User Satisfaction Evaluation of the EHR4CR Query Builder: A Multisite Patient Count Cohort System

The Electronic Health Records for Clinical Research (EHR4CR) project aims to develop services and technology for the leverage reuse of Electronic Health Records with the purpose of improving the efficiency of clinical research processes. A pilot program was implemented to generate evidence of the value of using the EHR4CR platform. The user acceptance of the platform is a key success factor in driving the adoption of the EHR4CR platform; thus, it was decided to evaluate the user satisfaction. In this paper, we present the results of a user satisfaction evaluation for the EHR4CR multisite patient count cohort system. This study examined the ability of testers (n=22 and n=16 from 5 countries) to perform three main tasks (around 20 minutes per task), after a 30-minute period of self-training. The System Usability Scale score obtained was 55.83 (SD: 15.37), indicating a moderate user satisfaction. The responses to an additional satisfaction questionnaire were positive about the design of the interface and the required procedure to design a query. Nevertheless, the most complex of the three tasks proposed in this test was rated as difficult, indicating a need to improve the system regarding complicated queries

User Satisfaction Evaluation of the EHR4CR Query Builder:A Multisite Patient Count Cohort System

The Electronic Health Records for Clinical Research (EHR4CR) project aims to develop services and technology for the leverage reuse of Electronic Health Records with the purpose of improving the efficiency of clinical research processes. A pilot program was implemented to generate evidence of the value of using the EHR4CR platform. The user acceptance of the platform is a key success factor in driving the adoption of the EHR4CR platform; thus, it was decided to evaluate the user satisfaction. In this paper, we present the results of a user satisfaction evaluation for the EHR4CR multisite patient count cohort system. This study examined the ability of testers (n=22 and n=16 from 5 countries) to perform three main tasks (around 20 minutes per task), after a 30-minute period of self-training. The System Usability Scale score obtained was 55.83 (SD: 15.37), indicating a moderate user satisfaction. The responses to an additional satisfaction questionnaire were positive about the design of the interface and the required procedure to design a query. Nevertheless, the most complex of the three tasks proposed in this test was rated as difficult, indicating a need to improve the system regarding complicated queries

Efficiency and effectiveness evaluation of an automated multi-country patient count cohort system

International audienceBackgroundWith the increase of clinical trial costs during the last decades, the design of feasibility studies has become an essential process to reduce avoidable and costly protocol amendments. This design includes timelines, targeted sites and budget, together with a list of eligibility criteria that potential participants need to match.The present work was designed to assess the value of obtaining potential study participant counts using an automated patient count cohort system for large multi-country and multi-site trials: the Electronic Health Records for Clinical Research (EHR4CR) system.MethodsThe evaluation focuses on the accuracy of the patient counts and the time invested to obtain these using the EHR4CR platform compared to the current questionnaire based process. This evaluation will assess the patient counts from ten clinical trials at two different sites. In order to assess the accuracy of the results, the numbers obtained following the two processes need to be compared to a baseline number, the “alloyed” gold standard, which was produced by a manual check of patient records.ResultsThe patient counts obtained using the EHR4CR system were in three evaluated trials more accurate than the ones obtained following the current process whereas in six other trials the current process counts were more accurate. In two of the trials both of the processes had counts within the gold standard’s confidence interval.In terms of efficiency the EHR4CR protocol feasibility system proved to save approximately seven calendar days in the process of obtaining patient counts compared to the current manual process.ConclusionsAt the current stage, electronic health record data sources need to be enhanced with better structured data so that these can be re-used for research purposes. With this kind of data, systems such as the EHR4CR are able to provide accurate objective patient counts in a more efficient way than the current methods.Additional research using both structured and unstructured data search technology is needed to assess the value of unstructured data and to compare the amount of efforts needed for data preparation

The Effect of Proton Energy on SEU Cross-Section of a 16Mbit TFT PMOS SRAM with DRAM Capacitors

Proton experimental data are analyzed for a 16-Mbit Thin-Film-Transistor (TFT) PMOS Static Random Access Memory (SRAM) with DRAM capacitors. The presence of high-Z materials as tungsten causes an unusual increase of the Single Event Upset (SEU) proton cross-section for the energies above 100MeV. Monte-Carlo simulations reproduce the experimentally measured cross-sections up to 480MeV and predict a further increase up to GeV energies. The implications of this increase are analyzed in the context of the LHC and other radiation environments where a significant fraction of the fluence lies above 100MeV

Evaluation of data completeness in the electronic health record for the purpose of patient recruitment into clinical trials: a retrospective analysis of element presence

Background Computerized clinical trial recruitment support is one promising field for the application of routine care data for clinical research. The primary task here is to compare the eligibility criteria defined in trial protocols with patient data contained in the electronic health record (EHR). To avoid the implementation of different patient definitions in multi-site trials, all participating research sites should use similar patient data from the EHR. Knowledge of the EHR data elements which are commonly available from most EHRs is required to be able to define a common set of criteria. The objective of this research is to determine for five tertiary care providers the extent of available data compared with the eligibility criteria of randomly selected clinical trials. Methods Each participating study site selected three clinical trials at random. All eligibility criteria sentences were broken up into independent patient characteristics, which were then assigned to one of the 27 semantic categories for eligibility criteria developed by Luo et al. We report on the fraction of patient characteristics with corresponding structured data elements in the EHR and on the fraction of patients with available data for these elements. The completeness of EHR data for the purpose of patient recruitment is calculated for each semantic group. Results 351 eligibility criteria from 15 clinical trials contained 706 patient characteristics. In average, 55% of these characteristics could be documented in the EHR. Clinical data was available for 64% of all patients, if corresponding data elements were available. The total completeness of EHR data for recruitment purposes is 35%. The best performing semantic groups were ‘age’ (89%), ‘gender’ (89%), ‘addictive behaviour’ (74%), ‘disease, symptom and sign’ (64%) and ‘organ or tissue status’ (61%). No data was available for 6 semantic groups. Conclusions There exists a significant gap in structure and content between data documented during patient care and data required for patient eligibility assessment. Nevertheless, EHR data on age and gender of the patient, as well as selected information on his disease can be complete enough to allow for an effective support of the manual screening process with an intelligent preselection of patients and patient data

Feasibility platform for stroke studies: an online tool to improve eligibility criteria for clinical trials

BACKGROUND AND PURPOSE Eligibility criteria are a key factor for the feasibility and validity of clinical trials. We aimed to develop an online tool to assess the potential effect of inclusion and exclusion criteria on the proportion of patients eligible for an acute stroke trial. METHODS We identified relevant inclusion and exclusion criteria of acute stroke trials. Based on these criteria and using a cohort of 1537 consecutive patients with acute ischemic stroke from 3 stroke centers, we developed a web portal feasibility platform for stroke studies (FePASS) to estimate proportions of eligible patients for acute stroke trials. We applied the FePASS resource to calculate the proportion of patients eligible for 4 recent stroke studies. RESULTS Sixty-one eligibility criteria were derived from 30 trials on acute ischemic stroke. FePASS, publicly available at http://fepass.uni-muenster.de, displays the proportion of patients in percent to assess the effect of varying values of relevant eligibility criteria, for example, age, symptom onset time, National Institutes of Health Stroke Scale, and prestroke modified Rankin Scale, on this proportion. The proportion of eligible patients for 4 recent stroke studies ranged from 2.1% to 11.3%. Slight variations of the inclusion criteria could substantially increase the proportion of eligible patients. CONCLUSIONS FePASS is an open access online resource to assess the effect of inclusion and exclusion criteria on the proportion of eligible patients for a stroke trial. FePASS can help to design stroke studies, optimize eligibility criteria, and to estimate the potential recruitment rate

GSK‐3 inhibition by adenoviral FRAT1 overexpression is neuroprotective and induces Tau dephosphorylation and β‐catenin stabilisation without elevation of glycogen synthase activity

Glycogen synthase kinase 3 (GSK-3) has previously been shown to play an important role in the regulation of apoptosis. However, the nature of GSK-3 effector pathways that are relevant to neuroprotection remains poorly defined. Here, we have compared neuroprotection resulting from modulation of GSK-3 activity in PC12 cells using either selective small molecule ATP-competitive GSK-3 inhibitors (SB-216763 and SB-415286), or adenovirus overexpressing frequently rearranged in advanced T-cell lymphomas 1 (FRAT1), a protein proposed as a negative regulator of GSK-3 activity towards Axin and Glycogen synthase kinase 3 (GSK-3) has previously been shown to play an important role in the regulation of apoptosis. However, the nature of GSK-3 effector pathways that are relevant to neuroprotection remains poorly defined. Here, we have compared neuroprotection resulting from modulation of GSK-3 activity in PC12 cells using either selective small molecule ATP-competitive GSK-3 inhibitors (SB-216763 and SB-415286), or adenovirus overexpressing frequently rearranged in advanced T-cell lymphomas 1 (FRAT1), a protein proposed as a negative regulator of GSK-3 activity towards Axin and β-catenin. Our data demonstrate that cellular overexpression of FRAT1 is sufficient to confer neuroprotection and correlates with inhibition of GSK-3 activity towards Tau and β-catenin, but not modulation of glycogen synthase (GS) activity. By comparison, treatment with SB-216763 and SB-415286 proved more potent in terms of neuroprotection, and correlated with inhibition of GSK-3 activity towards GS in addition to Tau and β-catenin-catenin. Our data demonstrate that cellular overexpression of FRAT1 is sufficient to confer neuroprotection and correlates with inhibition of GSK-3 activity towards Tau and β-catenin, but not modulation of glycogen synthase (GS) activity. By comparison, treatment with SB-216763 and SB-415286 proved more potent in terms of neuroprotection, and correlated with inhibition of GSK-3 activity towards GS in addition to Tau and β-cateni

Evaluation of data completeness in the electronic health record for the purpose of patient recruitment into clinical trials: a retrospective analysis of element presence

BACKGROUND: Computerized clinical trial recruitment support is one promising field for the application of routine care data for clinical research. The primary task here is to compare the eligibility criteria defined in trial protocols with patient data contained in the electronic health record (EHR). To avoid the implementation of different patient definitions in multi-site trials, all participating research sites should use similar patient data from the EHR. Knowledge of the EHR data elements which are commonly available from most EHRs is required to be able to define a common set of criteria. The objective of this research is to determine for five tertiary care providers the extent of available data compared with the eligibility criteria of randomly selected clinical trials. METHODS: Each participating study site selected three clinical trials at random. All eligibility criteria sentences were broken up into independent patient characteristics, which were then assigned to one of the 27 semantic categories for eligibility criteria developed by Luo et al. We report on the fraction of patient characteristics with corresponding structured data elements in the EHR and on the fraction of patients with available data for these elements. The completeness of EHR data for the purpose of patient recruitment is calculated for each semantic group. RESULTS: 351 eligibility criteria from 15 clinical trials contained 706 patient characteristics. In average, 55% of these characteristics could be documented in the EHR. Clinical data was available for 64% of all patients, if corresponding data elements were available. The total completeness of EHR data for recruitment purposes is 35%. The best performing semantic groups were ‘age’ (89%), ‘gender’ (89%), ‘addictive behaviour’ (74%), ‘disease, symptom and sign’ (64%) and ‘organ or tissue status’ (61%). No data was available for 6 semantic groups. CONCLUSIONS: There exists a significant gap in structure and content between data documented during patient care and data required for patient eligibility assessment. Nevertheless, EHR data on age and gender of the patient, as well as selected information on his disease can be complete enough to allow for an effective support of the manual screening process with an intelligent preselection of patients and patient data