How to gain public trust in health data?

Health data has a huge potential to promote medical research, healthcare delivery, and public health outcomes in the current digital era. However, to fully realize this potential, the public must have faith that their health information is being collected, stored, and used in a responsible manner. Building and maintaining such trust is essential to creating a partnership that benefits patients, healthcare providers, and data custodians. In this essay, we examine how critical it is to gain the public’s trust in health data and we highlight the essential guidelines for establishing the groundwork for moral data practices.

What is medical data?

Health data is individual information regarding their physical condition or any medical treatment. This data contains a wide range of information:

Personal information is a person’s identity, their name, date of birth, gender, contact number, etc.
Information on a person’s medical history, including past diseases, diagnoses, treatments, surgeries, medications, and allergies, is referred to as health information.
Vital Signs: Measurements of vital signs, such as blood pressure, heart rate, respiration rate, body temperature, and oxygen saturation levels, may be included in health information.
Results from diagnostic tests performed in laboratories, such as blood tests, imaging scans (X-rays, MRI, CT scans), pathology reports, genetic tests, and other diagnostic procedures, are included in this category.
Electronic Health Records (EHRs): EHRs store detailed health information about patients, including demographics, medical history, medication, and immunization history, and comments from medical staff.
Wearable and Sensor Data: With the development of wearable technology and sensors, health data now also includes information gathered from smartwatches, fitness trackers, and medical equipment that monitors factors such as glucose levels, sleep patterns, heart rate variability, and physical activity.
Information on an individual’s health-related behaviors, such as smoking, drinking, exercise routines, diet preferences, and mental health conditions, is included in the category of health behavior and lifestyle data.
Information about health insurance: Information on health insurance coverage, claims, and billing can also be included in health data.

When collected, handled, and analyzed appropriately, health data has a tremendous deal of promise to advance medical research, public health efforts, and individualized healthcare solutions.

What were the problems when it was first introduced?

Several problems and difficulties arose as a result of the introduction of the early adoption of digital formats for the collection of health data. Here are some significant issues that surfaced in the beginning:

The digitalization of medical records raises concerns about data security and privacy. Sensitive personal health data held electronically increased the danger of identity theft, data breaches, and unauthorized access. Because there weren’t enough security precautions in place, people’s health information’s confidentiality and privacy were put at risk.
Interoperability and Data Fragmentation: Health data was frequently dispersed throughout numerous healthcare organizations, clinics, hospitals, and laboratories, leading to data fragmentation. Comprehensive patient care was hampered by the inability to communicate and combine health information due to a lack of interoperability and standardized data formats.
Digital health data were introduced, raising concerns about user consent and control over their information. Many people were not aware of the methods being utilized to gather, use, and share personal data. People felt powerless and had ethical issues due to the lack of control and choices for withdrawing consent.
Data integrity and accuracy: Digital health data was prone to mistakes, inaccuracies, and discrepancies. The reliability and integrity of health data were undermined by data entry errors, duplicate entries, and insufficient information, which had an impact on clinical decision-making, research outputs, and public health programs.
Data governance and legal frameworks: At the beginning of the introduction of health data, the legal and regulatory frameworks were not well-established. Because of the ambiguity around data ownership, sharing privileges, and data custodian obligations, there were no clear rules or regulations in place.
Ethical Issues: The gathering and use of health data brought up moral conundrums. An important problem was striking a balance between the right to personal privacy and the necessity of data-driven research and public health actions. It required careful study and adherence to ethical standards to make sure that health data was utilized in a way that honored human autonomy, consent, and confidentiality.
Trust and Public Perception: The public’s initial reaction to the advent of health data in digital formats was one of skepticism and mistrust. Data breaches, information misuse, and a lack of openness raised growing concerns.

How to gain public trust in health data?

Trust is built on a foundation of transparency, and informed consent is that foundation. The collection, use, and preservation of health data must be outlined in transparent policies and practices that are put into place by healthcare organizations and data custodians. People must be made aware of the reason for data collection, any dangers or advantages, and the parties responsible for processing the data. Additionally, customers are offered the option of sharing or not sharing their health information once they have given their informed consent following a thorough explanation of the data’s use and any potential repercussions.
Gaining the public’s trust requires safeguarding the confidentiality and privacy of health data. Strong data security measures, such as encryption, access controls, and secure storage systems, guard against unauthorized access, breaches, and misuse. Organizations should adhere to stringent data protection standards, such as the General Data Protection Regulation (GDPR), the Health Insurance Portability and Accountability Act (HIPAA), or other pertinent local regulations, to ensure that data is handled responsibly and in accordance with legal requirements.
The anonymization or de-identification of health data is a crucial step in privacy protection. By eliminating or encrypting personally identifying information (PII), such as names, addresses, and social security numbers, it becomes far more challenging to link health data to specific individuals. Strict anonymization processes should be implemented to preserve individual privacy while preserving the data’s usefulness for research and analysis.
Accountability and Data Governance: The development of effective data governance frameworks encourages accountability and fosters public trust in the use of health data. Data stewards should be appointed by organizations to oversee data management, enforce rules, and guarantee compliance. Regular audits and assessments assist maintain high levels of data governance by identifying risks, filling any gaps in data protection, and addressing any issues.
Revocation of consent and data rights: Respecting people’s rights to their data fosters confidence and gives them the ability to keep control of their information. Transparency and accountability are strengthened by making accessible ways for people to simply withdraw consent and update their data preferences. To enable people to exercise their rights and keep faith in the data custodians, organizations should provide straightforward ways for them to view, edit, or delete their health data.
Ethical Research and Cooperation: All health data research and cooperation initiatives must be guided by ethical considerations. Researchers must follow accepted ethical standards, get the proper institutional review board approvals, and make sure their work advances people’s welfare and the interests of society at large. Collaboration efforts ought to put open communication, data-sharing agreements, and ethical data use first.

Conclusion

The process of gaining the public’s trust in health data is ongoing and necessitates dedication to ethical data practices. Building this trust is based on transparency, privacy protection, data governance, and individual rights. Healthcare organizations, researchers, and data custodians may foster an environment where people feel empowered to contribute their health data for the benefit of society by adopting these principles and ensuring that data is acquired, utilized, and shared ethically. The entire promise of data-driven healthcare will ultimately be realized by encouraging public trust in health data, which will spur innovation, enhance healthcare outcomes, and unleash new possibilities.

References

Evidence-based guiding principles to build public trust in personal data use in health systems: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9297454/
Assessing changes in US public trust in science amid the COVID-19 pandemic: https://pubmed.ncbi.nlm.nih.gov/32405095/
Framework for assessing governance of the health system in developing countries: gateway to good governance: https://pubmed.ncbi.nlm.nih.gov/18838188/
Limits of data anonymity: lack of public awareness risks trust in health system activities: https://pubmed.ncbi.nlm.nih.gov/34304736/