Determining the cut-off value for the Minimal Documentation System (MIDOS2) screening tool to initiate specialized palliative care based on patient's subjective need for palliative support and symptom burden in inpatients with advanced cancer.

PURPOSE: The Minimal Documentation System (MIDOS2) is recommended as a systematic screening tool for assessing symptom burden and patient needs in advanced cancer patients. Given the absence of an optimal weighting of individual symptoms and a corresponding cut-off value, this study aims to determine a threshold based on inpatient's subjective need for palliative support. Additionally, we investigate the correlation between symptom burden and subjective need for palliative support collected through a patient-reported outcome measure (PROM) with survival duration of less or more than one year. METHODS: Inpatients diagnosed with advanced solid cancer completed an electronic PROM, which included the MIDOS2 questionnaire among other tools. Differences in symptom burden were analysed between patients expressing subjective need for palliative support and those with survival of less or more than one year using ANOVA, Mann-Whitney-U Test, logistic regression, Pearson and Spearman correlation tests. Cut-off analyses were performed using a ROC curve. Youden-Index, sensitivity, and specificity measures were used as well. RESULTS: Between April 2020 and March 2021, 265 inpatients were included in the study. Using a ROC curve, the MIDOS2 analysis resulted in an Area under the curve (AUC) of 0.732, a corresponding cut-off value of eight points, a sensitivity of 76.36% and a specificity of 62.98% in assessing the subjective need for palliative support. The MIDOS2, with double weighting of the significant symptoms, showed a cut-off value of 14 points, achieving a sensitivity of 78.18% and a specificity of 72.38%. A total of 55 patients (20.8%) expressed a need for support from the palliative care team. This need was independent of the oncological tumour entity and increased among patients with a survival of less than one year. These patients reported significantly poorer physical (p < 0.001) or mental (p < 0.001) condition. Additionally, they reported higher intensities of pain (p = 0.002), depressive symptoms (p < 0.001), weakness (p < 0.001), anxiety (p < 0.001), and tiredness (p < 0.001). CONCLUSION: Using the established MIDOS2 cut-off value with an adjusted double weighting in our study, a large proportion of inpatients may be accurately referred to SPC based on their subjective need for palliative support. Additionally, subjective reports of poor general, mental, and physical condition, as well as pain, depressive symptoms, weakness, anxiety, and tiredness, increase the subjective need for palliative support, particularly in patients with a survival prognosis of less than one year.

Drivers and barriers of patients' acceptance of video consultation in cancer care.

Background: Due to digitization in the medical sector, many healthcare interactions are switched to online services. This study assessed the acceptance of video consultations (VCs) in cancer care, and determined drivers and barriers of acceptance. Methods: A cross-sectional online-based survey study was conducted in Germany from February 2022 to February 2023. Recruitment took place at oncology outpatient clinics, general practitioners, oncology practices and via cancer-related social media channels. Inclusion criteria were a cancer diagnosis, cancer treatment and internet access. Sociodemographic, medical data, eHealth-related data were acquired via an online assessment. The Unified Theory of Acceptance and Use of Technology (UTAUT) model was used to determine the acceptance of VC and its predictors. Results: Of N = 350 cancer patients, 56.0% (n = 196) reported high acceptance of VC, 28.0% (n = 98) stated moderate acceptance and 16.0% (n = 56) indicated low acceptance. Factors influencing acceptance were younger age (ß = -.28, p < .001), female gender (ß = .35, p = .005), stage of disease (ß = .11, p = .032), high digital confidence (ß = .14, p = .010), low internet anxiety (ß = -.21, p = .001), high digital overload (ß = -.12, p = .022), high eHealth literacy (ß = .14, p = .028), personal trust (ß = -.25, p < .001), internet use (ß = .17, p = .002), and the UTAUT predictors: performance expectancy (ß = .24, p < .001), effort expectancy (ß = .26, p < .001), and social influence (ß = .34, p < .001). Conclusions: Patients' acceptance of VC in cancer care is high. Drivers and barriers to acceptance identified should be considered for personalized applications. Considering the growing demand for cancer care establishing digital healthcare solutions is justified.