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Nov 24, 2024

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1 Job Description by (Name) The Name of the Class (Course) Professor (Tutor) The Name of the School (University) The City and State where it is located The Date

2 Job Title: PRN Advanced Practice Provider (Telehealth) Job ID: MMG1858 Company: MedStar Medical Group MedStar Medical Group is looking for an experienced and dedicated Advanced Practice Provider (APP) who has an interest in telehealth, which will improve patient access and care provision. An ideal candidate will have an acute care background and a good understanding of telemedicine technology and how to use it to deliver the best patient care. This role gives the opportunity to work within a team-based approach to care, cooperating with primary care and specialist teams to provide all-inclusive patient treatment. Responsibilities:  Perform virtual consultations and assessments with patients utilizing the MedStar eVisit system.  Cooperate with primary care and specialist teams to create and carry out patient care plans.  Use telemedicine technology properly for virtual check-ups, diagnosis of diseases, and prescription of suitable treatments.  Keep patient records in the MedStar system correct and updated.  Be on the lookout at all times for any developments in telemedicine technology and practices in a bid to equip yourself with the necessary skills.  Exhibit comprehension of delivering compassionate and patient-oriented care in a virtual platform Requirements:

3  Current licensure as a Nurse Practitioner in Maryland, DC, and Virginia.  Active DEA and CDS certificates.  A minimum of 2 years of experience as a Nurse Practitioner in acute care settings, preferably urgent care or emergency department environment.  Competency in handling telemedicine tech for virtual patient consultations.  Excellent interpersonal and communication skills, allowing to work collaboratively within a multidisciplinary team.  Dedication to continuous professional development and growth in the field of telemedicine. In their book, Hamza et al. (2020) explain how, at the beginning of Toeplitz matrix completion research, most approaches focused on heuristic approaches and iterative algorithms (Pg 1211). These methods were invented to approximate missing entries using known values and explore the structural properties implicit in Toeplitz matrices. Belyaev et al. (2020) discuss Iterative thresholding, which iteratively updates the missing entries via thresholding operations applied to observed ones (Pg 1187-1188). Though seemingly straightforward, iterative thresholding served as a good solution to the Toeplitz matrix completion in consideration of the cases where computation cost needed to be saved. Another popular approach was nuclear norm minimization; it became well-known as a tool for low-rank matrix recovery from incomplete observations ( Guglielmi & Scalone, 2020, Pg1-2 ). This technique that Candès and Recht promoted in the seminal 2009 paper on “Exact Matrix Completion via Convex Optimization” centers on the minimization of the nuclear norm

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4 of the matrix under certain constraints. Nuclear norm minimization was shown to be efficient for Toeplitz matrix completion utilizing the low-rank property of many datasets. Research by Huang et al. (2021) and Zhang et al. (2021) looked at low-rank matrix completion algorithms that intend to recover the underlying low-rank structure of matrices from partial observations at the early stage. These algorithms do the matrix completion using optimization methods to obtain a low-rank approximation of the incomplete matrix, which fills in the missing entries. Although computationally expensive, Cavalcante & Porsani (2022) explain in their book that low-rank matrix completion algorithms offered a robust solution to Toeplitz matrix completion, especially in cases where data exhibited low-rank properties (Pg 362).

5 Reference MedStar Health. (2023, August 9). Position. MedStar Health. Retrieved February 9, 2024, from https://careers.medstarhealth.org/global/en/job/MEHEGLOBALMMG1858MEDSTARM EDICA LGROUPENGLOBAL/PRN-Advanced-Practice-Provider-in-On-Demand- Telehealth?utm_source=indeed&utm_medium=phenom-feeds&\ &source=Indeed

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