Reducing the MRI outpatient waiting list through a capacity and demand time series improvement programme.

INTRODUCTION: A capacity and demand improvement initiative commenced in January 2019 with the goal of reducing the growing outpatient waiting list for magnetic resonance imaging (MRI) at Counties Manukau District Health Board (CMDHB). Initial work showed that the capacity (MRI machines and staff) actually outstripped demand, which challenged pre-existing assumptions. This became the basis for interventions to improve efficiency in the department. Interventions undertaken can be split into three distinct categories: (1) matching capacity to demand, (2) waiting list segmentation and (3) redesigning operational systems. METHODS: A capacity and demand time series during 2019 and 2020 was used as the basis for improving waiting list and operational systems. A combination of the Model for Improvement and Lean principles were used to embed operational improvements. Multiple small tests of change were implemented to various aspects of the MRI waiting list process. Staff engagement was central to the success of the quality improvement (QI) initiatives. The radiological information system (RIS) provided the bulk of the data, and this was supplemented with manual data collection. RESULTS: The number of people waiting for an MRI scan decreased from 1,954 at the start of the project to 413 at its conclusion-an overall reduction of 75%. Moreover, the average waiting time reduced from 96.4 days to 23.1. Achieving the Ministry of Health's (MoH) Priority 2 (P2) target increased from 23% to 87.5%. CONCLUSION: A partnership between Ko Awatea and the radiology department at CMDHB, examining capacity and demand for MRI and using multiple QI techniques, successfully and sustainably reduced the MRI waiting list over a two-year period. The innovative solutions to match capacity to demand may be instructive for other radiology departments, and other waiting list scenarios.

A new web-based Medication Error Reporting Programme (MERP) to supplement pharmacovigilance in New Zealand--findings from a pilot study in primary care.

AIMS: To determine if primary care clinicians would report medication errors using a new web-based system, and to obtain data illustrating the potential of the information collected to improve medication safety. METHOD: The New Zealand Pharmacovigilance Centre led the development of the Medication Error Reporting Programme (MERP) which was then piloted over an 8- month period involving 38 general practice and 28 community pharmacy staff. The Pharmacy Defence Association also contributed dispensing error claims. An analysis of the characteristics of errors was undertaken. RESULTS: A total of 376 reports were submitted; 55 (15%) reported patient harm, 1 of which required lifesaving intervention. The therapeutic groups most commonly implicated were medicines for managing 'nervous' and 'cardiovascular' systems. Wrong dose (25%) and wrong medicine (22%) were the most common error types, occurring predominantly with the prescribing and dispensing of medications. The most frequent contributing factors to errors in general practice were problems in the process of prescribing whereas in community pharmacy they related to product name and packaging factors. Time pressures, workload and interruptions were commonly cited for both settings. CONCLUSION: Primary care clinicians who volunteered for the pilot were willing and able to use the MERP system to report medication errors. The standardised data obtained through MERP enables rapid analysis and has the potential to inform initiatives for improving patient safety.

Aiming for zero: decreasing central line associated bacteraemia in the intensive care unit.

AIM: To eliminate Central Line Associated Bacteraemia (CLAB) in the Critical Care Complex (CCC)-Intensive Care Unit (ICU) and High Dependency Unit (HDU)-Middlemore Hospital. METHOD: Multifaceted quality improvement programme that included: engagement with ICU leadership and education of ICU staff; the introduction of a CLAB prevention bundle of care through standardised checklists for central line insertion (December 2008) and line maintenance (July 2009); the development of a central line pack; and rapid, visual feedback of results. RESULTS: Absolute numbers of CLAB in the CCC decreased from 14 in 2008, to 4 in 2009 and 1 in the first 6 months of 2010 (despite increase in bed census and a doubling of admissions). The CLAB rate per 1,000 line days decreased from 6.6 to 0.9. The days between CLAB increased from a median of 30 to >100 days, with zero CLAB for 5 of the last 6 months. Mortality for patients with CLAB was 37%, compared with mortality of 13% for all other ICU patients. The conservative cost savings were $200,000 in 2009 and $260,000 in 2010. CONCLUSION: Using an evidenced-based quality improvement approach, it is possible to significantly decrease Central Line Associated Bacteraemia in the Critical Care Complex. In doing so patient morbidity and mortality are reduced and money is saved for other healthcare needs.