MyMedR

Displaying all 4 publications

Abstract:

Sort:

Fulltext Enabling Factors for the Successful Implementation of the CBAHI Accreditation Program

Alsaedi A, Sukeri S, Yaccob NM

J Multidiscip Healthc, 2023;16:2189-2199.
PMID: 37547805 DOI: 10.2147/JMDH.S422174

BACKGROUND: Healthcare organizations worldwide tend to implement hospital accreditation programs to improve the quality of care they provide. However, the literature shows inconsistent findings on the impact of such programs on the quality of care due to improper implementation of accreditation programs.
PURPOSE: This study explored the enabling factors for the effective implementation of the Saudi Central Board for Accreditation of Healthcare Institutions (CBAHI) program in the Ministry of Health (MOH) hospitals in Madinah, Saudi Arabia.
METHODS: This qualitative study involved 22 professionals from five CBAHI-accredited MOH hospitals in Madinah, Saudi Arabia. A purposive sampling technique was applied, and data were collected through in-depth, semi-structured interviews. A thematic analysis approach was applied to the interview transcripts.
RESULTS: Four themes and 11 subthemes emerged. The emerging themes included the development of human capital, resolving quality management issues, ensuring the availability of resources, and strategizing CBAHI-specific solutions.
CONCLUSION: The current study fills this knowledge gap by identifying the factors leading to the effective implementation of the CBAHI accreditation program in the MOH hospitals. Only the effective execution of the CBAHI will increase healthcare quality and, as a result, justify the significant resources and efforts invested in these programs. Future research should replicate similar study in other governments or private hospitals.
Fulltext A comparative analysis on question classification task based on deep learning approaches

Zulqarnain M, Khalaf Zager Alsaedi A, Ghazali R, Ghouse MG, Sharif W, Aida Husaini N

PeerJ Comput Sci, 2021;7:e570.
PMID: 34435091 DOI: 10.7717/peerj-cs.570

Question classification is one of the essential tasks for automatic question answering implementation in natural language processing (NLP). Recently, there have been several text-mining issues such as text classification, document categorization, web mining, sentiment analysis, and spam filtering that have been successfully achieved by deep learning approaches. In this study, we illustrated and investigated our work on certain deep learning approaches for question classification tasks in an extremely inflected Turkish language. In this study, we trained and tested the deep learning architectures on the questions dataset in Turkish. In addition to this, we used three main deep learning approaches (Gated Recurrent Unit (GRU), Long Short-Term Memory (LSTM), Convolutional Neural Networks (CNN)) and we also applied two different deep learning combinations of CNN-GRU and CNN-LSTM architectures. Furthermore, we applied the Word2vec technique with both skip-gram and CBOW methods for word embedding with various vector sizes on a large corpus composed of user questions. By comparing analysis, we conducted an experiment on deep learning architectures based on test and 10-cross fold validation accuracy. Experiment results were obtained to illustrate the effectiveness of various Word2vec techniques that have a considerable impact on the accuracy rate using different deep learning approaches. We attained an accuracy of 93.7% by using these techniques on the question dataset.
Fulltext A review on non-edible oil as a potential feedstock for biodiesel: physicochemical properties and production technologies

Abdul Hakim Shaah M, Hossain MS, Salem Allafi FA, Alsaedi A, Ismail N, Ab Kadir MO, et al.

RSC Adv, 2021 Jul 13;11(40):25018-25037.
PMID: 35481051 DOI: 10.1039/d1ra04311k

There is increasing concern regarding alleviating world energy demand by determining an alternative to petroleum-derived fuels due to the rapid depletion of fossil fuels, rapid population growth, and urbanization. Biodiesel can be utilized as an alternative fuel to petroleum-derived diesel for the combustion engine. At present, edible crops are the primary source of biodiesel production. However, the excessive utilization of these edible crops for large-scale biodiesel production might cause food supply depletion and economic imbalance. Moreover, the utilization of edible oil as a biodiesel feedstock increases biodiesel production costs due to the high price of edible oils. A possible solution to overcome the existing limitations of biodiesel production is to utilize non-edible crops oil as a feedstock. The present study was conducted to determine the possibility and challenges of utilizing non-edible oil as a potential feedstock for biodiesel production. Several aspects related to non-edible oil as a biodiesel feedstock such as overview of biodiesel feedstocks, non-edible oil resources, non-edible oil extraction technology, its physicochemical and fatty acid properties, biodiesel production technologies, advantages and limitation of using non-edible oil as a feedstock for biodiesel production have been reviewed in various recent publications. The finding of the present study reveals that there is a huge opportunity to utilize non-edible oil as a feedstock for biodiesel production.
Fulltext Humanistic and socioeconomic burden of COPD patients and their caregivers in Malaysia

Rehman AU, Muhammad SA, Tasleem Z, Alsaedi A, Dar M, Iqbal MO, et al.

Sci Rep, 2021 11 19;11(1):22598.
PMID: 34799609 DOI: 10.1038/s41598-021-01551-5

Chronic obstructive pulmonary disease (COPD) is associated with substantial humanistic and socioeconomic burden on patients and their caregivers. COPD is expected to be 7th leading cause of disease burden till 2030. The objective of the current study was to assess the humanistic and socioeconomic burden of COPD patients and their caregivers in Malaysia. The burden includes the cost of management of COPD, QOL of COPD patients and their caregivers, work productivity and activity impairment of COPD patients and their caregivers due to COPD. One hundred and fifty COPD patients and their caregivers from the chest clinic of Penang Hospital were included in the study from August 2018 to August 2019. Caregiving cost was estimated using the replacement cost approach, while humanistic and social burden was assessed with the help of health status questionnaires. Overall, 64.66% and 7.1% of COPD patients reported to depend on informal caregivers and professional caregivers respectively. COPD patients reported dyspnoea score as 2.31 (1.31), EQ-5D-5L utility index 0.57 (0.23), CCI 2.3 (1.4), SGRQ-C 49.23 (18.61), productivity loss 31.87% and activity impairment 17.42%. Caregivers reported dyspnoea score as 0.72 (0.14), EQ-5D-5L utility index 0.57 (0.23), productivity loss 7.19% and social activity limitation as 21.63% due to taking care of COPD patients. In addition to the huge direct cost of management, COPD is also associated with substantial burden on society in terms of compromised quality of life, reduced efficiency at the workplace, activity impairment and caregiver burden.