Melisa Sayli

Dr Melisa Sayli


Postdoctoral Research Fellow
+44 (0)1483 684852
42 AD 02

Academic and research departments

Applied Microeconomics Group, Economics.

Publications

Giuseppe Moscelli, Marco Mello, Melisa Sayli , Adrian Boyle (2024)Nurse and doctor turnover and patient outcomes: a retrospective longitudinal study on English NHS acute hospitals, In: The BMJ / British Medical Association387 BMJ Publishing Group

Objective(s): To investigate the association between the monthly turnover rate of hospital nurses and senior doctors and health outcomes (mortality, unplanned readmissions) for patients admitted to hospital. Design: A retrospective longitudinal panel-data regression analysis, using nine years of monthly observations from rich administrative datasets at worker and patient levels. Associations using linear and unconditional quantile regressions were estimated, including controls for seasonality and hospital organisation. Participants: Yearly records on 236,000 nurses; 41,800 senior doctors (SAS doctors and hospital Consultants); and 8.1 million patients admitted to hospitals. Main outcome measures: Four hospital quality indicators (risk-adjusted by patient age, sex and Charlson index comorbidities) are used and measured at a monthly frequency on a % scale: mortality risk, in or outside the hospital, within 30 days from all-cause/emergency/elective admission to hospital; unplanned hospital emergency readmission risk within 30 days from discharge after elective hospital treatment. Results: A one standard deviation increase in nurse turnover rate is associated with 0.035 (95% CI: 0.024 to 0.045) and a 0.052 (95% CI: 0.037 to 0.067) percentage point increases respectively in all-cause and emergency admissions 30-day mortality risks. A one standard deviation increase in senior doctor turnover rate is associated with 0.014 (0.005 to 0.024) and 0.019 (0.006 to 0.033) percentage point increases respectively in all-cause and emergency admissions 30-day mortality risks. Higher nurse turnover rate is associated with higher 30-day mortality risk in surgery (p

Giuseppe Moscelli, Catia Nicodemo, Melisa Sayli, Marco Mello (2024)Trends and determinants of clinical staff retention in the English NHS: a double retrospective cohort study, In: BMJ Open14e078072 BMJ

Objectives To investigate how demographic, contractual and organisational factors are related to the retention of hospital workers in the English NHS. The study will specifically examine the trends in age-retention profiles. Design A double retrospective cross-cohort study using administrative data on senior and specialty doctors, nurses and midwives who were included in the 2009 and 2014 payrolls of all English NHS hospital Trusts. These individuals were tracked over time until 2019 to examine the associations between sociodemographic characteristics and the retention of hospital workers in each cohort. Logistic regressions were estimated at the individual worker level to analyse the data. Additionally, a multilevel panel regression was performed using linked payroll-survey data to investigate the association between hospital organisation characteristics and the retention of clinical staff. Setting Secondary acute and mental healthcare NHS hospital Trusts in England. Participants 70 777 senior doctors (specialty and specialist doctors and hospital consultants) aged 30–70, and a total of 448 568 between nurses and midwives of any grade aged 20–70, employed by English NHS Trusts. Primary outcome measures Employee retention, measured through binary indicators for stayers and NHS leavers, at 1-year and 5-year horizons. Results Minority doctors had lower 1-year retention rates in acute care than white doctors, while minority nurses and midwives saw higher retention. Part-time roles decreased retention for doctors but improved it for nurses. Fixed-term contracts negatively impacted both groups’ retention. Trends diverged for nurses and doctors from 2009 to 2014—nurses’ retention declined while doctors’ 5-year retention slightly rose. Engagement boosted retention among clinical staff under 51 years of age in acute care. For nurses over 50, addressing their feedback was positively associated with retention. Conclusions Demographic and contractual factors appear to be stronger predictors of hospital staff retention than organisational characteristics.

Anna Einarsdóttir, Karen A Mumford, Sudthasiri Siriviriyakul, Melisa Sayli (2023)Do I have to say I m gay? : Using a video booth for public visibility and impact, In: Qualitative research : QR23(6)pp. 1759-1780 SAGE Publications

Using data generated from a ‘video booth’, this paper explores how LGBT+ identifying individuals and allies navigate public visibility in front of a video camera. The video booth was set up in eight different NHS organisations in the UK to enable users to record short messages (30 s maximum) about their working life and/or experiences of LGBT+ employee networks, using a self-operated tablet system. The workplace context had an impact on how people represented themselves in front of the camera with prioritisation of professional identities and positive work-self. LGBT+ visibility was further masked by the inclusion of allies. We also discuss ethics and privacy issues related to using video booth methodology and signal how this methodology can best be used for future research purposes.

Giuseppe Moscelli, Melisa Sayli, Marco Mello, Alberto Vesperoni (2024)Staff engagement, coworkers' complementarity and employee retention: Evidence from English NHS hospitals, In: Economica Wiley

Retention of skilled workers is essential for labour-intensive organisations like hospitals, where an excessive turnover of doctors and nurses can reduce the quality and quantity of services provided to patients. Exploiting a unique and rich panel dataset based on employee-level payroll and staff survey records from the universe of English NHS hospitals, we empirically investigate the role played by two non-pecuniary job factors, staff engagement and the retention of complementary coworkers, in affecting employee retention within the public hospital sector. We estimate dynamic panel data models to deal with reverse causality bias and validate these estimates through unconditional quantile regressions with hospital-level fixed effects. Our findings show that a one standard deviation increase in nurse engagement is associated with a 16% standard deviation increase in their retention; and also that a 10% increase in nurse retention is associated with a 1.6% increase in doctor retention, with this coworkers' complementarity spillover effect driven by the retention of more experienced nurses. Nurse and doctor engagement is positively associated with managers who have effective communication, involve staff in the decision-making process, and act on staff feedback; in particular, older nurse engagement is responsive to managers caring for staff health and well-being.