Electronic health records (EHRs) are increasingly employed to maintain, store and share varied types of patient data. The data can also be utilized for various research purposes, such as clinical trials or epidemic control strategies. With the increasing cost and scarcity of healthcare services, healthcare organizations feel at ease in outsourcing these services to cloud-based EHRs. That serves as pay-as-you-go (PAYG) "e-health cloud" models to aid the healthcare organizations handling with existing and imminent demands yet restricting their costs. Technologies can host some risks; hence the privacy of information in these systems is of utmost importance. Regardless of its increased effectiveness and growing eagerness in its adoption, not much care is being employed to the privacy issues that might arise. Privacy preservation need to be reviewed about the changing privacy rules and legislations regarding sensitive personal data. Our work aims at answering three major questions: firstly, how privacy models and privacy techniques correlate with each other, secondly, how we can fix the privacy-utility-trade off by using different combinations of privacy models and privacy techniques and lastly, what are the most relevant privacy techniques that can be adapted to achieve privacy of EHR on cloud.