Pushing chronic care forward in Abu Dhabi by identifying priorities and addressing barriers: a modified Delphi technique

Ethnicity-Specific Features of COVID-19 Among Arabs, Africans, South Asians, East Asians, and Caucasians in the United Arab Emirates

Background

Dubai (United Arab Emirates; UAE) has a multi-national population which makes it exceptionally interesting study sample because of its unique demographic factors.

Objective

To stratify the risk factors for the multinational society of the UAE.

Methods

A retrospective chart review of 560 patients sequentially admitted to inpatient care with laboratory confirmed COVID-19 was conducted. We studied patients’ demographics, clinical features, laboratory results, disease severity, and outcomes. The parameters were compared across different ethnic groups using tree-based estimators to rank the ethnicity-specific disease features. We trained ML classification algorithms to build a model of ethnic specificity of COVID-19 based on clinical presentation and laboratory findings on admission.

Results

Out of 560 patients, 43.6% were South Asians, 26.4% Middle Easterns, 16.8% East Asians, 10.7% Caucasians, and 2.5% are under others. UAE nationals represented half of the Middle Eastern patients, and 13% of the entire cohort. Hypertension was the most common comorbidity in COVID-19 patients. Subjective complaint of fever and cough were the chief presenting symptoms. Two-thirds of the patients had either a mild disease or were asymptomatic. Only 20% of the entire cohort needed oxygen therapy, and 12% needed ICU admission. Forty patients (~7%) needed invasive ventilation and fifteen patients died (2.7%). We observed differences in disease severity among different ethnic groups. Caucasian or East-Asian COVID-19 patients tended to have a more severe disease despite a lower risk profile. In contrast to this, Middle Eastern COVID-19 patients had a higher risk factor profile, but they did not differ markedly in disease severity from the other ethnic groups. There was no noticeable difference between the Middle Eastern subethnicities—Arabs and Africans—in disease severity (p = 0.81). However, there were disparities in the SOFA score, D-dimer (p = 0.015), fibrinogen (p = 0.007), and background diseases (hypertension, p = 0.003; diabetes and smoking, p = 0.045) between the subethnicities.

Conclusion

We observed variations in disease severity among different ethnic groups. The high accuracy (average AUC = 0.9586) of the ethnicity classification model based on the laboratory and clinical findings suggests the presence of ethnic-specific disease features. Larger studies are needed to explore the role of ethnicity in COVID-19 disease features.

Consensus among healthcare stakeholders on a collaborative medication therapy management model for chronic diseases in Malaysia; A Delphi study

Background

The general problem is lack of inter-professional collaboration and the way private primary care responds to manage chronic diseases in Malaysia. Absence of prescription review, inadequate patient education, the highest percentage of prescribing errors and half of the chronic disease patients are nonadherent. Medicines are the most common and life long used interventions in chronic diseases. Hence, the need to manage medicine in chronic diseases becomes obligatory. As both general practitioner and community pharmacist can dispense medications, this has resulted in a business rivalry. There is a need to build consensus among various healthcare stakeholders for a collaborative medication therapy management model (CMTM) where community pharmacist has an active role in chronic care.

Method

This study utilized modified e-Delphi method to build consensus. A validated e-Delphi survey was administered to a purposive sample of 29 experts. Consensus was pre-defined to be the point where >85% of the experts fall in either agree or strongly agree category for each statement. The inter-expert agreement was computed in both rounds using Intra-class correlation coefficient and Kendall's W. Delphi operates in an iterative fashion till there comes stability in responses. At the end of each round, experts were provided aggregate response, their own response and choice to change their response in the light of aggregate response.

Results

Response rate was 70.73% and 100% in 1^st and 2^nd round, respectively. Consensus was achieved on 119/132 statements which mainly referred to the need, structural and regulatory aspects of CMTM model in Malaysia. However, there were some flashpoints on dispensing separation and means to finance this model. Stability in response of experts was achieved after 2^nd round; hence, no next round was executed.

Conclusion

Overall, the study findings witnessed the expert panel’s support for the CMTM model. Study helped to sketch CMTM model and facilitated development of some recommendations to the authorities which may help to formulate a policy to bring CPs under a working relationship with GPs. Hence, this study should be taken as a call for redefining of the roles of CPs and GPs in Malaysia.

How do we strengthen the health workforce in a rapidly developing high-income country? A case study of Abu Dhabi's health system in the United Arab Emirates

BACKGROUND

The United Arab Emirates (UAE) is a rapidly developing high-income country that was formed from the union of seven emirates in 1971. The UAE has experienced unprecedented population growth coupled with increased rates of chronic diseases over the past few decades. Healthcare workers are the core foundation of the health system, especially for chronic care conditions, and the UAE health workforce needs to be fully prepared for the increased rates of chronic diseases in the adult population. Abu Dhabi is the largest emirate in terms of land mass and population size, and the purpose of this paper was to assess how the health system has been using the Chronic Care Model to improve its capacity to reach out to all patients in the population.

CASE PRESENTATION

The Abu Dhabi health workforce has twice the number of doctors (52.4 vs. 23.2 per 10 000 population) and nurses (134.7 vs. 50.4 per 10 000 population) compared to the entire UAE health workforce. In addition to an overreliance on expatriate workers, there is an excess of some specializations such as general medicine and gynecology and a severe undersupply of other specialties including trauma and injury, and medical oncology. The digital infrastructure and skills of the health workforce need to be improved to minimize the proportion of the appointment time required to complete administrative tasks for a health insurance system and maximize the doctor-patient face-to-face interaction time for consultation and lifestyle counseling.

CONCLUSIONS

A greater emphasis needs to be placed on developing self-management support strategies using a combination of nurse health educators and community-based patient-led health programs. The UAE Vision 2021 includes developing a world-class healthcare system, and full implementation of the Chronic Care Model seems to facilitate the detailed planning and preparation of healthcare services and workers required to achieve this goal.