Performance Indicator Report

Health system performance is a shared responsibility. Improved performance takes the commitment of all health care providers working together to provide people with the best care, in the right place, at the right time. We are all in this together and we continue making strides to improve the health outcomes and care experience of the people we serve.

The HNHB LHIN Performance Indicator Report features information related to progress on its 14 Ministry-LHIN Accountability (MLAA) indicators. The Report is shared quarterly with the Quality & Safety Committee of the HNHB LHIN Board.

For consistency, some of the same measures and language the Ministry of Health and Long-Term Care (‘the Ministry’) uses in the MLAA are used here. This allows you to easily compare the information posted here with the information contained in our MLAA, annual reports, and the wait times section on the Ministry website. 

Performance Indicator Report

Performance Indicator Report

Performance Indicator Reports are posted below on a quarterly basis.


About the Ministry-LHIN Accountability Agreement (MLAA)

The MLAA is an agreement between the LHIN and the Ministry that outlines roles and responsibilities of each, including performance obligations for the local health system. Click here to read the most recent MLAA.

Health system indicators and provincial targets are set by the Ministry. LHINs and the Ministry negotiate LHIN targets based on evolving local circumstances. This is why MLAA targets may differ from year to year as circumstances change. A provincial target is an optimal performance result for an indicator, which may be based on expert consensus, performance achieved in other jurisdictions, Ministry expectations or trends over time.

Notes about Performance

  • The 90th percentile is the time that the 9th out of 10 patients waited. In other words, 90% waited less and 10% waited longer.

  • There may be instances where one hospital has unusually higher results compared to other hospitals. These differences could be influenced by a variety of factors including patient choice, patient availability, physician availability and operating room time. Further, the complexity of patients and sophistication of technology differs by hospital and thus can affect wait times. To understand the specific hospital variables, the hospital itself would need to be contacted directly.

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