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Controlling Cost $ through Data-Based Medical Management

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Controlling Cost $ through Data-Based Medical Management. Patrick Venditti , MHA Director - BJC HealthCare. Jo Daviess. Jo Daviess. Stephenson. Stephenson. Winnebago. Winnebago. Boone. Boone. Mchenry. Mchenry. Lake. Lake. Carroll. Carroll. Ogle. Ogle. Kane. Kane. De Kalb. - PowerPoint PPT Presentation
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Controlling Cost$ through Data-Based Medical Management Patrick Venditti, MHA Director - BJC HealthCare
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Page 1: Controlling Cost $  through  Data-Based Medical Management

Controlling Cost$ through Data-Based Medical

ManagementPatrick Venditti, MHA

Director - BJC HealthCare

Page 2: Controlling Cost $  through  Data-Based Medical Management

Platte

Adair

Adams

Alexander

Andrew

Atchison

Audrain

Barry

Barton

Bates Benton

Bollinger

Bond

Boone

Boone

Brown

Buchanan

Bureau

Butler

Caldwell

Calhoun

Callaway

Camden

Cape Girardeau

Carroll

Carroll

Carter

Cass

Cass

Cedar

Champaign

Chariton

Christian

Christian

Clark

Clark

Clay

Clay

Clinton

Clinton

Cole

Coles

Cook

CooperCrawford

Crawford

Cumberland

Dade

Dallas

Daviess

De Kalb

De Kalb

De Witt

Dent

Douglas

Douglas

Du Page

Dunklin

Edgar

Edwards

EffinghamFayette

Ford

Franklin

Franklin

Fulton

Gallatin

Gasconade

Gentry

Greene

Greene

Grundy

Grundy

Hamilton

Hancock

Hardin

Harrison

Henderson

Henry

Henry

Hickory

Holt

Howard

Howell

Iron

Iroquois

Jackson

Jackson Jasper

Jasper

JeffersonJefferson

Jersey

Jo Daviess

Johnson

Johnson

Kane

Kankakee

Kendall

Knox

Knox

La Salle

Laclede

Lafayette

Lake

Lawrence

Lawrence

Lee

Lewis

Lincoln

LinnLivingston

Livingston

Logan

MaconMacon

Macoupin

Madison

Madison

Maries

Marion

Marion

Marshall

Mason

Massac

Mcdonald

Mcdonough

Mchenry

Mclean

Menard

Mercer

Mercer

Miller

Mississippi

Moniteau

Monroe

Monroe

Montgomery

Montgomery

Morgan

Morgan

Moultrie

New Madrid

Newton

Nodaway

Ogle

Oregon

Osage

Ozark

Pemiscot

Peoria

Perry

Perry

Pettis

Phelps

Piatt

Pike

Pike

Polk

PopePulaski

Pulaski

Putnam

Putnam

Ralls

Randolph

RandolphRay

Reynolds

Richland

Ripley

Rock Island

Saline

Saline

Sangamon

Schuyler

Schuyler

Scotland

Scott

ScottShannon

Shelby

Shelby

St. Charles

St. Clair

St. ClairSt. Francois

St. Louis

Stark

Ste. Genevieve

Stephenson

StoddardStone

Sullivan

Taney

Tazewell

TexasUnion

Vermilion

Vernon

Wabash

Warren

Warren

Washington

Washington

Wayne

WayneWebster

White

Whiteside

Will

Williamson

Winnebago

Woodford

Worth

Wright

Adams

Alexander

Bond

Boone

Brown

Bureau

Calhoun

Carroll

CassChampaign

Christian

Clark

ClayClinton

Coles

Cook

Crawford

Cumberland

De Kalb

De Witt

Douglas

Du Page

Edgar

Edwards

EffinghamFayette

Ford

Franklin

Fulton

Gallatin

Greene

Grundy

Hamilton

Hancock

Hardin

Henderson

Henry

Iroquois

Jackson

Jasper

Jefferson

Jersey

Jo Daviess

Johnson

Kane

Kankakee

Kendall

Knox

Lake

La Salle

Lawrence

Lee

Livingston

Logan

Mcdonough

Mchenry

Mclean

Macon

Macoupin

MadisonMarion

Marshall

Mason

Massac

Menard

Mercer

Monroe

Montgomery

MorganMoultrie

Ogle

Peoria

Perry

Piatt

Pike

PopePulaski

Putnam

Randolph

Richland

Rock Island

St. Clair

Saline

Sangamon

Schuyler

Scott

Shelby

Stark

Stephenson

Tazewell

Union

Vermilion

Wabash

Warren

Washington Wayne

White

Whiteside

Will

Williamson

Winnebago

Woodford

Adair

Andrew

Atchison

Audrain

Barry

Barton

Bates Benton

Bollinger

Boone

Buchanan

Butler

Caldwell

Callaway

Camden

Cape Girardeau

Carroll

Carter

Cass

Cedar

Chariton

Christian

Clark

Clay

Clinton

Cole

Cooper

Crawford

Dade

Dallas

DaviessDe Kalb

Dent

Douglas

Dunklin

FranklinGasconade

Gentry

Greene

Grundy

Harrison

Henry

Hickory

Holt

Howard

Howell

Iron

Jackson

Jasper

Jefferson

Johnson

Knox

Laclede

Lafayette

Lawrence

Lewis

Lincoln

LinnLivingston

Mcdonald

Macon

Madison

Maries

Marion

Mercer

Miller

Mississippi

Moniteau

Monroe

Montgomery

Morgan

New Madrid

Newton

Nodaway

Oregon

Osage

Ozark

Pemiscot

Perry

Pettis

Phelps

Pike

PolkPulaski

Putnam

RallsRandolphRay

Reynolds

Ripley

St. Charles

St. ClairSte. GenevieveSt. Francois

St. Louis

Saline

SchuylerScotland

ScottShannon

Shelby

StoddardStone

Sullivan

Taney

Texas

Vernon

Warren

Washington

WayneWebster

Worth

Wright

BJC has 27,105 employees, and is the largest private employer in Missouri. (31,000 + 3,800 Volunteers)

Consists of 13 Hospitals and multiple community health locations within 150 mile radius of metropolitan St. Louis

BJC retains 4 of the Top Ten occupations with the most musculoskeletal disorders with days away from work: *

#2 Nursing aides, orderlies, and attendants#5 Registered Nurses#7 Janitors and cleaners#10 Maintenance and repair workers

* U.S. Department of Labor, Bureau of Labor Statistics. Nonfatal Occupational Injuries and Illnesses Requiring Days away From Work. 2006”. http://www.bls.gov/iif]

Page 3: Controlling Cost $  through  Data-Based Medical Management

10,157 - 38% - engage in patient handling

Average weight of patients at 4 of our largest hospitals ranges from 225-275 pounds

1,483 laborers, material handlers, housekeepers, maintenance and repair workers, etc. whom are at risk for strains and sprains from lifting, bending, twisting, reaching, pushing and pulling.

4 High-Injury Risk occupational groups make up 43% of our employee population;

as high as 68% at the hospitals

Page 4: Controlling Cost $  through  Data-Based Medical Management

2005 - Self-Administered

Self-Insured in Missouri since 1995; in Illinois since 2002SIR for Injuries - $1,000,000 per event;

Illnesses - $1,000,000 per individual

1995-2004 – Administered by various TPAs

3 Senior Case Coordinators (Adjusters)3 Technical SME’s

• Claims System & Compliance• Medical Claims Auditor –

Coding• System Programmer Analyst

Page 5: Controlling Cost $  through  Data-Based Medical Management

3 Soft-Tissue Back claimsfrom Lifting

Brian Pete Sam

Brian SamPete • Male• 32 years old• File Clerk• 1 prior claim• Employed 6 years

• Male• 48 years old• Mechanic• No prior claims • Employed 15 years

• Male• 38 years old• Welder• 3 prior claims• Employed 2 years

Page 6: Controlling Cost $  through  Data-Based Medical Management

• Female• 32 years old• File Clerk• 1 prior claim• Employed 6 years

• Male• 48 years old• Mechanic• No prior claims • Employed 15 years

• Male• 38 years old• Welder• 3 prior claims• Employed 2 years

Which claim is likely to:- Have delayed recovery?- Develop narcotic dependency?- Lose most time from work?- Become difficult to manage medically?- Cost the most?

3 Soft-Tissue Back claimsfrom Lifting

Brian SamPete

Page 7: Controlling Cost $  through  Data-Based Medical Management

Minimal

Moderate

High

Who is at the Highest Risk?

Page 8: Controlling Cost $  through  Data-Based Medical Management

Chronic Pain Syndrome

Get hooked on opiates

>$300K

??????

See 5 or more

doctors

Have several “unsuccessful”

surgeries

Page 9: Controlling Cost $  through  Data-Based Medical Management

Data Gathering Tool ◦ Collect Information on factors that could detect high probability for delayed

recovery… from supervisor, occupational health nurse, employee, health care providers

Step One: Case Risk Assessment

Page 10: Controlling Cost $  through  Data-Based Medical Management

Medical Severity

Pain Perception

PersonalRisk Factors

Claimant

Four Categories Of Risk

PsychosocialBehavioral

Factors

Page 11: Controlling Cost $  through  Data-Based Medical Management

Medical Severity

Minimal

Moderate

High

Based on expected Lost-time and/or

Surgery or Hospitalization

Page 12: Controlling Cost $  through  Data-Based Medical Management

Pain Perception

Medical Severity

Pain Perception

Claimant

Page 13: Controlling Cost $  through  Data-Based Medical Management

Pain Drawing

Measuring Pain Perception

Visual Analog Scale

0 – “Normal”1 – “Abnormal”

0 – 10 Scale

Page 14: Controlling Cost $  through  Data-Based Medical Management

Psychosocial Behavioral Factors

Medical Severity

Pain Perception

BehavioralFactors

Claimant

Page 15: Controlling Cost $  through  Data-Based Medical Management

• Psychosocial Behavioral Factors1. Prior Claims2. Causation Issues3. Delayed Reporting4. Contrary Witnesses or No Witnesses5. Upset, disgruntled6. Absenteeism, disciplinary issues7. Layoff, termination issues 8. Lack of Objective Findings at time of report9. Expectations (recovery, pain, RTW)10. Catastrophizing11. Litigation12. Other Psychosocial issues (Financial, Domestic, etc.)

Page 16: Controlling Cost $  through  Data-Based Medical Management

• Personal Risk Factors (CoMorbidities) Pre-existing Medical Conditions Biological, Lifestyle Factors, e.g.

Age BMI Smoking Diet Exercise Sleep, etc.

Under Physician’s Care Prior Injuries, Accidents, Surgeries Current Medications

Page 17: Controlling Cost $  through  Data-Based Medical Management

Adding non-traditional data elements from multiple sources adds insight and perspective when evaluating the potential exposure of a claim.

Brian SamPete• Male• 32 years old• File Clerk• 1 prior claim• Employed 6 years• Married

• Male• 48 years old• Mechanic• No prior claims • Employed 15years• Married

• Male• 38 years old• Welder• 3 prior claims• Employed 2 years• Single

• Medical Severity – Benign – no expected Lost-time

• Pain Perception – Abnormal

• Upset, disgruntled• Lack of Objective

Findings at time of report

• Other Psychosocial issues (Financial, Domestic, etc.)

• (-) Lifestyle Indicators

• Medical Severity – Benign – no expected Lost-time

• Pain Perception – Abnormal

• Upset, disgruntled• Lack of Objective

Findings at time of report

• No Psychosocial Issues• (-) Lifestyle Indicators

• Medical Severity – Benign – no expected Lost-time

• Pain Perception – Normal

• Calm, cooperative• Objective Findings at

time of report• No Psychosocial Issues• (+) Lifestyle Indicators

Page 18: Controlling Cost $  through  Data-Based Medical Management

Brian

Sam

Pete

LOW HIGHEXPOSURE

Clai

m O

utco

mes

Page 19: Controlling Cost $  through  Data-Based Medical Management

PersonalRisk Factors

BehavioralFactors

Medical Severity

Pain Perception

Claimant

Minimal

Case Coding for Risk Level

Page 20: Controlling Cost $  through  Data-Based Medical Management

Personal Risk Factors

BehavioralFactors

Medical Severity

Pain Perception

Claimant

High

Case Coding for Risk Level

Page 21: Controlling Cost $  through  Data-Based Medical Management

Step Two: Select Appropriate

Medical Provider

Page 22: Controlling Cost $  through  Data-Based Medical Management

Med-LegalManagement Skills

Good Clinical Outcomes

•Functional Recovery•Infection Rates•Pain Management•Disability•ROM•Strength•Patient Satisfaction•Best Practice Guidelines (ODG, MDA; ACOEM)…..

Lost-days Restricted Days Rehab Visits

CPT procedures - Imaging

Medications Surgery

•Are accessible when needed•Timely Information without bias•Prompt Communication •Reports – Logical, Evidence-Based, w/o bias, defensible•Appropriate Ratings - when requested•Consistency in reports, depos, testimony•Estimated MMI•Manage patient expectations•RTW within guidelines (ODG, MDA)•Medical Costs within guidelines (ODG, MDA)•Manage High Risk Cases•ACOEM – IAIABC Guuidelines

Page 23: Controlling Cost $  through  Data-Based Medical Management
Page 24: Controlling Cost $  through  Data-Based Medical Management

Vetting Process

Education

Analytics Communication•Internal Data•Key Performance Indicators

Guidelines:ODG, MDA-ACOEM

>150 Providers

•WC 101•Our Expectations•Our Processes

Page 25: Controlling Cost $  through  Data-Based Medical Management

ModerateRisk

HIGHRISK

HIGHRISKSkills

Page 26: Controlling Cost $  through  Data-Based Medical Management

HighRisk

LowRISKSkills

Page 27: Controlling Cost $  through  Data-Based Medical Management

$300K+Chronic Pain

Syndrome

Get hooked on opiates

See 5 or more

doctors

Have several “unsuccessful”

surgeries

Page 28: Controlling Cost $  through  Data-Based Medical Management

Historical Claim & Statistical Data

Page 29: Controlling Cost $  through  Data-Based Medical Management

Type 2005 2006 2007 2008 2009 2010 6 year total

Rotator cuff - shoulder surgeries 16 15 7 11 8 5 62Knee Surgery 14 4 5 7 8 1 39Carpal Tunnel Surgery 5 2 3 8 3 2 23Elbow Surgery 4 4 3 1 1 1 14Hand, Finger, Thumb Surgeries 6 1 2 1 2 2 14Foot and Ankle Surgeries 2 0 7 2 1 0 12Hernia repair 2 4 2 3 0 2 13Wrist Surgery 4 0 4 1 0 0 9Lumbar laminectomy and microdiscectomy 2 2 1 1 1 1 8Spinal Fusion - Lumbar 1 0 3 1 2 1 8Oral or facial Surgery 2 4 0 0 0 0 6Cervical Fusion 0 0 1 1 1 3 6Eye surgery 0 0 1 0 1 0 2Hip Surgery 0 0 0 2 0 0 2

Totals 58 36 38 37 28 18 218

Workers Compensation Administration Surgical History 2005-2010

Page 30: Controlling Cost $  through  Data-Based Medical Management

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 -

50

100

150

200

250

300

268

215

195

179

159 156

169 165

200

93 101

65 70 76

72 72

Workers' CompensationLost Time Cases as of 12/31/2010

Average 180

Average 76

58%

Page 31: Controlling Cost $  through  Data-Based Medical Management

Average = 6 week

Average Range = 4-8

Average Lost-Time Cases a week for 27,000 + employee - 13 Hospital Organization

2005-2010

Page 32: Controlling Cost $  through  Data-Based Medical Management

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 $-

$100,000

$200,000

$300,000

$400,000

$500,000

$600,000

$700,000

$800,000

$672,678

$355,257

$667,077

$354,680

$527,202

$591,326

$680,592

$423,373

$524,821

$183,415

$84,411

$152,481

$184,000

$134,669 $132,561

$153,837

Workers' Compensation Temporary Total Disability (TTD) Payments(lost wage benefits)

as of 12/31/2010

$533,000

$140,326

74%

Page 33: Controlling Cost $  through  Data-Based Medical Management

1

2

3

4

5

6

7

8

9

10

11

12

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

0

1.5

0

0

0.600000000000001

0.600000000000001

0.3

1.8

1.75

0.4

0.5

0

Opioid Medication Duration

Duration on Opioid Medication (Months)

Lost-time Cases - ≥3 mos.

Humeral neck Fracture

Cervical Fusion 2- level

Cervical Fusion 2- level

Risk Level(Color code)

Rotator Cuff Strain (Non-surg)

Med. Meniscus L Knee Surgery

Patellar fracture

Lost-time Duration (months)

3.0

3.0

3.1

3.4

3.5

4.2

4.2

5.1

5.3

8.2

10.5

12.6

Shoulder sprain

Hand tendon release

Rotator cuff surgery

Asthma Reaction

Lumbo-sacral radiculitis

Concussion

Page 34: Controlling Cost $  through  Data-Based Medical Management

Healthcare Cost - $1.31 $100 payroll

Milliman Mean Hospital Client Cost - $1.10 per $100 payroll

BJC Cost - $.51 per $100 payroll

$0

$5,000,000

$10,000,000

$15,000,000

$20,000,000

$16.7M

$14M

$6.5M

Workers' Compensation Costs Based on BJC 2011 Payroll

*Ultimate costs are the estimated costs for the life of the claims

Source: Milliman Actuarial Consultants Inc. 10/05/2010


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