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Abstract Background Depression and panic disorders have high prevalence rates in primary care. Given the crucial role of general practitioners in diagnosing and treating mental disorders, the two-arm cluster-randomized, controlled PREMA trial was designed. PREMA was aimed at investigating a new intervention combining cognitive behavioral therapy, case management and eHealth components for patients with depression and/or panic disorder with or without agoraphobia in primary care practices in Germany. This qualitative study, embedded in the PREMA trial, explores primary healthcare professionals’ lived experiences in using the new treatment program. Using a qualitative design, we conducted eleven interviews with general practitioners and medical assistants from Hesse, Germany, between July 2021 and March 2022. For both groups we relied on a semi-structured interview guide covering the following subjects: study procedures, implementation, practicality, and individual components of the treatment program. Interviews were audio-recorded, transcribed verbatim and analyzed by two researchers using content analysis. A deductive-inductive approach was used for the analysis according to Kuckartz. Results We narratively summarized the facilitators and barriers from two different stakeholders across five key themes regarding experiences of feasibility and practicability of the new treatment program: study instruction materials, individual components of the treatment program, practicality, target population, and benefits of the treatment program. Facilitators to become familiar with the study include study instruction materials that are easy to understand and not too complex, considering the limited time resources available; barriers included text-heavy instruction materials, lack of collegial exchange, and issues especially with digital materials also involved access and log-in difficulties on the online platform. Facilitators for using the treatment program include the combination of face-to-face consultations and the use of an online platform, enabling a structured approach and regularity; barriers included patients feeling unsupported in performing anxiety exercises independently at home. For practicality, the professional skills of medical assistants and their central role as points of contact for patients facilitated the implementation; barriers included time-intensive organization and planning of monitoring phone calls and consultations. Regarding the target population, general practitioners and medical assistants state that the treatment program would be most appropriate for patients with mild to moderate depression and for those waiting for psychotherapeutic treatment; it would be less suitable for older patients, and those with negative attitudes towards technological tools. For benefits of the program, facilitating factors included free and low-threshold access to the online platform and strengthening the relationship between medical assistants and patients; barriers included a preference for in-person conversations and the inability of some people to use online applications. Conclusions The complexity of the new treatment program and the associated high workload underline the need for further adjustments to the treatment approach. Team-based care and the expanded responsibilities of medical assistants demonstrated promising results. Trial registration The study was registered in the German Clinical Trials Register (DRKS00016622) on February 22, 2019.

Introduction Empowering people living with multimorbidity (multiple chronic conditions) to gain greater confidence in managing their health can enhance their quality of life. Education focused on self-management is a key tool for fostering patient empowerment and is mostly provided on an individual basis. Virtual communities of practice (VCoP) present a unique opportunity for online education in chronic condition self-management within a social context. This research aims to evaluate the effectiveness/cost-effectiveness of individualised, online self-management education compared with VCoP among middle-aged individuals living with multiple chronic conditions.Methods and analysis People aged 30–60, living with ≥2 chronic conditions and receiving care in primary care (PC) centres and outpatient hospital-based clinics in Madrid and Canary Islands will enrol in an 18-month parallel-design, blinded (intervention assessment and data analysts), pragmatic (adhering to the intention-to-treat principle), individually randomised trial. The trial will compare two 12-month web-based educational offers of identical content; one delivered individually (control) and the other with online social interaction (VCoP, intervention). Using repeated measures mixed linear models, with the patient as random effect and allocation groups and time per group as fixed effects, we will estimate between-arm differences in the change in Patient Activation Measure from baseline to 12 months (primary endpoint), including measurements at 6-month and 18-month follow-up. Other outcomes will include measures of depression and anxiety, treatment burden, quality of life. In addition to a process evaluation of the VCoP, we will conduct an economic evaluation estimating the relative cost-effectiveness of the VCoP from the perspectives of both the National Health System and the Community.Ethics and dissemination The trial was approved by Clinical Research Ethics Committees of Gregorio Marañón University Hospital in Madrid/Nuestra Señora Candelaria University Hospital in Santa Cruz de Tenerife. The results will be disseminated through workshops, policy briefs, peer-reviewed publications and local/international conferences.Trial registration number NCT06046326.

Abstract Background Despite attempts to improve the cross-sectoral flow of information, difficulties remain in routine healthcare. The resulting negative impact on continuity of care is often associated with poor health outcomes, especially in older patients. Our intervention aims to increase information availability with respect to medications and health conditions at the interface between inpatient and outpatient care and to contribute towards improving the quality of care in older patients. This pilot study focuses on feasibility and implementability. Methods The idea of the complex intervention has been developed in a previous study. This intervention will be tested in a prospective, multicenter, cluster-randomized (via web tool), controlled pilot trial with two parallel study arms (intervention and control group). The pilot study will be conducted in 20 general practices in Hesse and Saxony (Germany) and include 200 patients (≥ 65 years of age with multimorbidity and polypharmacy) recruited by the practices. Practice staff and patients will be blinded. We will use qualitative and quantitative methods to assess the feasibility and implementability of the intervention and the study design in a process evaluation covering topics ranging from expectations to experiences. In addition, the feasibility of proposed outcome parameters for the future definitive trial will be explored. The composite endpoint will include health-related patient outcomes (hospitalization, falls, and mortality using, e.g., the FIMA questionnaire), and we will assess information on medications (SIMS questionnaire), symptoms and side effects of the medication (pro-CTCAE questionnaire), and health literacy (HLQ questionnaire). Data will be collected at study begin (baseline) and after 6 months. Furthermore, the study will include surveys and interviews with patients, general practitioners, and healthcare assistants. Discussion The intervention was developed using a participatory approach involving stakeholders and patients. It aims to empower general practice teams as they provide patient-centered care and play a key role in the coordination and continuity of care. We aim to encourage patients to adopt an active role in their health care. Overall, we want to increase the availability of health-related information for patients and healthcare providers. The results of the pilot study will be used in the design and implementation of the future definitive trial. Trial registration The study was registered in DRKS-German Clinical Trials Register: registration number DRKS00027649 (date: 19 January 2022). Date and version identifier 10.07.2023; Version 1.3

Abstract Background Measurement of multimorbidity in research is variable, including the choice of the data source used to ascertain conditions. We compared the estimated prevalence of multimorbidity and associations with mortality using different data sources. Methods A cross-sectional study of SAIL Databank data including 2,340,027 individuals of all ages living in Wales on 01 January 2019. Comparison of prevalence of multimorbidity and constituent 47 conditions using data from primary care (PC), hospital inpatient (HI), and linked PC-HI data sources and examination of associations between condition count and 12-month mortality. Results Using linked PC-HI compared with only HI data, multimorbidity was more prevalent (32.2% versus 16.5%), and the population of people identified as having multimorbidity was younger (mean age 62.5 versus 66.8 years) and included more women (54.2% versus 52.6%). Individuals with multimorbidity in both PC and HI data had stronger associations with mortality than those with multimorbidity only in HI data (adjusted odds ratio 8.34 [95% CI 8.02-8.68] versus 6.95 (95%CI 6.79-7.12] in people with ≥ 4 conditions). The prevalence of conditions identified using only PC versus only HI data was significantly higher for 37/47 and significantly lower for 10/47: the highest PC/HI ratio was for depression (14.2 [95% CI 14.1–14.4]) and the lowest for aneurysm (0.51 [95% CI 0.5–0.5]). Agreement in ascertainment of conditions between the two data sources varied considerably, being slight for five (kappa

BackgroundThe transition of patients between inpatient and outpatient care can lead to adverse events and medication-related problems due to medication and communication errors, such as medication discontinuation, the frequency of (re-)hospitalizations, and increased morbidity and mortality. Older patients with multimorbidity and polypharmacy are particularly at high risk during transitions of care. Previous research highlighted the need for interventions to improve transitions of care in order to support information continuity, coordination, and communication. The HYPERION-TransCare project aims to improve the continuity of medication management for older patients during transitions of care.Methods and findingsUsing a qualitative design, 32 expert interviews were conducted to explore the perspectives of key stakeholders, which included healthcare professionals, patients and one informal caregiver, on transitions of care. Interviews were conducted between October 2020 and January 2021, transcribed verbatim and analyzed using content analysis. We narratively summarized four main topics (stakeholders' tasks, challenges, ideas for solutions and best practice examples, and patient-related factors) and mapped them in a patient journey map. Lacking or incomplete information on patients' medication and health conditions, inappropriate communication and collaboration between healthcare providers within and across settings, and insufficient digital support limit the continuity of medication management.ConclusionsThe study confirms that medication management during transitions of care is a complex process that can be compromised by a variety of factors. Legal requirements and standardized processes are urgently needed to ensure adequate exchange of information and organization of medication management before, during and after hospital admissions. Despite the numerous barriers identified, the findings indicate that involved healthcare professionals from both the inpatient and outpatient care settings have a common understanding.

Herbal medicines are becoming increasingly popular among patients because they are well tolerated and do not exert severe side effects. Nevertheless, they receive little consideration in therapeutic settings. The present article reviews the current state of research on the clinical benefits of herbal medicines on five indication groups, psychosomatic disorders, gynecological complaints, gastrointestinal disorders, urinary and upper respiratory tract infections. The study search was based on the database PubMed and concentrated on herbal medicines legally approved in Europe. After applying defined inclusion and exclusion criteria, 141 articles were selected: 59 for psychosomatic disorders (100% randomized controlled trials; RCTs), 20 for gynecological complaints (56% RCTs), 19 for gastrointestinal disorders (68% RCTs), 16 for urinary tract infections (UTI, 63% RCTs) and 24 for upper respiratory tract infections (URTI) (79% RCTs). For the majority of the studies, therapeutic benefits were evaluated by patient reported outcome measures (PROs). For psychosomatic disorders, gynecological complaints and URTI more than 80% of the study outcomes were positive, whereas the clinical benefit of herbal medicines for the treatment of UTI and gastrointestinal disorders was lower with 55%. The critical appraisal of the articles shows that there is a lack of high-quality studies and, with regard to gastrointestinal disorders, the clinical benefits of herbal medicines as a stand-alone form of therapy are unclear. According to the current state of knowledge, scientific evidence has still to be improved to allow integration of herbal medicines into guidelines and standard treatment regimens for the indications reviewed here. In addition to clinical data, real world data and outcome measures can add significant value to pave the way for herbal medicines into future therapeutic applications.

Plain English summary Digital patient and public involvement (PPI) activities differ from in-person meetings. For example, some forms of non-verbal cues and body language are limited and technical barriers may exist. Therefore, some research teams were hesitant to switch to a digital PPI format during the COVID-19 pandemic and postponed their PPI activities. In this paper, we aim to describe, how we adapted a PPI workshop series to a digital format, how patients and health care professionals experienced these digital workshops, and which conclusions we have drawn for future digital PPI activities. The workshop evaluation encompassed workshop observation protocols, participants’ feedback via chat on their chance to speak and the feasibility of the digital tools, and telephone interviews on participants’ experiences. The study results showed that moderators had an active role in verbally encouraging every participant to get involved. Technical challenges occurred, but were in most cases immediately addressed and solved. Most participants rated their chance to speak and the feasibility of the digital format as “very good”. They described the atmosphere as inclusive and on equal footing without hierarchy between different stakeholder groups. Participants reported benefits of the digital format such as overcoming geographical distance, saving time and combining workshop participation with professional or childcare obligations. They stressed technical support as a condition for getting actively involved in digital PPI. We conclude that some advantages of digital PPI may persist beyond the pandemic. Therefore, we encourage research teams to discuss the question of digital or in-person PPI with the involved patients and health professionals and decide on a case-by-case basis.

Background: Globally, noncommunicable diseases (NCD) demand a higher healthcare expenditure. Among NCDs, diabetes mellitus is often associated with multiple, co-existing chronic conditions. In low- and middle-income countries where most of the healthcare expenditure is borne out of pocket, diabetes management may pose a significant financial stress. Methods: A cross-sectional study was conducted in 17 urban primary healthcare facilities of Bhubaneswar to assess the healthcare utilization and out-of-pocket expenditure among type 2 diabetes patients attending these facilities. Healthcare utilization was determined by the number of visits to healthcare facilities in the last 6 months, and out-of-pocket expenditure was assessed by outpatient consultation fees, medicines, travels to health care facilities, and diagnostic tests. Total out-of-pocket expenditure was defined as the sum of these costs. Results: The median number of visits in 6 months for diabetes patients with any comorbidity was 4 and 5 for diabetes patients with more than 4 comorbidities. Among the comorbid conditions, depression, stroke, auditory impairment, and acid peptic disease were associated with higher healthcare utilization. The total out-of-pocket expense was 2.3 times higher among diabetes patients with any comorbid condition compared to patients with diabetes only. The total median expenditure was higher for diabetes patients having stroke, heart diseases, kidney diseases, and cancer compared with other comorbid conditions. The association of comorbidity in diabetes patients with health care utilization and out-of-pocket expenditure is statistically significant after adjustment for sociodemographic characteristics and diabetes duration. Conclusion: Considerable expenditure is incurred by diabetes patients attending primary healthcare facilities for the management of diabetes and other chronic conditions. This is a significant burden for diabetes patients below the poverty line and with limited or no insurance cover. There is a need to increase the coverage of insurance schemes to address the chronic conditions management expenditure of outpatients.

Abstract Background Due to ageing of the population the incidence of multimorbidity and polypharmacy is rising. Polypharmacy is a risk factor for medication-related (re)admission and therefore places a significant burden on the healthcare system. The reported incidence of medication-related (re)admissions varies widely due to the lack of a clear definition. Some medications are known to increase the risk for medication-related admission and are therefore published in the triggerlist of the Dutch guideline for Polypharmacy in older patients. Different interventions to support medication optimization have been studied to reduce medication-related (re)admissions. However, the optimal template of medication optimization is still unknown, which contributes to the large heterogeneity of their effect on hospital readmissions. Therefore, we implemented a clinical decision support system (CDSS) to optimize medication lists and investigate whether continuous use of a CDSS reduces the number of hospital readmissions in older patients, who previously have had an unplanned probably medication-related hospitalization. Methods The CHECkUP study is a multicentre randomized study in older (≥60 years) patients with an unplanned hospitalization, polypharmacy (≥5 medications) and using at least two medications from the triggerlist, from Zuyderland Medical Centre and Maastricht University Medical Centre+ in the Netherlands. Patients will be randomized. The intervention consists of continuous (weekly) use of a CDSS, which generates a Medication Optimization Profile, which will be sent to the patient’s general practitioner and pharmacist. The control group will receive standard care. The primary outcome is hospital readmission within 1 year after study inclusion. Secondary outcomes are one-year mortality, number of emergency department visits, nursing home admissions, time to hospital readmissions and we will evaluate the quality of life and socio-economic status. Discussion This study is expected to add evidence on the knowledge of medication optimization and whether use of a continuous CDSS ameliorates the risk of adverse outcomes in older patients, already at an increased risk of medication-related (re)admission. To our knowledge, this is the first large study, providing one-year follow-up data and reporting not only on quality of care indicators, but also on quality-of-life. Trial registration The trial was registered in the Netherlands Trial Register on October 14, 2018, identifier: NL7449 (NTR7691). https://www.trialregister.nl/trial/7449 .

BackgroundMultimorbidity is one of the greatest challenges facing health and social care systems globally. It is associated with high rates of health service use, adverse healthcare events, and premature death. Despite its importance, little is known about the effects of contextual determinants such as household and area characteristics on health and care outcomes for people with multimorbidity. This study protocol presents a plan for the examination of associations between individual, household, and area characteristics with important health and social care outcomes.MethodsThe study will use a cross-section of data from the SAIL Databank on 01 January 2019 and include all people alive and registered with a Welsh GP. The cohort will be stratified according to the presence or absence of multimorbidity, defined as two or more long-term conditions. Multilevel models will be used to examine covariates measured for individuals, households, and areas to account for social processes operating at different levels. The intra-class correlation coefficient will be calculated to determine the strength of association at each level of the hierarchy. Model outcomes will be any emergency department attendance, emergency hospital or care home admission, or mortality, within the study follow-up period.DiscussionHousehold and area characteristics might act as protective or risk factors for health and care outcomes for people with multimorbidity, in which case results of the analyses can be used to guide clinical and policy responses for effective targeting of limited resources.

Background It is particularly difficult for healthcare providers to deliver optimal medical care to multimorbid middle-aged persons because patients’ professional activities, family lives, and other everyday responsibilities hinder them from making necessary lifestyle changes. Our aim was to find out how patients and healthcare providers view and manage the problems of dealing with multimorbidity in middle age. Methods and findings This qualitative study consisted of three steps. First, we conducted semi-structured in-depth interviews with 15 purposively sampled middle-aged persons living with multimorbidity to explore the experiences of care in the context of their leisure time, family lives, and work. Second, further individual interviews were carried out to find out the views of 14 healthcare providers. Third, the results of the interviews with patients and healthcare providers were presented to and discussed with four healthcare providers at an interprofessional workshop. Interview data was coded using an inductive-deductive approach and analyzed using content analysis. While patients reflected on challenges in several life domains, healthcare providers differentiated between levels of challenges. Both shared recommendations for better care including i) helping patients cope, ii) providing relief in activities of daily living, iii) continuity of care, iv) interprofessional cooperation, v) health promotion/prevention, vi) expansion of health services and vii) general system-level changes. Furthermore, the healthcare provider workshop highlighted the importance of increasing patient-centeredness, reducing complexity through a care coordinator and promoting interprofessional cooperation/networking. Conclusions To further improve the care of patients living with multimorbidity, barriers to managing multiple chronic conditions and facilitators to navigating complex care scenarios should be explored not only for people beyond working age, but for individuals in their mid-life specifically.

BackgroundAnticholinergic burden has been associated with adverse outcomes such as falls. To date, no gold standard measure has been identified to assess anticholinergic burden, and no conclusion has been drawn on which of the different measure algorithms best predicts falls in older patients from general practice. This study compared the ability of five measures of anticholinergic burden to predict falls. To account for patients' individual susceptibility to medications, the added predictive value of typical anticholinergic symptoms was further quantified in this context.Methods and findingsTo predict falls, models were developed and validated based on logistic regression models created using data from two German cluster-randomized controlled trials. The outcome was defined as "≥ 1 fall" vs. "no fall" within a 6-month follow-up period. Data from the RIME study (n = 1,197) were used in model development, and from PRIMUM (n = 502) for external validation. The models were developed step-wise in order to quantify the predictive ability of anticholinergic burden measures, and anticholinergic symptoms. In the development set, 1,015 patients had complete data and 188 (18.5%) experienced ≥ 1 fall within the 6-month follow-up period. The overall predictive value of the five anticholinergic measures was limited, with neither the employed anticholinergic variable (binary / count / burden), nor dose-dependent or dose-independent measures differing significantly in their ability to predict falls. The highest c-statistic was obtained using the German Anticholinergic Burden Score (0.73), whereby the optimism-corrected c-statistic was 0.71 after interval validation using bootstrapping and 0.63 in the external validation. Previous falls and dizziness / vertigo had the strongest prognostic value in all models.ConclusionsThe ability of anticholinergic burden measures to predict falls does not appear to differ significantly, and the added value they contribute to risk classification in fall-prediction models is limited. Previous falls and dizziness / vertigo contributed most to model performance.

Abstract Background To investigate patients’ perspectives on polypharmacy and the use of a digital decision support system to assist general practitioners (GPs) in performing medication reviews. Methods Qualitative interviews with patients or informal caregivers recruited from participants in a cluster-randomized controlled clinical trial (cRCT). The interviews were transcribed verbatim and analyzed using thematic analysis. Results We conducted 13 interviews and identified the following seven themes: the patients successfully integrated medication use in their everyday lives, used medication plans, had both good and bad personal experiences with their drugs, regarded their healthcare providers as the main source of medication-related information, discussed medication changes with their GPs, had trusting relationships with them, and viewed the use of digital decision support tools for medication reviews positively. No unwanted adverse effects were reported. Conclusions Despite drug-related problems, patients appeared to cope well with their medications. They also trusted their GPs, despite acknowledging polypharmacy to be a complex field for them. The use of a digital support system was appreciated and linked to the hope that reasons for selecting specific medication regimens would become more comprehensible. Further research with a more diverse sampling might add more patient perspectives. Trial registration ClinicalTrials.gov, NCT03430336 . Registered on February 6, 2018.

Objectives To compare opioid prescription rates between patients enrolled in coordinated ambulatory care and patients receiving usual care.Design In this retrospective cohort study, we analysed claims data for insured patients with non-specific/specific back pain or osteoarthritis of hip or knee from 2014 to 2017.Setting The study was based on administrative data provided by the statutory health insurance fund ‘Allgemeine Ortskrankenkasse’, in the state of Baden-Wurttemberg, Germany.Participants The intervention group consisted of patients enrolled in a coordinated ambulatory healthcare model; the control group included patients receiving usual care. Outcomes were overall strong and weak opioid prescriptions. Generalised linear regression models were used to analyse the effect of the intervention.Results Overall, 46 001 (non-specific 18 787/specific 27 214) patients with back pain and 19 366 patients with osteoarthritis belonged to the intervention group, and 7038 (2803/4235) and 963 patients to the control group, respectively. No significant difference in opioid prescriptions existed between the groups. However, the chance of being prescribed strong opioids was significantly lower in the intervention group (non-specific back pain: Odds Ratio (OR) 0.735, 95% Confidential Interval (CI) 0.563 to 0.960; specific back pain: OR 0.702, 95% CI 0.577 to 0.852; osteoarthritis: OR 0.644, 95% CI 0.464 to 0.892). The chance of being prescribed weak opioids was significantly higher in patients with specific back pain (OR 1.243, 95% CI 1.032 to 1.497) and osteoarthritis (OR 1.493, 95% CI 1.037 to 2.149) in the intervention group.Conclusion Coordinated ambulatory healthcare appears to be associated with a lower prescription rate for strong opioids in patients with chronic musculoskeletal disorders.Trial registration number German Clinical Trials Register (DRKS00017548).

Abstract Aim To explore the perceived barriers and facilitators in the management of the patients having diabetes with comorbidities by primary care physicians. Methods A qualitative In-Depth Interview study was conducted among the primary care physicians at seventeen urban primary health care centres at Bhubaneswar city of Odisha, India. The digitally recorded interviews were transcribed verbatim and translated into English. The data were analysed using thematic analysis. Results Barriers related to physicians, patients and health system were identified. Physicians felt lack of necessary knowledge and skills, communication skills and overburdening due to multiple responsibilities to be major barriers to quality care. Patients’ attitude and beliefs along with socio-economic status played an important role in treatment adherence and in the management of their disease conditions. Poor infrastructure, irregular medicine supply, and shortage of skilled allied health professionals were also found to be barriers to optimal care delivery, as was the lack of electronic medical records and personal treatment records. Conclusion Comprehensive guidelines with on the job training for capacity building of the physicians and creation of multidisciplinary teams at primary care level for a more holistic approach towards management of diabetes with comorbidities could be the way forward to optimal delivery of care.

Abstract Background In case-control studies most algorithms allow the controls to be sampled several times, which is not always optimal. If many controls are available and adjustment for several covariates is necessary, matching without replacement might increase statistical efficiency. Comparing similar units when having observational data is of utter importance, since confounding and selection bias is present. The aim was twofold, firstly to create a method that accommodates the option that a control is not resampled, and second, to display several scenarios that identify changes of Odds Ratios (ORs) while increasing the balance of the matched sample. Methods The algorithm was derived in an iterative way starting from the pre-processing steps to derive the data until its application in a study to investigate the risk of antibiotics on colorectal cancer in the INTEGO registry (Flanders, Belgium). Different scenarios were developed to investigate the fluctuation of ORs using the combination of exact and varying variables with or without replacement of controls. To achieve balance in the population, we introduced the Comorbidity Index (CI) variable, which is the sum of chronic diseases as a means to have comparable units for drawing valid associations. Results This algorithm is fast and optimal. We simulated data and demonstrated that the run-time of matching even with millions of patients is minimal. Optimal, since the closest controls is always captured (using the appropriate ordering and by creating some auxiliary variables), and in the scenario that a case has only one control, we assure that this control will be matched to this case, thus maximizing the cases to be used in the analysis. In total, 72 different scenarios were displayed indicating the fluctuation of ORs, and revealing patterns, especially a drop when balancing the population. Conclusions We created an optimal and computationally efficient algorithm to derive a matched case-control sample with and without replacement of controls. The code and the functions are publicly available as an open source in an R package. Finally, we emphasize the importance of displaying several scenarios and assess the difference of ORs while using an index to balance population in observational data.

Background: Many patients with ongoing complaints after a SARS-CoV-2 infection are treated in primary care. Existing medical guidelines on how to diagnose and treat Long-/Post-COVID are far from being comprehensive. This study aims to describe how German general practitioners (GPs) deal with this situation, what problems they experience when managing such patients, and how they solve problems associated with the diagnosis and treatment of Long-/Post-COVID. Methods and Findings: We conducted a qualitative study and interviewed 11 GPs. The most commonly described symptoms were ongoing fatigue, dyspnea, chest tightness and a decrease in physical capacity. The most common way to identify Long-/Post-COVID was by exclusion. Patients suffering from Long-/Post-COVID were generally treated by their GPs and rarely referred. A very common non-pharmacological intervention was to take a wait-and-see approach and grant sick leave. Other non-pharmacological interventions included lifestyle advices, physical exercise, acupuncture and exercises with intense aromas. Pharmacological treatments focused on symptoms, like respiratory symptoms or headaches. Our study’s main limitations are the small sample size and therefore limited generalizability of results. Conclusions: Further research is required to develop and test pharmaceutical and non-pharmaceutical interventions for patients with Long-/Post-COVID. In addition, strategies to prevent the occurrence of Long-/Post-COVID after an acute infection with SARS-CoV-2 have to be developed. The routine collection of data on the diagnosis and management of Long-/Post-COVID may help in the formulation of best practices. It is up to policymakers to facilitate the necessary implementation of effective interventions in order to limit the huge societal consequences of large groups of patients suffering from Long-/Post-COVID.

Introduction Older patients with multimorbidity, polypharmacy and related complex care needs represent a growing proportion of the population and a challenge for healthcare systems. Particularly in transitional care (hospital admission and hospital discharge), medical errors, inappropriate treatment, patient concerns and lack of confidence in healthcare are major problems that may arise from a lack of information continuity. The aim of this study is to develop an intervention to improve informational continuity of care at the interface between general practice and hospital care.Methods and analysis A qualitative approach will be used to develop our participatory intervention. Overall, 32 semistructured interviews with relevant stakeholders will be conducted and analysed. The stakeholders will include healthcare professionals from the outpatient setting (general practitioners, healthcare assistants, ambulatory care nurses) and the inpatient setting (clinical doctors, nurses, pharmacists, clinical information scientists) as well as patients and informal caregivers. At a series of workshops based on the results of the stakeholder analyses, we aim to develop a participatory intervention that will then be implemented in a subsequent pilot study. The same stakeholder groups will be invited for participation in the workshops.Ethics and dissemination Ethical approval for this study was waived by the Ethics Committee of Goethe University Frankfurt because of the nature of the proposed study. Written informed consent will be obtained from all study participants prior to participation. Results will be tested in a pilot study and disseminated at (inter)national conferences and via publication in peer-reviewed journals.Trial registation number Clinical Trials Register: registration number DRKS00027649.

BackgroundPrognostic models can help to identify patients at risk for end-stage kidney disease (ESKD) at an earlier stage to provide preventive medical interventions. Previous studies mostly applied the Cox proportional hazards model. The aim of this study is to present a resampling method, which can deal with imbalanced data structure for the prognostic model and help to improve predictive performance.MethodsThe electronic health records of patients with chronic kidney disease (CKD) older than 50 years during 2005–2015 collected from primary care in Belgium were used (n = 11,645). Both the Cox proportional hazards model and the logistic regression analysis were applied as reference model. Then, the resampling method, the Synthetic Minority Over-Sampling Technique-Edited Nearest Neighbor (SMOTE-ENN), was applied as a preprocessing procedure followed by the logistic regression analysis. The performance was evaluated by accuracy, the area under the curve (AUC), confusion matrix, and F3 score.ResultsThe C statistics for the Cox proportional hazards model was 0.807, while the AUC for the logistic regression analysis was 0.700, both on a comparable level to previous studies. With the model trained on the resampled set, 86.3% of patients with ESKD were correctly identified, although it was at the cost of the high misclassification rate of negative cases. The F3 score was 0.245, much higher than 0.043 for the logistic regression analysis and 0.022 for the Cox proportional hazards model.ConclusionThis study pointed out the imbalanced data structure and its effects on prediction accuracy, which were not thoroughly discussed in previous studies. We were able to identify patients with high risk for ESKD better from a clinical perspective by using the resampling method. But, it has the limitation of the high misclassification of negative cases. The technique can be widely used in other clinical topics when imbalanced data structure should be considered.

Abstract Background Knowledge graphs can represent the contents of biomedical literature and databases as subject-predicate-object triples, thereby enabling comprehensive analyses that identify e.g. relationships between diseases. Some diseases are often diagnosed in patients in specific temporal sequences, which are referred to as disease trajectories. Here, we determine whether a sequence of two diseases forms a trajectory by leveraging the predicate information from paths between (disease) proteins in a knowledge graph. Furthermore, we determine the added value of directional information of predicates for this task. To do so, we create four feature sets, based on two methods for representing indirect paths, and both with and without directional information of predicates (i.e., which protein is considered subject and which object). The added value of the directional information of predicates is quantified by comparing the classification performance of the feature sets that include or exclude it. Results Our method achieved a maximum area under the ROC curve of 89.8% and 74.5% when evaluated with two different reference sets. Use of directional information of predicates significantly improved performance by 6.5 and 2.0 percentage points respectively. Conclusions Our work demonstrates that predicates between proteins can be used to identify disease trajectories. Using the directional information of predicates significantly improved performance over not using this information.

Abstract Background Multimorbidity in primary care is a challenge not only for developing countries but also for low and medium income countries (LMIC). Health services in LMIC countries are being provided by both public and private health care providers. However, a critical knowledge gap exists on understanding the true extent of multimorbidity in both types of primary care settings. Methods We undertook a study to identify multimorbidity prevalence and healthcare utilization among both public and private primary care attendees in Odisha state of India. A total of 1649 patients attending 40 primary care facilities were interviewed using a structured multimorbidity assessment questionnaire collecting information on 22 chronic diseases, medication use, number of hospitalization and number of outpatient visits. Result The overall prevalence of multimorbidity was 28.3% and nearly one third of patients of public facilities and one fourth from private facilities had multimorbidity. Leading diseases among patients visiting public facilities included acid peptic diseases, arthritis and chronic back pain. No significant difference in reporting of hypertension and diabetes across the facilities was seen. Besides age, predictors of multimorbidity among patients attending public facilities were, females [AOR: 1.6; 95% CI 1.1–1.3] and non-aboriginal groups [AOR: 1.6; 95%CI 1.1–2.3] whereas, in private females [AOR: 1.6; 95%CI 1.1–2.4], better socioeconomic conditions [AOR 1.4; 95% CI 1.0–2.1] and higher educational status [primary school completed [AOR 2.6; 95%CI 1.6–4.2] and secondary schooling and above [AOR 2.0; 95%CI 1.1–3.6] with reference to no education were seen to be the determinants of multimorbidity. Increased number of hospital visits to public facilities were higher among lower educational status patients [IRR: 1.57; 95% CI 1.13–2.18] whereas, among private patients, the mean number of hospital visits was 1.70 times more in higher educational status [IRR: 1.70; 95%CI 1.01–3.69]. The mean number of medicines taken per day was higher among patients attending private hospitals. Conclusion Our findings suggest that, multimorbidity is being more reported in public primary care facilities. The pattern and health care utilization in both types of settings are different. A comprehensive care approach must be designed for private care providers.

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.

ObjectiveAfter 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.MethodsThis 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.ResultsMultimorbidity 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.ConclusionsWe 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.

Abstract Background Panic disorder (PD), frequently occurring with agoraphobia (AG), and depression are common mental disorders in primary care and associated with considerable individual and societal costs. Early detection and effective treatment of depression and PD/AG are of major importance. Cognitive behavioural exposure exercises have been shown to be effective in reducing anxiety and depressive symptoms. Practice team-based case management can improve clinical outcomes for patients with chronic diseases in primary care. The present study aims at evaluating the effects and cost-effectiveness of a primary care team-based intervention using behavioural therapy elements and case management supported by eHealth components in patients with PD/AG or depression compared to treatment as usual. Methods/design This is a two-arm cluster-randomized, controlled trial (cRCT). General practices represent the units of randomisation. General practitioners recruit adult patients with depression and PD ± AG according to the International Classification of Diseases, version 10 (ICD-10). In the intervention group, patients receive cognitive behaviour therapy-oriented psychoeducation and instructions to self-managed exposure exercises in four manual-based appointments with the general practitioner. A trained health care assistant from the practice team delivers case management and is continuously monitoring symptoms and treatment progress in ten protocol-based telephone contacts with patients. Practice teams and patients are supported by eHealth components. In the control group, patients receive usual care from general practitioners. Outcomes are measured at baseline (T0), at follow-up after 6 months (T1), and at follow-up after 12 months (T2). The primary outcome is the mental health status of patients as measured by the Mental Health Index (MHI-5). Effect sizes of 0.2 standard deviation (SD) are regarded as relevant. Assuming a drop-out rate of 20% of practices and patients each, we aim at recruiting 1844 patients in 148 primary care practices. This corresponds to 12.5 patients on average per primary care practice. Secondary outcomes include depression and anxiety-related clinical parameters and health-economic costs. Discussion If the intervention is more effective than treatment as usual, the three-component (cognitive behaviour therapy, case-management, eHealth) primary care-based intervention for patients suffering from PD/AG or depression could be a valuable low-threshold option that benefits patients and primary care practice teams. Trial registration German clinical trials register, DRKS00016622. Registered on February 22nd, 2019.

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.

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.PROSPERO registration number CRD42020188879.

Abstract Background Multimorbidity, the coexistence of two or more chronic conditions is increasingly prevalent in primary care populations. Despite reports on its adverse impact on health outcomes, functioning and well-being, it’s association with quality of life is not well known in low and middle income countries. We assessed the health-related quality of life (HRQoL) of primary care patients with multimorbidity and identified the influencing factors. Methods This cross-sectional study was done across 20 public and 20 private primary care facilities in Odisha, India. Data were collected from 1649 adult out-patients using a structured multimorbidity assessment questionnaire for primary care (MAQ-PC). HRQoL was assessed by the 12-item short-form health survey (SF-12). Both physical (PCS) and mental components scores (MCS) were calculated. Multiple regression analysis was performed to determine the association of HRQoL with socio-demographics, number, severity and typology of chronic conditions. Results Around 28.3% [95% CI: 25.9–30.7] of patients had multimorbidity. Mean physical component scope (PCS) and mental component score (MCS) of QoL in the study population was 43.56 [95% CI: 43.26–43.86] and 43.69 [95% CI: 43.22–44.16], respectively. Patients with multimorbidity reported poorer mean PCS [43.23, 95% CI: 42.62–43.84] and MCS [41.58, 95% CI: 40.74–42.43] compared to those without. After adjusting for other variables, morbidity severity burden score was found to be negatively associated with MCS [adjusted coefficient: -0.24, 95% CI − 0.41 to − 0.08], whereas no significant association was seen with PCS. Hypertension and diabetes with arthritis and acid peptic diseases were found to be negatively related with MCS. Within multimorbidity, lower education was inversely associated with mental QoL and positively associated with physical QoL score after adjusting for other variables. Conclusion Our findings demonstrate the diverse negative effects of multimorbidity on HRQoL and reveal that apart from count of chronic conditions, severity and pattern also influence HRQoL negatively. Health care providers should consider severity as an outcome measure to improve QoL especially in individuals with physical multimorbidity. Given the differences observed between age groups, it is important to identify specific care needs for each group. Musculoskeletal clusters need prioritised attention while designing clinical guidelines for multimorbidity.

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: Cumulative anticholinergic exposure, also known as anticholinergic burden, is associated with a variety of adverse outcomes. However, studies show that anticholinergic effects tend to be underestimated by prescribers, and anticholinergics are the most frequently prescribed potentially inappropriate medication in older patients. The grading systems and drugs included in existing scales to quantify anticholinergic burden differ considerably and do not adequately account for patients’ susceptibility to medications. Furthermore, their ability to link anticholinergic burden with adverse outcomes such as falls is unclear. This study aims to develop a prognostic model that predicts falls in older general practice patients, to assess the performance of several anticholinergic burden scales, and to quantify the added predictive value of anticholinergic symptoms in this context.Methods: Data from two cluster-randomized controlled trials investigating medication optimization in older general practice patients in Germany will be used. One trial (RIME, n = 1,197) will be used for the model development and the other trial (PRIMUM, n = 502) will be used to externally validate the model. A priori, candidate predictors will be selected based on a literature search, predictor availability, and clinical reasoning. Candidate predictors will include socio-demographics (e.g. age, sex), morbidity (e.g. single conditions), medication (e.g. polypharmacy, anticholinergic burden as defined by scales), and well-being (e.g. quality of life, physical function). A prognostic model including sociodemographic and lifestyle-related factors, as well as variables on morbidity, medication, health status, and well-being, will be developed, whereby the prognostic value of extending the model to include additional patient-reported symptoms will be also assessed. Logistic regression will be used for the binary outcome, which will be defined as “no falls” vs. “≥1 fall” within six months of baseline, as reported in patient interviews.Discussion: As the ability of different anticholinergic burden scales to predict falls in older patients is unclear, this study may provide insights into their relative importance as well as into the overall contribution of anticholinergic symptoms and other patient characteristics. The results may support general practitioners in their clinical decision-making and in prescribing fewer medications with anticholinergic properties.

Background Polypharmacy interventions are resource-intensive and should be targeted to those at risk of negative health outcomes. Our aim was to develop and internally validate prognostic models to predict health-related quality of life (HRQoL) and the combined outcome of falls, hospitalisation, institutionalisation and nursing care needs, in older patients with multimorbidity and polypharmacy in general practices.Methods Design: two independent data sets, one comprising health insurance claims data (n=592 456), the other data from the PRIoritising MUltimedication in Multimorbidity (PRIMUM) cluster randomised controlled trial (n=502). Population: ≥60 years, ≥5 drugs, ≥3 chronic diseases, excluding dementia. Outcomes: combined outcome of falls, hospitalisation, institutionalisation and nursing care needs (after 6, 9 and 24 months) (claims data); and HRQoL (after 6 and 9 months) (trial data). Predictor variables in both data sets: age, sex, morbidity-related variables (disease count), medication-related variables (European Union-Potentially Inappropriate Medication list (EU-PIM list)) and health service utilisation. Predictor variables exclusively in trial data: additional socio-demographics, morbidity-related variables (Cumulative Illness Rating Scale, depression), Medication Appropriateness Index (MAI), lifestyle, functional status and HRQoL (EuroQol EQ-5D-3L). Analysis: mixed regression models, combined with stepwise variable selection, 10-fold cross validation and sensitivity analyses.Results Most important predictors of EQ-5D-3L at 6 months in best model (Nagelkerke’s R² 0.507) were depressive symptoms (−2.73 (95% CI: −3.56 to −1.91)), MAI (−0.39 (95% CI: −0.7 to −0.08)), baseline EQ-5D-3L (0.55 (95% CI: 0.47 to 0.64)). Models based on claims data and those predicting long-term outcomes based on both data sets produced low R² values. In claims data-based model with highest explanatory power (R²=0.16), previous falls/fall-related injuries, previous hospitalisations, age, number of involved physicians and disease count were most important predictor variables.Conclusions Best trial data-based model predicted HRQoL after 6 months well and included parameters of well-being not found in claims. Performance of claims data-based models and models predicting long-term outcomes was relatively weak. For generalisability, future studies should refit models by considering parameters representing well-being and functional status.

ObjectiveAn increasing number of diseases is linked to deterioration of quality of life (QoL). Part of this association can be explained by socio-economic factors, which are most commonly accounted for. Our aim was to explore the potential contribution of other factors related to clinical burden, social interaction and functioning.MethodsA cross-sectional analysis was conducted on wave 6 of the population-based Survey of Health, Ageing and Retirement in Europe (SHARE), among participants aged 50+ (n = 67 179). The Control, Autonomy, Self-Realization and Pleasure (CASP-12v1) questionnaire measured QoL. The association between number of diseases and QoL was tested in a mixed-effects linear regression model. The base model controlled for socio-economic characteristics. Factors of interest (symptoms, polypharmacy, unmet care needs, utilisation of care, social network, personal and financial help, loneliness and activities of daily living (ADL) with instrumental activities (IADL)) were added to the base model one at a time and tested for relevance (i.e. change in the β-coefficient of the number of conditions of 15% or more).ResultsSymptoms, polypharmacy, loneliness and ADL/IADL appeared relevant and were retained in the final model. The association between number of conditions and QoL in the base model was -2.44 [95% CI: -2.72; -2.16], while this association was -0.76 [95%CI: -0.97; -0.54] after all relevant factors were included.ConclusionFactors beyond the socio-economic circumstances play an important role in explaining the association between number of conditions and QoL. These factors should be considered to better estimate the impact of chronic diseases on QoL, and for improving patient care.

Abstract Background The current study evaluated time trends of statin use and incidence of recurrent CVD in secondary prevention from 1999 to 2013 and investigated which factors were associated with statin use in secondary prevention. Methods Intego is a primary care registration network with 111 general practitioners working in 48 practices in Flanders, Belgium. This retrospective registry-based study included patients aged 50 years or older with a history of CVD. The time trends of statin use and incidence of recurrent CVD in secondary prevention were determined by using a joinpoint regression analysis. Multivariable mixed-effect logistic regression analysis was used to assess factors associated with statin use in patients in secondary prevention in 2013. Results The overall prevalence of statin use increased and showed two trends: a sharp increase from 1999 to 2005 (annual percentage change (APC) 25.4%) and a weaker increase from 2005 to 2013 (APC 3.7%). The average increase in statin use was the highest in patients aged 80 and older. Patients aged 70–79 years received the most statins. Men used more statins than women did, but both genders showed similar time trends. The incidence of CVD decreased by an average APC of 3.9%. There were no differences between men and women and between different age groups. A significant decrease was only observed in older patients without statins prescribed. In 2013, 61% of the patients in secondary prevention did not receive a statin. The absence of other secondary preventive medication was strongly associated with less statin use. Gender, age and comorbidity were associated with statin use to a lesser degree. Conclusions The prevalence of statin use in secondary prevention increased strongly from 1999 to 2013. Less than 50% of patients with a history of CVD received a statin in 2013. Especially patients who did not receive other secondary preventive medication were more likely to not receive a statin. Despite the strong increase in statin use, there was only a small decrease in the incidence of recurrent CVD, and this occurred mainly in older patients without statins prescribed.

Background: Comorbidity is a cause of increased mortality, decreased quality of life and increased use of healthcare services. It is important particularly for physicians and other healthcare providers in primary care settings to evaluate these patients properly. Cardiovascular diseases (CVD) are the most common cause of death from non-communicable diseases worldwide and are characterized by a high level of comorbidities. Objectives: To address the distribution of CVDs and comorbidities across sociodemographic groups and associations between CVDs and comorbidities. Methods: A cross-sectional study was conducted using data of 67 786 patients. Data were collected by the Registration Network Family Practices (RegistratieNet Huisartspraktijken, RNH). Comorbidities were analysed using chi-square and logistic regression analyses. Results: At the time of study, 26.5% of the patients had at least one CVD and 10.5% of patients had two or more CVD diagnoses. The strongest association within cardiovascular diseases were between health failure and arrhythmias (OR: 9.20; 95%CI: 7.78–10.89). Coronary artery disease and hypertension had strong relationship with diabetes (OR: 2.22; 95%CI: 2.02–2.45, OR: 2.22; 95%CI: 2.02–2.45 respectively) and lipid metabolism disorders (OR: 2.04; 95%CI: 1.87–2.23, OR: 2.04; 95%CI: 1.87–2.23, respectively). The strongest associations for cerebrovascular diseases were with epilepsy (OR: 4.09; 95%CI: 3.29–5.10) and arrhythmias (OR: 2.23; 95%CI: 1.99–2.50). Conclusion: One out of every four patients suffered from at least one CVD. Having one CVD increased the risk of another, co-occurring CVD and a higher number of other chronic diseases.

Abstract Background The purpose of this paper is to analyse the utilization of formal and informal home care among older patients with cancer (OCP) and to compare this with middle-aged patients with cancer (MCP) and older patients without cancer (ONC). Additionally, we examined predictors of transitions towards formal care one year after a cancer diagnosis. Methods OCP and MCP had to be recruited within three months after a cancer diagnosis and have an estimated life expectancy over six months. ONC consisted of patients without known cancer, seen by the general practitioner. Formal and informal care were compared between the patient groups at baseline, i.e. shortly after a cancer diagnosis and changes in care were studied after one year. Results A total of 844 patients were evaluable for formal care at baseline and 469 patients (56%) at follow-up. At baseline, about half of older adults and 18% of MCP used formal care, while about 85% of cancer patients and 57% ONC used informal care. Formal care increased for all groups after one year though not significantly in OCP. The amount of informal care only changed in MCP which decreased after one year. Cancer-related factors and changes in need factors predict a transition towards formal care after a cancer diagnosis. Conclusions A cancer diagnosis has a different impact on the use of formal and informal care than ageing as such. The first year after a cancer diagnosis is an important time to follow-up on the patients’ needs for home care.

Abstract Background Morbidity estimates between different GP registration networks show large, unexplained variations. This research explores the potential of modeling differences between networks in distinguishing new (incident) cases from existing (prevalent) cases in obtaining more reliable estimates. Methods Data from five Dutch GP registration networks and data on four chronic diseases (chronic obstructive pulmonary disease [COPD], diabetes, heart failure, and osteoarthritis of the knee) were used. A joint model (DisMod model) was fitted using all information on morbidity (incidence and prevalence) and mortality in each network, including a factor for misclassification of prevalent cases as incident cases. Results The observed estimates vary considerably between networks. Using disease modeling including a misclassification term improved the consistency between prevalence and incidence rates, but did not systematically decrease the variation between networks. Osteoarthritis of the knee showed large modeled misclassifications, especially in episode of care-based registries. Conclusion Registries that code episodes of care rather than disease generally provide lower estimates of the prevalence of chronic diseases requiring low levels of health care such as osteoarthritis. For other diseases, modeling misclassification rates does not systematically decrease the variation between registration networks. Using disease modeling provides insight in the reliability of estimates.

Introduction Interaction of conditions and treatments, complicated care needs and substantial treatment burden make patient–physician encounters involving multimorbid older patients highly complex. To optimally integrate patients’ preferences, define and prioritise realistic treatment goals and individualise care, a patient-centred approach is recommended. However, the preferences of older patients, who are especially vulnerable and frequently multimorbid, have not been systematically investigated with regard to their health status. The purpose of this evidence map is to explore current research addressing health-related preferences of older patients with multimorbidity, and to identify the knowledge clusters and research gaps.Methods and analysis To identify relevant research, we will conduct searches in the electronic databases MEDLINE, EMBASE, PsycINFO, PSYNDEX, CINAHL, Social Science Citation Index, Social Science Citation Index Expanded and the Cochrane library from their inception. We will check reference lists of relevant articles and carry out cited reference research (forward citation tracking). Two independent reviewers will screen titles and abstracts, check full texts for eligibility and extract the data. Any disagreement will be resolved and consensus reached with the help of a third reviewer. We will include both qualitative and quantitative studies, and address preferences from the patients’ perspectives in a multimorbid population of 60 years or older. There will be no restrictions on the publication language. Data extraction tables will present study and patient characteristics, aim of study, methods used to identify preferences and outcomes (ie, type of preferences). We will summarise the data using tables and figures (ie, bubble plot) to present the research landscape and to describe clusters and gaps.Ethics and dissemination Due to the nature of the proposed evidence map, ethics approval will not be required. Results from our research will be disseminated by means of specifically prepared materials for patients, at relevant (inter)national conferences and via publication in peer-reviewed journals.

Background: Receiving a cancer diagnosis can be a major life event which causes distress even years after primary treatment. Aim: To examine the prevalence of distress in older patients with cancer (OPCs) up until 5 years post-diagnosis, and identify predictors present at time of diagnosis. Results are compared with reference groups of middle-aged patients with cancer (MPCs) and older patients without a cancer diagnosis (OPs). Design & setting: OPCs, MPCs, and OPs participated in a longitudinal cohort study in Belgium and the Netherlands by filling in questionnaires at designated time points from 2010–2019. Method: Data from 541 patients were analysed using multivariable logistic regression analyses. Results: At baseline, 40% of OPCs, 37% of MPCs, and 17% of OPs reported distress. After 5 years, 35% of OPCs, 23% of MPCs, and 25% of OPs reported distress. No significant predictors for long-term distress in OPCs and OPs were found. For MPCs, it was found that baseline distress (odds ratio [OR] 2.94; 95% confidence intervals [CI] = 1.40 to 6.19) and baseline fatigue (OR 4.71; 95% CI = 1.81 to 12.31) predicted long-term distress. Conclusion: Distress is an important problem for people with cancer, with peaks at different moments after diagnosis. Feelings of distress are present shortly after diagnosis but they decrease quickly for the majority of patients. In the long term, however, OPCs in particular appear to be most at risk for distress. This warrants extra attention from primary healthcare professionals, such as GPs who are often patients’ first medical contact point. More research into risk factors occurring later in an illness trajectory might shed more light on predictors for development of long-term distress.

ObjectivesThe aim of this paper was to describe the time trends in the prevalence of multimorbidity and polypharmacy in Flanders (Belgium) between 2000 and 2015, while controlling for age and sex.MethodsData were available from Intego, a Flemish-Belgian general practice-based morbidity registration network. The practice population between 2000 and 2015 was used as the denominator, representing a mean of 159,946 people per year. Age and gender-standardised prevalence rates were used for the trends of multimorbidity and polypharmacy in the total population and for subgroups. Joinpoint regression analyses were used to analyse the time trends and breaks in trends, for the entire population as well as for specific age and sex groups.ResultsOverall, in 2015, 22.7% of the population had multimorbidity, while the overall prevalence of polypharmacy was 20%. Throughout the study period the standardised prevalence rate of multimorbidity rose for both sexes and in all age groups. The largest relative increase in multimorbidity was observed in the younger age groups (up to the age of 50 years). The prevalence of polypharmacy showed a significant increase between 2000 and 2015 for all age groups except the youngest (0-25 years).ConclusionFor all adult age groups multimorbidity and polypharmacy are frequent, dynamic over time and increasing. This asks for both epidemiological and interventional studies to improve the management of the resulting complex care.

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.

Introduction: The Attitudes to Aging Questionnaire (AAQ) was developed to measure attitudes toward the aging process as a personal experience from the perspective of older people. The present study aimed to validate the French version of the AAQ. Participants and methods: This study examined factor structure, acceptability, reliability and validity of the AAQ’s French version in 238 Belgian adults aged 60 years or older. In addition, participants provided information on demographics, self-perception of their mental and physical health (single items), quality of life (WHOQOL-OLD) and social desirability (DS-36). Results: Exploratory Factor Analysis produced a three-factor solution accounting for 36.9% of the variance. No floor or ceiling effects were found. The internal consistency, measured by Cronbach’s alpha coefficients for the AAQ subscales were 0.62 (Physical Change), 0.74 (Psychological Growth), and 0.75 (Psychosocial Loss). A priori expected associations were found between AAQ subscales, self-reported health and quality of life, indicating good convergent validity. The scale also showed a good ability to discriminate between people with lower and higher education levels, supporting adequate known-groups validity. Finally, we confirmed the need to control for social desirability biases when assessing self-reported attitudes toward one’s own aging. Conclusion: The data support the usefulness of the French version of the AAQ for the assessment of attitudes toward their own aging in older people.

Background Physicians and other healthcare professionals involved in the care of patients with multimorbidity should consider the problems these patients experience in managing their own conditions. However, treatment burden from the patient's perspective has been poorly explored, even though this might hamper treatment adherence. Objective The present study examined the experiences of patients with multimorbidity in primary care in the Netherlands and Belgium using semi-structured interviews, with special attention to the daily life domains of treatment burden. Design Individual interviews gathering qualitative data to explore the treatment burden experienced by patients with multimorbidity in primary care. Twenty-two patients agreed to participate: seven men and fifteen women. The recorded interviews were transcribed verbatim and evaluated using thematic content analysis. Results The patients reported numerous aspects of treatment burden they experienced in various domains of their daily lives. These topics were categorized into four daily life domains of burden: organization of care, medication, patient's role, and impact on daily life (including the involvement of caregivers). Conclusions The findings indicate that primary care patients with multimorbidity report treatment burden in several domains of their daily lives, not restricted to medical issues, such as side effects of medication. Some issues, such as those related to organization of care, seem easily modifiable. Further research is required focusing on special factors of treatment burden as experienced by patients with multimorbidity, and the implications for treatment adherence, especially in European settings, as little information is currently available.

BackgroundRecent reports have suggested declining age-specific incidence rates of dementia in high-income countries over time. Improved education and cardiovascular health in early age have been suggested to be bringing about this effect. The aim of this study was to estimate the age-specific dementia incidence trend in primary care records from a large population in the Netherlands.Methods and findingsA dynamic cohort representative of the Dutch population was composed using primary care records from general practice registration networks (GPRNs) across the country. Data regarding dementia incidence were obtained using general-practitioner-recorded diagnosis of dementia within the electronic health records. Age-specific dementia incidence rates were calculated for all persons aged 60 y and over; negative binomial regression analysis was used to estimate the time trend. Nine out of eleven GPRNs provided data on more than 800,000 older people for the years 1992 to 2014, corresponding to over 4 million person-years and 23,186 incident dementia cases. The annual growth in dementia incidence rate was estimated to be 2.1% (95% CI 0.5% to 3.8%), and incidence rates were 1.08 (95% CI 1.04 to 1.13) times higher for women compared to men. Despite their relatively low numbers of person-years, the highest age groups contributed most to the increasing trend. There was no significant overall change in incidence rates since the start of a national dementia program in 2003 (-0.025; 95% CI -0.062 to 0.011). Increased awareness of dementia by patients and doctors in more recent years may have influenced dementia diagnosis by general practitioners in electronic health records, and needs to be taken into account when interpreting the data.ConclusionsWithin the clinical records of a large, representative sample of the Dutch population, we found no evidence for a declining incidence trend of dementia in the Netherlands. This could indicate true stability in incidence rates, or a balance between increased detection and a true reduction. Irrespective of the exact rates and mechanisms underlying these findings, they illustrate that the burden of work for physicians and nurses in general practice associated with newly diagnosed dementia has not been subject to substantial change in the past two decades. Hence, with the ageing of Western societies, we still need to anticipate a dramatic absolute increase in dementia occurrence over the years to come.

Multimorbidity is increasingly the primary concern of healthcare systems globally with substantial implications for patient outcomes and resource cost. A critical knowledge gap exists as to the magnitude of multimorbidity in primary care practice in low and middle income countries with available information limited to prevalence. In India, primary care forms the bulk of the health care delivery being provided through both public (community health center) and private general practice setting. We undertook a study to identify multimorbidity patterns and relate these patterns to severity among primary care attendees in Odisha state of India. A total of 1649 patients attending 40 primary care facilities were interviewed using a structured multimorbidity assessment questionnaire. Multimorbidity patterns (dyad and triad) were identified for 21 chronic conditions, functional limitation was assessed as a proxy measure of severity and the mean severity score for each pattern, was determined after adjusting for age. The leading dyads in younger age group i.e. 18-29 years were acid peptic disease with arthritis/ chronic back ache/tuberculosis /chronic lung disease, while older age groups had more frequent combinations of hypertension + arthritis/ chronic lung disease/vision difficulty, and arthritis + chronic back ache. The triad of acid peptic disease + arthritis + chronic backache was common in men in all age groups. Tuberculosis and lung diseases were associated with significantly higher age-adjusted mean severity score (poorer functional ability). Among men, arthritis, chronic backache, chronic lung disease and vision impairment were observed to have highest severity) whereas women reported higher severity for combinations of hypertension, chronic back ache and arthritis. Given the paucity of studies on multimorbidity patterns in low and middle income countries, future studies should seek to assess the reproducibility of our findings in other populations and settings. Another task is the potential implications of different multimorbidity clusters for designing care protocols, as currently the protocols are disease specific, hardly taking comorbidity into account.