Advance Care Planning in Primary Care: a Cluster Randomized Clinical Trial

Measuring the Effectiveness of a Training Program for the Implementation of Advance Care Planning in Primary Care Teams: a Cluster Randomized Clinical Trial

The study on the effectiveness of a training program in Advance Care Planning (ACP) with primary care professionals has been designed as a cluster-randomized clinical trial.

Aim: To measure the effectiveness of a training program on ACP in Primary healthcare professionals in a population area of Catalonia. Design: Cluster Randomized clinical trial with a measure of pre-post effectiveness between groups of intervention based on the measurement of self-efficacy in advance care planning. Scope: Barcelona Nord and Maresme (BNM). Population: Primary care doctors and nurses. Sample: doctors and nurses from the Primary Care Service (SAP) of the BNM. The study is divided into 3 phases: 1) Planning: training design, randomization and parallel assignment in 2 arms, online training versus online and face-to-face training; 2) Implementation: data collection pre-intervention and training; 3) Evaluation: post data collection (1 follow-up 4 months after recruitment/ after training) and data analysis. Intervention: both arms (A and B) will carry out the online training which consists of a 10 hours course. Arm B will also do the 6-hour face-to-face workshop, divided into two sessions of 3 hours. Primary outcome: ACP Self-efficacy (using a validated scale Advance Care Planning-Self Efficacy Spanish (ACP_SEs). Secondary outcomes: Socio-demographic: age, gender, years of professional experience and in the professional field, previous knowledge in ACP, previous training in ACP; training Satisfaction; ACP Registration Variables in the medical records of patients identified as chronic advanced patients:% clinical records with ACP processes registration, identification of the surrogate decision-maker, values, preferences, and specific decisions records, identification of the place of care and of death preferred, adequacy of the place of death in case of death. Analysis: calculation of the sample applying correction values for the cluster effect; mean, median, range, confidence interval, and standard deviation of quantitative variables and absolute and relative frequency of qualitative variables. Pre- and post-comparison for the measurement of variance (ANOVA) resulting between the intervention groups from the chi-square test; multivariate logistic regression model and 5% significance level

Inclusion Criteria:

• Cluster inclusion criteria:

  • Being a primary care team belonging to SAP BNM.

• Individuals inclusion criteria:

  • Being a doctor or a nurse working at the primary care teams recruited.
  • 280 will take part in the study, belonging to the 10 primary care teams recruited.

Exclusion Criteria:

• Cluster inclusion criteria:

  • Being teams that share Primary Care Center, in order to avoid contamination between clusters as long as they share patient assignment.

• Individuals inclusion criteria:

  • Professionals who refuse to be part of the study.