the impactable patient – knowing when to intervene

The Impactable Patient – Knowing When to Intervene

Population Needs

System Resources

CCNC Care Management Evolution

Disease Management Care of Complex Patients

Focus on High Cost/High Risk Focus on Most Impactable

One Size Fits All Right sizing of intervention to maximize ROI

4

Technology-enabled Care Management

Plan-Do-Study-Act

= Potentially preventable hospital (inpatient+ED) costs for an individual

$0 $1K $2K $3K $4K $5K $6K $7K $8K $9K $10K $11K $12K $13K $14K $15K $16K $17K $18K $19K $20K

Total Enrolled Population

Traditional Predictive Models

Who Should We Target for Care Management Outreach?




CRG#1

CRG#2

CRG#3

Because their utilization is higher than others in the same cohort, these patients would likely benefit from Targeted Care Management. Under conventional flagging methodology, they would have been missed

Under conventional flagging methodology, all of these people might have been flagged; care management would likely have had minimal impact for most of them.

GREATEST OPPORTUNITY

Every patient in the population is assigned to a clinical risk cohort according to a hierarchical model using standard claims data—including inpatient, outpatient, physician, and pharmacy data history.

Each dot represents an individual’s healthcare spending pattern, focusing on potentially preventable hospitalizations or emergency room visits.

Priority Patients for Care Management Outreach/Assessment

Series1

-$400

-$350

-$300

-$250

-$200

-$150

-$100

-$50

$0

$50

$100

Intervention GroupControl Group

Ch

ang

e in

PM

PM

Co

sts Overall,

difference of $73 PMPM, or 5.7% reduction in total spending relative to control group

AboveExpectedStrata: $6K+ $5-6K $4-5K <$4K Overall

Reduction in Per Member Spending After Being Flagged for Priority Outreach, By “Above Expected” Strata

Priority Patient List

8

...data-driven identification of individuals who are most likely to benefit from care management outreach

Peer-reviewed research

Cutting Costs for Highest Risk Recipients

• Significant savings for 169,667 non-elderly, disabled Medicaid recipients

• $184 million savings over 5 years

• Higher per-person savings for patients with multiple chronic conditions.

Peer-reviewed research

Transitional Care

• 20% reduction in readmissions for patients with multiple chronic conditions

• Benefit persists far beyond the first 30 days

• For every six interventions, one hospital readmissionavoided – strong ROI

0 1 2 3 4 5 6 7 8 9 10 11 120

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Transitional Care (N=1,966) Usual Care (N=1,035)

Months since discharge from the hospital

Pro

port

ion

still

out

of

the

hosp

ital

Survival Function

Time to First Readmission for Patients Receiving Transitional Care Vs. Usual CareLighter shaded lines represent time from initial discharge to second and third readmissions(Significant Chronic Disease in Multiple Organ Systems, Levels 5 & 6; ACRG3 = 65-66)

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Transitional Care (N=1,747) Usual Care (N=2,451) Column2Column3 Column4 Column5

Months since discharge from the hospital

Pro

port

ion

still

out

of

the

hosp

ital

Survival Function

Time to First Readmission for Patients Receiving Transitional Care Versus Usual CareLighter shaded lines represent time from initial discharge to second and third readmissions

(History of Significant Acute Disease, all severity levels ; ACRG3 = 20-25)Example of an ACRG with a LOW risk of readmission that didn’t benefit from transitional care.

-20%

-10%

0%

10%

20%

30%

40%

50%

Which Patients Benefit the Most from Transitional Care?R

educ

tion

in R

eadm

issi

on R

isk

Whe

n M

anag

ed

*Size of bubble reflects the size of the patient population.

Low Risk

Medium Risk

High Risk

Hig

her

is b

ette

r

Which Patients Benefit the Most from Transitional Care Management?

Patient Education

Timely Follow-up with

Outpatient Providers

Medication Management

Face-to-Face Patient

Encounters

Components of Transitional Care

KIDNEY & URINARY TRACT INFECTIONS W/O MCC 1943 16.0 31.5

30-Day 90-DayDIALYSIS WITH DIABETES LEVEL - 4 2941 43.3 71.3CHRONIC RENAL FAILURE - DIABETES - OTH DOM CHRON DIS LEVEL - 6 4170 42.9 66.6CONGESTIVE HEART FAILURE - DIABETES - COPD LEVEL - 6 3934 35.9 64.5HIV DISEASE LEVEL - 4 2568 31.9 54.5TWO OTHER DOMINANT CHRONIC DISEASES LEVEL - 6 2651 28.8 51.6DIABETES - ADVANCED CAD - OTH DOM CHRON DIS LEVEL - 6 2625 28.2 50.6DIABETES AND OTH DOM CHRON DIS LEVEL - 6 2254 29.9 50.3SCHIZOPHRENIA AND OTH MOD CHRON DIS LEVEL - 6 3254 23.9 47.5CONGENITAL QUADRIPLEGIA, DIPLEGIA OR HEMIPLEGIA LEVEL - 4 2134 23.9 41.6COPD AND OTH DOM CHRON DIS LEVEL - 6 2052 21.1 40.0DIABETES AND OTH MOD CHRON DIS LEVEL - 6 2450 20.6 38.0SCHIZOPHRENIA AND OTH MOD CHRON DIS LEVEL - 5 2771 18.9 37.8HIV DISEASE LEVEL - 3 2678 19.5 37.5ONE OTH DOM CHRON DIS AND ONE OR MORE MOD CHRON DIS LEVEL - 6 2142 20.2 37.5ONE OTH DOM CHRON DIS AND ONE OR MORE MOD CHRON DIS LEVEL - 5 1893 13.5 25.8SCHIZOPHRENIA AND OTH MOD CHRON DIS LEVEL - 4 3207 12.2 21.4SCHIZOPHRENIA AND OTH MOD CHRON DIS LEVEL - 3 4665 9.0 17.3TWO OTHER MODERATE CHRONIC DISEASES LEVEL - 4 1894 7.1 14.1SCHIZOPHRENIA AND OTH MOD CHRON DIS LEVEL - 2 3321 7.1 11.9ASTHMA AND OTH MOD CHRON DIS LEVEL - 2 2241 4.1 8.4

Top 20 Largest CRG's NReadmission Rates

Even within the multiple chronic population, the readmission rates are vastly different across CRG’s; with highest risk CRG’s having a 4-6 times greater risk of readmission.

Baseline Readmission Rates by Clinical Risk Group

Who needs what?

16

Answer:It matters more for some than others!

Question: How important is that follow-up appointment after discharge?

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YES (N=3,690) NO (N=6,337)

Days since discharge from the hospital

Pro

port

ion

still

out

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hosp

ital

Survival Function

Time to Readmission for Patients Receiving Outpatient Follow-up Within 7 Days of Discharge(Patients with single dominant or moderate chronic condition; ACRG3 = 51-56)

All CCNC enrolled at discharge; inpatient discharges during the period 4/1/12-3/31/13, excluding deliveries, newborns, discharges to another facility and members dually enrolled at discharge.

We analyzed time to 30-day readmission for patients who did vs. did not have an outpatient follow-up visit (testing different time intervals to the follow-up appointment, for different clinical risk groups).

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YES (N=581) NO (N=1,304)

Days since discharge from the hospital

Pro

port

ion

still

out

of

the

hosp

ital

Survival Function

Time to Readmission for Patients Receiving Outpatient Follow-up Within 7 Days of Discharge(Patients with multiple chronic conditions and 40-50% expected risk of readmission)

All CCNC enrolled at discharge; inpatient discharges during the period 4/1/12-3/31/13, excluding deliveries, newborns, discharges to another facility and members dually enrolled at discharge.

And observed that as patients’ clinical risk increased, the more likely they were to benefit from earlier outpatient follow-up.

Opportunity Analysis for Patients Receiving 7-day Follow-up

RecommendedFollow-up Period

Did the patient receive follow-upwithin 7 days of discharge?

NO YES TotalRisk StrataGrouping 0 30 days 16,082 10,242 26,324

1 21 days 9,834 4,237 14,071

2 14 days 9,099 4,151 13,250

3 7 days 11,515 5,510 17,025

Total 46,530 24,140 70,670

For every patient getting a 7-day follow-up who doesn’t need it, there is a patient who would have benefitted from 7-day follow-up who did not get it.

Key Insight: Current Outpatient Visit Resources are Mis-matched

Putting it into Action

Other Flags to Inform Next Steps:

Palliative Care PriorityHigh risk of mortality and preventable end-of-life spend

Chronic Pain PriorityPattern of frequent narcotic fills and ED visits

Risk of Drug Therapy ProblemRisk of drug interaction, duplication, or adherence problems based on real-time medication data from multiple sources

Real-time notification of hospital admissions with care management priorities

21

Question: Are Home Visits worth the additional cost?

Answer: Yes! If targeted appropriately

What is the incremental savings benefit of a home visit, compared to less intensive TC management activities?

22

Incremental Savings Achieved From Home Visits by Clinical Risk Strata

-$1,000

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$7,000

[X VALUE]

[X VALUE][Y VALUE]

[X VALUE][Y VALUE] [X VALUE]

[Y VALUE]

[X VALUE][Y VALUE]

[X VALUE][Y VALUE]

[X VALUE][Y VALUE]

Diff

eren

ce in

Tot

al C

ost o

f Car

e D

urin

g 6

Mon

th P

erio

d Aft

er In

dex

Dis

char

ge

23*Percentages reflect the relative clinical risk for patients in that strata with Multiple Chronic Conditions (MCC), based upon their expected risk of a 90-day readmission. ‘Non-MCC’ reflects the number of non-delivery/newborn discharges incurred by all other CCNC enrolled patients without MCC.

For patients with >30% readmission risk, savings far exceed the cost of the home visit

Admission and Readmission Rate Trends

24

10.5%

10.2%

NC Medicaid Beneficiaries with Multiple Chronic Conditions, 2008-2012

What about Emergency Department utilization?

063%

121%

2-515%

6-101%

More than 100%

Distribution of Number of ED Visits During CY2012 Among Non-dual Medicaid

# of Prior ED Visits N

Post-Period ED Visits

(EXPECTED)

Post-Period ED Visits(ACTUAL)

Absolute Reduction in

ED Visits NNT

0 2682 1140 1597 457 N/A

1 1509 1704 1400 -304 5.0

2 667 1223 926 -297 2.2

3 275 698 513 -185 1.5

4 158 512 554 42 N/A

5+ 227 1449 1445 -4 N/A

TOTAL 5518 6725 6435 -291

Does a follow-up call after ED visit make a difference?

“Sweet Spot” for Light-Touch Intervention; as few as 1.5-5.0 patients need to be reached to avert one ED visit in the next 6 months

0 1 2 3 4 5 6 7 8 9 10 11 12$0

$5,000

$10,000

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$35,000

Number of ED Visits During the Year

Tota

l Med

icai

d Sp

end

Durin

g th

e Ye

ar What about high ED Utilizers?

27

$0

$5,000

$10,000

$15,000

$20,000

$25,000

$30,000

$35,000


Tota

l Med

icaid

Spe

nd D

urin

g th

e Ye

ar

5 6 7 8 9 10 or more

• ED Visit frequency correlates well with total cost of care

• The size of the bubbles represent the size of the population

ED Superutilizers are characterized by high prevalence of both physical and mental health conditions, and tend to use multiple locations of care

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0 7 14 21 28 35 42 49 56 63 70 77 84 91

Pro

port

ion

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urne

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ED

Days since previous ED Visit

Time to Next ED Visit (based on number of previous ED visits)

1 ED Visit

2 ED Visits

3 ED Visits

4 ED Visits

5 ED Visits

6 ED Visits

7 ED Visits

8 ED Visits

9 ED Visits

The likelihood of another ED visit increases with each successive ED visit

*Legend indicates the number of ED visits the person already had during the year (e.g., the line labeled ‘2 ED Visits’ shows the time from the 2nd until the 3rd ED visit). Note that 90% of patients who currently have 9 ED visits are likely to have a 10th ED visit within the next 3 months.

Time to next ED Visit (based on number of previous ED visits)

Total Medicaid costs, by # of ED visits during the year

1 2 3 4 5 6 7 8 9 10 or more

$0

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ED Costs All Other Costs


30

ED visit costs account for <10% of total spend, even among ED superutilizers

Does Care Management Make a Difference?

31

# ED Visits in Prior Year Group N PMPM (PRE)PMPM (POST)

Mean Difference (PMPM)

None Control 2,979 $777 $805 $28

None Intervention 3,494 $1,047 $900 -$147

None† Savings -$176**

1-3 ED Visits Control 7,838 $807 $816 $9

1-3 ED Visits Intervention 10,991 $1,165 $1,048 -$117

1-3 ED Visits Savings -$126**

4-6 ED Visits Control 2,420 $1,197 $1,153 -$44


4-6 ED Visits Savings -$96*

7-9 ED Visits Control 827 $1,585 $1,490 -$95


7-9 ED Visits Savings -$171

10-19 ED Visits Control 631 $1,963 $1,853 -$109


10-19 ED Visits Savings -$541**

20 or more ED Visits Control 144 $3,340 $3,010 -$329

20 or more ED Visits Intervention 591 $3,894 $2,984 -$911

20 or more ED Visits Savings -$581**

*Simple t-tests, statistically significant at the .05 level,**simple t-tests, statistically significant at the .001 level†All patients also met priority patient criteria based on above-expected hospital spending

Key Insights: ED Super-utilizers

• Care Management makes a difference for ED super-utilizerso In multivariate regression analysis for patients with 10+ ED

Visits, after adjusting for covariates (age, gender, county, comorbidities, mental illness) and baseline differences in cost and utilization, savings estimate over subsequent 6 months was $302 per member per month (p<0.05)

• High ED Utilization can be thought of as a marker of *impactability* for total cost of care

32

Where are we going from here?

Impactability Scores as opposed to Risk Scores

Risk Scores predict the likelihood of a given event. They are designed to predict events/outcomes as part of usual care (i.e., if we didn’t intervene, what might be expected to happen). The dependent variable in the predictive models are typically events (e.g., hospital utilization) or costs.

Impactability Scores are designed to identify members who will benefit the most from a given intervention. The dependent variable in the predictive models are typically whether patients with similar characteristics and circumstances have been determined to be responsive to intervention, based on rigorous, controlled real-world evaluations.


Lightweight, flexible apps; “small data”

Care Triage was collaboratively developed by CCNC and GlaxoSmithKline


Prescriptive Analytics

Care Triage was collaboratively developed by CCNC and GlaxoSmithKline

Contact for more information: Annette DuBard, MD, MPHSVP for Informatics and [email protected]

Acknowledgements

Carlos Jackson, PhD, CCNC Director of Program Evaluation

Jennifer Cockerham, RN; Tom Wroth, MD; Troy Trygstad PharmD

800+ nurse care managers, clinical pharmacists, and other care team members out there doing the good work!

36

CCLCF by the Numbers

• 90,000 Medicaid patients

• 6 counties, largely rural, 4,479 square miles, or 9.2% of the state

• 2nd highest disease burden of all 14 networks

• Bladen and Columbus ranked 91 and 100 in North Carolina 2014 County Health Rankings

• Approximately 12,000 hospitalizations and 61,000 ED visits per year

• Only 80 staff members, have to be strategic

Using Data to Make Strategic Interventions

Population

Needs

System Resourc

es

Population

Needs

System Resourc

es

LargePopulation

Limited Resources

How to Touch Them

TC Package for TC Priority Admits

Target Interventions to match ROI

Efficient use of scarce resources

Face to Face for High Risk/Telephonic for low

QI Efforts to change Practice

Patterns

Deploying Resources Strategically

Use data to target care management interventions to those we can impact

Stratify level of intervention to complexity of patient

Additional flags help us tailor our interventions/utilize appropriate staff

Transitional Care (TC) Priority for patients at great risk of readmissions

CCNC Priority for those with future admission risk at top 1%

Chronic Pain Indicator for patients on high numbers of pain medications

Palliative Care Indicator for patients with 12 month mortality rate of 5% or greater

Care Alerts for elevated lab values, medication adherence issues, etc.

Foster Care Indicator for foster children with chronic conditions

LME Indicator for patients who have utilized psychiatric intervention in past 6 months, refer those with no chronic medical condition to LME, co-manage patients with both

Key Disease Indicators like heart failure, asthma, diabetes

Marrying of Data and Hands-On Care Management

Patient Story: Sally

Sally was admitted to hospital with TC Priority (high risk of readmission) and Palliative Care Indicator

TC service package would normally call for: CCNC bedside visit in hospital,

home visit within 3 days of discharge to assess condition,

reconcile medications,

reinforce treatment plan,

set up follow up appointments and supportive services,

communication with providers, etc. all to prevent future admissions

Palliative care indicator calls for closer look at goals

Sally: Connecting the Dots

Sally: 51 years old with metastatic lung cancer with a series of admissions following a lung resection due to incision that did not heal

Had home health services, but was living at home alone with 4 year old daughter

Traveling 2.5 hours one way in a cab weekly for chemotherapy. Unable to eat, drink, or get out of bed for several days after each treatment, disoriented, in great pain

No health care power of attorney, no living will, no idea what treatment was intended to do or what her outcome would be

Multiple agencies involved with Sally, communication not optimal Home health unaware of what was happening at treatment center

DSS pursuing Adult and Child Protective Service reports on both patient and child

Sally: Continued

CCNC RN care manager and Palliative Care Coordinator orchestrated a plan:

Engaged Oncology doctor and had him speak to Sally about her prognosis and treatment

Helped Sally to name close friend as power of attorney and make a living will

DSS agreed to close CPS case when Sally agreed to place daughter with grandparents

Home Health agreed to visit 2x weekly and provide aid; friend agreed to visit daily

As cancer progressed to bones, Sally became disoriented/needed supervised placement, staff helped her agree to assisted living and palliative care for pain and symptom management

Sally was able to discontinue some medications and become more alert. She made a goal to live for daughter’s 5th birthday a month away.

After her daughter’s birthday, Sally agreed to move to inpatient hospice center where her daughter could spend the night.

Sally sent a video message of gratitude from the center to our palliative care coordinator and died peacefully two days later.

A peaceful death, surrounded by family, that might otherwise have been alone, in a hospital bed, with a child in CPS custody while Sally pursued aggressive, costly treatment of little utility

Patient Story: Martin

Martin, 24 years old with intracerebral hemorrhage (stable), history of seizures and stroke (age 5), hypertension, and Sickle Cell

Picked up by care manager at age 22 from a list of patients with the Chronic Pain Indicator. (Martin filled narcotics from 3 different prescribers in a 2-month period and was using the hospital for uncontrolled pain)

When the nurse care manager called, Martin was frustrated and in pain crisis:

PCP not willing to prescribe, believed hematology clinic responsible for pain medications

Martin had not been to a PCP to establish care.

Specialist had mailed a Rx, but not there yet

Martin: Continued

Care manager advocated between providers for immediate help, pain meds provided, stopped Martin from going to ED

Began 2-year care management relationship that is working Got patient linked with local PCP and developed pain management plan

that incorporated PCP and specialty clinic (PCP now making home visits!)

Got Services for Blind to support eye exam and glasses due to vision impairment from stroke

Got approval for CAP-DA services so that Mom can continue working full time

Working now on increasing independence for Martin beyond Mom’s house. Coordinating with local MCO to get intellectual/DD programs and services that family didn’t realize he qualified for

Linking him with providers to do evaluations and behavioral health assessments needed to get him enrolled in Adult Day Activity or Supported Employment

Conclusions

Data drive prioritization and level of intervention to ensure efficient and effective use of limited resources

But having local staff as part of the care team in the practice and the hospital, and especially visiting patients in their homes, is priceless

CCNC Care Managers build relationships with patients, coordinate care across community agencies of all kinds, find out facts from home visits that providers cannot know, and connect the dots of patient care with primary care providers, specialists, and hospitals to ensure patients have the best outcomes possible

Questions?

Thank you!

the impactable patient – knowing when to intervene

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