Health Data for Research Through a Nationwide Privacy-Proof System in Belgium: Design and Implementation

Integrating human biomonitoring exposure data into a primary care morbidity database: a feasibility study

BACKGROUND

The detection of a local per- and polyfluoroalkyl substances (PFAS) pollution hotspot in Zwijndrecht (Belgium) necessitated immediate action to address health concerns of the local community. Several human biomonitoring (HBM) studies were initiated, gathering cross-sectional exposure data from more than 10,000 participants. The linkage of these HBM data with primary care health registries might be a useful new tool in environmental health analysis.

AIM

We assessed the feasibility of linking exposure data from HBM programs to health outcomes from the Intego registry, which collects data from general practitioners' electronic health records. This feasibility study uses exposure data from one of the completed PFAS HBM studies, which included 796 individuals. We describe the separate datasets, the process of integrating the HBM data into Intego, the analysis plan and the advantages and challenges of using this method.

RESULTS

We established the integration of HBM data into the Intego primary care morbidity database, adhering to stringent privacy regulations and quality standards to ensure result integrity. Because of the modest sample size used in this feasibility study, no conclusions about the impact of PFAS on health endpoints can be drawn. However, with PFAS data from more than 10,000 residents available soon, more robust studies will be possible with this new method.

INTERPRETATION

We introduce a novel approach for assessing the impact of environmental health hazards within primary care settings. The methods outlined here not only pave the way for larger-scale projects but also offer a promising avenue for long-term environmental health monitoring.

A systematic review and proposed framework for sustainable learning healthcare systems

BACKGROUND

The healthcare sector is a complex domain that faces challenges in effectively learning from practices and outcome data. The Learning Health System (LHS) has emerged as a potential framework to improve healthcare by promoting continuous learning. However, its adoption remains limited, often involving only a single clinical department or a part of the LHS cycle. There is a need to gain a better understanding of implementing LHS on a larger scale.

AIM

To identify complete implementations of the LHS for providing recommendations into their implementation strategies, success factors, barriers, and outcomes.

METHODS

A systematic review was conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines using PubMed and Scopus databases. Data from the included papers were thematically categorized into four primary areas: (1) Scale of LHS Implementation; (2) Implementation strategies and the factors that facilitated the implementation of LHS; (3) LHS outcomes; and (4) Barriers /challenges related to the LHS implementation.

RESULTS

We identified 1,279 papers, of which 37 were included in the final analysis. Barriers to implementing LHS included interoperability, data integration, electronic health records (EHRs) challenges, organizational culture, leadership, and regulatory hurdles. Most LHS initiatives lacked discussion on long-term economic sustainability models, and only 16 papers provided objective measurements of performance changes. Drawing from the findings of the included studies, this paper offers recommendations for the effective implementation of the LHS.

CONCLUSION

The establishment of sustainable LHS necessitates several key components. First, there is a need to develop long-term economic sustainability models. Secondly, governance at the national level should promote common Application Programming Interfaces (APIs) across LHS implementations, communication channels to share tacit knowledge, efficient Institutional Review Board, ethical approval processes, and connect various initiatives currently operating independently. Lastly, the success of LHS relies not only on technological infrastructure but also on the active participation of multidisciplinary teams in decision-making and sharing of tacit knowledge.

Monitoring COVID-19 in Belgian general practice: A tool for syndromic surveillance based on electronic health records

BACKGROUND

COVID-19 may initially manifest as flu-like symptoms. As such, general practitioners (GPs) will likely to play an important role in monitoring the pandemic through syndromic surveillance.

OBJECTIVES

To present a COVID-19 syndromic surveillance tool in Belgian general practices.

METHODS

We performed a nationwide observational prospective study in Belgian general practices. The surveillance tool extracted the daily entries of diagnostic codes for COVID-19 and associated conditions (suspected or confirmed COVID-19, acute respiratory infection and influenza-like illness) from electronic medical records. We calculated the 7-day rolling average for these diagnoses and compared them with data from two other Belgian population-based sources (laboratory-confirmed new COVID-19 cases and hospital admissions for COVID-19), using time series analysis. We also collected data from users and stakeholders about the syndromic surveillance tool and performed a thematic analysis.

RESULTS

4773 out of 11,935 practising GPs in Belgium participated in the study. The curve of contacts for suspected COVID-19 followed a similar trend compared with the curves of the official data sources: laboratory-confirmed COVID-19 cases and hospital admissions but with a 10-day delay for the latter. Data were quickly available and useful for decision making, but some technical and methodological components can be improved, such as a greater standardisation between EMR software developers.

CONCLUSION

The syndromic surveillance tool for COVID-19 in primary care provides rapidly available data useful in all phases of the COVID-19 pandemic to support data-driven decision-making. Potential enhancements were identified for a prospective surveillance tool.

"Goldmine" or "big mess"? An interview study on the challenges of designing, operating, and ensuring the durability of Clinical Data Warehouses in France and Belgium

OBJECTIVES

Clinical Data Warehouses (CDW) are the designated infrastructures to enable access and analysis of large quantities of electronic health record data. Building and managing such systems implies extensive "data work" and coordination between multiple stakeholders. Our study focuses on the challenges these stakeholders face when designing, operating, and ensuring the durability of CDWs for research.

MATERIALS AND METHODS

We conducted semistructured interviews with 21 professionals working with CDWs from France and Belgium. All interviews were recorded, transcribed verbatim, and coded inductively.

RESULTS

Prompted by the AI boom, healthcare institutions launched initiatives to repurpose data they were generating for care without a clear vision of how to generate value. Difficulties in operating CDWs arose quickly, strengthened by the multiplicity and diversity of stakeholders involved and grand discourses on the possibilities of CDWs, disjointed from their actual capabilities. Without proper management of the information flows, stakeholders struggled to build a shared vision. This was evident in our interviewees' contrasting appreciations of what mattered most to ensure data quality. Participants explained they struggled to manage knowledge inside and across institutions, generating knowledge loss, repeated mistakes, and impeding progress locally and nationally.

DISCUSSION AND CONCLUSION

Management issues strongly affect the deployment and operation of CDWs. This may stem from a simplistic linear vision of how this type of infrastructure operates. CDWs remain promising for research, and their design, implementation, and operation require careful management if they are to be successful. Building on innovation management, complex systems, and organizational learning knowledge will help.

Learning health systems on the front lines to strengthen care against future pandemics and climate change: a rapid review

BACKGROUND

An essential component of future-proofing health systems against future pandemics and climate change is strengthening the front lines of care: principally, emergency departments and primary care settings. To achieve this, these settings can adopt learning health system (LHS) principles, integrating data, evidence, and experience to continuously improve care delivery. This rapid review aimed to understand the ways in which LHS principles have been applied to primary care and emergency departments, the extent to which LHS approaches have been adopted in these key settings, and the factors that affect their adoption.

METHODS

Three academic databases (Embase, Scopus, and PubMed) were searched for full text articles reporting on LHSs in primary care and/or emergency departments published in the last five years. Articles were included if they had a primary focus on LHSs in primary care settings (general practice, allied health, multidisciplinary primary care, and community-based care) and/or emergency care settings. Data from included articles were catalogued and synthesised according to the modified Institute of Medicine's five-component framework for LHSs (science and informatics, patient-clinician partnerships, incentives, continuous learning culture, and structure and governance).

RESULTS

Thirty-seven articles were included, 32 of which reported LHSs in primary care settings and seven of which reported LHSs in emergency departments. Science and informatics was the most commonly reported LHS component, followed closely by continuous learning culture and structure and governance. Most articles (n = 30) reported on LHSs that had been adopted, and many of the included articles (n = 17) were descriptive reports of LHS approaches.

CONCLUSIONS

Developing LHSs at the front lines of care is essential for future-proofing against current and new threats to health system sustainability, such as pandemic- and climate change-induced events. Limited research has examined the application of LHS concepts to emergency care settings. Implementation science should be utilised to better understand the factors influencing adoption of LHS approaches on the front lines of care, so that all five LHS components can be progressed in these settings.

Model-based disease mapping using primary care registry data

BACKGROUND

Spatial modeling of disease risk using primary care registry data is promising for public health surveillance. However, it remains unclear to which extent challenges such as spatially disproportionate sampling and practice-specific reporting variation affect statistical inference.

METHODS

Using lower respiratory tract infection data from the INTEGO registry, modeled with a logistic model incorporating patient characteristics, a spatially structured random effect at municipality level, and an unstructured random effect at practice level, we conducted a case and simulation study to assess the impact of these challenges on spatial trend estimation.

RESULTS

Even with spatial imbalance and practice-specific reporting variation, the model performed well. Performance improved with increasing spatial sample balance and decreasing practice-specific variation.

CONCLUSION

Our findings indicate that, with correction for reporting efforts, primary care registries are valuable for spatial trend estimation. The diversity of patient locations within practice populations plays an important role.

Pneumococcal vaccination coverage and adherence to recommended dosing schedules in adults: a repeated cross-sectional study of the INTEGO morbidity registry

BACKGROUND

Since 2014, Belgium's Superior Health Council has recommended pneumococcal vaccination for adults aged 19-85 years at increased risk for pneumococcal diseases with a specific vaccine administration sequence and timing. Currently, Belgium has no publicly funded adult pneumococcal vaccination program. This study investigated the seasonal pneumococcal vaccination trends, evolution of vaccination coverage and adherence to the 2014 recommendations.

METHODS

INTEGO is a general practice morbidity registry in Flanders (Belgium) that represents 102 general practice centres and comprised over 300.000 patients in 2021. A repeated cross-sectional study was performed for the period between 2017 and 2021. Using adjusted odds ratios computed via multiple logistic regression, the association between an individual's characteristics (gender, age, comorbidities, influenza vaccination status and socioeconomic status) and schedule-adherent pneumococcal vaccination status was assessed.

RESULTS

Pneumococcal vaccination coincided with seasonal flu vaccination. The vaccination coverage in the population at risk decreased from 21% in 2017 to 18.2% in 2018 and then started to increase to 23.6% in 2021. Coverage in 2021 was highest for high-risk adults (33.8%) followed by 50- to 85-year-olds with comorbidities (25.5%) and healthy 65- to 85-year-olds (18.7%). In 2021, 56.3% of the high-risk adults, 74.6% of the 50+ with comorbidities persons, and 74% of the 65+ healthy persons had an adherent vaccination schedule. Persons with a lower socioeconomic status had an adjusted odds ratio of 0.92 (95% Confidence Interval (CI) 0.87-0.97) for primary vaccination, 0.67 (95% CI 0.60-0.75) for adherence to the recommended second vaccination if the 13-valent pneumococcal conjugate vaccine was administered first and 0.86 (95% CI 0.76-0.97) if the 23-valent pneumococcal polysaccharide vaccine was administered first.

CONCLUSION

Pneumococcal vaccine coverage is slowly increasing in Flanders, displaying seasonal peaks in sync with influenza vaccination campaigns. However, with less than one-fourth of the target population vaccinated, less than 60% high-risk and approximately 74% of 50 + with comorbidities and 65+ healthy persons with an adherent schedule, there is still much room for improvement. Furthermore, adults with poor socioeconomic status had lower odds of primary vaccination and schedule adherence, demonstrating the need for a publicly funded program in Belgium to ensure equitable access.

Development and operationalization of a data framework to assess quality of integrated diabetes care in the fragmented data landscape of Belgium

BACKGROUND

To assess the quality of integrated diabetes care, we should be able to follow the patient throughout the care path, monitor his/her care process and link them to his/her health outcomes, while simultaneously link this information to the primary care system and its performance on the structure and organization related quality indicators. However the development process of such a data framework is challenging, even in period of increasing and improving health data storage and management. This study aims to develop an integrated multi-level data framework for quality of diabetes care and to operationalize this framework in the fragmented Belgium health care and data landscape.

METHODS

Based on document reviews, iterative working group discussions and expert consultations, theoretical approaches and quality indicators were identified and assessed. After mapping and assessing the validity of existing health information systems and available data sources through expert consultations, the theoretical framework was translated in a data framework with measurable quality indicators. The construction of the data base included sampling procedures, data-collection, and several technical and privacy-related aspects of linking and accessing Belgian datasets.

RESULTS

To address three dimensions of quality of care, we integrated the chronic care model and cascade of care approach, addressing respectively the structure related quality indicators and the process and outcome related indicators. The corresponding data framework is based on self-collected data at the primary care practice level (using the Assessment of quality of integrated care tool), and linked health insurance data with lab data at the patient level.

CONCLUSION

In this study, we have described the transition of a theoretical quality of care framework to a unique multilevel database, which allows assessing the quality of diabetes care, by considering the complete care continuum (process and outcomes) as well as organizational characteristics of primary care practices.

Electronic Health Record-Triggered Research Infrastructure Combining Real-world Electronic Health Record Data and Patient-Reported Outcomes to Detect Benefits, Risks, and Impact of Medication: Development Study

Background

Real-world data from electronic health records (EHRs) represent a wealth of information for studying the benefits and risks of medical treatment. However, they are limited in scope and should be complemented by information from the patient perspective.

Objective

The aim of this study is to develop an innovative research infrastructure that combines information from EHRs with patient experiences reported in questionnaires to monitor the risks and benefits of medical treatment.

Methods

We focused on the treatment of overactive bladder (OAB) in general practice as a use case. To develop the Benefit, Risk, and Impact of Medication Monitor (BRIMM) infrastructure, we first performed a requirement analysis. BRIMM’s starting point is routinely recorded general practice EHR data that are sent to the Dutch Nivel Primary Care Database weekly. Patients with OAB were flagged weekly on the basis of diagnoses and prescriptions. They were invited subsequently for participation by their general practitioner (GP), via a trusted third party. Patients received a series of questionnaires on disease status, pharmacological and nonpharmacological treatments, adverse drug reactions, drug adherence, and quality of life. The questionnaires and a dedicated feedback portal were developed in collaboration with a patient association for pelvic-related diseases, Bekkenbodem4All. Participating patients and GPs received feedback. An expert meeting was organized to assess the strengths, weaknesses, opportunities, and threats of the new research infrastructure.

Results

The BRIMM infrastructure was developed and implemented. In the Nivel Primary Care Database, 2933 patients with OAB from 27 general practices were flagged. GPs selected 1636 (55.78%) patients who were eligible for the study, of whom 295 (18.0% of eligible patients) completed the first questionnaire. A total of 288 (97.6%) patients consented to the linkage of their questionnaire data with their EHR data. According to experts, the strengths of the infrastructure were the linkage of patient-reported outcomes with EHR data, comparison of pharmacological and nonpharmacological treatments, flexibility of the infrastructure, and low registration burden for GPs. Methodological weaknesses, such as susceptibility to bias, patient selection, and low participation rates among GPs and patients, were seen as weaknesses and threats. Opportunities represent usefulness for policy makers and health professionals, conditional approval of medication, data linkage to other data sources, and feedback to patients.

Conclusions

The BRIMM research infrastructure has the potential to assess the benefits and safety of (medical) treatment in real-life situations using a unique combination of EHRs and patient-reported outcomes. As patient involvement is an important aspect of the treatment process, generating knowledge from clinical and patient perspectives is valuable for health care providers, patients, and policy makers. The developed methodology can easily be applied to other treatments and health problems.

Benefits, challenges, and contributors to success for national eHealth systems implementation: a scoping review

OBJECTIVE

Our scoping review aims to assess what legal, ethical, and socio-technical factors contribute to or inhibit the success of national eHealth system implementations. In addition, our review seeks to describe the characteristics and benefits of eHealth systems.

MATERIALS AND METHODS

We conducted a scoping review of literature published in English between January 2000 and 2020 using a keyword search on 5 databases: PubMed, Scopus, Web of Science, IEEEXplore, and ProQuest. After removal of duplicates, abstract screening, and full-text filtering, 86 articles were included from 8276 search results.

RESULTS

We identified 17 stakeholder groups, 6 eHealth Systems areas, and 15 types of legal regimes and standards. In-depth textual analysis revealed challenges mainly in implementation, followed by ethico-legal and data-related aspects. Key factors influencing success include promoting trust of the system, ensuring wider acceptance among users, reconciling the system with legal requirements, and ensuring an adaptable technical platform.

DISCUSSION

Results revealed support for decentralized implementations because they carry less implementation and engagement challenges than centralized ones. Simultaneously, due to decentralized systems' interoperability issues, federated implementations (with a set of national standards) might be preferable.

CONCLUSION

This study identifies the primary socio-technical, legal, and ethical factors that challenge and contribute to the success of eHealth system implementations. This study also describes the complexities and characteristics of existing eHealth implementation programs, and suggests guidance for resolving the identified challenges.

The effect of a case-finding app on the detection rate of atrial fibrillation compared with opportunistic screening in primary care patients: protocol for a cluster randomized trial

Background

Atrial fibrillation is a cardiac arrhythmia commonly encountered in a primary care setting. Current screening is limited to pulse palpation and ECG confirmation when an irregular pulse is found. Paroxysmal atrial fibrillation will, however, still be difficult to pick up. With the advent of smartphones, screening could be more cost-efficient by making use of simple applications, lowering the need for intensive screening to discover (paroxysmal) atrial fibrillation.

Methods/design

This cluster randomized trial will examine the effect of using a smartphone-based application such as FibriCheck® on the detection rate of atrial fibrillation in a Flemish general practice population. This study will be conducted in 22 primary care practices across the Flanders region of Belgium and will last 12 months. Patients above 65 years of age will be divided in control and intervention groups on the practice level. The control group will be subjected to standard opportunistic screening only, while the intervention group will be prescribed the FibriCheck® app on top of this opportunistic screening. The difference in detection rate between control and intervention groups will be calculated at the end of the study.

We will use the online platform INTEGO for pseudonymized data collection and analysis, and risk calculation.

Discussion

Smartphone applications might offer a way to cost-effectively screen for (paroxysmal) atrial fibrillation in a primary care setting. This could open the door for the update of future screening guidelines.

Trial registration

ClinicalTrials.gov NCT04545723. Registered on September 10, 2020.

Primary care implementation study to scale up early identification and brief intervention and reduce alcohol-related negative outcomes at the community level (PINO): study protocol for a quasi-experimental 3-arm study

BACKGROUND

Primary healthcare-based Early Identification and Brief Intervention (EIBI) for hazardous and harmful alcohol use is both a clinically relevant and cost-effective strategy to reduce heavy drinking. Unfortunately, it remains poorly implemented in daily practice. Multiple studies have shown that training and support (T&S) programs can increase the use of EIBI. Nonetheless, gains have only been modest and short-term at best. Suggestions have been made to rely more on multicomponent programs that simultaneously address several barriers to the implementation of EIBI. The PINO-project aims to evaluate the added value of such a multicomponent program to improve EIBI delivery in daily practice.

METHODS/DESIGN

A quasi-experimental three-arm implementation study in Flanders (Belgium) will assess the effects of tailored T&S to General Practitioners (GPs) with or without community mobilisation on EIBI delivery in general practice. The study lasts 18 months and will take place in three comparable municipalities. In municipality 1 and 2, GPs receive a tailored T&S program. The T&S is theoretically founded and tailored to the GPs' views, needs and practice characteristics. Furthermore, community actions will be embedded within municipality 1 providing additional, contextual, support. In municipality 3, GPs are offered a minimal intervention to facilitate data collection. The primary outcome is the proportion of adult patients screened for hazardous and harmful alcohol use at the end of an 18-month implementation period. The secondary outcome is the scaling up activity at municipal level in screening rates, as assessed every 3 months, and the proportion of patients who received an additional brief intervention when necessary. Furthermore, the correlation between the opinions and needs of the GP's, their practice organisation and their EIBI performance will be explored.

DISCUSSION

The PINO-project addresses the gap between what is theoretically possible and the current practice. This is an innovative study combining T&S at GP level with community actions. At the same time, it implements and evaluates practice T&S based on the theoretical domains framework.

TRIAL REGISTRATION

This trial was approved by the Ethics Committee for Research of UZ/KU Leuven (reference number s63342 and G-2020-2177-R2(MAR)) and is registered on clinicaltrials.gov ( NCT04398576 ) in May 2020.

The effect of automated audit and feedback on data completeness in the electronic health record of the general physician: protocol for a cluster randomized controlled trial

Background

The electronic health record (EHR) of the general physician (GP) is an important tool that can be used to assess and improve the quality of healthcare. However, there are some problems when (re) using the data gathered in the EHR for quality assessments. One problem is the lack of data completeness in the EHR. Audit and feedback (A&F) is a well-known quality intervention that can improve the quality of healthcare. We hypothesize that an automated A&F intervention can be adapted to improve the data completeness of the EHR of the GP, more specifically, the number of correctly registered diagnoses of type 2 diabetes and chronic kidney disease.

Methods

This study is a pragmatic cluster randomized controlled trial with an intervention at the level of GP practice. The intervention consists of an audit and extended electronically delivered feedback with multiple components that will be delivered 4 times electronically to general practices over 12 months. The data will be analyzed on an aggregated level (per GP practice). The primary outcome is the percentage of correctly registered diagnoses of type 2 diabetes. The key secondary outcome is the registration of chronic kidney disease. Exploratory secondary outcomes are the registration of heart failure, biometric data and lifestyle habits, and the evolution of 4 different EHR-extractable quality indicators.

Discussion

This cluster randomized controlled trial intends to primarily improve the registration of type 2 diabetes in the EHR of the GP and to secondarily improve the registration of chronic kidney disease. In addition, the registration of heart failure, lifestyle parameters, and biometric data in the EHR of the GP are explored together with 4 EHR-extractable quality indicators. By doing so, this study aims to improve the data completeness of the EHR, paving the way for future quality assessments.

Trial registration

ClinicalTrials.gov NCT04388228. Registered on May 14, 2020.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-021-05259-9.

Electronic health record-based disease surveillance systems: A systematic literature review on challenges and solutions

OBJECTIVE

Disease surveillance systems are expanding using electronic health records (EHRs). However, there are many challenges in this regard. In the present study, the solutions and challenges of implementing EHR-based disease surveillance systems (EHR-DS) have been reviewed.

MATERIALS AND METHODS

We searched the related keywords in ProQuest, PubMed, Web of Science, Cochrane Library, Embase, and Scopus. Then, we assessed and selected articles using the inclusion and exclusion criteria and, finally, classified the identified solutions and challenges.

RESULTS

Finally, 50 studies were included, and 52 unique solutions and 47 challenges were organized into 6 main themes (policy and regulatory, technical, management, standardization, financial, and data quality). The results indicate that due to the multifaceted nature of the challenges, the implementation of EHR-DS is not low cost and easy to implement and requires a variety of interventions. On the one hand, the most common challenges include the need to invest significant time and resources; the poor data quality in EHRs; difficulty in analyzing, cleaning, and accessing unstructured data; data privacy and security; and the lack of interoperability standards. On the other hand, the most common solutions are the use of natural language processing and machine learning algorithms for unstructured data; the use of appropriate technical solutions for data retrieval, extraction, identification, and visualization; the collaboration of health and clinical departments to access data; standardizing EHR content for public health; and using a unique health identifier for individuals.

CONCLUSIONS

EHR systems have an important role in modernizing disease surveillance systems. However, there are many problems and challenges facing the development and implementation of EHR-DS that need to be appropriately addressed.

Cardiologists' perceptions on multidisciplinary collaboration in heart failure care - a qualitative study

BACKGROUND

Cardiologists play a key role in multidisciplinary care by guiding heart failure (HF) management in the hospital and in the community. Regional implementation of multidisciplinary health care interventions depends on how they perceive collaboration with other health care disciplines, yet research on this topic is limited. This study aimed to explore the views and opinions of cardiologists on multidisciplinary collaboration in HF care.

METHODS

We conducted a qualitative study based on face-to-face semi-structured interviews with 11 Belgian cardiologists between September 2019 and February 2020. We used the Qualitative Analysis Guide of Leuven (QUAGOL) method as guidance for data analysis until data saturation was reached.

RESULTS

Cardiologists consider the general practitioner (GP) and HF nurse as the most important partners in HF management. Cardiologists identified four problems in current multidisciplinary collaboration: the communication of a HF diagnosis to the patient, advanced care planning, titration of HF medication by the GP and electronic data exchange and communication. Three themes emerged as ideas for improvement of HF care: 1) expansion of the role of the HF nurse, 2) implementation of a structured, patient-centered, and flexible model of disease management program and 3) integrated data approaches.

CONCLUSION

Cardiologists value close cooperation with GPs in HF management. They advocate an expanded future role for the HF nurse, increased eHealth, and structured disease management to optimize current HF care.

Clinical decision support improves the appropriateness of laboratory test ordering in primary care without increasing diagnostic error: the ELMO cluster randomized trial

BACKGROUND

Inappropriate laboratory test ordering poses an important burden for healthcare. Clinical decision support systems (CDSS) have been cited as promising tools to improve laboratory test ordering behavior. The objectives of this study were to evaluate the effects of an intervention that integrated a clinical decision support service into a computerized physician order entry (CPOE) on the appropriateness and volume of laboratory test ordering, and on diagnostic error in primary care.

METHODS

This study was a pragmatic, cluster randomized, open-label, controlled clinical trial.

SETTING

Two hundred eighty general practitioners (GPs) from 72 primary care practices in Belgium.

PATIENTS

Patients aged ≥ 18 years with a laboratory test order for at least one of 17 indications: cardiovascular disease management, hypertension, check-up, chronic kidney disease (CKD), thyroid disease, type 2 diabetes mellitus, fatigue, anemia, liver disease, gout, suspicion of acute coronary syndrome (ACS), suspicion of lung embolism, rheumatoid arthritis, sexually transmitted infections (STI), acute diarrhea, chronic diarrhea, and follow-up of medication.

INTERVENTIONS

The CDSS was integrated into a computerized physician order entry (CPOE) in the form of evidence-based order sets that suggested appropriate tests based on the indication provided by the general physician.

MEASUREMENTS

The primary outcome of the ELMO study was the proportion of appropriate tests over the total number of ordered tests and inappropriately not-requested tests. Secondary outcomes of the ELMO study included diagnostic error, test volume, and cascade activities.

RESULTS

CDSS increased the proportion of appropriate tests by 0.21 (95% CI 0.16-0.26, p < 0.0001) for all tests included in the study. GPs in the CDSS arm ordered 7 (7.15 (95% CI 3.37-10.93, p = 0.0002)) tests fewer per panel. CDSS did not increase diagnostic error. The absolute difference in proportions was a decrease of 0.66% (95% CI 1.4% decrease-0.05% increase) in possible diagnostic error.

CONCLUSIONS

A CDSS in the form of order sets, integrated within the CPOE improved appropriateness and decreased volume of laboratory test ordering without increasing diagnostic error.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02950142 , registered on October 25, 2016.