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Shojania KG, Burton EC, McDonald KM, et al. The Autopsy as an Outcome and Performance Measure. Rockville (MD): Agency for Healthcare Research and Quality (US); 2002 Oct. (Evidence Reports/Technology Assessments, No. 58.)

  • This publication is provided for historical reference only and the information may be out of date.

This publication is provided for historical reference only and the information may be out of date.

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The Autopsy as an Outcome and Performance Measure.

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Appendix B: Statistical Analysis

The error rate was modeled from country, time, case mix and autopsy rate using a logistic model with a random study effect. Case mix and country were treated as categorical effects. More specifically, if X 1, X 2, … are the above predictor variables, Ne the number of errors found for a study with Na autopsies, then the error rate p (Ne / Na) is modeled as 1 / (1 + e) where λ = β0 + β1 X 1 + β2 X 2 + … + u with the random study effect, u, having a normal distribution with mean 0 and variance σ2. Computations were done using the SAS NLMixed procedure. [SAS software, version 8.2, SAS Institute: Cary, NC.]

In the tables and analysis below, Case Mix (CM) was categorized as follows:

  1. General inpatients or general adult inpatients
  2. Adult medical
  3. Adult ICU
  4. Adult or pediatric surgery
  5. Pediatric inpatients
  6. Neonatal or pediatric ICU
  7. Other

Country was treated as a dichotomous variable, with U.S. studies assigned the value –1 and non-U.S. studies =1.

Time was defined as the midpoint of the study period (using whole or half years) and centered with 1980 as T=0. Thus a study reporting autopsies over the calendar year 1979 would be centered at –0.5; a study with a 2-year study period including 1982 and 1983 would be centered at +3.

Autopsy rates were also centered, using the unweighted mean autopsy rate for the included studies, which was 44.3% for studies reporting Class I and major errors.

For each of the error definitions (Class I, major errors, discrepant major ICD disease classifications), the analysis began with a model that included all predictors–study period, autopsy rate, case mix (general adult inpatients, medical patients, surgical parents, pediatric, etc.) and country (U.S., non-U.S.). We then compared this model with models in which one variable at a time was dropped.

The differences between the results produced by these models and the more complete model above were not statistically significant for Class I errors, but they were for the other two error definitions (data not shown). Even for Class I errors, the contributions of these other factors (autopsy rate, country, case mix) were noticeable, even if not statistically significant, and were clearly plausible. Therefore, we used the more complete model to compute the mean error rate and the range of error rates shown in the analyses and tables below for all three error definitions.

A. Class I Error Rates

Model 1: Time, Autopsy rate, Country and Case Mix

VariableEstimateStandard ErrorOdds RatioLower 95% CIUpper 95% CIP-value
Intercept-2.26220.21750.104120.066990.1618<.0001
Time-0.81220.60070.443890.13131.50080.1848
Autopsy rate-0.030410.018250.970050.93481.00660.1044
Country-0.093380.13220.910850.69671.19090.4844
CM 2 vs 10.49690.35131.643700.80613.35160.1658
CM 3 vs 10.19850.31211.219550.64762.29680.5289
CM 4 vs 10.35890.34491.431730.71142.88150.3050
CM 5 vs 1-0.33060.63890.718500.19662.62540.6080
CM 6 vs 10.033480.36341.034050.49482.16100.9271
CM 7 vs 1-0.43480.40070.647420.28731.45920.2851

I. Time Trend

Coefficient for Year = -0.03041 → -0.3041 to use decade as unit of analysis instead of single year

Odds ratio = exp (–0.3041)= 0.7378

<Subtract above from 1.0 to obtain relative decreases>

→ 0.2622

Class I error rates showed relative decrease of 26.2% per decade (p=0.1044)

95% CI = exp (-0.3041 ± 2*0.1825)

= exp (-0.3041 ± 0.3650)

= exp (0.0609, -0.6691)

= (1.0628,0.5122)

<Subtract above from 1.0 to obtain relative decreases>

→ (-0.0628,0.4878)

→ Class I error rates showed relative decrease of 28.0% (95% CI: 48.8% decrease to 6.3% increase) per decade

II. Relationship to Autopsy Rate

Coefficient Autopsy Rate = -0.8122

(-0.8122/10 = -0.08122 to calculate relationship as per 10% change in Autopsy Rate

Odds ratio = exp (-0.08122) = 0.9220

<Subtract above from 1.0 to obtain relative decrease>

(0.0780)

For every 10% increase in autopsy rate, Class I error rate decreased by 7.8% (p=0.1848)

95% CI = exp (-0.08122 (2*0.6007/10)

= exp (-0.08122 (0.12014)

= exp (-0.20136, 0.03892)

= 0.8176, 1.04

<Subtract above from 1.0 to obtain relative decreases>

(-0.0400, 0.1824)

(Class I error rate exhibited 7.8% relative decrease (95% CI: 18.2% decrease to 4.0% increase) for each 10% increase in autopsies.

III. Calculation of “mean” Class I error rate

Because error rates varied with time and autopsy rate (as well as case mix, though to a lesser extent), a true “mean” error rate does not exist. However, we can estimate a “base error rate,” if the predictor variables are all set to their base values (i.e., time=1980, autopsy rate = mean rate of 44.3%, country=U.S., and case mix=general autopsies).

A point estimate for the base error rate can then be obtained from the regression equation,

Prob (Class I error) = 1 / (1 + e) where λ = β0 + β1 X 1 + β2 X 2 + … + u

Intercept= -2.2622 and, for the base probability, the terms for time, autopsy rate and case mix all equal zero, because the equation is centered on these values.

Therefore,

λ= -2.2622 + (1980-1980)(–0.03041) + (-0.8122)(0.443–0.443) + (-0.09338)(-1), where the –1 in the country term reflects the value assigned to U.S. (non-U.S.=+1).

Thus, λ= -2.16882, so that base prob (Class I error) = 1 / (1 + e‐(-2.16882))

→ Base prob (Class I error) = 0.10258→ 10.2%

Base error and 95% CI obtained from software were: 0.1023 and (0.06701, 0.1532)

Therefore, base rate of Class I errors was: 10.2% (95% CI: 6.7–15.3%)

Because the trends over time and the relationship to autopsy rate were not statistically significant for Class I errors, this base error rate provides a reasonable overall mean rate for Class I errors. It is clear, though (as shown in Table below), that the effects of study period (time) and autopsy rate are noticeable enough (even if not statistically significant for Class I errors). Therefore, a true “mean error rate” is not meaningful in the absence of stipulated values for time and autopsy rate. The table below shows how the Class I error rate varies with time and autopsy rate using the regression model above, with country equal to U.S. and case mix equal to general autopsies.

Autopsy Rate1970198019902000
5% 17.6%13.6%10.4%7.9%
10% 17.0%13.1%10.0%7.6%
15% 16.5%12.7%9.7%7.3%
20% 15.9%12.2%9.3%7.1%
25% 15.4%11.8%9.0%6.8%
30% 14.9%11.4%8.7%6.5%
40% 13.9%10.6%8.0%6.1%
50% 12.9%9.9%7.5%5.6%
60% 12.0%9.2%6.9%5.2%
70% 11.2%8.5%6.4%4.8%
80% 10.4%7.9%5.9%4.5%
100% 9.0%6.8%5.1%3.8%

B. Class I Errors: U.S. only

Model 1: Time, Autopsy rate and Case Mix

VariableEstimateStandard ErrorOdds RatioLower 95% CIUpper 95% CIP-value
Intercept-2.06780.25010.126470.074770.2139<.0001
Time-1.66291.25900.189580.013462.67030.2031
Autopsy rate-0.055010.028600.946470.89131.00510.0704
CM 2 vs 10.18570.58081.204050.35544.07960.7529
CM 3 vs 10.32230.39661.380270.60003.17540.4270
CM 4 vs 10.51440.69961.672610.38467.27340.4717
CM 5 vs 1-0.27630.58840.758610.22042.61130.6443
CM 6 vs 10.013200.63911.013290.26463.88020.9837
CM 7 vs 1-0.32280.45330.724100.27941.87690.4855

Coefficient for Time is –0.05501

→ -0.5501 to use decade as unit of analysis instead of single year

odds ratio = exp (–0.5501)= 0.57689

<Subtract above from 1.0 to obtain relative decrease>

→ 0.42311

→ Error rate showed relative decrease of 42.3% per decade, but this relationship was not statistically significant (p=0.07)

Coefficient Autopsy Rate = -1.6629

→ -1.6629/10 = -0.16629 to calculate relationship as per 10% change in Autopsy Rate

odds ratio = exp (-0.166291) = 0.8468

<Subtract above from 1.0 to obtain relative decrease>

→ For every 10% increase in autopsy rate, error rate decreases by approximately 15.3%, but this relationship was not statistically significant (p=0.2).

Prob (Class I error) = 1 / (1 + e) where λ = β0 + β1 X 1 + β2 X 2 + … + u

Intercept= -2.0678

For base probability, time, autopsy and case mix terms all equal zero and there is no country terms in the analysis restricted to U.S. only, so

λ = -2.0678

Therefore,

→ Base prob (Class I error) = 1 / (1 + e‐(-2.0678))

→ Base prob (Class I error) = 0.1117→ 11.2%

The value calculated using the statistical software corroborated this estimate and provided the corresponding confidence interval.

Thus, the mean Class I error rate using data from U.S. only is 11.2% (95% CI: 6.9–17.5%).

Summary

In the model adjusting for study period, variations in autopsy rates, differences in case mix and study country (U.S. vs. non-U.S.), the probability of the autopsy detecting a Class I error in a given case was 10.2% (95% CI: 6.7–15.3%). Restricting the analysis to data from U.S. institutions only, yielded a similar point estimate, but a slightly wider confidence interval, 11.2% (95% CI: 6.9–17.5%).

The expected inverse correlation between error rate and study period (i.e., the more recent the study the lower the error rate) was modest and statistically significant. Specifically, the probability of a Class I error showed a relative decrease of 28.0% per decade (p=0.1; 95% CI: 48.8% decrease to 6.3% increase).

The expected inverse correlation between error rate and autopsy rate (i.e., the higher the autopsy rate, the lower the error rate) was relatively weak and not statistically significant. Specifically, for every 10% increase in autopsies, the Class I error rate exhibited a relative decrease of 7.8% (p=0.2).

C. Major Errors

Model 1: Time, Autopsy Rate, Country and Case Mix

VariableEstimateStandard ErrorOdds RatioLower 95% CIUpper 95% CIP-value
Intercept-0.97730.12380.376330.29310.4831<.0001
a_rate-1.28460.32110.276770.14480.52910.0003
year-0.032880.011310.967660.94580.99000.0058
country0.088330.073231.092350.94231.26630.2345
cm20.25050.20241.284640.85381.93290.2228
cm30.093210.17961.097700.76391.57730.6065
cm40.75180.19692.120831.42543.15550.0004
cm5-0.74060.28420.476800.26870.84610.0126
cm60.019560.27731.019750.58271.78470.9441
cm7-0.21920.17810.803200.56071.15060.2253

I. Time Trend

Coefficient for Time is –0.03288 → -0.3288 to use decade as unit of analysis instead of single year

Odds ratio = exp (–0.3288 ) = 0.719787

<Subtract above from 1.0 to obtain relative decrease>

→ 0.2802

→ Major error rates showed decrease of 28.0% per decade (p=0.0058) relative to the base time period of 1980.

Coefficient Autopsy Rate = -1.2846

10% change → -1.2846/10= -0.12846

Odds ratio = exp (-0.12846) = 0.879449

<Subtract above from 1.0 to obtain relative decrease>

→ 0.120551

For every 10% increase in autopsy rate, major error rate decreases by 12.0% (p=0.0003)

The models dropping case mix, country and autopsy rate (one at a time) produced results with statistically significant differences from the above. Consequently, we used Model 1 (including autopsy rate, country, case mix as predictors of major errors) to compute the mean error rate and the range of error rates shown in the table below and the mean major error rate of 25.6% (95% CI: 20.8–31.2%). The point estimate can be obtained manually using the calculation shown below and was compared with the value generated by the statistical software. (The software was required to calculate the confidence interval.)

Prob (major error) = 1 / (1 + e) where λ = β0 + β1 X 1 + β2 X 2 + … + u

Substituting in Intercept (β0)= -0.9773

and base values of time (1980), autopsy rate (overall mean rate of 44.3%), country (U.S.=-1) and case mix (general autopsies, so that case mix terms CM2,…,CM7 all equal zero), then

λ = -0.9773 + (–0.02223)(1980-1980) + (-0.9603)(0.443–0.443) + (0.08833)(-1)

λ = -1.06563

→ Base prob (major error) = 1 / (1 + e‐(-0.88867))

→ Base prob (major error) = 0.256235 → 25.6%

Calculation performed with statistical software confirmed this estimate and provided the corresponding confidence interval of (0.2077, 0.3116).

Thus, base probability of major error was: 25.6% (95% CI: 20.8–31.2%)

Autopsy Rate1970198019902000
5% 44.3%36.4%29.2%22.9%
10% 42.7%34.9%27.9%21.8%
15% 41.2%33.5%26.6%20.7%
20% 39.6%32.1%25.4%19.7%
25% 38.1%30.7%24.2%18.7%
30% 36.6%29.4%23.0%17.7%
40% 33.7%26.8%20.8%15.9%
50% 30.9%24.3%18.8%14.3%
60% 28.2%22.0%16.9%12.8%
70% 25.7%19.9%15.2%11.4%
80% 23.3%17.9%13.6%10.2%
100% 19.0%14.5%10.8%8.1%

D. Major Errors: U.S. Studies Only

Model 1 – Time, Autopsy Rate, Case-mix

VariableEstimateStandard ErrorOdds RatioLower 95% CIUpper 95% CIP-value
Intercept-1.14990.20020.316660.20980.4779<.0001
Time-1.04110.53820.353060.11681.06730.0640
Autopsy rate-0.024600.018440.975700.93941.01340.1937
CM 2 vs 1-0.007910.46400.992120.38232.57500.9865
CM 3 vs 10.14290.26251.153630.67261.97870.5908
CM 4 vs 10.66150.32431.937740.99503.77380.0516
CM 5 vs 1-0.76280.33810.466370.23280.93440.0327
CM 6 vs 10.22190.49531.248500.45103.45610.6578
CM 7 vs 1-0.20930.25990.811180.47541.38410.4281

Coefficient for Time is –0.0246 → -0.246 to use decade as unit of analysis instead of single year

Odds ratio = exp (–0.246)= 0.78192

→ Error rate exhibited relative decrease of 21.8% per decade, but this relationship was not statistically significant (p=0.2).

Coefficient Autopsy Rate = -1.0411

10% change → -1.0411/10 = -0.10411

Odds ratio = exp (-0.10411) = 0.90113

For every 10% increase in autopsy rate, the major error rate decreased by 9.9% (p=0.06)

Summary

In the model adjusting for study period, variations in autopsy rates, differences in case mix and study country (U.S. vs. non-U.S.), the base probability of the autopsy detecting a major error in a given case was 25.6% (95% CI: 20.8–31.2%). Using data from U.S. institutions only, the base probability of the autopsy detecting a major error was slightly lower at 24.0%, but with an almost entirely overlapping confidence interval (95% CI: 17.3–32.3%).

The expected inverse correlation between error rate and autopsy rate (i.e., the higher the autopsy rate, the lower the error rate) was relatively weak, but in contrast to the results for Class I errors, this relationship was statistically significant. Specifically, for every 10% increase in the autopsy rate, the major error rate decreased by 12.0% (95% CI: 6.2–17.5%).

The expected inverse correlation between error rate and study period (i.e., the more recent the study the lower the error rate) was modest and, in contrast to the results for Class I errors, this relationship was statistically significant. Specifically, the probability of a major error exhibited a relative decrease of 28.0% per decade (95% CI: 9.8–42.6%).

E. ICD Disease Category Discrepancies

Nb: for the analysis below, time was centered at 1975, rather than 1980, as the study periods ranged from 1970-1980. Also, all of the studies using this error classification involved general inpatients or adult inpatients (Case Mix = 1), so case mix was not included in the models below.

Model 1: Time, Autopsy Rate, Country (Error definition 3)

VariableEstimateStandard ErrorOdds RatioLower 95% CIUpper 95% CIP-value
Intercept-2.02520.10240.1320.1030.170<.0001
Time0.24680.020981.2801.2161.347<.0001
Autopsy rate-0.26420.15410.7680.5271.1190.1373
Country0.41870.081261.5201.2461.8540.0021

Intercept= -2.0252; Standard error = 0.1024

95% CI= -2.0252 ± 2*0.1024 → -2.230, -1.8204

probability of error = 0.1166 (95% CI: 0.0971 -0.1394)

Coefficient for Time is 0.2468

Odds ratio = exp (0.2468)= 1.2800

→ Error rate increased by roughly 28% per year (p<0.0001).

Coefficient Autopsy Rate = -0.2642

5% change → -0.2644/20 = -0.01321

Odds ratio = exp(-0.01321) = 0.9869

For every 5% increase in autopsy rate, error rate decreases by approximately 1.4%, but this relationship was not statistically significant (p=0.1)

Summary

In the model adjusting for study period, variations in autopsy rates, study country (U.S. vs. non-U.S.), the autopsy and clinical diagnoses fell in different major ICD in 11.7% (95% CI: 9.7% -13.9%) of cases in this base time period and country and at the base autopsy rate.

In contrast with the other two definitions of errors, ICD discrepancies showed an increase over time, and this relationship was statistically significant. Specifically, the error rate increased by roughly 28% per year (p<0.0001).

The relationship between the ICD discrepancies and autopsy rate did have the expected inverse correlation (as with the other two definitions of errors), but the relationship was weak and not statistically significant. For every 5% increase in autopsy rate, error rate decreases by approximately 1.4%, but this relationship was not statistically significant (p=0.1)

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