Background: The WHO advised that the impact of COVID-19 pandemic on TB services was estimated to be dramatic due to the disruption of TB services. Methods: A retrospective data collection and evaluation was conducted to include all the patients hospitalized for TB at INMI from 9 March to 31 August 2020 (lockdown period and three months thereafter). For the purpose of the study, data from patients hospitalized in the same period of 2019 were also collected. Results: In the period of March–August 2019, 201 patients were hospitalized with a diagnosis of TB, while in the same period of 2020, only 115 patients, with a case reduction of 43%. Patients with weight loss, acute respiratory failure, concurrent extrapulmonary TB, and higher Timika radiographic scores were significantly more frequently hospitalized during 2020 vs. 2019. The median patient delay was 75 days (IQR: 40–100) in 2020 compared to 30 days (IQR: 10–60) in 2019 (p < 0.01). Diagnostic delays in 2020 remain significant in the multiple logistic model (AOR = 6.93, 95%CI: 3.9–12.3). Conclusions: Our experience suggests that COVID-19 pandemic had an impact on TB patient care in terms of higher diagnostic delay, reduction in hospitalization, and a greater severity of clinical presentations.

BackgroundClinical practice guidelines have been developed aiming to improve the quality of care. The implementation of the computerized clinical guidelines (CCG) has been supported by the development of computerized clinical decision support systems.This systematic review assesses the impact of CCG on the process of care compared with non-computerized clinical guidelines.MethodsSpecific features of CCG were studied through an extensive search of scientific literature, querying electronic databases: Pubmed/Medline, Embase and Cochrane Controlled Trials Register. A multivariable logistic regression was carried out to evaluate the association of CCG's features with positive effect on the process of care.ResultsForty-five articles were selected. The logistic model showed that Automatic provision of recommendation in electronic version as part of clinician workflow (Odds Ratio [OR]= 17.5; 95% confidence interval [CI]: 1.6-193.7) and Publication Year (OR = 6.7; 95%CI: 1.3-34.3) were statistically significant predictors.ConclusionsFrom the research that has been carried out, we can conclude that after implementation of CCG significant improvements in process of care are shown. Our findings also suggest clinicians, managers and other health care decision makers which features of CCG might improve the structure of computerized system.

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BackgroundThe promotion of safer healthcare interventions in hospitals is a relevant public health topic. This study is aimed to investigate predictors of Adverse Events (AEs) taking into consideration the Charlson Index in order to control for confounding biases related to comorbidity.MethodsThe study was a retrospective cohort study based on a two-stage assessment tool which was used to identify AEs. In stage 1, two physicians reviewed a random sample of patient records from 2008 discharges. In stage 2, reviewers independently assessed each screened record to confirm the presence of AEs. A univariable and multivariable analysis was conducted to identify prognostic factors of AEs; socio-demographic and some main organizational variables were taken into consideration. Charlson comorbidity Index was calculated using the algorithm developed by Quan et al.ResultsA total of 1501 records were reviewed; mean patients age was 60 (SD: 19) and 1415 (94.3%) patients were Italian. Forty-six (3.3%) AEs were registered; they most took place in medical wards (33, 71.7%), followed by surgical ones (9, 19.6%) and intensive care unit (ICU) (4, 8.7%). According to the logistic regression model and controlling for Charlson Index, the following variables were associated to AEs: type of admission (emergency vs elective: OR 3.47, 95% CI: 1.60-7.53), discharge ward (surgical and ICU vs medical wards: OR 2.29, 95% CI: 1.00-5.21 and OR 4.80, 95% CI: 1.47-15.66 respectively) and length of stay (OR 1.03, 95% CI 1.01-1.04). Among patients experiencing AEs a higher frequency of elderly (≥65 years) was shown (58.7% vs 49.3% among patients without AEs) but this difference was not statistically significant. Interestingly, a higher percentage of patients admitted through emergency department was found among patients experiencing AEs (69.7% vs 55.1% among patients without AEs).ConclusionsThe incidence of AEs was associated with length of stay, type of admission and unit of discharge, independently by comorbidity. On the basis of our results, it appears that organizational characteristics, taking into account the adjustment for comorbidity, are the main factors responsible for AEs while patient vulnerability played a minor role.Electronic supplementary materialThe online version of this article (doi:10.1186/1472-6963-14-358) contains supplementary material, which is available to authorized users.

PurposeThere are some methodological concerns regarding results from observational studies about the effectiveness of evidence-based (EB) drug therapy in secondary prevention after myocardial infarction. The present study used a nested case–control approach to address these major methodological limitations.MethodsA cohort of 6880 patients discharged from hospital after acute myocardial infarction (AMI) in 2006–2007 was enrolled and followed-up throughout 2009. Exposure was defined as adherence to each drug in terms of the proportion of days covered (cutoff ≥ 75%). Composite treatment groups, that is, groups with no EB therapy or therapy with one, two, three, or four EB drugs), were analyzed. Outcomes were overall mortality and reinfarction. Nested case–control studies were performed for both outcomes, matching four controls to every case (841 deaths, 778 reinfarctions) by gender, age, and individual follow-up. The association between exposure to EB drug therapy and outcomes was analyzed using conditional logistic regression, adjusting for revascularization procedures, comorbidities, duration of index admission, and use of the study drugs prior to admission.ResultsMortality and reinfarction risk decreased with the use of an increasing number of EB drugs. Combinations of two or more EB drugs were associated with a significant protective effect (p < 0.001) versus no EB drugs (mortality: 4 EB drugs: ORadj = 0.35; 95%CI: 0.21–0.59; reinfarction: 4 EB drugs: ORadj = 0.23; 95%CI: 0.15–0.37).ConclusionsThese findings of the beneficial effects of EB polytherapy on mortality and morbidity in a population-based setting using a nested case–control approach strengthen existing evidence from observational studies. Copyright © 2013 John Wiley & Sons, Ltd.