Developing a Dynamic Simulation Model for Point-of-Care Ultrasound Assessment and Learning Curve Analysis
The development of new diagnostic technologies is accelerating, and budgetary constraints in the health sector necessitate a systematic decision-making process to acquire emerging technologies. Health Technology Assessment methodologies integrate technology, clinical efficacy, patient safety, and or...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-07-01
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| Series: | Systems |
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| Online Access: | https://www.mdpi.com/2079-8954/13/7/591 |
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| author | Sandra Usaquén-Perilla Laura Valentina Bocanegra-Villegas Jose Isidro García-Melo |
| author_facet | Sandra Usaquén-Perilla Laura Valentina Bocanegra-Villegas Jose Isidro García-Melo |
| author_sort | Sandra Usaquén-Perilla |
| collection | DOAJ |
| description | The development of new diagnostic technologies is accelerating, and budgetary constraints in the health sector necessitate a systematic decision-making process to acquire emerging technologies. Health Technology Assessment methodologies integrate technology, clinical efficacy, patient safety, and organizational and financial factors in this context. However, these methodologies do not include the learning curve, a critical factor in operator-dependent technologies. This study presents an evaluation model incorporating the learning curve, developed from the domains of the AdHopHTA project. Using System Dynamics (SD), the model was validated and calibrated as a case study to evaluate the use of Point-of-Care Ultrasound (POCUS) in identifying dengue. This approach allowed for the analysis of the impact of the learning curve and patient demand on the revenues and costs of the healthcare system and the cost–benefit indicator associated with dengue detection. The model assesses physician competency and how different training strategies and frequencies of use affect POCUS adoption. The findings underscore the importance of integrating the learning curve into decision-making. This study highlights the need for further investigation into the barriers that limit the effective use of POCUS, particularly in resource-limited settings. It proposes a framework to improve the integration of this technology into clinical practice for early dengue detection. |
| format | Article |
| id | doaj-art-efa638b8ad594ed7bf581dcf6e8d3fb9 |
| institution | DOAJ |
| issn | 2079-8954 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Systems |
| spelling | doaj-art-efa638b8ad594ed7bf581dcf6e8d3fb92025-08-20T03:08:06ZengMDPI AGSystems2079-89542025-07-0113759110.3390/systems13070591Developing a Dynamic Simulation Model for Point-of-Care Ultrasound Assessment and Learning Curve AnalysisSandra Usaquén-Perilla0Laura Valentina Bocanegra-Villegas1Jose Isidro García-Melo2Faculty of Engineering, Universidad del Valle, Cali 760042, ColombiaIndustrial Engineering Department, National Technological Institute of Mexico TecNM, Orizaba 94300, MexicoFaculty of Engineering, Universidad del Valle, Cali 760042, ColombiaThe development of new diagnostic technologies is accelerating, and budgetary constraints in the health sector necessitate a systematic decision-making process to acquire emerging technologies. Health Technology Assessment methodologies integrate technology, clinical efficacy, patient safety, and organizational and financial factors in this context. However, these methodologies do not include the learning curve, a critical factor in operator-dependent technologies. This study presents an evaluation model incorporating the learning curve, developed from the domains of the AdHopHTA project. Using System Dynamics (SD), the model was validated and calibrated as a case study to evaluate the use of Point-of-Care Ultrasound (POCUS) in identifying dengue. This approach allowed for the analysis of the impact of the learning curve and patient demand on the revenues and costs of the healthcare system and the cost–benefit indicator associated with dengue detection. The model assesses physician competency and how different training strategies and frequencies of use affect POCUS adoption. The findings underscore the importance of integrating the learning curve into decision-making. This study highlights the need for further investigation into the barriers that limit the effective use of POCUS, particularly in resource-limited settings. It proposes a framework to improve the integration of this technology into clinical practice for early dengue detection.https://www.mdpi.com/2079-8954/13/7/591system dynamicshealth technology assessment (HTA)point-of-care ultrasound (POCUS)dengue |
| spellingShingle | Sandra Usaquén-Perilla Laura Valentina Bocanegra-Villegas Jose Isidro García-Melo Developing a Dynamic Simulation Model for Point-of-Care Ultrasound Assessment and Learning Curve Analysis Systems system dynamics health technology assessment (HTA) point-of-care ultrasound (POCUS) dengue |
| title | Developing a Dynamic Simulation Model for Point-of-Care Ultrasound Assessment and Learning Curve Analysis |
| title_full | Developing a Dynamic Simulation Model for Point-of-Care Ultrasound Assessment and Learning Curve Analysis |
| title_fullStr | Developing a Dynamic Simulation Model for Point-of-Care Ultrasound Assessment and Learning Curve Analysis |
| title_full_unstemmed | Developing a Dynamic Simulation Model for Point-of-Care Ultrasound Assessment and Learning Curve Analysis |
| title_short | Developing a Dynamic Simulation Model for Point-of-Care Ultrasound Assessment and Learning Curve Analysis |
| title_sort | developing a dynamic simulation model for point of care ultrasound assessment and learning curve analysis |
| topic | system dynamics health technology assessment (HTA) point-of-care ultrasound (POCUS) dengue |
| url | https://www.mdpi.com/2079-8954/13/7/591 |
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