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Improving the Effectiveness of Chronic Kidney Replacement Therapy in Latvia: A Quality and Cost Framework Based on the Latvian Kidney Disease Registry

Project/agreement No.
NVD-9/97-2024, NVD pilotprojekts Nr. 55
Project funding
799 964.00 EUR, of which Rīga Stradiņš University budget – EUR 113013
Project manager
Kārlis Rācenis, Paula Stradiņa Klīniskā universitātes slimnīca
Project realization
01.10.2024. - 31.03.2026.

Aim

The pilot project aims to implement a new model for improving treatment quality and cost efficiency for patients with kidney replacement therapy (KRT) using the Latvian Kidney Disease Registry (LKDR). The goal is to improve treatment quality and optimize costs within the context of value-based healthcare.

Description

The project will be implemented by the Scientific Institute of the State Limited Liability Company Pauls Stradiņš Clinical University Hospital as a main partner, together with Riga Stradiņš University.

Kidney replacement therapy (KRT) is a life-saving treatment that replaces kidney functions for people with end-stage kidney disease. Kidney transplantation offers significant benefits to the patient, including improved quality of life and survival and financial savings for the individual and the country.

The project is part of the National Health Service project 'Healthcare services development laboratory' and aims to introduce a new model for improving the quality and cost efficiency of KRT.

This pilot project is a new and innovative approach that will improve the quality of KRT in Latvia and optimize its costs. The project will use the LKDR to ensure the collection and analysis of standardized clinical and cost data. Using this data will allow us to identify problems, set treatment quality criteria, and develop recommendations for treatment improvement.

The project will improve the management of the kidney transplant waiting list, which is the most effective KRT modality, to improve access to kidney transplantation.

LKDR data will help monitor treatment outcomes, analyze economic impact, and optimize resource planning, providing valuable input for health policy development. The project aims to ensure effective, patient-tailored KRT long-term and contribute to the development of value-based healthcare in Latvia.

Initially, anonymized data about KRT patients in Latvia will be collected on a specialized platform. At the same time, measurable and evaluable quality criteria will be developed for all KRT modalities. This will be followed by data analysis and the development of recommendations to improve the quality of care for KRT patients. Based on the data analysis, a quality and cost evaluation model will be developed.

The project employs a team of experienced professionals who work with all KRT modalities in Riga and other regions of Latvia. It will foster close collaboration among nephrology professionals and actively involve them in validating the model.

Project team

  • Asst. Prof. Kārlis Rācenis, project manager – senior nephrologist at the Pauls Stradiņš Clinical University Hospital Nephrology Centre, leading researcher with experience in healthcare organization and reform development in Latvia
  • Asoc. prof. Viktorija Kuzema, lead expert, study group, and registry manager – senior nephrologist at the Pauls Stradiņš Clinical University Hospital Nephrology Centre, architect of the LKDR, and acting principal investigator at Riga Stradiņš University
  • Prof. Aivars Pētersons, Head of the KRT Methodology Centre – chief nephrologist at the Pauls Stradiņš Clinical University Hospital Nephrology Centre, internationally recognized expert, and author of scientific publications
  • Jana Živa, Training Coordinator – head nurse at the Pauls Stradiņš Clinical University Hospital Nephrology Centre, responsible for organizing data entry training for KRT centre coordinators and ensuring coordinated project implementation
  • Asst. Prof. Solvita Kļaviņa-Makrecka, – Data Analysis Expert, acting principal investigator at the Public Health Institute of Riga Stradiņš University, will provide expertise in data analysis