Health care taps analytics to support aging population

Call it the great northern seniors migration.

Those aren’t the words of Chris Sambol, but they epitomize a trend he describes: the composition of Sault Sainte Marie, Ont.’s population is quickly changing as as the elderly move into the northern Ontario city (from surrounding rural areas) for its health care services.

And as the number of seniors grow , those services must respond to the surge in demand, and they’re turning to technology to do so.

“Do you build more long-term care facilities? Do you build more resources to care for people at home?” says the manager of health and human services at the Sault Ste. Marie Innovation Centre. “Those are some decisions [being made] at this stage.”

Sault Ste. Marie’s average age is 44, compared to all of Ontario’s average of 39, according to Statistics Canada. Of the 62,500 residents over the age of 15 — 23,320 aren’t looking for employment, mostly because they’re already retired.  

The Innovation Centre’s approach to planning is to aggregate all that demographic data and map it over the entire community using GIS technology. By visualizing where elderly residents of the city live, it’s easier to determine where to target offerings and also avoid duplicating the efforts of various health services.

“People say a picture is worth a thousand words. A GIS image is worth a thousand pictures,” says Tom Vair, executive director of the centre. “It’s exciting to represent data in a geographic way.”

Working with Algoma Public Health and local city hospitals, the Centre helped a committee dedicated to the issue of elderly abuse identify key areas. Using demographic information on where their target audience was based, the committee sent out education packages to those who needed to know the information, and not to those who didn’t need to know.

It’s just one example of how analyzing data is playing a new role in Canadian health care planning. An ageing population isn’t a phenomenon restricted to northern Ontario, but a reality we witness coast-to-coast. As the baby boomer generation ages, it is inevitable that Canada’s public health care system will be called upon, as never before, to replace hips, help manage diabetes, and deal with all the other complications of ageing. With health care consuming a lion’s share of tax dollars and a tough economic environment, dealing with this trend efficiently is a critical government issue.

While news headlines of the day focus on diseases like swine flu, the real epidemic is unstoppable and fast approaching – people getting old.

Canada’s health care providers are tapping technology to deliver the services as efficiently as possible.

The massive public system has a backlog of data that holds the key to planning for the future – doctor’s notes, patient records, population demographics, and hospital charts. The answer to efficiency lies in the details, and powerful analytical software is being used to extract and display it in a useful manner.

“Health care organizations are trying to get the baseline data and understand the current situation,” Vair says. “You can use that information to go forward and plan accordingly.”

Before the data surrenders its forecasts, it needs to be collected from disparate sources and decanted in a way that makes sense. That’s where SAS Institute Inc. comes in – the business intelligences software company is no stranger to Canadian health care. The private company even has a health care advisory panel active in Ontario.

Out of the six large health authorities in British Columbia, three use SAS software, according to Brain Shorter, a healthcare consultant with SAS Canada. Those organizations are now starting to use their massive data sets for predictive modeling — ushering in a new era for the industry.

The Vancouver Island Health Authority, Vancouver Coastal Health Authority and Fraser Health Authority — all use the software.

“Health care for the longest time didn’t use forward-looking high-level statisticians,” Shorter says. “They tended to be more comfortable with historical data that shows disease and population data.”

SAS Forecast Studio was put to work in B.C., where the province had made reducing wait times a priority. As the list of patients waiting for hip surgeries grew and provincial budgets shrunk as a result of the recession, there was a sudden interest in detailed planning tools.

The situation was similar in the only other province to shorten waiting lists for certain critical surgeries – Ontario. SAS was asked by the Ontario government in 2007 to give a 15-year projection of hip surgery requirements. The company provided a team of experts as well as its predictive analytics software suite to tackle the problem.

The Ontario Ministry of Health and Long-Term Care announced in 2004 that it was actively working to reduce waiting times for hip replacement procedures. In 2002, Ontario surgeons performed 8,500 such operations – or 42 per cent of all hip surgeries performed in Canada. This number increased to 43 per cent from 1994 to 2004.

Ontario needed to know what to expect down the line.

The project was intended as a proof-of-concept, according to the ministry.

The aim being to demonstrate that software could be valuable as a forecasting platform. Ontario has other projects under development to create predictive models for future use of health care services and ageing is one of the variables that will be used in that equation.

“It’s been a fairly low priority item at many health care authorities for many years,” Shorter says. “But now the boards have become populated with people with some business acumen, demanding more scientific planning.”

SAS did provide month-by-month forecasts to Ontario for estimated hip surgeries to the year 2020. The final reports included confidence intervals, and standard error. The end result was achieved after collating a decade’s worth of records into 67 variables and overlaying population demographics by postal code.

Over in B.C., hip and knee surgeries have already hit levels the province had projected for 2010 and after cutbacks to health care, the province may want to consider a similar project to Ontario’s, Shorter says.

“They’re experiencing the same problem, and I don’t think as yet, that they’re nibbling at the solution,” he says. “Health care is always on the bleeding edge of just having enough money to survive. A small miscalculation can leave an organization without the resources to meet a population’s needs.”

It’s because of that urgent need that many health care authorities are starting to use technology to help plan for the future. The Niagara Health Services Organization uses SAS software when it condenses several health authorities into one body. In Waterloo, the Waterloo-Wellington Local Health Integration Network is working with the Sault Ste. Marie Innovation Centre to use GIS mapping to analyze its emergency room patients.

The project kicked off in April, Vair says. It’s starting with simple decisions, like where to put sand on the sidewalks in winter and where to ramp curbs for people in wheel chairs.

“We can look at where the Parabus picks up people in the community, where the seniors centres are,” Vair adds. “This project has got our team thinking about how GIS could be used for other health care applications.”

The centre is helping the province’s 14 Local Health Integration networks to coordinate a GIS technology taskforce to share best practices. Such a system could even be used to predict the number of chronic disease cases in a given area.

If the progress continues, then perhaps health care services will be brought to the older population that needs them instead of the older population coming to the health care services.

That might stop or reduce the Canadian seniors’ migration.

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