Nanopore sequencing is becoming increasingly commonplace in clinical settings, particularly for diagnostic assessments and outbreak investigations, due to its portability, low cost, and ability to operate in near real-time. Although high sequencing error rates initially hampered the wider implementation of this technology, improvements have been made continually with each iteration of the sequencing hardware and base-calling software. Here, we assess the feasibility of using nanopore sequencing to determine the complete genomes of human cytomegalovirus (HCMV) in high-viral-load clinical samples without viral DNA enrichment, PCR amplification, or prior knowledge of the sequences. We utilised a hybrid bioinformatic approach that involved assembling the reads de novo, improving the consensus sequence by aligning reads to the best-matching genome from a collated set of published sequences, and polishing the improved consensus sequence. The final genomes from a urine sample and a lung sample, the former with an HCMV to human DNA load approximately 50 times greater than the latter, achieved 99.97 and 99.93% identity, respectively, to the benchmark genomes obtained independently by Illumina sequencing. Thus, we demonstrated that nanopore sequencing is capable of determining HCMV genomes directly from high-viral-load clinical samples with a high accuracy.