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Clinical Optimization: One Approach to Integration

Session #192, February 14, 2019

Dr. Hiloni Bhavsar, Associate Director, Quality & Safety, Rochester General Hospital

James Williams, VP of Integration, Rochester Regional Health

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Dr. Hiloni BhavsarHas no real or apparent conflicts of interest to report

James Williams, MHSAHas no real or apparent conflicts of interest to report

Conflict of Interest

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• Learning Objectives

• Organization Overview

• Clinical Optimization Program Discussion

– Overview and Background

– Performance Improvement Process: Heart Failure Example

– Work Done to Date

– Challenges

– Future Areas of Focus

• Open Discussion (Encourage Questions / Comments Throughout)

Agenda

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• Describe an enterprise-wide approach to use clinical analytics to

drive performance improvement

• Describe a sustainable process to support clinical performance

improvement projects

• Discuss a methodology focused on understanding variations of

care to drive clinical integration and improve clinical outcomes

• List examples on how disparate clinical teams came together to

establish standards of care

Learning Objectives

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Organization Overview

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To enhance lives and preserve health by enabling access to a comprehensive, fully integrated network of the highest quality and most affordable care, delivered with kindness, integrity and respect.

Rochester Regional Health: Our Mission

Source: Rochester Regional Health Website

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Rochester Regional Health

2,500+medical staff

16K+system employees

87+primary care & ambulatory locations

5hospital locations

936long term care beds

8senior living facilities

370Kbehavioral health visits

54Patient lab testing sites

1M+clinical trials tests

245K+emergency room visits

1,600+system volunteers

Source: Rochester Regional Health

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Right Care. Right Time. Right Place.

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United Memorial

Medical Center

Unity HospitalRochester

General Hospital

Newark Wayne

Community Hospital

Clifton

Springs Hospital &

Clinic

Source: Rochester Regional Health

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Has your organization undergone a recent merger?

1. Past 1 year

2. Past 2-3 years

3. Planning in next 12-24 months

4. None

Audience Polling #1

https://live.eventbase.com/polls?event=himss19&polls=5147

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Clinical Optimization Program Discussion

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Which of the following applies regarding EMR in your organization?

1. Single EMR system across facilities

2. Multiple EMR systems across facilities

3. EMR + Paper

4. Paper

Audience Polling #2

https://live.eventbase.com/polls?event=himss19&polls=5148

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Where is your organization in the evolution of addressing variations in care?

1. Initial phases of discussion

2. Projects initiated but not fully integrated

3. Design and implementation

4. Sustained projects with results

Audience Polling #3

https://live.eventbase.com/polls?event=himss19&polls=5149

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• Reduce variation

• Create a culture of High Reliability

• Develop consistent clinical and patient experience across the continuum

• Utilize and implement evidence-based standards of care

• Yield sustainable results

Clinical Optimization Program Overview & Background

Principles of High Reliability Clinical Optimization

Deference to Expertise

Sensitivity of Operations

Reluctance to Simplify

Preoccupation with Failure

Commitment to Resilience

Clinical leads determine evidence based

approach for standardization

Understand current context to identify areas of

opportunity

Recognize value of reducing variation while

appreciating inherent complexity

Build in control plans to flex with future

changes/modifications, new sources of variation

Build in practice of rapid assessment and

improvement cycles that are data driven

Clinical Optimization Program Overview & Background

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• Using internal data, reviewed cost-per-case distribution for each DRG

• Establish internal peer-groups: system average cost-per-case and low-cost provider

• Run statistics for performance ranges to identify focus area

Clinical Optimization Program Overview & Background

Example

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# PLM - Product Case Count1 SDV + Mean

(System Avg)

1 SDV + Mean

(System Best)

Excess

Days

AVG SDV %

of Mean

1IP Other Medical 5,934 $3,666,263 $5,884,001 10,636 92%

2IP General/GI/Endocrine Surgery 2,776 $3,027,795 $8,101,527 8,606 66%

3IP Cardiac - Medical 4,916 $2,029,466 $3,477,155 6,153 79%

4IP Respiratory 3,711 $1,799,741 $3,097,401 5,150 80%

5IP Orthopedic Surgery 4,665 $1,648,500 $4,084,207 4,309 38%

6IP Gastroenterology 3,190 $1,144,384 $2,002,984 3,787 78%

7IP Nervous System 2,475 $1,140,282 $2,338,849 4,307 78%

8IP Neurosurgery 1,235 $998,915 $2,225,799 1,585 53%

9IP Cardiac Valve 400 $941,129 $941,129 1,084 50%

10IP Oncology/Hematology 1,135 $900,603 $1,614,253 1,890 98%

11IP Nephrology 1,711 $880,301 $1,328,587 3,008 98%

12IP Acute Rehab 482 $767,959 $1,817,588 4,438 78%

13IP Acute Psych 1,395 $753,280 $3,229,544 6,187 114%

14IP Surgical Other 515 $549,881 $4,817,101 4,831 111%

15IP Cardiothoracic Surgery 305 $513,883 $687,814 719 64%

SUBTOTAL 34,845 $20,762,383 $45,647,938 66,689 N/A

GRAND TOTAL 53,040 $26,619,455 $58,523,681 81,257 72%

OB (Special Care, Vaginal

Delivery, C-Section, Newborns)9,058 1,327,322 4,345,980 1,965 59%

% of Total 2015 Statistics 100% 8% 19% 31% N/A

Clinical Optimization Program Overview & Background

Volume

assessment

DRG Grouping

Engaged leaders

Data Source: EPSI, FY 15, Jan-Sep FY 16 inpatients, no exclusions

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Performance Improvement ProcessExample: Heart Failure

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Performance Improvement: Approach

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1. Macro-Analysis: Heart Failure Example

LOS largely driven by

discharge disposition

LOS largely driven by admit

day of the week

30-day readmission rates

higher than CMS targets

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FY 15 – YTD Sep FY 16 IP LOS by Discharge StatusMS DRG 291 Heart Failure Shock w/ MCC

Data Source: EPSI, FY 15, Jan-Sep FY 16 inpatients, no exclusions

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FY 15 – YTD Sep FY 16 IP LOS and Discharges by Day of Week

Enc –

MS DRG

CMS

ALOS

Admit Day of the Week - ALOS

Mon Tue Wed Thu Fri Sat Sun

293 3.1 2.75 2.60 2.65 2.80 3.46 2.51 2.40

292 4.5 4.27 4.64 4.69 4.74 4.50 4.47 3.67

291 5.9 5.12 5.83 5.75 6.17 6.21 6.32 5.85

Enc -

MS DRG

% of Cases Discharged by Discharge Date

Mon Tue Wed Thu Fri Sat Sun

293 15% 18% 16% 17% 19% 7% 8%

292 15% 16% 19% 17% 18% 7% 9%

291 15% 18% 18% 19% 18% 8% 5%

Enc -

MS DRG

% of Cases Admitted by Admit Date

Mon Tue Wed Thu Fri Sat Sun

293 18% 15% 14% 18% 15% 11% 10%

292 17% 15% 13% 14% 17% 13% 11%

291 19% 17% 13% 13% 15% 11% 13%

Data Source: EPSI, FY 15, Jan-Sep FY 16 inpatients, no exclusions

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HospitalPredicted

Readmission [a]

Expected

Readmission [b]

Excess Readmission

Ratio [c]

National Observed

Readmission [d]

NWCH 26.5% 21.8% 1.2152 21.9%

RGH 25.6% 21.8% 1.1732 21.9%

UNITY 21.8% 21.4% 1.0220 21.9%

UMMC 24.4% 20.8% 1.1709 21.9%

CLIFTON 22.9% 22.7% 1.0094 21.9%

[a] The 30-day readmission rate predicted on the basis of your hospital’s performance with its observed case mix and your hospital’s estimated

effect on readmissions (provided in your hospital discharge-level data). The Predicted Readmission Rate is also referred to as "Adjusted Actual

Readmissions" in Section 3025 of the Affordable Care Act.

[b] The 30-day readmission rate expected on the basis of average hospital performance with your hospital’s case mix and the average hospital

effect (provided in your hospital discharge-level data).

[c] Ratio of the predicted readmission rate [d] to the expected readmission rate [e]. (Note: Due to rounding the Excess Readmission Ratio may not

be the exact ratio of the numbers in columns D and E; see the replication instructions for how to exactly replicate the results in column F). The

Excess Readmission Ratio (also referred to as the Standardized Readmission Ratio [SRR]) is the measure that will be used to determine the

payment adjustment for the Program. If a hospital performs better than an average hospital that admitted similar patients (that is, patients with

similar risk factors for readmission such as age and comorbidities), the ratio will be less than 1.0000. If a hospital performs worse than average, the

ratio will be greater than 1.0000. Excess Readmission Ratios greater than 1.0000 will be included in the payment adjustment formula.

[d] The number of eligible unplanned 30-day readmissions nationally divided by the number of eligible discharges nationally.

Hospital Discharge Period: July 1, 2012 through June 30, 2015

CMS Public Reporting :Hospital Readmissions Reduction Program (HRRP) for Heart Failure

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2. Prioritization and Roadmap: Heart Failure ExampleBased on the data, the team identified areas where heart failure care can be improved.

We prioritized and mobilized four workgroups.

Work Groups

Wave 1: March - June

a. Standard Care Process

b. Medication Reconciliation

c. High-Risk Care Management

Wave 2: September

d. Home Health & SNF Care

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3. 90 Day Improvement Cycle: Heart Failure ExampleOnce the three workgroups were identified and mobilized, they each went through a

90-day improvement cycle.

Completed SWOT analysis

to develop current state

Identified gaps between

current/future statesDeveloped Heart Failure

initiative roadmap

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• Physician Champion on-board

• Existing HF care pathway at UH

• Institutional Support

• Collaboration with eHealth at Home

• Telemedicine support

• Poor identification and tracking of high-risk

patients

• Lack of adequate O/P care management

resources

• Inefficient med rec process at admission

• Non-standardized handoffs at transitions of

care

• Gap in patient medication knowledge

• No evidence standard HF care pathway in I/P

(built into care connect) and O/P setting

• Introduction of new positions (i.e, Nurse

Navigator, Practice Manager, Data

Analyst positions)

• Further education of community and

patients

• Improve patient and family experience

through care process (i.e. pharmacy-led

d/c medication counseling)

• Participation in clinical trials

• ED Avoidance/Admission –

Decrease in value

• PCP potentially view clinic and

eHealth at home O/P care

strategies as a threat

• Reimbursements

Strengths Weaknesses

Opportunities Threats

Current State – SWOT Analysis

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Gap Analysis

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Phases of Implementation

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4. Implement: Heart Failure Example

Workgroup Initiative

Medication

Reconciliation

Create minimum standards and standardized grading system for medication

reconciliation at admission

Pilot pharmacy-led medication counseling at discharge

Standard Care

Process

Build inpatient HF order set

Develop heart failure care pathway for Home Health patients

High-Risk Clinic

Pilot Heart Failure RN at RGH

Design and Build Heart Failure bricks and mortar clinic (lead by RGH Cardiology Dept)

At the end of the 90-day improvement cycle, six individual initiatives were ready for

implementation.

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4. Sustain and Monitor: Heart Failure ExampleThe team identified LOS and Readmissions as an opportunity; therefore, we will regularly monitor our

performance against these metrics.

Data Source: Premier/HF Dashboard/SQL Reporting

- RGH LOS and Readmission (Jan’ 16- Dec ‘16)

- MS-DRG Codes 291-293

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Discussion/Questions So far?

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Work Done to Date

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Work Done to Date

1 Sustain results and spread work

2Enhance physician engagement and

ownership

3Increase collaboration with Hospital

Capacity Management

4 Launch new teams

5 Further advance analytical tools

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RGH UHEastern

RegionUMMC GRIPA LTC Home Health

Heart Failure

Medication Reconciliation

Order Set Pending Pending

Home Care

PathwayPending Pending

Home Care

Pathway

High-Risk Clinic

Care

Transitions

ED Pathway

Daily Rounds

Stroke

Coding / Documentation

Order Sets

Imaging

Orthopaedics Joint Class Improvements

Sepsis 90-Day Improvement Cycles (System-Wide Initiative)

COPD 90-Day Improvement Cycles (System-Wide Initiative)

Bundled

Payments

Behavioral Health Schizophrenia Care Pathway

Oncology GI Cancer

1. Sustain Results and Spread Work

Original Clinical Optimization

Steering Committee

Chair: James Williams

Administration 9

Service Line Physician Leaders 0

Service Line Administrators 1

Business Intelligence 1

Finance / Supply Chain 1

IT & S 0

Quality Safety Institute and Clinical Optimization 1

2018 Clinical Optimization &

Hospital Capacity Management

Steering Committee

Chairs: Hiloni Bhavsar, MD & Anil Job, MD

Administration 2

Service Line Physician Leaders 3

Service Line Administrators 3

Business Intelligence 1

Finance / Supply Chain 2

IT & S 1

Quality Safety Institute and Clinical Optimization 3

The governance structure has evolved over the past two years to be chaired by two physician leaders and become more multi-disciplinary. This has resulted in enhanced physician ownership and engagement in the process.

2. Enhance Physician Engagement & Ownership

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Hospital Capacity Management (HCM) was initially a separate work group. Clinical optimization work and

hospital capacity management are tightly linked in terms of impact on process implementation and outcomes.

3. Increase Collaboration with Hospital Capacity Management

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How do you identify drivers of capacity or throughput in your organization?

1. External data analytics (Premier, Vizient etc.)

2. Internal metrics

3. Both

Audience Polling #4

https://live.eventbase.com/polls?event=himss19&polls=5150

COPD

• Launched four groups focusing on:

• Order Sets

• Pulmonary Rehab

• POET Clinic Expansion

• Education

Behavioral Health

• Trained the Trainer

• BH Team independently managed CO process

• Developed 10-day clinical pathway for treatment of Schizophrenia across RRH

Bundled Payment (February 2019

Update)

• Launched program on Oct 1, 2018 at NWCH

• Two bundles selected: AMI and GI Obstruction

• More information to come in Feb. 2019

Cancer Committee

• American College of Surgeons Commission on Cancer Accreditation requires annual quality studies and improvement projects

• Clinical Optimization approach was used to study GI cancer LOS

4. Launch New TeamsExpand Clinical Optimization framework to new clinical and service line areas.

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SYSTEM

Rochester Regional Health(Clinical Outcome View)

Clinical BundleBaseline

(2017)

Current

MonthPrevious Month Year to

DateMAR 2018 FEB 2018

LO

S

(Geo.

Mean) COPD 0.79 0.90 0.82 0.87

Heart Failure 0.94 0.90 1.07 0.98

Ortho 0.95 0.88 0.88 0.88

Sepsis 1.02 1.08 1.09 1.08

Stroke 1.00 1.05 1.27 1.07

Readm

issio

ns COPD 1.42 1.59 1.68 1.49

Heart Failure 1.39 1.33 1.79 1.53

Ortho 1.18 1.66 0.77 1.33

Sepsis 1.24 1.10 1.55 1.27

Stroke 1.36 1.63 1.04 1.55

Mort

alit

y

COPD 0.62 0.78 0.85 0.89

Heart Failure 0.74 0.99 0.79 0.95

Ortho 0.68 0.00 0.00 0.49

Sepsis 0.85 0.80 0.79 0.87

Stroke 0.86 1.04 0.76 0.88

SYSTEM

Rochester Regional Health(Clinical Bundle View)

Clinical BundleBaseline

(2017)

Current

MonthPrevious Month Year to

DateMAR 2018 FEB 2018

CO

PD LOS (Geo) 0.79 0.90 0.82 0.87

Readmissions 1.42 1.59 1.68 1.49

Mortality 0.62 0.78 0.85 0.89

Heart

Failu

re LOS (Geo) 0.94 0.90 1.07 0.98

Readmissions 1.39 1.33 1.79 1.53

Mortality 0.74 0.99 0.79 0.95

Ort

ho LOS (Geo) 0.95 0.88 0.88 0.88

Readmissions 1.18 1.66 0.77 1.33

Mortality 0.68 0.00 0.00 0.49

Sepsis LOS (Geo) 1.02 1.08 1.09 1.08

Readmissions 1.24 1.10 1.55 1.27

Mortality 0.85 0.80 0.79 0.87

Str

oke LOS (Geo) 1.00 1.05 1.27 1.07

Readmissions 1.36 1.63 1.04 1.55

Mortality 0.86 1.04 0.76 0.88

5. Further Advance Analytical Tools

An interactive and

near real-time

dashboard was

developed for use

by leaders across

RRH.

5. Further Advance Analytical ToolsSample Clinical Optimization Dashboard

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Major Themes Across Work Streams

Standard Terminology/

Defintions

• Standardizing clinical criteria

• Building consensus on treatment protocols

• Standardizing application of clinical definitions

• Documentation and coding consensus

Evidence Based Workflow via EMR

• Creating order sets

• Clinical pathways

• Implementing clinical decision support tools

• Utilizing reports for compliance

Education/Training

• Broad system based education

• Training for new workflows via online learning

• Knowledge builders for EMR based workflows

• System wide communication of new workflow

Role/Resource Standardization

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Challenges

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• More work added to the RRH IT queue

• Clinician time

• Resource competition

• Competing priorities

• Recently merged health system

• Timelines for implementation

• Control phase monitoring

Challenges

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Future Areas of Focus

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• Sepsis

– Consensus for definitions, EMR workflow via alerts/order sets, clinical pathway

• Supply Chain

– Physician Preference Items

– Resource utilization

• Pharmacy

– Roll-out of Premier Service-Line Analytics

– Value-analysis; cost versus quality

• Sustainability of Clinical Optimization

– Develop model for sustainability and growth

Future Areas of Focus

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Dr. Hiloni Bhavsar

Associate Director, Quality & Patient Safety

Rochester General Hospital

Rochester Regional HealthHiloni.bhavsar@rochesterregional.org

James Williams, MHSA

Vice President of Integration

Rochester Regional HealthJames.Williams@rochesterregional.org

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