Table 1.
Characteristics of included studies.
| First author | Publication year | Country | Mean/median age (years) | Centers | Alert sending | Sample size | Population | Setting | Design | Method | Clinical intervention |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Downey | 2018 | UK | 65.2 | Single | Nurse | 226 | Surgical wards | Wards | RCT | rule-based | sepsis alert |
| Downing | 2019 | USA | 63 | Single | Physician and nurse | 1123 | wards and stepdown unit | Wards | RCT | rule-based | severe sepsis alert |
| Hooper | 2012 | USA | 55 vs. 54 | Single | Physician | 442 | modified SIRS | ICU | RCT | rule-based | sepsis alert |
| Shimabukuro | 2017 | USA | 59.3 vs. 58.9 | Single | Physician | 142 | adult ICU patients | ICU | RCT | ML-based | severe sepsis alert |
| Semler | 2015 | USA | 57 vs. 55 | Single | ICU resident physician or nurse practitioner | 407 | ICU sepsis | ICU | RCT | rule-based | bundle implementation |
| Tarabichi | 2021 | USA | Single | Pharmacist | 598 | ED adult | ED | RCT | rule-based | sepsis alert | |
| Arabi | 2017 | Saudi Arabia | NA | Single | Nurse | 1330 | sepsis or septic shock | ED | NRS | rule-based | bundle implementation |
| Austrian | 2018 | USA | 67.1 | Single | Nurse | 2144 | Hospitalized patients | Wards | NRS | rule-based | sepsis alert |
| Bader | 2020 | Jordan | NA | Single | Nurse | 168 | ED patients with cancer and sepsis | ED | NRS | rule-based | sepsis alert |
| Benson | 2014 | USA | 59.8 vs. 60.1 | Single | Nurse | 239 | SIRS patients | Wards | NRS | rule-based | sepsis alert |
| Berger | 2010 | USA | 42.2 vs. 42.4 | Single | NA | 5796 | ED adult | ED | NRS | rule-based | severe sepsis alert |
| Burdick | 2020 | USA | 45 | Multiple | Provider | 17758 | Sepsis-related patients | Wards | NRS | ML-based | severe sepsis alert |
| Manaktala | 2017 | USA | 64 vs. 63 | Single | Nurse | 7388 | Hospitalized patients | Wards | NRS | rule-based | sepsis alert |
| Mathews | 2014 | USA | NA | Single | NA | 2109 | Sepsis-related patients | Wards | NRS | rule-based | severe sepsis alert |
| McRee | 2014 | USA | 70.5 vs. 69.9 | Single | Nurse | 171 | Sepsis-related patients | Wards | NRS | rule-based | sepsis alert |
| McCoy | 2017 | USA | NA | Single | NA | 1328 | Hospitalized patients | Wards | NRS | ML-based | sepsis alert |
| Croft | 2014 | USA | NA | Single | Physician or extender | 184 | Surgical ICU | ICU | NRS | rule-based | bundle implementation |
| Gatewood | 2015 | USA | NA | Single | Provider | 642 | ED adult | ED | NRS | rule-based | sepsis alert |
| Ferreras | 2015 | Spain | 77.6 vs. 75.5 | Single | Nurse | 433 | Sepsis-related patients | ED | NRS | rule-based | sepsis alert |
| Giannini | 2019 | USA | 58.5 vs. 58.7 | Single | Covering care team | 3677 | non-ICU admissions | Wards | NRS | ML-based | severe sepsis alert |
| Guirgis | 2017 | USA | 57.3 vs. 57.1 | Single | Provider | 3917 | Hospitalized patients | Wards | NRS | rule-based | sepsis alert |
| Hayden | 2016 | USA | 55 vs. 56 | Single | Physician | 238 | Sepsis-related patients | ED | NRS | rule-based | bundle implementation |
| Honeyford | 2020 | UK | NA | Single | Doctors and nurses | 21183 | Sepsis-related patients | ED | NRS | rule-based | bundle implementation |
| Idrees | 2016 | Australia | 58 vs. 59 | Single | NA | 90 | sepsis or septic shock | ICU | NRS | rule-based | sepsis alert |
| Jung | 2018 | USA | 54.7 vs. 50.6 | Single | Physician and nurse | 30 | Sepsis | ICU | NRS | rule-based | Sepsis-alert |
| Lipatov | 2022 | USA | 66.2 vs. 66.7 | Single | NA | 1950 | MICU sepsis | ICU | NRS | rule-based | bundle implementation |
| Machado | 2018 | USA | 68.5 vs. 67.7 | Single | Physician, nurse, X-ray technician and pharmacist | 314 | ED patients with suspected sepsis | ED | NRS | rule-based | sepsis alert |
| Moore | 2019 | USA | NA | Single | Physician | 312 | ED patients with sepsis | ED | NRS | rule-based | bundle implementation |
| Na | 2021 | Korea | 62 vs. 62 | Single | Provider | 1596 | Hospitalized patients | Wards | NRS | rule-based | sepsis alert |
| Narayanan | 2016 | USA | 66.7 vs. 67.1 | Single | Provider | 214 | ED adult | ED | NRS | rule-based | severe sepsis alert |
| Sawyer | 2011 | USA | 52.6 vs. 50.4 | Single | Provider | 270 | Sepsis-related patients | Wards | NRS | rule-based | sepsis alert |
| Song | 2019 | Korea | 74 vs. 77 | Single | Nurse | 631 | ED patients with qSOFA>2 | ED | NRS | rule-based | bundle implementation |
| Shah | 2018 | USA | 61.5 vs. 67 | Single | Physician | 115 | ED patients with sepsis | ED | NRS | rule-based | sepsis alert |
| Threatt | 2020 | USA | NA | Single | Physician | 310 | ED patients with sepsis | ED | NRS | rule-based | bundle implementation |
| Umscheid | 2015 | USA | 62 vs. 59.7 | Multiple | covering provider and rapid response coordinator | 1140 | non-ICU patients | Wards | NRS | rule-based | severe sepsis alert |
| Westra | 2017 | USA | 64.1 vs. 62.7 | Single | Nurse | 778 | Hospitalized patients | Wards | NRS | rule-based | sepsis alert |
ED emergency department, ICU intensive care unit, ML machine learning, SIRS systematic inflammatory response syndrome, qSOFA quick sequential organ failure assessment, NRS non-randomized study.