Contracting outsourced services with collaborative key performance indicatiors

While service outsourcing may benefit from the application of performance‐based contracts (PBCs), the implementation of such contracts is usually challenging. Service performance is often not only dependent on supplier effort but also on the behavior of the buying firm. Existing research on performance‐based contracting provides very limited understanding on how this challenge may be overcome. This article describes a design science research project that develops a novel approach to buyer–supplier contracting, using collaborative key performance indicators (KPIs). Collaborative KPIs evaluate and reward not only the supplier contribution to customer performance but also the customer's behavior to enable this. In this way, performance‐based contracting can also be applied to settings where supplier and customer activities are interdependent, while traditional contracting theories suggest that output controls are not effective under such conditions. In the collaborative KPI contracting process, indicators measure both supplier and customer (buying firm) performance and promote collaboration by being defined through a collaborative process and by focusing on end‐of‐process indicators. The article discusses the original case setting of a telecommunication service provider experiencing critical problems in outsourcing IT services. The initial intervention implementing this contracting approach produced substantial improvements, both in performance and in the relationship between buyer and supplier. Subsequently, the approach was tested and evaluated in two other settings, resulting in a set of actionable propositions on the efficacy of collaborative KPI contracting. Our study demonstrates how defining, monitoring, and incentivizing the performance of specific processes at the buying firm can help alleviate the limitations of traditional performance‐based contracting when the supplier's liability for service performance is difficult to verify

Internet-based treatment for depressive symptoms in hemodialysis patients: A cluster randomized controlled trial

Objective: To investigate the effectiveness of a guided internet-based self-help intervention for hemodialysis patients with depressive symptoms. Method: Chronic hemodialysis patients from nine Dutch hospitals with a depression score on the Beck Depression Inventory – second edition (BDI-II) of ≥10, were cluster-randomized into a five modules guided internet-based self-help problem solving therapy intervention or a parallel care-as-usual control group. Clusters were based on hemodialysis shift. The primary outcome depression was measured with the BDI-II. Analysis was performed with linear mixed models. Results: A total of 190 hemodialysis patients were cluster-randomized to the intervention (n = 89) or control group (n = 101). Post-intervention measurement was completed by 127 patients (67%) and more than half of the patients (54%) completed the intervention. No significant differences were found on the BDI-II score between the groups (mean difference − 0.1, 95%CI -3.0; 2.7, p = 0.94). Per protocol sensitivity analysis showed comparable results. No significant differences in secondary outcomes were observed between groups. Conclusions: Guided internet-based self-help problem solving therapy for hemodialysis patients with depressive symptoms does not seem to be effective in reducing these symptoms as compared to usual care. Future research should examine how to best design content and accessibility of an intervention for depressive symptoms in hemodialysis patients. Trial registration: Dutch Trial Register: Trial NL6648 (NTR6834) (prospectively registered 13th November 2017)

Depression, anxiety and quality of life of hemodialysis patients before and during the COVID-19 pandemic

Objective: To investigate the impact of the coronavirus pandemic on mental health in hemodialysis patients, we assessed depression, anxiety and quality of life with valid mental health measures before and after the start of the pandemic. Methods: Data were used from 121 hemodialysis patients from the ongoing prospective multicenter DIVERS-II study. COVID-19 related stress was measured with the Perceived Stress Scale – 10, depression with the Beck Depression Inventory – second edition (BDI-II)), anxiety with the Beck Anxiety Inventory (BAI) and quality of life with the Short Form – 12 (SF-12). Scores during the first and second COVID-19 wave in the Netherlands were compared to data prior to the pandemic with linear mixed models. Results: No significant differences were found in BDI-II, BAI and SF-12 scores between before and during the pandemic. During the first wave, 33% of participants reported COVID-19 related stress and in the second wave 37%. These patients had higher stress levels (mean difference (MD) 4.7 (95%CI 1.5; 8.0), p = 0.005) and BDI-II scores (MD 4.9 (95%CI 0.7; 9.0), p = 0.021) and lower SF-12 mental component summary scores (MD -5.3 (95%CI -9.0, −1.6), p = 0.006) than patients who did not experienced COVID-19 stress. These differences were already present before the pandemic. Conclusion: The COVID-19 pandemic does not seem to influence mental health in hemodialysis patients. However, a substantial subgroup of patients with pre-existent mental health problems may be more susceptible to experience COVID-19 related stress