Qulity nd Cost Evlution of Medicl Finncil Assistnce Progrm Dougls A Conner, PhD; Arne Beck, PhD; Christin Clrke; Leslie Wright, MA; Koml Nrwney, MD, PhD; Neys W Berminghm Perm J 2013 Winter;17(1):31-37 http://dx.doi.org/10.7812/tpp/12-070 Abstrct Bckground: Kiser Permnente Colordo hs been responding to the finncil chllenges of its members by providing medicl finncil ssistnce (MFA) progrm since 1992. However, there hve been no evlutions of the effect of this progrm on members use of helth services or their helth outcomes. Methods: A prospective cohort study of 308 MFA progrm members who were enrolled between My 16, 2008, nd My 16, 2009, exmined chnges in their use of helth services, costs, nd self-reported physicl nd mentl helth fter enrollment in the MFA progrm. Use of services ws nlyzed with multiple regression, nd costs of services with generlized liner models. Results: MFA incresed members ccess to helth services. There were no chnges in physicl or mentl helth sttus. For ech helth cre visit before the MFA wrd, ptients used the helth cre system 0.23 visits less. The MFA mount ws not ssocited with n increse or decrese in use. There ws no significnt difference in totl overll cost. Hospitl costs were lower, but costs for clinic visits, phrmcy services, phone clls, nd rdiology services were significntly higher, resulting in service cost neutrlity, possibly becuse finncil brriers before MFA wrd led to ccumulted demnd for services. Conclusions: Use of services decresed fter MFA ws received. There ws no significnt chnge in totl service cost. MFA improved members bility to py for medicl services nd incresed their stisfction with helth services. Introduction The cost of helth cre in the US hs incresed disproportiontely to spending on goods nd other services. In 1970, totl helth cre spending verged bout $356 per person ($1147 per person when djusted for infltion). In 2010, helth cre spending verged $6697 per person. Much of this expense hs been shifted to the ptient. For those living below the poverty level, the increse in out-of-pocket expenses is especilly burdensome. Helth cre costs consumed 26% of their income in 1996 nd 33% in 2003. 1 Employment is no gurntee of helth cre coverge. In 2004, lmost hlf (46%) of the uninsured worked full-time, nd 46% worked prt-time or for only few months of the yer. 2 As costs nd ffordbility chllenges increse, more individuls re self-restricting tretment for their helth conditions. Costrelted underuse, substitution, nd discontinution of mediction hve resulted in higher rtes of Emergency Deprtment (ED) visits, increses in nonelective medicl nd psychitric hospitliztions, nd decresed overll helth sttus. 3,4 Those with chronic conditions such s dibetes or hypertension re prticulrly sensitive to tretment disruption, poor mediction dherence, nd dverse helth outcomes. Since 1992, Kiser Permnente Colordo (KPCO) hs been responding to the finncil chllenges of its members by providing medicl finncil ssistnce (MFA) progrm. As prt of KPCO s lrger community benefit investment portfolio, this progrm provides free or deeply discounted ccess to the pproprite level of helth cre for ptients with limited finncil resources. The right level of helth cre for these ptients often includes greter use of plnned, coordinted outptient services, insted of preventble, frgmented, nd often more costly emergency services. There hve been no evlutions of the effectiveness of this progrm, formerly clled KP Helps, on members use of helth services or their helth outcomes. Chnges to the structure of the progrm nd its nme, now MFA, were implemented in April 2008. These chnges included elimintion of cp on ssistnce. Wheres the previous nnul cp totled $500, KPCO members who qulified for finncil ssistnce from April 2008 to April 2009 received nnul coverge of ll copyments nd deductibles for ll mediclly necessry helth-relted services (excluding opticl services, over-the-counter medictions, nd nonformulry prescriptions). KPCO members were eligible for MFA if their income ws t or below 300% of the federl poverty level ($10,400 in 2008, nd $10,830 in 2009). 5 The lck of dt vilble for cpturing the effectiveness of the previous progrm, in conjunction with the progrm chnges, provided n idel opportunity to prospectively evlute the impct of the progrm on members use of helth cre services, mediction dherence, nd physicl nd mentl helth sttus. Our specific question regrding MFA ws whether the increse in ssistnce would remove finncil brriers to preventive nd primry cre services nd prescription medictions, nd in turn, decrese use of emergency nd other hospitl services tht might otherwise result from delys in obtining cre. Such shift from higher to lower intensity cre might lso result in lower overll costs of cre, since emergency nd hospitl services re more costly thn primry cre services. An dditionl question ws whether incresed ccess to primry cre services nd prescriptions might reduce the risk of delys in necessry cre nd subsequent dverse outcomes, thereby improving members functionl sttus in different domins (eg, physicl, emotionl, nd work-relted functions). Dougls A Conner, PhD, is Senior Biosttisticin nd Resercher t the Institute for Helth Reserch in Denver, CO. E-mil: dougls..conner@kp.org. Arne Beck, PhD, is the Director of Qulity Improvement nd Strtegic Reserch t the Institute for Helth Reserch in Denver, CO. E-mil: rne.beck@kp.org. Christin Clrke is Dt Specilist nd SAS Progrmmer t the Institute for Helth Reserch in Denver, CO. E-mil: christin.l.clrke@kp.org. Leslie Wright, MA, is Project Mnger t the Institute for Helth Reserch in Denver, CO. E-fmil: leslie..wright@kp.org. Koml Nrwney, MD, PhD, is Biosttisticin t the Institute for Helth Reserch in Denver, CO. E-mil: koml.j.nrwney@kp.org. Neys W Berminghm is Community Access to Cre Mnger in the Deprtment of Community nd Locl Government Reltions for Kiser Permnente Colordo in Denver. E-mil: neys.w.berminghm@kp.org. The Permnente Journl/ Winter 2013/ Volume 17 No. 1 31
Qulity nd Cost Evlution of Medicl Finncil Assistnce Progrm We hypothesized tht incresed finncil ssistnce to KP Helps prticipnts would reduce hospitl dmissions nd ED visits reduce overll cost of cre improve self-reported physicl nd mentl helth sttus reduce work time lost becuse of illness increse mediction use counterct the self-reported impct of finncil limittions on use of helth cre services. Methods We contcted 393 MFA progrm recipients by mil, nd 308 recipients consented to prticipte in this prospective cohort study between My 16, 2008, nd My 16, 2009. The study ws pproved by KPCO s institutionl review bord. Two weeks fter ech member s MFA enrollment, the study tem miled them recruitment letter; physicl nd mentl helth sttus survey; n opt-out postcrd; nd self-ddressed, stmped envelope. A second survey ws miled 12 months lter to ech member who hd returned bseline survey. The primry outcomes for this study were chnges in use of helth services, including prescriptions, relted costs, nd self-reported physicl nd mentl helth sttus 12 months fter enrollment in the MFA progrm. Physicl nd Mentl Helth Sttus Survey The survey ssessed self-reported physicl nd mentl helth sttus, time missed t work, mediction dherence, nd impct of finncil limittions on use of helth cre services. The survey consisted of 8 demogrphic questions nd 13 items deling with physicl nd mentl helth sttus. It included 10 questions bout behviors to sve money on helth cre services or mediction. Likert scle responses rnged from very esy to very difficult, never to lwys, excellent to poor, or yes to no, depending on the question. The survey ws miled to MFA prticipnts t bseline nd 12 months fter progrm enrollment. Use of Helth Cre Services Most helth cre use nd demogrphic dt were obtined from our Virtul Dt Wrehouse. Use mesures comprised severl ctegories: inptient, ED, primry cre (fmily prctice, internl medicine, or primry cre), durble medicl equipment, mentl helth, oncology, nd the remining specilty deprtments. Other mesures used s covrites included sex, ge, rce, Qun score ( mesure of comorbidity burden), totl prior use, socioeconomic sttus (SES), MFA for prescriptions, MFA for weight mngement, MFA for opticl services, type of Helth Pln coverge, nd totl mount of MFA wrded. Costs Cost dt were obtined from KPCO s Decision Support System, which distributes totl costs for ll internl KPCO services from ech cost center tht then populte the Generl Ledger. These costs in the Generl Ledger re then llocted mong the different cost centers by ll encounter procedure codes nd their frequencies for ech cost center. Costs re bsed on the fourth edition of Current Procedurl Terminology intensity-weighted procedure codes (for more detiled description, see Ritzwoller et l). 6 The Decision Support System provides pre-mfa nd post- MFA costs for 12 cost centers for ll MFA prticipnts (including mbultory surgery, mbulnce, durble medicl equipment, emergency room, home helth, hospitl inptient services, hospitl outptient services, clinic visits, lbortory, phrmcy, phone clls to clinicl stff, nd rdiology). Totl cost ws the sum of costs of individul services. Socioeconomic Sttus Low SES ws defined s enrollment in the KPCO MFA progrm nd residence in neighborhood in which t lest 20% of residents were below the federl poverty level or in n re where less thn 25% grduted from high school. The designted vlue of the SES vrible ws Yes when these criteri were met, bsed on census dt in the Virtul Dt Wrehouse. Dt Anlyses Descriptive sttistics included ge, sex, rce, dignosis (including behviorl helth), Helth Pln coverge, comorbidity burden s mesured by Qun score, 7 nd Medicre membership. Differences between responses on pre-mfa nd post-mfa surveys were tested using the Wilcoxon signed rnk test or McNemr test. Liner regression ws used, with bseline use s covrite for the 12 months before MFA wrd, nd chnge in use s the outcome. To djust for the numerous covrites, two submodels were used: one included demogrphics nd socioeconomic sttus; nd the other included type nd mount of MFA wrd, type of medicl coverge, nd comorbidities. Initil covrites included sex, ge, rce, Qun score for comorbidities, totl prior use, SES, MFA for prescriptions, MFA for weight mngement, type of Helth Pln coverge, nd mount of MFA wrded. The finl submodels were then combined, nd the finl models were creted fter further bckwrd selection. Cost dt were nlyzed using two-prt model to ccount for zero-inflted dt ( lot of zero costs nd long til representing few but very high costs). The first prt of the model ddressed members who hd costs ssocited with ech cost center in question. Repeted mesures SAS Genmod procedures were used to mesure differences in pre-mfa nd post-mfa costs. A gmm distribution with log link ws used to normlize the skewed dt. The second prt then ddressed whether there were differences in the number of members whose cost for ech cost center ws zero. Multivrite logistic regression ws used for those members with no costs. Undjusted models for ech cost center were run, s well s models with demogrphic nd benefit covrites. Results Surveys Three hundred nd ninety-three surveys were miled to MFA recipients, nd 308 recipients consented to study prticiption (78.3%). One hundred nd seventy of the 308 members returned the bseline survey (43.3%). At 12 months, 170 surveys were miled, of which 107 (40%) were returned. One hundred nd seven enrollees completed both surveys. There were few differences between survey responders who returned both surveys nd those who completed only the bseline survey. Compred 32 The Permnente Journl/ Winter 2013/ Volume 17 No. 1
Qulity nd Cost Evlution of Medicl Finncil Assistnce Progrm ORIGINAL RESEARCH & CONTRIBUTIONS with those who completed both surveys, those who returned only the bseline survey were significntly younger nd the proportion who were mrried ws higher, but the proportion who were widowed or divorced ws lower. Significntly more nonresponders were working (results not shown). Tble 1 summrizes demogrphic, helth, nd Helth Pln dt from the bseline surveys. Sixty-four percent were women, nd the verge ge ws 61 yers. A substntil proportion (28%) hd low SES. Additionlly, ptients hd n verge Qun score of 4 (rnge, 0 14), which indictes reltively high burden of disese. 7 Tble 1. Descriptive mesures for 308 prticipnts Vrible Vlue Sex, n (%) Femle 198 (64.3) Mle 110 (35.7) Men ge in yers (SD) 61 (14.74) Hispnic, n (%) No 249 (80.8) Yes 59 (19.2) Rce, n (%) White 200 (64.9) Blck 24 (7.8) Mixed 4 (1.3) Other 34 (11) Missing/no response 46 (14.9) Low socioeconomic sttus, n (%) No 219 (71.1) Yes 85 (27.6) Missing/unknown 4 (1.3) Eduction, n (%) 8th grde or less 9 (2.9) Some high school 13 (4.2) High school diplom, GED 44 (14.3) Some college, 2-yer degree 46 (14.9) 4-yer college degree 16 (5.2) More thn 4-yer college degree 6 (1.9) Missing/no response 174 (56.5) Income in $, n (%) 10,000 or less 14 (4.5) 10,001-15,000 36 (11.7) 15,001-20,000 26 (8.4) 20,001-25,000 27 (8.8) 25,001-30,000 11 (3.6) 30,001-35,000 6 (1.9) 35,001-40,000 5 (1.6) 40,001 - higher 5 (1.6) Missing/no response 178 (57.8) Homeowner, n (%) Rent 60 (19.5) Own 62 (20.1) Other 11 (3.6) Missing/no response 175 (56.8) Number in household, n (%) 1 54 (17.5) 2 51 (16.6) 3 11 (3.6) 4 or more 13 (4.2) Missing/no response 179 (58.1) Vrible Vlue Mritl sttus, n (%) Mrried 55 (17.9) Widowed 23 (7.5) Divorced 37 (12) Seprted 6 (1.9) Never mrried 9 (2.9) Other 4 (1.3) Missing/no response 174 (56.5) Men MFA benefit in $ (SD) 2223.63 (468) MFA for opticl, n (%) No 230 (74.7) Yes 78 (25.3) MFA for outptient services, n (%) No 11 (3.6) Yes 297 (96.4) MFA for prescriptions, n (%) No 48(15.6) Yes 260 (84.4) MFA for weight mngement, n (%) No 303 (98.4) Yes 5 (1.6) KPCO product, n (%) DCO 27 (8.8) HDHP 2 (0.6) HMO 279 (90.6) Medicre, n (%) No 125 (40.6) Yes 183 (59.4) Medicid, n (%) No 308 (100) Yes 0 (0) Five most frequent chronic conditions mking up the Qun score, n (%) Dibetes, complicted nd 184 (59.7) uncomplicted Hypertension 188 (61.6) Chronic pulmonry disese 112 (36.7) Depression 102 (33.4) Fluid nd electrolyte imblnce 71 (23.3) Qun score (SD) 4 (3.13) DCO = deductible coinsurnce pln; GED = generl equivlency diplom; HDHP = high deductible helth pln; HMO = helth mintennce orgniztion pln; KPCO = Kiser Permnente Colordo; MFA = medicl finncil ssistnce; SD = stndrd devition. The Permnente Journl/ Winter 2013/ Volume 17 No. 1 33
Qulity nd Cost Evlution of Medicl Finncil Assistnce Progrm Tble 2. Bseline nd follow-up survey responses for those completing both surveys (n = 107) Question Response Bseline, % Follow-up, % p Ese/difficulty of pying for prescriptions in pst 12 months? (n = 101) Ese/difficulty of pying for other helth cre in pst 12 months? (n = 103) Wht were the chnges mde to sve money in pst 12 months? (n vried for ech item) For those employed in pst 4 weeks, hours of work missed becuse of illness in pst 4 weeks (men, SD) How often did you decide not to do enjoyble ctivities? (n = 102) How often did you decide not to get other medicl cre? (n = 100) How often did you borrow money or get help pying for helth cre? (n = 101) How often did you hve difficulty pying rent or other bills? (n = 105) Were you unemployed during the pst 12 months? (n = 107) Were you unemployed during the pst 4 weeks? (n = 107) During pst 4 weeks, how much did helth problems ffect productivity t work? (n = 40) Very esy/somewht esy 13.9 55.4 <0.001 Neither esy nor difficult 22.8 7.9 Somewht difficult/very difficult 63.4 36.6 Very esy/somewht esy 6.8 51.5 <0.001 Neither esy nor difficult 7.8 7.8 Somewht difficult/very difficult 85.4 40.8 Did not see physicin 61.2 33.7 <0.001 b Did not get other helth cre services 67.7 37.4 <0.001 b Used less mediction thn prescribed 45.8 27.1 0.003 b Stopped mediction 20.8 17.7 0.54 b Did not fill prescription for new 29.5 11.6 0.001 b mediction Switched to different mediction 22.9 12.5 0.04 b Bought medictions outside US 4.2 5.2 0.65 b Took someone else s mediction 8.3 6.2 0.40 b Got free mediction smples 10.9 8.7 0.56 b Used mil order 54.2 44.8 0.07 b 22.8 (37.7) 24.4 (46.2) 0.38 Never 13.7 30.4 0.002 Sometimes 31.4 39.2 Usully 38.2 14.7 Alwys 16.7 15.7 Never 37.0 52.0 0.005 Sometimes 37.0 35.0 Usully 14.0 5.0 Alwys 12.0 8.0 Never 29.7 41.6 0.17 Sometimes 38.6 33.7 Usully 20.8 10.9 Alwys 10.9 13.9 Never 19.1 42.9 <0.001 Sometimes 46.7 37.1 Usully 12.4 9.5 Alwys 21.9 10.5 Yes 68.2 67.3 0.86 b No 31.8 32.7 Yes 72.9 75.7 0.57 b No 27.1 24.3 No effect 10.0 20.0 0.48 Some effect 17.5 15.0 Moderte effect 27.5 20.0 Significnt effect 45.0 45.0 Rte your physicl helth (n = 103) Excellent/very good/good 35.0 39.8 0.31 Fir/poor 65.0 60.2 Rte your mentl helth (n = 102) Excellent/very good/good 72.5 73.5 0.82 Averge number of workdys missed becuse of illness in pst 12 months (n = 13) Averge number of work hours missed becuse of illness in pst 4 weeks (n = 10) Wilcoxon signed rnk test ws used for items with pired ordinl responses. b McNemr test ws used for items with pired nominl responses. SD = stndrd devition. Fir/poor 27.5 26.5 16.5 8.8 0.08 23.7 26.2 0.38 34 The Permnente Journl/ Winter 2013/ Volume 17 No. 1
Qulity nd Cost Evlution of Medicl Finncil Assistnce Progrm ORIGINAL RESEARCH & CONTRIBUTIONS Tble 2 summrizes responses to ech survey item. There ws significnt decrese in the percentge of members reporting helth-relted finncil difficulties. Members lso reported they were more likely to see doctor, ccess other helth services, nd use mediction s prescribed. Members reported greter bility to py their rent on the follow-up survey. In contrst, there were no differences in self-reported physicl or mentl helth or work dys or work hours missed (lthough the number of respondents for this ltter question ws only 10, indicting tht mny respondents were unemployed or retired). Use of Helth Cre Services Three hundred nd eight MFA enrollees greed to exmintion of their use of helth cre services. Univrite comprisons between pre-mfa nd post-mfa demogrphic vribles nd other covrites showed tht the medin number of helth cre visits for members reporting low SES incresed, s it did for members reporting higher SES following MFA (p = 0.0004, dt not shown). The finl regression model (Tble 3) for totl chnge in use included the following vribles: totl prior use, SES, MFA for prescriptions, MFA for weight mngement, Helth Pln type, nd MFA wrd mount. Ptients who received prescription MFA hd 4.23 fewer totl visits fter enrollment. Ptients significntly incresed their use fter MFA enrollment, fter djustment for ll covrites (p < 0.0001). For exmple, ptient who only hd one encounter the yer preceding MFA, received $2500 or more in MFA benefits, hd low SES, nd hd the High Deductible Helth Pln hd pproximtely 16 more visits the yer fter MFA enrollment. The finl regression model for phrmcy use (Tble 4) included totl prior prescription counts; Qun score; SES sttus; nd whether the MFA wrd ws for prescriptions, outptient services, or weight mngement. After djustment for ll covrites, the number of prescription fills ws significntly higher for the yer fter MFA enrollment, compred with the preceding yer (p = 0.0139). For exmple, ptient who hd 6 prescription fills the yer before MFA, hd MFA for prescriptions, hd low SES, nd hd Qun score 2, hd on verge pproximtely 17 more prescription fills the yer fter MFA. After djusting for the other covrites, ptients who received n MFA wrd specificlly for prescriptions were dis- Tble 3. Covrite prmeter estimtes for helth cre use Vrible Prmeter estimte Stndrd error t Pr > t 95% Confidence limits Intercept 10.38046 2.61460 3.97 5.23504, 15.52588 Totl prior use -0.22759 0.04547-5.01 <0.0001-0.31708, -0.13811 MFA $2000 (ref) MFA $2000-$2500 2.79867 1.66474 1.68 0.0938-0.47747, 6.07481 MFA $2500 5.63883 3.46577 1.63 0.1048-1.18166, 12.45931 MFA prescription -4.22503 2.15580-1.96 0.0509-8.46756, 0.01750 MFA weight mngement 13.54436 6.16621 2.20 0.0288 1.40952, 25.67919 DCO -5.80122 2.76759-2.10 0.0369-11.24771, -0.35472 HDHP Pln 0.82411 9.68684 0.09 0.9323-18.23917, 19.88740 High SES (ref) Low SES 0.63426 1.75559 0.36 0.7181-2.82066, 4.08918 Unknown SES 28.43189 6.93136 4.10 <0.0001 14.79126, 42.07251 Multivrite regression. DCO = deductible coinsurnce pln; HDHP = high deductible helth pln; MFA = medicl finncil ssistnce; SES = socioeconomic sttus. Tble 4. Covrite prmeter estimtes for phrmcy use Vrible Prmeter estimte Stndrd error t Pr > t 95% Confidence limits Intercept 26.82667 8.34576 3.21 0.0015 10.40257, 43.25076 Prior phrmcy use -0.11364 0.04593-2.47 0.0139-0.20404, -0.02324 MFA prescription 12.24700 3.52409 3.48 0.0006 5.31175, 19.18225 MFA outptient -8.88379 6.79965-1.31 0.1924-22.26520, 4.49762 MFA weight mngement -13.93630 10.02370-1.39 0.1655-33.66250, 5.78990 High SES (ref) Low SES -2.47941 2.84860-0.87 0.3848-8.08534, 3.12652 Unknown SES 22.15071 11.12630 1.99 0.0474 0.25464, 44.04679 Qun score 6 (ref) Qun score 2-13.02273 3.61941-3.60 0.0004-20.14557, -5.89989 Qun score 3-5 -8.62401 3.28729-2.62 0.0092-15.09325, -2.15477 Multivrite regression. MFA = medicl finncil ssistnce; SES = socioeconomic sttus. The Permnente Journl/ Winter 2013/ Volume 17 No. 1 35
Qulity nd Cost Evlution of Medicl Finncil Assistnce Progrm Prescription use lso incresed for those with the gretest number of comorbidities pensed n verge of 12.25 more fills fter the MFA wrd thn before (p = 0.0006, 95% confidence intervl [CI] 5.31 to 19.18). Ptients with Qun score < 2 were dispensed n verge of 13.02 fewer fills fter the MFA wrd thn those with Qun score 6 (p = 0.0004, 95% CI, -20.15 to -5.9). Additionlly, ptients with Qun score between 3 nd 5 were dispensed 8.62 fewer fills fter the MFA wrd thn those with Qun score 6 (p = 0.0092, 95% CI, -15.09 to -2.15). After MFA enrollment, ptients with n unknown SES were dispensed 22.15 more fills thn those with high SES (p = 0.045, 95% CI, 0.25 to 44.05). Those with low SES did hve different levels of prescription use thn those who did not hve low SES (p = 0.38, 95% CI, -8.09 to 3.13). Costs Univrite comprison of costs before nd fter MFA enrollment showed tht only Qun score ws influenced by comorbidity. A higher score, reflecting greter comorbidity, ws ssocited with higher costs during both the pre-mfa period nd the post-mfa period (p 0.001, results not shown). Tble 5 shows the verge costs for the pre-mfa nd post-mfa periods for ech of the 12 types of services, s well s for verge totl cost. Overll, there ws no significnt difference in totl cost before nd fter MFA enrollment, nd there were no demogrphic or Helth Pln covrites tht influenced the cost nlyses for ny service. There were significnt cost differences for some services. Hospitl costs were $13,299 less during the postenrollment period. Costs for clinic visits, phrmcy services, phone clls, nd rdiology services were significntly higher fter MFA progrm enrollment. This suggests pprecible shifts in cost between types of services. There were no significnt differences in the undjusted or covrite models for the presence of costs before nd following MFA progrm enrollment for the second prt of the 2-prt cost model. Discussion Findings from these nlyses, djusted for demogrphics, Helth Pln, nd other covrites, demonstrted tht MFA enrollees did chnge their overll use of services fter receiving n MFA wrd. A number of covrites significntly influenced the rtes of use, including the type of MFA wrd (eg, phrmcy versus weight mngement), SES, type of KPCO Helth Pln, prior use, nd the mount wrded. Adjusted prescription use ws higher for the postenrollment period when MFA wrd for prescriptions ws included in the model. This is not surprising, becuse the dditionl funds provided specificlly for prescriptions would increse demnd for prescriptions tht perhps hd not been filled before the MFA. Prescription use lso incresed for those with the gretest number of comorbidities (Qun score > 6). The tendency for greter prescription use by those with incresed comorbidities is well known nd suggests n pproprite use of the MFA wrd. 8,9 There were no significnt differences in totl cost before or following enrollment in the MFA progrm. There ws significnt decrese in hospitl costs following enrollment in the progrm, but it ws offset by increses in costs of primry cre, phrmcy, nd rdiology (including mmmogrms) services, which my suggest n increse in some preventive services. Although the svings in hospitliztion costs were considerble, they were outweighed by the combined increses for other services. This pttern of cost shifting from higher to lower intensity services is encourging in tht it reflects the gol of the MFA progrm to increse ccess to primry cre, phrmcy, nd preventive services, nd in turn reduce the need for inptient nd emergency services. These results demonstrte commonly reported pttern tht occurs when members hve not been using helth services becuse of limited ccess or finncil resources. Other investigtors hve Tble 5. Twelve-month undjusted verge costs in US dollrs before nd fter enrollment in medicl finncil ssistnce progrm Before After Cost Cost Center Men ± SD Medin n Men ± SD Medin n Difference p b Totl Cost c 24,209 ± 27,287 13,572 230 26,527 ± 28,391 17,336 231-2318 0.17 Ambultory surgery 3587 ± 4832 1928 67 4652 ± 6565 2813 79-1065 0.25 Ambulnce 1293 ±1471 804 62 980 ± 1395 615 56 313 0.23 DME 1023 ± 1880 343 95 881 ±1251 360 104 142 0.48 Emergency room 3430 ± 5150 360 104 2673 ± 2979 1426 100 757 0.14 Home helth 2209 ± 2781 1206 38 2710 ± 3922 1204 43-501 0.28 Hospitl, inptient 16,532 ± 17,692 10,836 77 3233 ± 4548 1826 84 13,299 <0.0001 Hospitl, outptient 4203 ± 10,876 515 102 6155 ± 14,873 716 124-1952 0.11 Clinic 9182 ±12,234 5782 228 12,583 ± 18,472 7602 230-3401 <0.0001 Lbortory 576 ± 606 379 216 617 ± 805 381 224-41 0.34 Phrmcy 2648 ± 4455 1337 225 3476 ± 5193 1892 230-828 0.003 Phone clls 85 ± 136 39 45 217 ± 380 97 135-132 0.003 Rdiology 1184 ±1449 651 182 1724 ± 3347 757 194-240 0.03 Positive cost difference equls cost svings for postenrollment period. b p vlues were determined using repeted mesures, Genmod models with gmm distribution nd log link. Zero costs were not included. c Cost differences for ll cost centers will not equl the totl cost difference becuse these re verge costs bsed on different numbers of members. DME = durble medicl equipment; SD = stndrd devition. 36 The Permnente Journl/ Winter 2013/ Volume 17 No. 1
Qulity nd Cost Evlution of Medicl Finncil Assistnce Progrm ORIGINAL RESEARCH & CONTRIBUTIONS found n incresed demnd for helth cre services following enrollment in helth pln compred to those lredy enrolled in the pln. Mrtin et l 10 found n incresed demnd for outptient nd emergency visits but lso found increses in the number of hospitliztions (unlike this study) nd hospitl stys fter members hd been uninsured for one yer. Frnks et l 11 found tht members new to n insurnce pln were more likely to visit physicin nd hd higher testing expenditures but fewer hospitliztions (s in this study) nd greter risk of not receiving mmmogrm fter enrolling in n insurnce pln. Differences in popultions, types of Helth Pln, nd other fctors my ccount for some of these differences with our results. There re number of resons certin costs nd use might increse once ptients gin ccess. These include lck of medicl cre before receiving the MFA wrd nd KPCO s emphsis on preventive cre, which my hve led to n initil increse in use of preventive services. Although our results demonstrte no differences in overll use or cost, there were significnt findings regrding ttitudes towrd costs nd ccess to helth cre. Most prticipnts found it esier to py for helth cre services nd prescriptions fter enrollment in the MFA progrm. The percentge of prticipnts who usully or lwys voided getting medicl cre or pying rent or other bills, or who hd to chnge how they mnged money significntly decresed fter MFA enrollment (Tble 2). There ws nonsignificnt increse in the percentge of prticipnts who reported excellent, very good, or good physicl helth. This my indicte tht 12 months is n insufficient length of time for prticipnts with multiple chronic conditions to experience self-perceived improvements in physicl nd mentl helth. The percentge of those who reported fir or poor physicl or mentl helth decresed fter MFA, perhps becuse of difficulty in coordinting cre to significntly chnge the physicl nd/or mentl helth of prticipnts whose disese burden is lredy severe. Finlly, the number of work dys missed becuse of illness decresed by n verge of pproximtely 5 dys over the preceding 12 months, but this finding ws bsed on only 13 employed respondents nd ws not sttisticlly significnt. Repliction of this finding in lrger cohort of employed MFA recipients would be of interest to employers, prticulrly those unble to fford more comprehensive helth cre coverge (or ny coverge) for their employees. Limittions Mesuring comorbidity burden ws somewht problemtic becuse ll comorbidity burden mesures depend on some kind of helth service use. Typiclly, this popultion uses helth services less thn other KPCO members; hence, ny mesure of burden must tke this into ccount. The proposed explntion tht incresed costs for clinic visits, phrmcy services, phone clls, nd rdiology services re cused by significnt previously unmet needs, lthough supported by other studies, needs to be tested further in mnged cre environment. One importnt question tht ws not exmined becuse of time constrints is, t wht point is this pent-up demnd for primry nd specilty cre nd rdiology nd phrmcy services sufficiently relieved to prevent more expensive ED services nd hospitliztions? Finlly, when deling with popultion with multiple helth nd psychosocil needs, 12 months my not be sufficient to observe significnt chnges in physicl or mentl helth. Anlysis over longer follow-up period would be instructive. Differences between the number of individuls enrolled in the MFA progrm (N = 308) nd the number tht completed the bseline (n = 170) nd follow-up (n = 107) surveys my hve resulted in bis, prticulrly when compring use nd costs bsed on survey responses. Conclusions An evlution of n MFA progrm within mnged cre orgniztion demonstrted significnt reductions in ED nd inptient hospitl costs. However, incresed use nd costs of primry cre, durble medicl equipment, nd phrmcy services offset these cost reductions. Although the progrm ws cost neutrl, the shift towrd primry cre services nd wy from inptient services reflects the gol of the MFA progrm to increse ccess to preventive services tht my hve the potentil to reduce use of more intensive services. Moreover, prticipnts reported improved bility to py for medicl services tht decresed potentilly hrmful strtegies (eg, not seeing clinicin, nd voiding necessry mediction) relted to limited ccess to helth cre. v Disclosure Sttement The uthor(s) hve no conflicts of interest to disclose. Acknowledgment Leslie Prker, ELS, provided editoril ssistnce. References 1. Bnthin JS, Bernrd DM. Chnges in finncil burdens for helth cre: ntionl estimtes for the popultion younger thn 65 yers, 1996 to 2003. JAMA 2006 Dec 13;296(22):2712-9. DOI: http://dx.doi.org/10.1001/jm.296.22.2712 2. Overview of the uninsured in the United Sttes: n nlysis of the 2005 Current Popultion Survey [monogrph on the Internet]. Wshington, DC: US Deprtment of Helth nd Humn Services; 2005 Sep 22 [cited 2012 Jul 16]. Avilble from: http://spe.hhs.gov/helth/reports/05/ uninsured-cps/index.htm#insurnce. 3. Hsu J, Price M, Hung J, et l. Unintended consequences of cps on Medicre drug benefits. N Eng J Med 2006 Jun 1;354(22):2349-59. DOI: http://dx.doi.org/10.1056/nejms054436 4. Piette JD, Heisler M, Wgner TH. Cost-relted mediction underuse mong chroniclly ill dults: the tretments people forgo, how often, nd who is t risk. Am J Public Helth 2004 Oct;94(10):1782-7. 5. Poverty guidelines, reserch, nd mesurement [monogrph on the Internet]. Wshington, DC: US Deprtment of Helth nd Humn Services; 2012 [cited 2012 Jul 25]. Avilble from: http:// spe.hhs.gov/poverty. 6. Ritzwoller DP, Sukhnov A, Beck AL, Bergmn D. A new model of well-child cre: implictions for resource costs nd dissemintion. Perm J 2011 Spring;15(2):15-22. DOI: http://dx.doi. org/10-7812/tpp/10-158 7. Qun H, Sundrrjn V, Hlfon P, et l. Coding lgorithms for defining comorbidities in ICD-9- CM nd ICD-10 dministrtive dt. Med Cre 2005 Nov;43(11):1130-9. DOI: http://dx.doi. org/10.1097/01.mlr.0000182534.19832.83 8. Von Korff M, Wgner EH, Sunders K. A chronic disese score from utomted phrmcy dt. J Clin Epidemiol 1992 Feb;45(2):197-203. DOI: http://dx.doi.org/10.1016/0895-4356(92)90016-g 9. Fishmn PA, Goodmn MJ, Hornbrook MC, Meenn RT, Bchmn DJ, O Keeffe Rosetti MC. Risk djustment using utomted mbultory phrmcy dt: the RxRisk model. Med Cre 2003 Jn;41(1):84-99. 10. Mrtin DP, Diehr P, Chedle A, Mdden CW, Ptrick DL, Skillmn SM. Helth cre utiliztion for the newly insured : results from the Wshington Bsic Helth Pln. Inquiry 1997 Summer;34(2):129-42. 11. Frnks P, Cmeron C, Bertkis KD. On being new to n insurnce pln: helth cre use ssocited with the first yers in helth insurnce pln. Ann Fm Med 2003 Sep-Oct;1(3):156-61. DOI: http://dx.doi.org/10.1370/fm.24 The Permnente Journl/ Winter 2013/ Volume 17 No. 1 37