Comparing absolute and relative distance and time travel measures of geographic access to healthcare facilities in rural Haiti.

INTRODUCTION: While travel distance and time are important proxies of physical access to health facilities, obtaining valid measures with an appropriate modelling method remains challenging in many settings. We compared five measures of geographic accessibility in Haiti, producing recommendations that consider available analytic resources and geospatial goals. METHODS: Eight public hospitals within the ministry of public health and population were included. We estimated distance and time between hospitals and geographic centroids of Haiti's section communes and population-level accessibility. Geographic feature data were obtained from public administrative databases, academic research databases and government satellites. We used validated geographic information system methods to produce five geographic access measures: (1) Euclidean distance (ED), (2) network distance (ND), (3) network travel time (NTT), (4) AccessMod 5 (AM5) distance (AM5D) and (5) AM5 travel time (AM5TT). Relative ranking of section communes across the measures was assessed using Pearson correlation coefficients, while mean differences were assessed using analysis of variance (ANOVA) and pairwise t-tests. RESULTS: All five geographic access measures were highly correlated (range: 0.78-0.99). Of the distance measures, ED values were consistently the shortest, followed by AM5D values, while ND values were the longest. ND values were as high as 2.3 times ED values. NTT models generally produced longer travel time estimates compared with AM5TT models. ED consistently overestimated population coverage within a given threshold compared with ND and AM5D. For example, population-level accessibility within 15 km of the nearest studied hospital in the Center department was estimated at 68% for ED, 50% for AM5D and 34% for ND. CONCLUSION: While the access measures were highly correlated, there were significant differences in the absolute measures. Consideration of the benefits and limitations of each geospatial measure together with the intended purpose of the estimates, such as relative proximity of patients or service coverage, are key to guiding appropriate use.

Health system costs of a breast cancer early diagnosis programme in a rural district of Rwanda: a retrospective, cross-sectional economic analysis.

OBJECTIVES: This study aimed to quantify the health system cost of the first 2 years of a Breast Cancer Early Detection (BCED) programme in a rural district in Rwanda. We also aimed to estimate the cost of implementing the programme in other districts with different referral pathways and identify opportunities for enhanced cost efficiency. DESIGN: Retrospective, cross-sectional analysis using time-driven activity-based costing, based on timed patient clinical encounters, retrospective patient data and unit costs of resources abstracted from administrative and finance records. SETTING: The BCED programme focused on timely evaluation of individuals with breast symptoms. The study evaluated the health system cost of the BCED programme at seven health centres (HCs) in Burera district and Butaro Cancer Centre of Excellence (BCCOE) at Butaro District Hospital. OUTCOME MEASURES: Health system costs per patient visit and cost per cancer diagnosed were quantified. Total start-up and recurring operational costs were also estimated, as well as health system costs of different scale-up adaptations in other districts. RESULTS: One-time start-up costswere US$36 917, recurring operational costswere US$67 711 and clinical costswere US$14 824 over 2 years. Clinical breast examinations (CBE) at HCs cost US$3.27/visit. At BCCOE, CBE-only visits cost US$13.47/visit, CBE/ultrasound US$14.79/visit and CBE/ultrasound/biopsy/pathology US$147.81/visit. Overall, clinical cost per breast cancer diagnosed was US$1482. Clinicalcost drivers were personnel at HCs (55%) and biopsy/pathology supplies at BCCOE (46%). In other districts, patients experience a longer breast evaluation pathway, adding about US$14.00/patient; this could be decreased if ultrasound services were decentralised. CONCLUSION: Clinical costs associated with BCED services at HCs were modest, similar to other general outpatient services. The BCED programme's start-up and operational costs were high but could be reduced by using local trainers and virtual mentorship. In other districts, decentralising ultrasound and/or biopsies to district hospitals could reduce costs.