Meta-consent allows patients to predefine under which circumstances their health data can be used in research. While this consent approach supports self-determination, its practical implementation remains hindered by challenges such as complexity and information overload. This study develops a patient-centered meta-consent framework for Germany addressing these challenges. Through a systematic literature review and representative survey (N=1534), we derive patient-centered decision dimensions encompassing the how, when, and what of data use for research, and patient factors, i.e., values and demographic characteristics influencing data-sharing decisions. We identified three patient types characterized by their patient factors: Privacy-Conscious, Science-Oriented, and Altruistic. Our analysis revealed that the perceived relevance of the decision dimensions varied by type. This allowed us to derive tailored recommendations to reduce complexity, i.e., by focusing on different dimensions per patient type. Future work can build upon our framework to implement meta-consent systems accommodating diverse user needs for informed data-sharing decisions.