scholarly journals Improving data quality and information utilization at Metema Primary Hospital, Amhara national regional state, Northwest Ethiopia 2018: Capstone project

2021 ◽  
Vol 27 (3) ◽  
pp. 146045822110431
Author(s):  
Tajebew Z Gonete ◽  
Lake Yazachew ◽  
Berhanu F Endehabtu
Keyword(s):  
Decision Making ◽  
Data Quality ◽  
Quality Data ◽  
Health Management Information System ◽  
Evidence Based ◽  
Supportive Supervision ◽  
Data Recording ◽  
Post Intervention ◽  
Information Utilization ◽  
Significant Difference

Quality data for evidence-based decision making become a growing concern globally. Available information needs to be disseminated on time and used for decision making. Therefore, an effective Health Management Information System is essential to make evidence-based decision. This study aimed to measure the change in data quality and information utilization before and after intervention. Facility-based pre-post interventional study design was conducted at Metema hospital from September/2016 to December30/2018. A total of 384 individual medical-records, HMIS registration-books and reports were reviewed. Training, supportive supervision and feedback were intervention packages. About 309 (80.5%) of charts were from outpatient department. Data recording completeness increased from 69.0% to 96.0%, data consistency increased from 84.0% to 99.5% and report timeliness enhanced from 66.0% to 100%. There was a statistically significant difference for data recording completeness between pre and post-intervention results with mean difference of −0.246 (−0.412, −0.081). Also, after the intervention, gap-filling feedback and supportive supervision were given to all departments. In addition, four quality improvement projects were developed at post-intervention phase. The level of data quality and use was improved after the intervention. So, designing and implementing intervention strategies based on the root causes will help to improve data quality and use.

Design of Marine Data Warehouse ETL System

2014 ◽  
Vol 668-669 ◽  
pp. 1374-1377 ◽  
Author(s):  
Wei Jun Wen
Keyword(s):  
Decision Making ◽  
Data Quality ◽  
Data Warehouse ◽  
Environmental Data ◽  
Data Sources ◽  
Quality Data ◽  
Critical Step ◽  
Marine Data ◽  
Data Extracting ◽  
Marine Environmental

ETL refers to the process of data extracting, transformation and loading and is deemed as a critical step in ensuring the quality, data specification and standardization of marine environmental data. Marine data, due to their complication, field diversity and huge volume, still remain decentralized, polyphyletic and isomerous with different semantics and hence far from being able to provide effective data sources for decision making. ETL enables the construction of marine environmental data warehouse in the form of cleaning, transformation, integration, loading and periodic updating of basic marine data warehouse. The paper presents a research on rules for cleaning, transformation and integration of marine data, based on which original ETL system of marine environmental data warehouse is so designed and developed. The system further guarantees data quality and correctness in analysis and decision-making based on marine environmental data in the future.

scholarly journals EVIDENCE-BASED MEDICINE IN THE TIMES OF COVID-19: A CROSS-SECTIONAL SURVEY TO UNDERSTAND THE INDIAN PERSPECTIVE

2021 ◽  
Vol 5 (5) ◽  
Author(s):  
Karan B. Bhanushali ◽  
Nikita Gupta ◽  
Vinayak Mishra ◽  
Heena Asnani
Keyword(s):  
Decision Making ◽  
Clinical Experience ◽  
Evidence Based Medicine ◽  
Online Survey ◽  
Medical Literature ◽  
Evidence Based ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Significant Difference ◽  
Based Medicine

Introduction: During the COVID-19 pandemic, there is a tremendous amount of literature published regularly. In a country like India, historically, where there is a paternalistic approach to practicing medicine, there is a lot of hindrance to evidence-based medicine (EBM). Doctors have always weighed one's clinical experience superior over any other form of decision-making. This system of practice has made decision-making difficult for the physicians during this pandemic as COVID-19 is a reasonably new disease entity and the physicians lack enough 'prior experience' dealing with such a situation. Our survey tries to address the common barriers to evidence-based medical practices especially during the COVID-19 pandemic in India. We also try to explore the various source of information used by the doctors. Methods: It is a descriptive cross-sectional survey. The questions were provided in multiple-choice question format. An online survey comprising of 10 questions entitled “Hurdles faced by physicians to assimilate evidence-based guidelines on COVID-19” was made using Google Forms (Google Inc, California, US) and circulated through email to medical practitioners in the Ghatkopar (Mumbai, India) Medical Association's register from 17th June 2020 to 1st September 2020. Results: Our survey collected 213 responses, out of which 80.3% (n=171) of doctors were involved in care, counseling, or management of COVID-19 patients. The most opted primary sources for evidence-based information during this pandemic were teachings of/discussions with medical colleagues (71.4%, n=152), followed by online webinars (59.6%, n= 127) and social media (41.8%, n=89). When questioned about the main obstacles faced by them to obtain evidence-based information, the responses were as follows: Overload of medical literature (53.5%, n=114), limited access to quality resources (40.8%, n=87), unfamiliarity with the bio-statistics analysis (39%, n= 83), difficulty in locating relevant medical literature (38%, n=81), unfamiliarity with the research methodology (37.1%, n=79), lack of time (30%, n=64).  Our respondents' perspective concerning EBM attributes: 57.3% (n=122) think evidence-based practice takes their clinical experience into account. 93.4% (n=199) of them have shown an interest in broadening their skills. There was no significant difference between doctors' attitudes with less than 10 years and more than 10 years of experience (chi-square value = 0.857, p = 0.65). Conclusion: Our survey results highlight the balance maintained between evidence-based medicine and experience-based medicine by Indian physicians. They identify the importance of EBM while acknowledging its shortcomings. They realize the significance of developing their repertoire to understand, appraise, and practice EBM. Keywords: EBM, COVID-19

scholarly journals Perceptions and experiences with district health information system software to collect and utilize health data in Bangladesh: A qualitative exploratory study

2020 ◽  
Author(s):  
Tahmina Begum ◽  
Shaan Muberra Khan ◽  
Bridgit Adamou ◽  
Jannatul Ferdous ◽  
Muhammad Masud Parvez ◽  
...  
Keyword(s):  
Information System ◽  
Data Quality ◽  
Health Information ◽  
Program Effectiveness ◽  
National Level ◽  
Digital Data ◽  
Quality Data ◽  
Health Management Information System ◽  
District Health ◽  
Implementation Framework

Abstract Background: Accurate and high-quality data are important for improving program effectiveness and informing policy.In 2009 Bangladesh’s health management information system (HMIS) adopted the District Health Information Software, Version 2 (DHIS2) to capture real-time health service utilization data. However, routinely collected data are being underused because of poor data quality and reporting. We aimed to understand the facilitators and barriers to implementing DHIS2 as a way to retrieve meaningful and accurate data for reproductive, maternal, newborn, child, and adolescent health (RMNCAH) services. Methods: This qualitative study was conducted in two districts of Bangladesh from September 2017 to 2018. Data collection included key informant interviews (n=11), in-depth interviews (n=23), and focus group discussions (n=2). The study participants were involved with DHIS2 implementation from the community level to the national level. The data were analyzed thematically.Results: DHIS2 could improve the timeliness and completeness of data reporting over time. The reported facilitating factors were strong government commitment, extensive donor support, and positive attitudes toward technology among staff. Quality checks and feedback loops at multiple levels of data gathering points are helpful for minimizing data errors. Introducing a dashboard makes DHIS2 compatible to use as a monitoring tool. Barriers to effective DHIS2 implementation were lack of human resources, slow Internet connectivity, frequent changes to DHIS2 versions, and maintaining both manual and electronic system side-by-side. The data in DHIS2 remains incomplete because it does not capture data from private health facilities. Having two parallel HMIS reporting the same RMNCAH indicators threatens data quality and increases the reporting workload. Conclusion: The overall insights from this study are expected to contribute to the development of effective strategies for successful DHIS2 implementation and building a responsive HMIS. Focused strategic direction is needed to sustain the achievements of digital data culture. Periodic refresher trainings, incentives for increased performance, and an automated single reporting system for multiple stakeholders could make the system more user-friendly. A national electronic health strategy and implementation framework can facilitate creating a culture of DHIS2 use for planning, setting priorities, and decision making among stakeholder groups.

Reducing inappropriate empiric vancomycin use in neutropenic fever.

2018 ◽  
Vol 36 (30_suppl) ◽  
pp. 290-290
Author(s):  
Nina Kim ◽  
Jessica Caro ◽  
Samantha Jacobs ◽  
Meenakshi Rana ◽  
Cardinale B. Smith
Keyword(s):  
Patient Outcomes ◽  
Nurse Practitioners ◽  
Neutropenic Fever ◽  
High Morbidity ◽  
Evidence Based ◽  
Intervention Period ◽  
Post Intervention ◽  
Inappropriate Use ◽  
Significant Difference ◽  
The Impact

290 Background: Neutropenic fever is an oncologic emergency associated with high morbidity and mortality, requiring prompt antibiotic initiation. National infectious disease and oncology guidelines do not recommend vancomycin for standard empiric therapy, unless used for certain evidence-based indications. At our institution, we observed inappropriate use of vancomycin for neutropenic fever and implemented an intervention to educate providers regarding appropriate indications. Methods: We conducted a series of educational sessions focused on the evidence-based indications for vancomycin use in neutropenic fever with residents, nurse practitioners, fellows, and attending physicians. We also displayed educational posters in work rooms and patient units. We conducted a retrospective chart review to assess the impact on vancomycin prescribing practices and patient outcomes pre-intervention (9/1/17 - 2/28/18) and post-intervention (3/1/18 - 5/24/18). We used descriptive statistics and chi-square tests to assess differences. Results: Vancomycin was frequently prescribed without an appropriate indication in the pre-intervention period. Both the overall use and the inappropriate use of vancomycin decreased significantly in the post-intervention period (Table 1). There was no significant difference in mean duration of fever (2.7 vs 2.1 days, p = 0.06) or length of stay (30 vs 34 days, p = 0.58) between the pre- and post-intervention groups, respectively, despite the reduction in vancomycin use. Conclusions: Multidisciplinary educational sessions reduced unnecessary vancomycin use as empiric treatment for neutropenic fever without adverse patient outcomes. This is a low resource intervention that can be applied to other healthcare settings. Future work will evaluate the effect on cost.[Table: see text]

scholarly journals Perceptions and experiences with District Health Information System software to collect and utilize health data in Bangladesh: A qualitative exploratory study

2020 ◽  
Author(s):  
Tahmina Begum ◽  
Shaan Muberra Khan ◽  
Bridgit Adamou ◽  
Jannatul Ferdous ◽  
Muhammad Masud Parvez ◽  
...  
Keyword(s):  
Information System ◽  
Data Quality ◽  
Health Information ◽  
Management Information System ◽  
Program Effectiveness ◽  
Health Management ◽  
Quality Data ◽  
Health Management Information System ◽  
Management Information ◽  
District Health

Abstract Background: Accurate and high-quality data are important for improving program effectiveness and informing policy. Bangladesh’s health management information system adopted the District Health Information Software, Version 2 (DHIS2) in 2009 to capture real-time health service utilization data. However, routinely collected data are being underused because of poor data quality. We aimed to understand the facilitators and barriers of implementing DHIS2 as a way to retrieve meaningful and accurate data for reproductive, maternal and child health (RMCAH) services. Methods: This qualitative study was conducted in two districts of Bangladesh from September 2017 to 2018. Data collection included key informant interviews (n=11), in-depth interviews (n=23), and focus group discussions (n=2). The study participants were individuals involved with DHIS2 implementation from the community level to the national level. The data were analyzed thematically.Results: DHIS2 could improve the timeliness and completeness of data reporting over time. The reported facilitating factors were strong government commitment, extensive donor support, and positive attitudes toward the technology among staffs. Quality checks and feedback loops at multiple levels of data gathering points were helpful to minimize data errors. Introducing a dashboard makes DHIS2 compatible to use as monitoring tool. However, the barriers to effective DHIS2 implementation were lack of human resources, slow Internet connectivity, frequent changes to of DHIS2 versions, and maintaining both manual and electronic system side-by-side. Data in DHIS2 remains incomplete because it does not capture data from private health facilities. Having two parallel management information systems reporting the same RMNCAH indicators threatens data quality and increases the reporting workload. Conclusion: The overall insights from this study are expected to contribute to the development of effective strategies for successful DHIS2 implementation and building responsive health management information system. Focused strategic direction is needed to sustain the achievements of digital data culture. Periodic refresher trainings, incentives for increased performance, and an automated single reporting system for multiple stakeholders could make the system more user-friendly. A national electronic health strategy and implementation framework can facilitate creating a culture of DHIS2 use for planning, setting priorities, and decision making among stakeholder groups.

scholarly journals Exploring the Potential of Online Webcam-based Eye Tracking in Decision-Making Research and Influence Factors on Data Quality

2021 ◽  
Author(s):  
Tim Schneegans ◽  
Matthew D. Bachman ◽  
Scott A. Huettel ◽  
Hauke Heekeren
Keyword(s):  
Decision Making ◽  
Eye Tracking ◽  
Data Quality ◽  
Open Source ◽  
Influence Factors ◽  
Frame Rate ◽  
Quality Data ◽  
Tracking Data ◽  
Chin Rest ◽  
Negative Effect

Recent developments of open-source online eye-tracking algorithms suggests that they may be ready for use in online studies, thereby overcoming the limitations of in-lab eye-tracking studies. However, to date there have been limited tests of the efficacy of online eye-tracking for decision-making and cognitive psychology. In this online study, we explore the potential and the limitations of online eye-tracking tools for decision-making research using the webcam-based open-source library Webgazer (Papoutsaki et al., 2016). Our study had two aims. For our first aim we assessed different variables that might affect the quality of eye-tracking data. In our experiment (N = 210) we measured a within-subjects variable of adding a provisional chin rest and a between-subjects variable of corrected vs uncorrected vision. Contrary to our hypotheses, we found that the chin rest had a negative effect on data quality. In accordance with out hypotheses, we found lower quality data in participants who wore glasses. Other influence factors are discussed, such as the frame rate. For our second aim (N = 44) we attempted to replicate a decision-making paradigm where eye-tracking data was acquired using offline means (Amasino et al., 2019). We found some relations between choice behavior and eye-tracking measures, such as the last fixation and the distribution of gaze points at the moment right before the choice. However, several effects could not be reproduced, such as the overall distribution of gaze points or dynamic search strategies. Therefore, our hypotheses only find partial evidence. This study gives practical insights for the feasibility of online eye-tacking for decision making research as well as researchers from other disciplines.

scholarly journals Emulating Agricultural Disease Management: Comparing Risk Preferences Between Industry Professionals and Online Participants Using Experimental Gaming Simulations and Paired Lottery Choice Surveys

2021 ◽  
Vol 7 ◽  
Author(s):  
Eric M. Clark ◽  
Scott C. Merrill ◽  
Luke Trinity ◽  
Gabriela Bucini ◽  
Nicholas Cheney ◽  
...  
Keyword(s):  
Decision Making ◽  
Risk Preferences ◽  
Disease Status ◽  
Well Being ◽  
Research Quality ◽  
Quality Data ◽  
Decision Making Process ◽  
Convenience Sample ◽  
Significant Difference ◽  
Industry Professionals

Mitigating the spread of disease is crucial for the well-being of agricultural production systems. Implementing biosecurity disease prevention measures can be expensive, so producers must balance the costs of biosecurity investments with the expected benefits of reducing the risk of infections. To investigate the risk associated with this decision making process, we developed an online experimental game that simulates biosecurity investment allocation of a pork production facility during an outbreak. Participants are presented with several scenarios that vary the visibility of the disease status and biosecurity protection implemented at neighboring facilities. Certain rounds allowed participants to spend resources to reduce uncertainty and reveal neighboring biosecurity and/or disease status. We then test how this uncertainty affects the decisions to spend simulation dollars to increase biosecurity and reduce risk. We recruited 50 attendees from the 2018 World Pork Expo to participate in our simulation. We compared their performance to an opportunity sample of 50 online participants from the survey crowdsourcing tool, Amazon Mechanical Turk (MTurk). With respect to biosecurity investment, we did not find a significant difference between the risk behaviors of industry professionals and those of MTurk participants for each set of experimental scenarios. Notably, we found that our sample of industry professionals opted to pay to reveal disease and biosecurity information more often than MTurk participants. However, the biosecurity investment decisions were not significantly different during rounds in which additional information could be purchased. To further validate these findings, we compared the risk associated with each group's responses using a well-established risk assessment survey implementing paired lottery choices. Interestingly, we did not find a correlation in risk quantified with simulated biosecurity investment in comparison to the paired lottery choice survey. This may be evidence that general economic risk preferences may not always translate into simulated behavioral risk, perhaps due to the contextual immersion provided by experimental gaming simulations. Online recruitment tools can provide cost effective research quality data that can be rapidly assembled in comparison to industry professionals, who may be more challenging to sample at scale. Using a convenience sample of industry professionals for validation can also provide additional insights into the decision making process. These findings lend support to using online experimental simulations for interpreting risk associated with a complex decision mechanism.

scholarly journals Perceptions and experiences with District Health Information System software to collect and utilize health data in Bangladesh: A qualitative exploratory study

2019 ◽  
Author(s):  
Tahmina Begum ◽  
Shaan Muberra Khan ◽  
Bridgit Adamou ◽  
Jannatul Ferdous ◽  
Muhammad Masud Parvez ◽  
...  
Keyword(s):  
Information System ◽  
Data Quality ◽  
Health Information ◽  
Management Information System ◽  
Program Effectiveness ◽  
Health Management ◽  
Quality Data ◽  
Health Management Information System ◽  
Management Information ◽  
District Health

Abstract Background: Accurate and high-quality data are important for improving program effectiveness and informing policy. Bangladesh’s health management information system adopted the District Health Information Software, Version 2 (DHIS2) in 2009 to capture real-time health service utilization data. However, routinely collected data are being underused because of poor data quality. We aimed to understand the facilitators and barriers of implementing DHIS2 as a way to retrieve meaningful and accurate data for reproductive, maternal and child health (RMCAH) services. Methods: This qualitative study was conducted in two districts of Bangladesh from September 2017 to 2018. Data collection included key informant interviews (n=11), in-depth interviews (n=23), and focus group discussions (n=2). The study participants were individuals involved with DHIS2 implementation from the community level to the national level. The data were analyzed thematically. Results: DHIS2 could improve the timeliness and completeness of data reporting over time. The reported facilitating factors were strong government commitment, extensive donor support, and positive attitudes toward the technology among staffs. Quality checks and feedback loops at multiple levels of data gathering points were helpful to minimize data errors. Introducing a dashboard makes DHIS2 compatible to use as monitoring tool. However, the barriers to effective DHIS2 implementation were lack of human resources, slow Internet connectivity, frequent changes to of DHIS2 versions, and maintaining both manual and electronic system side-by-side. Data in DHIS2 remains incomplete because it does not capture data from private health facilities. Having two parallel management information systems reporting the same RMNCAH indicators threatens data quality and increases the reporting workload. Conclusion: The overall insights from this study are expected to contribute to the development of effective strategies for successful DHIS2 implementation and building responsive health management information system. Focused strategic direction is needed to sustain the achievements of digital data culture. Periodic refresher trainings, incentives for increased performance, and an automated single reporting system for multiple stakeholders could make the system more user-friendly. A national electronic health strategy and implementation framework can facilitate creating a culture of DHIS2 use for planning, setting priorities, and decision making among stakeholder groups.

scholarly journals A Methodological Quality Assessment of Meta-Analysis Studies in Dance Therapy Using AMSTAR and AMSTAR 2

Healthcare ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 446
Author(s):  
Hye-Ryeon Kim ◽  
Chang-Hwan Choi ◽  
Eunhye Jo
Keyword(s):  
Decision Making ◽  
Dance Therapy ◽  
Methodological Quality ◽  
Meta Analysis ◽  
Assessment Tools ◽  
Quality Level ◽  
Evidence Based ◽  
Evaluation Scores ◽  
Significant Difference

Although earlier meta-analysis studies have provided evidence-based information useful for decision-making, debate regarding their quality continues. This study aimed to evaluate the quality of meta-analysis studies in the field of dance therapy (DT) using the Assessment of Multiple Systematic Reviews (AMSTAR) and AMSTAR 2 assessment tools. Meta-analysis studies on DT were collected from various databases. Seven meta-analysis studies were selected for this study. Our findings showed that the quality level of the meta-analysis studies related to DT was “High” on the AMSTAR evaluation, but their quality decreased to “Low” on the AMSTAR 2 evaluation. Moreover, using AMSTAR 2, 71.43% of the studies fell within the category of “Moderate” or below. There was no statistically significant difference in the quality scores of the characteristics of these studies. Our results suggest that (1) education on meta-analysis guidelines is required to improve the quality of DT-related meta-analysis studies, and (2) methodological caution is warranted, since different outcomes in evaluation scores for each tool may be obtained when using AMSTAR and AMSTAR 2. Based on this study, it is expected that common and specific guidelines for meta-analysis in DT can be established.

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