Subcategorizing the Expected Value of Perfect Implementation to Identify When and Where to Invest in Implementation Initiatives.

Purpose. Clinical practice variations and low implementation of effective and cost-effective health care technologies are a key challenge for health care systems and may lead to suboptimal treatment and health loss for patients. The purpose of this work was to subcategorize the expected value of per...

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Published in:Medical Decision Making Vol. 40; no. 3; pp. 327 - 339
Main Authors: Johannesen, Kasper, Janzon, Magnus, Jernberg, Tomas, Henriksson, Martin
Format: case study equations & formulas research tables/charts Journal Article
Published: Sage Publications Inc. Apr2020
Online Access:View this record in EBSCOhost
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      dt: Apr2020
      vid: 40
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      pub: Sage Publications Inc.
      place: Thousand Oaks, California
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        atl: Subcategorizing the Expected Value of Perfect Implementation to Identify When and Where to Invest in Implementation Initiatives.
      aug:
        au:
          Johannesen, Kasper
          Janzon, Magnus
          Jernberg, Tomas
          Henriksson, Martin
        affil: Department of Medical and Health Sciences, Linköping University, Linköping, Sweden
      sug:
        subj:
          Implementation Science
          Program Implementation
          Cost Benefit Analysis
          Health Care Delivery Methods
          Human
          Conceptual Framework
          Platelet Aggregation Inhibitors Administration and Dosage
          Myocardial Infarction Prevention and Control
          Quality-Adjusted Life Years
          Decision Making
      ab: Purpose. Clinical practice variations and low implementation of effective and cost-effective health care technologies are a key challenge for health care systems and may lead to suboptimal treatment and health loss for patients. The purpose of this work was to subcategorize the expected value of perfect implementation (EVPIM) to enable estimation of the absolute and relative value of eliminating slow, low, and delayed implementation. Methods. Building on the EVPIM framework, this work defines EVPIM subcategories to estimate the expected value of eliminating slow, low, or delayed implementation. The work also shows how information on regional implementation patterns can be used to estimate the value of eliminating regional implementation variation. The application of this subcategorization is illustrated by a case study of the implementation of an antiplatelet therapy for the secondary prevention after myocardial infarction in Sweden. Incremental net benefit (INB) estimates are based on published cost-effectiveness assessments and a threshold of SEK 250,000 (£22,300) per quality-adjusted life year (QALY). Results. In the case study, slow, low, and delayed implementation was estimated to represent 22%, 34%, and 44% of the total population EVPIM (2941 QALYs or SEK 735 million), respectively. The value of eliminating implementation variation across health care regions was estimated to 39% of total EVPIM (1138 QALYs). Conclusion. Subcategorizing EVPIM estimates the absolute and relative value of eliminating different parts of suboptimal implementation. By doing so, this approach could help decision makers to identify which parts of suboptimal implementation are contributing most to total EVPIM and provide the basis for assessing the cost and benefit of implementation activities that may address these in future implementation of health care interventions.
      pubtype: Academic Journal
      doctype:
        case study
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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