treatment patterns and outcome according to region and hospital type and volume among patients with rectal cancer in the Netherlands.\ud \ud Methods: All patients with rectal carcinoma diagnosed in the period 2001–2006 were selected from the Netherlands Cancer Registry. Logistic regression analyses were performed to examine the influence of relevant factors on the odds of receiving preoperative radiotherapy and on the odds of postoperative mortality. Relative survival analysis was used to estimate relative excess risk of dying according to hospital type and volume.\ud \ud Results: In total, 16 039 patients were selected. Patients diagnosed in a teaching or university hospital had a lower odds (OR 0.85; 95% CI 0.73–0.99 and OR 0.70; 95% CI 0.52–0.92) and patients diagnosed in a hospital performing >50 resections per year had a higher odds (OR 1.95; 95% CI 1.09–1.76) of receiving preoperative radiotherapy. A large variation between individual hospitals in rates of preoperative radiotherapy and between Comprehensive Cancer Centre-regions in the administration of preoperative chemoradiation was revealed. Postoperative mortality was not correlated to hospital type or volume. Patients with T1-M0 tumours diagnosed in a hospital with >50 resections per year had a better survival compared to patients diagnosed in a hospital with <25 resections per year (RER 0.11; 95% CI 0.02–0.78).\ud \ud Conclusion: This study demonstrated variation in treatment and outcome of patients with rectal cancer in the Netherlands, with differences related to hospital volume and hospitals teaching or academic status. However, variation in treatment patterns between individual hospitals proved to be much larger than could be explained by the investigated characteristics. Future studies should focus on the reasons behind these differences, which could lead to a higher proportion of patients receiving optimal treatment for their stage of the disease

Variation in case-mix between hospitals treating colorectal cancer patients in the Netherlands

Contains fulltext : 98509.pdf (publisher's version ) (Closed access)AIMS: The purpose of this study was to determine how expected mortality based on case-mix varies between colorectal cancer patients treated in non-teaching, teaching and university hospitals, or high, intermediate and low-volume hospitals in the Netherlands. MATERIAL AND METHODS: We used the database of the Dutch Surgical Colorectal Audit 2010. Factors predicting mortality after colon and rectum carcinoma resections were identified using logistic regression models. Using these models, expected mortality was calculated for each patient. RESULTS: 8580 patients treated in 90 hospitals were included in the analysis. For colon carcinoma, hospitals' expected mortality ranged from 1.5 to 14%. Average expected mortality was lower in patients treated in high-volume hospitals than in low-volume hospitals (5.0 vs. 4.3%, p < 0.05). For rectum carcinoma, hospitals expected mortality varied from 0.5 to 7.5%. Average expected mortality was higher in patients treated in non-teaching and teaching hospitals than in university hospitals (2.7 and 2.3 vs. 1.3%, p < 0.01). Furthermore, rectum carcinoma patients treated in high-volume hospitals had a higher expected mortality than patients treated in low-volume hospitals (2.6 vs. 2.2% p < 0.05). We found no differences in risk-adjusted mortality. CONCLUSIONS: High-risk patients are not evenly distributed between hospitals. Using the expected mortality as an integrated measure for case-mix can help to gain insight in where high-risk patients go. The large variation in expected mortality between individual hospitals, hospital types and volume groups underlines the need for risk-adjustment when comparing hospital performances