Table 3 Indicators used in the model
From: Operations management solutions to improve ED patient flows: evidence from the Italian NHS
Indicator | Variable Meaning | Source |
|---|---|---|
ED Input | ||
Share of vulnerable population (age > = 75 years) per day | Elderly individuals need more intensive services, and consequently, a higher share of patients over 75 years of age should be correlated with higher ED | ED database |
Share of red codes above average per daya | Red codes require immediate attention from all ED team members | ED database |
Number of admissions | This represents the workload level in the ED | ED database |
Share of red and yellow codes above average per daya | This is the daily share of major codes (red and yellow) that require more intensive care | ED database |
ED Process | ||
ED endowment | ||
ED type | This represents, in a three-scale variable, the endowment of technology and diagnostic equipment of each single hospital | Semistructured interview |
Number of doctors per admission | This represents the quantitative level of medical staff | Semistructured interview |
Number of nurses per admission | This represents the quantitative level of nursing staff | Semistructured interview |
Skill mix (number of doctors/number of nurses) | This represents the type of organizational model in terms of skill mix for nurses vs. physicians | Semistructured interview |
Visual management software | This is the availability of real time information on hospital bed occupancy | Semistructured interview |
ED flow separation | ||
Ambulatory for minor codesa | This refers to the outpatient setting managed by primary care doctors dedicated to white codes | Semistructured interview |
See and treat | This refers to the outpatient setting managed by nurses for the treatment of minor pathologies | Semistructured interview |
Fast track | This refers to direct access to outpatient specialties for specific clinical conditions | Semistructured interview |
ED Output | ||
ED hospital admissions | This is the number of patients who require hospital admission after ED visits | Hospital discharge database |
ED hospital admissions/Medicine ward | This is the number of patients admitted to the hospital in the medical ward from the ED | Hospital discharge database |
ED hospital admissions/Emergency ward | This is the number of patients admitted to the hospital in the emergency medicine ward from the ED | Hospital discharge database |
ED hospital admissions/Surgery ward | This is the number of patients admitted to the hospital in the surgical ward from the ED | Hospital discharge database |
“In and out” rate | This is the daily difference between the number of admissions and of discharges | Hospital discharge database |
Bed manager | This refers to the availability of a team in charge of coordinating patient flows between the ED and hospital wards | Semistructured interview |
Hospital | ||
Hospital ownership | This can be private vs. public | Semistructured interview |
Geographical context | This can be urban vs. rural | Semistructured interview |
Hospital dimension | This can be the number of beds | Semistructured interview |
Hospital case mix of production | This can be the number of medical vs. surgical patients | Hospital discharge database |
Hospital organization model | This can be process- vs. specialty-based hospitals | Semistructured interview |
Surgical capacity | This refers to the number of operating rooms | Semistructured interview |