The most commonly used tool for self-report of pruritus intensity is the visual analogue scale (VAS). Similar tools are the numerical rating scale (NRS) and verbal rating scale (VRS). In the present study, initiated by the International Forum for the Study of Itch assessing reliability of these tools, 471 randomly selected patients with chronic itch (200 males, 271 females, mean age 58.44 years) recorded their pruritus intensity on VAS (100-mm line), NRS (0-10) and VRS (four-point) scales. Re-test reliability was analysed in a subgroup of 250 patients after one hour. Statistical analysis showed a high reliability and concurrent validity (r>0.8; p<0.01) for all tools. Mean values of all scales showed a high correlation. In conclusion, high reliability and concurrent validity was found for VAS, NRS and VRS. On re-test, higher correlation and less missing values were observed. A training session before starting a clinical trial is recommended.
Electronic health records (EHRs) provide opportunities to enhance patient care, embed performance measures in clinical practice, and facilitate clinical research. Concerns have been raised about the increasing recruitment challenges in trials, burdensome and obtrusive data collection, and uncertain generalizability of the results. Leveraging electronic health records to counterbalance these trends is an area of intense interest. The initial applications of electronic health records, as the primary data source is envisioned for observational studies, embedded pragmatic or post-marketing registry-based randomized studies, or comparative effectiveness studies. Advancing this approach to randomized clinical trials, electronic health records may potentially be used to assess study feasibility, to facilitate patient recruitment, and streamline data collection at baseline and follow-up.Ensuring data security and privacy, overcoming the challenges associated with linking diverse systems and maintaining infrastructure for repeat use of high quality data, are some of the challenges associated with using electronic health records in clinical research. Collaboration between academia, industry, regulatory bodies, policy makers, patients, and electronic health record vendors is critical for the greater use of electronic health records in clinical research. This manuscript identifies the key steps required to advance the role of electronic health records in cardiovascular clinical research.
BackgroundElectronic medical record (EMR) systems are increasingly being implemented in hospitals of developing countries to improve patient care and clinical service. However, only limited evaluation studies are available concerning the level of adoption and determinant factors of success in those settings.ObjectiveThe objective of this study was to assess the usage pattern, user satisfaction level, and determinants of health professional’s satisfaction towards a comprehensive EMR system implemented in Ethiopia where parallel documentation using the EMR and the paper-based medical records is in practice.MethodsA quantitative, cross-sectional study design was used to assess the usage pattern, user satisfaction level, and determinant factors of an EMR system implemented in Ethiopia based on the DeLone and McLean model of information system success. Descriptive statistical methods were applied to analyze the data and a binary logistic regression model was used to identify determinant factors.ResultsHealth professionals (N=422) from five hospitals were approached and 406 responded to the survey (96.2% response rate). Out of the respondents, 76.1% (309/406) started to use the system immediately after implementation and user training, but only 31.7% (98/309) of the professionals reported using the EMR during the study (after 3 years of implementation). Of the 12 core EMR functions, 3 were never used by most respondents, and they were also unaware of 4 of the core EMR functions. It was found that 61.4% (190/309) of the health professionals reported over all dissatisfaction with the EMR (median=4, interquartile range (IQR)=1) on a 5-level Likert scale. Physicians were more dissatisfied (median=5, IQR=1) when compared to nurses (median=4, IQR=1) and the health management information system (HMIS) staff (median=2, IQR=1). Of all the participants, 64.4% (199/309) believed that the EMR had no positive impact on the quality of care. The participants indicated an agreement with the system and information quality (median=2, IQR=0.5) but strongly disagreed with the service quality (median=5, IQR=1). The logistic regression showed a strong correlation between system use and dissatisfaction (OR 7.99, 95% CI 5.62-9.10) and service quality and satisfaction (OR 8.23, 95% CI 3.23-17.01).ConclusionsHealth professionals’ use of the EMR is low and they are generally dissatisfied with the service of the implemented system. The results of this study show that this dissatisfaction is caused mainly and strongly by the poor service quality, the current practice of double documentation (EMR and paper-based), and partial departmental use of the system in the hospitals. Thus, future interventions to improve the current use or future deployment projects should focus on improving the service quality such as power infrastructure, user support, trainings, and more computers in the wards. After service quality improvement, other departments (especially inter-dependent departments) should be motivated and supported to use the EMR to avoid the depende...
Highly reliable data handling methods, human resources and effective project management, as well as technical architecture and infrastructure are all key factors for successful EMR implementation.
BackgroundWith the increasing implementation of Electronic Medical Record Systems (EMR) in developing countries, there is a growing need to identify antecedents of EMR success to measure and predict the level of adoption before costly implementation. However, less evidence is available about EMR success in the context of low-resource setting implementations. Therefore, this study aims to fill this gap by examining the constructs and relationships of the widely used DeLone and MacLean (D&M) information system success model to determine whether it can be applied to measure EMR success in those settings.MethodsA quantitative cross sectional study design using self-administered questionnaires was used to collect data from 384 health professionals working in five governmental hospitals in Ethiopia. The hospitals use a comprehensive EMR system since three years. Descriptive and structural equation modeling methods were applied to describe and validate the extent of relationship of constructs and mediating effects.ResultsThe findings of the structural equation modeling shows that system quality has significant influence on EMR use (β = 0.32, P < 0.05) and user satisfaction (β = 0.53, P < 0.01); information quality has significant influence on EMR use (β = 0.44, P < 0.05) and user satisfaction (β = 0.48, P < 0.01) and service quality has strong significant influence on EMR use (β = 0.36, P < 0.05) and user satisfaction (β = 0.56, P < 0.01). User satisfaction has significant influence on EMR use (β = 0.41, P < 0.05) but the effect of EMR use on user satisfaction was not significant. Both EMR use and user satisfaction have significant influence on perceived net-benefit (β = 0.31, P < 0.01; β = 0.60, P < 0.01), respectively. Additionally, computer literacy was found to be a mediating factor in the relationship between service quality and EMR use (P < 0.05) as well as user satisfaction (P < 0.01). Among all the constructs, user satisfaction showed the strongest effect on perceived net-benefit of health professionals.ConclusionEMR implementers and managers in developing countries are in urgent need of implementation models to design proper implementation strategies. In this study, the constructs and relationships depicted in the updated D&M model were found to be applicable to assess the success of EMR in low resource settings. Additionally, computer literacy was found to be a mediating factor in EMR use and user satisfaction of health professionals. Hence, EMR implementers and managers in those settings should give priority in improving service quality of the hospitals like technical support and infrastructure; providing continuous basic computer trainings to health professionals; and give attention to the system and information quality of the systems they want to implement.
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