The Clinical Information Network (CIN) was initiated in 2013 first to track changes in paediatric quality of care and since 2018 to track quality of inpatient neonatal care. The CIN now involves 19 Kenyan county hospitals and works to help develop improved information on the causes, characteristics and outcomes of neonatal admissions. The team has, over a number of years, developed a variety of metrics on the quality and outcomes of care provided to inpatient new borns with common illnesses. Hospitals in CIN are also now taking part in specific quality of care improvement programmes expected to last 3 or more years and the CIN team is looking for a post-doctoral epidemiologist or statistician to lead the further development of neonatal quality of care metrics and evaluate the changes in quality and outcomes of care over time and place. The CIN neonatal data comprise approximately 20,000 inpatient episodes per year with mortality rates in these wards of over 10%. This unique dataset will provide the post-holder with a unique research opportunity with findings that will be important nationally and globally.
The post-holder will work with a PI and Senior Scientist.
In particular, the CIN management team and the Neonatal group expects the post-holder will lead work (approximately 80% of their time):
- To optimise individual quality of neonatal care measurement indicators, and potentially develop composite indicators for the inpatient neonatal population
- To employ indicators developed to characterise hospitals’ quality of care and explore the variation in quality across hospitals and factors associated with this variation (work will require use of multiple imputation methods)
- To develop and apply time-series top evaluate the effects of health service interventions on the quality of hospital care over time and how this may vary across place & time
- To examine the links between quality of care and mortality at individual patient level
They will also contribute ideas and offer senior support to a large data science and analytics team that supports the paediatric and neonatal network activities that is continuously innovating as the CIN evolves as an example of a learning health system. This aspect of their role will be in a more supervisory role, including as appropriate contributions to PhD and MSc student supervision, and likely include (approximately 20% of their time):
- Contributions to the improvement of data analyses and infographics used to provide hospitals with regular feedback reports on the quality of care they provide
- Providing support to the development and testing of neonatal prognostic scoring tools and their use in case-mix adjustment of mortality outcomes
- Contributing to the development and implementation of new tools for data capture of inpatient and post-discharge growth for babies discharged from New born Units and providing support to more junior team members as these indicators are explored
- To provide support in statistical programming linked to data management of CIN and other projects
- To provide support to hospital-based teams who wish to develop local research reports
REPORTING LINES: Principal Investigator and Senior Scientist
- Take a leading role in optimizing specific and composite indicators for measuring the quality of in-patient neonatal care
- Using the indicators identified undertake analyses that evaluate the quality of neonatal care provided in CIN hospitals and explore the reasons for any variation observed
- Using the indicators identified undertake analyses on any changes in the quality of care that take place over time in response to improvement interventions and explore any apparent variation across hospitals and over time
- Using the indicators identified examine the relationship between quality of care and outcomes on hospitals’ neonatal units
- Lead the writing of manuscripts based on these analyses for submission to international peer-reviewed journals and present findings at national and international meetings
- Contribute in a general supervisory / advisory role together with senior clinical researchers to developments in the processes of data capture, management, security and analyses for CIN
- Supervise and mentor junior researchers including those undertaking MSc studies and, depending on experience, offer support to PhD students
- Contribute to the development of future funding proposals including, where appropriate, their own fellowship applications or proposals on which they are senior co-investigators
- PhD in Epidemiology / Statistics or PhD in Public Health with a strong element of epidemiological analysis
- Good understanding of the field of child or neonatal health or quality of care evaluation
- Advanced skills in use of R or STATA
- Familiarity with advanced methods for regression and time-series analyses ideally involving use of multi-level (hierarchical) models.
- Demonstrated ability to write and publish papers in the international peer-reviewed literature
- Good communication and presentation skills (use of powerpoint or other media)
- Ability to work with limited supervision
- Ability to meet deadlines
- Skills in use of data capture software tools such as REDCap
- Familiarity with GitHub and its use as a repository of analytical code
- Knowledge of statistical programming approaches
- Advanced data management skills – ideally experience with large databases including understanding of data dictionaries
- Experience of supervising junior scientists
Open plan seating arrangement in a quiet office space
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All applicants are required to state their current/last salary.
Candidates must supply an email and telephone contact that will be used when offering interviews. Only shortlisted candidates will be contacted. Shortlisted candidates shall be required to produce ORIGINALS of their National Identity Card, academic and professional certificates, original transcripts and testimonials, detailed curriculum vitae and valid clearance certificate (certificate of good conduct) during the interviews.
The application closing date is 6th March 2020
KEMRI-Wellcome Trust Research Programme (KWTRP) is an equal opportunity employer. Direct or indirect canvassing will lead to automatic disqualification. KWTRP does not charge a fee at any stage of the recruitment process (application, interview, meeting, processing, training or any other fees).