ABSTRACT
Pathology, clinical care teams, and public health experts often operate in silos. We hypothesized that large data sets from laboratories when integrated with other healthcare data can provide evidence that can be used to optimize planning for healthcare needs, often driven by health-seeking or delivery behavior. From the hospital information system, we extracted raw data from tests performed from 2019 to 2021, prescription drug usage, and admission patterns from pharmacy and nursing departments during the COVID-19 pandemic in Kenya (March 2020 to December 2021). Proportions and rates were calculated. Regression models were created, and a t-test for differences between means was applied for monthly or yearly clustered data compared to pre-COVID-19 data. Tests for malaria parasite, Mycobacterium tuberculosis, rifampicin resistance, blood group, blood count, and histology showed a statistically significant decrease in 2020, followed by a partial recovery in 2021. This pattern was attributed to restrictions implemented to control the spread of COVID-19. On the contrary, D-dimer, fibrinogen, CRP, and HbA1c showed a statistically significant increase (p-value <0.001). This pattern was attributed to increased utilization related to the clinical management of COVID-19. Prescription drug utilization revealed a non-linear relationship to the COVID-19 positivity rate. The results from this study reveal the expected scenario in the event of similar outbreaks. They also reveal the need for increased efforts at diabetes and cancer screening, follow-up of HIV, and tuberculosis patients. To realize a broader healthcare impact, pathology departments in Africa should invest in integrated data analytics, for non-communicable diseases as well.
ABSTRACT
Pathology, clinical care teams, and public health experts often operate in silos. We hypothesized that large data sets from laboratories when integrated with other healthcare data can provide evidence that can be used to optimize planning for healthcare needs, often driven by health-seeking or delivery behavior. From the hospital information system, we extracted raw data from tests performed from 2019 to 2021, prescription drug usage, and admission patterns from pharmacy and nursing departments during the COVID-19 pandemic in Kenya (March 2020 to December 2021). Proportions and rates were calculated. Regression models were created, and a t-test for differences between means was applied for monthly or yearly clustered data compared to pre-COVID-19 data. Tests for malaria parasite, Mycobacterium tuberculosis, rifampicin resistance, blood group, blood count, and histology showed a statistically significant decrease in 2020, followed by a partial recovery in 2021. This pattern was attributed to restrictions implemented to control the spread of COVID-19. On the contrary, D-dimer, fibrinogen, CRP, and HbA1c showed a statistically significant increase (p-value <0.001). This pattern was attributed to increased utilization related to the clinical management of COVID-19. Prescription drug utilization revealed a non-linear relationship to the COVID-19 positivity rate. The results from this study reveal the expected scenario in the event of similar outbreaks. They also reveal the need for increased efforts at diabetes and cancer screening, follow-up of HIV, and tuberculosis patients. To realize a broader healthcare impact, pathology departments in Africa should invest in integrated data analytics, for non-communicable diseases as well.
ABSTRACT
Background: Since COVID-19 was declared a pandemic in March 2020, hospitals and patient care facilities have faced challenges in protecting healthcare workers and patients from being exposed to the infection. The main challenge has been how exposure to COVID-19 can be controlled when asymptomatic patientscan transmit the infection. This study aims to evaluate pre-admission testing of COVID-19 in patients at the Aga Khan University Hospital, Nairobi as a screening strategy for understanding, preventing and controlling exposure to COVID-19. Methods: This was a descriptive retrospective chart review study that analysed the incidence of COVID-19, incidental detection of laboratory-confirmed COVID-19 and effects on plan of care in patients prior to admission at the Aga Khan University Hospital from April to December 31, 2020. Demographic data, clinical characteristics, COVID-19 test report and plan of care were retrieved from patients medical records review. Results: A total of 8837 pre-admission tests were done between April 2020 and December 2020, with a COVID-19 prevalence rate of 10.9% (961/8837). Among the positive pre-admission tests, 14.3% were incidental positive results (138/961). Among the 138 incidental positive tests 21% (30) had their plan of care affected, 14.5% [20] had their care interventions delayed, 4.3% [6] had their hospital stay shortened, 1.4% [2] their hospital stay prolonged and 0.7% [1] had their care diagnostics delayed. Conclusion: While community spread of COVID-19 fluctuated during this period; depending on the level of compliance to infection control measures, pre-admission prevalence rates were increasing as the year progressed. Mandatory testing of COVID-19 in hospital facilities remains an important admission requirement in controlling asymptomatic transmission of the virus. COVID-19 health burden justifies resource allocation for universal screening of all patients before hospital admission.