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Government & policy

Ontario seeks to improve quality of healthcare data

TORONTO –- As a method of raising the accuracy of data and improving access to information, Ontario’s government is establishing 14 Local Data Management Partnerships across the province, Health and Long-Term Care Minister George Smitherman announced.

“Quality patient care requires quality information,” Smitherman said. “We are building an information management system to support a new, patient-focused system of care that will consolidate, coordinate and standardize the way data are managed.”

The new Local Data Management Partnerships bring together health information management officials from hospitals and the community care sector in each of the 14 new Local Health Integration Networks. They will work together to identify best practices, standards, tools, and policies for better data quality and management.

“Information management is an area of health care that has suffered from decades of neglect,” said Dr. Adalsteinn Brown (pictured at left), Information Management Lead for the Ministry of Health and Long-Term Care’s Health Results Team. “This initiative is the first step in the implementation of a strategy that will lead to better information management in healthcare, and informed decisions made in the best interest of patients.”

“This is an opportunity to take a more integrated approach to data management that builds on informal approaches already used by hospitals and their partners to improve information sharing,” said Hilary Short, President and CEO of the Ontario Hospital Association. “This is an important step forward in providing our healthcare workers with the information they need to provide the safest care possible.”

The government has developed an Information Management Strategy which involves setting standards for data quality, better coordination of data collected by healthcare providers, and the consolidation of information into a common, integrated knowledge base.

It is focused on producing better data, supporting accountability and quality improvement through performance measurement, and supporting evidence-based decision-making.

“Information management is an area whose time has come,” said Jeff Lozon, President and CEO, St. Michael’s Hospital, Toronto. “From our perspective, information is vital in supporting our core functions of care, education and research. The implementation of a formal structure to improve the management of information, at a local level, is a step in the right direction for healthcare providers and the system alike. We look forward to contributing to this effort.”

This initiative is part of the government’s plan to build a healthcare system that delivers on three priorities -– keeping Ontarians healthy, reducing wait times and providing better access to doctors and nurses.

Some problematic areas for healthcare information collection in Ontario:

• Data on the use and efficiency of hospital care requires more than eight months to process – the same as it did in the 1960s.

• Right now there are nearly 100 separate health information databases in Ontario, many of which contain the same data.

• There are nearly 2,000 separate performance indicators in use in Ontario. Many are of limited use because they are either difficult to interpret, they provide only limited information, or they do not relate to the government’s key health priorities.

• Hospitals are submitting up to 200 separate data reports, some on a daily basis.

Health care in Ontario is an enormously complex system that depends on information. At the most fundamental level, it is used by doctors to decide on the best possible treatment options for their patients. At a system level, where decisions about the management and delivery of healthcare services are made, the data that healthcare providers across the province collect about patients is studied and analyzed to identify trends in population health, such as the incidence of stroke and obesity.

This evidence is then used to plan for and make decisions about which healthcare services will be provided where. Over the last decade, advances in technology have dramatically increased the capacity to collect, store and analyze a large volume of health-related data. The reality is that collecting all this data is placing a considerable burden on many healthcare providers.

With close to 100 separate health information databases in operation, healthcare planners, researchers and analysts are finding it more and more difficult to access the information they need. At the end of the day, when system planners and managers are looking to evaluate how the system is performing, the data itself is coming up short. Key pieces of information are missing to evaluate basic things like the quality of care overall in the province are missing.

The Ontario government has committed to breaking the cycle of ever-escalating health care costs by instilling a culture of accountability and improved outcomes – one that is tied to results. It needs accurate and comprehensive information to measure performance and provide a clear indication of the health system’s performance overall. Despite having more than 2,000 indicators in Ontario, many of these are of limited use because they are either difficult to interpret or they do not relate to the government’s health priorities.

The objectives of the new information management partnerships will be to:

• Make local data management processes more effective and efficient

• Improve the timeliness and quality of data

• Make more effective use of scarce health information management resources

• Encourage health care providers to adopt best practices.
The partnerships will be implemented in four phases, over a two-year period. Each phase will address a different area within the scope of activities related to health data management:

Phase I – Health records/health information management functions

Phase II – Financial data management functions

Phase III – Clinical data management functions

Phase IV – Primary care data management functions.

A provincial Data Management Council will be responsible for overseeing the four advisory committees that will be created for each phase of the partnerships as follows:

Phase I – Health Records Advisory Committee

Phase II – MIS Steering Committee

Phase III – Clinical Data Advisory Committee

Phase IV – Primary Care Advisory Committee

In Phase I, 14 Local Data Management Partnerships will be established in each of the province’s Local Health Integration Networks. Each partnership will include those responsible for health records/health information management from each hospital (e.g., the director of health records) and those responsible for health information management from each CCAC.

A chair for each partnership will sit on the provincial Health Records Advisory Committee. The committee will be responsible for recommending best practices and providing direction to the partnerships related to the collection and management of data. A representative from the Ministry of Health and Long-Term Care will chair this committee. Members will include Local Data Management Partnership chairs, as well as representatives from the various Health Information Management (HIM) programs and associations.

During Phase I, the partnerships will also be supported by the Physician Documentation Expert Panel and the Data Consistency Working Group.

The Physician Documentation Expert Panel is responsible for addressing documentation issues. The panel was established in September 2005, and is chaired by Dr. Ralph Kern, Assistant Professor of Medicine at the University of Toronto and Neurology Program Director at Mount Sinai Hospital. The panel will evaluate and promote changes to hospital physician education packages, medical school curricula and provincial policies related to chart completion, as well as identify other opportunities for improving chart documentation.

The Data Consistency Working Group will identify and promote opportunities to improve coding consistency and data quality. This group will include representatives from the partnerships and from organizations that use the data for purposes such as research and analysis.