2,711 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" "UNIV" positions at Duke University in United States
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surgery, anesthesia, imaging, and other departments to resolve care barriers. Monitor compliance with CMS and registry requirements, support data collection and quality initiatives, including standing
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, negotiation and decision- making. - Obtain adequate facts and evaluates data to identify and intervene in actual and/or potential safety and risk management issues. - Communicate pertinent information (verbal
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of billing. Maintain confidentiality of employee and patient information. Exhibit an attitude which promotes harmony and goodwill in the workplace. Display a clean, neat, professional appearance. Participate
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identity, genetic information, national origin, race, religion, sex (including pregnancy and pregnancy related conditions), sexual orientation or military status. Duke aspires to create a community built on
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the needs of the dog throughout the work shift to provide adequate rest and down time. Maintains accurate program data and statistics to support evaluation, quality improvements, and program development
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/payment. Schedules and pre-register patients, correcting as necessary all patient demographic and financial data. Resolve insurance claim rejections/denials and remedy expediently. Call patients to remind
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information for laboratory records, explain procedures, allay fears and elicit cooperation. Perform a variety of routine and specialized specimen preparation procedures including, but not limited to, general
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. Obtain and record patient data for medical records noting and informing RN/LPN of information collected. Administer treatment and personal care procedures to patients including, but not limited to, feeding
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physician orders and established policies and procedures to include collecting and analyzing patient data, developing and implementing nursing care plans, establishing interpersonal relationships with
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, and health insurance using large administrative claims. Our projects span methods such as difference‑in‑differences, panel data models / controlled interrupted time series/ segmented regression, and