Transcript Title
The Imperative of Linking Clinical and Financial Data to Improve Outcomes
Charles G. Macias M.D., M.P.H.
Chief Clinical Systems Integration Officer, Texas Children’s Hospital
Learning objectives
Assess the effectiveness of an
organization’s quality gaps
to ensure organizational readiness, drive efficiency and leverage opportunities to improve quality.
Illustrate how a
blend of clinical and financial data
informed by analytics from an enterprise data warehouse can improve outcomes.
Describe how an EDW and care process implementation can encourage a
culture of quality and safety
, providing physicians with the necessary
tools to integrate financial relevance
into the practice of delivering high-quality healthcare. Discuss how strategy for integration of
science
, data and predictive
analytics and operational improvement
a system towards the triple aim.
through improvement science can transform
Jenny Jones and the Challenges of a Fragmented System
Within six months, Jenny had visited: One PCP Two Hospitals Three ERs Leading to: Six different Asthma Action Plans with conflicting discharge instructions
Quality Defined
1 Institute of Medicine domains: Safe Effective Efficient Timely Patient centered Equitable 2 The degree to which health services for individuals and populations increase the
likelihood of desired health outcomes
and are consistent with
current professional knowledge
.
– Lohr, K.N., & Schroeder, S.A. (1990). A strategy for quality assurance in Medicare. New England Journal of Medicine, 322 (10):707-712.
3 Importance of minimizing unintended variation in health care delivery
The Healthcare Value Equation
In an environment where cost is marginally increasing, healthcare must markedly improve quality.
Adoption of EMRs and clinical systems should help push the quality agenda but alone may not be enough to deliver data intelligence.
Value
=
Quality Cost
4
I
n Second Look, Few Savings from Digital Health Records
New York Times: January 10, 2013
2005 RAND report forecasts $81 billion annual U.S. savings. “Seven years later the empirical data on the technology’s impact on health care efficiency and safety are mixed, and annual health care expenditures in the United States have grown by $800 billion.
” Disappointing performance of health IT to date largely attributed to: Sluggish adoption of health IT systems, coupled with the choice of systems that are neither interoperable nor easy to use; The failure of health care providers and institutions to reengineer care processes to reap the full benefits of health IT.
EHRs, Red Tape Eroding Physician Job Satisfaction Most physicians express frustration with the failure to provide efficiency. 20% want to return to paper 5
Variation in Care
Describing variation in care in three pediatric diseases: gastroenteritis, asthma, simple febrile seizure Pediatric Health Information System database (for data from 21 member hospitals) Two quality-of-care metrics measured for each disease process Wide variations in practice Increased costs were NOT associated with lower admission rates or 3-day ED revisit rates Implications?
Optimal care may be delivered at a lower cost than today’s care!
Kharbanda AB, Hall M, Shah SS, Freedman SB, Mistry RD, Macias CG, Bonsu B, Dayan PS, Alessandrini EA, Neuman MI. Variation in resource utilization across a national sample of pediatric emergency departments. J Pediatr. 2013 6
Consumer Care/Cost Uncertainty
Consumers: Trust their physicians Hope for the best Struggle to understand cost and care Don ’ t often know what they are getting Don’t always get great outcomes Value is what they want 7
Challenge of Healthcare
Physicians are: Driven by science and key values Overwhelmed with medical literature Not well trained to turn that experience into high quality patient outcomes Transparency of local data is part of the solution!
8
Poll Question #1
In your organization, what percentage of patient visits are your physicians talking about cost and care tradeoffs at the bedside?
a) 0-19% b) 20-39% c) 40-59% d) 60-79% e) 80-100% f) Unsure or not applicable 9
Physicians and Care Cost
Evidence Clinical Expertise Resource issues
Source: SAEM. Evidence Based Medicine Online Course 2005
Patient values and preferences Physician preferences
Once taboo, physicians should take cost into consideration:
No Money No Mission No Expansion No Innovation And so providers must…..
Understand what creates improvements Understand the story that their data tells.
11
About Texas Children’s Hospital
Number of Beds Annual Inpatient Admissions Statistics 469 21,744 1.44 million Annual Outpatient Visits Emergency Room Visits 82,049 Inpatient Surgeries 8,655 14,439 Outpatient Surgeries
A data management strategy to improve outcomes
IMPROVED OUTCOMES from high quality of care
Patient centric outcomes and institutional outcomes achieved Evidence Based Guidelines and Order sets, Clinical Decision Support, patient and provider materials
DEPLOYMENT SYSTEM Operations CLINICAL CONTENT SYSTEM Science and evidence
Advanced Quality Improvement course, QI curriculum, Care process teams Informatics, Electronic Data Warehousing
ANALYTIC SYSTEM Data analytics and collaborative data
SOURCE SYSTEMS (e.g. EMR, Financial, Costing, Patient Satisfaction)
Creating a foundation for EB practice
IMPROVED OUTCOMES from high quality of care
Evidence Based Guidelines and Order sets, Clinical Decision Support, patient and provider materials
DEPLOYMENT SYSTEM Operations CLINICAL CONTENT SYSTEM Science and evidence ANALYTIC SYSTEM Data analytics and collaborative data
SOURCE SYSTEMS (e.g. EMR, Financial, Costing, Patient Satisfaction)
Evidence-Based Guidelines: EBOC
Acute Chest Syndrome Acute Gastroenteritis Acute Heart Failure Acute Hematogenous Osteomyelitis Acute Ischemic Stroke Acute Otitis Media Appendicitis Arterial Thrombosis Asthma Bronchiolitis Cancer Center Procedural Management Cardiac Thrombosis Central Line-Associated Bloodstream Infections Closed Head Injury Community-Acquired Pneumonia Cystic Fibrosis – Nutrition/GI >12 y/o Autism Assessment and Diagnosis C-spine Assessment Intraosseus Line Placement IV Lock Therapy Postpartum Hemorrhage Deep Vein Thrombosis Diabetic Ketoacidosis Fever and Neutropenia in Children with Cancer Fever Without Localizing Signs (FWLS) 0-60 Days Fever Without Localizaing Signs (FWLS) 2-36 Months Housewide Procedural Sedation Hyperbilirubinemia Neonatal Thrombosis Nutrition/Feeding in the Post-Cardiac Neonate Rapid Sequence Intubation Skin and Soft Tissue Infection Status Epilepticus Tracheostomy Management Urinary Tract Infection
Poll Question #2
In ambulatory settings, what is the best estimate for the percentage of questions for which evidence exists to answer clinical questions that affect the decision to treat?
a) 5% b) 10% c) 15% d) 25% e) 50% f) Unsure or not applicable 16
Creating a foundation for data use
IMPROVED OUTCOMES from high quality of care DEPLOYMENT SYSTEM Operations CLINICAL CONTENT SYSTEM Science and evidence ANALYTIC SYSTEM Data analytics and collaborative data
SOURCE SYSTEMS (e.g. EMR, Financial, Costing, Patient Satisfaction)
Informatics, Electronic Data Warehousing
TCH’s EDW Architecture
Metadata: EDW Atlas Security and Auditing Common, Linkable Vocabulary; Late binding FINANCIAL SOURCES (e.g. EPSi,) ADMINISTRATIVE SOURCES (e.g. API Time Tracking)
Financial Source Marts Administrative Source Marts Clinical
• Asthma • Appendectomy • Deliveries • Pneumonia • Diabetes • Surgery • Neonatal dz • Transplant
EMR Source Marts Departmental Source Marts Operations
• Labor productivity • Radiology • Practice Mgmt • Financials • Patient Satisfaction • + others
Patient Source Marts HR Source Mart
EMR SOURCE (e.g. Epic) DEPARTMENTAL SOURCES (e.g. Sunquest Labs) PATIENT SATISFACTION SOURCES (e.g. NRC Picker, Human Resources (e.g. PeopleSoft)
Creating a foundation for QI deployment
IMPROVED OUTCOMES from high quality of care
Advanced Quality Improvement course, QI curriculum, Care process teams
DEPLOYMENT SYSTEM Operations CLINICAL CONTENT SYSTEM Science and evidence ANALYTIC SYSTEM Data analytics and collaborative data
Avenues for Dissemination
QUALITY LEADERS
National Programs and Partnerships
ADVANCED INTERMEDIATE BEGINNER
Classroom (e.g. AQI Program, Six Sigma Green Belt) •Project Required Online and Classroom (IHI Educational Resources, PEDI 101, EQIPP, Fellows College) •Project Required Online and Classroom (e.g. Nursing IMPACT (QI Basic). OJO Educational Resources, Lean Awareness Training)
NEW
Classroom and Department (e.g. New Employee Orientation, e-Learning, Unit/Department-based training)
Changes that result in process improvement
Improvement Ideas Adapted from: The Improvement Guide: A Practical Approach to Enhancing Organizational Performance, 2nd Ed. Gerald J. Langley, Ronald D. Moen, Kevin M. Nolan, Thomas W. Nolan, Clifford L. Norman, and Lloyd P. Provost; Jossey-Bass 2009
Pareto 80/20 Principle in Healthcare
TCH’s Care Process Analysis
Asthma
Size of Clinical Process
Improvement Opportunity: Large processes with significant variation
Bubble Size = Case Count
Driving clinical care improvement: linking science, data management, operations
MD Lead #5 Care Process
Clinical Program
Guidelines centered on evidence-based care MD Lead #4 Care Process MD Lead #3 Care Process MD Lead #2 Care Process MD Lead #1 Care Process Operation s Lead Clinical Director Domain MD Lead Data Manager Outcomes Analyst BI Developer Data Architect Permanent, integrated teams composed of clinicians, technologists, analysts and quality improvement personnel drive adoption of evidence-based medicine and achieve and sustain superior outcomes. Application Service Owner
Balanced scorecard-expanded visualizations
3.
Individual Ratings 1.
Care Process Defined 2.
Current Literature Research 5.
Group Creates Final Scorecard 4.
Aggregate Ratings
Severity Adjusted Variation
Data Drives Waste Reduction: Alternative Approaches
1.96 std
# of Cases 1 box = 100 cases in a year Mean # of Cases Excellent Outcomes Poor Outcomes Excellent Outcomes
Option 1: Focus on Outliers – the prescriptive approach Strategy
eliminate the unfavorable tail of the curve (“quality assurance”)
Result
Ithe impact is minimal Poor Outcomes 27
Alternative Approaches to Waste Reduction
# of Cases 1 box = 100 cases in a year Mean # of Cases Excellent Outcomes Poor Outcomes Excellent Outcomes Poor Outcomes
Option 2: Focus On Inliers – improving quality outcomes across the majority Strategy
variation Evidence and analytics applied through EBP clinical standards targets inlier
Result
impact Shifting more cases towards excellent outcomes has much more significant 28
Improving Cost Structure Through Waste Reduction
Ordering Waste
Ordering of tests that are neither diagnostic nor contributory
Workflow Waste Defect Waste
Variation in Emergency Care wait time ADEs, transfusion reactions, pressure ulcers, HAIs, VTE, falls, wrong surgery 29
Care Redesign Methodology
Quicker steroid delivery for status asthmaticus, goal directed therapy for septic shock Hypertonic saline and bronchodilators in select patients with bronchiolitis Evidence Supports Evidence equivocal Evidence against CXR utilization in patients with known asthma, steroids in bronchiolitis 30
80% 70% 60% 50% 40% 30% 20% 10% 0% Asthma: Care Process Team Cohort, Percentage of Chest X-rays Ordered* (Oct. 2010 - Ap r. 2013) Feedba ck of ra tes to hospita lists a nd Em ergency Center clinicia ns 51% Order set revisions 35% Month yea r * Inpa tient, Em ergency Center (EC) a nd observa tion pa tients (Ca re Process Tea m cohort), P-Cha rt ba sed upon EDW da ta extra ction of 5/14/2013 (M& W). 31
Improving Cost Structure Through Waste Reduction
Ordering Waste
Ordering of tests that are neither diagnostic nor contributory
Workflow Waste Defect Waste
Variation in Emergency Care wait time ADEs, transfusion reactions, pressure ulcers, HAIs, VTE, falls, wrong surgery 32
BEGIN Patient presents to Emergency Dept (ED).
Patient registers Patient waiting Patient evaluated by triage nurse Put patient in ED room Follow TCH AGE clinical algorithm
Flow chart of a patient with acute gastroenteritis through the TCH Emergency Department: Existing process
4 Patient discharged home
1
3 Does patient have vomiting &/ or diarrhea Evaluate per clinical symptoms Patient transferred to inpatient bed
2
Triage nurse does the following: · Vitals What is the patient’s level of dehydration?
Key:
___ solid arrow indicates “yes” _ _ broken arrow indicates “no”
1 Outcome: Time in ED 2 Outcome: Time to inpatient bed 3 Outcome: Length of stay (LOS) 4 Outcome: Revisit from ED discharge 4 Outcome: Revisit from inpatient discharge
Nurse discharges patient Fellow/ Attending does pre transfer check PCA checks vital signs Nurse-Nurse checkout occurs Bed approved Severe dehydration Triage nurse does the following: · Give Zofran · Provide gatorade/pedialyte Patient waiting Patient put in ED room PCA checks vital signs ED secretary requests bed Mild or Moderate dehydration Is the patient vomiting?
MD does discharge orders Decision to discharge patient MD does admission orders Decision to admit patient Triage nurse does the following: · Nothing or give patient gatorade/ pedialyte Patient evaluated by nurse Is the patient ok for discharge?
Patient evaluated by Medical student Patient evaluated by ED resident Patient evaluated by ED fellow
Process map before EBG
Patient evaluated by ED attending Modified: 7/21/2009
BEGIN Patient presents to Emergency Dept (ED).
Flow chart of a patient with acute gastroenteritis through the TCH Emergency Deparment
Does patient have vomiting &/ or diarrhea Evaluate per clinical symptoms 4 Patient discharged home
1
3 Patient transferred to inpatient bed
2
Fellow/ Attending does pre transfer check PCA checks vital signs Patient registers Patient waiting Triage nurse does the following: · Vitals ·
Assess dehydration (Gorelick score)**
What is the patient’s level of dehydration?
Key:
___ solid arrow indicates “yes” _ _ broken arrow indicates “no”
** New process 1 Outcome: Time in ED 2 Outcome: Time to inpatient bed 3 Outcome: Length of stay (LOS) 4 Outcome: Revisit from ED discharge 4 Outcome: Revisit from inpatient discharge
Nurse discharges patient Collect ORT tracking sheet Nurse-Nurse checkout occurs Bed approved Patient evaluated by triage nurse PCA checks vital signs ED secretary requests bed Severe dehydration Mild or Moderate dehydration MD does discharge orders MD does admission orders Is the patient vomiting?
Put patient in ED room Follow TCH AGE clinical algorithm Triage nurse does the following: · Provide patient education on ORT · Initiate ORT ·
Give ORT tracking sheet**
Decision to discharge patient Decision to admit patient Triage nurse does the following: · Give Zofran · Provide patient education on ORT · · Initiate ORT
Give ORT tracking sheet**
Is the patient ok for discharge?
Patient waiting Patient put in ED room Patient evaluated by nurse Bedside nurse does the following: ·
Assesses dehydration (Gorelick score)**
·
Monitors progress on ORT tracking sheet**
· Reemphasizes patient education on ORT Patient evaluated by Medical student Patient evaluated by ED resident Patient evaluated by ED fellow Patient evaluated by ED attending ED Fellow does the following: · · · · Determines patient disposition
Process map after EBG
Reemphasizes patient education on ORT Modified: 5/9/2009
35
Improving Cost Structure Through Waste Reduction
Ordering Waste
Ordering of tests that are neither diagnostic nor contributory
Workflow Waste Defect Waste
Variation in Emergency Care wait time ADEs, transfusion reactions, pressure ulcers, HAIs, VTE, falls, wrong surgery 36
Clinical Decision Support to Minimize Errors Streamlining and Improving Processes and Operations to Minimize Errors
37
Value =
EC: Early administration of Dexamethasone
Expanding evidence based practice -Provider and staff inservicing -Clinical decision support -Bridging a continuum for home care: second dose 10% decrease in TID
Inpatient: prolonged LOS
Evidence based approach to early medication weaning • • • • 35% reduction in LOS No change in 7 or 30 day readmission rate No change in days of school/days of work missed Direct variable cost ($60/hr)
I-MR Chart of CT - 1st q3h to d/c by Phase
1 200 150 100 50 0 Baseline 1 13 25 37 5 49 61
Obser vation
73 85 97 109 121 U C L=70.9
_ X=27.4
LC L=-16.1
200 150 100 50 0 1 Baseline 13 25 37 1 1 49 61
Obser vation
73 85 97 109 121 U C L=53.4
__ M R=16.4
LC L=0
The continuum: improved patient experience and outcomes
Improved time to first beta agonist (ED or inpatient arrival) • • • • Increase chronic severity assessment Improve accuracy Increase appropriate controller prescriptions Clinical decision support Increase influenza vaccination rate Increase number of culturally sensitive education encounters Increase number of social work/ legal support encounters • AAP use went from 20% to 44% in first cycle to 52% in second • ACT use went from 0% to 30% in first cycle to 41% in second • Severity classification went from 10% to 35% in first cycle to 54% in second
Registry Financial Score Card
42
Asthma Care Outcomes Dashboard
Financial conversations
$5 000 $4 500 $4 000 $3 500 $3 000 $2 500 $2 000 $1 500 $1 000 $500 $0 -$500 -$1 000 -$1 500 -$2 000 -$2 500 -$3 000 -$3 500 -$4 000 -$4 500 -$5 000
Margin y = 106,48x - 855,25
2011 Q1 2011 Q2 2011 Q3 2011 Q4 2012 Q1 2012 Q2 2012 Q3 2012 Q4 2013 Q1 2013 Q2 2013 Q3 2013 Q4 2014 Q1 2014 Q2
y = 291,62x - 3062,5
47
Examples Demonstrating ROI
Improved clinical care Decreases in LOS Decrease in readmission rates Decreased unnecessary test utilization Millions in savings across several disease processes
Reducing waste by systematizing reporting
EDW reports cost 70% less to build
Clinical operations tools allow global views for increased operational efficiency
48
Organizational direction for data
Improved outcomes for our patients and our enterprise
Data reporting
-EMR clinical reports -Financial reports Organizational evolution over time
Data analytics
-Shortening event to reporting time -Transforming data and translating to action
Decision support
-Integrating best evidence into delivery system infrastructures -EMR based recommendations and alerts -Integrated plans of care across continuums
Predictive analytics
--Linking likelihood of outcomes to care decisions driven with realtime data -Predicting financial outcomes and linking to clinical decisions for populations of patients -Linking outcomes across infrastructures
Predictive analytics: High risk asthma
Targets: reduce ED visits, hospitalization, albuterol overuse, ICS non adherence Critical data source: TCHP, TDSHS data
SHORT ACTING BETA AGONISTS
6 to 9 SABA = 1 point ≥ 10 SABA = 2 points
EC UTILIZATION
1-2 ER = 1 point > 2 ER = 2 points
HOSPITALIZATION
1 hospitalization = 1 point >= 2 hospitalizations = 4 points
NUMBER PRESCRIBING PROVIDERS
>= 3 different prescribing providers in 12 months one of above criteria met, add 1 point
PRIMARY CARE VISITS
Last PCP visit > 6 months + one of above criteria met = add 1 point
INHALED CORTICOSTERIOD
>= 6 ICS low dose canister equivalent refills, subtract 1 point Lieu TA et al Am J Respir Crit Care Med. 1998 Apr;157(4 Pt 1):1173-80 Farber HJ, et al. Ann Allergy Asthma Immunol. 2004 Mar;92(3):319-28. Farber HJ. J Asthma. 1998;35(1):95-9 Spitzer WO, et al. N Engl J Med 1992 Feb 20;326(8):501-6 Suissa S, et al. Thorax. 2002 Oct;57(10):880-4.
Targets: reduce ED visits/ unscheduled PCP visits Critical data source: TCH ED, PCP
Age 1-5 ,
4 of 5 below Government insurance (Medicaid or CHIP): Q2 under health insurance information Financial barrier to meds :Answered Yes to Q4 under health insurance information Previous asthma hospitalization: Yes to Q2 under past history of asthma care Chronic Severity= Mild persistent Acute Severity= Mild
Age 6+ All 3 of the following
Government insurance (Medicaid or CHIP): Q2 under health insurance information Chronic Severity= Mild persistent Acute Severity= Mild
Or All 3 of the following
Government insurance (Medicaid or CHIP): Q2 under health insurance information Exercise induced asthma: Answered yes to exercise page 3 of TEDAS. Acute Severity= Mild
Care Process Teams
Diabetes Pregnancy Asthma Transplant Pneumonia Hospital Acquired Conditions Sepsis and septic shock Obesity Appendicitis Transitions of care Survey explorer Newborn Additionally, completed a gap strategy for 38 “registries”
Content System
Using and innovating best practices Assuring an excellent patient experience Evidence Integrated practice via guidelines, order sets and measures
Improved Population Health
QI education and culture change Deployment strategy — Care Process Teams
Measurement System
Data/predictive analytics: measuring through meaningful metrics
Deployment System Knowledge management for population health
Analytic Insights Questions &
A
Session Feedback Survey
1. On a scale of 1-5, how satisfied were you overall with the Penny Wheeler, MD / Allina session?
2. What feedback or suggestions do you have for Penny Wheeler, MD / Allina session?
3. On a scale of 1-5, how satisfied were you overall with the Charles Macias / TCH session?
4. What feedback or suggestions do you have for the Charles Macias / TCH session?
54 5 4