RESUMEN
BACKGROUND: Qatar has culturally diverse health professionals; and therefore, the care provided may vary according to their background, resulting in variations in care. To bridge this gap, the Ministry of Public Health (MOPH) has established the National Clinical Guidelines (NCG) Program, which aims to reduce variation in care delivery, improve value-add from the healthcare system, adopt international best practices to local context, and enable insurers and providers to access the most currently reviewed evidence-based practice in diagnosis and management of diseases. The NCG for "Diagnosis and Management of Asthma in Adults" was developed in collaboration between Strategic Planning and Performance Department and Subject Matter Experts (SMEs) who are practicing healthcare professionals representing different healthcare organizations in Qatar. The NCG aims to standardize the management and treatment received by adult patients with asthma across the healthcare system and adapt the best practice recommendations in the management of asthma to the culture, customs, practice, and formulary of Qatar. METHODS: This NCG has been developed through a rigorous process that aligns with international best practices and localized to the context of Qatar, involving:⢠Extensive literature search for reputed published evidence specific to NCGs.⢠Critical appraisal of the literature.⢠Development of a baseline draft guideline.⢠Review of the baseline draft by SMEs and patients.⢠Review of the guidelines by the National Clinical Guidelines and Pathways Committee (NCGPC) from stakeholder organizations across Qatar. RESULTS: The first edition of the NCG was published on the MOPH website on December 14, 2016; and it was updated and republished on August 22, 2019. A Patient Information Leaflet (PIL) was prepared from the NCG using simple language for use by the patients. The NCG is currently under an updation process based on new evidence since August 22, 2019. A live demo was developed on how to access the NCG and its relevant pathways from the MOPH website and navigate each section of the guidelines. CONCLUSION: These NCGs will improve the quality of care for patients with asthma and advocate for the best clinical practice strategies on the management of asthma in adults.
RESUMEN
BACKGROUND: Atherosclerotic cardiovascular disease (ASCVD) is a common disease in the State of Qatar and results in considerable morbidity, impairment of quality of life and mortality. The American College of Cardiology/American Heart Association Pooled Cohort Equations (PCE) is currently used in Qatar to identify those at high risk of ASCVD. However, it is unclear if this is the optimal ASCVD risk prediction model for use in Qatar's ethnically diverse population. AIMS: This systematic review aimed to identify, assess the methodological quality of and compare the properties of established ASCVD risk prediction models for the Qatari population. METHODS: Two reviewers performed head-to-head comparisons of established ASCVD risk calculators systematically. Studies were independently screened according to predefined eligibility criteria and critically appraised using Prediction Model Risk Of Bias Assessment Tool. Data were descriptively summarized and narratively synthesized with reporting of key statistical properties of the models. RESULTS: We identified 20,487 studies, of which 41 studies met our eligibility criteria. We identified 16 unique risk prediction models. Overall, 50% (n = 8) of the risk prediction models were judged to be at low risk of bias. Only 13% of the studies (n = 2) were judged at low risk of bias for applicability, namely, PREDICT and QRISK3.Only the PREDICT risk calculator scored low risk in both domains. CONCLUSIONS: There is no existing ASCVD risk calculator particularly well suited for use in Qatar's ethnically diverse population. Of the available models, PREDICT and QRISK3 appear most appropriate because of their inclusion of ethnicity. In the absence of a locally derived ASCVD for Qatar, there is merit in a formal head-to-head comparison between PCE, which is currently in use, and PREDICT and QRISK3.
