Scaling up health knowledge at European level requires sharing integrated data: An approach for collection of database specification

Computerized health care databases have been widely described as an excellent opportunity for research. The availability of “big data” has brought about a wave of innovation in projects when conducting health services research. Most of the available secondary data sources are restricted to the geographical scope of a given country and present heterogeneous structure and content. Under the umbrella of the European Innovation Partnership on Active and Healthy Ageing, collaborative work conducted by the partners of the group on “adherence to prescription and medical plans” identified the use of observational and large-population databases to monitor medication-taking behavior in the elderly. This article describes the methodology used to gather the information from available databases among the Adherence Action Group partners with the aim of improving data sharing on a European level. A total of six databases belonging to three different European countries (Spain, Republic of Ireland, and Italy) were included in the analysis. Preliminary results suggest that there are some similarities. However, these results should be applied in different contexts and European countries, supporting the idea that large European studies should be designed in order to get the most of already available databases

Persistence as a Robust Indicator of Medication Adherence-Related Quality and Performance.

Medication adherence is a priority for health systems worldwide and is widely recognised as a key component of quality of care for disease management. Adherence-related indicators were rarely explicitly included in national health policy agendas. One barrier is the lack of standardised adherence terminology and of routine measures of adherence in clinical practice. This paper discusses the possibility of developing adherence-related performance indicators highlighting the value of measuring persistence as a robust indicator of quality of care. To standardise adherence and persistence-related terminology allowing for benchmarking of adherence strategies, the European Ascertaining Barriers for Compliance (ABC) project proposed a Taxonomy of Adherence in 2012 consisting of three components: initiation, implementation, discontinuation. Persistence, which immediately precedes discontinuation, is a key element of taxonomy, which could capture adherence chronology allowing the examination of patterns of medication-taking behaviour. Advances in eHealth and Information Communication Technology (ICT) could play a major role in providing necessary structures to develop persistence indicators. We propose measuring persistence as an informative and pragmatic measure of medication-taking behaviour. Our view is to develop quality and performance indicators of persistence, which requires investing in ICT solutions enabling healthcare providers to review complete information on patients' medication-taking patterns, as well as clinical and health outcomes

Adherence to chronic medication in older populations: application of a common protocol among three European cohorts

Purpose: The purpose of this study was to evaluate and compare medication adherence to chronic therapies in older populations across different regions in Europe. Methods: This explorative study applied a harmonized method of data extraction and analysis from pharmacy claims databases of three European countries to compare medication adherence at a cross-country level. Data were obtained for the period between January 1, 2010, and December 31, 2011. Patients (aged >= 65 years) who newly initiated to oral antidiabetics, antihyperlipidemics, or antiosteoporotics were identified and followed for over a 12-month period. Main outcome measures were medication adherence (medication possession ratio, [MPR]; implementation) and persistence on index treatment. All country-specific data sets were prepared by employing a common data input model. Outcome measures were calculated for each country and pooled using random effect models. Results: In total, 39, 186 new users were analyzed. In pooled data from the three countries, suboptimal implementation (MPR <80%) was 52.45% (95% CI: 33.43-70.79) for antihyperlipidemics, 61.35% (95% CI: 52.83-69.22) for antiosteoporotics, and 30.33% (95% CI: 25.53-35.60) for oral antidiabetics. Similarly, rates of non-persistence (discontinuation) were 55.63% (95% CI: 35.24-74.29) for antihyperlipidemics, 60.24% (95% CI: 45.35-73.46) for antiosteoporotics, and 46.80% (95% CI: 36.40-57.4) for oral antidiabetics. Conclusion: Medication adherence was suboptimal with >50% of older people non-adherent to antihyperlipidemics and antiosteoporotics in the three European cohorts. However, the degree of variability in adherence rates among the three countries was high. A harmonized method of data extraction and analysis across health-related database in Europe is useful to compare medication-taking behavior at a cross-country level

Persistence as a robust indicator of medication adherence-related quality and performance

Medication adherence is a priority for health systems worldwide and is widely recognised as a key component of quality of care for disease management. Adherence-related indicators were rarely explicitly included in national health policy agendas. One barrier is the lack of standardised adherence terminology and of routine measures of adherence in clinical practice. This paper discusses the possibility of developing adherence-related performance indicators highlighting the value of measuring persistence as a robust indicator of quality of care. To standardise adherence and persistence-related terminology allowing for benchmarking of adherence strategies, the European Ascertaining Barriers for Compliance (ABC) project proposed a Taxonomy of Adherence in 2012 consisting of three components: initiation, implementation, discontinuation. Persistence, which immediately precedes discontinuation, is a key element of taxonomy, which could capture adherence chronology allowing the examination of patterns of medication-taking behaviour. Advances in eHealth and Information Communication Technology (ICT) could play a major role in providing necessary structures to develop persistence indicators. We propose measuring persistence as an informative and pragmatic measure of medication-taking behaviour. Our view is to develop quality and performance indicators of persistence, which requires investing in ICT solutions enabling healthcare providers to review complete information on patients’ medication-taking patterns, as well as clinical and health outcomes

The Need to Develop Standard Measures of Patient Adherence for Big Data: Viewpoint

Despite half a century of dedicated studies, medication adherence remains far from perfect, with many patients not taking their medications as prescribed. The magnitude of this problem is rising, jeopardizing the effectiveness of evidence-based therapies. An important reason for this is the unprecedented demographic change at the beginning of the 21st century. Aging leads to multimorbidity and complex therapeutic regimens that create a fertile ground for nonadherence. As this scenario is a global problem, it needs a worldwide answer. Could this answer be provided, given the new opportunities created by the digitization of health care? Daily, health-related information is being collected in electronic health records, pharmacy dispensing databases, health insurance systems, and national health system records. These big data repositories offer a unique chance to study adherence both retrospectively and prospectively at the population level, as well as its related factors. In order to make full use of this opportunity, there is a need to develop standardized measures of adherence, which can be applied globally to big data and will inform scientific research, clinical practice, and public health. These standardized measures may also enable a better understanding of the relationship between adherence and clinical outcomes, and allow for fair benchmarking of the effectiveness and cost-effectiveness of adherence-targeting interventions. Unfortunately, despite this obvious need, such standards are still lacking. Therefore, the aim of this paper is to call for a consensus on global standards for measuring adherence with big data. More specifically, sound standards of formatting and analyzing big data are needed in order to assess, uniformly present, and compare patterns of medication adherence across studies. Wide use of these standards may improve adherence and make health care systems more effective and sustainable

Association between proton pump inhibitor therapy and clostridium difficile infection: a contemporary systematic review and meta-analysis.

Abstract Introduction Emerging epidemiological evidence suggests that proton pump inhibitor (PPI) acid-suppression therapy is associated with an increased risk of Clostridium difficile infection (CDI). Methods Ovid MEDLINE, EMBASE, ISI Web of Science, and Scopus were searched from 1990 to January 2012 for analytical studies that reported an adjusted effect estimate of the association between PPI use and CDI. We performed random-effect meta-analyses. We used the GRADE framework to interpret the findings. Results We identified 47 eligible citations (37 case-control and 14 cohort studies) with corresponding 51 effect estimates. The pooled OR was 1.65, 95% CI (1.47, 1.85), I2 = 89.9%, with evidence of publication bias suggested by a contour funnel plot. A novel regression based method was used to adjust for publication bias and resulted in an adjusted pooled OR of 1.51 (95% CI, 1.26–1.83). In a speculative analysis that assumes that this association is based on causality, and based on published baseline CDI incidence, the risk of CDI would be very low in the general population taking PPIs with an estimated NNH of 3925 at 1 year. Conclusions In this rigorously conducted systemic review and meta-analysis, we found very low quality evidence (GRADE class) for an association between PPI use and CDI that does not support a cause-effect relationship

PICALM modulates autophagy activity and tau accumulation.

Genome-wide association studies have identified several loci associated with Alzheimer's disease (AD), including proteins involved in endocytic trafficking such as PICALM/CALM (phosphatidylinositol binding clathrin assembly protein). It is unclear how these loci may contribute to AD pathology. Here we show that CALM modulates autophagy and alters clearance of tau, a protein which is a known autophagy substrate and which is causatively linked to AD, both in vitro and in vivo. Furthermore, altered CALM expression exacerbates tau-mediated toxicity in zebrafish transgenic models. CALM influences autophagy by regulating the endocytosis of SNAREs, such as VAMP2, VAMP3 and VAMP8, which have diverse effects on different stages of the autophagy pathway, from autophagosome formation to autophagosome degradation. This study suggests that the AD genetic risk factor CALM modulates autophagy, and this may affect disease in a number of ways including modulation of tau turnover.We are grateful for funding from a Wellcome Trust Principal Research Fellowship (D.C.R.), a Wellcome Trust/MRC Strategic Grant on Neurodegeneration (D.C.R., C.J.O’.K.), a Wellcome Trust Strategic Award to Cambridge Institute for Medical Research, Wellcome Trust Studentship (E.Z.), the Alzheimer’s disease Biomedical Research Unit and Addenbrooke’s Hospital, the Tau Consortium, a fellowship from University of Granada (A.L.R.), a V Foundation/Applebee’s Research Grant (D.S.W.) and NCI R01 CA 109281 (D.S.W.).This is the final published version. It is also available from Nature Publishing at http://www.nature.com/ncomms/2014/140922/ncomms5998/full/ncomms5998.html

A feasibility study of a theory-based intervention to improve appropriate polypharmacy for older people in primary care

Background: A general practitioner (GP)-targeted intervention aimed at improving the prescribing of appropriate polypharmacy for older people was previously developed using a systematic, theory-based approach based on the UK Medical Research Council’s complex intervention framework. The primary intervention component comprised a video demonstration of a GP prescribing appropriate polypharmacy during a consultation with an older patient. The video was delivered to GPs online and included feedback emphasising the positive outcomes of performing the behaviour. As a complementary intervention component, patients were invited to scheduled medication review consultations with GPs. This study aimed to test the feasibility of the intervention and study procedures (recruitment, data collection). Methods: GPs from two general practices were given access to the video, and reception staff scheduled consultations with older patients receiving polypharmacy (≥4 medicines). Primary feasibility study outcomes were the usability and acceptability of the intervention to GPs. Feedback was collected from GP and patient participants using structured questionnaires. Clinical data were also extracted from recruited patients’ medical records (baseline and 1 month post-consultation). The feasibility of applying validated assessment of prescribing appropriateness (STOPP/ START criteria, Medication Appropriateness Index) and medication regimen complexity (Medication Regimen Complexity Index) to these data was investigated. Data analysis was descriptive, providing an overview of participants’ feedback and clinical assessment findings. Results: Four GPs and ten patients were recruited across two practices. The intervention was considered usable and acceptable by GPs. Some reservations were expressed by GPs as to whether the video truly reflected resource and time pressures encountered in the general practice working environment. Patient feedback on the scheduled consultations was positive. Patients welcomed the opportunity to have their medications reviewed. Due to the short time to follow-up and a lack of detailed clinical information in patient records, it was not feasible to detect any prescribing changes or to apply the assessment tools to patients’ clinical data. Conclusion: The findings will help to further refine the intervention and study procedures (including time to follow-up) which will be tested in a randomised pilot study that will inform the design of a definitive trial to evaluate the intervention’s effectiveness

Genetic Analysis of Human Traits In Vitro: Drug Response and Gene Expression in Lymphoblastoid Cell Lines

Lymphoblastoid cell lines (LCLs), originally collected as renewable sources of DNA, are now being used as a model system to study genotype–phenotype relationships in human cells, including searches for QTLs influencing levels of individual mRNAs and responses to drugs and radiation. In the course of attempting to map genes for drug response using 269 LCLs from the International HapMap Project, we evaluated the extent to which biological noise and non-genetic confounders contribute to trait variability in LCLs. While drug responses could be technically well measured on a given day, we observed significant day-to-day variability and substantial correlation to non-genetic confounders, such as baseline growth rates and metabolic state in culture. After correcting for these confounders, we were unable to detect any QTLs with genome-wide significance for drug response. A much higher proportion of variance in mRNA levels may be attributed to non-genetic factors (intra-individual variance—i.e., biological noise, levels of the EBV virus used to transform the cells, ATP levels) than to detectable eQTLs. Finally, in an attempt to improve power, we focused analysis on those genes that had both detectable eQTLs and correlation to drug response; we were unable to detect evidence that eQTL SNPs are convincingly associated with drug response in the model. While LCLs are a promising model for pharmacogenetic experiments, biological noise and in vitro artifacts may reduce power and have the potential to create spurious association due to confounding.Molecular and Cellular Biolog