RELIABILITY OF 30-DAY READMISSION MEASURES IN THE HOSPITAL - - PowerPoint PPT Presentation

RELIABILITY OF 30-DAY READMISSION MEASURES IN THE HOSPITAL READMISSION REDUCTION PROGRAM

Michael P . Thompson PhD, Health Services and Policy Research Group Department of Preventive Medicine, University of Tennessee Health Science Center

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ACKNOWLEDGEMENTS

 Co-Authors:

 UTHSC – Teresa M. Waters, PhD; Cameron M. Kaplan, PhD  VCU – Gloria J. Bazzoli, PhD;

Yu Cao, MS  Supported by: R01HS023783 (AHRQ; TM Waters, PI)

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HOSPITAL READMISSIONS

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$24 billion in hospital costs in 2011 1 in 5 beneficiaries are readmitted within 30-days

RISK-STANDARDIZED READMISSION RATES

 RSRRs for AMI, Heart Failure, and

Pneumonia

 Hierarchical Regression Model (HLM)

𝑍

𝑗𝑘 = 𝑐0𝑘 + 𝐶𝑌 + 𝑓𝑗𝑘

𝑐0𝑘 ~ 𝑂(𝜈, 𝝊𝟑)

 After risk-adjustment (𝐶𝑌), there are

systematic differences in outcomes (𝝊𝟑)

 Underlying differences in quality

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MEASURE RELIABILITY

 To what extent is the observed variation in RSRRs due to systematic differences

between hospitals, rather than statistical noise?

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𝑺𝒇𝒎𝒋𝒃𝒄𝒋𝒎𝒋𝒖𝒛 = 𝑻𝒋𝒉𝒐𝒃𝒎 𝑻𝒋𝒉𝒐𝒃𝒎 + 𝑶𝒑𝒋𝒕𝒇

 Signal = Between-hospital variation in RSRR



HLM random intercept variance

𝑍

𝑗𝑘 = 𝑐0𝑗 + 𝐶𝑌 + 𝑓𝑗𝑘

𝑐0𝑗 ~ 𝑂(𝜈, 𝝊𝟑)

 Noise = Within-hospital variation in RSRR



p = hospital event rate, n = hospital case volume

𝑂𝑝𝑗𝑡𝑓 = 𝑞(1 − 𝑞) 𝑜

ILLUSTRATING RELIABILITY

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12 16 20 24 28 32 36 1 2 3 4 5 RSRR (%) 12 16 20 24 28 32 36 1 2 3 4 5 RSRR (%)

High Reliability Low Reliability

Between Between Within Within

MEASURE RELIABILITY

 Study Questions:

1.

What is the reliability of 30-day RSRRs initially targeted by the HRRP?

2.

How many hospitals meet a predetermined benchmark for reliability?  Reliably identifying low performing hospitals is

critical for policy success of the HRRP

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DATA SOURCES AND SAMPLE

 Data Sources

 HCUP SID Data (2009-2011)

 AR, CA, FL, IA, NY, and WA

 AHA Annual Survey  Area Health Resource Files

(AHRF)

 CMS criteria

 ICD-9 Codes  Inclusion/Exclusion criteria Table 1. Condition-specific cohort sample size and RSRRs

AMI Heart Failure Pneumonia Hospitals, N 603 860 896 Patients, n 156,177 367,188 282,041 Number of Readmissions 31,658 86,759 57,796 RSRRs (%), Median (Range) 20.3 (14.1-28.4) 23.2 (14.8-45.6) 19.7 (11.6-55.2)

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STATISTICAL ANALYSIS

1.

HLM model for readmissions, adjusted for patient characteristics, to estimate hospital-specific reliability  signal / (signal + noise)

 Median reliability (interquartile range)  Also, adjusted for hospital and community-level socioeconomic factors

2.

Compare reliability estimates to commonly used benchmark (R=0.7), and estimate:

 Three-year case-volume threshold where R=0.70  Percent of hospitals with reliability ≥0.70

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Table 2. Median reliability of 30-day readmission measures for AMI, Heart Failure, and Pneumonia cumulatively adjusted for patient, hospital, and community-level factors. Condition Hospitals, N Median Reliability (IQR) Patient * + Hospital † + Community-Level‡ AMI 603 0.54 (0.41-0.63) 0.52 (0.39-0.61) 0.50 (0.38-0.60) Heart Failure 860 0.71 (0.61-0.78) 0.66 (0.56-0.74) 0.65 (0.54-0.73) Pneumonia 896 0.82 (0.76-0.86) 0.80 (0.72-0.83) 0.79 (0.72-0.83)

* Adjusted for age, gender, race, dual eligible status, median income category, number of Elixhauser comorbidities, length of stay, discharge disposition, index admission through ED, planned admission, weekend admission, and major OR procedure

† Adjusted for hospital teaching status, bed size, safety-net hospital, hospital system member, for-profit status, rural hospital,

and hospital Medicare proportion

‡ Adjusted for HPSA-primary care shortage area, % county below FPL, and % county uninsured 10

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0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 250 500 750 1000 1250 1500 1750 2000

Reliability (R) Hospital Volume (n) AMI HF PN

• Figure. Relationship between hospital volume and reliability of 30-day RSRRs for AMI (N=603), Heart Failure (N=860),

and Pneumonia (N=896) (note: observations of volume>2000 not shown).

Table 3. Volume required to achieve moderate reliability (R=0.70) and percent of hospitals exceeding that threshold

Condition Volume Threshold R≥0.7, % AMI 674 11.4 Heart Failure 243 54.9 Pneumonia 62 88.5

PRINCIPAL FINDINGS

 Reliability of RSRRs varies widely by condition  The AMI readmission measure is particularly unreliable:  Low volume  Low between-hospital variation: AMI: 14%-28%, PN: 12%-55%  A modest amount of the variation in RSRRs can be explained by hospital and community-level factors,

beyond patient factors

 Only 79 hospitals (8.8%) had moderate reliability on all measures (AMI, Heart Failure, and Pneumonia 12

LIMITATIONS

 No Medicare claims data

 CMS risk-adjustment models  Does not ensure all individuals are Medicare beneficiaries

 Limited sample – selected states (AR, CA, FL, IA, NY, and WA)  Expanded list of measures – COPD, TH/KA, CABG

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POLICY IMPLICATIONS

 To the extent that their measures are unreliable, many hospitals may

end up being penalized unnecessarily

 As between-hospital variation in RSRRs reduces, measures become

less reliable

 Reducing readmissions requires investments into multifaceted

interventions

 Hospital investments may be misallocated

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FUTURE DIRECTIONS: IMPROVING RELIABILITY

• 1. Raise minimum case volume for eligibility
• 2. Eligibility criteria based on minimum benchmark
• f reliability, rather than volume
• 3. Drop AMI measure, add other conditions
• 4. Employ composite Readmission measure

 Condition groups  Hospital-Wide All-Cause Readmission Rate

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ILLUSTRATION CREDITS

Illustration Credits



Man by Giovanni Tagliente



currency by Creative Stall from the Noun Project



Money by Marie Van den Broeck



signal by useiconic.com from the Noun Project



low signal by TMD from the Noun Project



Dice by Les Kleuver from the Noun Project



pressure horizontal by ImageCatalog from the Noun Project



trend by ChangHoon Baek from the Noun Project

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