Consultations for Influenza-like Illness in Primary Care in The Netherlands: A Regression Approach

ObjectiveIntensive Care Unit (ICU) data are registered for quality monitoring in the Netherlands with near 100% coverage. They are a ‘big data’ type source that may be useful for infectious disease surveillance. We explored their potential to enhance the surveillance of influenza which is currently based on the milder end of the disease spectrum. We ultimately aim to set up a real-surveillance system of severe acute respiratory infections.IntroductionWhile influenza-like-illness (ILI) surveillance is well-organized at primary care level in Europe, little data is available on more severe cases. With retrospective data from ICU’s we aim to fill this current knowledge gap and to explore its worth for prospective surveillance. Using multiple parameters proposed by the World Health Organization we estimated the burden of severe acute respiratory infections (SARI) to ICU and how this varies between influenza epidemics.MethodsWe analyzed weekly ICU admissions of adults in the Netherlands (2007-2016) from the national intensive care evaluation (NICE) quality registry (100% coverage of adult ICU in 2016; population size 14 million adults. A SARI syndrome was defined as admission diagnosis being any of 6 pneumonia or pulmonary sepsis codes in the Acute Physiology and Chronic Health Evaluation IV (APACHE IV) prognostic model. Influenza epidemic periods were retrieved from primary care sentinel influenza surveillance data. In recent years NICE has explored and promoted increased timeliness and automation of data transfer.ResultsAnnually, 11-14% of medical admissions to adult ICUs were for a SARI (5-25% weekly). Admissions for bacterial pneumonia (59%) and pulmonary sepsis (25%) contributed most to ICU-SARI. Between influenza epidemics, severity indicators varied: ICU-SARI incidence (between 558-2,400 cumulated admissions nation-wide, rate: 0.40-1.71/10,000 inhabitants), average APACHE score (between 71-78), ICU-SARI mortality (between 13-20%), ICU-SARI/ILI ratio (between 8-17 SARI ICU cases per 1,000 expected medically attended influenza-like-illness in primary care), peak incidence (between 101-188 ICU-SARI admissions nationally in the highest week, rate: between 0.07-0.13/10,000 population).ICUs use different types of electronic health records (EHRs). Data submitted to the NICE registry is mainly based on routinely collected data extracted from these EHRs. The timeliness of data submission varies between a few weeks and three months. Together with ICUs, the NICE registry has recently undertaken actions to increase timeliness of ICU data submission.ConclusionsIn ICU data, great variation can be seen between the yearly influenza epidemic periods in terms of different influenza severity parameters. The parameters also complement each other by reflecting different aspects of severity. Prospective syndromic ICU-SARI surveillance, as proposed by the World Health Organization would provide insight into severity of ongoing influenza epidemics which differ from season to season.Currently a subset of hospitals provide data with a 6-week delay. This can be a worthwhile addition to current influenza surveillance, which, while timelier, is based on milder cases seen by general practitioners (primary care). Future increases in data timeliness will remain an aim.

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Use of ambulance dispatch calls for surveillance of severe acute respiratory infections?

Online Journal of Public Health Informatics ◽

10.5210/ojphi.v11i1.9900 ◽

2019 ◽

Vol 11 (1) ◽

Author(s):

Susana Monge ◽

Janneke Duijster ◽

Geert Jan Kommer ◽

Jan Van de Kassteele ◽

Ge Donker ◽

...

Keyword(s):

Primary Care ◽

The Netherlands ◽

Respiratory Infections ◽

Time Of Day ◽

Influenza Surveillance ◽

Influenza Like Illness ◽

Main Complaint ◽

Ambulance Dispatch ◽

Study Population ◽

Urgency Level

ObjectiveWe aim to assess whether influenza circulation, as measured through influenza-like-illness (ILI) in primary care, is reflected in ambulance dispatch (AD) calls.IntroductionSurveillance of severe influenza infections is lacking in the Netherlands. Ambulance dispatch (AD) data may provide information about severity of the influenza epidemic and its burden on emergency services.The current gold standard, primary care-based surveillance of influenza-like-illness (ILI), mainly captures mild to moderate influenza cases, and does not provide adequate information on severe disease.Monitoring the severity of the annual epidemic, particularly among groups most at risk of complications, is of importance for the planning of health services and the public health response.MethodsWe analysed all calls from four ambulance dispatch centers serving 4.3 million people in the Netherlands, between January 2014 and December 2016. The main complaint and urgency level is recorded during triage; those possibly caused by respiratory infections were grouped as respiratory syndrome calls (RSC). We modelled the proportion of all RSC calls against the weekly ILI incidence (we allowed up to 4-week lags and leads), from sentinel primary-care surveillance. We used binomial regression with identity link to obtain differences in proportions. We built separate models by age group, urgency level and time of day. We tested heterogeneity of effects by season.ResultsWe included 289,307 calls; 6.7% were RSC. Overall, proportion of RSC increased by 0.114 percentage points for each increase of 1/10,000 population in ILI incidence. In our study population, this translated into 550 ambulance calls attributable to influenza (as measured by ILI) per year. Association was stronger in the models including only out-of-office hours, children (<15 years) and highest urgency level calls. In the latter two, the effect varied by season. RSC was best associated with ILI from the previous 1-3 weeks in all models, except in children where RSC preceded ILI by 1 week.ConclusionsOur results demonstrate the potential usefulness of ambulance dispatch data to complement existing influenza surveillance by providing information on the volume and timing of severe cases attributable to influenza within the yearly epidemics.

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Faculty Opinions recommendation of Oseltamivir plus usual care versus usual care for influenza-like illness in primary care: an open-label, pragmatic, randomised controlled trial.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.737097923.793569009 ◽

2019 ◽

Author(s):

Allen Cheng

Keyword(s):

Primary Care ◽

Randomised Controlled Trial ◽

Usual Care ◽

Controlled Trial ◽

Open Label ◽

Influenza Like Illness ◽

Randomised Controlled ◽

Pragmatic Randomised Controlled Trial

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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

Open Heart ◽

10.1136/openhrt-2020-001459 ◽

2021 ◽

Vol 8 (1) ◽

pp. e001459

Author(s):

Jelle C L Himmelreich ◽

Wim A M Lucassen ◽

Ralf E Harskamp ◽

Claire Aussems ◽

Henk C P M van Weert ◽

...

Keyword(s):

Atrial Fibrillation ◽

Primary Care ◽

High Risk ◽

The Netherlands ◽

Patient Selection ◽

Low Cost ◽

Calibration Plot ◽

Primary Care Data ◽

C Statistic ◽

Kaplan Meier

AimsTo 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.MethodsWe 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.ResultsAmong 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.ConclusionIn 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.

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Platelet aggregation inhibitor prescription for newly diagnosed peripheral arterial disease in the Netherlands: a cohort study

BMJ Open ◽

10.1136/bmjopen-2020-041715 ◽

2021 ◽

Vol 11 (1) ◽

pp. e041715

Author(s):

Aarent RT Brand ◽

Eline Houben ◽

Irene D Bezemer ◽

Frank L J Visseren ◽

Michiel L Bots ◽

...

Keyword(s):

Primary Care ◽

Cohort Study ◽

The Netherlands ◽

Peripheral Arterial Disease ◽

Arterial Disease ◽

Free Text ◽

Newly Diagnosed ◽

Patient Journey ◽

P2y12 Inhibitors ◽

Peripheral Arterial

ObjectivesPharmacological treatment of peripheral arterial disease (PAD) comprises of antiplatelet therapy (APT), blood pressure control and cholesterol optimisation. Guidelines provide class-I recommendations on the prescription, but there are little data on the actual prescription practices. Our study provides insight into the prescription of medication among patients with PAD in the Netherlands and reports a ‘real-world’ patient journey through primary and secondary care.DesignWe conducted a cohort study among patients newly diagnosed with PAD between 2010 and 2014.SettingData were obtained from the PHARMO Database Network, a population-based network of electronic pharmacy, primary and secondary healthcare setting records in the Netherlands. The source population for this study comprised almost 1 million individuals.Participants‘Newly diagnosed’ was defined as a recorded International Classification of Primary Care code for PAD, a PAD-specific WCIA examination code or a diagnosis recorded as free text episode in the general practitioner records with no previous PAD diagnosis record and no prescription of P2Y12 inhibitors or aspirin the preceding year. The patient journey was defined by at least 1 year of database history and follow-up relative to the index date.ResultsBetween 2010 and 2014, we identified 3677 newly diagnosed patients with PAD. Most patients (91%) were diagnosed in primary care. Almost half of all patients (49%) had no APT dispensing record. Within this group, 33% received other anticoagulant therapy (vitamin K antagonist or direct oral anticoagulant). Mono-APT was dispensed as aspirin (40% of patients) or P2Y12 inhibitors (2.5% of patients). Dual APT combining aspirin with a P2Y12 inhibitor was dispensed to 8.5% of the study population.ConclusionHalf of all patients with newly diagnosed PAD are not treated conforming to (international) guideline recommendations on thromboembolism prevention through APT. At least 33% of all patients with newly diagnosed PAD do not receive any antithrombotic therapy. Evaluation and improvement of APT prescription and thereby improved prevention of (secondary) cardiovascular events is warranted.

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General practitioners' contribution to the management of community-acquired pneumonia in the Netherlands: a retrospective analysis of primary care, hospital, and national mortality databases with individual data linkage

Primary Care Respiratory Journal ◽

10.4104/pcrj.2013.00085 ◽

2013 ◽

Vol 22 (4) ◽

pp. 400-405 ◽

Cited By ~ 17

Author(s):

Bianca EP Snijders ◽

Wim van der Hoek ◽

Irina Stirbu ◽

Marianne AB van der Sande ◽

Arianne B van Gageldonk-Lafeber

Keyword(s):

Primary Care ◽

The Netherlands ◽

Retrospective Analysis ◽

General Practitioners ◽

Data Linkage ◽

Community Acquired Pneumonia ◽

Care Hospital ◽

Individual Data ◽

National Mortality ◽

Primary Care Hospital

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Interprofessional collaboration among care professionals in obstetrical care: are perceptions aligned?

BMJ Quality & Safety ◽

10.1136/bmjqs-2016-006401 ◽

2017 ◽

Vol 27 (4) ◽

pp. 279-286 ◽

Cited By ~ 9

Author(s):

Anita Romijn ◽

Pim W Teunissen ◽

Martine C de Bruijne ◽

Cordula Wagner ◽

Christianne J M de Groot

Keyword(s):

Primary Care ◽

The Netherlands ◽

Interprofessional Collaboration ◽

Cross Sectional Study ◽

Measurement Scale ◽

Cross Sectional ◽

Communication Accommodation ◽

Obstetrical Care ◽

The North ◽

Ensure Patient Safety

BackgroundIn an obstetrical team, obstetricians, midwives and nurses work together in a dynamic and complex care setting. Different professional cultures can be a barrier for effective interprofessional collaboration. Although the different professional cultures in obstetrical care are well known, little is understood about discrepancies in mutual perceptions of collaboration. Similar perceptions of collaboration are important to ensure patient safety. We aimed to understand how different care professionals in an obstetrical team assess interprofessional collaboration in order to gain insight into the extent to which their perceptions are aligned.MethodsThis cross-sectional study was performed in the north-western region of the Netherlands. Care professionals from five hospitals and surrounding primary-care midwifery practices were surveyed. The respondents consisted of four groups of care professionals: obstetricians (n=74), hospital-based midwives known as clinical midwives (n=42), nurses (n=154) and primary-care midwives (n=109). The overall response rate was 80.8%. We used the Interprofessional Collaboration Measurement Scale (IPCMS) to assess perceived interprofessional collaboration. The IPCMS distinguishes three subscales: communication, accommodation and isolation. Data were analysed using non-parametrical tests.ResultsOverall, ratings of interprofessional collaboration were good. Obstetricians rated their collaboration with clinical midwives, nurses and primary-care midwives more positively than these three groups rated the collaboration with obstetricians. Discrepancies in mutual perceptions were most apparent in the isolation subscale, which is about sharing opinions, discussing new practices and respecting each other.ConclusionWe found relevant discrepancies in mutual perceptions of collaboration in obstetrical care in the Netherlands. Obstetrical care is currently being reorganised to enable more integrated care, which will have consequences for interprofessional collaboration. The findings of this study indicate opportunities for improvement especially in terms of perceived isolation.

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Datasets collected in general practice: an international comparison using the example of obesity

Australian Health Review ◽

10.1071/ah17157 ◽

2018 ◽

Vol 42 (5) ◽

pp. 563 ◽

Cited By ~ 1

Author(s):

Elizabeth Sturgiss ◽

Kees van Boven

Keyword(s):

Primary Care ◽

General Practice ◽

The Netherlands ◽

Care Management ◽

Clinical Care ◽

International Comparisons ◽

Health Condition ◽

Practice Management ◽

Number Of Patients ◽

Primary Care Management

International datasets from general practice enable the comparison of how conditions are managed within consultations in different primary healthcare settings. The Australian Bettering the Evaluation and Care of Health (BEACH) and TransHIS from the Netherlands collect in-consultation general practice data that have been used extensively to inform local policy and practice. Obesity is a global health issue with different countries applying varying approaches to management. The objective of the present paper is to compare the primary care management of obesity in Australia and the Netherlands using data collected from consultations. Despite the different prevalence in obesity in the two countries, the number of patients per 1000 patient-years seen with obesity is similar. Patients in Australia with obesity are referred to allied health practitioners more often than Dutch patients. Without quality general practice data, primary care researchers will not have data about the management of conditions within consultations. We use obesity to highlight the strengths of these general practice data sources and to compare their differences. What is known about the topic? Australia had one of the longest-running consecutive datasets about general practice activity in the world, but it has recently lost government funding. The Netherlands has a longitudinal general practice dataset of information collected within consultations since 1985. What does this paper add? We discuss the benefits of general practice-collected data in two countries. Using obesity as a case example, we compare management in general practice between Australia and the Netherlands. This type of analysis should start all international collaborations of primary care management of any health condition. Having a national general practice dataset allows international comparisons of the management of conditions with primary care. Without a current, quality general practice dataset, primary care researchers will not be able to partake in these kinds of comparison studies. What are the implications for practitioners? Australian primary care researchers and clinicians will be at a disadvantage in any international collaboration if they are unable to accurately describe current general practice management. The Netherlands has developed an impressive dataset that requires within-consultation data collection. These datasets allow for person-centred, symptom-specific, longitudinal understanding of general practice management. The possibilities for the quasi-experimental questions that can be answered with such a dataset are limitless. It is only with the ability to answer clinically driven questions that are relevant to primary care that the clinical care of patients can be measured, developed and improved.

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