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Increasing Value, Saving Lives: Health Care in a New Era - Keynote Address by Brent James
 

Increasing Value, Saving Lives: Health Care in a New Era - Keynote Address by Brent James

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Keynote address by Brent James at the 2013 Saskatchewan Health Care Quality Summit. For more information about the summit, visit www.qualitysummit.ca. Follow @QualitySummit on Twitter. ...

Keynote address by Brent James at the 2013 Saskatchewan Health Care Quality Summit. For more information about the summit, visit www.qualitysummit.ca. Follow @QualitySummit on Twitter.

Dr. Brent James describes how Intermountain Healthcare is systematically, and successfully, bringing together clinicians, patients and leaders to: establish best practices; drive out waste in their system; and ultimately deliver better, safer care. Dr. James will share insights about the structures, strategies and relationships that have been pivotal in transforming their health system.

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    Increasing Value, Saving Lives: Health Care in a New Era - Keynote Address by Brent James Increasing Value, Saving Lives: Health Care in a New Era - Keynote Address by Brent James Presentation Transcript

    • Increasing Value, Saving Lives:Health Care in a New EraBrent C. James, M.D., M.Stat.Executive Director, Institute forHealth Care Delivery ResearchIntermountain HealthcareSalt Lake City, Utah, USASaskatchewan Health Quality CouncilSaskatchewan Health Care Quality Summit 2013Evraz Place, Regina, Saskatchewan, CanadaThursday, 11 April 2013 -- 8:15a - 9:45a
    • DisclosuresNeither I, Brent C. James, nor anyfamily members, have any relevant financialrelationships to be discussed, directly orindirectly, referred to or illustrated with orwithout recognition within the presentation.I have no financial relationships beyond myemployment at Intermountain Healthcare.
    • Quality, Utilization, & Efficiency (QUE)Six clinical areas studied over 2 years:- transurethral prostatectomy (TURP)- open cholecystectomy- total hip arthroplasty- coronary artery bypass graft surgery (CABG)- permanent pacemaker implantation- community-acquired pneumoniapulled all patients treated over a defined time periodacross all Intermountain inpatient facilities - typically 1 yearidentified and staged (relative to changes in expected utilization)- severity of presenting primary condition- all comorbidities on admission- every complication- measures of long term outcomescompared physicians with meaningful # of cases(low volume physicians included in parallel analysis, as a group)
    • Intermountain TURP QUE StudyMedian Surgery Minutes vs Median Grams TissueM L K J P B C O N A I D H E G F020406080100020406080100Attending PhysicianMedian surgical time Median grams tissue removedGramstissue/Surgeryminutes
    • Intermountain TURP QUE Study1500 1549 1568161815431697191322332140 21561598126911641552 15561662A B C D E F G H I J K L M N O PAttending Physician05001000150020002500Dollars05001000150020002500Average Hospital Cost
    • Total Hip Arthroplasty - LOS1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 30246810121416LengthofStay(days)1988 1989 1990Month/Year02468101214161 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 31988 1989 1990
    • Total Hip Arthroplasty - Cost024681012141988 1989 1990024681012141 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 31988 1989 1990Month/YearAveragecostpercase($1,000s)1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3
    • Deming: Quality controls costQuality Cost ForuminternalinternalCost-benefit society-Waste:SavingsPotential25-40%> 50%(none)Inefficiency wasteQuality waste
    • Deep post-op wound infections% prophylaxis givenat optimal time1985 1986 199140 58 96% Infections 1.8 0.9 0.4Est. decrease in infectionsrelative to 1985 rate -- 33 51Est. savings at $14,000per case (in thousands) -- 462 714National standard: 2 - 4% deep post-op wound infection rateLDSH Dept of Clinical Epidemiology
    • Deep post-op wound infections1985 199438.0 37.140.0 99.119.0 5.343.0 14.3% elective surgeriesreceiving prophylaxis% receiving first dose0-2 hrs before incision% continuing prophylaxis24 hrs after surgeryMean number ofdoses per caseLDSH Dept of Clinical Epidemiology
    • NIH-funded randomized controlled trialassessing an "artifical lung" vs. standard ventilator managementfor acute respiratory distress syndrome (ARDS)discovered large variations in ventilator settingsacross and within expert pulmonologistscreated a protocol for ventilator settings in the control arm ofthe trialDr. Alan Morris, LDS Hospital, 1991:We generalized the method
    • Problems with "best care" protocolsLack of evidence for best practice- Level 1, 2, or 3 evidence available only about 15-25% of the timeExpert consensus is unreliable- experts cant accurately estimate rates using subjective recall(produce guesses that range from 0 to 100%, with no discernable pattern of response)- what you get depends on whom you invite (specialty level, individual level)Guidelines dont guide practice- systems that rely on human memory execute correctly~50% of the time (McGlynn: 55% for adults, 46% for children)No two patients are the same; therefore, no guidelineperfectly fits any patient (with very rare exception)
    • NIH-funded randomized controlled trialassessing an "artifical lung" vs. standard ventilator managementfor acute respiratory distress syndrome (ARDS)discovered large variations in ventilator settingsacross and within expert pulmonologistscreated a protocol for ventilator settings in the control arm ofthe trialImplemented the protocol using Lean principles(Womack et al., 1990 - The Machine That Changed the World)- built into clinical workflows - automatic unless modified- clinicians encouraged to vary based on patient need- variances and patient outcomes fed back in a Lean Learning LoopDr. Alan Morris, LDS Hospital, 1991:We generalized the method
    • 1. Identify a high-priority clinical process (key process analysis)2. Build an evidence-based best practice protocol(always imperfect: poor evidence, unreliable consensus)3. Blend it into clinical workflow (= clinical decision support; dontrely on human memory; make "best care" the lowest energy state, defaultchoice that happens automatically unless someone must modify)4. Embed data systems to track (1) protocol variations and(2) short and long term patient results (intermediate and finalclinical, cost, and satisfaction outcomes)5. Demand that clinicians vary based on patient need6. Feed those data back (variations, outcomes) in a LeanLearning Loop- constantly update and improve the protocol- provide true transparency to front-line clinicians- generate formal knowledge (peer-reviewed publications)Shared Baseline "Lean" protocols (bundles)
    • ARDS Protocol Compliance29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 590102030405060708090100ARDS Patient Number%ProtocolInstructionsFollowed010203040506070809010029 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59
    • Results:survival (for ECMO entry criteria patients) improved from 9.5% to 44%costs fell by ~25% (from $160k to $120k)physician time fell by ~50%Dr. Alan Morris, LDS Hospital, 1991
    • Key take-aways1. No protocol perfectly fits any patient- solution: Shared Baseline "bundles"(mass customization = "patient centered care")2. Serious limitations to protocol development- solution: a Learning System (embedded variance and outcomestracking; continuous protocol review and tested improvement)3. Reliance on human memory (craft of medicine)produces "55% execution"- solution: tools to embed protocols in workflows4. Only two differences from traditional practice: It requires (1)coordinated teams with (2) reliable data systems
    • there is nothing new here ...It should have started in medicine ...except the idea that"it takes a team"(and true transparency = embedded data systems)
    • 07JanMarMayJulSepNov08JanMarMayJulSepNov09JanMarMayJulSepNov10JanMarMonth020406080100%compliance020406080100ER bundle ICU bundle All componentsSepsis bundle compliance
    • 04JanMaySep05JanMaySep06JanMaySep07JanMaySep08JanMaySep09JanMaySep10JanMonth00.10.20.30.40.5Mortalityrate00.10.20.30.40.5Sepsis mortality - ER-ICU transfers20.2%8.0%~116 fewer inpatient deaths per year283244374542422334294133455338504739313034244041352827222827243244363952517065604757525061514377737765716948525946636868637094907581697981788270748491n=
    • We count our successes in lives ...Lesson 1
    • 6.663.362.47 2.653.444.2637 38 39 40 41 42Weeks gestation0246810PercentNICUadmissions0246810Deliveries w/o Complications, 2002 - 20038,001 18,988 33,185 19,601 4,505 258n =NICU admits by weeks gestation
    • Elective inductions < 39 weeks5.55.16.66.3 65.38.25.45.76.66.67.96.47.67.64.63.54.54.36.53.22.62.34.22.13.23.42.4533.526.726.92929.225.327.620.419.116.515.28.410.78.16.85.96.1 65.16.3Jan01MarMayJulSepNovJan02MarMayJulJan03MarMayJulSepNovJan04MarMayJulSepNovJan05MarMayJul051015202530%electiveinductions<39weeks051015202530382372490415430435422455430382356337372366455n =423453473476 512475602557667564637578541573533505501474536562545535493520494430440500421474562549555528491
    • 3331.436.128.317.715.117.614.4 14.35.84.52.10208.2 8.53.6 3.4 3.93.22.41.1 0.9 10 01 2 3 4 5 6 7 8 9 10 11 12 13Bishop score0510152025303540Percentc-sections0510152025303540Unplanned c-section ratesElectively induced patients by Bishop score, Jan 2002 - Aug 200310 49 130 274 567 856 1114 1266 1062 737 415 86 1918 35 61 99 164 278 375 487 453 346 179 47 7MultipsPrimipsn
    • 22.120.717.415.71513.812.611.610.49 97.58.212.41210.810.19.28.17.67.16.45.95.55.14.11 2 3 4 5 6 7 8 9 10 11 12 13Bishop score0510152025Hours0510152025Average hours in labor & deliveryElectively induced patients by Bishop score, Jan 2002 - Aug 200310 49 130 274 567 856 1114 1266 1062 737 415 86 1918 35 61 99 164 278 375 487 453 346 179 47 7MultipsPrimipsn
    • 15.31415.314.514.711.612.811.812.612.815.112.19.98.86.8 6.5 6 6.17.66.5 6.65.2 4.98.44.3 4.3 4.56.15.44.4 3.953 5363535745565241526246493521 212628342822182035151815182521 2011087119109124911079410010511887816757 57465260554937336730 303648453734Jan2003FebMarAprMayJunJulAugSepOctNovDecJan2004FebMarAprMayJunJulAugSepOctNovDecJan2005FebMarAprMayJunJul020406080100120140Numberofpatients01020304050%ofallprimiparousdeliveriesPrimiparous elective inductionsBishops score < 10Bishops score < 8Goal: Reduce "inappropriate" nullip inductions by 50%
    • Elective induction: length of laborJan2001MarMayJulSepNovJan2002MarMayJulSepNovJan2003MarMayJulSepNovJan2004MarMayJulSepNovJan2005MarMayJulSepNov0246810Averagehoursfromadmissiontodelivery02468108.57.97.57.16.9(note: includes all elective inductions)
    • Overall c-section rate9697989920000102030405060%10%20%30%40%Percentc-sectionsoverall0%10%20%30%40%National Intermountain
    • 2001 2002 2003 200402,000,0004,000,0006,000,0008,000,00010,000,000Coststructureimprovement($)01,000,0002,000,0003,000,0004,000,0005,000,0006,000,0007,000,0008,000,0009,000,00010,000,000Cumulativeannualtotal($)Combined maternal and neonatal variable costDeliveries without complications resulting in normal newbornsActual - expected cost, based on year-end 2000 with PPI inflationQuality-based cost improvement
    • Very often,better care is cheaper care ...Lesson 2
    • 50+% of all resource expenditures inhospitals isquality-associated waste:recovering from preventable foul-upsbuilding unusable productsproviding unnecessary treatmentssimple inefficiencyAndersen, C. 1991James BC et al., 2006
    • No good deed goes unpunishedNeonates > 33 weeks gestational agewho develop respiratory distress syndromeTreat at birth hospital with nasal CPAP (preventsalveolar collapse), oxygen, +/- surfactantTransport to NICU declines from 78% to 18%.Financial impact (NOI; ~110 patients per year; raw $):Birth hospitalTransport (staff only)Tertiary (NICU) hospitalDelivery system totalIntegrated health planMedicaidOther commerical payersPayer totalBefore84,24422,199958,4671,064,910900,599652,103429,1011,981,803After553,479- 27,222209,829736,086512,120373,735223,2151,109,070Net469,235- 49,421-748,638-328,824388,479278,368205,886872,733
    • Current U.S. payment mechanismsActively incent overutilization: do more, get paidmore - even when there is no health benefitI am paid to harm my patients (paid more forcomplications)Actively disincents innovation that reducescosts through better quality (a key success factor forthe rest of the U.S. economy)Very strong, deep, wide evidence showingexactly this effect throughout U.S. healthcare
    • 1. ACOs, AMHs, bundled payment, shared savings,pay for value: sophisticated forms of capitation- provider at (financial) risk ... but with far better data systems for(1) quality measurement and (2) risk adjustment2. Represent "managed care at the bedside"- ask clinical teams at the bedside to manage the care, not distantand disengaged insurance companies3. More than 80% of cost saving opportunities liveon the clinical side; 70+% of clinicalimprovement activities reduce costs by freeingup care delivery capacity (technically, "fixed cost leverage").Capitation makes a comeback
    • A fundamental shift in focusThe past:1. "Top-line" revenue enhancement- Systems designed around documentation to support FFS payment,clinical decision support as a secondary "bolt-on"2. Quality defined as regulatory compliance - e.g.- CMS Core Measures- Pay for Value- Meaningful UseThe future:1. Quality becomes the core business- Demonstrated performance for key clinical processes- Systems designed around clinical decision support (processmanagement), producing documentation as an integrated by-product2. "Bottom-line" cost control and waste eliminationin a "provider at risk" financial environment
    • 1. Quality improvement isthe science of process management2. A focus on process management forcespatient-centered care - care built along the fullcontinuum of care; not buildings, technologies, or physicians3. Combining patient- centered care withvarious levels of provider-at-financial-riskforcespopulation-level care and the triple aim- collaborating with other community organizations(churches, schools, local governments, etc.) to promotebest health and high functionGetting to the Triple Aim
    • Better has no limit ...an old Yiddish proverb