Background The COVID-19 pandemic has turned the care model of health systems around the world upside down, causing the abrupt cancellation of face-to-face visits and redirection of the model toward telemedicine. Digital transformation boosts information systems—the more robust they are, the easier it is to monitor the health care system in a highly complex state and allow for more agile and reliable analysis. Objective The purpose of this study was to analyze diagnoses from primary care visits and distinguish between those that had higher and lower variations, relative to the 2019 and 2020 periods (roughly before and during COVID-19), to identify clinical profiles that may have been most impaired from the least-used diagnostic codes for visits during the pandemic. Methods We used a database from the Primary Care Services Information Technologies Information System of Catalonia. We analyzed the register of visits (n=2,824,185) and their International Classification of Diseases (ICD-10) diagnostic codes (n=3,921,974; mean 1.38 per visit), as approximations of the reasons for consultations, at 3 different grouping levels. The data were represented by a term frequency matrix and analyzed recursively in different partitions aggregated according to date. Results The increase in non–face-to-face visits (+267%) did not counterbalance the decrease in face-to-face visits (–47%), with an overall reduction in the total number of visits of 1.36%, despite the notable increase in nursing visits (10.54%). The largest increases in 2020 were visits with diagnoses related to COVID-19 (ICD-10 codes Z20-Z29: 2.540%), along with codes related to economic and housing problems (ICD-10 codes Z55-Z65: 44.40%). Visits with most of the other diagnostic codes decreased in 2020 relative to those in 2019. The largest reductions were chronic pathologies such as arterial hypertension (ICD-10 codes I10-I16: –32.73%) or diabetes (ICD-10 codes E08-E13: –21.13%), but also obesity (E65-E68: –48.58%) and bodily injuries (ICD-10 code T14: –33.70%). Visits with mental health–related diagnostic codes decreased, but the decrease was less than the average decrease. There was a decrease in consultations—for children, adolescents, and adults—for respiratory infections (ICD-10 codes J00-J06: –40.96%). The results show large year-on-year variations (in absolute terms, an average of 12%), which is representative of the strong shock to the health system. Conclusions The disruption in the primary care model in Catalonia has led to an explosive increase in the number of non–face-to-face visits. There has been a reduction in the number of visits for diagnoses related to chronic pathologies, respiratory infections, obesity, and bodily injuries. Instead, visits for diagnoses related to socioeconomic and housing problems have increased, which emphasizes the importance of social determinants of health in the context of this pandemic. Big data analytics with routine care data yield findings that are consistent with those derived from intuition in everyday clinical practice and can help inform decision making by health planners in order to use the next few years to focus on the least-treated diseases during the COVID-19 pandemic.

The epidemiological situation generated by COVID-19 has highlighted the importance of applying non-pharmacological measures. Among these, mass screening of the asymptomatic general population has been established as a priority strategy by carrying out diagnostic tests to limit the spread of the virus. In this article, we aim to evaluate the economic impact of mass COVID-19 screenings of an asymptomatic population through a Cost-Benefit Analysis based on the estimated total costs of mass screening versus health gains and associated health costs avoided. Excluding the value of monetized health, the Benefit-Cost ratio was estimated at approximately 0.45. However, if monetized health is included in the calculation, the ratio is close to 1.20. The monetization of health is the critical element that tips the scales in favour of the desirability of screening. Screenings with the highest return are those that maximize the percentage of positives detected.

Background: The epidemiological situation generated by COVID-19 has highlighted the importance of applying non-pharmacological measures in the management of the epidemic. Mass screening of the asymptomatic general population has been established as a priority strategy by carrying out diagnostic tests to detect possible cases, isolate contacts, cut transmission chains and thus limit the spread of the virus. Objective: To evaluate the economic impact of mass COVID-19 screenings of an asymptomatic population during the first and second wave of the epidemic in Catalonia, Spain. Methodology: Cost-Benefit Analysis based on the estimated total costs of mass screening versus health gains and associated health costs avoided. Results: Excluding the value of monetized health, the Benefit-Cost ratio was estimated at 0.45, a low value that would seem to advise against mass screening policies. However, if monetized health is included, the ratio is close to 1.20, reversing the interpretation. In other words, the monetization of health is the critical element that tips the scales in favour of the desirability of screening. Results show that the interventions with the highest return are those that maximize the percentage of positives detected. Conclusion: Efficient management of resources for the policy of mass screening in asymptomatic populations can generate high social returns. The positivity rate critically determines its desirability. Likewise, precocity in the detection of cases will cut more transmissions in the chain of contagion and increase the economic return of these interventions. Maximizing the value of resources depends on screening strategies being accompanied by contact-tracing and specific in their focus, targeting, for example, high-risk subpopulations with the highest rate of expected positives.

Background: The epidemiological situation generated by COVID-19 has cast into sharp relief the delicate balance between public health priorities and the economy, with businesses obliged to toe the line between employee health and continued production. In an effort to detect as many cases as possible, isolate contacts, cut transmission chains, and limit the spread of the virus in the workplace, mass testing strategies have been implemented in both public health and industrial contexts to minimize the risk of disruption in activity. Objective: To evaluate the economic impact of the mass workplace testing strategy as carried out by a large automotive company in Catalonia in terms of health and healthcare resource savings. Methodology: Analysis of health costs and impacts based on the estimation of the mortality and morbidity avoided because of screening, and the resulting savings in healthcare costs. Results: The economic impact of the mass workplace testing strategies (using both PCR and RAT tests) was approximately €10.44 per test performed or €5575.49 per positive detected; 38% of this figure corresponds to savings derived from better use of health resources (hospital beds, ICU beds, and follow-up of infected cases), while the remaining 62% corresponds to improved health rates due to the avoided morbidity and mortality. In scenarios with higher positivity rates and a greater impact of the infection on health and the use of health resources, these results could be up to ten times higher (€130.24 per test performed or €69,565.59 per positive detected). Conclusion: In the context of COVID-19, preventive actions carried out by the private sector to safeguard industrial production also have concomitant public benefits in the form of savings in healthcare costs. Thus, governmental bodies need to recognize the value of implementing such strategies in private settings and facilitate them through, for example, subsidies.