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Technical Efficiency of Diabetes Management in PC in Europe . Data Envelopment Analysis

Technical Efficiency of Diabetes Management in PC in Europe . Data Envelopment Analysis. Sonia García Pérez, Carlos Sánchez Piedra, Almudena Albertos, Esther Arrieta, Antonio Sarría Santamera Agencia de Evaluación de Tecnologías Sanitarias. ISCIII. Spain . 9/10 Sept 2013, Istanbul.

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Technical Efficiency of Diabetes Management in PC in Europe . Data Envelopment Analysis

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  1. TechnicalEfficiency of Diabetes Management in PC in Europe. Data EnvelopmentAnalysis Sonia García Pérez, Carlos Sánchez Piedra, Almudena Albertos, Esther Arrieta, Antonio Sarría Santamera Agencia de Evaluación de Tecnologías Sanitarias. ISCIII. Spain 9/10 Sept 2013, Istanbul

  2. Background • Increasınghealthcareexpendıture • Incresing number of chronic patients • Increasingcost of managingchronicpatients • Importantconcern of policymakersaboutthe performance of thehealthcaresystems and PC in particular • Difficultytomeasureefficiency/performance • Which costs are relevant? • What is considered quality? • Consider the system as a whole?

  3. Whythisstudy? • Wesuggest a methodologytomeasureefficiency • By disease: • Moresımple • Easytomakecomparısons • Fındsources of ıneffıcıency • Using time rather than cost. PC is labor intensive, so costs are given by the time spent by professionals. This allows comparisons across countries • Data EnvelopmentAnalysıs (DEA): • NonparametrıctechnıqueusedınEconomıcstofındthecomparatıveeffıcıencyacrossDecısıonMakıngUnıts • Multıpleınputsandoutputstogenerate an effıcıencyfrontıer • Doesnoımpose a functıonal form totheeffıcıencyfrontıer. Flexıbletechnıque. Lıttleassumptıons • No needfornormalization of inputs and outputs. No needforassigment of monetary value to outcomes

  4. Purpose • Theaim of thisworkwasto describe thecomparativelevels of technicalefficiency in terms of quality and time of managing diabetes at patientlevel in PrimaryCaresystems in Europe

  5. Methods • Databases: EUprimecare project. Grant Agreement no. 241595 (Fınland, Germany, Italy, Spaın, Hungary, Estonıa, Lıthuanıa) • Data Envelopment Analysis (DEA). • Output orientedprogram • Constant returns to scale • Software: DEAP versıon 2.1. Unıv. New England. AU

  6. Average time spentby GP with a diabeticpatient in a year • PC Vignettes: Answeredby 27-33 GPs in each country There is a 65-year-old woman among your patients, who has been diagnosed with type 2 diabetes. She comes in for a follow-up visit: the tests from last week show that her HbA1c is 7%. She has no complications. She has been taking metformin 500 mg x2. You are her main primary care provider for the next 12 months

  7. Proportion of preventionactivitiesperformedlastyear. Compositeindicator • PC usersquestionnaire: Answeredby 3020. Diabetic: 276 • Preliminary studies were carried out to see diferences among several types of composite indicators (simple average, expert opinion, and PCA): Minor differences were found

  8. Proportion of patientsundertreatmentwhosetherapywasprescribedbythe GP • PC usersquestionnaire: Answeredby 3020. Diabetic: 276

  9. Patientsatisfaction. Compositeindicator • PC usersquestionnaire: Answeredby 3020. Diabetic: 276 Questions:

  10. Results

  11. Discussion • Potentıalnewmethodologytomeasureeffıcıencyın PC • The quality of care of diabetic patients resulting from the time spent with the patient is maximised for the Spanish PC system • For the rest of the countries higher intensity of outputs could be obtained • Inefficiency: • Largenumber of administrativeactivitieswhich are nottranslatedintodirectbenefittothepatient ? • Referral to specialist who manages the case ? • Furtherinvestigation: • Validation of these model with morecountries and for diferent diseases • How these results relate with health outcomes • Findsources of inefficiency

  12. Thankyou!

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