scholarly journals The availability of health information system for decision-making with evidence-based medicine approach-a case study: Kermanshah, Iran

Data in Brief ◽  
2018 ◽  
Vol 19 ◽  
pp. 890-895 ◽  
Author(s):  
Ameneh Safari ◽  
Yahya Safari
Keyword(s):  
Decision Making ◽  
Information System ◽  
Health Information ◽  
Evidence Based Medicine ◽  
Health Information System ◽  
Evidence Based ◽  
Based Medicine

scholarly journals Routine Health Information System Utilization for Evidence-Based Decision Making in Amhara National Regional State, Northwest Ethiopia: a multi-level analysis.

2020 ◽  
Author(s):  
Moges Asressie Chanyalew ◽  
Mezgebu Yitayal ◽  
Asmamaw Atnafu ◽  
Binyam Tilahun
Keyword(s):  
Decision Making ◽  
Information System ◽  
Health Information ◽  
Performance Monitoring ◽  
Health Information System ◽  
Evidence Based ◽  
Department Heads ◽  
Target Setting ◽  
Work Location ◽  
And Performance

Abstract Background: Health Information System (HIS) is the key to making evidence-based decisions. Ethiopia has been implementing the Health Management Information System (HMIS) since 2008 to collect routine health data and revised it in 2017. However, the evidence is meager on the use of routine health information for decision making among department heads in the health facilities. The study aimed to assess the proportion of routine health information systems utilization for evidence-based decisions and factors associated with it. Method: A cross-sectional study was carried out among 386 department heads from 83 health facilities in ten selected districts in the Amhara region Northwest of Ethiopia from April to May 2019. The study participants were selected using a simple random sampling technique. Descriptive statistics mean and percentage were calculated. The study employed a generalized linear mixed-effect model. Adjusted Odds Ratio (AOR) and the 95% CI were calculated. Variables with p-value <0.05 were considered as predictors of routine health information system use. Result: Proportion of information use among department heads for decision making was estimated at 46%. Displaying demographic (AOR= 12.42, 95% CI: [5.52, 27.98]) and performance (AOR= 1.68; 95% CI: [1.33, 2.11]) data for monitoring, and providing feedback to HMIS unit (AOR= 2.29; 95% CI: [1.05, 5.00]) were individual (level-1) predictors. Maintaining performance monitoring team minute (AOR= 3.53; 95% CI: [1.61, 7.75]), receiving senior management directives (AOR= 3.56; 95% CI: [1.76, 7.19]), supervision (AOR= 2.84; 95% CI: [1.33, 6.07]), using HMIS data for target setting (AOR= 3.43; 95% CI: [1.66, 7.09]), and work location (AOR= 0.16; 95% CI: [0.07, 0.39]) were organizational (level-2) explanatory variables. Conclusion: The proportion of routine health information utilization for decision making was low. Displaying demographic and performance data, providing feedback to HMIS unit, maintaining performance monitoring team minute, conducting supervision, using HMIS data for target setting, and work location were factors associated with the use of routine health information for decision making. Therefore, strengthening the capacity of department heads on data displaying, supervision, feedback mechanisms, and engagement of senior management are highly recommended.

scholarly journals Routine health information system utilization for evidence-based decision making in Amhara national regional state, northwest Ethiopia: a multi-level analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Moges Asressie Chanyalew ◽  
Mezgebu Yitayal ◽  
Asmamaw Atnafu ◽  
Binyam Tilahun
Keyword(s):  
Decision Making ◽  
Information System ◽  
Health Information ◽  
Performance Monitoring ◽  
Health Information System ◽  
Evidence Based ◽  
Department Heads ◽  
Target Setting ◽  
Work Location ◽  
And Performance

Abstract Background Health Information System is the key to making evidence-based decisions. Ethiopia has been implementing the Health Management Information System (HMIS) since 2008 to collect routine health data and revised it in 2017. However, the evidence is meager on the use of routine health information for decision making among department heads in the health facilities. The study aimed to assess the proportion of routine health information systems utilization for evidence-based decisions and factors associated with it. Method A cross-sectional study was carried out among 386 department heads from 83 health facilities in ten selected districts in the Amhara region Northwest of Ethiopia from April to May 2019. The single population proportion formula was applied to estimate the sample size taking into account the proportion of data use 0.69, margin of error 0.05, and the critical value 1.96 at the 95% CI. The final sample size was estimated at 394 by considering 1.5 as a design effect and 5% non-response. The study participants were selected using a simple random sampling technique. Descriptive statistics mean and percentage were calculated. The study employed a generalized linear mixed-effect model. Adjusted Odds Ratio (AOR) and the 95% CI were calculated. Variables with p value < 0.05 were considered as predictors of routine health information system use. Result Proportion of information use among department heads for decision making was estimated at 46%. Displaying demographic (AOR = 12.42, 95% CI [5.52, 27.98]) and performance (AOR = 1.68; 95% CI [1.33, 2.11]) data for monitoring, and providing feedback to HMIS unit (AOR = 2.29; 95% CI [1.05, 5.00]) were individual (level-1) predictors. Maintaining performance monitoring team minute (AOR = 3.53; 95% CI [1.61, 7.75]), receiving senior management directives (AOR = 3.56; 95% CI [1.76, 7.19]), supervision (AOR = 2.84; 95% CI [1.33, 6.07]), using HMIS data for target setting (AOR = 3.43; 95% CI [1.66, 7.09]), and work location (AOR = 0.16; 95% CI [0.07, 0.39]) were organizational (level-2) explanatory variables. Conclusion The proportion of routine health information utilization for decision making was low. Displaying demographic and performance data, providing feedback to HMIS unit, maintaining performance monitoring team minute, conducting supervision, using HMIS data for target setting, and work location were factors associated with the use of routine health information for decision making. Therefore, strengthening the capacity of department heads on data displaying, supervision, feedback mechanisms, and engagement of senior management are highly recommended.

scholarly journals Use of Evidence in Acute Stroke Decision-Making: Implications for Evidence-Based Medicine

2021 ◽  
Author(s):  
Timothe Langlois-Therien ◽  
Brian Dewar ◽  
Ross Upshur ◽  
Michel Shamy
Keyword(s):  
Decision Making ◽  
Evidence Based Medicine ◽  
Best Practice ◽  
Medical Decision Making ◽  
Medical Decision ◽  
Evidence Based ◽  
Physician Decision Making ◽  
Prescriptive Model ◽  
Based Medicine

Evidence-Based Medicine proposes a prescriptive model of physician decision-making in which “best evidence” is used to guide best practice. And yet, proponents of EBM acknowledge that EBM fails to offer a systematic theory of physician decision-making. In this paper, we explore how physicians from the neurology and emergency medicine communities have responded to an evolving body of evidence surrounding the acute treatment of patients with ischemic stroke. Through analysis of this case study, we argue that EBM’s vision of evidence-based medical decision-making fails to appreciate a process that we have termed epistemic evaluation. Namely, physicians are required to interpret and apply any knowledge — even what EBM would term “best evidence” — in light of their own knowledge, background and experience. This is consequential for EBM as understanding what physicians do and why they do it would appear to be essential to achieving optimal practice in accordance with best evidence.

scholarly journals Applying evidence-based medicine in general practice: a video-stimulated interview study on workplace-based observation

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Lisanne S. Welink ◽  
Kaatje Van Roy ◽  
Roger A. M. J. Damoiseaux ◽  
Hilde A. Suijker ◽  
Peter Pype ◽  
...  
Keyword(s):  
Decision Making ◽  
General Practice ◽  
Evidence Based Medicine ◽  
Evidence Based ◽  
Clinical Expertise ◽  
Stimulated Recall ◽  
Previous Discussion ◽  
Based Medicine ◽  
Stimulated Recall Interviews ◽  
Gp Training

Abstract Background Evidence-based medicine (EBM) in general practice involves applying a complex combination of best-available evidence, the patient’s preferences and the general practitioner’s (GP) clinical expertise in decision-making. GPs and GP trainees learn how to apply EBM informally by observing each other’s consultations, as well as through more deliberative forms of workplace-based learning. This study aims to gain insight into workplace-based EBM learning by investigating the extent to which GP supervisors and trainees recognise each other’s EBM behaviour through observation, and by identifying aspects that influence their recognition. Methods We conducted a qualitative multicentre study based on video-stimulated recall interviews (VSI) of paired GP supervisors and GP trainees affiliated with GP training institutes in Belgium and the Netherlands. The GP pairs (n = 22) were shown fragments of their own and their partner’s consultations and were asked to elucidate their own EBM considerations and the ones they recognised in their partner’s actions. The interview recordings were transcribed verbatim and analysed with NVivo. By comparing pairs who recognised each other’s considerations well with those who did not, we developed a model describing the aspects that influence the observer’s recognition of an actor’s EBM behaviour. Results Overall, there was moderate similarity between an actor’s EBM behaviour and the observer’s recognition of it. Aspects that negatively influence recognition are often observer-related. Observers tend to be judgemental, give unsolicited comments on how they would act themselves and are more concerned with the trainee-supervisor relationship than objective observation. There was less recognition when actors used implicit reasoning, such as mindlines (internalised, collectively reinforced tacit guidelines). Pair-related aspects also played a role: previous discussion of a specific topic or EBM decision-making generally enhanced recognition. Consultation-specific aspects played only a marginal role. Conclusions GP trainees and supervisors do not fully recognise EBM behaviour through observing each other’s consultations. To improve recognition of EBM behaviour and thus benefit from informal observational learning, observers need to be aware of automatic judgements that they make. Creating explicit learning moments in which EBM decision-making is discussed, can improve shared knowledge and can also be useful to unveil tacit knowledge derived from mindlines.

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