A quality improvement program for adolescents with cystic fibrosis: focus on psychosocial skills

Background

The two pediatric cystic fibrosis centers (CFCs) in Paris (Robert Debré) and Nantes, France, have been developing therapeutic patient education (TPE) programs since 2006 and have been engaged in the pilot phase of the quality improvement program (QIP) named the Hospital Program to Improve Outcomes and Expertise in Cystic Fibrosis (PHARE-M) since 2011. The objective was to improve the FEV1 of the cohort of adolescents to prepare them for their optimal transition to an adult CFC.

Methods

The two CFCs formed a multidisciplinary quality team and used the analysis of causes of insufficient respiratory function taking into account the adolescents’ psychosocial factors. At the Nantes CFC, the approach was centered on adolescents’ body image and their motivation to take care of themselves by assigning specific aspects of patient follow-up to each professional in the team. At R. Debré, an individual cause-and-effect diagram identified for each patient the medical and psychosocial factors that could account for insufficient respiratory function. Personalized actions were offered to each patient.

Results

In 2014, the median FEV1 (Forced Expiratory Volume in 1 Second) of the adolescent cohort exceeds 90% at the 2 CFCs (Nantes and R. Debré). Between 2011 and 2014 both centers improved their ranking for FEV1% in adolescents in the Registry histograms. At R. Debré, the personalized process allowed to reinforce equality of care, offering to all the opportunity to benefit from TPE sessions and coaching with an adapted physical activity teacher. The psychologist developed a specific tool to support the patient-centered process.

Conclusion

The link between TPE and QIP was strong at our two centers enhancing patient centered care and targeting an optimal transition to an adult program.

     

Introduction of a collaborative quality improvement program in the French cystic fibrosis network: the PHARE-M initiative

Background

An agreement, signed in 2007 by the 49 French Cystic Fibrosis Centers, included a commitment to participate, within the next 5 years, in a care quality assessment and improvement program (QIP). The objective was to roll out in the French Cystic Fibrosis (CF) care network a QIP adapted from the US program for Accelerating Improvement in Cystic Fibrosis Care developed by The Dartmouth Institute Microsystem Academy (TDIMA) and customized by the US CF Foundation between 2002 and 2013.

Methods

The French national team at the Nantes-Roscoff CF Center of Expertise was trained at TDIMA and visited US CF centers involved in US Learning and Leadership Collaboratives (LLCs). It introduced the PHARE-M QIP in France by transposing the Action Guide and material. A PHARE-M LLC1 including seven centers, underwent two external assessments. Adjustments were made, then a PHARE-M LLC2 was rolled out at seven more centers in two regions. On-site coaching was strengthened. The teams’ satisfaction was assessed and further adjustments were made. In 2014, the program sought recognition as a continuing education program for healthcare professionals.

Results

Ninety-six trainees including 14 patients/parents from the 14 CFCs volunteered to participate, test and adapt the program during LLC1 and LLC2 sessions. Comparison of patient outcomes collected in the Registry report by CF center, reflection on potential best practices, selection by each team of an improvement theme, implementation of improvement actions, and exchanges between teams fostered the adhesion of the teams. The program strengthened quality of care, interdisciplinary functioning and collaboration with patients/parents at the centers. The satisfaction expressed by the teams increased over time. A post-PHARE-M cycle maintains the focus on continuous quality improvement (CQI). In 2015, PHARE-M was recognized as a continuing professional development program in healthcare.

Conclusions

The PHARE-M is a complex intervention in multidisciplinary teams working in a variety of hospital settings. A confluence of factors motivated teams to engage in the program. Involving Patient/Parent in quality improvement (QI) work and developing patient therapeutic education for self-management appeared to be complementary approaches to improve care. Incorporating the program into hospital continuing education insures its sustainability. Transparency of Patient Registry indicators per center published in a brief lapse of time is required to effectively support CQI. The impact of the PHARE-M on patient outcomes after 3 years is the subject of a research program funded by the French Ministry of Health whose results will be available in 2017.

     

Quality of care in cystic fibrosis: assessment protocol of the French QIP PHARE-M

Background

The PHARE-M care quality improvement program, modeled on the US Cystic Fibrosis Quality Improvement Program, was introduced at 14 cystic fibrosis centers (CFCs) in the French Cystic Fibrosis Network between 2011 and 2013. The pilot phase assessments attested the progressive adherence of the teams and improvements in care management. The PHARE-M Performance research project aims at assessing in 2015 the impact of the PHARE-M program on patient health indicators at trained versus untrained centers. It also sought to identify contextual factors that could account for variability in the performance of the PHARE-M among the trained centers.

Methods

A mixed methodology combining:

• a quantitative experimental study: a comparison, using a mixed model for repeated data (from 2011 to 2015), of the average changes over time in forced expiratory volume in 1 s (FEV1) and body mass index (BMI) between two groups of patients included in a closed cohort (non-transplant patients, continuous follow-up at one participating CFC, and a CF-causing mutation), one having benefitted from the PHARE-M program and the other not having done so, and
• a realistic study: a characterization of the impact on care management and an identification of mechanisms through which the PHARE-M intervention improved the team’s effectiveness in different CFC contexts; this required modeling the intervention, context, and impact on care management with respect to the criteria of the chronic care model (CCM); this was done using a self-administered questionnaire given to professionals and patients/parents supplemented with focus groups.

Conclusion

Although the study population was controlled, it may be difficult to establish a causal relationship between the differences in the changes over time in patient health indicators in the two groups of patients and the PHARE-M intervention as it is often the case in complex interventions rolled out in adaptive environments. The analysis of factors associated with variations in the impact of the PHARE-M at the different trained CFCs required the adoption of instruments validated in other contexts; these could be useful for assessing the performance of other interventions in healthcare practices at CFCs in France.

     

Nationwide claims data validated for quality assessments in acute myocardial infarction in the Netherlands

Introduction

Since health insurance is compulsory in the Netherlands, the centrally registered medical claims data might pose a unique opportunity to evaluate quality of (cardiac) care on a national level without additional collection of data. However, validation of these claims data has not yet been assessed.

Design

Retrospective cohort study.

Methods

National claims data (‘national registry’) were compared with data collected by patient records reviews in four representative hospitals (‘validation registry’). In both registries, we extracted the national diagnosis codes for ST-segment elevation myocardial infarction and non-ST-segment elevation myocardial infarction of 2012 and 2013. Additionally, data on medication use at one year after acute myocardial infarction (AMI) was extracted from the Dutch pharmacy information systems and also validated by local patient records reviews. The data were compared at three stages: 1) validation of diagnosis and treatment coding; 2) validation of the hospital where follow-up has taken place; 3) validation of follow-up medical treatment after 365 days.

Results

In total, 3,980 patients (‘national registry’) and 4,014 patients (‘validation registry’) were compared at baseline. After one-year follow-up, 2,776 and 2,701 patients, respectively, were evaluated. Baseline characteristics, diagnosis and individual medication were comparable between the two registries. Of all 52,672 AMI patients in the Netherlands in 2012 and 2013, 81% used aspirin, 76% used P2Y12 inhibitors, 85% used statins, 82% used beta-blockers and 74% angiotensin converting enzyme inhibitors/angiotensin II antagonists. Optimal medical treatment was achieved in 49% of the patients with AMI.

Conclusion

Nationwide routinely collected claims data in patients with an acute myocardial infarction are highly accurate. This offers an opportunity for use in quality assessments of cardiac care.

     

Workflow to improve patient recruitment for clinical trials within hospital information systems – a case-study

Background

The identification of suitable patients is a common problem in clinical trials that is especially evident in tertiary care hospitals.

Methods

We developed and analysed a workflow, which uses routine data captured during patient care in a hospital information system (HIS), to identify potential trial subjects. Study nurses or physicians are notified automatically by email and verify eligibility.

Results

As a case study we implemented the system for acute myeloid leukemia (AML) trials in Münster. During a test period of 50 days 41 patients were identified by the system. 13 could be included as new trial patients, 7 were already included during earlier visits. According to review of paper records no AML trial patient was missed by the system. In addition, the hospital information system further allowed to preselect patients for specific trials based on their disease status and individual characteristics.

Conclusion

Routine HIS data can be used to support patient recruitment for clinical trials by means of an automated notification workflow.

     

Privacy-preserving record linkage in large databases using secure multiparty computation

Background

Practical applications for data analysis may require combining multiple databases belonging to different owners, such as health centers. The analysis should be performed without violating privacy of neither the centers themselves, nor the patients whose records these centers store. To avoid biased analysis results, it may be important to remove duplicate records among the centers, so that each patient’s data would be taken into account only once. This task is very closely related to privacy-preserving record linkage.

Methods

This paper presents a solution to privacy-preserving deduplication among records of several databases using secure multiparty computation. It is build upon one of the fastest practical secure multiparty computation platforms, called Sharemind.

Results

The tests on ca 10 million records of simulated databases with 1000 health centers of 10000 records each show that the computation is feasible in practice. The expected running time of the experiment is ca. 30 min for computing servers connected over 100 Mbit/s WAN, the expected error of the results is 2^?40, and no errors have been detected for the particular test set that we used for our benchmarks.

Conclusions

The solution is ready for practical use. It has well-defined security properties, implied by the properties of Sharemind platform. The solution assumes that exact matching of records is required, and a possible future research would be extending it to approximate matching.

     

A lost opportunity for science: journals promote data sharing in metabolomics but do not enforce it

Introduction

Data sharing is being increasingly required by journals and has been heralded as a solution to the ‘replication crisis’.

Objectives

(i) Review data sharing policies of journals publishing the most metabolomics papers associated with open data and (ii) compare these journals’ policies to those that publish the most metabolomics papers.

Methods

A PubMed search was used to identify metabolomics papers. Metabolomics data repositories were manually searched for linked publications.

Results

Journals that support data sharing are not necessarily those with the most papers associated to open metabolomics data.

Conclusion

Further efforts are required to improve data sharing in metabolomics.

     

Logistic regression over encrypted data from fully homomorphic encryption

Background

One of the tasks in the 2017 iDASH secure genome analysis competition was to enable training of logistic regression models over encrypted genomic data. More precisely, given a list of approximately 1500 patient records, each with 18 binary features containing information on specific mutations, the idea was for the data holder to encrypt the records using homomorphic encryption, and send them to an untrusted cloud for storage. The cloud could then homomorphically apply a training algorithm on the encrypted data to obtain an encrypted logistic regression model, which can be sent to the data holder for decryption. In this way, the data holder could successfully outsource the training process without revealing either her sensitive data, or the trained model, to the cloud.

Methods

Our solution to this problem has several novelties: we use a multi-bit plaintext space in fully homomorphic encryption together with fixed point number encoding; we combine bootstrapping in fully homomorphic encryption with a scaling operation in fixed point arithmetic; we use a minimax polynomial approximation to the sigmoid function and the 1-bit gradient descent method to reduce the plaintext growth in the training process.

Results

Our algorithm for training over encrypted data takes 0.4–3.2 hours per iteration of gradient descent.

Conclusions

We demonstrate the feasibility but high computational cost of training over encrypted data. On the other hand, our method can guarantee the highest level of data privacy in critical applications.

     

Untargeted metabolomics suffers from incomplete raw data processing

Introduction

Untargeted metabolomics is a powerful tool for biological discoveries. To analyze the complex raw data, significant advances in computational approaches have been made, yet it is not clear how exhaustive and reliable the data analysis results are.

Objectives

Assessment of the quality of raw data processing in untargeted metabolomics.

Methods

Five published untargeted metabolomics studies, were reanalyzed.

Results

Omissions of at least 50 relevant compounds from the original results as well as examples of representative mistakes were reported for each study.

Conclusion

Incomplete raw data processing shows unexplored potential of current and legacy data.

     

Practice of ST-segment elevation myocardial infarction care in the Netherlands during four snapshot weeks with the National Cardiovascular Database Registry for Acute Coronary Syndrome

Background

Clinical registries provide information on the process of care and patient outcomes, with the potential to improve the quality of patient care. A large Dutch national acute coronary syndrome (ACS) registry is currently lacking. Recently, we initiated the National Cardiovascular Database Registry (NCDR) for ACS in the Netherlands. The purpose of this study was to assess the NCDR ACS registry on feasibility and data completeness during a pilot phase of four snapshot weeks.

Methods

Between 2013 and 2015, we invited all hospitals in the Netherlands to record a predefined dataset for every patient that was admitted to their hospital with ST-segment elevation myocardial infarction (STEMI). Data were entered in an online case report form. All patient-specific data were encrypted to ensure privacy.

Results

A total of 392 patients were registered in 35 centres. The mean age of the patients was 64 years (SD 13); 8% of patients presented with signs of cardiogenic shock and 11% with an out-of-hospital cardiac arrest. The median time from first medical contact to percutaneous coronary intervention (PCI) was 75 min (IQR 51–108) and this was significantly longer for patients who presented at a non-PCI centre or to a primary care physician. In-hospital and 30-day mortality rates were 5.2% and 7.8%, respectively. The amount of completeness varied, with improved completeness over time.

Conclusion

This report shows that a Dutch ACS registry is feasible with respect to STEMI patients. Data completeness, however, was suboptimal. Improved data completeness is warranted for the future.

     

Factor XIII Val34Leu polymorphism and risk of recurrent pregnancy loss in Iranian population: a case control study

BACKGROUND

Recurrent pregnancy loss (RPL) is a heterogeneous condition and thrombophilias have been considered as a probable cause.

OBJECTIVE

The aim of this study was to investigate the prevalence of the coagulation factor XIII Val34Leu polymorphism among women with unexplained RPL.

METHODS

A total of 140 women with a history of unexplained RPL and 100 age-matched healthy fertile women were recruited. The presence of FXIII Val34Leu polymorphism among the cases and controls was investigated using PCR-RFLP method.

RESULTS

Genotype analyses of the subjects revealed that the patients had a significantly higher prevalence of V/L and L/L than the controls (P<0.05): 33.5% vs. 15%, and 9.2% vs. 2%, respectively.

CONCLUSION

These results indicate a significant association between FXIII Val34Leu polymorphism and unexplained RPL in the Iranian patient.

     

KniMet: a pipeline for the processing of chromatography–mass spectrometry metabolomics data

Introduction

Data processing is one of the biggest problems in metabolomics, given the high number of samples analyzed and the need of multiple software packages for each step of the processing workflow.

Objectives

Merge in the same platform the steps required for metabolomics data processing.

Methods

KniMet is a workflow for the processing of mass spectrometry-metabolomics data based on the KNIME Analytics platform.

Results

The approach includes key steps to follow in metabolomics data processing: feature filtering, missing value imputation, normalization, batch correction and annotation.

Conclusion

KniMet provides the user with a local, modular and customizable workflow for the processing of both GC–MS and LC–MS open profiling data.

     

Hypocapnia is a biological marker for orthostatic intolerance in some patients with chronic fatigue syndrome

Context

Patients with chronic fatigue syndrome and those with orthostatic intolerance share many symptoms, yet questions exist as to whether CFS patients have physiological evidence of orthostatic intolerance.

Objective

To determine if some CFS patients have increased rates of orthostatic hypotension, hypertension, tachycardia, or hypocapnia relative to age-matched controls.

Design

Assess blood pressure, heart rate, respiratory rate, end tidal CO2 and visual analog scales for orthostatic symptoms when supine and when standing for 8 minutes without moving legs.

Setting

Referral practice and research center.

Participants

60 women and 15 men with CFS and 36 women and 4 men serving as age matched controls with analyses confined to 62 patients and 35 controls showing either normal orthostatic testing or a physiological abnormal test.

Main outcome measures

Orthostatic tachycardia; orthostatic hypotension; orthostatic hypertension; orthostatic hypocapnia or combinations thereof.

Results

CFS patients had higher rates of abnormal tests than controls (53% vs 20%, p < .002), but rates of orthostatic tachycardia, orthostatic hypotension, and orthostatic hypertension did not differ significantly between patients and controls (11.3% vs 5.7%, 6.5% vs 2.9%, 19.4% vs 11.4%, respectively). In contrast, rates of orthostatic hypocapnia were significantly higher in CFS than in controls (20.6% vs 2.9%, p < .02). This CFS group reported significantly more feelings of illness and shortness of breath than either controls or CFS patients with normal physiological tests.

Conclusion

A substantial number of CFS patients have orthostatic intolerance in the form of orthostatic hypocapnia. This allows subgrouping of patients with CFS and thus reduces patient pool heterogeneity engendered by use of a clinical case definition.

     

Pseudo current density maps of electrophysiological heart,nerve or brain function and their physical basis

Background

In recent years the visualization of biomagnetic measurement data by so-called pseudo current density maps or Hosaka-Cohen (HC) transformations became popular.

Methods

The physical basis of these intuitive maps is clarified by means of analytically solvable problems.

Results

Examples in magnetocardiography, magnetoencephalography and magnetoneurography demonstrate the usefulness of this method.

Conclusion

Hardware realizations of the HC-transformation and some similar transformations are discussed which could advantageously support cross-platform comparability of biomagnetic measurements.

     

An oncoplastic technique to reduce the formation of lateral 'dog-ears' after mastectomy

Background

Lateral skin folds or 'dog-ears' are frequent following mastectomy, particularly in patients with large body habitus.

Methods

We describe a method of modifying the mastectomy incision and suturing to eliminate these lateral 'dog-ears'.

Conclusion

This surgical technique, as compared to others described in the literature, is simple, does not require additional incisions and is cosmetically acceptable to the patient.

     

GLI 2012 equations define few spirometric anomalies in the general population: the PneumoLaus study

Background

Reduced lung function predicts increased mortality, but its prevalence may vary depending on definition considered, use of bronchodilation and applied reference values. We aimed to assess lung function abnormalities in Lausanne, Switzerland, and their association with clinical history.

Methods

In a general population sample, spirometry was performed and bronchodilation applied if the ratio forced expiratory volume in 1?s (FEV1) / forced vital capacity (FVC) or the FVC was below the lower limit of normal (LLN) according to Global Lung Function Initiative 2012 references. Results for FEV1/FVC according to the LLN were compared to the 0.7 fixed ratio. Respiratory risk factors, symptoms and self-reported respiratory diagnoses were recorded through a questionnaire.

Results

Out of the 3342 included subjects, 3.8% had chronic obstruction and 2.5% reversible obstruction when using the LLN; possible lung restriction alone was present in 1.8%, and associated with chronic obstruction in 0.4%. Ever smokers had a higher prevalence of abnormal spirometry, chronic obstruction and reversible obstruction; there was no difference with regard to possible restriction. Overall, chronic airway obstruction was found in 8.9% of current smokers, 4.6% of former smokers and 1.5% of never smokers. Only one third of participants with chronic obstruction were aware of a respiratory disease.

Conclusion

Prevalence of abnormal lung function in the population of Lausanne is low. This may be due to a low rate of ever-smokers, the application of a full bronchodilation dose, but also to inherent characteristics of this population.

     

Optimization of fecal sample preparation for untargeted LC-HRMS based metabolomics

Introduction

Collecting feces is easy. It offers direct outcome to endogenous and microbial metabolites.

Objectives

In a context of lack of consensus about fecal sample preparation, especially in animal species, we developed a robust protocol allowing untargeted LC-HRMS fingerprinting.

Methods

The conditions of extraction (quantity, preparation, solvents, dilutions) were investigated in bovine feces.

Results

A rapid and simple protocol involving feces extraction with methanol (1/3, M/V) followed by centrifugation and a step filtration (10 kDa) was developed.

Conclusion

The workflow generated repeatable and informative fingerprints for robust metabolome characterization.

     

<Emphasis Type="Italic">massPix</Emphasis>: an R package for annotation and interpretation of mass spectrometry imaging data for lipidomics

Introduction

Mass spectrometry imaging (MSI) experiments result in complex multi-dimensional datasets, which require specialist data analysis tools.

Objectives

We have developed massPix—an R package for analysing and interpreting data from MSI of lipids in tissue.

Methods

massPix produces single ion images, performs multivariate statistics and provides putative lipid annotations based on accurate mass matching against generated lipid libraries.

Results

Classification of tissue regions with high spectral similarly can be carried out by principal components analysis (PCA) or k-means clustering.

Conclusion

massPix is an open-source tool for the analysis and statistical interpretation of MSI data, and is particularly useful for lipidomics applications.

     

Mapping data elements to terminological resources for integrating biomedical data sources

Background

Data integration is a crucial task in the biomedical domain and integrating data sources is one approach to integrating data. Data elements (DEs) in particular play an important role in data integration. We combine schema- and instance-based approaches to mapping DEs to terminological resources in order to facilitate data sources integration.

Methods

We extracted DEs from eleven disparate biomedical sources. We compared these DEs to concepts and/or terms in biomedical controlled vocabularies and to reference DEs. We also exploited DE values to disambiguate underspecified DEs and to identify additional mappings.

Results

82.5% of the 474 DEs studied are mapped to entries of a terminological resource and 74.7% of the whole set can be associated with reference DEs. Only 6.6% of the DEs had values that could be semantically typed.

Conclusion

Our study suggests that the integration of biomedical sources can be achieved automatically with limited precision and largely facilitated by mapping DEs to terminological resources.