Screening Administrative Data - PowerPoint PPT Presentation

1 / 22
About This Presentation
Title:

Screening Administrative Data

Description:

Screening Administrative Data To Assess the Accuracy Of Present-on-Admission Coding Michael Pine, M.D., M.B.A. Michael Pine and Associates, Inc. Chicago, Illinois – PowerPoint PPT presentation

Number of Views:47
Avg rating:3.0/5.0
Slides: 23
Provided by: Michael3197
Learn more at: https://archive.ahrq.gov
Category:

less

Transcript and Presenter's Notes

Title: Screening Administrative Data


1
Screening Administrative Data To Assess the
Accuracy Of Present-on-Admission Coding Michael
Pine, M.D., M.B.A. Michael Pine and Associates,
Inc. Chicago, Illinois 773-643-1700 mpine_at_aol.com
2
Overview
  • Rationale for Development of POA Screens
  • Developmental Database and Selection of Cases
  • Description and Aggregate Performance of 12
    Screens
  • Evaluation of Coding By Individual Hospitals
  • Computation of Composite Scores for Hospitals

3
Rationale for Development of POA Screens
  • POA Code Identifies Hospital-Acquired
    Complications
  • Important in Computing Rates of Adverse Outcomes
  • Important in Risk-Adjusting Performance Measures
  • Accurate Coding Requires Expertise and Teamwork
  • Inaccurate Coding
  • Affects Assessments of Clinical Quality
  • Affects Reimbursement
  • Chart Reviews to Detect Coding Errors Are
    Expensive
  • Well-Designed Screens Can Detect Problems
    Efficiently

4
Developmental Database
  • New York State SPARCS Data from 2003 through 2005
  • 8,388,179 Discharges from 246 Hospitals
  • Secondary Diagnosis Codes Have POA Modifiers
  • 1 Present on Admission
  • 2 Hospital-Acquired
  • 9 Status on Admission Unknown

5
Selection of Cases for Screening
  • High-Risk Conditions By Principal Diagnosis
  • 33 Categories (e.g., septicemia, respiratory
    failure)
  • Mortality 9.2 70 of Deaths 22 of
    Discharges
  • Elective Admissions for Selected Surgical
    Procedures
  • 7 Procedures (e.g., hysterectomy, knee
    replacement)
  • Principal Diagnosis Consistent with Procedure
  • Operation During First 2 Days of Hospitalization
  • Inpatient Childbirth By Diagnosis or Procedure
    Codes

6
Diagnoses Almost Always Present on Admission
  • 231 Diagnosis Groups (e.g., malignancy,
    osteoporosis)
  • Analyzed for Each of the 3 Sets of Cases Screened
  • Aggregate Data for Each Set

Data Set Codes Inpatient Unknown
High-Risk Conditions 5,506,043 1.13 5.75
Elective Surgery 588,874 0.63 4.52
Inpatient Childbirth 112,987 1.85 8.93
7
Complications in High-Risk Conditions
  • Chronic Diagnoses with and without Acute
    Components
  • 21 Pairs (e.g., hernia with and without
    obstruction)
  • Rates At Which Coded As Hospital-Acquired
  • Chronic without Acute 1.06 of 1,612,079
    Diagnoses
  • Chronic with Acute 3.34 of 222,641 Diagnoses
  • Diagnoses Frequently Hospital-Acquired (e.g.,
    anuria)
  • 3 Categories Based on Frequency Hospital-Acquired
  • 27 Diagnosis Groups in Category A 59 in B 54 in
    C
  • Category A - 63.5 of 172,472 Codes
    Hospital-Acquired
  • Category B - 34.7 of 469,970 Codes
    Hospital-Acquired
  • Category C - 24.8 of 772,049 Codes
    Hospital-Acquired

8
Mortality with Hospital-Acquired Complications
  • Only for High-Risk Conditions
  • Mortality Greater When Diagnosis
    Hospital-Acquired
  • 3 Categories Based on Ratio of Mortality Rates
  • 66 Diagnosis Groups in Category A 54 in B 64 in
    C
  • Aggregate Data for Each Category

Category POA Dx Dead Hosp Dx Dead Odds Ratio
A 348,860 12.6 27,406 27.0 2.57
B 747,172 15.3 80,856 25.2 1.87
C 1,335,879 21.2 247,144 30.5 1.64
9
Complications in Elective Surgical Admissions
  • Diagnoses Frequently Hospital-Acquired
    Complications
  • 64 Diagnosis Groups (e.g., septicemia, shock)
  • Of 138,655 Codes, 68.3 Hospital-Acquired
  • Chronic Diagnoses with and without Acute
    Components
  • 21 Pairs (e.g., asthma with and without
    exacerbation)
  • Rates At Which Coded As Hospital-Acquired
  • Chronic without Acute 0.39 of 187,453 Diagnoses
  • Chronic with Acute 18.72 of 2,174 Diagnoses

10
Risk-Adjusted Post-Op Lengths of Stay
  • High Rates of Prolonged LOS in Uncomplicated
    Cases
  • Develop Predictive Equations for Routine Post-Op
    LOS
  • Compute Observed Minus Predicted Post-Op LOS
  • For All Live Discharges at Each Hospital
  • Create XmR Control Charts of OBS minus PRED LOS
  • Remove Outliers with Prolonged Post-Op LOS
  • Repeat Process Until No Further Outliers
    Identified
  • Set Upper Bound at Median Outlier Rate for All
    Hospitals
  • Repeat Process Using Only Uncomplicated Cases
  • Compute Outlier Rates for Each Hospital
  • Identify Hospitals with Rates Greater Than Upper
    Bound

11
Risk-Adjusted Post-Op Lengths of StayLive
Discharges with and without Reported Complications
12
Risk-Adjusted Post-Op Lengths of StayLive
Discharges without Reported Complications
13
Complications in Obstetrical Admissions
  • Diagnoses Usually Present on Admission
  • 7 Diagnosis Groups (e.g., multiple gestation)
  • Of 448,242 Codes, 5.19 Hospital-Acquired
  • Fifth Digit Codes Incompatible with Inpatient
    Delivery
  • 737,125 Inpatient Deliveries
  • Fifth Digit 0 or 3 or 4 in 0.27
  • Inpatient Post-Partum Complications
  • 74,669 Cases with Obstetrical Fifth Digit 2
  • No Diagnosis Coded As Hospital-Acquired in 36.5

14
Initial Analyses of Hospital Coding
  • 226 Hospitals Screened with One or More Measures
  • 22 Hospitals Have More Than 10 Unknowns
  • Diagnoses Almost Always Present on Admission
  • Less Than 2 of Diagnoses Hospital-Acquired

Data Set Hospitals Meeting Criterion
High-Risk Conditions 200 91.5
Elective Surgery 123 89.4
Inpatient Delivery 48 45.8
15
Hospital Coding for High-Risk Conditions
  • Chronic Diagnoses with Acute Components
  • Hospital-Acquired Rate Greater Than 2 AND
    Greater Than Twice Rate for Chronic Codes
  • Of 145 Hospitals, 71.7 Met Criteria
  • Diagnoses Frequently Hospital-Acquired
  • Hospital-Acquired Rate Greater Than 15 for
    Category B Diagnoses AND Rate Monotonically
    Decreasing from Category A to Category C
  • Of 181 Hospitals, 83.4 Met Criteria

16
Hospital Mortality Rates for High-Risk Conditions
  • Compute Predicted Mortality Rates
  • Indirect Standardization within Each Category
  • Based on Rates for Diagnoses Present on Admission
  • Odds Ratio of Observed to Predicted Mortality
    Rates
  • Greater Than 1.60 for All Diagnoses OR
  • Greater Than 1.30 for All Diagnoses AND Greater
    Than 1.60 for Diagnoses in Categories A and B
  • Of 184 Hospitals, 82.6 Met Criteria

17
Hospital Coding for Elective Surgical Admissions
  • Diagnoses Frequently Hospital-Acquired
    Complications
  • Hospital-Acquired Rate Greater Than 65
  • Of 175 Hospitals, 61.1 Met Criterion
  • Chronic Diagnoses with Acute Components
  • Compute 2 Standard Deviation Lower Bounds for
    Hospital-Acquired Rates
  • Hospital-Acquired Rate Greater Than 12 AND
    Greater Than Three Times Rate for Chronic Codes
    OR
  • Lower Bound Greater Than Twice Rate for Chronic
    Codes
  • Of 93 Hospitals, 96.8 Met Criteria

18
Prolonged Risk-Adjusted Post-Op Length of Stay
  • Median Outlier Rate for All Live Discharges
    5.36
  • Outlier Rates for Uncomplicated Cases Less Than
    Upper Bound
  • In 81.5 of 178 Hospitals
  • In 98.4 of 64 Reference Hospitals
  • In 71.9 of 114 Remaining Hospitals

19
Hospital Coding for Obstetrical Admissions
  • Diagnoses Usually Present on Admission
  • Hospital-Acquired Rate Less Than 3
  • Of 134 Hospitals, 63.4 Met Criterion
  • Fifth Digit Codes Incompatible with Inpatient
    Delivery
  • Less Than 0.5 of Obstetrical Codes Incompatible
  • Of 134 Hospitals, 87.3 Met Criterion
  • Cases with Inpatient Post-Partum Complications
  • Less Than 20 without Hospital-Acquired Diagnosis
  • Of 123 Hospitals, 41.5 Met Criterion

20
Composite Hospital Scoring
  • Range of Points Assigned to Each Measure
  • Range from 1 to N with N 4, 5, 8, or 10
  • Score Only for 204 Hospitals with Adequate Data
  • Score Measure Only When Volume Criteria Met
  • For Each Hospital, Compute
  • Total of Points Scored for Each Measure
  • Maximum and Minimum Possible Points
  • For Each Measure, Compute Average of Points
    Scored
  • Obtain Final Adjusted Hospital Scores By
    Interpolation

21
Final Adjusted Hospital Scores
Hospital Total Maximum Minimum Adjusted Score Adjusted Score ()
AVG 77.8 96 12 77.8 81.1
A 96 96 12 96.0 100
B 61 61 8 96.0 100
C 66 96 12 66.0 68.8
D 61 68 8 82.7 86.2
E 54 57 7 88.8 92.5
F 48 82 10 55.7 58.0
22
Screening and Improvement of POA Coding
Write a Comment
User Comments (0)
About PowerShow.com