Potentially Preventable Readmissions (PPRs) in the Texas Medicaid Population, Fiscal Year 2009

Hospital SeminarsJanuary 2011

Agenda

1. Overview 2. 3M All Patient Refined Diagnostic Related Groups

(APR-DRGs) and PPRs3. Study data – sources and preparation 4. Study methods – casemix adjustment5. Statewide results6. Hospital reports

For Further Information• www.hhsc.state.tx.us for the public PPR report• PPR.report@tmhp.com for questions

OVERVIEW

Presenters• John Chapman, PhD

– Senior Consultant, Payment Method Development, ACS Government Healthcare Solutions

• Lisa Lyons, RN– Product Marketing Manager, 3M HIS

• Kevin Quinn, MA, EMT-P– Vice President, Payment Method Development, ACS Government

Healthcare SolutionsThe study was performed by Affiliated Computer Services, Inc.

(ACS), a Xerox Company, which is the parent company of Texas Medicaid and Healthcare Partnership (TMHP). 3M provided valuable technical assistance but is not responsible for how the PPR methodology was applied or for the results.

OVERVIEW

Learning Objectives

• Understand what a PPR is and how it is identified• Understand what data was used for the reports, both

in general and for one’s own hospital• Understand how to compute and assess PPR rates• Have familiarity with general PPR patterns• Be able to assess and explain your hospital’s PPR

rate, and explore reduction strategies.

OVERVIEW

Please Bear in Mind• Statements and opinions are those of the presenters and not

necessarily those of the Health and Human Services Commission (HHSC).

• This is the first year this analysis has been performed. Suggestions to improve data, methodology, and presentation are welcome.

• TMHP and ACS have no financial interest in any DRG algorithm or method of measuring readmissions.

• Results in this analysis were produced using data obtained through the use of proprietary computer software created, owned, and licensed by the 3M Company. All copyrights in and to the 3MTM Software are owned by 3M. All rights reserved.

OVERVIEW

Concern over Readmissions• 20 percent of Medicare inpatients were

readmitted within 30 days, almost all unplanned

• Half of medical patients did not see a physician in the interval before readmission

-- Jencks et al.

Reducing readmissions at Park Nicolet: “We’ve kept it up out of a sense of moral obligation to these patients, but we’re getting killed,” said David K. Wessner, chief executive of Park Nicollet. “We will totally run out of gas.”

-- NY Times

“The Congress should direct the Secretary to reduce payments to hospitals with relatively high readmission rates for select conditions… “

-- MedPAC

Over 150,000 people a year in Florida—11 percent of the all-payer population studied—were readmitted for potentially preventable reasons.

-- Goldfield et al.

OVERVIEW

Texas’ Readmissions Statute (Gov. Code, Sec. 531.913)

• Enacted in 2009• Requires HHSC to measure and report on potentially preventable readmissions

(PPRs) of Medicaid patients.– Defined as the return hospitalization due to deficiencies in care or treatment

during the initial hospital stay or in post-hospital discharge follow-up. – Does not include readmission from unrelated events. – But does include readmission for:

• Same condition or procedure.• Infection or other complication resulting from care previously provided.• Condition or procedure indicating that the previous admission’s surgical

intervention was unsuccessful in achieving the anticipated outcome.• Another condition or procedure of a similar nature

• HHSC must create a program to identify PPRs and exchange PPR performance information with each hospital.

• Each hospital must distribute this information to its health care providers.

• Focus on individual stays or overall rates– Traditional approach is on “medical errors” in individual stays– Alternative approach is focusing on hospital-wide rates– Emphasis on potentially preventable events

• Punishing bad performance vs. enabling excellence• “Name/blame/shame” vs transparency/collaboration

– “Good people working in bad systems”– “Medical errors” vs. continuous quality improvement

• How to help hospitals improve themselves?– Give hospitals information they can use

OVERVIEW

Questions of Tone and Approach

OVERVIEW

76-Year-Old Man with Heart Failure Admitted…

• The patient– Active 76-year-old male, retired investment broker– History of seven chronic conditions– Takes nine meds daily; coping with dietary restrictions – Lives with wife of 50 years; she shows cognitive changes– Three children with families living in other states

• The care– Under the care of six specialists– Primary care provider retired– Admitted and treated for exacerbation of heart failure

Based on a case study presented by Randall Krakauer, M.D., in a 12/2/09 presentation “Aligning Reimbursement to Reduce Avoidable Hospital Readmissions,” sponsored by the Healthcare Intelligence Network.

OVERVIEW

… and Readmitted

• The handoff– Three new medications ordered– Oral and handwritten discharge instructions– Told to schedule follow-up MD appointment within seven

days

• The outcome– Can’t read discharge instructions – Has questions about meds but doesn’t know who to call– Weak, dizzy, unable to eat– First available MD appointment more than two weeks away– Two weeks later, rehospitalized for acute heart failure– “Due to lack of adherence to prescribed therapies”

OVERVIEW

Which Solution Makes the Most Sense?

Good Instructions, MD Visit Scheduled, Home

Visit by RN

Price tag: < $500

Readmission with Implantation of Left

Ventricular Heart Assist

Price tag: $88,000

OVERVIEW

Steps in Our Analysis1. Create analytical dataset based on claims extract and

encounter files

Includes extensive data validation

2. Group by APR-DRG

Base DRG plus level of severity (e.g., DRG 123-4)

314 base DRGs x 4 = 1,256 total DRGs

3. Calculate PPRs using 3M PPR software

Analyze admits in 11 months with PPRs in 12 months

4. Calculate risk-adjusted PPR rates by hospital

Adjust for base DRG, severity, age, psych comorbidity

OVERVIEW

PPR Results for Fiscal Year 2009

Medicaid Care Category

Initial Admits

Readmit Chains

Same Hospital

Other Hospital All PPR Rate

PediatricRespiratory 27,239 649 552 170 722 2.4%Other medical 41,311 1,223 1,073 389 1,462 3.1%Other surgical 10,935 470 442 89 531 4.5%MH/SA 14,307 1,181 871 593 1,464 9.2%Subtotal 93,792 3,523 2,938 1,241 4,179 3.9%

AdultCirculatory 13,809 1,025 835 409 1,244 8.2%Other medical 49,808 3,618 2,914 1,517 4,431 8.0%Other surgical 17,650 1,005 914 243 1,157 6.1%MH/SA 14,126 1,445 1,112 978 2,090 12.0%Subtotal 95,393 7,093 5,775 3,147 8,922 8.2%

Obstetrics 155,038 1,180 1,001 216 1,217 0.8%Total 344,223 11,796 9,714 4,604 14,318 3.6%

Total Readmissions

MH/SA: Mental health and substance abuse

STUDY DATA

Data Sources

• Fee-for-Service (FFS) and Primary Care Case Management (PCCM)– Based on standard claims extract– Well-established and familiar to hospitals– Augmented to include up to ten diagnoses and up to six procedures

• Managed care encounter data– Claims adjudicated by the managed care plan and submitted to HHSC– Required greater review and validation efforts:

• Combining multiple records for a stay• Removing duplicate records• Removing records with critical data issues

STUDY DATA

Key Data Quality Questions for PPR

• Is there one, and only one, record in the dataset for each hospital stay in the real world?

• Are providers and recipients accurately and consistently identified?

• Are the diagnosis, procedure, and discharge status code fields accurate, complete, and consistent?

STUDY DATA

Main Data Validation Edits

• Consolidation of multiple records for a single stay (claim chaining)

• Removed duplicates• Removed invalid/unreliable discharge status• Removed undocumented aliens, because not all stays

are covered and so PPR assignment would be inappropriate.

STUDY DATA

Identifying Patients and Hospitals

• Patients consistently identified by recipient number– No names, Social Security numbers, or birth dates, even in

confidential data to hospitals

• Hospitals identified by Texas Provider Identifier (TPI)– FFS/PCCM claims show the Medicaid TPI– Encounter claims show National Provider Identifier (NPI)– NPI cross-walked to TPI using NPI, bill type, address,

taxonomy, etc.– TPIs reviewed for duplicates, anomalies

STUDY DATA

Completeness of Dx and Px Coding• Children’s and

psychiatric hospitals not paid by DRG may code less completely

• We compared the number of diagnoses and procedures reported for each stay, controlling for the mix of DRGs

Chart A.2.4.3.1Measure of Diagnosis and Procedure Coding Completeness

1.080.96

0.77

1.13

-

0.25

0.50

0.75

1.00

1.25

Children'sHospitals

DRG Hospitals Psych SpecialtyHospitals

DRG Hospitals

See text for explanation of comparison

• Children’s hospitals showed no obvious evidence of ‘under’ coding, while psychiatric hospitals did

STUDY DATA

APR-DRG and PPR Assignment

• APR-DRG and PPR status assigned to each stay• 0.6 percent of stays had APR-DRG or PPR grouping

errors and were omitted from the final dataset• Major methodological exclusions from dataset

– Newborns, multiple trauma, metastatic cancer, left against medical advice, etc.

– Initial admissions in August 2009• Every remaining stay was either an “initial

admission” or a PPR• Initial admissions may or may not be the initial claim

in a PPR chain

STUDY DATA

Data Review and Preparation Results

Adjustment FFS/PCCM Encounter Total

Records received 484,995 245,418 730,413

Removed to assure each record represents a unique, IP stay: 50 21,822 21,872

Removed due to data issues: 1,633 19,688 21,321

Removed for study design reasons: 264,899 78,098 342,997

Final Analytic Dataset 218,413 125,810 344,223

Note: Further detail is in Appendix Table A.2.1 of the report.

STUDY METHODS

Introduction to Casemix for PPRs

Four characteristics strongly influence the likelihood that a stay will have a PPR– Base APR-DRG – Severity of illness– Age– Serious mental health or substance abuse co-morbidity

STUDY METHODS

Variation by DRG

Base DRG PPR RateCesarean delivery 1.4%

Bronchiolitis and RSV pneumonia 2.6%

Appendectomy 4.1%

Diabetes 7.4%

Heart Failure 10.2%

Schizophrenia 14.7%

STUDY METHODS

Variation by Severity

Severity Level

Base DRG 1 2 3 4Cesarean delivery 1.1% 2.0 % 3.0 % 3.1 %

Bronchiolitis and RSV pneumonia

2.1% 2.8 % 5.3 % 12.7 %

Heart Failure 8.1 % 9.9 % 11.4 % 8.8 %

Schizophrenia 15.3% 13.8% 17.3% N/A

STUDY METHODS

Variation by Age

Pediatric PPR Rates in Relation to Adult Rates

0%20%40%60%80%

100%120%

750-2 S

chizophren

ia753

-1 Bipolar

Dis753

-2 Bipolar

Dis

751-2 M

aj Depres

sion

383-2 C

ellulitis

139-2 O

th Pneumonia463

-2 Kidney/

UTI420

-2 Diab

etes

751-1 M

aj Depres

sion

139-3 O

th Pneumonia

APR-DRGs shown are the ten most common adult DRGs that also had at least 100 pediatric initial admissions

% o

f Adu

lt Ra

te

AdultPediatric

STUDY METHODS

Variation by MH/SA Co-morbidity

Age Category MH/SA Co-morbidity Adj. Factor Pediatric No 0.993

Yes 1.337Adult No 0.978

Yes 1.127

Note: Excludes obstetrics and MH/SA stays, for which the MH/SA co-morbidity is not a significant factor.

STUDY METHODS

PPR Rates by Medicaid Care Category

MCCS are intended to be typical of internal hospital organization and Medicaid policy areas

MCCs reflect three of the four sources of variation in the likelihood of a PPR.

MCC Pediatric Adult

Respiratory / Circulatory 2.4% 8.2 %

Other Medical 3.1 % 8.0 %

Other Surgical 4.5 % 6.1 %

MH / SA 9.2 % 12.0 %

Obstetrics 0.8 %

STUDY METHODS

But PPR Rates Also Vary Within MCCs

Other Medical DRGs Pediatric Adult

383-1 Cellulitis & Oth Bact Skin Inf 0.7 2.8

249-2 Non-Bact Gastroenteritis, N&V 2.2 6.2

720-3 Septicemia & Disseminated Inf 6.0 9.6

STUDY METHODS

Norms

For this report, norms were established:

• For each combination of :– Base DRG– Severity level– Age category

• Using average Texas Medicaid statewide rates• Norms do not necessarily reflect best practices

STUDY METHODS

Comparing TX Medicaid with FL All-Payer

Chart 2.1.1Comparison of Results: Texas Medicaid vs. Florida All-Payer

0%

2%

4%

6%

8%

10%

12%

14%

Ped Resp Ped OthMedical

Ped OthSurgical

Ped MH/SA Adult Circ Adult OthMedical

Adult OthSurgical

AdultMH/SA

Obstetrics Total

Florida results have been made comparable to Texas results through adjustment for frequency by APR-DRG and adult/pediatric age split,

TX Medicaid FL All-Payer

STUDY METHODS

Expected Values

The expected value, or PPR likelihood, for each stay is:• The norm for that stay

– Multiplied by• The applicable MH co-morbidity factor.

The expected PPR rate for a group of stays – such as all the stays of a hospital – is the sum of the expected values of the stays in the group.

STUDY METHODS

Expected PPR Rates: IllustrationDRG Age MH Comb. MH

Adj.Norm Indiv.

Prob. of PPR

A 14 No .9 10% 9%

B 32 Yes 1.5 20% 30%

C 54 No .95 22% 21%

Sum 60%

Group Expected Rate (average of individual probabilities)

20%

Note: Numbers are hypothetical, for illustration

STUDY METHODS

Expected PPR Rates: ExampleDRG Age MH Comb. MH

Adj.Norm Indiv.

Prob. of PPR

249-2 14 No .99 6.0% 5.9 %

249-2 32 Yes 1.127 10.8% 12.7 %

194-3 54 No 0.98 11.4 % 11.2 %

Group Expected Rate (average of individual probabilities)

9.9%

STUDY METHODS

Actual-to-Expected (A/E) Ratio

• There is need to assess PPR rates for various mixes of DRGs, severity, etc.– Each hospital has its own mix– Within a hospital, each MCC has a distinct mix

• To measure how each observed PPR rate compared to its norm we computed actual-to-expected ratios.

• An expected rate is computed for each hospital.• The ratio of the hospital’s actual rate to this expected rate is a

standard measure of performance.• This method is called indirect adjustment.

STUDY METHODS

Actual-to-Expected Ratio: ExampleDRG Age

GroupMH

Comb.Number of

StaysIndiv.

Prob. of PPR

Actual # of PPRs

Exp. # of PPRs

249-2 Pediatric No 100 5.9 % 5 5.9

249-2 32 Yes 100 12.7 % 12 12.7

194-3 54 No 100 11.2 % 10 11.2

Total 27 29.8

Actual-to-Expected Ratio 29.8 / 27 = 0.91

STUDY METHODS

Interpreting A/E Ratios

At one level it is what it is – this study is using all applicable stays, so is not subject to sampling variation.

BUT….It’s not only tempting, but useful, to generalize.

This can be done, but with caution and only when volumes are large enough.

STUDY METHODS

PPR Rates with Few Stays• Imagine a hospital with a true PPR rate of 5 percent

for all its stays.• It has 40 admissions a year.• The expected number of PPRs each year is two.• But it’s not unlikely that it will have one or three in

any given year.• If it has one, its A/E ratio is 0.5• If it has three, its A/E ratio is 1.5

STUDY METHODS

Protection Against Over-interpretation: Step 1

• Minimum volume threshold– At least 40 stays, and– At least five actual PPRs, and– At least five expected PPRs

• If the volume threshold is not met, we provide the actual and expected values, but not the A/E ratio.

• While it’s important not to over-interpret a single high or low A/E ratio, it’s still important to become aware of what PPRs are occurring.

STUDY METHODS

Protection Against Over-interpretation: Step 2

• Test of how likely it is that the observed A/E ratio differs from 1.00 simply by random chance

• Depends on how different the observed A/E ratio is from 1.00 and on the volume of stays

• Cochran-Mantel-Haenszel (CMH) statistic• A/E ratio in hospital-specific reports is flagged

– * if the p-value < 0.10– ** if the p-value < 0.05

STATEWIDE RESULTS

Overview of Results

Medicaid Care Category

Initial Admits

Readmit Chains

Same Hospital

Other Hospital All PPR Rate

PediatricRespiratory 27,239 649 552 170 722 2.4%Other medical 41,311 1,223 1,073 389 1,462 3.1%Other surgical 10,935 470 442 89 531 4.5%MH/SA 14,307 1,181 871 593 1,464 9.2%Subtotal 93,792 3,523 2,938 1,241 4,179 3.9%

AdultCirculatory 13,809 1,025 835 409 1,244 8.2%Other medical 49,808 3,618 2,914 1,517 4,431 8.0%Other surgical 17,650 1,005 914 243 1,157 6.1%MH/SA 14,126 1,445 1,112 978 2,090 12.0%Subtotal 95,393 7,093 5,775 3,147 8,922 8.2%

Obstetrics 155,038 1,180 1,001 216 1,217 0.8%Total 344,223 11,796 9,714 4,604 14,318 3.6%

Total Readmissions

STATEWIDE RESULTS

Most PPRs

Table 2.4.1 PPR Rates by APR-DRG: Top 20 APR-DRGs in Terms of Total Readmissions

Base DRG Initial

Admits Readmit Chains

Readmit Stays

Stays per Chain PPR Rate

753 Bipolar Disorders 11,283 1,176 1,530 1.3 10.42%

750 Schizophrenia 5,082 745 1,129 1.5 14.66%

751 Major Depression 4,998 475 615 1.3 9.50%

540 Cesarean Delivery 41,035 565 577 1.0 1.38%

560 Vaginal Delivery 91,865 543 560 1.0 0.59%

194 Heart Failure 2,861 291 369 1.3 10.17%

140 COPD 3,188 301 355 1.2 9.44%

139 Other Pneumonia 9,990 296 339 1.1 2.96%

420 Diabetes 2,535 187 266 1.4 7.38%

138 Bronchiolitis & RSV Pneumonia 9,270 236 252 1.1 2.55%

662 Sickle Cell Anemia Crisis 1,611 177 252 1.4 10.99%

720 Septicemia & Disseminated Infections 2,335 192 226 1.2 8.22%

053 Seizure 3,808 167 209 1.3 4.39%

249 Non-Bacterial Gastroenteritis 5,673 162 195 1.2 2.86%

279 Hepatic Coma & Oth Major Liver Disorders 737 139 190 1.4 18.86%

280 Alcoholic Liver Disease 765 147 188 1.3 19.22%

383 Cellulitis & Other Bacterial Skin Infections 6,492 168 178 1.1 2.59%

460 Renal Failure 1,431 137 167 1.2 9.57%

463 Kidney & Urinary Tract Infections 4,572 140 163 1.2 3.06%

282 Disorders of Pancreas except Malignancy 1,338 118 155 1.3 8.82%

Note: The APR-DRG shown is the DRG for the initial admission.

STATEWIDE RESULTS

Statewide Results: By Delivery MethodTable 2.2.1

PPR Results by Health Care Delivery Method

Fee-for-Service Primary Care Case Management Managed Care Organization

Medicaid Care Category

Initial Admits

Actual PPR Rate

Expctd PPR Rate

Actual / Expctd Ratio

Initial Admits

Actual PPR Rate

Expctd PPR Rate

Actual / Expctd Ratio

Initial Admits

Actual PPR Rate

Expctd PPR Rate

Actual / Expctd Ratio

Pediatric

Respiratory 7,442 3.0% 2.9% 1.05 10,259 2.2% 2.2% 0.98 8,816 2.3% 2.3% 0.98

Other medical 11,937 4.0% 3.7% 1.07 13,942 2.6% 2.7% 0.96 13,970 2.8% 2.9% 0.97

Other surgical 4,532 5.6% 4.9% 1.12 2,992 4.2% 4.4% 0.97 2,880 3.2% 4.1% 0.78

MH/SA 4,766 9.2% 9.3% 0.99 3,390 7.0% 8.7% 0.80 4,687 10.8% 9.4% 1.14

Subtotal 28,677 4.8% 4.6% 1.05 30,583 3.1% 3.4% 0.92 30,353 3.9% 3.9% 1.02

Adult

Circulatory 5,372 8.1% 8.3% 0.98 7,011 8.3% 8.1% 1.02 182 6.0% 7.1% 0.85

Other medical 20,900 8.4% 8.0% 1.04 22,360 7.9% 8.1% 0.98 2,117 4.4% 5.6% 0.78

Other surgical 8,669 6.2% 6.2% 1.00 6,873 6.4% 6.2% 1.03 951 2.9% 4.5% 0.65

MH/SA 3,602 10.8% 11.4% 0.94 2,836 9.1% 11.5% 0.79 5,598 14.3% 12.6% 1.13

Subtotal 38,543 8.1% 8.0% 1.01 39,080 7.8% 8.0% 0.97 8,848 10.5% 10.0% 1.06

Obstetrics 17,408 0.6% 0.8% 0.82 53,472 0.7% 0.8% 0.87 82,941 0.8% 0.8% 1.13

Total 84,628 5.4% 5.4% 1.02 123,135 3.5% 3.7% 0.95 122,142 2.3% 2.2% 1.06

Note: Actual/expected ratios were calculated using more decimal places in the actual and expected PPR rates than are shown here.

STATEWIDE RESULTS

Statewide Results: Reasons for Readmission

Reason ShareMedical readmissions for the same condition as the initial admission 23%

Medical readmissions for a different acute condition that could plausibly have had a clinical association with the initial admission

29%

Mental health or substance abuse readmissions that followed an initial admission for mental health or substance abuse

24%

Post-surgical complications– Only 11% of readmissions following surgery are in this category

2%

Other reasons 22%

STATEWIDE RESULTS

Statewide Results: Variation among hospitals

Table 2.6.1 Number of Hospitals by PPR Performance

Ratio of Actual PPRs to

Expected PPRs Interpretation Hospitals Stat Sig

Diff Lower than 0.75 Much lower than expected 23 11

0.75 to 0.89 Lower than expected 45 8

0.90-1.10 About as expected 83 0

1.11 to 1.25 Higher than expected 45 9

Higher than 1.25 Much higher than expected 34 23

Total 230 51

Notes 1. Low-volume hospitals are excluded. Low-volume hospitals do not meet the criteria of having at least 40 initial admissions, at least five expected readmissions, and at least five actual readmissions. 2. “Stat Sig Diff” shows the number of hospitals where the difference from 1.00 is statistically significant at the 90% confidence level.

STATEWIDE RESULTS

Statewide Results: Variation among hospitals

Chart 2.6.1PPR Actual-to-Expected Ratios by Hospital Rank

-

0.50

1.00

1.50

2.00

2.50

0 50 100 150 200 250Hospitals Ranked by Actual/Expected PPR Ratio (From Low to High)

Actu

al-to

-Exp

ecte

d Ra

tio

Each dot is a hospital. A hospital with an actual/expected ratio below 1.00 had fewer PPRs than

expected; a hospital with an actual/expected ratio above 1.00 had more PPRs than expected.

STATEWIDE RESULTS

PPRs by Days Since Discharge

Chart 2.7.1Patterns in PPR Initiation by Days Since Discharge

0

200

400

600

800

1000

1200

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Days Since Discharge

Num

ber o

f PPR

Cha

ins

Initi

ated

(Bro

ken

Blue

Lin

e)

-

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,000

Cum

ulat

ive

PPR

Chai

ns In

itiat

ed(S

olid

Red

Lin

e)

HOSPITAL REPORTS

Hospital-Specific Data Reports

• Provided confidentially to each hospital• Each hospital to share with its providers• Information:

– Hospital-specific version of PPR report– Excel® file includes Excel version of tables in PPR report

plus individual claim data