There is no doubt that the coronavirus pandemic affected people’s lives and changed how businesses operate. But it has also popularized analytics concepts. There are public discussions of projection models and trends showing case volumes and other relevant metrics. The general public is even now more familiar with healthcare dashboards, as many refer to the popular Johns Hopkins COVID-19 dashboards and others.
While healthcare companies had no choice but to work in an uncertain environment, analytics teams have stepped up to meet the need for insight to help manage this crisis. They support healthcare leaders in planning and implementing effective strategies to respond to the challenges brought up by the pandemic without jeopardizing patient care.
We applaud these teams which often work behind the scenes and would like to mention just a few examples of how they contributed to healthcare operations during the coronavirus pandemic.
1- Helping monitor and manage COVID-19 cases
For executives to stay informed during this health crisis, data visualizations are necessary to identify where and how to step in to improve patient care. Analytics teams are helping keep the focus on COVID-19 patients by retooling existing dashboards and adding more data points to understand the status of the pandemic. Detailed and specific information related to the daily cases led to better reporting over time. Redefining healthcare KPIs was a must so that they would be more reliable and accurate by encompassing the number of cases, visits, death rates, discharges, and other related measures. This also means:
- Distinguishing Covid-19 patients from usual patients in existing reports/dashboards.
- Creating new reports/dashboards to highlight COVID-19 related activities.
- Modify report filters and parameters because new departments were created or allocated solely for COVID-19 purposes.
The uncertainties and challenges brought up by this crisis often demanded that reporting teams adopt agile responses to deliver actionable insight for protecting staff, improving quality of care, and making efficient management and financial decisions.
2- Monitoring testing and lab turnaround times
To help achieve service quality in terms of availability, cost, and timeliness, executives turned to analytics teams to:
- Monitor the number of tests done daily.
- Give recommendations to adjust the volume of tests done. For example, test only symptomatic people to decrease exposure and pressure and stress on laboratories and improve turnaround times.
- Monitor testing capacity.
- Track COVID-19 test supply availability.
This task is not easy because COVID-19 testing is occurring in new settings such as drive-thru centers, tents, and parking lots which complicates results’ mining.
3- Creating operational reports to manage supplies and bed capacity
PPE was at one point the only way healthcare workers could protect themselves from the virus. With the increased number of cases, healthcare organizations needed to manage these resources. Therefore, analytics teams have generated operational reports to understand the availability and usage of PPE(s):
- They made sure to follow the recommendations and guidelines given by the WHO in the usage of PPE.
- They helped manage PPE resources by providing reports that monitor the PPE utilization rates and assess potential for shortages.
In addition to PPE usage reports, analytics teams also provided critical operational reports to support discharge planning, hospital capacity management, and patient flow management. All contributed to an increase in COVID-19 bed availability.
4- Submitting COVID-19 related data to public agencies
Reporting case volumes to the CDC and other public agencies is a necessary initiative to keep the public informed and aware of any progress achieved. Healthcare organizations turned to analytics teams to:
- Assure collaboration with the public health organizations requirements
- Ensure timeliness and transparency of reporting
- Provide daily basis reporting to facilitate planning, monitoring, and resource allocation during the COVID-19 Public Health Emergency (PHE)
The reports prepared showed hospital capacity. Some of the reported data include hospital bed occupancy, mechanical ventilators usage, confirmed positive COVID-19 cases, E/D overflow, and PPE usage.
5- Helping hospital administration teams monitor business recovery efforts
As reopening allowed for increased access to outpatient clinics and other hospital services, tracking revenue recovery is needed. Analytics teams develop dashboards that encompass financial metrics such as margins, cost savings, and other related metrics that could help executives monitor and set new target recovery revenue strategies. As we all know, COVID-19 pandemic enabled new ways to care for patients that organizations must adapt to and survive without compromising profit. Therefore, analytic teams empowered executives with analytics for a smoother pivot, monitoring and adoption of online and Telehealth services.
6- Predicting the location and volume of cases
Data scientists created dynamic models to adapt to the unforeseen effects of this crisis with quantitative projections that assisted in the planning and allocation of resources. Some of the challenges they had to overcome while applying advanced analytics during this pandemic include:
- Availability of data - pertinent data was not necessarily available due to the unexpected nature of what should be trekked and how fast changes were occurring
- Being constrained by what is known vs. assumptions - number of confirmed vs. suspected cases
- Uncertainty or variability in data - for example, the duration of infection varies from one person to another
We applaud analytics teams that have served and continue to perform behind the scenes to provide the insight needed to manage the current public health crisis. As tragic as the pandemic is, it does highlight how critical it is to deliver the right insight at the right time. It can not only help healthcare run more efficiently, but also save lives.