- ISSN: 0253-8253
- E-ISSN: 2227-0426
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oa Evaluation of the timeliness and completeness of communicable disease reporting: Surveillance in The Cuban Hospital, Qatar
- Source: Qatar Medical Journal, Volume 2014, Issue 1, يوليو ٢٠١٤,
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- ٠٦ أبريل ٢٠١٤
- ٣٠ يونيو ٢٠١٤
- ٠١ أغسطس ٢٠١٤
ملخص
Public health surveillance systems should be evaluated periodically, and should involve an assessment of system attributes. Objective: Evaluate hospital-based surveillance of communicable diseases using the elements of timeliness and data quality. Method: Descriptive study was conducted of communicable diseases reported at The Cuban Hospital, Qatar during January 2012 to December 2013. The completeness of notifications were assessed for contact number, address, place of work, and date of symptom onset. Time between the symptoms onset and physician notification, time between physician and Supreme Council of Health notification and time between physician notification and lab confirmation were calculated for each case. Analysis: Percentage of cases with documented essential information and 95% confidence interval (CI) were determined. Mean and standard deviation (SD) of time were calculated. Results: 1065 patients were reported, 75% were male, 80% non-qataries and 91.5% were group 1 (high priority) diseases. Symptom onset date was documented in 91.5% (95% CI, 89.8; 93.2) of cases; contact number in 84.7% (82.5;86.8), with lower frequencies for address (68.1%, 65.3;70.9) and place of work (60.5%, 57.5;63.4). Diagnostic time for tuberculosis was 61.7 days (SD 93.0), acute hepatitis 18.5 days (SD 17.6), typhoid fever 17.0 days (SD 11.6 days), other diseases of sexual transmission 300.2 days, chronic hepatitis 165 days and AIDS 154.5 days. The time of notification to the Supreme Council of Health for group 1 diseases was 1.2 days (SD 1.4). Conclusion: Our results show that the quality of essential data and timeliness is not sufficient to meet the needs of the health system. Additional studies should focus on the evaluation of time delay for diagnosis of high priority diseases.
