OBJECTIVES: Bladder cancer (BC) can be life-long and requires intensive and routine monitoring and treatment, which makes it costly and impacts on patients' health perception. Hexaminolevulinate is a photosensitizing agent selectively absorbed by cancer cells which light up in red when illuminated with blue light, approved for improved detection and management of BC. The objective was to evaluate the cost-consequences of using Hexaminolevulinate-guided blue-light flexible-cystoscopy (HBLFC) as an adjunctive to white-light flexible-cystoscopy (WLFC), compared with WLFC alone, in the detection of non-muscle invasive BC (NMIBC) one year after diagnosis and recurrence.  METHODS: A cost-consequence model using a combination of a decision tree and Markov cohort state transition model structure was developed using a Swedish setting, Swedish guidelines and a hospital perspective. 231 patients were followed in an outpatient setting after diagnosed with NMIBC and successfully treated with an initial transurethral resection of bladder tumour (TURBT).The 231 patients were distributed across all risk groups. The model captured costs (2014 SEK) of surveillance and treatment of recurrence and progression over a 5-year period using 3-month-cycles.  RESULTS: The total cost over five years was marginally higher, 1.6%, for HBLFC (SEK 14,033,864) compared to WLFC (SEK 13,815,155) although cost-saving from year 2. HBLFC resulted in reduced resource demand versus the comparator (TURBTs: 121.4 vs 126.1; cystectomies: 56.3 vs 58.8; operating room [OR] time [hours]: 428.9 vs 447.4; bed days: 18.7 vs 19.5). High-risk patients represented the largest share of the costs but also the main benefits in clinical outcomes.  CONCLUSIONS: HBLFC was cost neutral over 5 years and reduced the number of bed days and OR time compared to WLFC alone, resulting mainly from fewer TURBTs and cystectomies. The greatest overall benefits were seen among high-risk patients, but other risk-groups are likely to benefit as well. Future model development will include quality-of-life data.