COVID Staffing
As the threat of ongoing surges of COVID-19 in U.S. continues, a variety of interventions will be required to meet the demand for critical care resources. To determine the ability to meet these demands, we explored the intersection of critical care bed (CCB) capacity and staffing availability in U.S. counties.
Objectives
The model described here aims to provide decision support to stakeholders attempting to minimise the unmet demand for COVID-19 critical care. Optimal reallocation of nurses and physicians within their current state of employement and within 250 miles of the border of the county of employment was estimated. Active constraints (critical care beds, nurse staffing, and/or physician staffing), along with slack or excess for each resource was also identified.
Assumptions
Critical Care Demand 1-5
Demand for critical care beds, as well as projected COVID-19 cases, for US counties were estimated using an adaptive meta-population SEIR model published previously. The estimates are updated regularly and provide projects for up to six weeks from the date of the date of publication.5 For the purposes of this model and planning tool, two week projections are used.
Occupancy 6
ICU occupancy was estimated using the CMS Medicare Hospital Cost Report.
Total number of ICU patient days / 365Occupied beds remain occupied
Remaining beds available for COVID-19 patients
Beds 5,7
Critical care beds (CCBs) were calculated using:
- ● Intensive care unit (ICU) beds
- ● Operating room (OR) beds (1 bed: 1 OR)
- ● Post-anesthesia care unit (PACU) beds (1.5 PACU beds: 1 OR)
- ● Step-down beds (1 step-down bed: 4 ICU beds)
- ● Long-term acute care (LTAC) beds.
CCB counts were summed at the county level for all US civilian hospitals including long-term acute care facilities. The highest, reasonable ICU bed count reported by each hospital was used.
Four Surge Scenarios 8-13
| Scenario | Baseline (Conventional) | Moderate | Contingency | Crisis |
|---|---|---|---|---|
| Critical Care Beds | All hospital ICU beds except NICU | All hospital ICU beds except NICU | All hospital ICU beds except NICU | All hospital ICU beds except NICU + OR, PACU, & LTAC |
| Nursing Ratios | 2 Critical care beds / nurse | 3 Critical care beds / nurse | 5 Critical care beds / nurse | 6 Critical care beds / nurse |
| Nursing Staffing | 15% of full-time RNs + 15% of part-time RNs | 15% of full-time RNs + 15% of part-time RNs | 15% of full-time RNs + 15% of part-time RNs | 15% of full-time RNs + 15% of part-time RNs |
| Physician Ratios | 7 Critical care beds / intensivist | 10 Critical care beds / physician * | 12 Critical care beds / physician * | 12 Critical care beds / physician * |
| Physician Staffing* | 100% of Intensivists | 100% of Intensivists + 45% of Medical/Surgical Specialists** | 100% of Intensivists + 45% of Medical/Surgical Specialists** | 100% of Intensivists + 45% of Medical/Surgical Specialists** |
| Advanced Practice Practitioners* | 12% of Nurse Practitioners + 1.4% of Physician Assistants + 50% of Certified Registered Nurse Anesthetists | 12% of Nurse Practitioners + 1.4% of Physician Assistants + 50% of Certified Registered Nurse Anesthetists | 12% of Nurse Practitioners + 1.4% of Physician Assistants + 50% of Certified Registered Nurse Anesthetists | 12% of Nurse Practitioners + 1.4% of Physician Assistants + 50% of Certified Registered Nurse Anesthetists |
*Advanced Practice Practitioners (APP) count as physician extenders with each APP counting as 0.5 physicians
**Counts include 30% of Cardiovascular disease, gastroenterology, geriatrics, internal medicine, infectious disease, interventional cardiology, nephrology, neurology, pediatric cardiology, pediatrics, pulmonology, urology, surgeons, and anesthesiologists
Model
A single linear optimization model was developed and solved using the revised simplex method. It aims to minimise unmet demand for COVID-19 critical care through an optimal combination of (i) redistribution of nurses and physicians within each state (limited to a maximum distance of 250 miles) and (ii) provision of additional emergency CCB capacity and critical care staff. This model can provide decision support to stakeholders by directly suggesting the optimal interventions.
COVID Staffing
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