Dataset Information

Using text analysis software to identify determinants of inappropriate clinical question reporting and diagnostic procedure referrals in Reggio Emilia, Italy.

ABSTRACT:

Background

Inappropriate prescribing of diagnostic procedures leads to overdiagnosis, overtreatment and resource waste in healthcare systems. Effective strategies to measure and to overcome inappropriateness are essential to increasing the value and sustainability of care. We aimed to describe the determinants of inappropriate reporting of the clinical question and of inappropriate imaging and endoscopy referrals through an analysis of general practitioners' (GP) referral forms in the province of Reggio Emilia, Italy.

Methods

A clinical audit was conducted on routinely collected referral forms of all GPs of Reggio Emilia province. All prescriptions for gastroscopy, colonoscopy, neurological and musculoskeletal computerised tomography (CT) and magnetic resonance imaging (MRI) from 2012 to 2017 were included. The appropriateness of referral forms was assessed using Clinika VAP software, which combines semantic analysis of clinical questions and available metadata. Local protocols agreed on by all physicians defined criteria of appropriateness. Two multilevel logistic models were used to identify multiple predictors of inappropriateness of referral forms and to analyse variability among GPs, primary care subdistricts and healthcare districts.

Results

Overall, 37% of referral forms were classified as inappropriate, gastroscopy and CT showed higher proportions of inappropriate referrals compared to colonoscopy and MRI. Inappropriateness increased with patient age for CT and MRI; for gastroscopy, it was lower for patients aged 65-84 compared to those younger, and for colonoscopy, it was higher for older patients. Fee exemptions were associated with inappropriateness in MRI referral forms. The effect of GPs' practice organization was consistent across all tests, showing higher inappropriateness for primary care medical networks than in primary care medical groups. Male GPs were associated with inappropriateness in endoscopy, and older GPs were associated with inappropriateness in musculoskeletal CT. While there was moderate variability in the inappropriate prescribing among GPs, there was not among the healthcare districts or primary care subdistricts.

Conclusions

Routinely collected data and IT tools can be useful to identify and monitor diagnostic procedures at high risk of inappropriate prescribing. Assessing determinants of inappropriate referral makes it possible to tailor educational and organizational interventions to those who need them.

SUBMITTER: Venturelli F

PROVIDER: S-EPMC7847028 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Publications

Using text analysis software to identify determinants of inappropriate clinical question reporting and diagnostic procedure referrals in Reggio Emilia, Italy.

Venturelli Francesco F Ottone Marta M Pignatti Fabio F Bellocchio Eletta E Pinotti Mirco M Besutti Giulia G Djuric Olivera O Giorgi Rossi Paolo P

BMC health services research 20210129 1

<h4>Background</h4>Inappropriate prescribing of diagnostic procedures leads to overdiagnosis, overtreatment and resource waste in healthcare systems. Effective strategies to measure and to overcome inappropriateness are essential to increasing the value and sustainability of care. We aimed to describe the determinants of inappropriate reporting of the clinical question and of inappropriate imaging and endoscopy referrals through an analysis of general practitioners' (GP) referral forms in the pr ...[more]

PMID: 33514372

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Project description:BackgroundSince February 2020, the COVID-19 epidemic has rapidly spread throughout Italy. Some studies showed an association of environmental factors, such as PM10, PM2.5, NO2, temperature, relative humidity, wind speed, solar radiation and mobility with the spread of the epidemic. In this work, we aimed to predict via Deep Learning the real-time transmission of SARS-CoV-2 in the province of Reggio Emilia, Northern Italy, in a grid with a small resolution (12 km × 12 km), including satellite information.MethodsWe focused on the Province of Reggio Emilia, which was severely hit by the first wave of the epidemic. The outcomes included new SARS-CoV-2 infections and COVID-19 hospital admissions. Pollution, meteorological and mobility data were analyzed. The spatial simulation domain included the Province of Reggio Emilia in a grid of 40 cells of (12 km)2. We implemented a ConvLSTM, which is a spatio-temporal deep learning approach, to perform a 7-day moving average to forecast the 7th day after. We used as training and validation set the new daily infections and hospital admissions from August 2020 to March 2021. Finally, we assessed the models in terms of Mean Absolute Error (MAE) compared with Mean Observed Value (MOV) and Root Mean Squared Error (RMSE) on data from April to September 2021. We tested the performance of different combinations of input variables to find the best forecast model.FindingsDaily new cases of infection, mobility and wind speed resulted in being strongly predictive of new COVID-19 hospital admissions (MAE = 2.72 in the Province of Reggio Emilia; MAE = 0.62 in Reggio Emilia city), whereas daily new cases, mobility, solar radiation and PM2.5 turned out to be the best predictors to forecast new infections, with appropriate time lags.InterpretationConvLSTM achieved good performances in forecasting new SARS-CoV-2 infections and new COVID-19 hospital admissions. The spatio-temporal representation allows borrowing strength from data neighboring to forecast at the level of the square cell (12 km)2, getting accurate predictions also at the county level, which is paramount to help optimise the real-time allocation of health care resources during an epidemic emergency.

Project description:ObjectivesTo explore radiographers' actions toward inappropriate referrals and hindrances to assessing referrals.MethodsAn online survey was distributed to radiographers via the International Society of Radiographers and Radiological Technologists (ISRRT) networks. The questionnaire consisted of 5-point Likert scale questions on radiographers' actions to supplement referral information, actions for unjustified referrals and hindrances to referral assessment. The questionnaire was validated using a test-retest reliability analysis. Kappa values ≥ 0.6 were accepted. SPSS software was used for data analysis and chi-square tests to compare subgroups.ResultsTotal responses received were 279. The most reported actions to supplement missing referral information were to ask the patient or relative, examine the body region of concern and check medical records (73%, 70%, 67%, responded often/always, respectively). The actions when confronted with unjustified referrals were reported equally to consult the radiologist, referring clinician and radiographer (69-68% often/always responses). The hindering factors ranked high (agreed/strongly agreed responses) pertained to inadequate information in referral forms (83%), ineffective communication among healthcare professionals (79%), lack of training (70%) and allocated time (61%). Statistically significant associations were observed for a few actions and hindrances with education level, modality of practice and responsibility to screen imaging referrals.ConclusionRadiographers consult colleagues about suspected unjustified referrals. Effective communication pathways, training and time allocation to improve radiographers' skills to assess referrals may enhance appropriate imaging and delivery of quality patient care.Key points• Radiographers' actions of supplementing missing information in radiology referrals facilitate provision of high-quality health services. • Radiographers' strategy when confronted with inappropriate referrals is to consult radiologists and referring clinicians. • Better inter-professional communication and organisation of tasks can facilitate radiographers' participation in referral assessment to ensure appropriate imaging.

Dataset Information

Using text analysis software to identify determinants of inappropriate clinical question reporting and diagnostic procedure referrals in Reggio Emilia, Italy.

Background

Methods

Results

Conclusions

Publications

Using text analysis software to identify determinants of inappropriate clinical question reporting and diagnostic procedure referrals in Reggio Emilia, Italy.

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