The Effect of CMIA on Healthcare Informatics

The Effect of CMIA on Healthcare Informatics

The Confidentiality of Medical Information Act (CMIA) is a policy presently used in California to provide strong privacy protections for patients’ electronic medical information. Its purpose is to protect patient medical data, whether it is in electronic or paper format, from unauthorized disclosure. Second, CMIA applies to any individually identifiable health information that is collected from patients, which includes physical condition, treatment, medical, and mental health. Third, it offers protection for patients’ information, such as the person’s Social Security Number. Lastly, the policy allows California’s medical practitioners to combine publicly available patient information to reveal a person’s identity (Wallerstein et al., 2017). Following this discussion, the healthcare organization should introduce a policy regarding engaging the consumer in providing informed consent to protect health practitioners from ethical dilemmas that arise when sharing patient data with other relevant stakeholders The Effect of CMIA on Healthcare Informatics.


Impact of CMIA on System Implementation

Protection of Patient Data from Breaches

The policy requires that the HMIS system fulfill all regulations concerning protecting patient’s confidential data. However, most HIMS systems are not effective enough to protect patients’ electronic data against breaches. Thus, in the case of a data breach, the auditing teams will be required to conduct IT audits to determine whether the system is suitable for implementation or not (Wallerstein et al., 2017). In addition, the law requires that HMIS vendors design a system that can prevent data loss, especially involving a third party after a ransomware attack The Effect of CMIA on Healthcare Informatics.

Unauthorized Sharing of Data to Third Parties

It is a CMIA requirement that the HMIS should demonstrate the capability to protect patients’ personal information. The system should be tested whether it can protect patients’ personal information (Kotz et al., 2016). The system should protect confidential patient data against unauthorized disclosure to third parties, who can use the data to spy on patients.

Impact of CMIA on Clinical Care

Cost of the Management mHealth Systems

Due to weak health systems, it can be challenging for clinical practitioners to afford the cost of upgrading their systems to ensure patients’ data was secure. The CMIA restricts clinical practitioners from sharing data with third-party providers. Clinical data can only be shared among healthcare providers and other relevant stakeholders within a specific region (Genes et al., 2018). The failure to adhere to the policy’s requirements can increase clinicians’ damages for protecting patient data.

Protection of Patient Confidential Data

Clinicians have a role in protecting the patient data, such as by including consumer data preferences, which can further ease up the operating procedures at clinical centers (Akbar, Coiera & Magrabi, 2020). In addition, clinical practitioners and providers should demonstrate the capacity to handle the complex interplay of many stakeholders by giving patients the decision to choose how the data should be managed, which can help prevent patient confidentiality liabilities associated with CMIA regulations.

Impact of a Clinical Organization

A clinician who relies on the traditional information management model cannot know which personal data should be shared with other health-and-non-health providers. This can cause wide gaps for creative abstractions and interfaces that can lead to data breaches (Genes et al., 2018). Moreover, CMIA requires that clinicians ensure that patients are not fully informed about the health data they want to submit to healthcare organizations.

A Recommendation for Policies and Procedures

Outsourcing HMIS development to Competitive Data Companies

The first option will be to make the management of HIMS open to competitive private data companies. This implies creating a competitive environment for the creation of an effective health system with restricted access. (Akbar, Coiera & Magrabi, 2020). The organization can consider this option if the state currently has weak-security, health systems and is searching for the best companies to protect patient data from unauthorized access The Effect of CMIA on Healthcare Informatics.

Introducing Geofencing Policy

The second offer will be for the organization to set a different policy. For example, perhaps the organization can choose to deal with specific companies in the mobile phone sector that can offer health services instead of adopting a geofencing health system (Akbar, Coiera & Magrabi, 2020). This option can be good if the selected companies will cover most privacy and confidentiality needs of patients.

Informed Patient Consent

The third option the director can consider is investing in research and development. The hospital can allocate a budget for developing the geofencing of health systems. The policy will include recommendations for consumers on adding layers of security over the dissemination of their electronic health data within the state (Sampat & Prabhakar, 2017). This policy will have comprehensive details on how the patient data will be disseminated and engage the consumer in providing informed consent to protect health practitioners from ethical dilemmas that arise when sharing patient data with other relevant stakeholders.


Akbar, S., Coiera, E., & Magrabi, F. (2020). Safety concerns with consumer-facing mobile health

Applications and their consequences: a scoping review. Journal of the American Medical Informatics Association, 27 (2), 330–340.

Genes et al. (2018). From smartphone to EHR: a case report on integrating patient-generated

Health data. NPJ Digital Medicine, 1 (23), 1-6.

Kotz, D., Gunter, C.A., Kumar, S., &Weiner, J. P. (2016). Privacy and security in mobile health:

A research agenda. Computer (Long Beach, Calif), 49 (6), 22–30.

Sampat, B. H., & Prabhakar, B. (2017). Privacy risks and security threats in health apps.

Journal of International Technology and Information Management, 26 (4), 126-153.

Wallerstein, N., Duran, B., Oetzel, J. G., & Minkler, M. (2017). Community-based participatory

Research for health: Advancing social and health equity. San Francisco: John Wiley & Sons The Effect of CMIA on Healthcare Informatics.








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