Teresa Scassa - Blog

Displaying items by tag: health information


It has been quite a while since I posted to my blog. The reason has simply been a crushing workload that has kept me from writing anything that did not have an urgent deadline! In the meantime, so much has been going on in terms of digital and data law and policy in Canada and around the world. I will try to get back on track!

Artificial intelligence (AI) has been garnering a great deal of attention globally –for its potential to drive innovation, its capacity to solve urgent challenges, and its myriad applications across a broad range of sectors. In an article that is forthcoming in the Canadian Journal of Law and Technology, Bradley Henderson, Colleen Flood and I examine issues of algorithmic and data bias leading to discrimination in the healthcare context. AI technologies have tremendous potential across the healthcare system – AI innovation can improve workflows, enhance diagnostics, accelerate research and refine treatment. Yet at the same time, AI technologies bring with them many concerns, among them, bias and discrimination.

Bias can take many forms. In our paper, we focus on those manifestations of bias that can lead to discrimination of the kind recognized in human rights legislation and the Charter. Discrimination can arise either from flawed assumptions being coded into algorithms, from adaptive AI that makes its own correlations, or from unrepresentative data (or from a combination of these).

There are some significant challenges when it comes to the data used to train AI algorithms. Available data may reflect existing disparities and discrimination within the healthcare system. For example, some communities may be underrepresented in the data because of lack of adequate access to healthcare, or from a lack of trust in the healthcare system that tends to keep them away until health issues become acute. Lack of prescription drug coverage or access to paid sick leave may also impact when and how people access health care services. Racial or gender bias in terms of how symptoms or concerns are recorded or how illness is diagnosed can also affect the quality and representativeness of existing stores of data. AI applications developed and trained on data from US-based hospitals may reflect the socio-economic biases that impact access to health care in the US. It may also be questionable the extent to which they are generalizable to the Canadian population or sub-populations. In some cases, data about race or ethnicity may be important markers for understanding diseases and how they manifest themselves but these data may be lacking.

There are already efforts afoot to ensure better access to high quality health data for research and innovation in Canada, and our paper discusses some of these. Addressing data quality and data gaps is certainly one route to tackling bias and discrimination in AI. Our paper also looks at some of the legal and regulatory mechanisms available. On the legal front, we note that there are some recourses available where things go wrong, including human rights complaints, lawsuits for negligence, or even Charter challenges. However, litigating the harms caused by algorithms and data is likely to be complex, expensive, and fraught with difficulty. It is better by far to prevent harms than to push a system to improve itself after costly litigation. We consider the evolving regulatory landscape in Canada to see what approaches are emerging to avoid or mitigate harms. These include regulatory approaches for AI-enabled medical devices, and advanced therapeutic products. However, these systems focus on harms to human health, and would not apply to AI tools developed to improve access to healthcare, manage workflows, conduct risk assessments, and so on. There are regulatory gaps, and we discuss some of these. The paper also makes recommendations regarding improving access to better data for research and innovation, with the accompanying necessary enhancements to privacy laws and data governance regimes to ensure the protection of the public.

One of the proposals made in the paper is that bias and discrimination in healthcare-related AI applications should be treated as a safety issue, bringing a broader range of applications under Health Canada regulatory regimes. We also discuss lifecycle regulatory approaches (as opposed to one-off approvals), and providing warnings about data gaps and limitations. We also consider enhanced practitioner licensing and competency frameworks, requirements at the procurement stage, certification standards and audits. We call for law reform to human rights legislation which is currently not well-adapted to the AI context.

In many ways, this paper is just a preliminary piece. It lays out the landscape and identifies areas where there are legal and regulatory gaps and a need for both law reform and regulatory innovation. The paper is part of the newly launched Machine MD project at uOttawa, which is funded by the Canadian Institutes for Health Research, and that will run for the next four years.

The full pre-print text of the article can be found here.

Published in Privacy

Given that we are in the middle of a pandemic, it is easy to miss the amendments to Ontario’s Personal Health Information Protection Act (PHIPA) and the Freedom of Information and Protection of Privacy Act (FIPPA) that were part of the omnibus Economic and Fiscal Update Act, 2020 (Bill 188) which whipped through the legislature and received Royal Assent on March 25, 2020.

There is much that is interesting in these amendments. The government is clearly on a mission to adapt PHIPA to the digital age, and many of the new provisions are designed to do just that. For example, although many health information custodians already do this as a best practice, a new provision in the law (not yet in force) will require health information custodians that use digital means to manage health information to maintain an electronic audit log. Such a log must detail the identity of anyone who deals with the information, as well as the date and time of any access or handling of the personal information. The Commissioner may request a custodian to provide him with the log for audit or review. Clearly this is a measure designed to improve accountability for the handling of digital health information and to discourage snooping (which is also further discouraged by an increase in the possible fine for snooping found later in the bill).

The amendments will also create new obligations for “consumer electronic service providers”. These companies offer services to individuals to help manage their personal health information. The substance of the obligations remains to be further fleshed out in regulations; the obligations will not take effect until the regulations are in place. The Commissioner will have a new power to order that a health information custodian or class of custodians cease providing personal health information to a consumer electronic service provider. Presumably this will occur in cases where there are concerns about the privacy practices of the provider.

Interestingly, at a time when there is much clamor for the federal Privacy Commissioner to have new enforcement powers to better protect personal information, the PHIPA amendments give the provincial Commissioner the power to levy administrative penalties against “any person” who, in the opinion of the Commissioner, has contravened the Act or its regulations. The administrative penalties are meant either to serve as ‘encouragement’ to comply with the Act, or as a means of “preventing a person from deriving, directly or indirectly, any economic benefit as a result of contravention” of PHIPA. The amount of the penalty should reflect these purposes and must be in accordance with regulations. The amendments also set a two-year limitation period from the date of the most recent contravention for the imposition of administrative penalties. In order to avoid the appearance of a conflict of interest, administrative penalties are paid to the Minister of Finance of the province. These provisions await the enactment of regulations before taking effect.

The deidentification of personal information is a strategy relied upon to carry out research without adversely impacting privacy, but the power of data analytics today raises serious concerns about reidentification risk. It is worth noting that the definition of “de-identify” in PHIPA will be amended, pending the enactment of regulations to that can require the removal of any information “in accordance with such requirements as may be prescribed.” The requirements for deidentification will thus made more adaptable to changes in technology.

The above discussion reflects some of the PHIPA amendments; readers should be aware that there are others, and these can be found in Bill 188. Some take effect immediately; others await the enactment of regulations.

I turn now to the amendments to FIPPA, which is Ontario’s public sector data protection law. To understand these amendments, it is necessary to know that the last set of FIPPA amendments (also pushed through in an omnibus bill) created and empowered “inter-ministerial data integration units”. This was done to facilitate inter-department data sharing with a view to enabling a greater sharing of personal information across the government (as opposed to the more siloed practices of the past). The idea was to allow the government to derive more insights from its data by enabling horizontal sharing, while still protecting privacy.

These new amendments add to the mix the “extra-ministerial data integration unit”, which is defined in the law as “a person or entity, or an administrative division of a person or entity, that is designated as an extra-ministerial data integration unit in the regulations”. The amendments also give to these extra-ministerial data integration units many of the same powers to collect and use data as are available to inter-ministerial data integration units. Notably, however, an extra-ministerial data integration unit, according to its definition, need not be a public-sector body. It could be a person, a non-profit, or even a private sector organization. It must be designated in the regulations, but it is important to note the potential scope. These legislative changes appear to pave the way for new models of data governance in smart city and other contexts.

The Institute for Clinical Evaluative Sciences (ICES) is an Ontario-based independent non-profit organization that has operated as a kind of data trust for health information in Ontario. It is a “prescribed entity” under s. 45 of PHIPA which has allowed it to collect “personal health information for the purpose of analysis or compiling statistical information with respect to the management of, evaluation or monitoring of, the allocation of resources to or planning for all or part of the health system, including the delivery of services.” It is a trusted institution which has been limited in its ability to expand its data analytics to integrate other relevant data by public sector data protection laws. In many ways, these amendments to FIPPA are aimed at better enabling ICES to expand its functions, and it is anticipated that ICES will be designated in the regulations. However, the amendments are cast broadly enough that there is room to designate other entities, enabling the sharing of municipal and provincial data with newly designated entities for the purposes set out in FIPPA, which include: “(a) the management or allocation of resources; (b) the planning for the delivery of programs and services provided or funded by the Government of Ontario, including services provided or funded in whole or in part or directly or indirectly; and (c) the evaluation of those programs and services.” The scope for new models of governance for public sector data is thus expanded.

Both sets of amendments – to FIPPA and to PHIPA – are therefore interesting and significant. The are also buried in an omnibus bill. Last year, the Ontario government launched a Data Strategy Consultation that I have criticized elsewhere for being both rushed and short on detail. The Task Force was meant to report by the end of 2019; not surprisingly, given the unrealistic timelines, they have not yet reported. It is not even clear that a report is still contemplated.

While it is true that technology is evolving rapidly and that there is an urgent need to develop a data strategy, the continued lack of transparency and the failure to communicate clearly about steps already underway is profoundly disappointing. One of the pillars of the data strategy was meant to be privacy and trust. Yet we have already seen two rounds of amendments to the province’s privacy laws pushed through in omnibus bills with little or no explanation. Many of these changes would be difficult for the lay person to understand or contextualize without assistance; some are frankly almost impenetrable. Ontario may have a data strategy. It might even be a good one. However, it seems to be one that can only be discovered or understood by searching for clues in omnibus bills. I realize that we are currently in a period of crisis and resources may be needed elsewhere at the moment, but this obscurity predates the pandemic. Transparent communication is a cornerstone of trust. It would be good to have a bit more of it.

Published in Privacy

Ongoing litigation in Canada over the recovery by provincial governments of health care costs related to tobacco use continues to raise interesting issues about the intersection of privacy, civil procedure, and big data analytics. A March 7 2019 decision by the New Brunswick Court of Queen’s Bench (Her Majesty the Queen v. Rothmans Inc.) picks up the threads left hanging by the rather muted decision of the Supreme Court of Canada in The Queen v. Philip Morris International Inc.

The litigation before the Supreme Court of Canada arose from the BC government’s attempt to recover tobacco-related health care costs in that province. The central issue concerned the degree of access to be provided to one of the big tobacco defendants, Philip Morris International (PMI), to the databases relied upon by the province to calculate tobacco-related health care costs. PMI wanted access to the databases in order to develop its own experts’ opinions on the nature and extent of these costs, and to challenge the opinions to be provided by provincial experts who would have full access to the databases. Although the databases contained aggregate, de-identified data, the government denied access, citing the privacy interests of British Columbians in their health care data. As a compromise, they offered limited and supervised access to the databases at Statistics Canada Research Data Centre. While the other tobacco company defendants accepted this compromise, PMI did not, and sought a court order granting it full access.

The Supreme Court of Canada’s decision was a narrow one. It interpreted the applicable legislation as making health care records and documents of individuals non-compellable in litigation for recovery of costs based on aggregate health care data. The Court considered the health databases to be “records” and “documents” and therefore not compellable. However, their decision touched only on the issue of whether PMI was entitled to access the databases to allow its own experts to prepare opinions. The Court did not address whether a defendant would be entitled to access the databases in order to challenge the plaintiff’s expert’s report that was created using the database information. Justice Brown, who wrote for the unanimous Court stated: “To be clear, the databases will be compellable once "relied on by an expert witness": s. 2(5)(b). A "statistically meaningful sample" of the databases, once anonymized, may also be compelled on a successful application under ss. 2(5)(d) and 2(5) (e).” (at para 36) In response to concerns about trial fairness, Justice Brown noted the early stage of the litigation, and stated that: “Within the Act, the Legislature has provided a number of mechanisms through which trial fairness may be preserved. Specifically, s. 2(5)(b) itself requires that any document relied upon by an expert witness be produced.” (at para 34) He also observed that:


[Section] 2(5)(d) permits a court, on application, to order discovery of a "statistically meaningful sample" of any of the records and documents that are otherwise protected by s. 2(5)(b). No defendant has yet made such an application and thus no court has yet had reason to consider what would constitute a "statistically meaningful sample" of the protected documents. (at para 35)

The Supreme Court of Canada therefore essentially laid the groundwork for the motions brought to the New Brunswick Court of Queen’s Bench under essentially similar legislation. Section 2 of New Brunswick’s Tobacco Damages and Health Care Costs Recovery Act is more or less identical to the provisions considered by the Supreme Court of Canada. Sections 2(5)(d) and (e) of the Act provide:

2(5). . .

(b) the health care records and documents of particular individual insured persons or the documents relating to the provision of health care benefits for particular individual insured persons are not compellable except as provided under a rule of law, practice or procedure that requires the production of documents relied on by an expert witness,

. . .

(d) notwithstanding paragraphs (b) and (c), on application by a defendant, the court may order discovery of a statistically meaningful sample of the documents referred to in paragraph (b) and the order shall include directions concerning the nature, level of detail and type of information to be disclosed, and

(e) if an order is made under paragraph (d), the identity of particular individual insured persons shall not be disclosed and all identifiers that disclose or may be used to trace the names or identities of any particular individual insured persons shall be deleted from any documents before the documents are disclosed.

Thus, the provisions allow for discovery of documents relied upon by the government, subject to an obligation to deidentify them.

An expert witness for the Province of New Brunswick had produced several reports relying on provincial health care data. The province maintained that for privacy reasons the defendant should not have direct access to the data, even though it was deidentified in the database. It offered instead to provide recourse through a Statistics Canada Research Data Centre. The defendant sought “a "statistically meaningful sample" of clinical health care records concerning 1,273 individual insured persons in New Brunswick, under the authority of subsections 2(5)(d) and (e) of the Act.” (at para 2) It also sought a production order for “all Provincial administrative databases and national survey data” that was relied upon by the Province’s expert witness in preparing his reports. In addition, they sought access to data from other provincial health databases that were not relied upon by the expert in his report – the defendant was interested in assessing the approaches he chose not to pursue in addition to those he actually pursued. The province argued that it had provided sufficient access to relevant data through the Statistics Canada RDC, which implemented appropriate safeguards to protect privacy.

Justice Petrie first considered whether the access via Statistics Canada was adequate and he concluded that it was not. He noted that one of the other defendants in the litigation had filed an access to information request with Statistics Canada and had thereby learned of some of the work carried out by the province’s expert witness, including some “calculations and analysis” that he had chosen not to rely upon in his work. While the defendants were not prejudiced by this disclosure, they used it as an example of a flaw in the system administered by Stats Canada since its obligations under the Access to Information Act had led to the disclosure of confidential and privileged information. They argued that they could be prejudiced in their own work through Stats Canada by access to information requests from any number of entities with interests adverse to theirs, including other provincial governments. Justice Petrie sided with the defendants. He found that: “the Province's production of the data and materials relied upon by Dr. Harrison only within the confines and authority of a third party to this litigation, StatsCan/RDC poses a real risk to the confidentiality and privilege that must be accorded to the defendants and their experts.” (at para 66) He also stated:


The risk of potential premature or inadvertent disclosure, as determined by StatsCan, presents an unfair obstacle to the defendants' experts if required to undertake their analysis only within StatsCan/RDC. In short, the StatsCan Agreement terms and conditions are overly restrictive and likely pose a serious risk to trial fairness. I am of the view that less restrictive options are available to the Court and ones that more fairly balance trial fairness with the risks to any privacy breach for individual New Brunswickers. (at para 65)

These less restrictive options stem from the Courts own power to “provide for directions on production and to protect the personal and sensitive information of individuals.” (at para 68) Justice Petrie found that “there are no applicable restrictions under privacy legislation to prohibit the Court from ordering document production outside of the StatsCan/RDC in the circumstances.” (at para 72) He rejected arguments that the Statistics Act prevented such disclosures, ruling that custody and control over the health data remained shared between the province and Stats Canada, and that the court could order the province to disclose it. Further, it found:


Where, as here, the Province has served the defendants with five expert reports of Dr. Harrison and indicated their intention to call him as a witness at trial, I find that subsection 2(5)(b) of the Act expressly requires production of the materials "relied upon" by the expert in the ordinary course. I am confident that the Court is capable of fashioning an order which would adequately address any privacy or reidentification concerns while, at the same time, imposing more balanced measures on the defendants and/or their experts. (at para 82)

These measures could include a direction by the court that no party attempt to identify specific individuals from the deidentified data.

On the issue of the disclosure of a statistically significant sample of health records, the defendant sought a sample from over 1200 New Brunswick patients. The legislation specifically provides in s. 2(5)(d) that a court may order discovery of a statistically meaningful sample of the documents”, so long as they are deidentified. Justice Petrie found that there was a statutory basis for making this order, so long as privacy could be preserved. He rejected the province’s argument that the only way to do this was through the Stats Canada RDC. Instead, he relied upon the court’s own powers to tailor orders to the circumstances. He stated: “I am of the view that there is a satisfactory alternative to the StatsCan/RDC Agreement on terms that can allow for any re-identification risks to be properly addressed by way of a consent order preferably, and if not, by way of further submissions and ruling of this Court.” (at para 131)

On the issue of privacy and the deidentified records in the statistically significant sample, Justice Petrie stated:


Even if individuals might be able to be re-identified, which I am not convinced, it is not clear why the defendants would ever do so. [. . .] With respect to this request for an individual's personal health records, the Province has suggested no other alternative to such a sample, nor any alternative to the suggested approach on "anonymization" of the information. (at para 141)

He granted the orders requested by the defendants and required the parties to come to terms on a consent order to protect privacy in a manner consistent with his reasons.

This decision raises issues that are more interesting than those that were before the Supreme Court of Canada, mainly because the court is required in this case to specifically address the balance between privacy and fairness in litigation. The relevant legislation clearly does not require defendants to accept the plaintiff’s analyses of health data at face value; they are entitled to conduct their own analyses to test the plaintiff’s evidence, and they are permitted to do so using the data directly and not through some intermediary. While this means that sensitive health data, although anonymized, will be in the hands of the defendant tobacco companies, the court is confident that the rules of the litigation process, including the implied undertaking rule and the power of the court to set limits on parties’ conduct will be sufficient to protect privacy. Although this court seems to believe that reidentification is not likely to be possible (a view that is certainly open to challenge), even if it were possible, direction from the court that no analyses designed to permit identification will take place, is considered sufficient.

Published in Privacy

The Supreme Court of Canada has issued its unanimous decision in The Queen v. Philip Morris International Inc. This appeal arose out of an ongoing lawsuit brought by the province of British Columbia against tobacco companies to recover the health care costs associated with tobacco-related illnesses in the province. Similar suits brought by other provincial governments are at different stages across the country. In most cases, the litigation is brought under provincial legislation passed specifically to enable and to structure this recourse.

The central issue in this case concerned the degree of access to be provided to Philip Morris International (PMI)to the databases relied upon by the province to calculate tobacco-related health care costs. PMI wanted access to the databases in order to develop its own experts’ opinions on the nature and extent of these costs, and to challenge the opinions to be provided by provincial experts who would have full access to the databases. Although the databases contained aggregate, de-identified data, the government refused access, citing the privacy interests of British Columbians in their health care data. As a compromise, they offered limited and supervised access to the databases at Statistics Canada Data Centre. Although the other tobacco company defendants accepted this compromise, PMI did not, and sought a court order granting it full access. The court at first instance and later the Court of Appeal for British Columbia sided with PMI and ordered that access be provided. The SCC overturned this order.

This case had been watched with interest by many because of the broader issues onto which it might have shed some light. On one view, the case raised issues about how to achieve fairness in litigation where one party relies on its own vast stores of data – which might include confidential commercial data – and the other party seeks to test the validity or appropriateness of analytics based on this data. What level of access, if any, should be granted, and under what conditions? Another issue of broader interest was, where potentially re-identifiable personal information is sought, what measures are appropriate to protect privacy, including the deemed undertaking rule. Others were interested in knowing what parameters the court might set for assessing the re-identification risk where anonymized data are disclosed.

Those who hoped for broader take-aways for big data, data analytics and privacy, are bound to be disappointed in the decision. In deciding in favour of the BC government, the Supreme Court largely confined its decision to an interpretation of the specific language of the Tobacco Damages and Health Care Costs Recovery Act. The statute offered the government two ways to proceed against tobacco companies – it could seek damages related to the healthcare costs of specific individuals, in which case the health records of those individuals would be subject to discovery, or it could proceed in a manner that considered only aggregate health care data. The BC government chose the latter route. Section 2(5) set out the rules regarding discovery in an aggregate action. The focus of the Supreme Court’s interpretation was s. 2(5)(b) of the Act which reads:

2(5)(b) the health care records and documents of particular individual insured persons or the documents relating to the provision of health care benefits for particular individual insured persons are not compellable except as provided under a rule of law, practice or procedure that requires the production of documents relied on by an expert witness [My emphasis]

While it was generally accepted that this meant that the tobacco companies could not have access to individual health care records, PMI argued that the aggregate data was not a document “relating to the provision of health care benefits for particular individual insured persons”, and therefore its production could be compelled.

The Supreme Court disagreed. Writing for the unanimous court, Justice Brown defined both “records” and “documents” as “means of storing information” (at para 22). He therefore found that the relevant databases “are both “records” and “documents” within the meaning of the Act.” (at para 22) He stated:

Each database is a collection of health care information derived from original records or documents which relate to particular individual insured persons. That information is stored in the databases by being sorted into rows (each of which pertains to a particular individual) and columns (each of which contains information about the field or characteristic that is being recorded, such as the type of medical service provided). (at para 22)

He also observed that many of the fields in the database were filled with data from individual patient records, making the databases “at least in part, collections of health care information taken from individuals’ clinical records and stored in an aggregate form alongside the same information drawn from the records of others.” (at para 23) As a result, the majority found that the databases qualified under the legislation as “documents relating to the provision of health care benefits for particular individual insured persons”, whether or not those individuals were identified within the database.

Perhaps the most interesting passage in the Court’s decision is the following:

The mere alteration of the method by which that health care information is stored — that is, by compiling it from individual clinical records into aggregate databases — does not change the nature of the information itself. Even in an aggregate form, the databases, to the extent that they contain information drawn from individuals’ clinical records, remain “health care records and documents of particular individual insured persons”. (at para 24)

A reader eager to draw lessons for use in other contexts might be see the Court to be saying that aggregate data derived from personal data are still personal data. This would certainly be important in the context of current debates about whether the deidentification of personal information removes it from the scope of private sector data protection laws such as the Personal Information Protection and Electronic Documents Act. But it would be a mistake to read that much into this decision. The latter part of the quoted passage grounds the Court’s conclusion on this point firmly in the language of the BC tobacco legislation. Later the Court specifically rejects the idea that a “particular” individual under the BC statute is the same as an “identifiable individual”.

Because the case is decided on the basis of the interpretation of s. 2(5)(b), the Court neatly avoids a discussion of what degree of reidentification risk would turn aggregate or anonymized data into information about identifiable individuals. This topic is also of great interest in the big data context, particularly in relation to data protection law. And, although it might have been interesting to know whether any degree of reidentification risk could be sufficiently mitigated by the deemed undertaking rule so as to permit discovery remains unexplored territory, those looking for a discussion of the relationship between re-identification risk and the deemed undertaking rule will also have to wait for a different case.

Published in Privacy

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