2,068 computer-security-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"LGEF" positions at Duke University
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compliance with performance improvement plans, JCAHO, and other licensing, accrediting, and regulatory agencies. The Duke University Health System offers career advancement through a clinical ladder program
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of experience who are exceptional performers may be eligible for this level. CN Is are eligible for promotion to CN II by meeting criteria set forth by the DUHS Vizient Nurse Residency Program within 12 months
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school program. Experience Work generally requires two years of experience in health care EXPERIENCE specialties related to the specific position; two years additional years related experience may be
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(s). Accessing and systematically using data from multiple sources such as patient medical records, claims, and program metric reports to target recipient(s) and provider(s) for outreach, education
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for quality assurance. Runs summaries and reports on existing data. Follows required processes, policies, and systems to ensure data security and provenance. In addition, recognizes and reports security
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. Administrative Responsibilities: Help develop and implement policies to ensure patient comfort and safety and participate in creating new policies. Contribute to maintaining the care environment, including
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/reactions to mobilization and documents in medical record as appropriate. Basic computer skills, ability to learn and use DUHS computer system programs. Understand oxygen procedures in transport of patients
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Qualifications at this Level Education Work requires graduation from an accredited BSN program. Exception: Registered nurses hired between July 1, 2014 and April 11, 2021 without a Bachelor's degree in Nursing
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- 4:30pm, 8:30am - 5:00pm or 9:00am - 5:30pm *** DUHS Commitment Bonus Program $5000.00 (paid in 2 installments over 12 months - 6 month increments) *** * Only new hires who have not worked for Duke
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systems, social sciences, epidemiology or other health-related fields. Demonstrated proficiency through previous developed analytical codes with R Language for Statistical Computing and/or Python The ideal