Resources and Geographic Access to Care for Severe Pediatric Pneumonia in Four Resource-limited Settings

Abstract

Rationale: Pneumonia is the leading cause of death in children worldwide. Identifying and appropriately managing severe pneumonia in a timely manner improves outcomes. Little is known about the readiness of healthcare facilities to manage severe pediatric pneumonia in low-resource settings. Objectives: As part of the HAPIN (Household Air Pollution Intervention Network) trial, we sought to identify healthcare facilities that were adequately resourced to manage severe pediatric pneumonia in Jalapa, Guatemala (J-GUA); Puno, Peru (P-PER); Kayonza, Rwanda (K-RWA); and Tamil Nadu, India (T-IND). We conducted a facility-based survey of available infrastructure, staff, equipment, and medical consumables. Facilities were georeferenced, and a road network analysis was performed. Measurements and Main Results: Of the 350 healthcare facilities surveyed, 13% had adequate resources to manage severe pneumonia, 37% had pulse oximeters, and 44% had supplemental oxygen. Mean (±SD) travel time to an adequately resourced facility was 41 ± 19 minutes in J-GUA, 99 ± 64 minutes in P-PER, 40 ± 19 minutes in K-RWA, and 31 ± 19 minutes in T-IND. Expanding pulse oximetry coverage to all facilities reduced travel time by 44% in J-GUA, 29% in P-PER, 29% in K-RWA, and 11% in T-IND (all P < 0.001). Conclusions: Most healthcare facilities in low-resource settings of the HAPIN study area were inadequately resourced to care for severe pediatric pneumonia. Early identification of cases and timely referral is paramount. The provision of pulse oximeters to all health facilities may be an effective approach to identify cases earlier and refer them for care and in a timely manner.

Keywords: health service accessibility; low- and middle-income country; pneumonia; pulse oximetry.

Figure 1.

Healthcare facility locations and road networks in the study boundaries in J-GUA, P-PER, K-RWA, and T-IND. Each map displays the healthcare facilities by type and road network within the boundaries of each study site. Maps are not drawn to scale; they are sized to optimize the display of facility distribution at each site. Facility locations in India were offset with a minimum separation of 2.5 km so that facilities in very close proximity could be distinguished. Facility type (i.e., hospital, health center, and other) is based on country-specific designations. The “other” category includes health posts, community health centers, and private clinics. The T-IND study site comprises two separate sites in Villupuram (left) and Nagapattinam (right). J-GUA = Jalapa, Guatemala; K-RWA = Kayonza, Rwanda; P-PER = Puno, Peru; T-IND = Tamil Nadu, India.

Figure 2.

Percentage of the modeled population living within a 10-, 30-, 60-, or 120-minute travel time to any health facility and to any health facility with available resources to administer supplemental oxygen, conduct pulse oximetry assessments, and diagnose and treat severe pneumonia. Study locations are J-GUA, P-PER, K-RWA, and T-IND. For definition of abbreviations, see Figure 1.

Figure 3.

Geographic accessibility to health facilities adequately resourced to diagnose and treat severe pneumonia in J-GUA, P-PER, K-RWA, and T-IND. Solid and open circles represent health facilities that do or do not meet criteria to manage severe pneumonia (i.e., open every day with overnight beds, a physician onsite, pulse oximeters, supplemental oxygen, chest radiography or ultrasound capacity, and antibiotics available), respectively. Shading identifies regions that are within 30, 60, 90, and 120 minutes of facilities meeting these criteria. All maps were constructed in ArcGIS Pro version 2.6.2. Health facility locations were based on Global Positioning System (GPS) coordinates measured by study staff, and the availability of resources was derived from a comprehensive survey administered to facility leaders. Mapping and analysis were limited to facilities that provided information about pneumonia treatment criteria in the survey. Study area boundaries were estimated by using buffers equaling the average distance between each health facility and its closest neighboring health facility. Road networks were constructed by using OpenStreetMap roads where motorized travel was possible. Each study area was divided into a gridded matrix of 0.1 × 0.1-km cells, and the origin–destination cost matrix solver from ArcGIS Pro Network Analyst was used to estimate the least-cost pathway in minutes from every cell to the nearest facility meeting pneumonia management criteria. Travel time accounted for road attributes, such as speed limits and directional limitations, and incorporated multiple modes of travel (i.e., walking to the road at 5 km/h and driving at half of the speed limit thereafter). Maps were not drawn to scale. The T-IND study site comprises two separate sites in Villupuram (left) and Nagapattinam (right). For definition of abbreviations, see Figure 1.

Figure 4.

Geographic accessibility to health facilities with supplemental oxygen in J-GUA, P-PER, K-RWA, and T-IND. Solid and open circles represent health facilities with and without supplemental oxygen, respectively. Shading identifies regions that are within 30-, 60-, 90-, or 120-minute travel times to facilities with supplemental oxygen within study area boundaries. All maps were constructed in ArcGIS Pro version 2.6.2. Health facility locations were based on Global Positioning System (GPS) coordinates measured by study staff, and the availability of oxygen was derived from a comprehensive survey administered to facility leaders. Mapping and analysis were limited to facilities that provided survey responses for oxygen supplementation. Study area boundaries were estimated by using buffers equaling the average distance between each health facility and its closest neighboring health facility. Road networks were constructed by using OpenStreetMap roads where motorized travel was possible. Each study area was divided into a gridded matrix of 0.1 × 0.1-km cells, and the origin–destination cost matrix solver from ArcGIS Pro Network Analyst was used to estimate the least-cost pathway in minutes from every cell to the nearest facility with supplemental oxygen. Travel time accounted for road attributes, such as speed limits and directional limitations, and incorporated multiple modes of travel (i.e., walking to the road at 5 km/h and driving at half of the speed limit thereafter). Maps are not drawn to scale. The T-IND study site comprises two separate sites in Villupuram (left) and Nagapattinam (right). For definition of abbreviations, see Figure 1.

Figure 5.

Geographic access to health facilities adequately resourced to diagnose and refer cases of severe pneumonia before and after the implementation of universal pulse oximetry coverage. (A1, B1, C1, and D1) Shading indicates the study areas in Puno, Peru; Kayonza, Rwanda; Jalapa, Guatemala; and Tamil Nadu, India (T-IND), respectively, that were within 10, 30, 60, 90, or 120 minutes of a facility with pulse oximetry (at the time of survey administration) for the diagnosis and referral of severe pneumonia; by default, this included facilities that were adequately resourced to treat severe pneumonia. (A2, B2, C2, and D2) Shading indicates regions in Puno, Peru; Kayonza, Rwanda; Jalapa, Guatemala; and T-IND, respectively, that would be within 30, 60, 90, or 120 minutes of a facility meeting the same diagnostic criteria if pulse oximetry were universally available in all facilities. Study area boundaries were estimated by using buffers equaling the average distance between each health facility and its closest neighboring health facility. Road networks were constructed by using OpenStreetMap roads where motorized travel was possible. Each study area was divided into a gridded matrix of 0.1 × 0.1-km cells, and the origin–destination cost matrix solver from ArcGIS Pro Network Analyst was used to estimate the least-cost pathway in minutes from every cell to the nearest facility with pulse oximetry before and after the hypothetical pulse oximetry intervention. Travel time accounted for road attributes, such as speed limits and directional limitations, and incorporated multiple modes of travel (i.e., walking to the road at 5 km/h and driving at half of the speed limit thereafter). Maps were not drawn to scale. The T-IND study site comprises two separate sites in Villupuram (left) and Nagapattinam (right).