With　the　help　of　Internet　technology,　digital　reform　of　the　medical　system　has　gradually　sprung　up　and　begun　to　reconstruct　the　medical　and　health　industry　chain　and　service　model,　which　has　brought　great　change　to　the　medical　industry.　At　present,　there　are　many　digitalization　solutions　of　medical　system　on　the　market.　However,　there　are　many　differences　in　the　technical　standards,　functions,　prices　and　service　objects　of　these　solutions,　and　the　objective　environment　is　uncertain.　At　the　same　time,　decision-makers　often　have　subjective　uncertainty　when　making　choices.　Therefore,　it　is　difficult　for　decision-makers　to　choose　the　most　satisfactory　one　from　many　digitalization　solutions.　To　solve　these　problems,　this　study　proposes　the　IVT-SFS　weighted　Muirhead　mean　(IVTSFWMM)　operator,　and　establishes　the　evaluation　and　decision-making　method　of　digitalization　solutions　of　medical　system　based　on　this　operator.　Then　we　apply　this　method　to　cases　and　select　the　best　performing　solution　from　the　four　existing　digitalization　solutions　of　medical　system　in　the　market　to　prove　the　effectiveness　of　the　method.　The　advantage　of　the　method　proposed　in　this　study　is　that　it　can　express　subjective　uncertainty　when　the　decision-maker　gives　the　evaluation　information　in　the　form　of　interval-valued　fuzzy　numbers,　and　the　interaction　between　any　number　of　indicators　can　be　considered　when　aggregating　indicators.　The　results　show　that　the　method　proposed　in　this　paper　can　effectively　express　the　fuzzy　evaluation　information　in　complex　environments,　and　provide　suggestions　for　system　designers　to　provide　decision　support　for　the　evaluation　and　selection　of　intelligent　medical　solutions.(c)　2022　Elsevier　B.V.　All　rights　reserved.