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.

Prenatal Exposure to the 1944-45 Dutch Famine and Risk for Dementia up to Age 75: An Analysis of Primary Care Data.

BACKGROUND: A poor prenatal environment adversely affects brain development. Studies investigating long-term consequences of prenatal exposure to the 1944-45 Dutch famine have shown that those exposed to famine in early gestation had poorer selective attention, smaller brain volumes, poorer brain perfusion, older appearing brains, and increased reporting of cognitive problems, all indicative of increased dementia risk. OBJECTIVE: In the current population-based study, we investigated whether dementia incidence up to age 75 was higher among individuals who had been prenatally exposed to famine. METHODS: We included men (n=6,714) and women (n=7,051) from the Nivel Primary Care Database who had been born in seven cities affected by the Dutch famine. We used Cox regression to compare dementia incidence among individuals exposed to famine during late (1,231), mid (1,083), or early gestation (601) with those unexposed (born before or conceived after the famine). RESULTS: We did not observe differences in dementia incidence for those exposed to famine in mid or early gestation compared to those unexposed. Men and women exposed to famine in late gestation had significantly lower dementia rates compared to unexposed individuals (HR 0.52 [95%CI 0.30-0.89]). Sex-specific analyses showed a lower dementia rate in women exposed to famine in late gestation (HR 0.39 [95%CI 0.17-0.86]) but not in men (HR 0.68 [95%CI 0.33-1.41]). CONCLUSION: Although prenatal exposure to the Dutch famine has previously been associated with measures of accelerated brain aging, the present population-based study did not show increased dementia incidence up to age 75 in those exposed to famine during gestation.

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.

Comparison of depression care provided in general practice in Norway and the Netherlands: registry-based cohort study (The Norwegian GP-DEP study).

BACKGROUND: Depression is highly prevalent in general practice, and organisation of primary health care probably affects the provision of depression care. General practitioners (GPs) in Norway and the Netherlands fulfil comparable roles. However, primary care teams with a mental health nurse (MHN) supplementing the GP have been established in the Netherlands, but not yet in Norway. In order to explore how the organisation of primary mental care affects care delivery, we aimed to examine the provision of GP depression care across the two countries. METHODS: Registry-based cohort study comprising new depression episodes in patients aged ≥ 18 years, 2011-2015. The Norwegian sample was drawn from the entire population (national health registries); 297,409 episodes. A representative Dutch sample (Nivel Primary Care Database) was included; 27,362 episodes. Outcomes were follow-up consultation(s) with GP, with GP and/or MHN, and antidepressant prescriptions during 12 months from the start of the depression episode. Differences between countries were estimated using negative binomial and Cox regression models, adjusted for patient gender, age and comorbidity. RESULTS: Patients in the Netherlands compared to Norway were less likely to receive GP follow-up consultations, IRR (incidence rate ratio) = 0.73 (95% confidence interval (CI) 0.71-0.74). Differences were greatest among patients aged 18-39 years (adj IRR = 0.64, 0.63-0.66) and 40-59 years (adj IRR = 0.71, 0.69-0.73). When comparing follow-up consultations in GP practices, including MHN consultations in the Netherlands, no cross-national differences were found (IRR = 1.00, 0.98-1.01). But in age-stratified analyses, Dutch patients 60 years and older were more likely to be followed up than their Norwegian counterparts (adj IRR = 1.21, 1.16-1.26). Patients in the Netherlands compared to Norway were more likely to receive antidepressant drugs, adj HR (hazard ratio) = 1.32 (1.30-1.34). CONCLUSIONS: The observed differences indicate that the organisation of primary mental health care affects the provision of follow-up consultations in Norway and the Netherlands. Clinical studies are needed to explore the impact of team-based care and GP-based care on the quality of depression care and patient outcomes.

Unwillingness to participate in health checks for cardiometabolic diseases: A survey among primary health care patients in five European countries.

BACKGROUND AND AIMS: Since cardiometabolic diseases (CMD) are a frequent cause of death worldwide, preventive strategies are needed. Recruiting adults for a health check could facilitate the identification of individuals at risk for CMD. For successful results, participation is crucial. We aimed to identify factors related to unwillingness to participate in CMD health checks. METHODS: We performed a cross-sectional study in the Czech Republic, Denmark, Greece, the Netherlands, and Sweden. A questionnaire was distributed among persons without known CMD consulting general practice between January and July 2017 within the framework of the SPIMEU study. RESULTS: In total, 1354 persons responded. Nine percent was unwilling to participate in a CMD health check. Male gender, smoking, higher self-rated health, never been invited before, and not willing to pay were related to unwillingness to participate. The most mentioned reason for unwillingness to participate was "I think that I am healthy" (57%). Among the respondents who were willing to participate, 94% preferred an invitation by the general practitioner and 66% was willing to pay. CONCLUSION: A minority of the respondents was unwilling to participate in a CMD health check with consistent results within the five countries. This provides a promising starting point to increase participation in CMD health checks in primary care.

Cost-effectiveness of a stepwise cardiometabolic disease prevention program: results of a randomized controlled trial in primary care.

BACKGROUND: Cardiometabolic diseases (CMD) are the major cause of death worldwide and are associated with a lower quality of life and high healthcare costs. To prevent a further rise in CMD and related healthcare costs, early detection and adequate management of individuals at risk could be an effective preventive strategy. The objective of this study was to determine long-term cost-effectiveness of stepwise CMD risk assessment followed by individualized treatment if indicated compared to care as usual. A computer-based simulation model was used to project long-term health benefits and cost-effectiveness, assuming the prevention program was implemented in Dutch primary care. METHODS: A randomized controlled trial in a primary care setting in which 1934 participants aged 45-70 years without recorded CMD or CMD risk factors participated. The intervention group was invited for stepwise CMD risk assessment through a risk score (step 1), additional risk assessment at the practice in case of increased risk (step 2) and individualized follow-up treatment if indicated (step 3). The control group was not invited for risk assessment, but completed a health questionnaire. Results of the effectiveness analysis on systolic blood pressure (- 2.26 mmHg; 95% CI - 4.01: - 0.51) and total cholesterol (- 0.15 mmol/l; 95% CI - 0.23: - 0.07) were used in this analysis. Outcome measures were the costs and benefits after 1-year follow-up and long-term (60 years) cost-effectiveness of stepwise CMD risk assessment compared to no assessment. A computer-based simulation model was used that included data on disability weights associated with age and disease outcomes related to CMD. Analyses were performed taking a healthcare perspective. RESULTS: After 1 year, the average costs in the intervention group were 260 Euro higher than in the control group and differences were mainly driven by healthcare costs. No meaningful change was found in EQ 5D-based quality of life between the intervention and control groups after 1-year follow-up (- 0.0154; 95% CI - 0.029: 0.004). After 60 years, cumulative costs of the intervention were 41.4 million Euro and 135 quality-adjusted life years (QALY) were gained. Despite improvements in blood pressure and cholesterol, the intervention was not cost-effective (ICER of 306,000 Euro/QALY after 60 years). Scenario analyses did not allow for a change in conclusions with regard to cost-effectiveness of the intervention. CONCLUSIONS: Implementation of this primary care-based CMD prevention program is not cost-effective in the long term. Implementation of this program in primary care cannot be recommended. TRIAL REGISTRATION: Dutch Trial Register NTR4277 , registered on 26 November 2013.

Trends in the incidence of diagnosed diabetes: a multicountry analysis of aggregate data from 22 million diagnoses in high-income and middle-income settings.

BACKGROUND: Diabetes prevalence is increasing in most places in the world, but prevalence is affected by both risk of developing diabetes and survival of those with diabetes. Diabetes incidence is a better metric to understand the trends in population risk of diabetes. Using a multicountry analysis, we aimed to ascertain whether the incidence of clinically diagnosed diabetes has changed over time. METHODS: In this multicountry data analysis, we assembled aggregated data describing trends in diagnosed total or type 2 diabetes incidence from 24 population-based data sources in 21 countries or jurisdictions. Data were from administrative sources, health insurance records, registries, and a health survey. We modelled incidence rates with Poisson regression, using age and calendar time (1995-2018) as variables, describing the effects with restricted cubic splines with six knots for age and calendar time. FINDINGS: Our data included about 22 million diabetes diagnoses from 5 billion person-years of follow-up. Data were from 19 high-income and two middle-income countries or jurisdictions. 23 data sources had data from 2010 onwards, among which 19 had a downward or stable trend, with an annual estimated change in incidence ranging from -1·1% to -10·8%. Among the four data sources with an increasing trend from 2010 onwards, the annual estimated change ranged from 0·9% to 5·6%. The findings were robust to sensitivity analyses excluding data sources in which the data quality was lower and were consistent in analyses stratified by different diabetes definitions. INTERPRETATION: The incidence of diagnosed diabetes is stabilising or declining in many high-income countries. The reasons for the declines in the incidence of diagnosed diabetes warrant further investigation with appropriate data sources. FUNDING: US Centers for Disease Control and Prevention, Diabetes Australia Research Program, and Victoria State Government Operational Infrastructure Support Program.

CHARGE-AF in a national routine primary care electronic health records database in the Netherlands: validation for 5-year risk of atrial fibrillation and implications for patient selection in atrial fibrillation screening.

AIMS: To validate a multivariable risk prediction model (Cohorts for Heart and Aging Research in Genomic Epidemiology model for atrial fibrillation (CHARGE-AF)) for 5-year risk of atrial fibrillation (AF) in routinely collected primary care data and to assess CHARGE-AF's potential for automated, low-cost selection of patients at high risk for AF based on routine primary care data. METHODS: We included patients aged ≥40 years, free of AF and with complete CHARGE-AF variables at baseline, 1 January 2014, in a representative, nationwide routine primary care database in the Netherlands (Nivel-PCD). We validated CHARGE-AF for 5-year observed AF incidence using the C-statistic for discrimination, and calibration plot and stratified Kaplan-Meier plot for calibration. We compared CHARGE-AF with other predictors and assessed implications of using different CHARGE-AF cut-offs to select high-risk patients. RESULTS: Among 111 475 patients free of AF and with complete CHARGE-AF variables at baseline (17.2% of all patients aged ≥40 years and free of AF), mean age was 65.5 years, and 53% were female. Complete CHARGE-AF cases were older and had higher AF incidence and cardiovascular comorbidity rate than incomplete cases. There were 5264 (4.7%) new AF cases during 5-year follow-up among complete cases. CHARGE-AF's C-statistic for new AF was 0.74 (95% CI 0.73 to 0.74). The calibration plot showed slight risk underestimation in low-risk deciles and overestimation of absolute AF risk in those with highest predicted risk. The Kaplan-Meier plot with categories <2.5%, 2.5%-5% and >5% predicted 5-year risk was highly accurate. CHARGE-AF outperformed CHA2DS2-VASc (Cardiac failure or dysfunction, Hypertension, Age >=75 [Doubled], Diabetes, Stroke [Doubled]-Vascular disease, Age 65-74, and Sex category [Female]) and age alone as predictors for AF. Dichotomisation at cut-offs of 2.5%, 5% and 10% baseline CHARGE-AF risk all showed merits for patient selection in AF screening efforts. CONCLUSION: In patients with complete baseline CHARGE-AF data through routine Dutch primary care, CHARGE-AF accurately assessed AF risk among older primary care patients, outperformed both CHA2DS2-VASc and age alone as predictors for AF and showed potential for automated, low-cost patient selection in AF screening.

Opportunistic screening versus usual care for detection of atrial fibrillation in primary care: cluster randomised controlled trial.

OBJECTIVE: To investigate whether opportunistic screening in primary care increases the detection of atrial fibrillation compared with usual care. DESIGN: Cluster randomised controlled trial. SETTING: 47 intention-to-screen and 49 usual care primary care practices in the Netherlands, not blinded for allocation; the study was carried out from September 2015 to August 2018. PARTICIPANTS: In each practice, a fixed sample of 200 eligible patients, aged 65 or older, with no known history of atrial fibrillation in the electronic medical record system, were randomly selected. In the intention-to-screen group, 9218 patients eligible for screening were included, 55.0% women, mean age 75.2 years. In the usual care group, 9526 patients were eligible for screening, 54.3% women, mean age 75.0 years. INTERVENTIONS: Opportunistic screening (that is, screening in patients visiting their general practice) consisted of three index tests: pulse palpation, electronic blood pressure measurement with an atrial fibrillation algorithm, and electrocardiography (ECG) with a handheld single lead electrocardiographic device. The reference standard was 12 lead ECG, performed in patients with at least one positive index test and in a sample of patients (10%) with three negative tests. If 12 lead ECG showed no atrial fibrillation, patients were invited for more screening by continuous monitoring with a Holter electrocardiograph for two weeks. MAIN OUTCOME MEASURES: Difference in the detection rate of newly diagnosed atrial fibrillation over one year in intention-to-screen versus usual care practices. RESULTS: Follow-up was complete for 8874 patients in the intention-to-screen practices and for 9102 patients in the usual care practices. 144 (1.62%) new diagnoses of atrial fibrillation in the intention-to-screen group versus 139 (1.53%) in the usual care group were found (adjusted odds ratio 1.06 (95% confidence interval 0.84 to 1.35)). Of 9218 eligible patients in the intention-to-screen group, 4106 (44.5%) participated in the screening protocol. In these patients, 12 lead ECG detected newly diagnosed atrial fibrillation in 26 patients (0.63%). In the 266 patients who continued with Holter monitoring, four more diagnoses of atrial fibrillation were found. CONCLUSIONS: Opportunistic screening for atrial fibrillation in primary care patients, aged 65 and over, did not increase the detection rate of atrial fibrillation, which implies that opportunistic screening for atrial fibrillation is not useful in this setting. TRIAL REGISTRATION: Netherlands Trial Register No NL4776 (old NTR4914).

Applying machine learning on health record data from general practitioners to predict suicidality.

BACKGROUND: Suicidal behaviour is difficult to detect in the general practice. Machine learning (ML) algorithms using routinely collected data might support General Practitioners (GPs) in the detection of suicidal behaviour. In this paper, we applied machine learning techniques to support GPs recognizing suicidal behaviour in primary care patients using routinely collected general practice data. METHODS: This case-control study used data from a national representative primary care database including over 1.5 million patients (Nivel Primary Care Database). Patients with a suicide (attempt) in 2017 were selected as cases (N = 574) and an at risk control group (N = 207,308) was selected from patients with psychological vulnerability but without a suicide attempt in 2017. RandomForest was trained on a small subsample of the data (training set), and evaluated on unseen data (test set). RESULTS: Almost two-third (65%) of the cases visited their GP within the last 30 days before the suicide (attempt). RandomForest showed a positive predictive value (PPV) of 0.05 (0.04-0.06), with a sensitivity of 0.39 (0.32-0.47) and area under the curve (AUC) of 0.85 (0.81-0.88). Almost all controls were accurately labeled as controls (specificity = 0.98 (0.97-0.98)). Among a sample of 650 at-risk primary care patients, the algorithm would label 20 patients as high-risk. Of those, one would be an actual case and additionally, one case would be missed. CONCLUSION: In this study, we applied machine learning to predict suicidal behaviour using general practice data. Our results showed that these techniques can be used as a complementary step in the identification and stratification of patients at risk of suicidal behaviour. The results are encouraging and provide a first step to use automated screening directly in clinical practice. Additional data from different social domains, such as employment and education, might improve accuracy.

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.

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.

Estimating Morbidity Rates Based on Routine Electronic Health Records in Primary Care: Observational Study.

BACKGROUND: Routinely recorded electronic health records (EHRs) from general practitioners (GPs) are increasingly available and provide valuable data for estimating incidence and prevalence rates of diseases in the population. This paper describes how we developed an algorithm to construct episodes of illness based on EHR data to calculate morbidity rates. OBJECTIVE: The goal of the research was to develop a simple and uniform algorithm to construct episodes of illness based on electronic health record data and develop a method to calculate morbidity rates based on these episodes of illness. METHODS: The algorithm was developed in discussion rounds with two expert groups and tested with data from the Netherlands Institute for Health Services Research Primary Care Database, which consisted of a representative sample of 219 general practices covering a total population of 867,140 listed patients in 2012. RESULTS: All 685 symptoms and diseases in the International Classification of Primary Care version 1 were categorized as acute symptoms and diseases, long-lasting reversible diseases, or chronic diseases. For the nonchronic diseases, a contact-free interval (the period in which it is likely that a patient will visit the GP again if a medical complaint persists) was defined. The constructed episode of illness starts with the date of diagnosis and ends at the time of the last encounter plus half of the duration of the contact-free interval. Chronic diseases were considered irreversible and for these diseases no contact-free interval was needed. CONCLUSIONS: An algorithm was developed to construct episodes of illness based on routinely recorded EHR data to estimate morbidity rates. The algorithm constitutes a simple and uniform way of using EHR data and can easily be applied in other registries.

Calculating incidence rates and prevalence proportions: not as simple as it seems.

BACKGROUND: Incidence rates and prevalence proportions are commonly used to express the populations health status. Since there are several methods used to calculate these epidemiological measures, good comparison between studies and countries is difficult. This study investigates the impact of different operational definitions of numerators and denominators on incidence rates and prevalence proportions. METHODS: Data from routine electronic health records of general practices contributing to NIVEL Primary Care Database was used. Incidence rates were calculated using different denominators (person-years at-risk, person-years and midterm population). Three different prevalence proportions were determined: 1 year period prevalence proportions, point-prevalence proportions and contact prevalence proportions. RESULTS: One year period prevalence proportions were substantially higher than point-prevalence (58.3 - 206.6%) for long-lasting diseases, and one year period prevalence proportions were higher than contact prevalence proportions (26.2 - 79.7%). For incidence rates, the use of different denominators resulted in small differences between the different calculation methods (-1.3 - 14.8%). Using person-years at-risk or a midterm population resulted in higher rates compared to using person-years. CONCLUSIONS: All different operational definitions affect incidence rates and prevalence proportions to some extent. Therefore, it is important that the terminology and methodology is well described by sources reporting these epidemiological measures. When comparing incidence rates and prevalence proportions from different sources, it is important to be aware of the operational definitions applied and their impact.

Selective prevention of cardiometabolic diseases: activities and attitudes of general practitioners across Europe.

Background: Cardiometabolic diseases (CMDs) are the number one cause of death. Selective prevention of CMDs by general practitioners (GPs) could help reduce the burden of CMDs. This measure would entail the identification of individuals at high risk of CMDs-but currently asymptomatic-followed by interventions to reduce their risk. No data were available on the attitude and the extent to which European GPs have incorporated selective CMD prevention into daily practice. Methods: A survey among 575 GPs from the Czech Republic, Denmark, Greece, the Netherlands and Sweden was conducted between September 2016 and January 2017, within the framework of the SPIMEU-project. Results: On average, 71% of GPs invited their patients to attend for CMD risk assessment. Some used an active approach (47%) while others used an opportunistic approach (53%), but these values differed between countries. Most GPs considered selective CMD prevention as useful (82%) and saw it as part of their normal duties (84%). GPs who did find selective prevention useful were more likely to actively invite individuals compared with their counterparts who did not find prevention useful. Most GPs had a disease management programme for individuals with risk factor(s) for cardiovascular disease (71%) or diabetes (86%). Conclusions: Although most GPs considered selective CMD prevention as useful, it was not universally implemented. The biggest challenge was the process of inviting individuals for risk assessment. It is important to tailor the implementation of selective CMD prevention in primary care to the national context, involving stakeholders at different levels.

The value of joint ultrasonography in predicting arthritis in seropositive patients with arthralgia: a prospective cohort study.

BACKGROUND: The value of joint ultrasonography (US) in the prediction of clinical arthritis in individuals at risk of developing rheumatoid arthritis (RA) is still a point of debate, due to varying scanning protocols and different populations. We investigated whether US abnormalities assessed with a standard joint protocol can predict development of arthritis in seropositive patients with arthralgia. METHODS: Anti-citrullinated protein antibodies and/or rheumatoid factor positive patients with arthralgia, but without clinical arthritis were included. US was performed at baseline in 16 joints: bilateral metacarpophalangeal 2-3, proximal interphalangeal 2-3, wrist and metatarsophalangeal (MTP) joints 2-3 and 5. Images were scored semi-quantitatively for synovial thickening and for positive signs on power Doppler (PD). Association between US abnormalities and arthritis development at the joint and at the patient level was evaluated. Also, we investigated the added value of US over clinical parameters. RESULTS: Out of 163 patients who underwent US examination, 51 (31%) developed clinical arthritis after a median follow-up time of 12 (interquartile range 5-24) months, of which 44 (86%) satisfied the 2010 American College of Rheumatology/European League Against Rheumatism classification criteria for RA. US revealed synovial thickening and PD in at least one joint in 49 patients (30%) and 7 patients (4%), respectively. Synovial thickening was associated with both development and timing of clinical arthritis in any joint (patient level) when MTP joints were excluded from the US assessment (odds ratio 6.6, confidence interval (CI) 1.9-22), and hazard ratio 3.4, CI 1.6-6.8, respectively, with a mean time to arthritis of 23 versus 45 months when synovial thickening was present versus not present). There was no association between US and arthritis development at the joint level. Predictive capacity was highest in the groups with an intermediate and high risk of developing arthritis based on a prediction rule with clinical parameters. CONCLUSIONS: Synovial thickening on US predicted clinical arthritis development at the patient level in seropositive patients with arthralgia when MTPs were excluded from the US assessment. Positive PD signs were infrequently seen in these at-risk individuals and was not predictive. In patients at intermediate risk of RA, US may help to identify those at higher risk of developing arthritis.

Increased healthcare utilisation among atopic children in a general practice database: a nested index-control study.

BACKGROUND: Atopic eczema, asthma, and allergic rhinitis (AR) create a serious burden on general practice resources. AIM: To investigate the use of general practice resources (that is, consultation visits, telephone contacts, and home visits) in children with physician-diagnosed atopic disorders (ADs). DESIGN & SETTING: In a nested index-control study design, all children (here defined as individuals aged 2-18 years) listed in a representative general practice database were selected in 2014. METHOD: Children diagnosed with ADs were matched on age and sex with non-atopic controls within the same practice. For all the different groups, the number and frequency of children contacting the GP were calculated. RESULTS: Of the children with atopic eczema (n = 15 202), 80% consulted the GP in 2014 (controls = 67%). Of the children with asthma (n = 7754), 80% consulted the GP (controls = 65%), and for children with AR (n = 6710), this was 82% (controls = 66%). Of the children with all three ADs, 91% consulted the GP (controls = 68%). On average, a child with atopic eczema contacted the GP 2.8 times/year (controls = 1.9); for children with asthma, the contact frequency was 3.0 (controls = 1.9); and for AR, 3.2 (controls = 1.9). For children with all three ADs, the contact frequency was 4.3 (controls = 2.0). Consultations related to the ADs investigated only explain a smaller part of the increased healthcare utilisation in atopic children. CONCLUSION: Atopic children use more general practice resources compared to non-atopic children, yet frequently for morbidity or other health-related questions not related to one of the ADs.

Overweight in patients with chronic obstructive pulmonary disease needs more attention: a cross-sectional study in general practice.

Guidelines for management of chronic obstructive pulmonary disease (COPD) primarily focus on the prevention of weight loss, while overweight and obesity are highly prevalent in patients with milder stages of COPD. This cross-sectional study examines the association of overweight and obesity with the prevalence of comorbid disorders and prescribed medication for obstructive airway disease, in patients with mild to moderate COPD. Data were used from electronic health records of 380 Dutch general practices in 2014. In total, we identified 4938 patients with mild or moderate COPD based on spirometry data, and a recorded body mass index (BMI) of ≥21 kg/m2. Outcomes in overweight (BMI ≥ 25 and <30 kg/m2) and obese (BMI ≥30 kg/m2) patients with COPD were compared to those with a normal weight (BMI ≥ 21 and <25 kg/m2), by logistic multilevel analyses. Compared to COPD patients with a normal weight, positive associations were found for diabetes, osteoarthritis, and hypertension, for both overweight (OR: 1.4-1.7) and obese (OR: 2.4-3.8) patients, and for heart failure in obese patients (OR: 2.3). Osteoporosis was less prevalent in overweight (OR: 0.7) and obese (OR: 0.5) patients, and anxiety disorders in obese patients (OR: 0.5). No associations were found for coronary heart disease, stroke, sleep disturbance, depression, and pneumonia. Furthermore, obese patients were in general more often prescribed medication for obstructive airway disease compared to patients with a normal weight. The findings of this study underline the need to increase awareness in general practitioners for excess weight in patients with mild to moderate COPD.

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.