Reliably estimating prevalences of atopic children: An epidemiological study in an extensive and representative primary care database

Electronic health records stored in primary care databases might be a valuable source to study the epidemiology of atopic disorders and their impact on health-care systems and costs. However, the prevalence of atopic disorders in such databases varies considerably and needs to be addressed. For this study, all children aged 0-18 years listed in a representative primary care database in the period 2002-2014, with sufficient data quality, were selected. The effects of four different strategies on the prevalences of atopic disorders were examined: (1) the first strategy examined the diagnosis as recorded in the electronic health records, whereas the (2) second used additional requirements (i.e., the patient had at least two relevant consultations and at least two relevant prescriptions). Strategies (3) and (4) assumed the atopic disorders to be chronic based on strategy 1 and 2, respectively. When interested in cases with a higher probability of a clinically relevant disorder, strategy 2 yields a realistic estimation of the prevalence of atopic disorders derived from primary care data. Using this strategy, of the 478,076 included children, 28,946 (6.1%) had eczema, 29,182 (6.1%) had asthma, and 28,064 (5.9%) had allergic rhinitis; only 1251 (0.3%) children had all three atopic disorders. Prevalence rates are highly dependent on the clinical atopic definitions used. The strategy using cases with a higher probability of clinically relevant cases, yields realistic prevalences to establish the impact of atopic disorders on health-care systems. However, studies are needed to solve the problem of identifying atopic disorders that are missed or misclassified

Risks for comorbidity in children with atopic disorders: an observational study in Dutch general practices

OBJECTIVE: This study aimed to investigate both atopic and non-atopic comorbid symptoms and diseases in children with physician-diagnosed atopic disorders (atopic eczema, asthma and allergic rhinitis).METHODS: All children aged 0-18 years listed in a nationwide primary care database (the Netherlands Institute for Health Services Research-Primary Care Database) with routinely collected healthcare data in 2014 were selected. Children with atopic disorders were matched on age and gender with non-atopic controls within the same general practice. A total of 404 International Classification of Primary Care codes were examined. Logistic regression analyses were performed to examine the associations between the presence of atopic disorders and (non-)atopic symptoms and diseases by calculating ORs.RESULTS: Having one of the atopic disorders significantly increased the risk of having other atopic-related symptoms, even if the child was not registered as having the related atopic disorder. Regarding non-atopic comorbidity, children with atopic eczema (n=15 530) were at significantly increased risk for (infectious) skin diseases (OR: 1.2-3.4). Airway symptoms or (infectious) diseases (OR: 2.1-10.3) were observed significantly more frequently in children with asthma (n=7887). Children with allergic rhinitis (n=6835) had a significantly distinctive risk of ear-nose-throat-related symptoms and diseases (OR: 1.5-3.9). Neither age nor gender explained these increased risks.CONCLUSION: General practitioners are not always fully aware of relevant atopic and non-atopic comorbidity. In children known to have at least one atopic disorder, specific attention is required to avoid possible insufficient treatment and unnecessary loss of quality of life

Risk of pneumonia in the vicinity of goat farms: a comparative assessment of temporal variation based on longitudinal health data

BACKGROUND: Although the association between living in the vicinity of a goat farm and the occurrence of pneumonia is well-documented, it is unclear whether the higher risk of pneumonia in livestock dense areas is season-specific or not. This study explored the temporal variation of the association between exposure to goat farms and the occurrence of pneumonia. METHODS: A large population-based study was conducted in the Netherlands, based on electronic health records from 49 general practices, collected for a period of six consecutive years (2014-2019). Monthly incidence rates of pneumonia in a livestock dense area were compared with those of a control group (areas with low livestock density) both per individual year and cumulatively for the entire six-year period. Using individual estimates of livestock exposure, it was also examined whether incidence of pneumonia differed per month if someone lived within a certain radius from a goat farm, compared to residents who lived further away. RESULTS: Pneumonia was consistently more common in the livestock dense area throughout the year, compared to the control area. Analyses on the association between the individual livestock exposure estimates and monthly pneumonia incidence for the whole six-year period, yielded a generally higher risk for pneumonia among people living within 500 m from a goat farm, compared to those living further away. Significant associations were observed for March (IRR 1.68, 95% CI 1.02-2.78), August (IRR 2.67, 95% CI 1.45-4.90) and September (IRR 2.52, 95% CI 1.47-4.32). CONCLUSIONS: The increased occurrence of pneumonia in the vicinity of goat farms is not season-specific. Instead, pneumonia is more common in livestock dense areas throughout the year, including summer months

Assessing quality of hepato-pancreato-biliary surgery: nationwide benchmarking

Background: Clinical auditing is a powerful tool to evaluate and improve healthcare. Deviations from the expected quality of care are identified by benchmarking the results of individual hospitals using national averages. This study aimed to evaluate the use of quality indicators for benchmarking hepato-pancreato-biliary (HPB) surgery and when outlier hospitals could be identified. Methods: A population-based study used data from two nationwide Dutch HPB audits (DHBA and DPCA) from 2014 to 2021. Sample size calculations determined the threshold (in percentage points) to identify centres as statistical outliers, based on current volume requirements (annual minimum of 20 resections) on a two-year period (2020–2021), covering mortality rate, failure to rescue (FTR), major morbidity rate and textbook/ideal outcome (TO) for minor liver resection (LR), major LR, pancreaticoduodenectomy (PD) and distal pancreatectomy (DP). Results: In total, 10 963 and 7365 patients who underwent liver and pancreatic resection respectively were included. Benchmark and corresponding range of mortality rates were 0.6% (0 −3.2%) and 3.3% (0–16.7%) for minor and major LR, and 2.7% (0–7.0%) and 0.6% (0–4.2%) for PD and DP respectively. FTR rates were 5.4% (0–33.3%), 14.2% (0–100%), 7.5% (1.6%–28.5%) and 3.1% (0–14.9%). For major morbidity rate, corresponding rates were 9.8% (0–20.5%), 28.1% (0–47.1%), 36% (15.8%–58.3%) and 22.3% (5.2%–46.1%). For TO, corresponding rates were 73.6% (61.3%–94.4%), 54.1% (35.3–100), 46.8% (25.3%–59.4%) and 63.3% (30.7%–84.6%). Mortality rate thresholds indicating a significant outlier were 8.6% and 15.4% for minor and major LR and 14.2% and 8.6% for PD and DP. For FTR, these thresholds were 17.9%, 31.6%, 22.9% and 15.0%. For major morbidity rate, these thresholds were 26.1%, 49.7%, 57.9% and 52.9% respectively. For TO, lower thresholds were 52.5%, 32.5%, 25.8% and 41.4% respectively. Higher hospital volumes decrease thresholds to detect outliers. Conclusion: Current event rates and minimum volume requirements per hospital are too low to detect any meaningful between hospital differences in mortality rate and FTR. Major morbidity rate and TO are better candidates to use for benchmarking

Non-participation in population-based disease prevention programs in general practice

<p>Abstract</p> <p>Background</p> <p>The number of people with a chronic disease will strongly increase in the next decades. Therefore, prevention of disease becomes increasingly important. The aim of this systematic review was to identify factors that negatively influence participation in population-based disease prevention programs in General Practice and to establish whether the program type is related to non-participation levels.</p> <p>Methods</p> <p>We conducted a systematic review in Pubmed, EMBASE, CINAHL and PsycINFO, covering 2000 through July 6th 2012, to identify publications including information about characteristics of non-participants or reasons for non-participation in population-based disease prevention programs in General Practice.</p> <p>Results</p> <p>A total of 24 original studies met our criteria, seven of which focused on vaccination, eleven on screening aimed at early detection of disease, and six on screening aimed at identifying high risk of a disease, targeting a variety of diseases and conditions. Lack of personal relevance of the program, younger age, higher social deprivation and former non-participation were related to actual non-participation. No differences were found in non-participation levels or factors related to non-participation between the three program types. The large variation in non-participation levels within the program types may be partly due to differences in recruitment strategies, with more active, personalized strategies resulting in higher participation levels compared to an invitation letter.</p> <p>Conclusions</p> <p>There is still much to be gained by tailoring strategies to improve participation in those who are less likely to do so, namely younger individuals, those living in a deprived area and former non-participants. Participation may increase by applying more active recruitment strategies.</p

Amplified prevalence and incidence of cardiovascular disease in patients with inflammatory arthritis and coexistent autoimmune disorders

OBJECTIVE: This study aims to assess the prevalence proportion and incidence rate of cardiovascular morbidity in patients with inflammatory arthritis compared with that in controls, and to determine whether the co-existence of multiple autoimmune disorders is associated with an amplified risk of cardiovascular disease. METHODS: Data from the Nivel Primary Care Database were used to assess prevalence proportion and incidence rate of cardiovascular disease in patients with inflammatory arthritis only, patients with inflammatory arthritis coexistent with another autoimmune disorder, and controls. Hazard ratios were calculated using Cox regression models. RESULTS: The prevalence proportions in inflammatory arthritis patients were increased for type 1 diabetes [odds ratio (OR) 1.80, 95% CI: 1.27, 2.55], hypothyroidism (OR 1.49, 95% CI: 1.37, 1.61), psoriasis (OR 2.72, 95% CI: 2.49, 2.97) and IBD (OR 2.64, 95% CI: 2.28, 3.07) compared with that in controls. Cardiovascular disease prevalence (OR 1.34, 95% CI: 1.28, 1.41) and incidence rates (incidence rate ratio 1.3, 95% CI: 1.23, 1.41) were higher in inflammatory arthritis patients compared with that in controls, and were further increased in the presence of a second autoimmune disorder. The hazard ratio for cardiovascular disease was 1.32 (95% CI: 1.23, 1.41) for patients with inflammatory arthritis only, and 1.49 (95% CI: 1.31, 1.68) for patients with inflammatory arthritis co-existent with another autoimmune disorder. CONCLUSION: The amplification of cardiovascular disease risk in inflammatory arthritis patients with multiple autoimmune disorders warrants greater awareness, and since autoimmune disorders often co-exist, the need for cardiovascular risk management in these patients is once again emphasized

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Effectiveness of a stepwise cardiometabolic disease prevention program: Results of a randomized controlled trial in primary care

Effective preventive strategies for cardiometabolic disease (CMD) are needed. We aim to establish the effectiveness of a stepwise CMD risk assessment followed by individualized treatment if indicated compared to care as usual. We conducted a RCT between 2014 and 2017. Individuals (45–70 years) without CMD or CMD risk factors were invited for stepwise CMD risk assessment through a risk score (step1), additional risk assessment at the practice in case of high-risk (step2) and individualized follow-up treatment if indicated (step3). We compared newly detected CMD and newly prescribed drugs during one-year follow-up, and change in CMD risk profile between baseline and one-year follow-up among participants who completed step2 to matched controls. A CMD was diagnosed almost three times more often (OR 2.90, 95% CI 2.25: 3.72) in the intervention compared to the control group, in parallel with newly prescribed antihypertensive and lipid lowering drugs (OR 2.85, 95% CI 1.96: 4.15 and 3.23, 95% CI 2.03: 5.14 respectively). Waist circumference significantly decreased between the intervention compared to the control group (mean −3.08 cm, 95% CI −3.73: −2.43). No differences were observed for changes in BMI and smoking. Systolic blood pressure (mean −2.26 mmHg, 95% CI −4.01: −0.51) and cholesterol ratio (mean −0.11, 95% CI −0.19: −0.02) significantly decreased within intervention participants between baseline and one-year follow-up. In conclusion, implementation of the CMD prevention program resulted in the detection of two- to threefold more patients with CMD. A significant drop in systolic blood pressure and cholesterol levels was found after one year of treatment. Modelling of these results should confirm the effect on long term endpoints. Trial registration: Dutch trial Register number NTR4277

Uptake and detection rate of a stepwise cardiometabolic disease detection program in primary care - A cohort study

Background: Early detection and treatment of cardiometabolic diseases (CMD) in high-risk patients is a promising preventive strategy to anticipate the increasing burden of CMD. The Dutch guideline 'the prevention consultation' provides a framework for stepwise CMD risk assessment and detection in primary care. The aim of this study was to assess the outcome of this program in terms of newly diagnosed CMD. Methods: A cohort study among 30 934 patients, aged 45-70 years without known CMD or CMD risk factors, who were invited for the CMD detection program within 37 general practices. Patients filled out a CMD risk score (step 1), were referred for additional risk profiling in case of high risk (step 2) and received lifestyle advice and (pharmacological) treatment if indicated (step 3). During 1-year follow-up newly diagnosed CMD, prescriptions and abnormal diagnostic tests were assessed. Results: Twelve thousand seven hundred and thirty-eight patients filled out the risk score of which 865, 6665 and 5208 had a low, intermediate and high CMD risk, respectively. One thousand seven hundred and fifty-five high-risk patients consulted the general practitioner, in 346 of whom a new CMD was diagnosed. In an additional 422 patients a new prescription and/or abnormal diagnostic test were found. Conclusions: Implementation of the CMD detection program resulted in a new CMD diagnosis in one-fifth of high-risk patients who attended the practice for completion of their risk profile. However, the potential yield of the program could be higher given the considerable number of additional risk factors - such as elevated glucose, blood pressure and cholesterol levels - found, requiring active follow-up and presumably treatment in the future