Implementing the pharmacy technician role in existing pharmacy settings:Stakeholders views of barriers and facilitators

Background: The field of pharmacy will benefit from pharmacy technicians, a higher educated mid-level support workforce. They support pharmacists in providing pharmaceutical patient care through delegated roles and responsibilities. Empirical research on pharmacy technicians within pharmacy practice community and hospital pharmacy practices tends to focus on the practical outcomes of this workforce addition. It mostly addresses the ‘WHAT’ of service delivered by pharmacy technicians. Literature on the ‘HOW’ of their role development in practice is scarce. Furthermore, it seems difficult for most pharmacy technicians to effectively fulfil this professional role. Objective: This qualitative study explored factors influencing role development of pharmacy technicians in community and hospital pharmacies. Methods: On site, individual and small-group interviews were conducted with pharmacy technicians (n = 10), and two colleagues: pharmacists (n = 7) and pharmacy assistants (n = 6). Interviews were based on a semi-structured interview guide. Participants were asked to describe specific incidents and organisational, relational and pharmaceutical care perspectives, illustrative of the process of developing and implementing the pharmacy technician role. Template analysis was used to develop a list of codes representing themes identified in the data. Results: Five interrelated themes influenced development and implementation of the pharmacy technician role. Two of them were at a more contextual level: (a) experiencing a lack of vision on added value of the new role within the field of pharmacy and (b) learning climate. The other three were related to personal interactions between staff members: (c) role expectations and organisational fit, (d) personal traits of pharmacy technicians and (e) support of pharmacy technicians through task delegation and role enhancement. Conclusions: The data showed that development and implementation of pharmacy technician roles is a complicated process. A detailed plan for addressing and remediating the five identified themes is important to promote role development of pharmacy technicians

Implementing the pharmacy technician role in existing pharmacy settings: Stakeholders views of barriers and facilitators

BACKGROUND: The field of pharmacy will benefit from pharmacy technicians, a higher educated mid-level support workforce. They support pharmacists in providing pharmaceutical patient care through delegated roles and responsibilities. Empirical research on pharmacy technicians within pharmacy practice community and hospital pharmacy practices tends to focus on the practical outcomes of this workforce addition. It mostly addresses the 'WHAT' of service delivered by pharmacy technicians. Literature on the 'HOW' of their role development in practice is scarce. Furthermore, it seems difficult for most pharmacy technicians to effectively fulfil this professional role. OBJECTIVE: This qualitative study explored factors influencing role development of pharmacy technicians in community and hospital pharmacies. METHODS: On site, individual and small-group interviews were conducted with pharmacy technicians (n = 10), and two colleagues: pharmacists (n = 7) and pharmacy assistants (n = 6). Interviews were based on a semi-structured interview guide. Participants were asked to describe specific incidents and organisational, relational and pharmaceutical care perspectives, illustrative of the process of developing and implementing the pharmacy technician role. Template analysis was used to develop a list of codes representing themes identified in the data. RESULTS: Five interrelated themes influenced development and implementation of the pharmacy technician role. Two of them were at a more contextual level: (a) experiencing a lack of vision on added value of the new role within the field of pharmacy and (b) learning climate. The other three were related to personal interactions between staff members: (c) role expectations and organisational fit, (d) personal traits of pharmacy technicians and (e) support of pharmacy technicians through task delegation and role enhancement. CONCLUSIONS: The data showed that development and implementation of pharmacy technician roles is a complicated process. A detailed plan for addressing and remediating the five identified themes is important to promote role development of pharmacy technicians

Role of eHealth application Oncokompas in supporting self-management of symptoms and health-related quality of life in cancer survivors:a randomised, controlled trial

Background Knowledge about the efficacy of behavioural intervention technologies that can be used by cancer survivors independently from a health-care provider is scarce. We aimed to assess the efficacy, reach, and usage of Oncokompas, a web-based eHealth application that supports survivors in self-management by monitoring health-related quality of life (HRQOL) and cancer-generic and tumour-specific symptoms and obtaining tailored feedback with a personalised overview of supportive care options. Methods In this non-blinded, randomised, controlled trial, we recruited patients treated at 14 hospitals in the Netherlands for head and neck cancer, colorectal cancer, breast cancer, Hodgkin lymphoma, or non-Hodgkin lymphoma. Adult survivors (aged ≥18 years) were recruited through the Netherlands Cancer Registry (NCR) and invited by their treating physician through the Patient Reported Outcomes Following Initial Treatment and Long term Evaluation of Survivorship (PROFILES) registry. Participants were randomly assigned (1:1) by an independent researcher to the intervention group (access to Oncokompas) or control group (access to Oncokompas after 6 months), by use of block randomisation (block length of 68), stratified by tumour type. The primary outcome was patient activation (knowledge, skills, and confidence for self-management), assessed at baseline, post-intervention, and 3-month and 6-month follow-up. Linear mixed models (intention-to-treat) were used to assess group differences over time from baseline to 6-month follow-up. The trial is registered in the Netherlands Trial Register, NTR5774 and is completed. Findings Between Oct 12, 2016, and May 24, 2018, 625 (21%) of 2953 survivors assessed for eligibility were recruited and randomly assigned to the intervention (320) or control group (305). Median follow-up was 6 months (IQR 6−6). Patient activation was not significantly different between intervention and control group over time (difference at 6-month follow-up 1·7 [95% CI −0·8–4·1], p=0·41). Interpretation Oncokompas did not improve the amount of knowledge, skills, and confidence for self-management in cancer survivors. This study contributes to the evidence for the development of tailored strategies for development and implementation of behavioural intervention technologies among cancer survivors

Crowdsourced mapping of unexplored target space of kinase inhibitors

Despite decades of intensive search for compounds that modulate the activity of particular protein targets, a large proportion of the human kinome remains as yet undrugged. Effective approaches are therefore required to map the massive space of unexplored compound-kinase interactions for novel and potent activities. Here, we carry out a crowdsourced benchmarking of predictive algorithms for kinase inhibitor potencies across multiple kinase families tested on unpublished bioactivity data. We find the top-performing predictions are based on various models, including kernel learning, gradient boosting and deep learning, and their ensemble leads to a predictive accuracy exceeding that of single-dose kinase activity assays. We design experiments based on the model predictions and identify unexpected activities even for under-studied kinases, thereby accelerating experimental mapping efforts. The open-source prediction algorithms together with the bioactivities between 95 compounds and 295 kinases provide a resource for benchmarking prediction algorithms and for extending the druggable kinome. The IDG-DREAM Challenge carried out crowdsourced benchmarking of predictive algorithms for kinase inhibitor activities on unpublished data. This study provides a resource to compare emerging algorithms and prioritize new kinase activities to accelerate drug discovery and repurposing efforts

Detection and localization of early- and late-stage cancers using platelet RNA

Cancer patients benefit from early tumor detection since treatment outcomes are more favorable for less advanced cancers. Platelets are involved in cancer progression and are considered a promising biosource for cancer detection, as they alter their RNA content upon local and systemic cues. We show that tumor-educated platelet (TEP) RNA-based blood tests enable the detection of 18 cancer types. With 99% specificity in asymptomatic controls, thromboSeq correctly detected the presence of cancer in two-thirds of 1,096 blood samples from stage I–IV cancer patients and in half of 352 stage I–III tumors. Symptomatic controls, including inflammatory and cardiovascular diseases, and benign tumors had increased false-positive test results with an average specificity of 78%. Moreover, thromboSeq determined the tumor site of origin in five different tumor types correctly in over 80% of the cancer patients. These results highlight the potential properties of TEP-derived RNA panels to supplement current approaches for blood-based cancer screening

Quality indicators for learner-centered postgraduate medical e-learning

Abstract Objectives: The objectives of this study were to identify the needs and expectations of learners and educational experts in postgraduate medical e-learning, and to contribute to the current literature. Methods: We performed four focus-group discussions with e-learning end-users (learners) and didactic experts. The participants were postgraduate learners with varying levels of experience, educational experts from a Dutch e-learning task group, and commercial experts from a Dutch elearning company. Verbatim transcribed interview recordings were analyzed using King's template analysis. The initial template was created with reference to recent literature on postgraduate medical e-learning quality indicators. The transcripts were coded, after which the emerging differences in template interpretation were discussed until a consensus was reached within the team. Results: The final template consisted of three domains of positive e-learning influencers (motivators, learning enhancers, and real-world translation) and three domains of negatively influential parameters (barriers, learning discouragers, and poor preparation). The interpretation of the final template showed three subjects which form the basis of e-learning, namely, Motivate, Learn and Apply. Conclusions: This study forms a basis for learning in general and could be applied to many educational instruments. Individual characteristics should be adapted to the target audience. Three subjects form the basis of, and six themes cover all items needed for, good (enough) postgraduate e-learning. Further research should be carried out with learners and real-world e-learning to validate this template

Quality indicators for learner-centered postgraduate medical e-learning

Objectives: The objectives of this study were to identify the needs and expectations of learners and educational experts in postgraduate medical e-learning, and to contribute to the current literature. Methods: We performed four focus-group discussions with e-learning end-users (learners) and didactic experts. The participants were postgraduate learners with varying levels of experience, educational experts from a Dutch e-learning task group, and commercial experts from a Dutch e-learning company. Verbatim transcribed interview recordings were analyzed using King's template analysis. The initial template was created with reference to recent literature on postgraduate medical e-learning quality indicators. The transcripts were coded, after which the emerging differences in template interpretation were discussed until a consensus was reached within the team. Results: The final template consisted of three domains of positive e-learning influencers (motivators, learning enhancers, and real-world translation) and three domains of negatively influential parameters (barriers, learning discouragers, and poor preparation). The interpretation of the final template showed three subjects which form the basis of e-learning, namely, Motivate, Learn and Apply. Conclusions: This study forms a basis for learning in general and could be applied to many educational instruments. Individual characteristics should be adapted to the target audience. Three subjects form the basis of, and six themes cover all items needed for, good (enough) postgraduate e-learning. Further research should be carried out with learners and real-world e-learning to validate this template

Quality indicators for learner-centered postgraduate medical e-learning

Objectives: The objectives of this study were to identify the needs and expectations of learners and educational experts in postgraduate medical e-learning, and to contribute to the current literature. Methods: We performed four focus-group discussions with e-learning end-users (learners) and didactic experts. The participants were postgraduate learners with varying levels of experience, educational experts from a Dutch e-learning task group, and commercial experts from a Dutch e-learning company. Verbatim transcribed interview recordings were analyzed using King's template analysis. The initial template was created with reference to recent literature on postgraduate medical e-learning quality indicators. The transcripts were coded, after which the emerging differences in template interpretation were discussed until a consensus was reached within the team. Results: The final template consisted of three domains of positive e-learning influencers (motivators, learning enhancers, and real-world translation) and three domains of negatively influential parameters (barriers, learning discouragers, and poor preparation). The interpretation of the final template showed three subjects which form the basis of e-learning, namely, Motivate, Learn and Apply. Conclusions: This study forms a basis for learning in general and could be applied to many educational instruments. Individual characteristics should be adapted to the target audience. Three subjects form the basis of, and six themes cover all items needed for, good (enough) postgraduate e-learning. Further research should be carried out with learners and real-world e-learning to validate this template

Consensus on quality indicators of postgraduate medical e-learning:Delphi study

Background: The progressive use of e-learning in postgraduate medical education calls for useful quality indicators. Many evaluation tools exist. However, these are diversely used and their empirical foundation is often lacking. Objective: We aimed to identify an empirically founded set of quality indicators to set the bar for “good enough” e-learning. Methods: We performed a Delphi procedure with a group of 13 international education experts and 10 experienced users of e-learning. The questionnaire started with 57 items. These items were the result of a previous literature review and focus group study performed with experts and users. Consensus was met when a rate of agreement of more than two-thirds was achieved. Results: In the first round, the participants accepted 37 items of the 57 as important, reached no consensus on 20, and added 15 new items. In the second round, we added the comments from the first round to the items on which there was no consensus and added the 15 new items. After this round, a total of 72 items were addressed and, of these, 37 items were accepted and 34 were rejected due to lack of consensus. Conclusions: This study produced a list of 37 items that can form the basis of an evaluation tool to evaluate postgraduate medical e-learning. This is, to our knowledge, the first time that quality indicators for postgraduate medical e-learning have been defined and validated. The next step is to create and validate an e-learning evaluation tool from these items