Sloan Health System Innovation

Retsef LeviJ. Spencer Standish (1945) Professor

of Operations Management,Sloan School of Management, MIT

mHealth, Tel-Aviv, Israel, June 2015

Bio

• Israeli Defense Forces, intelligence officer (1990-2001)

• B.A. in Mathematics with trend in Operations Research, Tel-Aviv University, Israel

• PhD (2005) in Operations Research, Cornell University

• Spent a year at IBM

• Research: Inventory, supply-chain, healthcare and revenue management optimization, risk management

• Experience in industry: Healthcare (MGH, Children, Beth-Israel, AAMC), FDA, Oil Industry (Sunoco, BP), Air Force logistics, Hi-Tech, Print industry

U.S. HC System Solution Approaches

• Market Approach (Economists and Policy Makers) =

Change the incentives and market design and let the players adjust

• Front-Line Approach =

Change the system design and operations of healthcare delivery systems (create new ones) and make the change from the inside

How do we change the healthcare cost-effectiveness equation?

Multidisciplinary approach to rethink the organizational capabilities of health systems (organization design, analytics, HR policies, IT,…)

PCAST Report on Health SystemsRecommendation 1: Accelerate the alignment of payment incentives and reported information with better outcomes for individuals and populations.

Recommendation 2: Accelerate efforts to develop the Nation’s health-data infrastructure.

Recommendation 3: Provide national leadership in systems engineering by increasing the supply of data available to benchmark performance, understand a community's health, and examine broader regional or national trends.

Recommendation 4: Increase technical assistance (for a defined period—3-5 years) to health-care professionals and communities in applying systems approaches.

Recommendation 5: Support efforts to engage communities in systematic health- care improvement.

Recommendation 6: Establish awards, challenges, and prizes to promote the use of systems methods and tools in health care.

Recommendation 7: Build competencies and workforce for redesigning health care.

Health System Innovation at Sloan

• Over 30 faculty doing health related research recently formed into the Initiative for Health System Innovation

• Fits within the mission of Sloan:

- Make an impact on the world (research & outreach)- Calls for business innovation- Employment opportunities- Educational mission (certificate)

http://mitsloan.mit.edu/mba/program-components/healthcare-certificate.

• Massachusetts is pioneering in healthcare delivery (the national reform builds upon the MA reform), and a hub of health innovation

Healthcare Network

Health Systems: New Challenges

6

Academic Medical Center

Physician Organizations

Community Hospitals and Clinics

…Network1 Network2 Networkn

Manage Population Health

B2B Market Interactions

System Re-Design and Resource Deployment to meet Network’s

Objectives

Fee-for-service

Risk ContractsCapitation +

Quality

Under Risk Contracts

Pay/Design for Performance

Operations Research Applied to

Academic Medical Centers

MGH-MIT Collaboration

The Team

MGH • Perioperative Administration in collaboration with other areas:

• 950 beds, 48,500+ admissions annually

• 37,000+ surgical operations in CY14

MIT

• Sloan School of Management & Operations Research Center

• Broad set of disciplines:

Operations Research

Operations Management

Economics

Organizations

Finance

Peter Dunn, Bethany Daily

Cecilia Zenteno

Clinicians, administrators,

data analysts, project specialists

Retsef Levi

Postdoctoral Fellows

LGO Fellows (Master’s students)

Data Analytics

(decision support

tools )

Simulation-Optimization

Models (predictions)

System/Process Re-

design

(business practices)

Collaboration

Admitting

Primary Care

Neurosciences

Cancer Center

Other Specialty Outpatient clinics

Work to date

Implemented & Results

• OR scheduling of elective and non-elective cases

• Inventory management of surgical supplies - Part I

• ICU patient flow (awaiting results)

Ready to start implementation

• Intra-day surgical scheduling

• Post-surgery Recovery Area patient flow

• Cancer Center

• Primary Care Redesign

New projects

• Hospital bed capacity management (predictions & decision support)

• Primary Care Redesign – Provider Scheduling

• Critical Care

• EP – Cath Lab

• Non-Oncology Infusion

9

In Implementation

New projects

ICU Patient Flow

Objective: Study hospital-wide ICU bed availability and

throughput as part of optimizing patient flow and eliminate

patient delaysImpact:i. Increased subsequent LOS

1 day of delay 1.18 additional days on the floor

ii.~$12 million in additional costsICU cost per day ~$3.5k

iii.Longer wait times from ED/OR to ICU

Cumulative # ICU delayed bed-days2

B. Christensen, P. Cobb, B. Daily, S. Dolcetti , A. Doney, P. Dunn, J. Lee, R. Levi, D. Scheinker, T. Tehan

ICU Patient Flow

B. Christensen, P. Cobb, B. Daily, S. Dolcetti , A. Doney, P. Dunn, J. Lee, R. Levi, D. Scheinker, T. Tehan

Potential reasons for result

1. Clinical factorsStaffing (PT, OT, SLP), equipment (invasive monitoring), care elements

2. Non-clinical factorsDesign of medical plan, hand-off process between ICU and floor

Results for different Patient Segments

Segment* Delay impact (coeff., 95% CI)

a. All ICUs 1.18 [1.00,1.36]

b. Neurosurgery ICU 1.02, [0.80,1.23]

c. Neurology ICU 1.72, [1.49,1.95]

Cancer Infusion CenterObjective: Improve Infusion Center throughput by smoothing chair utilization throughout the day (MGH: Mara Bloom, Inga Lennes, Debra Burke; MIT: Wendi Reib, R. Levi)

• Midday congestion causes

perception of insufficient

capacity.

• Root-cause: (separate)

scheduling practices in Infusion

Unit and Practice.

• Developed scheduling algorithm

that takes into account relevant

constraints.

.

Avg (std. dev.) peak reduction: 57 (±7.6) to 40 (±4.9)

0

10

20

30

40

50

60

Infusion Center Average Uti-lization

Retrospective Orig

Time of Day

Chair

s

Current State

0102030405060

Infusion Center Average Uti-lization

Retrospective OrigProspective

Time of Day

Chair

s

CurrentState

New Approach to Safety and Risk Management

Joint work with Fernanda Agnes Hu, Yiyin-Ma and Adam Traina from MIT

and Pat Folcare, Danny Talmor and others from Beth Israel Deaconess Medical Center

Quality Efforts in the U.S.

• To Err is Human (IOM, 2000)

• 5 Million (100K) Lives Campaign (IHSI, 2006)

• Check List (Peter Pronovost, J. Hopkins, 2008)

- Millions of central lines are put every year in ICUs- 4% of patients develop infection- 5-25% mortality rate and extensive LOS- Reduced infection rate by 66% in 18 months

• Measure safety through frequency of (a few) harms and develop (many) check lists

New Approach

• Develop a notion of aggregated ‘burden of harm’ (allows statistical power)

• Identify ‘environmental’ and system risk (states) drivers (unit and shift level) that lead to harm

• Apply statistical models to find correlation that identifies risky states (higher likelihood of harm)

• Intervene to monitor, control and avoid risky states!

The “Burden of Harm”Consortium Defined HarmsCLABSIVAC/IVAC/PossVAP/ProbVAPHigh Tidal VolumeVTE-PEICU-Acquired DeliriumDecrease in Function Mobility Scale

BIDMC Incident Reporting SystemICU-Acquired Pressure UlcerFallsMedication / Fluid ErrorLab Specimen IdentificationCommunication / Handoff IssueCode Purple / SecurityNutrition…

IHI Global Trigger ToolPositive C. Diff and Blood CultureBleedingOversedatoinReadmission to ICUReintubation and Unplanned ExtubationGlucose < 50 while on insulin BUN or Creatinine Doubled BaselinePTT > 100 while on HeparinINR > 6 while on WarfarinAdministering NaloxoneAdministering Vitamin K

Other Source (BIDMC)Catheter-associated Urinary Tract InfectionIatrogenic PneumothoraxCode Blue

Risk Drivers

AcuitySOFA ScoreNursing IntensityLength of Unit StayLength of Hospital StayPts in first 24 hrs

ExperienceFloat NurseNew Nurse <1 yearRare Unit ProcedureBoarding Patient

Other EventsReadmission"ED Critical"UnitNight shift vs Day shiftWeekend vs Weekday

UtilizationHours of CareAdmissionsDischargesNursing Intensity Score (Workload)

Risk Drivers:Conditions (states) of the ICU environment, system and people in the system that increase the likelihood of harms

Statistical Analysis

• Assume common risk drivers to harms

• Employ statistical analysis to identify risky (safe) states of increased (decreased) likelihood of harm

• Many technical challenges!

- Descriptive identification of risky states- How to aggregate harm?- How to validate?

Risky State (I)

Driver Low High

TISS 24.59

New Nurse

24%

Staff Ratio

2:1

Float Nurse

21%

Boarders 76%

SOFA 11.8

The chance of harm is 7%

Number of Shifts:124

P-Value 1.54e-05

Success Drivers and Challenges

• System level innovation is essential for creating required organizational capabilities

• Multi-lens approach and skills are key! (analytics, organizational change management, behaviors)

• New formats of collaboration needed (learn the respective characteristic of the organization)

• System innovation: Models to predict impact? Infrastructures to test ideas? Methodologies to measure post implementation effectiveness?