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Development of a Trusted Third Party at a Large University Hospital: Design and Implementation Study

Development of a Trusted Third Party at a Large University Hospital: Design and Implementation Study

The most important nonfunctional requirements are as follows: (1) scalability, particularly when executing cross-service operations, and (2) documentation of administration functions. In this section, we will describe basic building blocks of the developed application stack. As mentioned previously, the application has been developed around the MOSAIC tools [17] as core components.

Eric Wündisch, Peter Hufnagl, Peter Brunecker, Sophie Meier zu Ummeln, Sarah Träger, Marcus Kopp, Fabian Prasser, Joachim Weber

JMIR Med Inform 2024;12:e53075

Machine Learning–Based Prediction Models for Different Clinical Risks in Different Hospitals: Evaluation of Live Performance

Machine Learning–Based Prediction Models for Different Clinical Risks in Different Hospitals: Evaluation of Live Performance

While much work has been done on developing distinct clinical risk prediction models, the scalability of the prediction models has been much less explored (ie, the extensibility of the risk prediction model for multiple diseases over different hospitals) [6]. Rajkomar et al [6] designed a single data structure based on the FHIR (Fast Healthcare Interoperability Resources) standard [7] and developed different clinical scenarios over two hospitals with this common data structure.

Hong Sun, Kristof Depraetere, Laurent Meesseman, Patricia Cabanillas Silva, Ralph Szymanowsky, Janis Fliegenschmidt, Nikolai Hulde, Vera von Dossow, Martijn Vanbiervliet, Jos De Baerdemaeker, Diana M Roccaro-Waldmeyer, Jörg Stieg, Manuel Domínguez Hidalgo, Fried-Michael Dahlweid

J Med Internet Res 2022;24(6):e34295

An Integrated, Scalable, Electronic Video Consent Process to Power Precision Health Research: Large, Population-Based, Cohort Implementation and Scalability Study

An Integrated, Scalable, Electronic Video Consent Process to Power Precision Health Research: Large, Population-Based, Cohort Implementation and Scalability Study

In this paper, we describe phase 2 of the ATLAS Community Health Initiative, which focuses on the operational implementation and scalability of the UCON process. This includes its interoperability with the EHR and laboratory information management systems that power the UCLA ATLAS precision health biobank. We expanded the animated UCON process to 18 UCLA Health clinics across the Los Angeles region to test its scalability as an enterprise solution.

Clara Lajonchere, Arash Naeim, Sarah Dry, Neil Wenger, David Elashoff, Sitaram Vangala, Antonia Petruse, Maryam Ariannejad, Clara Magyar, Liliana Johansen, Gabriela Werre, Maxwell Kroloff, Daniel Geschwind

J Med Internet Res 2021;23(12):e31121

Effect of Door-to-Door Screening and Awareness Generation Activities in the Catchment Areas of Vision Centers on Service Use: Protocol for a Randomized Experimental Study

Effect of Door-to-Door Screening and Awareness Generation Activities in the Catchment Areas of Vision Centers on Service Use: Protocol for a Randomized Experimental Study

Although community engagement has been established as an important element of primary care [1], the evidence for the cost-effectiveness of a door-to-door screening model will help in decision making regarding the scalability of such an intervention. In India, like in many low-to-middle-income countries, the majority of the population resides in rural areas [25]. With an unequal distribution of doctors, including ophthalmologists, in rural locations [26], the need for primary care is greater there.

Shalinder Sabherwal, Anand Chinnakaran, Ishaana Sood, Gaurav K Garg, Birendra P Singh, Rajan Shukla, Priya A Reddy, Suzanne Gilbert, Ken Bassett, Gudlavalleti V S Murthy, Operational Research Capacity Building Study Group

JMIR Res Protoc 2021;10(11):e31951

Domains and Methods Used to Assess Home Telemonitoring Scalability: Systematic Review

Domains and Methods Used to Assess Home Telemonitoring Scalability: Systematic Review

the concept of scalability without providing an assessment method Studies just focusing on describing disease risk patterns or intervention efficacy testing Study protocols or medical testing procedures for potential scalability assessment and possible scale-up Statistical or conceptual modeling without a real-world study Facilitators and barriers to scale-up within specific interventions or general experiences of scale-up that did not provide a scalability assessment method Studies recommending an assessment

Salome Padua Azevedo, Teresa Cipriano Rodrigues, Ana Rita Londral

JMIR Mhealth Uhealth 2021;9(8):e29381

Characterizing the Anticancer Treatment Trajectory and Pattern in Patients Receiving Chemotherapy for Cancer Using Harmonized Observational Databases: Retrospective Study

Characterizing the Anticancer Treatment Trajectory and Pattern in Patients Receiving Chemotherapy for Cancer Using Harmonized Observational Databases: Retrospective Study

Furthermore, we performed a pilot study to identify the time of neutropenia onset across various chemotherapy regimens, to validate the scalability of the algorithm. All methods were independently applied to each database and data were collected exclusively as graphical summaries. We conducted this study using two EHRs of Korean tertiary hospitals and a nationwide claims database from South Korea.

Hokyun Jeon, Seng Chan You, Seok Yun Kang, Seung In Seo, Jeremy L Warner, Rimma Belenkaya, Rae Woong Park

JMIR Med Inform 2021;9(4):e25035

Design Choices and Trade-Offs in Health Care Blockchain Implementations: Systematic Review

Design Choices and Trade-Offs in Health Care Blockchain Implementations: Systematic Review

This improves scalability, but a trade-off is that EMR data may be harder to audit. While the principle of cryptographically linked blocks underpins a blockchain, many design choices can be made [13]. However, these choices may result in trade-offs [14]: trade-offs are defined as “a compromise between two desirable but incompatible features.”

Odhran O'Donoghue, Anuraag A Vazirani, David Brindley, Edward Meinert

J Med Internet Res 2019;21(5):e12426