INTRODUCTION One of the greatest challenges in the healthcare field is planning the health workforce under limited financial resources while being fully capable of responding to an affordable, fair and efficient healthcare system. This study aimed to demonstrate the implementation process of the health workforce planning tool 'Workload Indicators of Staffing Needs' introduced by the World Health Organization. METHODS A descriptive and cross-sectional study was carried out at four (two public and two private) hospitals in Greece, to estimate midwifery staff requirements at ward level during 2015-2016, using the WISN software tool. Focus group discussions, structured interviews and annual service statistics from the hospitals' records were used to obtain data. RESULTS Results for both private hospitals showed a shortage in the number of midwives. However, after combining the interpretation of the results, as indicated by the WISN methodology and the structured interviews, current and required staffing is in balance in both. On the other hand, both public hospitals indicate a surplus of midwives (1.83 and 1.33 ratios for the General hospitals in Korinthos and Kalamata, respectively). CONCLUSIONS This study demonstrated the implementation process of the WISN methodology through its application in midwifery staff at four hospitals in Greece and confirmed its usefulness in estimating staffing requirements. The application of the WISN methodology should be viewed as a vital tool in assessing overstaffing and understaffing through the estimation of workload pressure among different categories of health staff, thus providing the basis for effective health workforce redistribution in Greece. AFFILIATION

The big-data revolution is creating a challenge for the provision of services in the health sector to keep pace with the expectations of the general population. Utilization of crowdsourcing can impact positively on the quality, cost and speed of healthcare by involving large sections of professionals and the public and creating novel science within an ethical framework. In 2007, the DYSCERNE project was funded by the European Commission Public Health Executive Agency (EU DG Sanco) aimed at setting up a network of expertise for rare dysmorphic disorders. As part of DYSCERNE, a Dysmorphology Diagnostic System was set up to enable clinicians throughout the EU to submit cases electronically for diagnosis using a secure, web-based interface, hosted at specified access points (submitting nodes), in 26 different European countries. DYSCERNE utilized the process of crowdsourcing international expertise for the clinical diagnosis of very rare genetic syndromes of multiple congenital anomalies. This is the first reported account of collaborative crowd sourcing in dysmorphology, as part of a clinical genetics service.