Voci, Claudio
  
(2021)
Use of electronic health data for the identification of cases and for the evaluation of healthcare consumptions and chronic kidney  disease costs, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. 
 Dottorato di ricerca in 
Scienze mediche generali e scienze dei servizi, 33 Ciclo. DOI 10.48676/unibo/amsdottorato/9580.
  
 
  
  
        
        
        
  
  
  
  
  
  
  
    
  
    
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      Abstract
      Introduction
Chronic kidney disease (CKD) is a common condition characterized by a gradual loss of kidney function and consequently increasing costs associated with the disease. 
Aims
The aim was to use administrative databases and a pathology registry to characterize CKD patient according to their stage and to evaluate the burden of disease; to identify incident patients on dialysis; to investigate the impact of COVID-19 on mortality in CKD patients. 
Methods
Data from a regional pathology registry and administrative databases were used to classify CKD patients into different disease progression subgroups (CT-PIRP classification) using the following 6 variables: age, sex, diabetes, glomerular filtration rate, proteinuria, phosphate level and different CKD stages (3a, 3b, 4, 5). Healthcare consumptions and costs were evaluated. Incident chronic dialysis patients were defined those seen regularly in outpatient clinics. The incidence and mortality of COVID-19 among CKD patients were estimated. 
Results
The study cohort includes 7737 CKD patients, aged 73.2±11.6 years, 64.5% males, mostly stage 4 (3136, 40.5%) and 3b (2799, 36.2%). Average annual costs were significantly higher for CT-PIRP groups 2 and 3 (€7239 and €8825 respectively) and more than twofold higher for CKD stage 5 (€7,993) compared to stage 3a (€3,973). 
Both algorithms used to identify incident chronic dialysis patients had high sensitivity, 90.8% and 88.4%, high positive predictive value (84.0% and 82.0%) and high agreement (77.4% and 74.1%).
The incidence of COVID-19 infection was 4.16%. COVID-19 hospitalized patients were the 95.5%, those on home isolation were the 3.6% and the 0.9% were asymptomatic. Compared to those without COVID-19, the overall excess mortality ranged between 34.4% and 56.3%.
Conclusion
Administrative databases are a powerful tool to describe the burden of CKD disease, in order to assess the interventions aimed at reducing the impact of CKD and improving the quality of care of CKD patients.
     
    
      Abstract
      Introduction
Chronic kidney disease (CKD) is a common condition characterized by a gradual loss of kidney function and consequently increasing costs associated with the disease. 
Aims
The aim was to use administrative databases and a pathology registry to characterize CKD patient according to their stage and to evaluate the burden of disease; to identify incident patients on dialysis; to investigate the impact of COVID-19 on mortality in CKD patients. 
Methods
Data from a regional pathology registry and administrative databases were used to classify CKD patients into different disease progression subgroups (CT-PIRP classification) using the following 6 variables: age, sex, diabetes, glomerular filtration rate, proteinuria, phosphate level and different CKD stages (3a, 3b, 4, 5). Healthcare consumptions and costs were evaluated. Incident chronic dialysis patients were defined those seen regularly in outpatient clinics. The incidence and mortality of COVID-19 among CKD patients were estimated. 
Results
The study cohort includes 7737 CKD patients, aged 73.2±11.6 years, 64.5% males, mostly stage 4 (3136, 40.5%) and 3b (2799, 36.2%). Average annual costs were significantly higher for CT-PIRP groups 2 and 3 (€7239 and €8825 respectively) and more than twofold higher for CKD stage 5 (€7,993) compared to stage 3a (€3,973). 
Both algorithms used to identify incident chronic dialysis patients had high sensitivity, 90.8% and 88.4%, high positive predictive value (84.0% and 82.0%) and high agreement (77.4% and 74.1%).
The incidence of COVID-19 infection was 4.16%. COVID-19 hospitalized patients were the 95.5%, those on home isolation were the 3.6% and the 0.9% were asymptomatic. Compared to those without COVID-19, the overall excess mortality ranged between 34.4% and 56.3%.
Conclusion
Administrative databases are a powerful tool to describe the burden of CKD disease, in order to assess the interventions aimed at reducing the impact of CKD and improving the quality of care of CKD patients.
     
  
  
    
    
      Tipologia del documento
      Tesi di dottorato
      
      
      
      
        
      
        
          Autore
          Voci, Claudio
          
        
      
        
          Supervisore
          
          
        
      
        
      
        
          Dottorato di ricerca
          
          
        
      
        
      
        
          Ciclo
          33
          
        
      
        
          Coordinatore
          
          
        
      
        
          Settore disciplinare
          
          
        
      
        
          Settore concorsuale
          
          
        
      
        
          Parole chiave
          chronic kidney disease  healthcare  electronic health data
          
        
      
        
          URN:NBN
          
          
        
      
        
          DOI
          10.48676/unibo/amsdottorato/9580
          
        
      
        
          Data di discussione
          17 Marzo 2021
          
        
      
      URI
      
      
     
   
  
    Altri metadati
    
      Tipologia del documento
      Tesi di dottorato
      
      
      
      
        
      
        
          Autore
          Voci, Claudio
          
        
      
        
          Supervisore
          
          
        
      
        
      
        
          Dottorato di ricerca
          
          
        
      
        
      
        
          Ciclo
          33
          
        
      
        
          Coordinatore
          
          
        
      
        
          Settore disciplinare
          
          
        
      
        
          Settore concorsuale
          
          
        
      
        
          Parole chiave
          chronic kidney disease  healthcare  electronic health data
          
        
      
        
          URN:NBN
          
          
        
      
        
          DOI
          10.48676/unibo/amsdottorato/9580
          
        
      
        
          Data di discussione
          17 Marzo 2021
          
        
      
      URI
      
      
     
   
  
  
  
  
  
    
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