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MI ROW De c re me nting I nve nto ry via E le c tro nic Da ta E xc ha ng e AI RA Na tio na l Co nfe re nc e April 6, 2016 Se a ttle , WA Ove rvie w I ntro duc tio n to MI ROW Ove rvie w o f DI -v-E DE I mple me nta

  1. MI ROW De c re me nting I nve nto ry via E le c tro nic Da ta E xc ha ng e AI RA Na tio na l Co nfe re nc e April 6, 2016 – Se a ttle , WA

  2. Ove rvie w  I ntro duc tio n to MI ROW  Ove rvie w o f DI -v-E DE  I mple me nta tio n Co nside ra tio ns  Use r Pe rspe c tive

  3. I ntro duc tio n to MI ROW  T he Mo de ling o f I mmuniza tio n Re g istry Ope ra tio ns Wo rkg ro up  F o rme d in 2005  AI RA in pa rtne rship I I SSB a t the CDC  Ob je c tive  De ve lo p a nd pro mo te I I S Be st Pra c tic e s  Go a l  Pro vide the b a sis a nd suppo rt fo r unifo rm a lig nme nt o f I I S pro c e sse s I nc o nsiste nc y amo ng I I S ne g ative ly affe c ts o ve rall data q uality, c o mparab ility, o pe ratio nal c o st, and use fulne ss o f info rmatio n.

  4. MI ROW Ste e ring Co mmitte e  Ove rsig ht fro m the MI ROW Ste e ring Co mmitte e  Wa rre n Willia ms – Co -Cha ir  E  AI la ine L o we ry - Co -Cha ir RA Sta ff  Bra ndy Altsta dte r, ST C  Re b e c c a Co yle  Ama nda Ha rris, NV  Nic ho le L a mb re c ht  Da vid L ya lin, CDC  Me g a n Me ldrum, NY  E liza b e th Pa rilla , MN  K a tie Re e d, HP  K im T ic hy, I A  Bha va ni Sa thya , NJ

  5. Ho w MI ROW Wo rks  Busine ss a na lysis a nd de ve lo pme nt pro c e ss suppo rt pro vide d b y I I SSB/ CDC a nd AI RA pub lic he a lth c o nsulta nts  Org a niza tio na l suppo rt fo r in-pe rso n me e ting s fro m AI RA sta ff  F a c ilita tio n suppo rt fo r in-pe rso n me e ting s pro vide d b y e xte rna l c o nsulta nts  Vo lunte e ring sub je c t ma tte r e xpe rts fro m the I I S c o mmunity

  6. T he MI ROW Pro c e ss Bra insto rming Co nse nsus = Disc ussing “ I c an live with that and suppo rt it” Re a c hing Co nse nsus

  7. T he MI ROW Pro c e ss

  8. Pa st T o pic s  Ma na g e me nt o f Pa tie nt Ac tive / I na c tive Sta tus in I I S  Da ta Qua lity Assura nc e – Se le c te d Aspe c ts  I nve nto ry Ma na g e me nt  Pa tie nt E lig ib ility fo r the VF C Pro g ra m a nd Gra nte e I mmuniza tio n Pro g ra ms  Re minde r/ Re c a ll  I nc o ming Da ta Qua lity Assura nc e – I nc o ming Da ta  Va c c ina tio n L e ve l De duplic a tio n  I I S-Va c c ine Adve rse E ve nt Re po rting Syste m Co lla b o ra tio n (pilo t pro je c t)

  9. MI ROW Do c ume nts Mini-g uide – 4 to 8 pa g e s Co mple te Guide – 150 pa g e s Do wnlo a d MI ROW do c ume nts a t: AI RA we b site : http:/ / www.immre g istrie s.o rg / pub s/ miro w.html CDC we b site : www.c dc .g o v/ va c c ine s/ pro g ra ms/ iis/ a c tivitie s/ miro w.html

  10. Why DI -v-E DE ?  DI -v-E DE a ssists immuniza tio n pro g ra ms in ma inta ining mo re a c c ura te pro vide r va c c ine inve nto rie s a nd pro vide r o rg a niza tio ns in me e ting a wa rde e immuniza tio n pro g ra m o pe ra tio na l re q uire me nts (e .g ., va c c ine a c c o unta b ility).

  11. De ve lo pme nt Me tho ds  F o rme d a dive rse wo rkg ro up c o mprise d o f 13 sub je c t ma tte r e xpe rts  I I S Sta ff  I I S Ve ndo r Sta ff  He a lth I T Ve ndo r Sta ff  Utilize d mo de rn b usine ss a na lysis a nd fa c ilita tio n te c hniq ue s  Co nduc te d pre limina ry wo rk  Co lle c te d a nd a na lyze d e xisting I I S ma te ria ls  Me t July 2015 (De c a tur, GA)  Ana lyze d e xisting pra c tic e s  F o rmula te d c o nse nsus-b a se d re c o mme nda tio ns  F ina lize d wo rk via pho ne me e ting s  Sma ll g ro up a nd wo rksho p

  12. DI -v-E DE Co nc e pts  T he DI -v-E DE pro c e ss is a n a uto ma te d me tho d to de c re me nt the numb e r o f va c c ine do se s in a pro vide r o rg a niza tio n’ s inve nto ry in the I I S whe n the o rg a niza tio n re po rts a va c c ina tio n e ve nt thro ug h e le c tro nic da ta e xc ha ng e fro m a n E HR to the I I S.  E a c h pro vide r o rg a niza tio n’ s va c c ine inve nto ry is c a te g o rize d b a se d o n funding indic a to rs.  T o de duc t a va c c ine do se fro m the a ppro pria te sto c k the I I S ma tc he s info rma tio n tha t the pro vide r o rg a niza tio n sub mits re g a rding a va c c ina tio n e ve nt a g a inst the info rma tio n tha t I I S ha s fo r the inve nto ry o f tha t pro vide r o rg a niza tio n.  T he I I S use s da ta e le me nts suc h a s lo t numb e r, lo t numb e r e xpira tio n da te , do se le ve l e lig ib ility, lo t le ve l pub lic / priva te indic a to r a nd, in so me c a se s, do se le ve l pub lic / priva te indic a to r to ma tc h inve nto ry.

  13. F unda me nta l Co nc e pts  F und T ype  Sto ra g e Mo de l  Do se L e ve l E lig ib ility  Do se L e ve l Pub lic / Priva te I ndic a to r  L o t L e ve l Pub lic / Priva te I ndic a to r

  14. F und T ype  De sc rib e s the pro g ra m (o r a priva te pa ye e ) tha t pa id fo r va c c ine .  E a c h do se o f va c c ine is pa id fo r with funds fro m a pub lic pro g ra m (e .g ., VF C, 317, sta te o r CHI P funds) o r priva te funding .

  15. Sto ra g e Mo de l  De sc rib e s the wa y va c c ine sto c ks a re physic a lly se pa ra te d in the pro vide r o rg a niza tio n’ s sto ra g e unit.  De pe nding o n the a wa rde e ’ s re q uire me nts,  the pro vide r o rg a niza tio n ma y ne e d to se pa ra te the va c c ine s b y fund type o r  ma y b e a llo we d to ha ve le ss spe c ific c a te g o rie s (e .g ., VF C pub lic , no n-VF C pub lic a nd priva te ).

  16. Multi-sto c k (4 o r mo re ) mo de l Pro vide r o rg a niza tio n se pa ra te s va c c ine s b y fund type (e .g ., VF C, 317, CHI P, • Sta te , a nd priva te ). T his mo de l ta ke s a dva nta g e o f the fa c t tha t a pro vide r o rg a niza tio n kno ws • fund type fo r e a c h va c c ine fro m the pa c king slip o r o the r me c ha nism.

  17. T hre e -sto c k mo de l Pro vide r o rg a niza tio n se pa ra te s va c c ine s into thre e funding so urc e • c a te g o rie s. T his is the o nly mo de l tha t VF C re c o mme nds; ho we ve r, a wa rde e s c a n • re q ue st to use a mo de l tha t b le nds fund type s into two sto c ks o r o ne sto c k.

  18. T wo -sto c k mo de l T he pro vide r o rg a niza tio n se pa ra te s va c c ine s into two funding so urc e c a te g o rie s.

  19. One -sto c k mo de l  Do e s no t re q uire pro vide r o rg a niza tio ns to pa rtitio n va c c ine s into multiple inve nto ry sto c ks within the ir sto ra g e .  T wo type s:  Re pla c e me nt: T he pro vide r o rg a niza tio n use s priva te ly-funde d va c c ine s to va c c ina te a ll pa tie nts a nd the VF C pro g ra m re pla c e s priva te ly-funde d va c c ine s tha t we re a dministe re d to VF C e lig ib le c hildre n.  Unive rsa l: T he pro vide r o rg a niza tio n o nly ha s pub lic ly-funde d va c c ine (a t le a st fo r pe dia tric pa tie nts) supplie d dire c tly fro m the a wa rde e immuniza tio n pro g ra m.

  20. Do se L e ve l E lig ib ility  Do se le ve l e lig ib ility de sc rib e s a pa tie nt’ s e lig ib ility fo r a do se o f va c c ine fro m a funding pro g ra m (e .g . VF C, 317, e tc .)  De te rmine d fo r e a c h do se a dministe re d to a pa tie nt a t the time o f the va c c ina tio n e ve nt.

  21. Do se L e ve l Pub lic / Priva te I ndic a to r  T he pro vide r se le c ts a do se o f va c c ine fro m the sto ra g e unit b a se d o n the pa tie nt’ s e lig ib ility.  Whe n the pro vide r do c ume nts the va c c ina tio n e ve nt, the y ma y inc lude  spe c ific fund type o f the do se a dministe re d o r  le ss spe c ific c a te g o rie s (e .g ., VF C pub lic , no n-VF C pub lic & priva te ).

  22. Do se L e ve l Pub lic / Priva te I ndic a to r  T he se le ss spe c ific c a te g o rie s a re re fe rre d to a s do se le ve l pub lic / priva te indic a to r sinc e the da ta e le me nt ide ntifie s if the do se tha t wa s a dministe re d wa s purc ha se d with pub lic o r priva te funds.  Do se le ve l pub lic / priva te indic a to r is a n a g g re g a te d re fle c tio n o f fund type a t the va c c ine do se le ve l.

  23. L o t L e ve l Pub lic / Priva te I ndic a to r  T he lo t le ve l pub lic / priva te indic a to r is a n a g g re g a te d re fle c tio n o f fund type a t the va c c ine lo t le ve l.  I t indic a te s if va c c ine do se s with a g ive n lo t numb e r a re a sso c ia te d with pub lic ly-funde d o r priva te ly-funde d inve nto ry in the I I S.

  24. DI -v-E DE Wo rkg ro up  E xpe rts  Bra ndy Altsta dte r, ST C  Je nnife r Be dna r, HP  Ja ne t F  Pro je c t Suppo rt T a th, CDC e a m  Da nie lle Ha ll, ME  Wa rre n Willia m, Co -Cha ir  Ama nda Ha rris, NV  E la ine L o we ry, Co -Cha ir  T  Nic ho le L he re se Ho yle , MI a mb re c ht, AI RA  T ra c y L ittle , OR  Ang e la L indsa y, CDC  Me g a n Me ldrum, NY  Da vid L ya lin, CDC  Bha va ni Sa thya , NJ  E liza b e th Pa rilla , MN

  25. I mple me nta tio n Co nside ra tio ns  K e y Da ta E le me nts  Da ta Qua lity  HL 7 I mmuniza tio n Me ssa g ing  E HR  Outre a c h a nd E duc a tio n  Sta ff T ime  Re so urc e s

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