This paper introduces a novel approach that combines multiple techniques, namely LWT (Lifting Wavelet Transform), SVD (Singular Value Decomposition), and BCM (Beta Chaotic Map), to create a hybrid robust watermarking method. The proposed method starts by decomposing the medical image into sub-bands ( \(LL_{1}\) , \(LH_{1}\) , \(HL_{1}\) and \(HH_{1}\) ) using 2-level LWT. Next, the watermark is embedded by fusing the orthogonal singular value of the watermark with the orthogonal singular value of the low-frequency sub-band ( \(LL_{1}\) ) of the cover image, utilizing a scaling factor \(\alpha \) . To enhance security, the watermarked image is encrypted using BCM. The encrypted image is decrypted using the same BCM key for watermark extraction. The watermarked image is then decomposed using 2-level LWT. Finally, the extraction singular value is computed using \(\alpha \) and inverted to obtain the extracted watermark. To achieve a balance between imperceptibility and robustness, the evaluation of the proposed method incorporates metrics such as PSNR (Peak Signal-to-Noise Ratio), SSIM (Structural Similarity Index), and NC (Normalized Correlation). The paper aims to demonstrate a reliable watermarking method that offers a good trade-off between imperceptibility and robustness in securing medical images in smart healthcare systems.