Science, technology, and innovation in health for the next twenty years: A survey analysis in Colombia.

Background: Colombia is a Latin American country with a very complex social and political context that has not allowed the allocation of sufficient resources to the fields of science, technology, and innovation (STI). This is particularly worrying for the area of health since not enough resources are allocated for public health, research, or education. Methods: The so-called "Great Survey in Health 2019" was administered online through the SurveyMonkey platform to 5298 people in different regions of the country, representing the public, private, and academic sectors. The questionnaire consisted of 46 open and closed questions, including demographic inquiries. Data analysis involved textual analytics and sentiment analysis. Results: Overall, 56% of those surveyed were women within the adult life cycle. Most respondents had a postgraduate education. Greater participation was observed in the Oriental, Bogotá, and Antioquia regions, which also concentrate the largest number of resources for STI. Among the main recommendations derived from the results, priorities include investing in research, personalised medicine, promoting the social appropriation of knowledge, addressing mental health, regulating research through a statute, promoting undergraduate research, and establishing recertification exams to pursue excellence. Conclusion: The results of this original study serve as a fundamental input to promote and strengthen the STI processes in life sciences and health. They serve as a guide to generate public policies and actions that guarantee better health and well-being for the Colombian population, strategically proposing a clear roadmap for the next 20 years.

Predictive models for health outcomes due to SARS-CoV-2, including the effect of vaccination: a systematic review.

BACKGROUND: The interaction between modelers and policymakers is becoming more common due to the increase in computing speed seen in recent decades. The recent pandemic caused by the SARS-CoV-2 virus was no exception. Thus, this study aims to identify and assess epidemiological mathematical models of SARS-CoV-2 applied to real-world data, including immunization for coronavirus 2019 (COVID-19). METHODOLOGY: PubMed, JSTOR, medRxiv, LILACS, EconLit, and other databases were searched for studies employing epidemiological mathematical models of SARS-CoV-2 applied to real-world data. We summarized the information qualitatively, and each article included was assessed for bias risk using the Joanna Briggs Institute (JBI) and PROBAST checklist tool. The PROSPERO registration number is CRD42022344542. FINDINGS: In total, 5646 articles were retrieved, of which 411 were included. Most of the information was published in 2021. The countries with the highest number of studies were the United States, Canada, China, and the United Kingdom; no studies were found in low-income countries. The SEIR model (susceptible, exposed, infectious, and recovered) was the most frequently used approach, followed by agent-based modeling. Moreover, the most commonly used software were R, Matlab, and Python, with the most recurring health outcomes being death and recovery. According to the JBI assessment, 61.4% of articles were considered to have a low risk of bias. INTERPRETATION: The utilization of mathematical models increased following the onset of the SARS-CoV-2 pandemic. Stakeholders have begun to incorporate these analytical tools more extensively into public policy, enabling the construction of various scenarios for public health. This contribution adds value to informed decision-making. Therefore, understanding their advancements, strengths, and limitations is essential.

Detecting unexpected growths in health technologies expenditures: the case of MIPRES in Colombia.

We developed an algorithm to explore unexpected growth in the usage and costs of health technologies. We exploit data from the expenditures on technologies funded by the Colombian government under the compulsory insurance system, where all prescriptions for technologies not included in an explicit list must be registered in a centralized information system, covering the period from 2017 to 2022. The algorithm consists of two steps: an outlier detection method based on the density of the expenditures for selecting a first set of technologies to consider (39 technologies out of 106,957), and two anomaly detection models for time series to determine which insurance companies, health providers, and regions have the most notorious increases. We have found that most medicines associated with atypical behavior and significant monetary growth could be linked to the use of recently introduced drugs in the market. These drugs have valid patents and very specific clinical indications, often involving high-cost pharmacological treatments. The most relevant case is the Burosumab, approved in 2018 to treat a rare genetic disorder affecting skeletal growth. Secondly, there is clear evidence of anomalous increasing trend evolutions in the identified enteral nutritional support supplements or Food for Special Medical Purposes. The health system did not purchase these products before July 2021, but in 2022 they represented more than 500,000 USD per month.

Loss ratio of the capitation payment unit of the health-promoting entities in Colombia between 2017 and 2021: a financial-actuarial approach.

BACKGROUND: Because of a change of government, the Colombian Ministry of Health and Social Protection is in the process of presenting a structural reform for the General System of Social Security in Health (GSSSH), in order to implement a 'preventive and predictive health model'. However, it will always be relevant to review and analyze the fiscal implications of any proposed public policy program, to protect financial sustainability and to promote the better functioning of the system in question. METHODS: To contribute to this topic, we have calculated, using a financial-actuarial approach, the loss ratio for the years 2017 to 2021 for the Capitation Payment Unit (CPU) for all the Health-Promoting Entities (HPE) for both contributory and subsidized schemes. This information, derived from public reports available on the official website of the National Health Superintendency, allows us to estimate the financial burden of the institutions that guarantee access to and provision of health services and technologies in Colombia. RESULTS: The study shows that close to half of the HPEs in Colombia (which represent 11.6 million affiliates) have CPU loss ratios of more than 100% for the year 2021, evidencing insufficient resources for the operation of health insurance. CONCLUSIONS: Finally, we propose some policy recommendations regarding the strengthening of informed decision-making to allow the healthy financial sustainability of the Colombian GSSSH.

Vulnerability interactive geographic viewer against COVID-19 at the block level in Colombia: Analytical tool based on machine learning techniques.

To mitigate the effects of the coronavirus disease 2019 (COVID-19) pandemic, different countries have developed computational tools and dashboards that generate value for decision-making in public health. We aimed to build an interactive geographic viewer for vulnerability to COVID-19 at the block level in Colombia to identify the location of populations that, because of sociodemographic characteristics and health conditions, could have more complications from COVID-19 infections. The vulnerability levels of the different blocks of 1,102 municipal capitals were calculated. Additionally, the institutions that provide health services and hotels were georeferenced, and changes in people's mobility dynamics in large cities were identified.