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TRANSCRIPT
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• [email protected] 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)