AbstractOBJECTIVES:After hospitalization, many older adults need post-acute care, including rehabilitation or home care. However, post-acute care expenses can be as high as the costs for the initial hospitalization. Detailed information on monthly post-acute health care expenditures and the characteristics of patients that make up for a large share of these expenditures is scarce. We aimed to calculate costs in acutely hospitalized older patients and identify patient characteristics that are associated with high post-acute care costs.DESIGN:Prospective multicenter cohort study (between October 2015 and June 2017).SETTING AND PARTICIPANTS:401 acutely hospitalized older persons from internal medicine, cardiology, and geriatric wards.MEASUREMENTS:Our primary outcome was mean post-acute care costs within 90 days postdischarge. Post-acute care costs included costs for unplanned readmissions, home care, nursing home care, general practice, and rehabilitation care. Three costs categories were defined: low [0-50th percentile (p0-50)], moderate (p50-75), and high (p75-100). Multinomial logistic regression analyses were conducted to assess the associations between costs and frailty, functional impairment, health-related quality of life, cognitive impairment, and depressive symptoms.RESULTS:Costs were distributed unevenly in the population, with the top 10.0% (n = 40) accounting for 52.1% of total post-acute care costs. Mean post-acute care costs were €4035 [standard deviation (SD) 4346] or $4560 (SD 4911). Frailty [odds ratio (OR) 3.44, 95% confidence interval (CI) 1.78-6.63], functional impairment (OR 1.80, 95% CI 1.03-3.16), and poor health-related quality of life (OR 1.89, 95% CI 1.09-3.28) at admission were associated with classification in the high-cost group, compared with the low-cost group.CONCLUSIONS/IMPLICATIONS:Post-acute care costs are substantial in a small portion of hospitalized older adults. Frailty, functional impairment, and poor health-related quality of life are associated with higher post-acute care costs and may be used as an indicator of such costs in practice.
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Perceptions and values of care professionals are critical in successfully implementing technology in health care. The aim of this study was threefold: (1) to explore the main values of health care professionals, (2) to investigate the perceived influence of the technologies regarding these values, and (3) the accumulated views of care professionals with respect to the use of technology in the future. In total, 51 professionals were interviewed. Interpretative phenomenological analysis was applied. All care professionals highly valued being able to satisfy the needs of their care recipients. Mutual inter-collegial respect and appreciation of supervisors was also highly cherished. The opportunity to work in a careful manner was another important value. Conditions for the successful implementation of technology involved reliability of the technology at hand, training with team members in the practical use of new technology, and the availability of a help desk. Views regarding the future of health care were mainly related to financial cut backs and with a lower availability of staff. Interestingly, no spontaneous thoughts about the role of new technology were part of these views. It can be concluded that professionals need support in relating technological solutions to care recipients' needs. The role of health care organisations, including technological expertise, can be crucial here.
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Background: The substitution of healthcare is a way to control rising healthcare costs. The Primary Care Plus (PC+) intervention of the Dutch ‘Blue Care’ pioneer site aims to achieve this feat by facilitating consultations with medical specialists in the primary care setting. One of the specialties involved is dermatology. This study explores referral decisions following dermatology care in PC+ and the influence of predictive patient and consultation characteristics on this decision. Methods: This retrospective study used clinical data of patients who received dermatology care in PC+ between January 2015 and March 2017. The referral decision following PC+, (i.e., referral back to the general practitioner (GP) or referral to outpatient hospital care) was the primary outcome. Stepwise logistic regression modelling was used to describe variations in the referral decisions following PC+, with patient age and gender, number of PC+ consultations, patient diagnosis and treatment specialist as the predicting factors. Results: A total of 2952 patients visited PC+ for dermatology care. Of those patients with a registered referral, 80.2% (N = 2254) were referred back to the GP, and 19.8% (N = 558) were referred to outpatient hospital care. In the multivariable model, only the treating specialist and patient’s diagnosis independently influenced the referral decisions following PC+. Conclusion: The aim of PC+ is to reduce the number of referrals to outpatient hospital care. According to the results, the treating specialist and patient diagnosis influence referral decisions. Therefore, the results of this study can be used to discuss and improve specialist and patient profiles for PC+ to further optimise the effectiveness of the initiative.
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Due to the ageing population, the prevalence of musculoskeletal disorders will continue to rise, as well as healthcare expenditure. To overcome these increasing expenditures, integration of orthopaedic care should be stimulated. The Primary Care Plus (PC+) intervention aimed to achieve this by facilitating collaboration between primary care and the hospital, in which specialised medical care is shifted to a primary care setting. The present study aims to evaluate the referral decision following orthopaedic care in PC+ and in particular to evaluate the influence of diagnostic tests on this decision. Therefore, retrospective monitoring data of patients visiting PC+ for orthopaedic care was used. Data was divided into two periods; P1 and P2. During P2, specialists in PC+ were able to request additional diagnostic tests (such as ultrasounds and MRIs). A total of 2,438 patients visiting PC+ for orthopaedic care were included in the analysis. The primary outcome was the referral decision following PC+ (back to the general practitioner (GP) or referral to outpatient hospital care). Independent variables were consultation- and patient-related predictors. To describe variations in the referral decision, logistic regression modelling was used. Results show that during P2, significantly more patients were referred back to their GP. Moreover, the multivariable analysis show a significant effect of patient age on the referral decision (OR 0.86, 95% CI = 0.81– 0.91) and a significant interaction was found between the treating specialist and the period (p = 0.015) and between patient’s diagnosis and the period (p < 0.001). Despite the significant impact of the possibility of requesting additional diagnostic tests in PC+, it is important to discuss the extent to which the availability of diagnostic tests fits within the vision of PC+. In addition, selecting appropriate profiles for specialists and patients for PC+ are necessary to further optimise the effectiveness and cost of care.
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Background: Information is scarce concerning the perceived needs and the amount of health-care utilization of persons with suicidal ideation (SI) compared to those without SI. Aims: To describe the needs and health care use of persons with and without SI and to investigate whether these differences are associated with the severity of the axis-I symptomatology. Method: Data were obtained from 1,699 respondents with a depressive and/or anxiety disorder who participated in the Netherlands Study of Depression and Anxiety. Persons with and without SI were distinguished. Outcome variables were perceived needs and health-care utilization. We used multivariate regression in two models: (1) adjusted only for sociodemographic variables and (2) adjusted additionally for severity of axis-I symptomatology. Results: Persons with SI had higher odds for both unmet and met needs in almost all domains and made more intensive use of mental-health care. Differences in needs and health-care utilization of persons with and without SI were strongly associated with severity of axis I symptomatology. Conclusions: Our results validate previous findings about perceived needs and health-care use of persons with SI. The results also suggest that suicidal persons are more seriously ill, and that they need more professional care, dedication, and specialized expertise than anxious and depressed persons without SI, especially in the domains of information and referral.
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Across all health care settings, certain patients are perceived as ‘difficult’ by clinicians. This paper’s aim is to understand how certain patients come to be perceived and labelled as ‘difficult’ patients in community mental health care, through mixed-methods research in The Netherlands between June 2006 and October 2009. A literature review, a Delphi-study among experts, a survey study among professionals, a Grounded Theory interview study among ‘difficult’ patients, and three case studies of ‘difficult’ patients were undertaken. Analysis of the results of these qualitative and quantitative studies took place within the concept of the sick role, and resulted in the construction of a tentative explanatory model. The ‘difficult’ patient-label is associated with professional pessimism, passive treatment and possible discharge or referral out of care. The label is given by professionals when certain patient characteristics are present and a specific causal attribution (psychological, social or moral versus neurobiological) about the patient’s behaviours is made. The status of ‘difficult’ patient is easily reinforced by subsequent patient and professional behaviour, turning initial unusual help-seeking behaviour into ‘difficult’ or ineffective chronic illness behaviour, and ineffective professional behaviour. These findings illustrate that the course of mental illness, or at least the course of patients’ contact with mental health professionals and services, is determined by patient and professional and reinforced by the social and mental health care system. This model adds to the broader sick role concept a micro-perspective in which attribution and learning principles are incorporated. On a practical level, it implies that professionals need to look into their own role in the perpetuation of difficult behaviours as described here.
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It is unclear to what extent self-employed choose to become self-employed. This study aimed to compare the health care expenditures-as a proxy for health-of self-employed individuals in the year before they started their business, to that of employees. Differences by sex, age, and industry were studied. In total, 5,741,457 individuals aged 25-65 years who were listed in the tax data between 2010 and 2015 with data on their health insurance claims were included. Self-employed and employees were stratified according to sex, age, household position, personal income, region, and industry for each of the years covered. Weighted linear regression was used to compare health care expenditures in the preceding (year x-1) between self-employed and employees (in year x). Compared with employees, expenditures for hospital care, pharmaceutical care and mental health care were lower among self-employed in the year before they started their business. Differences were most pronounced for men, individuals ≥40 years and those working in the industry and energy sector, construction, financial institutions, and government and care. We conclude that healthy individuals are overrepresented among the self-employed, which is more pronounced in certain subgroups. Further qualitative research is needed to investigate the reasons why these subgroups are more likely to choose to become self-employed.
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Introduction F-ACT is a flexible version of Assertive Community Treatment to deliver care in a changing intensity depending on needs of individuals with severe mental illnesses (Van Veldhuizen, 2007). In 2016 a number of the FACT-teams in the Dutch region of Utrecht moved to locations in neighborhoods and started to work as one network team together with neighborhood based facilities in primary care (GP’s) and in the social domain (supported living, social district teams, etc.). This should create better chances on clinical, social and personal recovery of service users. Objectives This study describes the implementation, obstacles and outcomes for service users. The main question is whether this Collaborative Mental Health Care in the Community produces better outcome than regular FACT. Measures include (met/unmet) needs for care, quality of life, clinical, functional and personal recovery, and hospital admission days. Methods Data on care utilization regarding the innovation are compared to regular FACT. Qualitative interviews are conducted to gain insight in the experiences of service users, their family members and mental health care workers. Changes in outcome measures of service users in pilot areas (N=400) were compared to outcomes of users (matched on gender and level of functioning) in regular FACT teams in the period 2015-2018 (total N=800). Results Data-analyses will take place from January to March 2019. Initial analyses point at a greater feeling of holding and safety for service users in the pilot areas and less hospital admission days. Conclusions Preliminary results support the development from FACT to a community based collaborative care service.
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Acne vulgaris is considered one of the most common medical skin conditions globally, affecting approximately 85% of individuals worldwide. While acne is most prevalent among adolescents between 15 to 24 years old, it is not uncommon in adults either. Acne addresses a number of different challenges, causing a multidimensional disease burden. These challenges include clinical sequelae, such as post inflammatory hyperpigmentation (PIH) and the chance of developing lifelong disfiguring scars, psychological aspects such as deficits in health related quality of life, chronicity of acne, economic factors, and treatment-related issues, such as antimicrobial resistance. The multidimensionality of the disease burden stipulates the importance of an effective and timely treatment in a well organised care system. Within the Netherlands, acne care provision is managed by several types of professional care givers, each approaching acne care from different angles: (I) general practitioners (GPs) who serve as ‘gatekeepers’ of healthcare within primary care; (II) dermatologists providing specialist medical care within secondary care; (III) dermal therapists, a non-physician medical professional with a bachelor’s degree, exclusively operating within the Australian and Dutch primary and secondary health care; and (IV) beauticians, mainly working within the cosmetology or wellness domain. However, despite the large variety in acne care services, many patients experience a delay between the onset of acne and receiving an effective treatment, or a prolonged use of care, which raises the question whether acne related care resources are being used in the most effective and (cost)efficient way. It is therefore necessary to gain insights into the organization and quality of Dutch acne health care beyond conventional guidelines and protocols. Exploring areas of care that may need improvement allow Dutch acne healthcare services to develop and improve the quality of acne care services in harmony with patient needs.
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Rationale, aims and objective: Primary Care Plus (PC+) focuses on the substitution of hospital-based medical care to the primary care setting without moving hospital facilities. The aim of this study was to examine whether population health and experience of care in PC+ could be maintained. Therefore, health-related quality of life (HRQoL) and experienced quality of care from a patient perspective were compared between patients referred to PC+ and to hospital-based outpatient care (HBOC). Methods: This cohort study included patients from a Dutch region, visiting PC+ or HBOC between December 2014 and April 2018. With patient questionnaires (T0, T1 and T2), the HRQoL and experience of care were measured. One-to-two nearest neighbour calliper propensity score matching (PSM) was used to control for potential selection bias. Outcomes were compared using marginal linear models and Pearson chi-square tests. Results: One thousand one hundred thirteen PC+ patients were matched to 606 HBOC patients with well-balanced baseline characteristics (SMDs <0.1). Regarding HRQoL outcomes, no significant interaction terms between time and group were found (P > .05), indicating no difference in HRQoL development between the groups over time. Regarding experienced quality of care, no differences were found between PC+ and HBOC patients. Only travel time was significantly shorter in the HBOC group (P ≤ .001). Conclusion: Results show equal effects on HRQoL outcomes over time between the groups. Regarding experienced quality of care, only differences in travel time were found. Taken as a whole, population health and quality of care were maintained with PC+ and future research should focus more on cost-related outcomes.
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