Long-term care homes play an essential role within health and social care. Successful measures to support older people at home for longer have led to increased prevalence of disability, frailty and... Show moreLong-term care homes play an essential role within health and social care. Successful measures to support older people at home for longer have led to increased prevalence of disability, frailty and cognitive impairment in those who live in care homes over the last two decades. The need for care home places is projected to increase for the next two decades. Modern care homes provide care for people who are predominantly over 80, have multiple long-term conditions, take multiple medicines, are physically dependent and live with cognitive impairment. Residents do better when services recognise the contributions of staff and care home providers rather than treating residents as individual patients living in a communal setting. There is a strong case given residents' frailty, multimorbidity and disability, that care should be structured around Comprehensive Geriatric Assessment (CGA). Care should be designed to allow opportunities for multiprofessional teams to come together for CGA, particularly if healthcare professionals are based outside care homes. Good data about care homes and residents are central to efforts to deliver high quality care-in some countries, these data are collected but not collated. Collating such data is a priority. Care home staff are under-recognised and underpaid-parity of pay and opportunity with NHS staff is the bare minimum to ensure that the best are recruited and retained in the sector. During the COVID-19 pandemic, residents and relatives have frequently been left out of decisions about policies that affect them, and better consultation is needed to deliver high quality care. Show less
Lay Summary Mental health problems among children and youths are common and have impacts, not only on the person affected but also on families and communities. They are often not recognized and... Show moreLay Summary Mental health problems among children and youths are common and have impacts, not only on the person affected but also on families and communities. They are often not recognized and acted upon by primary care providers (PCPs), such as general practitioners. This may be due to a lack of confidence in talking to young people or insufficient knowledge about mental health problems. PCPs make decisions about managing or referring these problems to mental health specialists, which can be assisted through clinical decision support methods (CDSMs). CDSMs can be divided into electronic and non-electronic. This study provided an overview of both types of CDSMs. We focused on the capabilities of CDSMs and how they help PCPs in their decision-making. More than half of the reviewed CDSMs were electronic CDSMs; several CDSMs involved telecommunication between PCPs and mental health specialists. Two of the CDSMs comprised a combination of components of both types of CDSMs. CDSMs offered patients more information about their health while providing PCPs with suggestions for their decision-making.Background Mental health disorders among children and youths are common and often have negative consequences for children, youths, and families if unrecognized and untreated. With the goal of early recognition, primary care physicians (PCPs) play a significant role in the detection and referral of mental disorders. However, PCPs report several barriers related to confidence, knowledge, and interdisciplinary collaboration. Therefore, initiatives have been taken to assist PCPs in their clinical decision-making through clinical decision support methods (CDSMs). Objectives This review aimed to identify CDSMs in the literature and describe their functionalities and quality. Methods In this review, a search strategy was performed to access all available studies in PubMed, PsychINFO, Embase, Web of Science, and COCHRANE using keywords. Studies that involved CDSMs for PCP clinical decision-making regarding psychosocial or psychiatric problems among children and youths (0-24 years old) were included. The search was conducted according to PRISMA-Protocols. Results Of 1,294 studies identified, 25 were eligible for inclusion and varied in quality. Eighteen CDSMs were described. Fourteen studies described computer-based methods with decision support, focusing on self-help, probable diagnosis, and treatment suggestions. Nine studies described telecommunication methods, which offered support through interdisciplinary (video) calls. Two studies described CDSMs with a combination of components related to the two CDSM categories. Conclusion Easy-to-use CDSMs of good quality are valuable for advising PCPs on the detection and referral of children and youths with mental health disorders. However, valid multicentre research on a combination of computer-based methods and telecommunication is still needed. Show less
Background A variety of information sources are used in the best-evidence diagnostic procedure in child and adolescent mental healthcare, including evaluation by referrers and structured assessment... Show moreBackground A variety of information sources are used in the best-evidence diagnostic procedure in child and adolescent mental healthcare, including evaluation by referrers and structured assessment questionnaires for parents. However, the incremental value of these information sources is still poorly examined. Aims To quantify the added and unique predictive value of referral letters, screening, multi-informant assessment and clinicians' remote evaluations in predicting mental health disorders. Method Routine medical record data on 1259 referred children and adolescents were retrospectively extracted. Their referral letters, responses to the Strengths and Difficulties Questionnaire (SDQ), results on closed-ended questions from the Development and Well-Being Assessment (DAWBA) and its clinician-rated version were linked to classifications made after face-to-face intake in psychiatry. Following multiple imputations of missing data, logistic regression analyses were performed with the above four nodes of assessment as predictors and the five childhood disorders common in mental healthcare (anxiety, depression, autism spectrum disorders, attention-deficit hyperactivity disorder, behavioural disorders) as outcomes. Likelihood ratio tests and diagnostic odds ratios were computed. Results Each assessment tool significantly predicted the classified outcome. Successive addition of the assessment instruments improved the prediction models, with the exception of behavioural disorder prediction by the clinician-rated DAWBA. With the exception of the SDQ for depressive and behavioural disorders, all instruments showed unique predictive value. Conclusions Structured acquisition and integrated use of diverse sources of information supports evidence-based diagnosis in clinical practice. The clinical value of structured assessment at the primary-secondary care interface should now be quantified in prospective studies. Show less
Objectives: To describe health care use and its associated factors in the chronic phase after stroke. Methods: Patients completed a questionnaire on health care use, 58 years after hospital... Show moreObjectives: To describe health care use and its associated factors in the chronic phase after stroke. Methods: Patients completed a questionnaire on health care use, 58 years after hospital admission for stroke. It comprised the number of visits to physicians or other health care professionals over the past 6 months (Physician-visits; Low <= 1 or High >= 2) and other health care professionals (Low = 0 or High >= 1). In addition the Longer-term Unmet Needs after Stroke (LUNS), Frenchay Activity Index (FAI) and Physical and Mental Component Summary Scales of the Short Form 12 (PCS and MCS) were administered. Their associations with health care use (high, low) were determined by means of logistic regression analysis, adjusted for sex and age. Results: Seventy-eight of 145 patients (54%) returned the questionnaires; mean time-since-stroke was 80.3 months (SD10.2), age-at-stroke 61.7 years (SD13.8), and 46 (59%) were male. Physician contacts concerned mainly the general practitioner (58; 79.5%). Forty-one (52.6%) and 37 (47.4%) of the patients had a high use of physician and other health professionals visits, respectively. Worse PCS scores were associated with both high use of physician and other health professionals visits (OR.931; 95%CI.877-.987 and OR.941; 95%CI.891-.993, respectively), whereas the FAI, MCS, or LUNS were not related to health care use. Conclusions: Health care use after stroke is substantial and is related to physical aspects of health status, not to mental aspects, activities or unmet needs, suggesting a mismatch between patients' needs and care delivered. Show less
Aim: To evaluate if, one year after notification of possible overtreatment, diabetes care providers de-intensified glucose-lowering medications and to gain insight into the opinions and beliefs of... Show moreAim: To evaluate if, one year after notification of possible overtreatment, diabetes care providers de-intensified glucose-lowering medications and to gain insight into the opinions and beliefs of both care providers and patients regarding de-intensification.Methods: Mixed methods using routine care data from five health-care centres in the Netherlands. Patient characteristics and medication prescription of patients, previously identified as possibly over-treated, were extracted from patients' medical records. Opinions of care providers were obtained through interviews. Patients received questionnaires about their diabetes treatment and were asked to participate in focus groups.Results: A total of 64 elderly patients with type 2 diabetes were previously identified as possibly over-treated and included; 57.8% male, median age 75 years (IQR=72-82), median diabetes duration 12 years (IQR=8-18). De-intensification was implemented in more than half (n=36) of them. Care providers preferred person-centred care above just setting general HbA1c target values, considering patient characteristics (such as comorbidity) and patient's preference. Patients valued glucose levels as most important in determining their treatment. Both patients and care providers felt that de-intensification should occur gradually.Conclusion: Treatment had been de-intensified in more than half of the patients (56.3%). Insight in reasons for not de-intensifying elderly patients is important since treatment for them can be "person-centred care". De-intensification is an iterative and time-intensive process. Show less
Kuipers, E.; Wensing, M.; Smet, P.A.G.M. de; Teichert, M. 2018
Background: Worldwide nearly 3 million people die from chronic obstructive pulmonary disease (COPD) every year. Integrated disease management (IDM) improves quality of life for COPD patients and... Show moreBackground: Worldwide nearly 3 million people die from chronic obstructive pulmonary disease (COPD) every year. Integrated disease management (IDM) improves quality of life for COPD patients and can reduce hospitalization. Self-management of COPD through eHealth is an effective method to improve IDM and clinical outcomes.Objectives: The objective of this implementation study was to investigate the effect of 3 chronic obstructive pulmonary disease eHealth programs applied in primary care on health status. The e-Vita COPD study compares different levels of integration of Web-based self-management platforms in IDM in 3 primary care settings. Patient health status is examined using the Clinical COPD Questionnaire (CCQ).Methods: The parallel cohort design includes 3 levels of integration in IDM (groups 1, 2, 3) and randomization of 2 levels of personal assistance for patients (group A, high assistance, group B, low assistance). Interrupted time series (ITS) design was used to collect CCQ data at multiple time points before and after intervention, and multilevel linear regression modeling was used to analyze CCQ data.Results: Of the 702 invited patients, 215 (30.6%) registered to a platform. Of these, 82 participated in group 1 (high integration IDM), 36 in group 1A (high assistance), and 46 in group 1B (low assistance); 96 participated in group 2 (medium integration IDM), 44 in group 2A (high assistance) and 52 in group 2B (low assistance); also, 37 participated in group 3 (no integration IDM). In the total group, no significant difference was found in change in CCQ trend (P=.334) before (-0.47% per month) and after the intervention (-0.084% per month). Also, no significant difference was found in CCQ changes before versus after the intervention between the groups with high versus low personal assistance. In all subgroups, there was no significant change in the CCQ trend before and after the intervention (group 1A, P=.237; 1B, P=.991; 2A, P=.120; 2B, P=.166; 3, P=.945).Conclusions: The e-Vita eHealth-supported COPD programs had no beneficial impact on the health status of COPD patients. Also, no differences were found between the patient groups receiving different levels of personal assistance. Show less
