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An earthquake followed by tsunami and liquefaction on September 28, 2018, in Central Sulawesi caused health system disruptions. This study aimed to know health system disruption at the primary health center (PHC) level due to the disaster in 3 districts (Palu, Sigi, Donggala) of Central Sulawesi.
Methods:
This was a qualitative study conducted in March 2019 involving 36 PHCs. Data were collected through interview of PHC officers using a structured questionnaire. Variables included disruption of management, budget, human resources, drug supply, Early Warning Alert and Response System (EWARS) of epidemic prone disease (EPD), human resource migration, health facility damage, and health facility access. Descriptive analysis was conducted to define disruption for a 1-y projection.
Results:
Health system disruptions in Palu affected management, budget, human resources, EWARS, health facility damage, and health access; occurred within 1-2 mo; and were projected to become better after 6 mo. Problems in Sigi were management, human resources, drug supply, EPD, and EWARS for 1 mo after disaster and were projected to be better after 2 mo. The problems in Donggala were health services access, management, human resources for 1 mo after the disaster and were projected to be normal after 2 mo.
Conclusions:
Health system disruptions occurred in Central Sulawesi Province at the PHC level within 1-2 mo and were projected to become better after 3 mo in most PHCs.
In resource-constrained settings, primary health centers (PHCs) are critical for universal health coverage. Laboratory service is one of its important components. While PHC and its performance are focused, its laboratory service has been neglected in developing countries like India.
Aim:
To determine the role of different level of PHC laboratory services on the overall PHC performance.
Methods:
Cross-sectional study based on 42 PHCs of Osmanabad District, Maharashtra, India was performed. The study used levels of laboratory services in PHC as independent parameter and PHC outpatient department (OPD) visits per day (≤ 80 versus > 80) as dependent parameter. The control parameters used in the study were number of medical doctors, availability of laboratory technicians (LTs) and population coverage by PHC. Field visit was done to collect data on levels of laboratory services, but secondary source was used for other parameters. The logistic regression analysis was performed in study.
Findings:
The study found variation in PHC population coverage (10 788–74 702) and OPD visits per day (40–182) across PHC. Strong positive association was observed between levels of laboratory services and number of OPD visits per day in PHC. PHC offering both malaria and tuberculosis in-house testing had higher odds (4.81) of getting more OPDs (≥ 80 OPD visits per day) as compared to PHC not offering in-house testing facility for malaria and tuberculosis. This association was stronger in PHCs with lower population coverage (0–75 quartile) as compared to PHCs with higher population coverage (75–100 quartile).
Conclusion:
Focus on laboratory services is needed to enhance the existing PHCs performance. Skill-up gradation of existing LT could help in improving the contribution of the existing laboratories in PHC functioning.
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