Public Health Intervention Initiatives

While some people are very aware of their health and attuned to early-warning signs of illness, disease, and disorders, many others aren’t. Health education and approaches to talking about health issues can vary among different demographics and wildly fluctuate among different ages, races, and cultures. Some even may find themselves with little ability to engage in public health systems due to language or cultural barriers.

Applications and Solutions: Data-based Health Intervention

Data is a powerful tool, and information about health trends among certain groups can allow public health systems to help people before they are afflicted by an issue. By taking a proactive approach, municipalities can engage communities before those communities are afflicted by a crisis – which can often result in a significant risk to safety and greater expenditure of resources.

Technologies

Trend Tracking – Surveys and other sources of data are a valuable tool, and municipalities may employ them (or data collected through them) to target certain communities for public health campaigns. Communities particularly affected by tobacco use, alcohol abuse, and/or obesity, for example, could be identified as at-risk so that the municipality may then develop programs to address.

Routine Data Collection – A wealth of data is collected simply through routine medical activities within provincial health systems. This data could potentially be used to track trends among geographic locations and specific demographics to better target citizens for public health campaigns relevant to their unique health risks.

Bulk Data – Bulk data such as those relating to health-related purchases can be used to draw conclusions about the general populace and track trends.

Algorithmic Risk Assessment – Algorithms combined with data on age, race, weight, height, etc., can be used to assess groups of people for potential health risks. Flagged individuals can be more closely monitored by healthcare professionals or may be asked to undertake additional tests more frequently .

Managing Liability Issues

Privacy

Issues.

⚠️ Health-related data must be considered in a sensitive context. Any data that could potentially identify individuals could be potentially problematic, given how private the nature of health data is.

Managing Issues.

✅ Ensure compliance with established regimes. Provinces may possess their own legislative regimes in relation with health-related data, such as the Personal Health Information Protection Act (PHIPA) in Ontario.

✅ Conduct annual audits and/or risk assessments. Doing so could raise issues of privacy that may not be examined otherwise.

✅ Anonymize data. While a certain amount of disclosure is necessary to ensure that the data is actually useful (i.e. age, weight, height, etc), unnecessary details should always be excluded.

✅ De-identify at the source. Extraneous information should not be gathered when data is being obtained for use in datasets if it is unnecessary.

✅ Provide notice and allow for opt-out. If data provided by an individual may be disclosed to different stakeholders, they should be informed of this disclosure, its nature, and scope. Objections should factor greatly into risk assessments and given heavy consideration.

✅ Consult stakeholders. Since intervention initiatives seek to function in specific communities, it logically follows that those communities should be consulted before any measures are put in place. They may be able to provide needed data or raise specific issues that were not previously considered.

✅ Use “heat maps”. Instead of specifically identifying where individuals are located at time of data collection, data can instead be collated into a specific area to further aid in anonymization.

✅ Follow good privacy practices.

Security

Issues.

⚠️ Security of data once it is collected is a key issue. Health data is particularly sensitive, and any data that is collected must be kept secure to protect privacy and prevent unauthorized access and identification of individuals.

Managing issues.

✅ Ensure compliance with established regimes. Provinces may possess their own legislative regimes in relation with health-related data, such as the Personal Health Information Protection Act (PHIPA) in Ontario.

✅ Institute privacy solutions. Many privacy solutions that seek to strip identifying data will also address issues of security.

✅ Hold data in a secure location. If data cannot be anonymized, it should be held in a secure location. This ensures individuals cannot be identified by it except in authorized situations.

✅ Limit access. Any collected user data should only be able to be accessed by those who need to use the information.

✅ Follow good security practices.