<p>Medical data, commonly known as patient health records (PHRs), contains medical images and related text information. Ensuring secure and efficient PHR transmission among hospitals and research centers is critical in the digital healthcare system. Current technology prefers cloud-based architecture for PHR transmission. Secure PHR transmission requires an efficient cryptographic architecture. Traditional cryptographic algorithms are complex and process images and text separately. The output is then stored in a single third-party cloud, making it susceptible to single-point attacks. This study introduces a simple, distributed framework for PHR transmission in digital healthcare applications to overcome single-point attacks. The proposed framework uses multiple-image secret sharing and data hiding for efficient and secure PHR transmission. Simulation results demonstrate the superiority of the proposed method in terms of the number of shares, the ability to combine images and text, better bit error rate, low operational complexity, improved security, and better reconstruction. Tabulated security parameters such as SSIM (<InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\approx \)</EquationSource> <EquationSource Format="MATHML"><math> <mo>≈</mo> </math></EquationSource> </InlineEquation>0), correlation of adjacent pixels (<InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(\approx \)</EquationSource> <EquationSource Format="MATHML"><math> <mo>≈</mo> </math></EquationSource> </InlineEquation>0), PSNR (<InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(\le \)</EquationSource> <EquationSource Format="MATHML"><math> <mo>≤</mo> </math></EquationSource> </InlineEquation> 8 dB), entropy (<InlineEquation ID="IEq4"> <EquationSource Format="TEX">\(\approx \)</EquationSource> <EquationSource Format="MATHML"><math> <mo>≈</mo> </math></EquationSource> </InlineEquation>8), NPCR (<InlineEquation ID="IEq5"> <EquationSource Format="TEX">\(\approx \)</EquationSource> <EquationSource Format="MATHML"><math> <mo>≈</mo> </math></EquationSource> </InlineEquation>0.996) and UACI (<InlineEquation ID="IEq6"> <EquationSource Format="TEX">\(\approx \)</EquationSource> <EquationSource Format="MATHML"><math> <mo>≈</mo> </math></EquationSource> </InlineEquation>35.49%) show that the proposed method exhibits the highest level of security. Similarly, tabulated human visual system parameters show better reconstruction.</p>