ArticleBMJ open2019
Real-time utilisation of administrative data in the ED to identify older patients at risk: development and validation of the Dynamic Silver Code.
Article in BMJ open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Epidemiology, Patients' Journey and Healthcare Costs in Early-Stage Non-Small-Cell Lung Carcinoma: A Real-World Evidence Analysis in Italy.Pharmaceuticals (Basel, Switzerland) · 2023Article
- COVID-19, Vulnerability, and Long-Term Mortality in Hospitalized and Nonhospitalized Older Persons.Journal of the American Medical Directors Association · 2022Article
- Identifying elderly patients at risk of readmission after discharge from a short-stay unit in the emergency department using performance-based tests of daily activities.BMC geriatrics · 2020Article
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveIdentification of older patients at risk, among those accessing the emergency department (ED), may support clinical decision-making. To this purpose, we developed and validated the Dynamic Silver Code (DSC), a score based on real-time linkage of administrative data. DESIGN AND
settingThe 'Silver Code National Project (SCNP)', a non-concurrent cohort study, was used for retrospective development and internal validation of the DSC. External validation was obtained in the 'Anziani in DEA (AIDEA)' concurrent cohort study, where the DSC was generated by the software routinely used in the ED.
participantsThe SCNP contained 281 321 records of 180 079 residents aged 75+ years from Tuscany and Lazio, Italy, admitted via the ED to Internal Medicine or Geriatrics units. The AIDEA study enrolled 4425 subjects aged 75+ years (5217 records) accessing two EDs in the area of Florence, Italy.
interventionsNone. OUTCOME MEASURES: Primary outcome: 1-year mortality. SECONDARY OUTCOMES: 7 and 30-day mortality and 1-year recurrent ED visits.
resultsAdvancing age, male gender, previous hospital admission, discharge diagnosis, time from discharge and polypharmacy predicted 1-year mortality and contributed to the DSC in the development subsample of the SCNP cohort. Based on score quartiles, participants were classified into low, medium, high and very high-risk classes. In the SCNP validation sample, mortality increased progressively from 144 to 367 per 1000 person-years, across DSC classes, with HR (95% CI) of 1.92 (1.85 to 1.99), 2.71 (2.61 to 2.81) and 5.40 (5.21 to 5.59) in class II, III and IV, respectively versus class I (p<0.001). Findings were similar in AIDEA, where the DSC predicted also recurrent ED visits in 1 year. In both databases, the DSC predicted 7 and 30-day mortality.
conclusionsThe DSC, based on administrative data available in real time, predicts prognosis of older patients and might improve their management in the ED.
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