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Uncertainty is a central theme in the illness experiences of older cancer patients throughout their illness trajectory. Mishel’s popular theory on uncertainty during illness approaches uncertainty as an outcome and is characterized by the patient’s inability to find meaning in illness events. This study used the concepts of liminality and subjunctivity to explore uncertainty throughout the illness trajectory of cancer patients. We interviewed 18 older (age range = 57–92 years) patients with breast cancer or gastro-intestinal cancer 3 to 4 years post diagnosis. Our analysis is based on the QUAGOL guide that draws on elements of grounded theory such as constant comparison. We found that liminality and subjunctivity provide a useful frame for understanding uncertainty with a specific focus on its productive potential and meaning making. Health care professionals should be open to acquiring a complete picture of patients’ diverse and dynamic experiences of uncertainty in the different stages of their illness trajectory.
Background: Interventional studies on polypharmacy often fail to significantly improve patient-relevant outcomes, or confine themselves to measuring surrogate parameters. Interventions and settings are complex, with many factors affecting results. The AdAM study’s aim is to reduce hospitalization and death by requiring general practitioners (GPs) to use a computerized decision-support system (CDSS). The study will undergo a process evaluation to identify factors for successful implementation and to assess whether the intervention was implemented as intended.
Objective: To evaluate our complex intervention, based on the Medical Research Council’s guideline dimensions.
Research Questions:
We will assess implementation (reach, fidelity, dose, tailoring) by asking: (1) Who took part in the intervention (proportion of GPs using the CDSS, proportion of patients enrolled in them)? Information on GPs’ and patients’ characteristics will also be collected. (2) How many and which medication alerts were dealt with? (3) Was the intervention implemented as intended? (4) On what days did GPs use the intervention tool?
Methods: The process evaluation is part of a stepped-wedge cluster-randomized controlled trial. Characteristics of practices, GPs and patients using the CDSS will be compared with the non-participating population. CDSS log data will be analyzed to evaluate how the number of medication alerts changed between baseline and 2 months later, and to identify the kind of alerts that were dealt with. Comparison of enrolled patients on weekdays versus weekends will shed light on GPs’ use of the CDSS in the absence or presence of patients. Outcomes will be presented using descriptive statistics, and significance tests will be used to identify associations between them. We will conduct subgroup analyses, including time effects to account for software improvements.
Discussion: This study protocol is the basis for conducting analyses of the quantitative process evaluation. By providing insight into how GPs conduct medication reviews, the evaluation will provide context to the trial results and support their interpretation. The evaluation relies on the proper documentation by GPs, potentially limiting its explanatory power.
Polypharmacy is associated with a risk of negative health outcomes. Potentially inappropriate medications, interactions resulting from contradicting medical guidelines, and inappropriate monitoring, all increase the risk. This process evaluation (PE) of the AdAM study investigates implementation and use of a computerized decision-support system (CDSS). The CDSS analyzes medication appropriateness by including claims data, and hence provides general practitioners (GPs) with full access to patients’ medical treatments. We based our PE on pseudonymized logbook entries into the CDSS and used the four dimensions of the Medical Research Council PE framework. Reach, which examines the extent to which the intended study population was included, and Dose, Fidelity, and Tailoring, which examine how the software was actually used by GPs. The PE was explorative and descriptive. Study participants were representative of the target population, except for patients receiving a high level of nursing care, as they were treated less frequently. GPs identified and corrected inappropriate prescriptions flagged by the CDSS. The frequency and intensity of interventions documented in the form of logbook entries lagged behind expectations, raising questions about implementation barriers to the intervention and the limitations of the PE. Impossibility to connect the CDSS to GPs’ electronic medical records (EMR) of GPs due to technical conditions in the German healthcare system may have hindered the implementation of the intervention. Data logged in the CDSS may underestimate medication changes in patients, as documentation was voluntary and already included in EMR.
Background: We conducted a comprehensive medication review at the patients’ home, using data from electronic patient records, and with input from relevant specialists, general practitioners and pharmacists formulated and implemented recommendations to optimize medication use in patients aged 60+ years with polypharmacy. We evaluated the effect of this medication review on quality of life (QoL) and medication use. Methods: Cluster randomized controlled trial (stepped wedge), randomly assigning general practices to one of three consecutive steps. Patients received usual care until the intervention was implemented. Primary outcome was QoL (SF-36 and EQ-5D); secondary outcomes were medication changes, medication adherence and (instrumental) activities of daily living (ADL, iADL) which were measured at baseline, and around 6- and 12-months post intervention. Results: Twenty-four general practices included 360 women and 410 men with an average age of 75 years (SD 7.5). A positive effect on SF-36 mental health (estimated mean was stable in the intervention, but decreased in the control condition with −6.1, p = 0.009,) was found with a reduced number of medications at follow-up compared to the control condition. No significant effects were found on other QoL subscales, ADL, iADL or medication adherence. Conclusion: The medication review prevented decrease of mental health (SF36), with no significant effects on other outcome measures, apart from a reduction in the number of prescribed medications.
Background: Increasingly, informal caregivers in Belgium care in group for an older patient. This study aimed to decrease the caregiver burden and to increase the well-being of caregivers and patients by supporting the needs of informal care groups of older patients (≥70 years).
Method: Through an online self-management tool, the groups were supported to make informed choices concerning the care for the older patient, taking into account the standards, values, concerns and needs of every caregiver and patient. A pre-post study was performed.
Results: Although patients and caregivers considered the self-management tool as useful and supportive, no clear evidence for decreased caregiver burden was found. There was a positive trend in group characteristics such as the distribution of tasks, communication and prevalence of conflicts. Caregivers also stated that they took more time for themselves, had less feelings of guilt and experienced less barriers to ask help.
Conclusion: Tailor-made support of informal care groups starts with facilitating and guiding a process to achieve consent within the group to optimise the care for the patient and also for the caregivers. With a shared vision and supported decisions, caregivers can enter into conversations with the professional caregiver to coordinate adjusted support regarding the care needs.
Introduction: Mental disorders such as depression are common, and an estimated 264 million people are affected by them throughout the world. In recent years, studies on digital health interventions to treat mental disorders have shown evidence of their efficacy, and interest in using them has increased as a result. In the primary care setting, depression and anxiety are the two most frequently diagnosed and treated mental disorders. When they do not refer them to specialists, primary care professionals such as general practitioners treat patients with mental disorders themselves but have insufficient time to treat them adequately. Furthermore, there is a shortage of psychotherapists and those that exist have long waiting lists for an appointment. The purpose of this mixed methods systematic review is to explore the attitudes of primary care professionals towards the use of digital health interventions in the treatment of patients with mental disorders. Their attitudes will provide an indication whether digital mental health interventions can effectively complement standard care in the primary care setting.
Methods and analysis: We searched for qualitative, quantitative and mixed methods studies published in English, German, Spanish, Russian, French and Dutch after January 2010 for inclusion in the review. The included studies must involve digital mental health interventions conducted via computer and/or mobile devices in the primary care setting. The search was conducted in July 2020 in the following electronic bibliographic databases: MEDLINE, Embase, CINAHL, PsycINFO and Web of Science Core Collection. Two reviewers will independently screen titles, abstracts and full texts and extract data. We will use the ‘Integrated methodology’ framework to combine both quantitative and qualitative data.
Ethics and dissemination: Ethical approval is not required. We will disseminate the results of the mixed methods systematic review in a peer-reviewed journal and scientific conferences.
Background: One of the lesser recognized complications of diabetes mellitus are musculoskeletal (MSK) complications of the upper and lower extremity. No prevalence studies have been conducted in general practice. Thus, the aim of this study was to investigate the prevalence of upper extremity MSK disorders in patients with type 2 diabetes (T2DM) in the Netherlands. Methods: We conducted a cross-sectional study with two different approaches, namely a representative Dutch primary care medical database study and a questionnaire study among patients with T2DM. Results: In the database study, 2669 patients with T2DM and 2669 non-diabetes patients were included. MSK disorders were observed in 16.3% of patients with T2DM compared to 11.2% of non-diabetes patients (p < 0.001, OR 1.53, 95% CI 1.31, 1.80). In the questionnaire study, 200 patients with T2DM were included who reported a lifetime prevalence of painful upper extremity body sites for at least four weeks of 67.3%. Conclusion: We found that upper extremity MSK disorders have a high prevalence in Dutch patients with T2DM presenting in general practice. The prevalence ranges from 16% based on GP registered disorders and complaints to 67% based on self-reported diagnosis and pain. Early detection and treatment of these disorders may play a role in preventing the development of chronic MSK disorders.
Objective To explore factors that potentially impact external validation performance while developing and validating a prognostic model for hospital admissions (HAs) in complex older general practice patients.
Study design and setting Using individual participant data from four cluster-randomised trials conducted in the Netherlands and Germany, we used logistic regression to develop a prognostic model to predict all-cause HAs within a 6-month follow-up period. A stratified intercept was used to account for heterogeneity in baseline risk between the studies. The model was validated both internally and by using internal-external cross-validation (IECV).
Results Prior HAs, physical components of the health-related quality of life comorbidity index, and medication-related variables were used in the final model. While achieving moderate discriminatory performance, internal bootstrap validation revealed a pronounced risk of overfitting. The results of the IECV, in which calibration was highly variable even after accounting for between-study heterogeneity, agreed with this finding. Heterogeneity was equally reflected in differing baseline risk, predictor effects and absolute risk predictions.
Conclusions Predictor effect heterogeneity and differing baseline risk can explain the limited external performance of HA prediction models. With such drivers known, model adjustments in external validation settings (eg, intercept recalibration, complete updating) can be applied more purposefully.
Trial registration number PROSPERO id: CRD42018088129.
Objective: After stratifying for age, sex and multimorbidity at baseline, our aim is to analyse time trends in incident multimorbidity and polypharmacy in the 15-year clinical trajectories of individual patients in a family medicine setting.
Methods: This study was carried out using data from the Registration Network Family Medicine in the South of the Netherlands. The clinical trajectories of 10037 subjects during the 15-year period (2000–2014) were analyzed in a repeated measurement of using a generalized estimating equations model as well as a multilevel random intercept model with repeated measurements to determine patterns of incident multimorbidity and polypharmacy. Hierarchical age-period-cohort models were used to generate age and cohort trajectories for comparison with prevalence trends in multimorbidity literature.
Results: Multimorbidity was more common in females than in males throughout the duration of the 15-year trajectory (females: 39.6%; males: 33.5%). With respective ratios of 11.7 and 5.9 between the end and the beginning of the 15-year period, the youngest female and male groups showed a substantial increase in multimorbidity prevalence. Ratios in the oldest female and male groups were 2.2 and 1.9 respectively. Females had higher levels of multimorbidity than males in the 0-24-year and 25-44-year age groups, but the levels converged to a prevalence of 92.2% in the oldest male and 90.7% in the oldest female group. Similar, albeit, moderate differences were found in polypharmacy patterns.
Conclusions: We sought to specify the progression of multimorbidity from an early age. As a result, our study adds to the multimorbidity literature by specifying changes in chronic disease accumulation with relation to polypharmacy, and by tracking differences in patient trajectories according to age and sex. Multimorbidity and polypharmacy are common and their prevalence is accelerating, with a relatively rapid increase in younger groups. From the point of view of family medicine, this underlines the need for a longitudinal approach and a life course perspective in patient care.
Evidence-based clinical guidelines generally consider single conditions, and rarely multimorbidity. We developed an evidence-based guideline for a structured care program to manage polypharmacy in multimorbidity by using a realist synthesis to update the German polypharmacy guideline including the following five methods: formal prioritization in focus groups; systematic guideline review of evidence-based multimorbidity/polypharmacy guidelines; evidence search/synthesis and recommendation development; multidisciplinary consent of recommendations; feasibility test of updated guideline. We identified the need for a better description of the target group, decision support, prioritization of medication, consideration of patient preferences and anticholinergic properties, and of healthcare interfaces. We conducted a systematic guideline review of eight guidelines and extracted and synthesized recommendations using the Ariadne principles. We also included 48 systematic reviews. We formulated and agreed upon 34 recommendations for the revised guideline. During the feasibility test, guideline use enabled 57% of GPs to identify problems, leading to medication changes in 49% and self-assessed improvement in 56% of patients. Although 58% of GPs felt that it was too long, 92% recommended it. Polypharmacy should be systematically reviewed at least annually. Patients, family members, and healthcare professionals should monitor and adjust it using prospective process validation, taking into account patient preferences and agreed treatment goals.