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Better treatment and lower costs: Health monitoring after hip and knee joint replacement Overview

  • Better treatment and lower costs: Health monitoring after hip and knee joint replacement

    Overview

Optimizing physician visits for knee replacement patients via assignment policies - a machine learning approach

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  6. Optimizing physician visits for knee replacement patients via assignment policies - a machine learning approach
    Health Benefit Packages for India – Pilot Project Breast CancerInternational Health Systems Research CollaborativeThe Swiss hospital capacity planning: An empirical evaluation of its impact on hospital service delivery, quality and costsRecommendations for the contents and user groups of a national quality monitoring system for healthcare servicesEvaluierung der Auswirkungen von betrieblichem Gesundheitsmanagement auf wirtschaftliches Wachstum und die Entwicklung von VersicherungsschädenDeveloping policies to manage hospital process bottlenecks – a machine learning approachSwissPAH: Potentially avoidable hospitalizations in chronic disease – Past and future trends in SwitzerlandÖkonomische Evaluierung und Optimierung verschiedener Massnahmen zur Verbesserung der Prognose von MASH-Patienten (Metabolic Dysfunction-associated steatohepatitis)PROMoting QualityDaVinci - Effektivität der robotergestützten Chirurgie bei radikalen ProstatektomienApplication of Positive and Unlabeled Learning Algorithms to Hospital Administrative DataHealth economic evaluation of rapid recovery post-surgery for knee replacement patientsDeriving optimal policies for selecting knee replacement patients for rapid recovery post-surgery using causal forest and policy treeOptimizing physician visits for knee replacement patients via assignment policies - a machine learning approachEstimation of adjusted minimal important differences for hip and knee replacement patientsOptimizing Clinical Practice Guideline Adherence in Primary CareAssociation of hospital digitalization, profitability, and qualityQuality monitoring systems and dashboards in the Swiss healthcare system: Development of a knowledge base and stakeholder dialoguesGKV-SVBridging the Gap from Data to Action: A Cross-Country Analysis of the Potential of Large Lan-guage Models in Public Reporting

Project description

Knee replacement patients regularly see their physician after surgery to receive feedback on their recovery progress, and on potential alteration of their post-surgery treatment protocol. In a world with increasing healthcare costs and limited availability of healthcare personnel, only patients that require a visit should see their physician. Analytics can help to steer patients to visit their physician only if it benefits their recovery progress.  

With this paper we aim to develop an algorithm that optimally assigns rules for physician visits at three-, six- and twelve-months post-surgery based on patient characteristics and recovery pathways. We aim to build optimal assignment rules to maximize functional improvement and functional outcome of the patient, and to analyze the distributional effect of assignment rules depending on the chosen dependent variable. 

 

Project team

Johannes Cordier, Benedikt Langenberger, Irene Salvi, Dr. David Kuklinski, Prof. Dr. Alexander Geissler 

 

 

Cooperation partner

Technical University of Berlin

 

Funding source

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Duration

12 months (July 2023 to July 2024)

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