Illness in Children and Parental Response

Most children suffer from illnesses from time to time. In only a small part of these ill children parents decide to seek professional help. So, most child health care is carried out by parents. In general, this phenomenon is called the iceberg of symptoms. The part of the iceberg under the surface is the illness that is experienced but not brought to the attention of a health care provider. Often this illness is of a self-limiting nature and medical attention is not necessary. The part above the surface consists of the illnesses brought to the attention of a health care professional, which In The Netherlands is the general practitioner (GP) for adults as well as for children

Molluscum contagiosum in Dutch general practice

BACKGROUND: While molluscum contagiosum is considered to be a frequently encountered disease, few data on its incidence are known. AIM: The objective of this study was to describe the incidence of molluscum contagiosum in Dutch general practice and to assess the importance of venereal molluscum contagiosum. METHOD: Data were taken from the national survey of morbidity and interventions in general practice, drawn from 103 practices across the Netherlands, with a study population of 332300. RESULTS: The infection appeared to be common in childhood (cumulative incidence 17% in those aged under 15 years); the adult, sexually transmitted, form was rare. Incidence was higher between January and June than between July and December. Cases were unequally divided between recording practices, which is though to have been caused by the occurrence of small epidemics. CONCLUSION: The incidence of molluscum contagiosum in Dutch general practice was found to be 2.4 per 1000 person years. Molluscum contagiosum should still be considered as a mainly paediatric disease

Effect of COVID-19 on health system integration in the Netherlands: a mixed-methods study

Objectives Overcrowding in acute care services gives rise to major problems, such as reduced accessibility and delay in treatment. In order to be able to continue providing high-quality health care, it is important that organizations are well integrated at all organizational levels. The objective of this study was to to gain an understanding in which extent cooperation within an urban acute care network in the Netherlands (The Hague) improved because of the COVID-19 crisis. Methods Exploratory mixed-methods questionnaire and qualitative interview study. Semistructured interviews with stakeholders in the acute care network at micro (n = 10), meso (n = 9), and macro (n = 3) levels of organization. Thematic analysis took place along the lines of the 6 dimensions of the Rainbow Model of Integrated Care. Results In this study we identified themes that may act as barriers or facilitators to cooperation: communication, interaction, trust, leadership, interests, distribution of care, and funding. During the crisis many facilitators were identified at clinical, professional, and system level such as clear agreements about work processes, trust in each other's work, and different stakeholders growing closer together. However, at an organizational and communicative level there were many barriers such as interference in each other's work and a lack of clear policies. Conclusion The driving force behind all changes in integration of acute care organizations in an urban context during the COVID-19 crisis seemed to be a great sense of urgency to cooperate in the shared interest of providing the best patient care. We recommend shifting the postcrisis focus from overcoming the crisis to overcoming cooperative challenges.Prevention, Population and Disease management (PrePoD)Public Health and primary car

Assessment of the Adjusted Clinical Groups system in Dutch primary care using electronic health records: a retrospective cross-sectional study

Background: Within the Dutch health care system the focus is shifting from a disease oriented approach to a more population based approach. Since every inhabitant in the Netherlands is registered with one general practice, this offers a unique possibility to perform Population Health Management analyses based on general practitioners’ (GP) registries. The Johns Hopkins Adjusted Clinical Groups (ACG) System is an internationally used method for predictive population analyses. The model categorizes individuals based on their complete health profile, taking into account age, gender, diagnoses and medication. However, the ACG system was developed with non-Dutch data. Consequently, for wider implementation in Dutch general practice, the system needs to be validated in the Dutch healthcare setting. In this paper we show the results of the first use of the ACG system on Dutch GP data. The aim of this study is to explore how well the ACG system can distinguish between different levels of GP healthcare utilization.Methods: To reach our aim, two variables of the ACG System, the Aggregated Diagnosis Groups (ADG) and the mutually exclusive ACG categories were explored. The population for this pilot analysis consisted of 23,618 persons listed with five participating general practices within one region in the Netherlands. ACG analyses were performed based on historical Electronic Health Records data from 2014 consisting of primary care diagnoses and pharmaceutical data. Logistic regression models were estimated and AUC’s were calculated to explore the diagnostic value of the models including ACGs and ADGs separately with GP healthcare utilization as the dependent variable. The dependent variable was categorized using four different cut-off points: zero, one, two and three visits per year.Results: The ACG and ADG models performed as well as models using International Classification of Primary Care chapters, regarding the association with GP utilization. AUC values were between 0.79 and 0.85. These modelsmperformed better than the base model (age and gender only) which showed AUC values between 0.64 and 0.71.Conclusion: The results of this study show that the ACG system is a useful tool to stratify Dutch primary care populations with GP healthcare utilization as the outcome variable.Prevention, Population and Disease management (PrePoD)Public Health and primary car

Measuring morbidity of children in the community: a comparison of interview and diary data

BACKGROUND: Little is known about the validity of estimates of morbidity experienced at home. METHODS: In the Dutch National Survey of Morbidity and Interventions in General Practice mothers of 1630 children answered a health interview and kept a health diary for 3 weeks (only the first 2 weeks were used). Children's symptoms were recorded during the interview using a check list and monitored in the health diary through open-ended questions. RESULTS: In the interview parents reported symptoms for 65% of their children and in the diary for 54% of children. Ear problems, colds, fever and weakness and anxiety were reported more often in the interview. Mother's mental health was assessed by the General Health Questionnaire; those scoring >4 were assessed as having impaired mental health and these parents reported symptoms for more children in the interview (81%) than in the diary (65%). For similar reference periods, the least educated mothers reported fewer children with symptoms in the diary (45%) than in the interview (66%). More highly educated mothers reported similarly in the diary (67%) and the interview (70%). CONCLUSION: Both data collection methods yield different estimates of community morbidity. Explanations such as telescoping, the seriousness of the symptoms, the amount of psychological distress of the respondent, forgetfulness and literacy limitations are discussed. We recommend that diaries should not be used in less educated populations

Identifying complex patients using Adjusted Clinical Groups risk stratification tool

OBJECTIVES: To produce an efficient and practically implementable method, based on primary care data exclusively, to identify patients with complex care needs who have problems in several health domains and are experiencing a mismatch of care. The Johns Hopkins ACG System was explored as a tool for identification, using its Aggregated Diagnosis Group (ADG) categories. STUDY DESIGN: Retrospective cross-sectional study using general practitioners' electronic health records combined with hospital data. METHODS: A prediction model for patients with complex care needs was developed using a primary care population of 105,345 individuals. Dependent variables in the model included age, sex, and the 32 ADGs. The prediction model was externally validated on 30,793 primary care patients. Discrimination and calibrations were assessed by computing C statistics and by visual inspection of the calibration plot, respectively. RESULTS: Our model was able to discriminate very well between complex and noncomplex patients (C statistic = 0.9; 95% CI, 0.88-0.92), whereas the calibration plot suggests that the model provides overestimates of complex patients. CONCLUSIONS: With this study, the ACG System has proven to be a useful tool in the identification of patients with complex care needs in primary care, opening up possibilities for tailored interventions of care management for this complex group of patients. Utilizing ADGs, the prediction model that we developed had a very good discriminatory ability to identify those complex patients. However, the of the model still needs improvement.Analysis and Stochastic

Collaboration processes and perceived effectiveness of integrated care projects in primary care: A longitudinal mixed-methods study

Background: Collaborative partnerships are considered an essential strategy for integrating local disjointed health and social services. Currently, little evidence is available on how integrated care arrangements between professionals and organisations are achieved through the evolution of collaboration processes over time. The first aim was to develop a typology of integrated care projects (ICPs) based on the final degree of integration as perceived by multiple stakeholders. The second aim was to study how types of integration differ in changes of collaboration processes over time and final perceived effectiveness. Methods: A longitudinal mixed-methods study design based on two data sources (surveys and interviews) was used to identify the perceived degree of integration and patterns in collaboration among 42 ICPs in primary care in The Netherlands. We used cluster analysis to identify distinct subgroups of ICPs based on the final perceived degree of integration from a professional, organisational and system perspective. With the use of ANOVAs, the subgroups were contrasted based on: 1) changes in collaboration processes over time (shared ambition, interests and mutual gains, relationship dynamics, organisational dynamics and process management) and 2) final perceived effectiveness (i.e. rated success) at the professional, organisational and system levels. Results: The ICPs were classified into three subgroups with: 'United Integration Perspectives (UIP)', 'Disunited Integration Perspectives (DIP)' and 'Professional-oriented Integration Perspectives (PIP)'. ICPs within the UIP subgroup made the strongest increase in trust-based (mutual gains and relationship dynamics) as well as control-based (organisational dynamics and process management) collaboration processes and had the highest overall effectiveness rates. On the other hand, ICPs with the DIP subgroup decreased on collaboration processes and had the lowest overall effectiveness rates. ICPs within the PIP subgroup increased in control-based collaboration processes (organisational dynamics and process management) and had the highest effectiveness rates at the professional level. Conclusions: The differences across the three subgroups in terms of the development of collaboration processes and the final perceived effectiveness provide evidence that united stakeholders' perspectives are achieved through a constructive collaboration process over time. Disunited perspectives at the professional, organisation and system levels can be aligned by both trust-based and control-based collaboration processes

Exploring the success of an integrated primary care partnership:A longitudinal study of collaboration processes

Background: Forming partnerships is a prominent strategy used to promote integrated service delivery across health and social service systems. Evidence about the collaboration process upon which partnerships evolve has rarely been addressed in an integrated-care setting. This study explores the longitudinal relationship of the collaboration process and the influence on the final perceived success of a partnership in such a setting. The collaboration process through which partnerships evolve is based on a conceptual framework which identifies five themes: shared ambition, interests and mutual gains, relationship dynamics, organisational dynamics and process management. Methods: Fifty-nine out of 69 partnerships from a national programme in the Netherlands participated in this survey study. At baseline, 338 steering committee members responded, and they returned 320 questionnaires at follow-up. Multiple-regression-analyses were conducted to explore the relationship between the baseline as well as the change in the collaboration process and the final success of the partnerships. Results: Mutual gains and process management were the most significant baseline predictors for the final success of the partnership. A positive change in the relationship dynamics had a significant effect on the final success of a partnership. Conclusions: Insight into the collaboration process of integrated primary care partnerships offers a potentially powerful way of predicting their success. Our findings underscore the importance of monitoring the collaboration process during the development of the partnerships in order to achieve their full collaborative advantage

A systematic review of risk stratification tools internationally used in primary care settings

Background and AimsIn our current healthcare situation, burden on healthcare services is increasing, with higher costs and increased utilization. Structured population health management has been developed as an approach to balance quality with increasing costs. This approach identifies sub-populations with comparable health risks, to tailor interventions for those that will benefit the most. Worldwide, the use of routine healthcare data extracted from electronic health registries for risk stratification approaches is increasing. Different risk stratification tools are used on different levels of the healthcare continuum. In this systematic literature review, we aimed to explore which tools are used in primary healthcare settings and assess their performance.MethodsWe performed a systematic literature review of studies applying risk stratification tools with health outcomes in primary care populations. Studies in Organisation for Economic Co-operation and Development countries published in English-language journals were included. Search engines were utilized with keywords, for example, “primary care,” “risk stratification,” and “model.” Risk stratification tools were compared based on different measures: area under the curve (AUC) and C-statistics for dichotomous outcomes and R2 for continuous outcomes.ResultsThe search provided 4718 articles. Specific election criteria such as primary care populations, generic health utilization outcomes, and routinely collected data sources identified 61 articles, reporting on 31 different models. The three most frequently applied models were the Adjusted Clinical Groups (ACG, n = 23), the Charlson Comorbidity Index (CCI, n = 19), and the Hierarchical Condition Categories (HCC, n = 7). Most AUC and C-statistic values were above 0.7, with ACG showing slightly improved scores compared with the CCI and HCC (typically between 0.6 and 0.7).ConclusionBased on statistical performance, the validity of the ACG was the highest, followed by the CCI and the HCC. The ACG also appeared to be the most flexible, with the use of different international coding systems and measuring a wider variety of health outcomes.Public Health and primary carePrevention, Population and Disease management (PrePoD