Italia · Pronto Soccorso
Sovraffollamento in Pronto Soccorso: l'evidenza italiana, in un cruscotto
Una sintesi strutturata degli studi italiani su sovraffollamento, flusso dei pazienti e sicurezza — con un'interfaccia dedicata che pesa il blocco a valle (bed management, OBI, See-and-Treat) come indicano Marsilio/Villa e la survey SIMEU, e affianca l'indice EDWIN al NEDOCS.
A structured digest of Italian ED-overcrowding research with an Italy-specific modelling tool — reweighting the output/admission dimension and organisational levers.
20
studi italiani sintetizzati
4
aree tematiche
2011–2026
arco temporale
~30%
ospedali con Bed Manager (SIMEU 2017)
Cruscotto italiano · demo interattiva
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Modella e traccia il tuo Pronto Soccorso
Sposta i cursori per descrivere un turno. Il NEDOCS resta lo standard, ma qui affianchiamo l'indice EDWIN (che negli studi italiani ha seguito meglio i picchi COVID) e un Indice Operativo Italiano che ripartisce la pressione tra le dimensioni input · processo · output secondo le quote di varianza di Marsilio/Villa (2022). Le leve organizzative modificano pesi e parametri.
Parti da un turno tipo
Variabili NEDOCS
Case mix & risorse (contesto italiano)
Il sovraffollamento peggiora al crescere dell'età media (Marsilio/Villa).
Potenzialmente eleggibili a See-and-Treat / Fast Track.
Usato nel denominatore dell'EDWIN.
Leve organizzative — modificano pesi e parametri
NEDOCS
72
Busy
Formula di Weiss et al. 2004 — lo standard 0–200.
EDWIN
1.6
Occupato
Σ(nᵢ·tᵢ) / [Na·(letti − ricoveri)]. Soglia sovraffollamento ≈ 2.
Indice Operativo IT
54
Pressione media
Input · processo · output pesati (Marsilio/Villa 2022), 0–100.
Indice Operativo Italiano — scomposizione per dimensione
54
−0 punti dalle leve
Grezzo (senza leve): 54
Lettura del turno (anteprima euristica)
Generata dai valori a sinistra.
Solo conteggi operativi — nessun dato personale (PHI). Seguire le procedure aziendali e il giudizio clinico.
Traccia questi dati per il tuo PS
Attiviamo la tua struttura con NEDOCS + EDWIN, le leve organizzative italiane e lo storico dei turni. Inserimento manuale — nessun feed EHR richiesto.
Nota metodologica. L'Indice Operativo Italiano è uno strumento illustrativo, non un punteggio validato. Ripartisce la pressione tra le tre dimensioni del modello di Asplin usando come pesi le quote normalizzate di varianza dell'ED-LOS riportate da Marsilio, Roldan, Salmasi & Villa (BMC HSR 2022): output/gestione ricoveri ≈ 0,57, processo/dotazione PS ≈ 0,24, input/arrivi ≈ 0,19. Le leve organizzative attenuano i parametri delle dimensioni corrispondenti (es. il Bed Manager riduce la componente output, coerentemente con la riduzione del sovraffollamento dal 26,6% al 17,9% osservata nella revisione sul bed management). NEDOCS ed EDWIN sono calcolati con le formule pubblicate.
Digest dell'evidenza
Studi italiani su sovraffollamento, flusso e sicurezza
Sintesi parafrasate da full-text open-access e abstract. Per tabelle e metodi verbatim, consultare gli originali ai DOI/link indicati. I preprint e le sedi non indicizzate sono segnalati.
1. Emergency department overcrowding — causes, measurement, and organization
Italian evidence on why EDs crowd, how it is measured, and how services are organised around the input–process–output model of crowding.
Operations management solutions to improve ED patient flows: evidence from the Italian NHS
Marsilio M, Roldan ET, Salmasi L, Villa S.
Mixed-method, three-phase sequential exploratory study built on Asplin's input–process–output model; two focus groups with operations-management professionals from 10 Italian hospitals and regression on full-year 2018 ED and discharge records (PCA + Shapley Value Decomposition).
- The three model dimensions together explained ~77–80% of ED length-of-stay (LOS) variability.
- The output / admission-management dimension was dominant (30.3%, 60.4% and 15.9% of explained variance across three subsamples); number of admissions and presence of a bed manager were the strongest levers (bed manager alone up to 35.6% in the admitted subsample).
- The process / ED-endowment dimension was second (~13%), driven mainly by nurses per shift; the input dimension (~10%) by admissions, case mix and elderly patients.
- Crowding worsened as mean patient age rose; a higher physician-to-nurse ratio correlated positively with ED-LOS (doctor-heavy EDs front-load work before admission).
- Levers: dedicated pathways for fragile/elderly patients; capacity planning around demand peaks (arrivals peak 8–10 a.m., Mondays busiest); skill-mix (scribes, social workers); an admissions buffer ward; a real-time bed-management office; earlier discharges. Italian EDs were already at maximum capacity just before COVID-19.
DOI 10.1186/s12913-022-08339-x · Open access (CC BY)
Overcrowding in Italian EDs: the "Settimana Nazionale del Pronto Soccorso 2017" SIMEU survey
Caporaletti P, Maragno M, Cosi M, et al.
National SIMEU survey (1 Mar–30 Apr 2017) of 219 facilities across all 20 regions (~33% of Italian EDs); reference volume 10,072,924 patients in 2016.
- Bed Manager present in only 30% of hospitals (50% of 2nd-level, 28% of 1st-level, 13% of First Aid points).
- Holding area in 21% of EDs — mostly staffed by emergency physicians; an inappropriate but common workaround.
- Only 45% of hospitals knew real-time bed availability; only 24% had ED-dedicated beds daily; 80% perceived required admissions as exceeding allocated beds.
- 56% knew regional overcrowding guidelines; 47% had an Overcrowding Management Plan, applied in only 39%.
- Short-observation units (OBI) in 84% of EDs; post-triage nursing paths in 67%; Fast Track in 49%; dedicated chronic/long-term pathways in only 8%.
- Only 22% used a validated overcrowding tool (e.g. NEDOCS), limiting cross-site comparison.
DOI 10.23832/ITJEM.2018.036
Overcrowding at a large Turin ED: driven by access block, not inappropriate use
San Giovanni Battista (Molinette) University Hospital, Turin
Study verifying whether overcrowding at a large Turin ED is driven by restricted access to inpatient beds rather than inappropriate patient use.
- Confirmed overcrowding at the ED.
- The main cause was a shortage of available hospital beds producing extended ED stays for patients needing emergency admission — not inappropriate ED use.
- An early, frequently-cited Italian statement of the access-block / boarding thesis.
PubMed ID 22508607
Do health-care professionals' perceptions measure ED overcrowding? Pilot at Ferrara
Strada A, Bravi F, Valpiani G, Bentivegna R, Carradori T.
Single-centre prospective observational pilot (S. Anna University Hospital of Ferrara, 19 Feb–7 Mar 2018) comparing staff perception of crowding against the NEDOCS objective score (Cohen's weighted kappa).
- Tested whether frontline perception tracks a validated objective measure, and catalogued local tools (case management, flow manager).
- Frames perception as a possible complementary monitoring signal alongside NEDOCS.
DOI 10.1186/s12873-019-0259-9
Overcrowding analysis through indices: single-centre study
Colella Y, Di Laura D, Borrelli A, Triassi M, Amato F, Improta G.
Compared two crowding indices — EDWIN and NEDOCS — around Italy's first COVID lockdown (declared 9 Mar 2020), using Pearson correlation.
- EDWIN tracked the lockdown pattern (most congested 8:00–20:00, peaks 8:00–12:00); NEDOCS did not and was judged less reliable in this setting.
- Pearson r between the two indices was only 0.317 — they diverge substantially.
DOI 10.1186/s12873-022-00735-0
A case study on the impact of overcrowding indices in EDs
Improta G, Majolo M, Raiola E, Russo G, Longo G, Triassi M.
Companion Naples analysis evaluating ED overcrowding-evaluation indices (NEDOCS, EDWIN).
- Reinforces the methodological theme: index choice materially affects whether crowding is detected.
DOI 10.1186/s12873-022-00703-8
ED overcrowding: retrospective spatial analysis & geocoding — pilot in Rome
ISPRS International Journal of Geo-Information (Policlinico Umberto I, Rome)
GIS/geocoding of ED attendances at Policlinico Umberto I (Lazio) to map where inappropriate 'white code' (non-urgent) visits originate.
- Identifies city sectors amplifying ED demand so triage/territorial interventions can target them — a supply-and-demand, public-health-geography angle on crowding.
MDPI 2020;9(10):579
Overcrowding in EDs: strategies and solutions for effective reorganization (narrative review)
Italian Journal of Medicine (ED, AUSL Umbria1, Gubbio/Gualdo Tadino)
Narrative review of the main critical issues inside Italian EDs and the highest-impact strategies.
- Situated against Ministry of Health input and regional projects aimed at cutting waiting times and streamlining the diagnostic–therapeutic pathway.
DOI 10.4081/itjm.2024.1714
2. Patient throughput, flow, and bed management
Evidence on hospital-wide flow, the Bed Manager role, and nurse-led protocols that move non-emergency patients out of the main ED stream.
A framework to analyze hospital-wide patient flow logistics: an Italian comparative study
Villa S, Prenestini A, Giusepi I.
Comparative study of six Italian hospitals developing a three-level framework — hospital, 'pipelines' (patient journeys), and production units (e.g. ORs).
- The dominant driver of patient-flow problems was not shortage of capacity but flow variability caused by inadequate allocation of capacity.
- A foundational Italian reference for the system-wide (rather than single-unit) view of flow.
The impact of bed management models on hospital performance and patient flow: a systematic review
Altavilla S, et al.
Systematic review (PubMed, CINAHL, Scopus; English + Italian; 2005–2025) of explicit bed-management interventions and the Bed Manager role; seven studies, mostly observational pre–post.
⚠ Preprint — verify peer-review status before formal citation.
- Active bed management cut ED-LOS by up to 98 minutes and overcrowding from 26.6% to 17.9%.
- A logistics-management program cut ED evaluation time from 219 to 193 minutes (p<0.001) across 28,684 admissions and trimmed inpatient LOS by 0.1 days.
- A flow/bed manager absorbed a 22% rise in urgent admissions without raising mean LOS; digital/centralized systems reduced bed turnover time from 111 to 49 minutes.
- Caveat: non-randomized designs dominate; multicentre studies with standardized KPIs and safety measures are still needed.
Improving ED efficiency through integrated bed management & radiology workflow
Tatò E, Guglielmi G, et al. ("Dimiccoli" Teaching Hospital, Barletta)
Organizational intervention study implementing a model to improve patient flow, hospital bed turnover, and radiology workflow in the ED.
- Positions inefficient bed management and imaging delays as central, modifiable contributors to ED congestion.
Bed management in Italy: modelling strategic and organizational change
Landa P, et al.
Discusses the relatively recent adoption of the Bed Manager role in Italian public hospitals under budget constraints.
- Models how bed management supports patient flow across integrated pathways.
"See-and-Treat" protocol impact on patient flow
Sassuolo Hospital ED (Northern Italy)
Modelling study estimating the potential impact of a nurse-led See-and-Treat protocol on eligible minor-code patients, using all minor access codes from 2022 (home-discharged; excluding specialist / Fast-Track needs).
- Frames nurse-independent protocols to manage non-emergency patients outside the main ED stream — reducing crowding, delayed treatment, and cost.
S1755-599X(24)00164-2
Diagnostic anticipation to reduce ED length of stay
Ferrara University Hospital
Retrospective cohort testing whether 'diagnostic anticipation' (ordering tests earlier, at triage) shortens ED-LOS; crowding quantified with the NEDOCS score auto-calculated hourly (the tool used in Emilia-Romagna); multiple regression adjusted for age, sex, priority code, consultations, imaging.
- A throughput intervention aimed at the process phase of the input–process–output model.
3. Length of stay, boarding, and mortality outcomes
Italian cohorts examining whether ED length of stay and overnight boarding are independently associated with mortality.
Overnight stay in the ED and in-hospital mortality among elderly patients: 6-year study (Forlì)
Fabbri A, Tascioglu AB, Bertini F, Montesi D.
Monocentric retrospective study (Morgagni-Pierantoni Hospital, Forlì) of patients ≥75 needing urgent hospitalization, 2017–2022; ED-overnight-stay (EDOS) group vs Ward group; primary outcome 30-day in-hospital mortality.
- 20,009 patients (median age 85); EDOS group 3,064 (15.3%), Ward group 16,945 (84.7%).
- In-hospital mortality in 3,020 (15.1%), with no significant difference between groups — an ED overnight wait for a ward bed was not independently associated with higher mortality in this elderly cohort.
DOI 10.3390/jcm14092879
Machine-learning prediction of prolonged ED length of stay: a case study from Italy
Northern Italian hospital ED
Retrospective analysis of 32,967 ED accesses (2022–2024); 12 classification algorithms predicting LOS and prolonged LOS (pLOS); structured data vs structured + free-text nursing-note features.
⚠ Preprint — verify peer-review status.
- pLOS treated as a major contributor to congestion and adverse outcomes (LWBS, suboptimal care, mortality, burnout, cost).
- Aimed at early forecasting to enable process improvement.
Impact of ED length of stay on in-hospital mortality
Retrospective cohort (Italy)
Retrospective cohort; primary outcome 30-day in-hospital mortality; ED-LOS (registration to admission) analysed by quartiles; multivariable logistic regression.
- No independent association between ED-LOS before admission to general (non-ICU) wards and inpatient mortality in this cohort.
- A reminder that the boarding–mortality link is not universal and varies by setting/population. Much of the larger boarding-mortality literature is US-based, though frequently cited as background.
4. Patient safety and adverse events
How overcrowding and the emergency-admission pathway connect to downstream inpatient safety and adverse drug events.
Incidence of adverse events in an Italian acute-care hospital
Italian acute-care hospital (two-stage retrospective cohort)
Two-stage retrospective record review; 1,501 records reviewed; mean age 60; 94.3% Italian patients.
- 46 adverse events (3.3%), most in medical wards (71.7%), then surgical (19.6%) and ICU (8.7%).
- 78.2% of patients who experienced an AE had been admitted as emergencies — linked by the authors to ED overcrowding and prolonged ED stays.
- The AE rate was below the ~5.2% average of an earlier Italian multicentre study. Connects overcrowding/boarding to downstream inpatient safety.
Italian ED visits & hospitalizations for outpatients' adverse drug events: 12-year active pharmacovigilance (MEREAFaPS)
Lombardi N, Crescioli G, Bettiol A, et al.
Nationwide, multicentre, retrospective active-pharmacovigilance surveillance of adverse-drug-event (ADE)–related ED visits and hospitalizations in the Italian general population.
- Describes frequency, seriousness and preventability of ADE-related ED visits and identifies predictors of ADE-related hospitalization.
- ADEs as a significant, partly preventable driver of ED visits and admissions — a drug-safety lens on ED burden.
DOI 10.3389/fphar.2020.00412
Risk of hospitalization for ADEs in women vs men: post-hoc MEREAFaPS analysis
Crescioli G, Boscia E, Bettiol A, et al.
Post-hoc analysis of the Italian active-pharmacovigilance program (Jan 2007–Dec 2018): 61,855 ADE reports leading to ED visits; 30.6% resulted in hospitalization.
- Sex-specific drug-class risks — women: heparins (ROR 1.41), antidepressants (1.12), antidiabetics (1.13); men: vitamin K antagonists (1.28), opioids (1.30), digitalis glycosides (1.32).
- Older age, multiple suspect drugs and comorbidities raised hospitalization risk; post-immunization events carried lower risk.
DOI 10.3390/ph14070678
Sintesi trasversale
Cross-cutting takeaways from the Italian literature above.
Root-cause consensus
Across Italian studies the dominant driver of ED overcrowding is downstream access block — a shortage of, and poor real-time management of, inpatient beds — rather than inappropriate patient use (Turin Molinette; Marsilio/Villa; SIMEU).
Bed management is the highest-value lever
But it is unevenly implemented (present in only ~30% of hospitals per the 2017 SIMEU census); where implemented it shows favorable flow effects (bed-management review; Marsilio/Villa).
Measurement is inconsistent
NEDOCS and EDWIN can diverge sharply (Pearson ~0.32), and only ~22% of Italian EDs used any validated crowding tool as of 2017 — limiting benchmarking.
Mortality signal is mixed
Some Italian cohorts find no independent LOS/overnight-stay–mortality association (Forlì elderly; PubMed 37788143), even though international background literature cites increased mortality with crowding.
Safety harms extend beyond the ED
Emergency admission (a proxy for the crowded pathway) is strongly over-represented among inpatients who suffer adverse events.
Sintesi compilata luglio 2026. Le cifre e le statistiche esatte provengono dalle fonti citate; dove uno studio è preprint o non indicizzato, è segnalato.
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Conosci un articolo italiano su sovraffollamento in PS, flusso dei pazienti o sicurezza che dovremmo includere? Invia i riferimenti — li revisioniamo e, se idonei, li aggiungiamo al digest. Suggest a study for the evidence library.