AIMS: This study aimed to identify, appraise, and integrate the evidence for the experiences and preferences of Muslim patients and/or families for end-of-life care in Muslim-majority countries.
DESIGN: Systematic review.
DATA SOURCES: PsychINFO, MEDLINE, Embase, Global Health, CINAHL, Cochrane Library and Registry of Clinical Trials, PubMed, Applied Social Sciences Index and Abstracts (ASSIA), Social Services Abstracts, Sociological Abstracts, Social Policy & Practice, and Scopus were searched until December 2018. Handsearching was performed, and gray literature was included. Qualitative studies analyzed using thematic analysis and quantitative component provided triangulation.
RESULTS: The initial search yielded n = 5098 articles, of which n = 30 met the inclusion criteria. A total of 5342 participants (4345 patients; 81.3%) were included; 97.6% had advanced cancer. Most (n = 22) studies were quantitative. Three themes and subthemes from qualitative studies were identified using thematic analysis: selflessness (burden to others and caregiver responsibilities), ambivalence (hope and hopelessness), and strong beliefs in Islam (beliefs in death and afterlife and closeness to Allah). Qualitative studies reported triangulation; demonstrating conflicts in diagnosis disclosure and total pain burden experienced by both patients and families.
CONCLUSION: Despite the scarce evidence of relatively low quality, the analysis revealed core themes. To achieve palliative care for all in line with the total pain model, beliefs must be identified and understood in relation to decision-making processes and practices.
METHODS: Convenience sampling was employed for data collection in three government hospitals for 7 months. A standardized effectiveness survey for EHR systems was administered to primary health care providers (specialists, medical officers, and nurses) as they participated in medical education programs. Empirical data were assessed by employing partial least squares-structural equation modeling for hypothesis testing.
RESULTS: The results demonstrated that knowledge quality had the highest score for predicting performance and had a large effect size, whereas system compatibility was the most substantial system quality component. The findings indicated that EHR systems supported the clinical tasks and workflows of care providers, which increased system quality, whereas the increased quality of knowledge improved user performance.
CONCLUSION: Given these findings, knowledge quality and effective use should be incorporated into evaluating EHR system effectiveness in health institutions. Data mining features can be integrated into current systems for efficiently and systematically generating health populations and disease trend analysis, improving clinical knowledge of care providers, and increasing their productivity. The validated survey instrument can be further tested with empirical surveys in other public and private hospitals with different interoperable EHR systems.