Clinical Implementation Lead

Duke Careers • Durham, NC

3d • Onsite

About The Position

As a Clinical Implementation Lead, you’ll transform data into actionable insights, launch innovative population health programs, and collaborate across clinical, technical, and research teams. Your work will help build scalable technology solutions that drive meaningful change within Duke clinical enterprise.

This position will interface with care providers and Duke Health leaders, as well as with industry partners to identify and develop opportunities and to execute projects for DIHI. The Consultant will foster collaborations amongst data scientists, statistics/machine learning experts, clinicians/clinical researchers, and software developers to build valuable technology solutions that are scalable both within the Duke clinical enterprise as well as more broadly.

This role will help to build capability and capacity (including both personnel and technology) for DIHI to rapidly develop, validate, support deployment and commercialize health care new data science products.

The Clinical Implementation Lead must maintain contemporary expertise in healthcare delivery, clinical research, data science, to collaborate with and help supervise individuals from a wide array of disciplines. He/she will work closely with the DIHI Executive Director to manage existing efforts that rely on the effective use of heath care data and to help set strategic priorities for future opportunities.

The Clinical Implementation Lead will report to the Executive Director for DIHI.

Requirements

• Bachelor’s degree in math, statistics, computer science, economics, physics, or another quantitative field required.
• Health care professional training (MD, nurse practitioner, or physician assistant) required.
• Health care provider training (MD, NP, PA or PhD) required.
• Preferred experience: five years of experience, including experience in patient-care environment, population health improvement, applications programming, database management and analysis and interpretation of health care data with statistical programming/data science tools.
• Strong background manipulating and analyzing large data sets in Python or go lang.
• Strong background using SQL to query enterprise data warehouses.
• Strong background working with electronic health record and claims data and fluency working with ICD, CPT, LOINC, RxNorm and related standardized vocabularies.
• Strong background combining publicly and proprietary data to support AI/ML development, deployment, integration and lifecycle management.
• Strong background visualizing data.
• Strong background developing, validating and deploying traditional statistical models (logistic regression, multi variable regression) and experience working with machine learning models (random forest, hidden Markov model, ridge regression).
• Strong background in clinical research study design and health care economics evaluations and value analysis (cost-benefit analysis, cost effectiveness analysis).
• Strong background in ethics in AI/ML in healthcare.
• First-hand exposure to patient care environment and deep knowledge of professional practice.
• Strong background identifying drivers of cost and utilization within health care populations and ability to identify opportunities to improve health care outcomes and efficiency.
• Strong background managing interdisciplinary teams.
• Excellent communication and interpersonal skills.
• Ability to rapidly problem solve and mobilize team members to deliver on ad hoc projects and established initiatives.
• Personnel management, including supervision and performance appraisals an added plus.

Nice To Haves

• Master’s degree with quantitative focus preferred.
• Additional work in public health and the improvement of health in populations preferred.
• Experience working at a population level to identify opportunities to improve health care outcomes and health care delivery efficiency.
• Experience working with R or Python data science tools to analyze and visualize health care data and to develop data pipelines to support machine learning model development.
• Experience working with academic and industry professionals to leverage data and technology to produce valuable health care innovations.
• Clinical experience and ability to relate data to clinical outcomes strongly preferred.

Responsibilities

• Support DIHI Executive Director to manage teams of data science professionals, statisticians, clinical researchers, clinicians, and software developers who have received DIHI support to develop data science products to improve healthcare and health system operations.
• Interact with leaders across the Duke Health, academic departments, and industry to identify opportunities to leverage data and technology to improve health care delivery.
• Work with the DIHI Executive Director to set strategic priorities to maximize the impact and value of innovative data science efforts.
• Interact with collaborators from Duke Health, Duke University academic departments, and industry to identify opportunities to leverage data and technology to improve health care delivery.
• Manage the development and expansion of student and trainee programs aimed at engaging undergraduate students, graduate students, 3rd year MD students and health care professional trainees from across campus in DIHI efforts.
• Help with recruitment and growth of DIHI analytics and data science full-time staff and work with departments across the health system to build data science capabilities.
• Develop documentation, software, support tools, and a technology infrastructure to enhance the ability of analysts and operational leaders across the clinical enterprise to effectively and rapidly extract meaning from health care data.
• Maintain fluency in existing and emerging data science technologies and complete online coursework or independent study to fill in gaps of knowledge as needed to manage and execute innovation projects.
• Oversee the development of data pipelines that extract and transform large data sets from a variety of sources (e.g., electronic health record, claims, wearable device, publicly available data, etc.) to support machine learning model development and deployment.
• Work with quantitative sciences and clinical faculty to secure internal and external funding for high-impact projects that enhance population health programs and clinical enterprise operations.
• Work with quantitative sciences and clinical faculty to evaluate predictive models and innovation pilots and help disseminate results through peer-reviewed publications and at academic conferences.
• Safeguard the integrity and security of institutional data.
• Represent DIHI at internal and external conferences and gatherings that bring together experts in population health, machine learning, and data science in health care.
• As needed, develop written materials and visual presentations to convey and disseminate information to internal and external audiences.
• Identify opportunities to commercialize the output of innovations validated at Duke and work with the Office of Licensing and Ventures, internal, and external partners to support project leaders during such transitions.
• As needed, obtain additional training in Epic database structure, medical claims, and clinical research, combining in-classroom and self-directed learning.

Benefits

• Duke provides comprehensive and competitive medical and dental care programs, generous retirement benefits, and a wide array of family-friendly and cultural programs to eligible team members.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees