Risk adjustment is vital in health policy design. Risk adjustment defines the annual capitation payments to health insurers and is a key determinant of insolvency risk for health insurers. In this study we compare the current risk adjustment formula used by Colombia's Ministry of Health and Social Protection against alternative specifications that adjust for additional factors. We show that the current risk adjustment formula, which conditions on demographic factors and their interactions, can only predict 30% of total health expenditures in the upper quintile of the expenditure distribution. We also show the government's formula can improve significantly by conditioning ex ante on measures indicators of 29 long-term diseases. We contribute to the risk adjustment literature by estimating machine learning based models and showing non-parametric methodologies (e.g., boosted trees models) outperform linear regressions even when fitted in a smaller set of regressors.

This paper measures consumer responsiveness to cost sharing in healthcare using a regression discontinuity design. I use a novel and detailed claims-level dataset from the Colombian healthcare market, where the government exogenously determines a tier system for coinsurance rates and copays based on the enrollee's monthly income. I find that patients exposed to higher coinsurance rates demand fewer services relative to patients facing lower cost sharing. This reduction holds for both discretionary and preventive services.Lower utilization translates into lower costs, despite evidence that patients facing higher prices do not substitute away from more expensive providers.

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Health-care systems that rely on hospitalization for early patient treatment pose a financial concern for governments. In this article, the author suggests a hospitalization prevention program in which the decision of whether to intervene on a patient depends on a simple decision model and the prediction of the patient risk of an annual length-of-stay using machine learning techniques. These results show that the prevention program achieves significant cost savings relative to several base scenarios for program efficacies greater than or equal to 40% and intervention costs per patient of 100,000 to 700,000 Colombian pesos (i.e., approximately 14% to 100% of the average cost per patient in Colombia statuary health care system). This article also shows how tree-based methods outperform linear regressions when predicting an annual length-of-stay and the final model achieves a lower out-of-sample error compared to those of the Heritage Health Prize.

A sizable body of literature has concluded that males do better in math compared with females. Although differences have narrowed over time, generally speaking males do better on standardized test scores. However, there is no agreement on when such disparity appears and how big the differences are. This paper explores at what point during elementary school gender differences appear, when these become significant and how the gap evolves as children progress at early years. To explain differences by gender, math scores are used. Data comes from the Early Childhood Longitudinal Program (ECLS-K) in the USA. Longitudinal and cross-sectional analysis are conducted. Gender gaps are decomposed through the use of ñopo-match. Results show that gender gaps are almost inexistent at the beginning of schooling but they broaden rapidly. Between first and fifth grade, gender gaps increase by 60.8%. The unexplained components of gender differences increase over time, which suggests that the importance of socioeconomic and school factors decreases as children progress in the school.

Prescription drug formularies are an element of health insurance plan design that determine coverage and coinsurance rates for medications. Formularies are an important mechanism for healthcare cost containment that can increase the bargaining power of insurance companies in their negotiations with pharmaceutical manufacturers over the price of prescription drugs. The complexity of insurance plan design in settings such as the U.S. healthcare market and insurers' discretion over the elements of that design make it difficult to assess how changes in prescription drug coverage impact consumers. Evaluating changes in formulary design when such changes are endogenous choices of the insurer usually requires a structural approach as well as information on all other plan characteristics. While expanded coverage might increase prescription drug costs, spillovers from drug to non-drug spending raise the possibility that adding drugs to a formulary might decrease healthcare costs overall. For instance, Tamblyn et al. (2001) show that the rate of adverse health outcomes and emergency room visits increase among poor and elderly individuals following an increase in cost sharing for essential prescription drugs. Understanding how formulary design impacts healthcare costs and utilization is of great concern to countries like Canada, Mexico, Japan, Colombia, and the U.S. where prescription drug spending comprises more than 10% of total healthcare costs (OECD, 2020). Also of keen interest is how insurers' ability to respond to exogenous changes in formulary design impacts enrollees.

El presente Acuerdo de Confidencialidad (el "Acuerdo") es suscrito el día __ de ________ de 20__, entre QUANTIL SAS una compañía debidamente constituida bajo las leyes de la República de Colombia, con domicilio en la ciudad de Bogotá D.C. NIT 900225936-1 y dirección en la carrera 7 No. 77-07 de la misma ciudad (en adelante "LA COMPAÑIA"); y _______________________, identificado con cédula de ciudadanía No. __________ de _______ con domicilio en la ciudad de _________ y dirección en ______________________ (en caso de ser persona jurídica "obrando en nombre y representación de la sociedad "_____________________" domiciliada en ___________, constituida por medio