A Review of Emergency and Disaster Management in the Process of Healthcare Operation Management for Improving Hospital Surgical Intake Capacity
Abstract
:1. Introduction
Terminology
2. A Mathematical Framework for Current OM Approaches
2.1. Number of ORs and Flexibility
2.2. Staffing Decisions
2.3. Optimal Block Sizes
2.4. OR Scheduling
2.5. Improving Schedules
2.6. Major Incident Situation Happened; How Do CCUS and Specialist Staff Act?
- (a)
- Capacity of a conventional response at least 20 percent greater than the baseline incentive care unit maximum;
- (b)
- Crisis response is able to expand via at least 200% above baseline incentive care unit max capacity via regional, local, national, and international agencies;
- (c)
- Ability to expand quickly in the event of an emergency by at least 100% above baseline incentive care unit maximum capacity by utilizing local and regional resources.
- -
- Vasopressor administration
- -
- Mechanical ventilation
- -
- Sedation and analgesia
- -
- If recommended by the hospital or a region, the best therapeutics and interventions, such as renal replacement therapy and nutrition for patients who cannot eat by mouth
- -
- IV fluid resuscitation
- -
- Antidote or antimicrobial administration for special disease processes, if applicable
- -
- Algorithms to decrease adverse consequences of critical care and critical illness.
- -
- Training and education of specialists and staff
- -
- A degree of equipment stockpiling or recognition of substitute resources (e.g., use of anesthetic ventilators to supply ventilatory support and NIV machines)
- -
- Recognition of specialists and staff via transferable skills like recovery nurses, respiratory nurses, and previous critical care nurses;
3. A Mathematical Framework for Emergency Departments (EDs)
- What factors can most effectively sculpt (even out) the demand for ED services?
- How can the ED service processes be improved? Improvement is measured with respect to certain performance metrics that we discuss in (Section 3.1).
- How can hospital managers ensure that there is an adequate supply of downstream beds for ED patients who may need additional hospital services?
3.1. ED Demand
- Balking-related metrics: include patients leaving without being seen (LWBS) and ambulance diversions [63].
- Capacity-related metrics: frequency of ED census approaching or exceeding the available ED beds or personnel capacity, the daily number of ED visits exceeding a targeted number, and ED nurses or physicians reporting being rushed [66].
3.2. ED Treatment Process
3.3. Downstream Bed Availability
4. OM Opportunities
5. Impact of Unit Size & Scope
5.1. The Impact of the Choice of Performance Metrics
5.2. The Impact of Patient Movement Policies
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Nomenclatures
A&E | Accident and Emergency |
ABM | Total Surgery Minutes |
ADT | Admission, discharge, and transfer system |
ANA | American Nurses Association |
BES | Block Efficiency Score |
CCDF | Complementary Cumulative Distribution Function |
CCU | Critical Care Unit |
CDF | Cumulative Distribution Function |
CMS | Centres for Medicare and Medicaid Services |
CQI | Clinical Quality Indicators |
EDs | Emergency Department |
EMTALA | Emergency Medical Treatment & Labor Act |
ESI | Emergency Severity Index |
FTE | Full-time equivalent |
GBD | The Global Burden of Disease Study |
ICU | Incentive Care Unit |
LOS | Length of Stay |
NDNQI | National Database of Nursing Quality Indicators |
NHPPD | Nursing Hours per Patient Day |
OM | Operations Management |
ORs | Operating Room |
OT | Overtime |
QED | Quality-in-Emergency-care-Dashboard |
SDS | Supply Demand Score |
TDABC | Time-driven activity-based costing |
TBM | Total in _ Block Minutes |
TSM | Total Surgery Minutes |
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Selected Day of Week | Shift Types | Shift Start Times | ||||||
---|---|---|---|---|---|---|---|---|
7:30 | 7:45 | 8:00 | 8:15 | 8:30 | 8: 45 | 9:00 | ||
Current | 8 h | 10 | n.a. | n.a. | n.a. | n.a. | n.a. | n.a. |
10 h | n.a. | n.a. | n.a. | n.a. | n.a. | n.a. | n.a. | |
12 h | 6 | n.a. | n.a. | n.a. | n.a. | n.a. | n.a. | |
Proposed | 8 h | 3 | n.a. | 3 | n.a. | n.a. | n.a. | 2 |
10 h | n.a. | n.a. | 1 | n.a. | 1 | n.a. | n.a. | |
12 h | n.a. | 1 | n.a. | n.a. | n.a. | n.a. | n.a. |
Service | DoW | n | B (min) | Initial Config | Revised Config | W (min) | A/W | Initial Unit | Revised Unit | |
---|---|---|---|---|---|---|---|---|---|---|
A | M | 49 | 2 | 900 | 7:30–15:00 7:30–15:00 | 7:30–12:00 7:30–18:00 | 46,588 | 0.95 | 55 | 66 |
A | T | 50 | 2 | 900 | 7:30–15:00 7:30–15:00 | 7:30–14:00 7:30–16:00 | 50,438 | 0.89 | 62 | 69 |
A | W | 51 | 2 | 900 | 7:30–15:00 7:30–15:00 | 7:30–13:45 7:30–16:15 | 46,115 | 1.00 | 53 | 65 |
A | TR | 50 | 2 | 1020 | 7:30–15:00 7:30–17:00 | 7:30–13:30 7:30–18:30 | 48,119 | 1.06 | 59 | 61 |
A | F | 49 | 2 | 900 | 7:30–15:00 7:30–15:00 | 7:30–13:30 7:30–16:30 | 47,134 | 0.94 | 53 | 61 |
B | F | 45 | 2 | 1020 | 7:30–16:00 8:30–17:00 | 7:30–15:00 7:30–17:00 | 28,620 | 1.60 | 49 | 51 |
C | M | 27 | 2 | 720 | 9:30–13:30 9:00–17:00 | 9:00–13:30 10:00–17:30 | 11,876 | 1.64 | 40 | 45 |
C | T | 34 | 2 | 720 | 9:00–17:00 11:00–15:00 | 9:00–17:00 10:30–14:30 | 14,946 | 1.64 | 40 | 50 |
ESI Level | Description |
---|---|
ESI Level 1 | The patient requires immediate life-saving intervention (1–3% of all ED patients) |
ESI Level 2 | The patient should not wait to be seen if they are in a high-risk situation, are confused, lethargic, or disoriented, or are in excruciating pain or distress (20–30% of all ED patients) |
ESI Level 3 | The patient is not Level 1 or Level 2, has vital signs within the accepted range for the patient’s age, and is predicted to require two or more resources, such as labs; diagnostic testing; intravenous fluids; intravenous, intramuscular or nebulized medications; specialty consultation; and/or a simple procedure or complex procedure (30–40% of all ED patients) |
ESI Level 4 | The patient has vital signs within the accepted range for the patient’s age and is predicted to use one resource. Levels 4 and 5 combined comprise 20–35% of all ED patients. Level 4 is an appropriate level to stream through the fast track. |
ESI Level 5 | The patient has vital signs within the accepted range for the patient’s age and is predicted to require no resources. Levels 4 and 5 combined comprise 20–35% of all ED patients. Level 5 is an appropriate level to stream through fast-track. |
QED Indicators ([63], p. 31), (CQI; United Kingdom) | CMS Indicators McHugh et al. ([67], p. 5), (United States) |
Time in the ED—% less than 4 h | The median patient time from ED arrival to ED departure for patients who were discharged |
% of patients with ED stay exceeding 6 h | Median time from ED arrival to ED departure for admitted patients |
Time for arrival to treatment by a decision-maker—% within 60 min or less | Door-to-diagnostic time, i.e., time to evaluation by a qualified medical professional |
% Left Without Being Seen | The patient left before being seen |
% Unplanned re-attendance to the ED within 7 days | No equivalent metric |
No equivalent metric | The average amount of time admitted patients spend between being accepted and leaving |
Time to initial assessment for patients arriving by ambulance—% less than 15 min | No equivalent metric |
Absentee Rate | Metric | Poisson LOS | Geometric LOS | ||
---|---|---|---|---|---|
Targeting | Static Priority | Targeting | Static Priority | ||
0% | Min OT/Shift | 0.83 | 0.95 | 0.54 | 0.61 |
# Unserved/Shift | 0.74 | 0.65 | 0.49 | 0.43 | |
Movement | 0.43 | 0.4 | 0.34 | 0.25 | |
10% | Min OT/Shift | 2.37 | 2.38 | 1.75 | 1.74 |
# Unserved/Shift | 1.17 | 1.21 | 0.86 | 0.92 | |
Movement | 0.75 | 0.49 | 0.87 | 0.57 | |
20% | Min OT/Shift | 4.22 | 4.18 | 3.53 | 3.48 |
# Unserved/Shift | 1.45 | 1.58 | 1.21 | 1.34 | |
Movement | 0.61 | 0.39 | 0.76 | 0.45 |
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Heydari, M.; Lai, K.K.; Fan, Y.; Li, X. A Review of Emergency and Disaster Management in the Process of Healthcare Operation Management for Improving Hospital Surgical Intake Capacity. Mathematics 2022, 10, 2784. https://doi.org/10.3390/math10152784
Heydari M, Lai KK, Fan Y, Li X. A Review of Emergency and Disaster Management in the Process of Healthcare Operation Management for Improving Hospital Surgical Intake Capacity. Mathematics. 2022; 10(15):2784. https://doi.org/10.3390/math10152784
Chicago/Turabian StyleHeydari, Mohammad, Kin Keung Lai, Yanan Fan, and Xiaoyang Li. 2022. "A Review of Emergency and Disaster Management in the Process of Healthcare Operation Management for Improving Hospital Surgical Intake Capacity" Mathematics 10, no. 15: 2784. https://doi.org/10.3390/math10152784