Regional variation in hospitalisation and mortality in heart failure: comparison of England and Lombardy using multistate modelling.

Heart failure (HF) is a common, serious chronic condition with high morbidity, hospitalisation and mortality. The healthcare systems of England and the northern Italian region of Lombardy share important similarities and have comprehensive hospital administrative databases linked to the death register. We used them to compare admission for HF and mortality for patients between 2006 and 2012 (n = 37,185 for Lombardy, 234,719 for England) with multistate models. Despite close similarities in age, sex and common comorbidities of the two sets of patients, in Lombardy, HF admissions were longer and more frequent per patient than in England, but short- and medium-term mortality was much lower. English patients had more very short stays, but their very elderly also had longer stays than their Lombardy counterparts. Using a three-state model, the predicted total time spent in hospital showed large differences between the countries: women in England spent an average of 24 days if aged 65 at first admission and 19 days if aged 85; in Lombardy these figures were 68 and 27 days respectively. Eight-state models suggested disease progression that appeared similar in each country. Differences by region within England were modest, with London patients spending more time in hospital and having lower mortality than the rest of England. Whilst clinical practice differences plausibly explain these patterns, we cannot confidently disentangle the impact of alternatives such as coding, casemix, and the availability and use of non-hospital settings. We need to better understand the links between rehospitalisation frequency and mortality.

How health service delivery guides the allocation of major trauma patients in the intensive care units of the inclusive (hub and spoke) trauma system of the Emilia Romagna Region (Italy). A cross-sectional study.

OBJECTIVE: To evaluate cross-sectional patient distribution and standardised 30-day mortality in the intensive care units (ICU) of an inclusive hub and spoke trauma system. SETTING: ICUs of the Integrated System for Trauma Patient Care (SIAT) of Emilia-Romagna, an Italian region with a population of approximately 4.5 million. PARTICIPANTS: 5300 patients with an Injury Severity Score (ISS) >15 were admitted to the regional ICUs and recorded in the Regional Severe Trauma Registry between 2007 and 2012. Patients were classified by the Abbreviated Injury Score as follows: (1) traumatic brain injury (2) multiple injuriesand (3) extracranial lesions. The SIATs were divided into those with at least one neurosurgical level II trauma centre (TC) and those with a neurosurgical unit in the level I TC only. RESULTS: A higher proportion of patients (out of all SIAT patients) were admitted to the level I TC at the head of the SIAT with no additional neurosurgical facilities (1083/1472, 73.6%) compared with the level I TCs heading SIATs with neurosurgical level II TCs (1905/3815; 49.9%). A similar percentage of patients were admitted to level I TCs (1905/3815; 49.9%) and neurosurgical level II TCs (1702/3815, 44.6%) in the SIATs with neurosurgical level II TCs. Observed versus expected mortality (OE) was not statistically different among the three types of centre with a neurosurgical unit; however, the best mean OE values were observed in the level I TC in the SIAT with no neurosurgical unit. CONCLUSION: The Hub and Spoke concept was fully applied in the SIAT in which neurosurgical facilities were available in the level I TC only. The performance of this system suggests that competition among level I and level II TCs in the same Trauma System reduces performance in both. The density of neurosurgical centres must be considered by public health system governors before implementing trauma systems.

Evaluation of the survival benefit of Trauma-Centre care in the Italian setting.

BACKGROUND: Trauma Centres (TC) are expected to have a lower mortality - after controlling for injury-severity - than non-designated hospitals in order to justify their funding. This benefit has been demonstrated in the USA not long ago, while the evidence from other settings is still limited. We evaluated the mortality benefit of TC care in an Italian setting, where the first Trauma System with designated TCs was instituted six years ago. MATERIALS AND METHODS: We compared 30-day mortality among 4059 severely injured patients treated in the three TCs and in 12 other hospitals of the region Emilia-Romagna, Italy between 2007 and 2011. We used propensity-score weighting to adjust for differences in potential confounders. RESULTS: In the overall population there was no difference in the adjusted mortality - OR (95% CI) 1.02 (0.81-1.29). However, an interaction existed between TC care and injury severity. Subgroup analyses showed that the benefit of TC care was significant for the patients with a TMPM-ICD9 severity score>0.12 - OR (95% CI) 0.70 (0.52-0.97). These patients comprised about one-third of the study population. Further subgroup investigations showed that this effect was concentrated in the patients with less than 45 years. CONCLUSIONS: The risk of death for patients with particularly severe injuries is significantly lower when they are treated in TCs as compared to Non-Trauma Centres, especially if they are younger than 45 years. TC care should be provided to a larger number of patients than currently done.

A population based study on the night-time effect in trauma care.

BACKGROUND: The so-called off hour effect-that is, increased mortality for patients admitted outside normal working hours-has never been demonstrated in trauma care. However, most of the studies excluded transferred cases. Because these patients are a special challenge for trauma systems, we hypothesised that their processes of care could be more sensitive to the off hour effect. METHODS: The study design was retrospective, cohort and population based. We compared the mortality of all patients by daytime and night-time admittance to hospitals in an Italian region, with 4.5 million inhabitants, following a major injury in 2011. Logistic regression was used, adjusted for demographics and severity of injury (TMPM-ICD9), and stratified by transfer status. RESULTS: 1940 major trauma cases were included; 105 were acutely transferred. Night-time admission had a significant pejorative effect on mortality in the adjusted analysis (OR=1.49; 95% CI 1.05 to 2.11). This effect was most evident in transferred cases (OR=3.71; 95% CI 1.11 to 12.43). CONCLUSIONS: The night-time effect in trauma care was demonstrated for the first time and was maximal in transferred cases. This may explain why it was not found in previous studies where these patients were mostly excluded. Also, the use of population based data-whereby patients not accessing trauma centre care and presumably receiving poorer care were included-may have contributed to the findings.

Clinical governance network for clinical audit to improve quality in epithelial ovarian cancer management.

BACKGROUND: Epithelial ovarian cancer (EOC) is the most lethal gynecological cancer. Several hospitals throughout the region provide primary treatment for these patients and it is well know that treatment quality is correlated to the hospital that delivers. The aim of this study was to investigate the management and treatment of EOC in a Region of the North Italy (Emilia-Romagna, Italy). METHODS: A multidisciplinary group made up of 11 physicians and 3 biostatisticians was formed in 2009 to perform clinical audits in order to identify quality indicators and to develop Region-wide workup in accordance with the principles of evidence-based medicine (EBM). The rationale was that, by setting up an oncogynecology network so as to achieve the best clinical practice, critical points would decrease or even be eliminated. Analysis of cases was based on the review of the medical records. RESULTS: 614 EOC patients treated between 2007 and 2008 were identified. We found only 2 high-volume hospitals (≥ 21 patients/year), 3 medium-volume hospitals (11-20 operated patients/year), and 7 low-volume hospitals (≤ 10 operated patients /year). Only 222 patients (76.3%) had a histological diagnosis, FIGO surgical staging was reported only in 206 patients (70.9%) but not all standard surgical procedures were always performed, residual disease were not reported in all patients. No standard number of neoadjuvant chemotherapy cycles was observed. CONCLUSIONS: The differences in terms of treatments provided led the multidisciplinary group to identify reference centers, to promote centralization, to ensure uniform and adequate treatment to patients treated in regional centers and to promote a new audit involving all regional hospitals to a complete review of the all the EOC patients.

Is the TMPM-ICD9 revolution in trauma risk-adjustment compatible with imperfect administrative coding?

BACKGROUND: TMPM-ICD9 is the latest injury-severity measure based on empirical estimation from ICD-9-CM codes. It is candidate to replace expert-based AIS measures worldwide because of easier accessibility and better predictive performances. In Italy and other countries administrative ICD coding is generally less complete than dedicated AIS coding. We attempted to ascertain how this affects TMPM performances. METHODS: Discrimination (c statistics) and calibration (calibration curves, Akaike's criterion) of hierarchical logistic regression models for hospital mortality comprising TMPM or ISS were compared using trauma-registry data on 3570 patients of years 2007-2009. The completeness of AIS vs. ICD-9-CM coding was also investigated through the ratio of the respective numbers of codes per patient. Model discrimination was further analyzed after stratification according to the above ratio (>1 and ≤ 1). RESULTS: The models with TMPM showed worse performances. The differences, concerned calibration (graphical evidence) in univariate models and discrimination (-1.2% of area under the ROC curve, p<0.05) in models completed with age, gender, mechanism of injury, motor GCS and systolic pressure. In parallel, ICD coding was less complete than AIS, as expected: 68% of patients had a ratio >1. The discrimination of TMPM vs. ISS models improved when the ratio changed from >1 to ≤ 1. CONCLUSIONS: The predictive performances of TMPM-ICD9 vs. ISS were lower than in the previous studies; the sub-optimal quality of ICD coding was a main cause. Imperfect administrative coding may hence hamper the TMPM-ICD9 revolution, although in our setting the negligible differences and the ready availability of administrative data may still give reason for adopting TMPM-ICD9.

The counterintuitive effect of multiple injuries in severity scoring: a simple variable improves the predictive ability of NISS.

BACKGROUND: Injury scoring is important to formulate prognoses for trauma patients. Although scores based on empirical estimation allow for better prediction, those based on expert consensus, e.g. the New Injury Severity Score (NISS) are widely used. We describe how the addition of a variable quantifying the number of injuries improves the ability of NISS to predict mortality. METHODS: We analyzed 2488 injury cases included into the trauma registry of the Italian region Emilia-Romagna in 2006-2008 and assessed the ability of NISS alone, NISS plus number of injuries, and the maximum Abbreviated Injury Scale (AIS) to predict in-hospital mortality. Hierarchical logistic regression was used. We measured discrimination through the C statistics, and calibration through Hosmer-Lemeshow statistics, Akaike's information criterion (AIC) and calibration curves. RESULTS: The best discrimination and calibration resulted from the model with NISS plus number of injuries, followed by NISS alone and then by the maximum AIS (C statistics 0.775, 0.755, and 0.729, respectively; AIC 1602, 1635, and 1712, respectively). The predictive ability of all the models improved after inclusion of age, gender, mechanism of injury, and the motor component of Glasgow Coma Scale (C statistics 0.889, 0.898, and 0.901; AIC 1234, 1174, and 1167). The model with NISS plus number of injuries still showed the best performances, this time with borderline statistical significance. CONCLUSIONS: In NISS, the same weight is assigned to the three worst injuries, although the contribution of the second and third to the probability of death is smaller than that of the worst one. An improvement of the predictive ability of NISS can be obtained adjusting for the number of injuries.