The　shortage　of　inpatient　beds　causes　surgery　cancellations,　treatment　delays,　and　inappropriate　ward　arrangements.　That　is　why　studying　how　to　make　admission　decisions　on　the　wards　of　crowded　units　under　premature　discharge　decisions　is　essential.　In　this　study,　we　set　up　an　infinite-horizon　total　discounted　cost　Markov　decision　process　model　to　minimize　the　total　expected　cost　to　the　hospital.　By　analyzing　the　structural　properties　of　the　optimal　value　function,　we　find　that　there　is　an　optimal　admission　control　policy　of　the　threshold　type　for　low-acuity　emergency　patients　(type-2).　Numerical　experiments　are　done　to　examine　how　optimal　dynamic　policy　depends　on　key　system　parameters.　Furthermore,　we　evaluate　the　performance　of　the　optimal　dynamic　policy　with　a　benchmark　policy　without　premature　discharge　decisions.　The　results　indicate　that　the　optimal　admission　control　policy　helps　hospitals　in　maintaining　low　costs　and　enables　patients　with　high-acuity　diseases　to　enter　primary　wards　more　quickly.