ISMETT – Best Quality Data Model FINALIST – 2018


ISMETT is an organ transplant centre developed in partnership between the Region of Sicily, the Civico and Cervello Hospitals in Palermo and the University of Pittsburgh Medical Center.

In 2013 it developed a Nursing Care Score system, built into the electronic health record to optimise nursing workload and staff allocation. The system takes 53 nursing work tasks and assigns them a score, this is then used to determine the nurse to patient ratio and the nurse’s tasks related to each patient. The outcomes have had a positive impact on nurse job satisfaction and the frequency of adverse events.


Briefly describe the organisation giving number of facilities, staff, revenue numbers.

Established more than 20 years ago, ISMETT is a government-approved research hospital (IRCSS) and center of excellence for organ transplantation and highly specialized therapies. ISMETT offers all solid organ transplant programs (liver, kidney, pancreas, heart, and lung) also from living donors, and its outcomes are in line with the top international centers. ISMETT has a total of 78 beds, 4 operating rooms and 8 beds in the day hospital units. Since the very first liver transplant performed in Sicily, in 1999, over 2,000 transplants have been performed at ISMETT. ISMETT offers top-level patient care and contributes to developing future health care through clinical and management innovation, research, and commitment to theoretical and hands-on training offered to all clinicians. In addition to UPMC, ISMETT collaborates with the most important Italian and international research centers, including collaborative projects with national research groups, international research groups, industries, NGOs, and other organizations. ISMETT is the first hospital in Southern Italy to receive Joint Commission International (JCI) accreditation, an advanced accreditation system that assesses the quality and safety of hospital facilities.

Please briefly describe the medical service, which the organisation is delivering in which it has deployed the best quality data model

A quality improvement (QI) initiative was conducted by an inter-professional team in the 33-bed cardio-thoracic unit of a 72-bed hospital in Palermo, Italy, with the aim to develop, implement, and evaluate a Nursing Care Score (NCS) system, built into the electronic health record, to optimize nursing workload and staff allocation.

Please describe the way the organisation has deployed and used the best quality data model.

How has it changed the way it collects and manages data?

A seven-phase process was used to develop, implement, and evaluate the NCS, which lists 53 nursing work tasks, each assigned a score from 1.5 to 5.0. The nurse-to-patient ratio on all shifts was determined by the NCS. The total score, obtained for each patient, determines the amount of nurse’s working tasks related to assigned patients during each shift (patient NCS). The sum of values, related to the 53 items of the scale, have a “0” to “170” range. The sum of all patients’ scores is then divided for the number of patients staying in the Unit, so as to obtain average NCS of a specific Unit. The average NCS is used for nursing patient assignments in such a way that each nurse has an equal average NCS.

What new quality data has the organisation created?

Before the beginning of each shift, all nurses and team leaders for each shift receive an e-mail with the NCS of the patients present on the unit, allowing for a more effective method of staff planning and approach to patient care.

How has that new quality data been used to change the way that health care services are delivered?

The results from this QI initiative have several implications for nursing practice. First,
optimal workload distribution may lead in the future to a reduction in stress and burnout
syndrome among nurses, and to improvements in job satisfaction, and consequently better
retention in the workplace. Second, since resourcing of nursing care is a very real concern for
nurse managers across the globe today, understanding the level of the nursing workload is
crucial in appropriate resource planning. Resource planning depends on adequate nursing
workload allocation, which is associated with lower rates of adverse patient outcomes that are
potentially nursing sensitive, such as urinary tract infections, pneumonia, shock, cardiac
arrest, upper gastrointestinal bleeding, failure to rescue, and length of hospital stay
(Needleman et al., 2002). Furthermore, a higher proportion of registered nurses is associated
with positive outcomes, such as lower rates of medication errors and hospital-acquired
infections (McGillis Hall et al., 2004).

Based on the results of this QI initiative, a number of recommendations for future QI initiatives
can be made. Patient outcomes, such as infection rates, pressure ulcers, and falls, could be evaluated pre- and post-implementation of the NCS system on other units to verify that the NCS system promotes safety and quality care for patients.

When did the quality data model start affecting service delivery?

  • Month : July
  • Year : 2013

What are the main key performance indicators? How does the organisation measure the success of the project?

Nurse satisfaction with both the existing system and the NCS workload system was assessed. Measuring staff satisfaction, overtime hours, and monitoring adverse events rate (Falls, Med errors, ulcers, HAIs).

Post-implementation questionnaire results indicated enhanced nursing satisfaction, as a result of appropriate and fair distribution of nursing work tasks among the nursing staff. The NCS proved to be a valuable tool for measuring workload in the unit.