Cost-sharing and associated factors in the Peruvian private health care system.

BACKGROUND: The costs associated with healthcare are of critical importance to both decision-makers and users, given the limited resources allocated to the health sector. However, the available scientific evidence on healthcare costs in low- and middle-income countries, such as Peru, is scarce. In the Peruvian context, the health system is fragmented, and the private health insurance and its financing models have received less research attention. We aimed to analyse user cost-sharing and associated factors within the private healthcare system. METHODS: Our study was cross-sectional, using open data from the Electronic Transaction Model of Standardized Billing Data-TEDEF-SUSALUD, between 2021-2022. Our unit of analysis is the user's medical bills. We considered the total amount of cost-sharing, proportion of total payments as cost-sharing, and cost-sharing as a proportion of minimum salaries. We use a multiple regression model to perform the analyses. RESULTS: Our study included 5,286,556 health services provided to users of the private health insurance in Peru. We found a significant difference was observed in the cost-sharing for hospitalization-related services, with an average of 419.64 soles per day (95% CI: 413.44 to 425.85). Also, we identified that for hospitalization-related services per day is, on average, 0.41 (95% CI: 0.41 to 0.41) minimum salaries more expensive than outpatient care, although cost-sharing per day of hospitalization represent on average only 14% of the total amount submitted. CONCLUSIONS: Our study provides a detailed overview of cost-sharing in the private healthcare system in Peru and the factors associated with them. Policymakers can use the study's finding that higher cost-sharing for inpatient hospitalization compared to outpatient care in private insurance can create inequities in access to healthcare to design policies aimed at reducing these costs and promoting a more equitable and accessible healthcare system in Peru.

Impact of the COVID-19 pandemic on the services provided by the Peruvian health system: an analysis of people with chronic diseases.

During the pandemic, many individuals with chronic or infectious diseases other than COVID-19 were unable to receive the care they needed due to the high demand for respiratory care. Our study aims to assess the impact of the COVID-19 pandemic on services provided to people with chronic diseases in Peru from 2016 to 2022. We performed a secondary database analysis of data registered by the comprehensive health insurance (SIS), the intangible solidarity health fund (FISSAL), and private healthcare institutions (EPS), using interrupted time series analysis. Our study identified 21,281,128 individual users who received care. The pooled analysis revealed an average decrease of 1,782,446 in the number of users receiving care in the first month of the pandemic compared with the expected values for that month based on pre-pandemic measurements. In addition, during the pandemic months, there was an average increase of 57,911 in the number of new additional single users who received care per month compared with the previous month. According to the time-series analysis of users receiving care per month based on each chronic disease group, the most significant decreases included people with diabetes without complications and chronic lung disease.

Free-Roaming Dog Surveys in Quito, Ecuador: Experiences, Lessons Learned, and Future Work.

The selection of a survey method of free-roaming dog populations should be based on analyses of local capacities and management priorities. Here, we compare the results of surveys of the stray dog population in Quito, Ecuador, using two different methodologies and propose an alternative method for future surveys in the city. We carried out all surveys in ~5 km-transects in a sample of eight urban and eight rural parishes (16 transects total). In 2018, we used the capture-recapture method to estimate absolute population size and 95% CI. We began transect surveys at 04 h 00 (local time) and identified individuals with photographs. The main limitations of this method were errors in identifying individuals, since photographs were not always clear, partly due to low light conditions during the surveys. This method also required more time and more complex logistics. In 2019, we used distance sampling to estimate population density and began the surveys at 08 h 00 (local time). Errors in the estimation of animal-observer distances and angles were our main concern when using this method. For future surveys, we propose to carry out direct observations of dog abundance (number of free-roaming dogs/km) during street counts, complemented with capture-recapture surveys every 5 years. This alternative method albeit simple, is sensitive enough to (1) provide local authorities with objective assessments of management interventions, (2) better understanding the dynamics of free-roaming dog populations and (3) increasing public awareness about the problem of pet abandonment through citizen participation in the surveys.