Competition Law and Healthcare Data Access and Competition

1. Introduction

Healthcare data access and competition concerns the relationship between control over health-related information and the ability of firms to compete in healthcare markets.

Healthcare data can include:

electronic health records (EHRs);

laboratory and diagnostic information;

prescription records;

medical imaging;

claims information;

pharmacy data;

genomic information;

clinical-trial information;

wearable-device information;

patient-generated health data; and

healthcare utilisation information.

Modern healthcare markets increasingly depend upon access to such information. A hospital may need data interoperability to change EHR providers; an AI company may require clinical datasets to develop diagnostic tools; an insurer may require claims information; and a digital-health application may require access to patient records.

Consequently, control over healthcare data can become a source of competitive advantage.

The central competition-law question is:

When does control over healthcare data become sufficiently important that restricting competitors' access can harm competition?

The answer depends upon market definition, dominance, indispensability, replicability, interoperability, foreclosure effects, legitimate privacy/security justifications and the specific conduct involved.

2. Why Healthcare Data Access Is Different

Healthcare data has several characteristics that make competition analysis particularly complex.

2.1 Sensitive information

Health information is highly sensitive. Competition law cannot simply require unrestricted disclosure of patient information.

2.2 Longitudinal value

A ten-year patient record can be considerably more valuable for some purposes than a single medical event.

2.3 Network effects

More healthcare participants can generate more data, potentially improving the value of the platform.

2.4 High switching costs

Moving thousands or millions of patient records between systems can be expensive.

2.5 Interoperability dependence

Healthcare providers often depend on technical standards and interfaces to exchange information.

2.6 AI significance

Large clinical datasets can be valuable for developing and testing AI systems.

Thus, healthcare data may simultaneously be:

a privacy asset + a clinical asset + a technological asset + a competitive asset.

3. Healthcare Data Access and Market Power

Possession of a large amount of data does not automatically establish dominance.

Competition authorities should consider:

quality of the data;

uniqueness;

volume;

timeliness;

accuracy;

geographic coverage;

interoperability;

replicability;

switching costs;

alternative data sources;

access to patients and providers;

network effects; and

the cost of obtaining comparable information.

For example, a dataset may contain millions of records but still be relatively easy for competitors to reproduce.

Conversely, a smaller dataset may be strategically important if it contains unique longitudinal information that cannot realistically be replicated.

4. Relevant Markets

Healthcare-data cases may involve several different relevant markets.

Possible upstream markets

EHR software;

healthcare data-management systems;

health-data interoperability;

medical databases;

diagnostic information systems.

Possible downstream markets

digital health;

AI diagnostics;

healthcare analytics;

insurance analytics;

telemedicine;

pharmaceutical research;

personalised healthcare.

The same conduct may therefore affect competition in more than one market.

For example:

EHR platform

↓ controls

patient data

↓ used to compete in

health analytics

This creates a potential leveraging problem.

5. Types of Healthcare Data Access Restrictions

Competition concerns may arise through several forms of conduct.

A. Refusal to provide access

A dominant provider refuses access to data or interfaces.

B. Discriminatory access

The provider gives its own affiliate better access than independent competitors.

C. Excessive access charges

A platform imposes commercially unreasonable fees.

D. Technical restrictions

The platform deliberately makes interoperability difficult.

E. Delayed access

Data is technically available but provided so slowly that competitors cannot effectively compete.

F. Exclusive arrangements

Hospitals or healthcare providers are contractually prevented from sharing information with competing platforms.

G. Tying

Access to one healthcare service is conditioned on purchasing another.

H. Data self-preferencing

A platform uses data obtained through its infrastructure to advantage its own competing service.

6. Refusal to Deal and Healthcare Data

The classic competition-law question is whether a dominant undertaking can be required to provide access to an asset controlled by it.

The law generally does not impose a universal duty to deal.

A refusal may become problematic under exceptional circumstances where, among other considerations:

the undertaking is dominant;

access is indispensable;

competitors cannot reasonably reproduce the facility/data;

refusal eliminates effective competition;

access is technically possible; and

there is no legitimate justification.

Healthcare data adds an additional requirement:

Any access remedy must comply with confidentiality, consent, cybersecurity and data-protection obligations.

7. Essential-Facilities Doctrine

The essential-facilities doctrine is particularly relevant to healthcare data access.

An asset is not "essential" merely because it is useful.

The important question is whether:

effective competition is realistically impossible without access to it.

For healthcare data, this might arise where a dominant infrastructure provider controls an interface through which virtually all relevant patient records must pass.

However, authorities must be cautious because declaring every commercially valuable dataset an essential facility could undermine incentives to invest in data collection and infrastructure.

8. Data Interoperability

Interoperability is one of the strongest mechanisms for reducing data-based market power.

Suppose:

Hospital A → EHR Platform X

A competing EHR platform wants to attract Hospital A.

If patient information can be transferred easily:

switching costs ↓

If the information is locked into Platform X:

switching costs ↑

Therefore:

Interoperability → lower switching costs → greater contestability

This is particularly important for healthcare because providers often accumulate years of information in a single system.

9. API Access

Application programming interfaces can determine whether third-party healthcare applications can interact with a platform.

A dominant EHR provider could potentially control access to:

patient records;

appointment information;

prescription data;

laboratory results;

billing information.

If third-party applications receive discriminatory access compared with the platform's own applications, competition concerns may arise.

However, restrictions justified by:

cybersecurity;

patient safety;

authentication;

fraud prevention;

regulatory requirements

may constitute legitimate justifications.

10. Data Portability

Data portability can mitigate lock-in.

Patients and healthcare providers may benefit from the ability to transfer information between competing platforms.

Competition benefits may include:

lower switching costs;

increased innovation;

easier entry;

greater consumer choice;

reduced incumbent power.

But portability must preserve:

accuracy;

privacy;

security;

patient consent;

authentication;

integrity of medical records.

11. Self-Preferencing

Consider a company that operates:

an EHR platform;

a health-data exchange;

an AI diagnostic service.

It might possess information about:

diagnostic patterns;

disease prevalence;

patient behaviour;

treatment outcomes.

If it gives its own AI product privileged access while competitors receive inferior access, competition concerns may arise.

This is analogous to the broader self-preferencing problem found in digital-platform competition law.

12. Data as a Barrier to Entry

A new healthcare analytics company may need substantial amounts of data before its products become commercially competitive.

An incumbent may already possess:

millions of patient records;

years of historical data;

provider relationships;

laboratory connections;

insurance information.

This can create a data-based entry barrier.

The concern is strongest where:

the dataset is unique + non-replicable + competitively important.

13. Exclusive Healthcare Data Agreements

Suppose a dominant healthcare platform signs exclusive contracts with major hospitals.

The agreements prevent those hospitals from providing comparable information to rival platforms.

Such arrangements could make entry substantially more difficult.

Competition analysis would consider:

duration;

scope;

market coverage;

availability of alternative hospitals;

importance of the data;

contractual necessity;

efficiencies;

foreclosure effects.

An exclusive arrangement is therefore not automatically unlawful.

14. Tying and Bundling

Healthcare platforms may offer several interconnected services:

EHR + cloud + analytics + billing + AI

A dominant provider could potentially condition access to one service on the purchase of another.

For example:

A hospital cannot obtain access to a particular EHR system unless it also purchases the provider's analytics service.

Where the legal conditions for tying or bundling are satisfied, this can raise abuse-of-dominance concerns.

15. Leveraging Across Healthcare Markets

Data access can allow a company to transfer market power from one market into another.

For example:

EHR dominance

↓

control over patient information

↓

AI diagnostic market

↓

competitive advantage over rival AI providers

This is a form of potential ecosystem leveraging.

The fact that the company is not dominant in the downstream AI market does not necessarily end the analysis; authorities may need to examine whether upstream power is being used to foreclose downstream competition.

16. Case Law 1 — IMS Health, Case C-418/01

Background

IMS Health operated a sophisticated system for organising pharmaceutical sales information. A competitor sought access to the structure because it was important for competing in pharmaceutical data services.

The European Court of Justice considered whether refusal to license intellectual property could constitute abuse of dominance.

Principle

The Court established stringent conditions for treating refusal to provide access as abusive.

Important considerations included:

indispensability;

elimination of competition;

inability to reproduce the facility;

absence of objective justification.

Healthcare Data Relevance

This case is highly relevant because healthcare data platforms may similarly claim proprietary rights over databases or systems.

The principle demonstrates that:

valuable healthcare information does not automatically have to be shared with competitors.

Access becomes a competition-law issue when the stringent conditions associated with exceptional refusal-to-deal situations are satisfied.

17. Case Law 2 — Bronner, Case C-7/97

Background

In Oscar Bronner v Mediaprint, the Court of Justice examined whether a dominant newspaper company was required to provide competitors access to its newspaper-delivery network.

Principle

The Court adopted a demanding approach to compulsory access.

The facility had to be effectively indispensable, with no realistic alternative and no reasonable possibility of duplication.

Healthcare Data Relevance

The reasoning is useful for healthcare infrastructure.

Suppose an EHR provider operates an important data-exchange system.

The question would be:

Can competitors realistically build or obtain an alternative data-access mechanism?

If the answer is yes, mandatory access becomes more difficult to justify.

If the system is genuinely indispensable, the analysis becomes more serious.

18. Case Law 3 — Slovak Telekom, Joined Cases C-165/19 P and C-165/19 P / related proceedings

Background

The Slovak Telekom litigation involved access to telecommunications infrastructure controlled by a dominant undertaking.

The European courts examined exclusionary conduct concerning access and competition in downstream markets.

Principle

The case is relevant to the relationship between:

control of an upstream infrastructure → competition downstream.

Healthcare Data Relevance

Healthcare data systems can similarly function as infrastructure.

For example:

EHR system → data access → healthcare applications

A dominant provider could potentially use control of the upstream system to restrict downstream competitors.

The case therefore provides an important analogy for infrastructure-based foreclosure.

19. Case Law 4 — Google Shopping

Background

Google operated a dominant general search service while also operating its own comparison-shopping service.

The European Commission found that Google favoured its own comparison-shopping service in search results.

Competition Principle

The case demonstrates the potential significance of discriminatory treatment where a platform both:

controls an important gateway; and

competes with businesses dependent upon that gateway.

Healthcare Data Relevance

Consider:

Health-data platform → controls access/ranking → competing health applications

If the platform systematically favoured its own healthcare applications through privileged access to data or ranking, Google Shopping provides a relevant analytical framework.

20. Case Law 5 — United States v. Microsoft

Background

Microsoft possessed substantial power in PC operating systems and was found to have engaged in exclusionary conduct affecting competing browser technologies.

Competition Principles

The case is important for:

network effects;

platform power;

technological barriers;

exclusionary arrangements;

leveraging.

Healthcare Data Relevance

EHR systems can develop comparable platform characteristics.

A dominant EHR platform may connect:

hospitals;

physicians;

pharmacies;

laboratories;

insurers;

patients.

Once a network becomes sufficiently entrenched, technical restrictions may make competing systems less attractive.

The Microsoft case therefore provides an important framework for examining platform-based foreclosure.

21. Case Law 6 — FTC v. Surescripts

Background

Surescripts operated an important electronic-prescribing network in the United States.

The FTC brought enforcement proceedings concerning alleged exclusionary practices and maintenance of monopoly power in electronic prescribing.

Competition Significance

The case is particularly useful because it concerns healthcare technology infrastructure.

Electronic prescribing exhibits network effects:

More doctors → more pharmacies → more usefulness → more users.

A dominant network can therefore become difficult for competitors to challenge.

Healthcare Data Access Relevance

The case illustrates how control over healthcare information infrastructure can influence competition.

It demonstrates that competition analysis should consider not only the immediate price of a service but also:

network participation;

access;

contractual restrictions;

switching;

infrastructure dependence.

22. Case Law 7 — Google Android

Background

The European Commission examined Google's contractual practices concerning Android and the distribution of applications and services.

The case involved questions of:

tying;

contractual restrictions;

ecosystem leverage;

foreclosure.

Healthcare Data Relevance

A healthcare technology company may similarly operate multiple interconnected services:

EHR + cloud + data exchange + analytics + AI

If access to one service is conditioned on using another, competition concerns can arise depending upon market power and competitive effects.

23. Case Law 8 — FTC v. Facebook/Meta

Background

The FTC's litigation concerning Facebook/Meta examined alleged exclusionary conduct and the role of network effects in social networking.

Competition Significance

The case illustrates how:

network effects;

scale;

user data;

switching costs;

entry barriers

can reinforce a platform's market position.

Healthcare Data Relevance

The same economic mechanism may arise in healthcare:

More hospitals/patients → more data → better service → more hospitals/patients.

The analogy is structural rather than sector-specific.

24. Case Law 9 — WhatsApp/Facebook Data-Sharing Proceedings in India

The Indian competition proceedings concerning WhatsApp's privacy policy are relevant to understanding how data practices can interact with competition law.

The Competition Commission of India considered whether WhatsApp's position and data-sharing arrangements could strengthen Meta's position in adjacent markets.

Relevance to Healthcare Data

The case demonstrates that data-related conduct can have competition implications beyond traditional price competition.

In healthcare, the stakes can be even greater because health data may be substantially more sensitive and commercially valuable.

However:

a data-sharing practice should not automatically be characterised as an antitrust violation merely because it involves personal information.

The competition effects must be established separately.

25. Case-Law Comparison

26. Healthcare Data and Competition in India

The Competition Act, 2002 provides several relevant provisions.

Section 3 — Anti-competitive agreements

Potential concerns include:

exclusive data agreements;

coordinated data-sharing;

market allocation;

agreements restricting interoperability.

Section 4 — Abuse of dominant position

Potential conduct includes:

discriminatory data access;

refusal of access;

denial of market access;

tying;

leveraging;

unfair conditions.

Sections 5 and 6 — Combinations

Healthcare-data acquisitions can raise merger-control concerns where a transaction combines:

large datasets;

important healthcare infrastructure;

EHR systems;

diagnostic technology;

AI capabilities.

27. Privacy and Competition Law

Healthcare data creates a fundamental tension.

Competition authorities may want:

greater data portability and interoperability

while privacy law may require:

strict control over disclosure and processing.

These objectives are not necessarily contradictory.

A competition remedy can potentially provide:

patient-controlled portability;

consent-based access;

standardised APIs;

secure authentication;

purpose limitation;

audit trails.

Thus:

Open competition does not mean unrestricted disclosure.

28. Data Access and Consumer Welfare

Greater healthcare data access can produce significant benefits.

For patients

easier switching;

continuity of care;

personalised treatment;

greater provider choice.

For healthcare providers

better interoperability;

improved clinical information;

reduced administrative costs.

For innovators

development of new applications;

AI research;

better analytics;

improved diagnostic tools.

For competition

lower switching costs;

reduced incumbent advantage;

easier market entry;

increased innovation.

29. Risks of Excessive Mandatory Data Sharing

Mandatory data access also creates risks.

1. Investment disincentives

Companies may have less incentive to invest in data infrastructure.

2. Privacy risks

Sensitive medical information could be improperly exposed.

3. Cybersecurity risks

More access points can create additional vulnerabilities.

4. Data quality risks

Poorly transferred information could affect clinical decisions.

5. Free-riding

Competitors might benefit from infrastructure they did not help develop.

Competition authorities therefore need to balance:

contestability + innovation incentives + privacy + security.

30. Data Access as a Competition Remedy

Where an antitrust violation is established, possible remedies could include:

A. Interoperability

Require technical compatibility.

B. Data portability

Allow authorised transfer of patient information.

C. Non-discriminatory access

Require comparable treatment of affiliated and independent applications.

D. API access

Provide standardised technical interfaces.

E. Data separation

Prevent certain competitively sensitive information from being transferred internally.

F. Behavioural restrictions

Prevent discriminatory ranking or access.

G. Structural remedies

In exceptional circumstances, separation of infrastructure from competing downstream services could potentially be considered.

31. Healthcare AI and Data Access

The issue becomes particularly important as healthcare AI expands.

An AI developer may require:

diagnostic images;

laboratory results;

clinical notes;

treatment outcomes;

genomic information.

A dominant healthcare platform that controls such data could obtain a significant advantage.

The competition cycle could become:

More data

↓

Better AI

↓

More hospitals

↓

More data

↓

Better AI

This is a powerful form of data-driven network effect.

32. Healthcare Data Marketplaces

Future healthcare ecosystems may develop dedicated data marketplaces.

A platform might connect:

Hospitals ↔ Researchers ↔ AI companies ↔ Pharmaceutical companies

Potential competition concerns include:

discriminatory access;

exclusive datasets;

preferential treatment;

excessive fees;

self-preferencing;

data aggregation;

vertical integration.

A dominant platform could potentially use control of the marketplace to advantage its own research or AI businesses.

33. Data Access and Merger Control

Competition authorities should examine whether mergers combine complementary assets that reinforce each other.

For example:

EHR company + AI company

could combine:

data + algorithm.

Or:

Wearable company + insurer

could combine:

behavioural health data + claims information.

Or:

Pharmacy platform + health-data platform

could combine:

purchasing data + clinical data.

The competitive effect may therefore be greater than the individual market shares of the merging firms suggest.

34. Key Questions for Antitrust Authorities

A comprehensive healthcare-data competition investigation should ask:

Who controls the data?

Is the data unique?

Is it indispensable?

Can rivals replicate it?

How expensive is replication?

Can patients transfer their information?

Are APIs available?

Are third parties treated equally?

Is there a dominant platform?

Is the platform vertically integrated?

Does it compete with users of its infrastructure?

Does it self-preference?

Are there exclusive arrangements?

Does the conduct raise switching costs?

Does it restrict innovation?

Are there legitimate privacy or security justifications?

Would access remedies undermine investment?

Could less restrictive remedies preserve competition?

35. Overall Competition Model

The competitive mechanism can be represented as:

Control of Healthcare Data

↓

Network Effects

↓

More Users and Providers

↓

More Data

↓

Better Analytics/AI

↓

Higher Switching Costs

↓

Entry Barriers

↓

Potential Market Power

The antitrust concern becomes strongest when a dominant undertaking adds exclusionary conduct to this natural data feedback loop.

36. Conclusion

Healthcare data access is becoming an important competition-law issue because modern healthcare markets increasingly depend on interoperability, data portability, digital infrastructure and AI.

The principal competition issues are:

refusal to provide data access;

denial of interoperability;

discriminatory APIs;

exclusive data arrangements;

data portability restrictions;

self-preferencing;

tying and bundling;

leveraging;

data-driven entry barriers;

healthcare-network effects;

data-based merger concerns;

algorithmic coordination; and

control over healthcare infrastructure.

The most useful authorities include IMS Health, Bronner, Slovak Telekom, Google Shopping, United States v Microsoft, FTC v Surescripts, Google Android, FTC v Facebook/Meta, and the WhatsApp/Facebook proceedings in India.

The fundamental principle is that control over healthcare data does not by itself create an antitrust violation. The critical inquiry is whether a firm's control over data or data infrastructure produces market power and whether that power is used to foreclose competitors, restrict market access, raise switching costs, suppress innovation or leverage dominance into adjacent healthcare markets, while taking legitimate privacy, security and investment considerations into account.