Healthcare Quarterly
A Health Economic Analysis of the Potential in Transforming Canada’s Health Data Systems
Abstract
The goal of the Canadian Institute for Health Information (CIHI)'s transformation initiatives is to maximize the value of Canada's health data by ensuring that it is timely, connected, accessible, comprehensive, relevant, contextualized and trusted. This analysis draws on the academic and grey literature to estimate the high-level potential health economic value of health data interoperability, application of artificial intelligence (AI) and other technologies enabled by high-quality data and advancing secondary uses in the public and private sectors. Maximizing the use of health data could create financial value in excess of $9.4 billion annually, with patient health-related quality of life benefits of a similar magnitude.
Introduction
The current landscape
The global market for digital health products exceeded $270 billion in 2021 and is forecast to grow by over 20% annually through 2030 (Competition Bureau Canada 2022a). Health systems are estimated to produce over 30% of the world's data, but lag in their ability to manage that firehose, failing to ensure that data is available where, when and in the format needed. This difficulty creates an environment that can be described as “data-rich but information-poor” (OECD 2019).
Canada exemplifies this issue. In 2017, it scored eighth of the 26 Organisation for Economic Co-operation and Development (OECD) nations in openness of government data, buoyed by data availability (seventh), but lagging in terms of accessibility and reuse (11th) (OECD 2018). Its data is also highly fragmented across different organizations and levels of government (OECD 2015). A trove of data that could improve healthcare for Canadians, reduce costs and support innovation is therefore left underutilized.
Other nations have created major government initiatives focused on healthcare data collection, management and clinical use, including America's 21st Century Cures Act (Competition Bureau Canada 2022b), the UK's National Health Service Data Spine and Australia's My Health Record (Competition Bureau Canada 2022b). Investments have also been made in research and development (R&D) projects, such as the European Health Data Space.
The Canadian federal government has also invested, including $240.5 million to accelerate the use of virtual tools in healthcare and $505 million over five years for the creation of a Centre of Excellence on health worker data, to advance digital health tools and an interoperability roadmap, and to underpin efforts to use data to improve safety and quality of care. Barriers remain, however. In many provinces, healthcare data is locked into electronic medical record systems (EMRs) in a way that is not shareable, limiting interoperability and stifling competition and innovation (Competition Bureau Canada 2022b). While we possess most of the technical capacity for data sharing, syntactic and semantic interoperability capabilities lag (Lehne et al. 2019). Political and legal barriers also exist that fail to incentivize or actively discourage data sharing (Affleck et al. 2024).
The objective of this report is to provide a high-level picture of a future in which health data in Canada is used to its fullest potential, creating health benefits to patients, fiscal savings for the government and increased economic opportunity for Canadian health sector businesses.
Summary of CIHI transformation initiatives
CIHI has advanced the state of health information in Canada for the past 30 years. Building on the significant progress already made, CIHI's Transformation Agenda intends to accelerate the modernization of Canada's health data systems outlined in its 2022–2027 Strategic Plan (CIHI 2022) through a program of initiatives grouped around seven themes:
- Connected: Health data systems are interoperable; data are available in a usable format where needed.
- Timely: Near real-time data collection and use.
- Accessible: Streamlined access to the CIHI's data.
- Contextualized: Comparable and meaningful indicators to measure progress and identify areas for improvement.
- Trusted: Data flows across jurisdictions are safe and efficient. Respect Indigenous data sovereignty. Ensure that stakeholder needs are addressed.
- Comprehensive: Bring together datasets from diverse sources across the healthcare continuum.
- Relevant: Address high-priority data gaps, increase relevancy of indicators.
The themes are intended to foster innovation, support evidence-based policy development, improve clinical delivery and support economic opportunities in Canada's health technology sector. Many projects aligned with the Transformation Agenda are already underway, while the overall strategy was launched in the fall of 2024 and additional initiatives will be implemented in the coming years.
The work of transforming Canadian health data systems will involve many stakeholders, and the benefits achieved will be the result of a joint effort. The CIHI's Transformation Agenda involves partnering with stakeholders to form a more functional whole that serves Canadian's healthcare needs. Important partners in the transformation work include Canada Health Infoway and Statistics Canada, as well as federal, provincial and territorial governments and health agencies, Indigenous groups, patients, clinicians, researchers and private stakeholders, such as digital health vendors.
Approach
Initiatives under the CIHI transformation plan were grouped into categories based on the type of impact they could have on the healthcare system – care provision and administration, academic and commercial research and decision making and legislation.
The three overarching categories were used to inform a search of the academic and grey literature for quantitative estimates of the nature and size of those impacts, either in Canada or abroad. Calculations for obtaining quantitative estimates are presented in the Appendix found at here.
Results
Care provision and administration
Interoperability
Interoperability refers to the ability of data systems to interact so that external data are available to users within their own systems. For example, interoperable EMRs allow primary care physicians to see charts from interactions patients have across the acute care system. Interoperability ensures that clinicians do not miss key information, allows more reliable triaging of work within the clinical team and reduces time regathering information that already exists.
Canadian primary care physicians spend 37 avoidable minutes per day tracking down patient information not available in their practice's EMR, and only one-third are confident that they have adequate access to that information (Canada Health Infoway 2022). In 2019, fewer than a quarter of physicians had EMRs that could automatically notify them when their patients were discharged from the hospital, interface with home care data systems or share lab results, diagnostic imaging or prescriptions with colleagues electronically (Doty et al. 2020). In 2023, fewer than 40% reported being able to electronically exchange patient summaries, 29% below the average of Commonwealth countries (Canada Health Infoway 2023). Conversely, as of 2022, over 40% reported receiving patient information via fax (Canada Health Infoway 2022).
Interoperability improves system performance. For example, in emergency departments, it reduces unnecessary lab tests and diagnostic imaging, prevents admissions and reduces readmissions, producing significant cost savings per visit (Lammers et al. 2014; Saef et al. 2014; Vest et al. 2014a, 2014b; Winden et al. 2014). Integrating primary care EMRs with acute care can also reduce post-discharge office visits by more than half while cutting down onduplicate testing (Li et al. 2022).
System-level estimates of interoperability's financial/efficiency impact in primary and acute care
Canada Health Infoway estimates that although EMR modernization efforts to date have reduced spending by $1.5 billion, achieving full health data interoperability could save an additional $2.4 billion. Savings result from effective use of acute care space (e.g., preventing unnecessary admissions, faster discharges), more efficient ambulatory care and reduced lab testing and diagnostic imaging. Implementation of standard patient summaries transferable between EMRs alone could save approximately $950 million per year (Canada Health Infoway 2023).
Reducing unnecessary care via interoperability could save Canadians more than 50 million hours annually, with a value of $1.24 billion, as well as 5.7 million hours of provider time representing over $600 million of health system resources (Canada Health Infoway 2023).
Table 1 summarizes international estimates of interoperability's impact and scales them to Canada's healthcare system. They are significantly larger, relative to total spending, than Infoway's work. This partly reflects the more advanced state of interoperability in Canada in 2024 versus the comparator countries in the early 2000s.
| TABLE 1. International estimates of health data interoperability value | |||||
| Estimate | Year | Country | Impact | Percentage of national health expenditure | Canadian equivalent* |
| Canada Health Infoway | 2023 | Canada | $2.4 billion | 0.65% | NA |
| Hillestad et al. | 2005 | US | US$78 billion | 3.96% (Muñoz et al. 2010) | $14.7 billion |
| Walker et al. | 2005 | US | US$141–317 billion | 7.16–16.09% (Muñoz et al. 2010) | $26.6–59.9 billion |
| Wayman and Hunerlach | 2019 | UK | £4.6 billion | 2.04% (Office for National Statistics 2021) | $7.6 billion |
| Sprivulis et al. | 2007 | Australia | AU$3 billion | 2.89% (AIHW 2009) | $10.75 billion |
| *Based on total Canadian health system expenditures in 2024 from CIHI (2024c). | |||||
Primary and acute care interoperability – impact on patient outcomes
In a systematic review, 9 out of 10 studies examining the impact of health information exchange (HIE) on care quality found improvements, with reduced errors and improved compliance with preventive healthcare being key benefits (Menachemi et al. 2018). Interoperability's total potential patient benefits are difficult to systematically estimate because they depend on system context, but the examples below highlight key opportunities.
IT-related issues account for 47% of hospital errors, and of those, 8% are failures of interoperability (Adams et al. 2017; Fong et al. 2017). The event type most tied to interoperability is medication errors, the sixth leading cause of death in hospitals, caused by a lack of physician access to necessary information (Torab-Miandoab et al. 2023). Eliminating these errors in Canada (estimated 3,200 per year) would represent a gain of 1,560 quality-adjusted life years (QALYs) for patients (CIHI 2024a), for which the health system would typically be willing to pay up to $78 million.
HIE has also been found to increase colonoscopy compliance by 22% (Nagykaldi et al. 2014). Applying that increase to all Canadians aged 50–74 years could prevent 1,400 cancers and 600 deaths per year, for a gain of 2,500 QALYs valued at up to $126 million. Similar gains could be realized for mammography, another proven cost-effective intervention (Stout et al. 2006). HIE is also shown to improve vaccination rates and chronic disease management (Kern et al. 2012).
Community pharmacy data: an additional opportunity for interoperability
Data sharing has benefits beyond acute and primary care. In 2014, Taiwan implemented PharmaCloud, a system giving providers access to a patient's complete medication history across healthcare settings. Approximately three-quarters of patients had their records accessed in the following nine months. Compared with matched patients whose records were not accessed, prescription costs fell 13.8% relative to the period before implementation. In addition, the system flagged potential drug interactions for 7% of the patients and reduced medication duplication (Liao et al. 2019).
Medication review by community pharmacists has been found to reduce prescriptions in elderly patients with polypharmacy by a magnitude similar to that seen in the PharmaCloud implementation and to improve health-related quality of life as a result (Jódar-Sánchez et al. 2014; Sanyal and Husereau 2019).
A program similar to PharmaCloud in Canada could potentially save $3.6 billion in private and $200 million in social security spending (CIHI 2024c), and reducing polypharmacy could gain 64,900 QALYS worth up to $3.25 billion per year for patients.
Artificial intelligence and big data for administrative efficiency and quality of clinical care
The availability of standardized data also enables the implementation of technology to interpret and analyze the data, particularly AI/machine learning (ML). As of 2024, 86 randomized controlled trials (RCTs) had been published on the impact of AI on clinical outcomes, with 81% achieving positive results (Han et al. 2024). Economic evaluations of 21 studies had also been published (Vithlani et al. 2023). The majority had serious limitations, underscoring the fact that the study of healthcare AI is in its early stages, but five studies found the AI/ML tool to economically dominate standard care (improving outcomes while reducing cost), 10 found it to be cost-effective and two found it to be cost-saving without assessing quality.
As a Canadian example, a trial of AI monitoring to prompt early intervention by a critical care team on a general internal medicine ward reduced non-palliative deaths by 26%, roughly one death prevented per 200 admissions (Verma et al. 2024).
Economic modelling suggests that AI/ML could save 5–10% of healthcare labour time, divided roughly equally between reduced administrative burden and improved clinical efficiency (Sahni et al. 2023). Canada currently faces a health workforce emergency, with vacancy rates over 20% for key staff types (CIHI 2024d). Canada's spending on physicians, other health personnel and administration in 2024 was $58.2 billion, so 5% savings would represent $2.9 billion in critical resources freed up (CIHI 2024c).
Supporting Academic and Commercial Research
Commercial development
Pharmaceuticals and medical devices
Canada currently hosts 4% of global clinical trial sites and leads the Group of Seven (G7) in trials per capita (ISED 2022). Its large public health systems, with the potential for unified data, position it to grow the domestic pharmaceutical sector. Despite those advantages, as of 2010, Canada ranked 14 of the 17 OECD countries for health innovation (Snowdon et al. 2011). Private R&D spending in Canada has fallen as a share of gross domestic product (GDP) over the past three years and is currently sixth among the G7 (Statistics Canada 2024b). Pharmaceutical R&D spending in 2021 was $2.65 billion, with the whole pharma industry contributing $16 billion to GDP and supporting 103,000 jobs (Collins et al. 2024).
Canadian businesses identify data access as a barrier to growth (ISED 2020). In Europe, the EMR for Clinical Research (EMR4CR) program uses transnational pooled EMR data to facilitate enrollment, protocol development and adverse event reporting, creating an estimated €113 million of value per successful drug candidate through reduced costs and faster approval and market access (Beresniak et al. 2016; Dupont et al. 2016). Based on the number of trials facilitated, the program could create up to €3.75 billion in additional value on Europe's €30.5 billion annual R&D expenditure. Scaled to the Canadian sector, a similar system could create $330 million per year.
Such programs would also make Canada a more attractive investment target. Canada's Economic Strategy Tables, a program that fostered collaboration between industry and government on economic development, estimated in 2018 that Canada could double the size of its health and biosciences sector by 2025, increasing exports to $26 billion and venture capital investment to $2 billion, but identified data access as a key barrier to achieving that ambition (CEST 2018).
AI, big data and other health data businesses
Data is also an important business in itself. The top 50 healthcare AI startups globally raised US$8.5 billion in 2019. None were Canadian (Spatharou et al. 2020). However, it is worth noting that Canadian digital health startups did raise $300 million in 2020, a 100% annual increase (Karpathakis et al. 2024).
The federal government has invested nearly $200 million in developing support for AI businesses and pledged $2 billion to boost accessibility of computing power (Competition Bureau Canada 2022a; ISED 2024). Transforming a strong academic base and nascent startup market into a globally competitive industry will require addressing data access and quality, issues that AI executives and investors identify as major barriers to AI business development (Spatharou et al. 2020). Developing domestic industry has become more urgent as the ongoing tariff war between the US and most countries around the world creates an opportunity for Canada as a trusted partner for countries that may at present be hesitant to invest in American solutions.
Supporting academic research
Academic research also benefits from the availability of high-quality data, especially in the case of complex questions with important health and system efficiency implications (e.g., large-scale public health studies and analyses that take advantage of natural experiments [CCA 2023]).
Canada's spending on higher education R&D relative to GDP is the highest in the G7 and grew 8.7% in 2023 (Statistics Canada 2024b). Limitations on data access and usability hamper that investment's value. Stakeholders have expressed concerns that data issues hinder our competitiveness internationally, especially compared with the US, and researchers report opting not to pursue important inquiries due to concerns about feasibility (Aggarwal et al. 2024; Dahl et al. 2020).
In New South Wales, Australia, publications increased fivefold within five years after the introduction of linked health data (Tew et al. 2017). Data availability was cited by researchers as a key factor in attracting and retaining top research talent and helped Australia to become the top performer in a comparison of national healthcare research productivity, while Canada was in the middle of the pack (Hajjar et al. 2019; Holman et al. 2008).
The turmoil in the American research system has created an opportunity to attract talent, with 75% of American scientists in one poll considering international opportunities (Witze 2025). Commitment to provide access to high-quality data could play a role in attracting some of those researchers.
Supporting policy development and decision making
It is not possible to quantify the potential for quality-linked health data to support policy development in general, as it depends on specific policy choices in individual contexts, but examples from around the world show how data can inform policy.
In Australia, the availability of linked data has been used to flag technologies associated with increased readmissions, allowing their use to be suspended and preventing patient harm and unnecessary costs. It has also allowed tracking of the impact of government funding policies and has been used to help draft legislation to reform mental health care (Holman et al. 2008).
In the UK, national databases have been used both to develop new policies and to evaluate the effectiveness of existing ones. One example of the former is the use of comparative audit to identify characteristics of renal dialysis programs with lower costs and better outcomes, leading to the development of a national best practices standard. The latter includes the use of data to evaluate a triage and routing policy for patients with severe head trauma, which was found to reduce 30-day mortality by 43% (Black and Tan 2013).
Several OECD countries use national monitoring systems to assess health system performance and allocate funding to high-performing areas, or to flag areas at risk and ensure that they have adequate support (OECD 2019). While Canada's provincial health funding system may limit the ability to reallocate funds, improved national evaluation metrics could be used to identify practices in high-performing provinces for broad adoption.
Finally, high-quality data can help to prevent fraud and abuse. Based on data from seven OECD countries, these consume an average of 6% of healthcare spending. Data mining allows health systems to identify typical patterns of care and flag deviations for further screening when warranted (OECD 2017).
Summary and Conclusion
Table 2 summarizes the components of the value proposition for health data transformation to which specific financial estimates could be applied. Achieving the total will take time and investment and will require the maturing of emerging technologies such as AI.
| TABLE 2. Summary of potential financial impacts | |
| Area | Potential value |
| Impacts of data interoperability on direct patient care and administration | $2.4 billion+ |
| National pharmaceutical data interoperability | $3.8 billion |
| AI for administrative efficiency | $2.9 billion |
| Supporting health product commercialization | $0.3 billion |
| Total | $9.4 billion+ |
| AI = artificial intelligence. | |
In addition to financial benefits, transforming Canada's health data would improve outcomes and quality of life for Canadians. Interoperability could create health benefits with a willingness to pay value of several billion dollars per year, similar in scale to the financial benefits. Applying AI and other technologies in clinical decision support roles could increase that impact. Finally, health data transformation would improve the productivity of Canada's public and private R&D sectors and help to optimize decision making for the public health system.
Canada possesses the raw materials to be a global leader in the application of health data. Investments in EMRs have already been made, and we have governmental and academic institutions and commercial businesses that are ready to take the data generated and apply it to improve outcomes, minimize costs and fuel the growth of the Canadian economy. The missing piece is the ability to transfer, pool and use health data. If CIHI and its partners succeed in their transformation initiatives, the benefits will be substantial.
About the Author(s)
Thomas Mullie, MA, is a health economist at Acute Care Alberta in Calgary, AB, with experience studying Canadian healthcare systems in the private, public and academic sectors.
Anderson Chuck, Phd, is the Chief Executive Officer of Canadian Institute for Health Information (CIHI) in Ottawa, ON, and was formerly the chief health economist for Alberta Health Services in Edmonton, AB. Anderson can be reached by e-mail at achuck@cihi.ca.
Fahad Razak, MD, MSc, FRCPC, is the Canada research chair in data informed healthcare improvement at the University of Toronto in Toronto, ON, an internist at St. Michael's Hospital in Toronto, ON, provincial clinical lead at Ontario Health in Toronto, ON and a senior fellow at Massey College, Toronto, ON.
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