Difficult medical encounters in oncology: What physicians need. An exploratory study

Objective

The objective of this study was to assess how often-medical oncology professionals encounter difficult consultations and if they desire support in the form of training.

Methods

In February 2022, a survey on difficult medical encounters in oncology, training and demographics was set up. The survey was sent to 390 medical oncology professionals part of the OncoZON network of the Southeast region of the Netherlands.

Results

Medical oncology professionals perceive a medical encounter as difficult when there is a dominant family member (n = 27), insufficient time (n = 24), or no agreement between medical professional and patient (n = 22). Patients involved in these encounters are most often characterized with low health literacy (n = 12) or aggressive behavior (n = 10). The inability to comprehend difficult medical information or perceived difficult behavior complicates encounters. Of the medical oncology professionals, 27-44% preferred a training as a physical group meeting (24%) or an individual virtual meeting (19%).

Conclusion

Medical oncology professionals consider dominant or aggressive behavior and the inability to comprehend medical information by patients during consultations as difficult encounters for which they would appreciate support.

Innovation

Our results highlight concrete medical encounters in need of specific education programs within daily oncology practice.

External validation of a prediction model for timely implementation of innovations in radiotherapy

BACKGROUND AND PURPOSE

The aim of this study was to externally validate a model that predicts timely innovation implementation, which can support radiotherapy professionals to be more successful in innovation implementation.

MATERIALS AND METHODS

A multivariate prediction model was built based on the TRIPOD (Transparent Reporting of a multivariate prediction model for Individual Prognosis Or Diagnosis) criteria for a type 4 study (1). The previously built internally validated model had an AUC of 0.82, and was now validated using a completely new multicentre dataset. Innovation projects that took place between 2017-2019 were included in this study. Semi-structured interviews were performed to retrieve the prognostic variables of the previously built model. Projects were categorized according to the size of the project; the success of the project and thepresence of pre-defined success factors were analysed.

RESULTS

Of the 80 included innovation projects (32.5% technological, 35% organisational and 32.5% treatment innovations), 55% were successfully implemented within the planned timeframe. Comparing the outcome predictions with the observed outcomes of all innovations resulted in an AUC of the external validation of the prediction model of 0.72 (0.60-0.84, 95% CI). Factors related to successful implementation included in the model are sufficient and competent employees, desirability and feasibility, clear goals and processes and the complexity of a project.

CONCLUSION

For the first time, a prediction model focusing on the timely implementation of innovations has been successfully built and externally validated. This model can now be widely used to enable more successful innovation in radiotherapy.

Clues to address barriers for access to proton therapy in the Netherlands

BACKGROUND AND PURPOSE

The Netherlands has National Indication Protocols on proton therapy (PT) to select patients who benefit most from PT. However, referrals to proton therapy centres (PTCs) are lagging. The objective of this research is to identify the barriers for access to PT and to design interventions to address these barriers.

MATERIAL AND METHODS

We conducted a nationwide survey among radiation oncologists (ROs), and semi- structured in-depth interviews with ROs and patients. Subsequently, four workshops were held, in which ROs from one PTC and ROs from referring hospitals participated. The workshops were based on design-thinking research, where ideas were co-created on a multidisciplinary basis to encourage joint problem ownership. Kruskal Wallis and X2 tests were used to analyze data.

RESULTS

The most prominent barriers mentioned by ROs were patient selection, poor logistics, and logistical worries about the combination of radiation treatment with chemotherapy. Patients pointed out the inefficient coordination between organisations, poor communication, travel issues and discomfort during treatment. Clues to increase referrals revealed the need for additional tools for patient selection and innovative ways to improve logistics. A case manager was identified as beneficial to the patients' journey as part of a multidisciplinary approach. Such an approach should include the active involvement of medical oncologists, surgeons and pulmonologists.

CONCLUSION

Barriers for access to PT were identified and prioritized in the inter-organisational care- pathway of proton therapy patients in The Netherlands. Innovative solutions were co- designed to solve the barriers.

Development and external validation of multivariate prediction models for erectile dysfunction in men with localized prostate cancer

While the 10-year survival rate for localized prostate cancer patients is very good (>98%), side effects of treatment may limit quality of life significantly. Erectile dysfunction (ED) is a common burden associated with increasing age as well as prostate cancer treatment. Although many studies have investigated the factors affecting erectile dysfunction (ED) after prostate cancer treatment, only limited studies have investigated whether ED can be predicted before the start of treatment. The advent of machine learning (ML) based prediction tools in oncology offers a promising approach to improve the accuracy of prediction and quality of care. Predicting ED may help aid shared decision-making by making the advantages and disadvantages of certain treatments clear, so that a tailored treatment for an individual patient can be chosen. This study aimed to predict ED at 1-year and 2-year post-diagnosis based on patient demographics, clinical data and patient-reported outcomes (PROMs) measured at diagnosis. We used a subset of the ProZIB dataset collected by the Netherlands Comprehensive Cancer Organization (Integraal Kankercentrum Nederland; IKNL) that contained information on 964 localized prostate cancer cases from 69 Dutch hospitals for model training and external validation. Two models were generated using a logistic regression algorithm coupled with Recursive Feature Elimination (RFE). The first predicted ED 1 year post-diagnosis and required 10 pre-treatment variables; the second predicted ED 2 years post-diagnosis with 9 pre-treatment variables. The validation AUCs were 0.84 and 0.81 for 1 year and 2 years post-diagnosis respectively. To immediately allow patients and clinicians to use these models in the clinical decision-making process, nomograms were generated. In conclusion, we successfully developed and validated two models that predicted ED in patients with localized prostate cancer. These models will allow physicians and patients alike to make informed evidence-based decisions about the most suitable treatment with quality of life in mind.

Health Literacy and eHealth: Challenges and Strategies

Given the impact of health literacy (HL) on patients' outcomes, limited health literacy is a major barrier to improve cancer care globally. HL refers to the degree in which an individual is able to acquire, process, and comprehend information in a way to be actively involved in their health decisions. Previous research found that almost half of the population in developed countries have difficulties in understanding health-related information. With the gradual shift toward the shared decision making process and digital transformation in oncology, the need for addressing low HL issues is crucial. Decision making in oncology is often accompanied by considerable consequences on patients' lives, which requires patients to understand complex information and be able to compare treatment methods by considering their own values. How health information is perceived by patients is influenced by various factors including patients' characteristics and the way information is presented to patients. Currently, identifying patients with low HL and simple data visualizations are the best practice to help patients and clinicians in dealing with limited health literacy. Furthermore, using eHealth, as well as involving HL mediators, supports patients to make sense of complex information.

Clinician perspectives on clinical decision support systems in lung cancer: Implications for shared decision-making

Background

Lung cancer treatment decisions are typically made among clinical experts in a multidisciplinary tumour board (MTB) based on clinical data and guidelines. The rise of artificial intelligence and cultural shifts towards patient autonomy are changing the nature of clinical decision‐making towards personalized treatments. This can be supported by clinical decision support systems (CDSSs) that generate personalized treatment information as a basis for shared decision‐making (SDM). Little is known about lung cancer patients' treatment decisions and the potential for SDM supported by CDSSs. The aim of this study is to understand to what extent SDM is done in current practice and what clinicians need to improve it.

Objective

To explore (1) the extent to which patient preferences are taken into consideration in non‐small‐cell lung cancer (NSCLC) treatment decisions; (2) clinician perspectives on using CDSSs to support SDM.

Design

Mixed methods study consisting of a retrospective cohort study on patient deviation from MTB advice and reasons for deviation, qualitative interviews with lung cancer specialists and observations of MTB discussions and patient consultations.

Setting and Participants

NSCLC patients (N = 257) treated at a single radiotherapy clinic and nine lung cancer specialists from six Dutch clinics.

Results

We found a 10.9% (n = 28) deviation rate from MTB advice; 50% (n = 14) were due to patient preference, of which 85.7% (n = 12) chose a less intensive treatment than MTB advice. Current MTB recommendations are based on clinician experience, guidelines and patients' performance status. Most specialists (n = 7) were receptive towards CDSSs but cited barriers, such as lack of trust, lack of validation studies and time. CDSSs were considered valuable during MTB discussions rather than in consultations.

Conclusion

Lung cancer decisions are heavily influenced by clinical guidelines and experience, yet many patients prefer less intensive treatments. CDSSs can support SDM by presenting the harms and benefits of different treatment options rather than giving single treatment advice. External validation of CDSSs should be prioritized.

Patient or Public Contribution

This study did not involve patients or the public explicitly; however, the study design was informed by prior interviews with volunteers of a cancer patient advocacy group. The study objectives and data collection were supported by Dutch health care insurer CZ for a project titled ‘My Best Treatment’ that improves patient‐centeredness and the lung cancer patient pathway in the Netherlands.

The barriers and facilitators of radical innovation implementation in secondary healthcare: a systematic review

PURPOSE

This study aimed to identify the barriers and facilitators related to the implementation of radical innovations in secondary healthcare.

DESIGN/METHODOLOGY/APPROACH

A systematic review was conducted and presented in accordance with a PRISMA flowchart. The databases PubMed and Web of Science were searched for original publications in English between the 1st of January 2010 and 6th of November 2020. The level of radicalness was determined based on five characteristics of radical innovations. The level of evidence was classified according to the level of evidence scale of the University of Oxford. The Consolidated Framework for Implementation Research was used as a framework to classify the barriers and facilitators.

FINDINGS

Based on the inclusion and exclusion criteria, nine publications were included, concerning six technological, two organizational and one treatment innovation. The main barriers for radical innovation implementation in secondary healthcare were lack of human, material and financial resources, and lack of integration and organizational readiness. The main facilitators included a supportive culture, sufficient training, education and knowledge, and recognition of the expected added value.

ORIGINALITY/VALUE

To our knowledge, this is the first systematic review examining the barriers and facilitators of radical innovation implementation in secondary healthcare. To ease radical innovation implementation, alternative performance systems may be helpful, including the following prerequisites: (1) Money, (2) Added value, (3) Timely knowledge and integration, (4) Culture, and (5) Human resources (MATCH). This study highlights the need for more high-level evidence studies in this area.

Practitioners' views on shared decision-making implementation: A qualitative study

INTRODUCTION

Shared decision-making (SDM) refers to the collaboration between patients and their healthcare providers to make clinical decisions based on evidence and patient preferences, often supported by patient decision aids (PDAs). This study explored practitioner experiences of SDM in a context where SDM has been successfully implemented. Specifically, we focused on practitioners' perceptions of SDM as a paradigm, factors influencing implementation success, and outcomes.

METHODS

We used a qualitative approach to examine the experiences and perceptions of 10 Danish practitioners at a cancer hospital experienced in SDM implementation. A semi-structured interview format was used and interviews were audio-recorded and transcribed. Data was analyzed through thematic analysis.

RESULTS

Prior to SDM implementation, participants had a range of attitudes from skeptical to receptive. Those with more direct long-term contact with patients (such as nurses) were more positive about the need for SDM. We identified four main factors that influenced SDM implementation success: raising awareness of SDM behaviors among clinicians through concrete measurements, supporting the formation of new habits through reinforcement mechanisms, increasing the flexibility of PDA delivery, and strong leadership. According to our participants, these factors were instrumental in overcoming initial skepticism and solidifying new SDM behaviors. Improvements to the clinical process were reported. Sustaining and transferring the knowledge gained to other contexts will require adapting measurement tools.

CONCLUSIONS

Applying SDM in clinical practice represents a major shift in mindset for clinicians. Designing SDM initiatives with an understanding of the underlying behavioral mechanisms may increase the probability of successful and sustained implementation.

Shared decision-making for prophylactic cranial irradiation in extensive-stage small-cell lung cancer: an exploratory study

Background

Prophylactic cranial irradiation (PCI) offers extensive-stage small-cell lung cancer (ES-SCLC) patients a lower chance of brain metastasis and slightly longer survival but is associated with a short-term decline in quality of life due to side-effects. This tradeoff between survival and quality of life makes PCI suitable for shared decision-making (SDM), where patients and clinicians make treatment decisions together based on clinical evidence and patient preferences. Despite recent clinical practice guidelines recommending SDM for PCI in ES-SCLC, as well as the heavy disease burden, research into SDM for lung cancer has been scarce. This exploratory study presents patients’ experiences of the SDM process and decisional conflict for PCI.

Methods

Radiation oncologists (n=7) trained in SDM applied it in making the PCI decision with ES-SCLC patients (n=25). We measured patients’ preferred level of participation (Control Preferences Scale), the level of SDM according to both groups (SDM-Q-9 and SDM-Q-Doc), and patients’ decisional conflict [decisional conflict scale (DCS)].

Results

Seventy-nine percent of patients preferred a collaborative role in decision-making, and median SDM scores given by patients and clinicians were 80 (IQR: 75.6–91.1) and 85.2 (IQR: 78.7–88.9) respectively, indicating satisfaction with the process. However, patients experienced considerable decisional conflict. Over 50% lacked clarity about which choice was suitable for them and were unsure what to choose. Sixty-four percent felt they did not know enough about the harms and benefits of PCI, and 60% felt unable to judge the importance of the harms/benefits in their life.

Conclusions

ES-SCLC patients prefer to be involved in their treatment choice for PCI but a substantial portion experiences decisional conflict. Better information provision and values clarification may support patients in making a choice that reflects their preferences.

Factors predicting timely implementation of radiotherapy innovations: the first model

OBJECTIVE

The improvement of radiotherapy depends largely on the implementation of innovations, of which effectivity varies widely. The aim of this study is to develop a prediction model for successful innovation implementation in radiotherapy to improve effective management of innovation projects.

METHODS

A literature review was performed to identify success factors for innovation implementation. Subsequently, in two large academic radiotherapy centres in the Netherlands, an inventory was made of all innovation projects executed between 2011 and 2017. Semi-structured interviews were performed to record the presence/absence of the success factors found in the review for each project. Successful implementation was defined as timely implementation, yes/no. Cross-tables, Χ² tests, t-tests and Benjamin-Hochberg correction were used for analysing the data. A multivariate logistic regression technique was used to build a prediction model.

RESULTS

From the 163 identified innovation projects, only 54% were successfully implemented. We found 31 success factors in literature of which 14 were significantly related to successful implementation in the innovation projects in our study. The prediction model contained the following determinants: (1) sufficient and competent employees, (2) complexity, (3) understanding/awareness of the project goals and process by employees, (4) feasibility and desirability. The area Under the curve (AUC) of the prediction model was 0.86 (0.8-0.92, 95% CI).

CONCLUSION

A prediction model was developed for successful implementation of innovation in radiotherapy.

ADVANCES IN KNOWLEDGE

This prediction model is the first of its kind and, after external validation, could be widely applicable to predict the timely implementation of radiotherapy innovations.

Development and validation of a patient decision aid for prostate Cancer therapy: from paternalistic towards participative shared decision making

BACKGROUND

Patient decision aids (PDAs) can support the treatment decision making process and empower patients to take a proactive role in their treatment pathway while using a shared decision-making (SDM) approach making participatory medicine possible. The aim of this study was to develop a PDA for prostate cancer that is accurate and user-friendly.

METHODS

We followed a user-centered design process consisting of five rounds of semi-structured interviews and usability surveys with topics such as informational/decisional needs of users and requirements for PDAs. Our user-base consisted of 8 urologists, 4 radiation oncologists, 2 oncology nurses, 8 general practitioners, 19 former prostate cancer patients, 4 usability experts and 11 healthy volunteers.

RESULTS

Informational needs for patients centered on three key factors: treatment experience, post-treatment quality of life, and the impact of side effects. Patients and clinicians valued a PDA that presents balanced information on these factors through simple understandable language and visual aids. Usability questionnaires revealed that patients were more satisfied overall with the PDA than clinicians; however, both groups had concerns that the PDA might lengthen consultation times (42 and 41%, respectively). The PDA is accessible on http://beslissamen.nl/ .

CONCLUSIONS

User-centered design provided valuable insights into PDA requirements but challenges in integrating diverse perspectives as clinicians focus on clinical outcomes while patients also consider quality of life. Nevertheless, it is crucial to involve a broad base of clinical users in order to better understand the decision-making process and to develop a PDA that is accurate, usable, and acceptable.

Prevention of the metabolic syndrome in IGT subjects in a lifestyle intervention: results from the SLIM study

BACKGROUND AND AIMS

The Study on Lifestyle intervention and Impaired glucose tolerance Maastricht (SLIM), a randomized controlled trial, directed at diet and physical activity in impaired glucose tolerant subjects was effective to improve glucose tolerance and prevent type 2 diabetes. The aim of this study was to determine the effects of the SLIM lifestyle intervention on the incidence and prevalence of the metabolic syndrome (MetS) during the active intervention and four years thereafter.

METHODS AND RESULTS

MetS was diagnosed according to the NCEP ATP III criteria. At baseline, 66.4% of all participants (n = 146, age 57 ± 7 years, BMI 29.7 ± 3.6, 51.3% female) fulfilled the criteria for MetS. No significant difference in MetS prevalence was observed between the intervention (63.9%) and control group (68.9%). At the end of active intervention (average duration 4.2 ± 2.0 years), prevalence of MetS was significantly lower in the intervention group (52.6%, n = 57) compared to the control group (74.6%, n = 59) (p = 0.014). Furthermore, in participants without MetS at baseline, cumulative incidence of MetS was 18.2% in the intervention group at the end of active intervention, compared to 73.7% in the control group (Log-rank test, p = 0.011). Four years after stopping active intervention, the reduced incidence of MetS was maintained (Log-rank test, p = 0.002).

CONCLUSION

In conclusion, a combined diet-and-exercise intervention to improve glucose tolerance, not only prevented type 2 diabetes, but also reduced the prevalence of MetS and prevented MetS development, showing the long-term impact of lifestyle intervention on cardiovascular risk reduction.

Changes in transferrin are related to changes in insulin resistance: the SLIM study

AIMS

To determine the effect of a lifestyle intervention on serum transferrin and ferritin levels and the relationship between changes in transferrin and ferritin and changes in glucose tolerance and insulin resistance.

METHODS

Randomized controlled lifestyle intervention directed at a healthy diet and increased physical activity in subjects with impaired glucose tolerance.

RESULTS

After 1 year, the change in ferritin levels in the intervention group as compared with the control group did not reach statistical significance (P = 0.06). Transferrin change was independently related to the change in homeostasis model assessment of insulin resistance and ferritin change was related to the change in 2-h free fatty acids.

CONCLUSIONS

Changes in insulin sensitivity and postprandial lipid metabolism are related to changes in iron metabolism.

Impact of 3-year lifestyle intervention on postprandial glucose metabolism: the SLIM study

OBJECTIVE

To determine the effect of a 3-year diet and exercise lifestyle intervention, based on general public health recommendations, on glucose tolerance, insulin resistance and metabolic cardiovascular risk factors in Dutch subjects with impaired glucose tolerance (IGT).

METHODS

The study was a randomized controlled lifestyle intervention over 3 years. A total of 147 IGT subjects (75 male, 72 female) were randomized to the intervention (INT) group or control (CON) group; 106 subjects (52 INT, 54 CON) completed 3 years of intervention. Annually, glucose, insulin and free fatty acid (FFA) concentrations were determined fasting and after an oral glucose tolerance test. Measurements of body weight, serum lipids, blood pressure and maximal aerobic capacity were also performed.

RESULTS

Analysis of those who completed the 3-year trial, showed that the lifestyle intervention improved body weight (INT -1.08 +/- 4.30 kg; CON +0.16 +/- 4.91 kg, P = 0.01), homeostatis model assessment index for insulin resistance and 2-h FFA. Two-hour glucose concentrations improved in the INT group, the difference being most pronounced after 1 year, with a return to baseline values after 3 years, from 8.59 +/- 1.55 to 8.55 +/- 0.34 mm; in contrast, 2-h glucose deteriorated in the CON group-from 8.46 +/- 1.84 to 9.35 +/- 2.50 mm (P = 0.02). In the INT group, diabetes incidence was reduced by 58% (P = 0.025).

CONCLUSION

Our lifestyle intervention showed a sustained beneficial effect on 2-h glucose concentrations, insulin resistance and 2-h FFA, even after 3 years. Our lifestyle intervention is effective, but for implementation more information is needed about factors influencing adherence.