Code for COVID: A model to inform ICU and ventilator usage in Mexican hospitals

Link to model and Tableau dashboard: https://codeforcovid.shinyapps.io

COVID-19 has been rapidly spreading in Mexico, straining the capacity of health care systems to respond and save lives. The number of cases, hospitalizations, ICU utilization and deaths are rising in Mexican states and municipalities. In response, healthcare organizations and communities are increasingly acting to design strategies to proactively protect inpatient resource consumption and mitigate the burden by planning resource utilization and flexing health workforce. Strategies to maximize the current health workforce include planning for complex critical care including ICU and ventilation equipment. Hospitals also are transitioning to “surge capacity” or “flex staffing” by redeploying health workers to high-need areas.

Managing hospital resource consumption and workforce load during SARS-CoV-2 pandemic is especially critical in Mexico where there is evidence that infection rates are higher for healthcare workers than in countries. In addition to the cost of inpatient treatment due to more complex care, workforce load management and availability of ICU resources must be planned for and put into place in an agile manner as seasonal impact of this disease is relatively unknown. Much of the focus has been on intensive care, acute care, and emergency department capacity of hospitals, which are all critical areas in caring for moderate and severe cases. In addition, community health care providers—primary care, specialty care, pharmacies, skilled nursing facilities, mental health, and many others—are essential during this pandemic. To maintain health care service levels for the more complex inpatient cases requires early identification of those at most at risk for ICU care and intubation for extended lengths of stay.

Whilst the impact of comorbidities and age on mortality for this disease is documented in Mexico, the utilization rates for ICU admission and ventilation by demographic and comorbidity is not well-known. A thorough assessment of comorbidities may help establish risk stratification of patients with Covid-19 upon hospital admission so that hospital operations management can plan for resource and workforce load.

Our analysis looks at the probability of ICU admission and ventilation use for comorbidity by state and municipality. The objective of our study is to define parameters to identify those patients at highest risk for ICU admission and intubation. Having access to this information upon admission will enable hospitals to be more agile in securing resource to treat the more severe cases of SARS-CoV-2.