Comments
Abstract
Rationale: National efforts to compare hospital outcomes for patients with pneumonia may be biased by hospital differences in diagnosis and coding of aspiration pneumonia, a condition that has traditionally been excluded from pneumonia outcome measures.
Objectives: To evaluate the rationale and impact of including patients with aspiration pneumonia in hospital mortality and readmission measures.
Methods: Using Medicare fee-for-service claims for patients 65 years and older from July 2012 to June 2015, we characterized the proportion of hospitals’ patients with pneumonia diagnosed with aspiration pneumonia, calculated hospital-specific risk-standardized rates of 30-day mortality and readmission for patients with pneumonia, analyzed the association between aspiration pneumonia coding frequency and these rates, and recalculated these rates including patients with aspiration pneumonia.
Results: A total of 1,101,892 patients from 4,263 hospitals were included in the mortality measure analysis, including 192,814 with aspiration pneumonia. The median proportion of hospitals’ patients with pneumonia diagnosed with aspiration pneumonia was 13.6% (10th–90th percentile, 4.2–26%). Hospitals with a higher proportion of patients with aspiration pneumonia had lower risk-standardized mortality rates in the traditional pneumonia measure (12.0% in the lowest coding and 11.0% in the highest coding quintiles) and were far more likely to be categorized as performing better than the national mortality rate; expanding the measure to include patients with aspiration pneumonia attenuated the association between aspiration pneumonia coding rate and hospital mortality. These findings were less pronounced for hospital readmission rates.
Conclusions: Expanding the pneumonia cohorts to include patients with a principal diagnosis of aspiration pneumonia can overcome bias related to variation in hospital coding.
Pneumonia is the most common infectious cause of hospitalization in the United States, resulting in more than 1 million admissions each year and incurring costs estimated at more than $10 billion annually (1–5). Because of its large public health impact, improving care for patients with pneumonia has been a national priority for decades.
Ongoing programs led by the U.S. Centers for Medicare and Medicaid Services (CMS) that make information about hospital-specific mortality and readmission rates for patients with pneumonia available to the public represent a key federal strategy for improving pneumonia care (6). Although it is widely recognized that such programs depend on risk adjustment to account for differences in patient risk related to age, disease severity, or comorbidity, less attention has been paid to the importance of uniform diagnosis and coding practices across hospitals (7).
We recently reported on trends in hospital diagnosis and coding practices related to sepsis and acute respiratory failure in the setting of severe pneumonia. We found that, over time, an increasing percentage of patients have received one of these alternative principal diagnoses, complicating efforts to evaluate national trends in pneumonia hospitalizations and outcomes because patients with these diagnoses had not been included in pneumonia cohorts (8). In addition, variation between hospitals in the application of sepsis and respiratory failure diagnosis codes among cases of pneumonia have biased efforts to compare hospital performance on CMS mortality and readmission outcome measures, because patients who receive a principal diagnosis of sepsis or respiratory failure have a higher risk of death than those who receive a principal diagnosis of pneumonia (9).
Similarly, CMS’s hospital 30-day pneumonia mortality and readmission measures have traditionally not included patients with a principal diagnosis of aspiration pneumonia, a subset of bacterial pneumonia for which there is no agreed-on definition or gold standard diagnostic test (10, 11). Because patients who receive a diagnosis of aspiration pneumonia tend to be the frail elderly with a high risk of death, as in the case of sepsis and respiratory failure, variation between hospitals in their tendency to diagnose and code aspiration pneumonia has the potential to bias efforts to compare mortality and readmission rates across hospitals (12–14). A particular concern is that hospitals in which a higher percentage of patients receive a diagnosis of aspiration pneumonia might appear to achieve better clinical outcomes, when in fact these findings may simply be an artifact of excluding the highest-risk patients from the measure.
The objective of this study was to characterize variation across U.S. acute care hospitals in the diagnosis of aspiration pneumonia, to analyze the impact of any observed variation on hospital-specific risk-standardized mortality and readmission rates, and to determine the effects of expanding the pneumonia measure cohort to include patients with aspiration pneumonia on hospital outcomes.
We created a total of four patient cohorts to calculate hospital-specific readmission and mortality rates using two different sets of inclusion criteria. Each cohort included Medicare beneficiaries aged 65 years and older who were discharged from a nonfederal, short-term, acute care hospital between July 2012 and June 2015. Two narrowly defined cohorts, created based on traditional CMS readmission and mortality measures specifications used before 2016, included only discharges with a principal diagnosis of pneumonia (International Classification of Diseases, Ninth Revision codes: 480.x, 481, 482.x, 483.x, 485, 486, 487.0, 488.11). The expanded cohorts, one created for each measure, also included discharges with a principal diagnosis of pneumonia or aspiration pneumonia (International Classification of Diseases, Ninth Revision code: 507.0). In constructing each cohort, we included only admissions for patients enrolled in fee-for-service Medicare Parts A and B for 12 months before their index hospitalization. The information from claims in the 12 months before the index admission augments information about patient comorbidities recorded during the index admission and maximizes our ability to adjust for differences in case mix between hospitals.
For the mortality measure cohorts, we excluded admissions for patients who left the hospital against medical advice as well as admissions of individuals enrolled in hospice at admission or at any time in the previous 12 months. In addition, the mortality cohorts included one randomly selected admission per patient annually. For the readmission measure cohorts, we included only admissions for patients who were discharged alive. Multiple index admissions per patient were included if another otherwise qualified admission occurred at least 30 days after discharge from the prior index hospitalization. An admission was never counted as both an index admission and a readmission outcome. We excluded patients who were not enrolled in CMS fee-for-service plans for at least 30 days after discharge.
We defined 30-day mortality as death due to any cause within 30 days of the date of admission, and readmission as the occurrence of any unplanned hospitalization within 30 days of discharge from an index admission. Frequencies and percentages were used to summarize categorical variables and median and interquartile range to summarize continuous variables.
To characterize aspiration pneumonia coding frequency across hospitals, the number of patients with a principal diagnosis of aspiration pneumonia was calculated for each hospital and divided by the total number of patients with pneumonia and aspiration pneumonia. To assess variation in the proportion of pneumonia cases not due to differences in patient case mix, we used a hierarchical generalized linear model to calculate a risk-standardized aspiration pneumonia rate, adjusted for age, race, and patient comorbidities. The risk-standardized aspiration pneumonia rate is calculated as the ratio of the “predicted” number of patients with aspiration pneumonia to the “expected” number of patients with aspiration pneumonia for each hospital multiplied by the national rate of aspiration pneumonia.`
Using the hierarchical generalized linear models for current public reporting programs, we calculated hospital-level 30-day risk-standardized mortality rates (RSMRs) and risk-standardized readmission rates. The RSMRs and risk-standardized readmission rates are the ratio of “predicted” outcome events to the number of “expected” outcome events for each hospital. The ratio is then multiplied by the observed national rate. In addition, we used bootstrap methods to create 95% confidence intervals for the risk-standardized rates. As is done in ongoing public reporting programs, hospitals were then classified into one of three performance categories: “better than the U.S. national rate” if their entire confidence interval is below the national rate, “no different than the U.S. national rate” if their confidence interval includes the national rate, and “worse than the U.S. national rate” if their entire confidence interval was above the national rate.
We first examined the RSMRs, risk-standardized readmission rates, and the associated performance categories for the traditional pneumonia cohort by stratifying hospitals into quintiles on the basis of their observed rate of aspiration pneumonia coding. Retaining this stratification, we then examined the RSMRs, risk-standardized readmission rates, and associated performance categories for an expanded pneumonia cohort that also included patients with a principal diagnosis of aspiration pneumonia. We interpreted the association between coding frequency and performance ranking by examining the relative proportion of hospitals categorized as performing better or worse than the national rate within each quintile. If there was no association between coding frequency and performance on quality measures, we would expect that the relative proportions of hospitals performing better or worse than the national rate would be independent of the percentage of pneumonia cases given a diagnosis of aspiration.
A P value < 0.05 was considered statistically significant. All analyses were done using SAS 9.4 (SAS Institute Inc., Cary, NC). Institutional Review Board approval was obtained through the Yale University Human Investigations Committee.
A total of 1,101,892 patients aged 65 years and older from 4,263 hospitals were included in the mortality analysis, including 192,814 (17.5%) who were given a principal diagnosis of aspiration pneumonia. Compared with patients with other forms of pneumonia, those who received a diagnosis of aspiration were older (84 vs. 81 yr); had a higher burden of comorbidity—notably cerebrovascular disease (37.1 vs. 21%), dementia (59.5 vs. 30.4%), and malnutrition (28.1 vs. 12.8%); and were nearly three times as likely to die within 30 days of admission (29.4 vs. 11.6%) (Table 1). Characteristics of the patients included in the readmission cohort were similar to those in the mortality cohort; however, patients with a diagnosis of aspiration pneumonia had only modestly higher rates of readmission within 30 days compared with those with other forms of pneumonia (18.7 vs. 16.5%) (see Table E1 in the online supplement).
| Pneumonia Only | Aspiration Pneumonia Only | |
|---|---|---|
| No. of index admissions | 909,078 | 192,814 |
| Mortality within 30 d of admission | 11.6 | 29.4 |
| Age, median (interquartile range), yr | 81 (74, 87) | 84 (77, 89) |
| Male | 44.7 | 52.3 |
| Acute myocardial infarction | 3.9 | 4.6 |
| Asthma | 11.7 | 8.7 |
| Cardiorespiratory failure or shock | 22.2 | 28.0 |
| Cerebrovascular disease | 21.0 | 31.7 |
| Chronic liver disease | 2.2 | 2.3 |
| Chronic obstructive pulmonary disease | 53.3 | 46.1 |
| Congestive heart failure | 37.7 | 40.9 |
| Coronary atherosclerosis or angina | 48.8 | 48.1 |
| Decubitus ulcer or chronic skin ulcer | 5.4 | 13.2 |
| Delirium and encephalopathy | 8.5 | 18.3 |
| Dementia or other specified brain disorders | 30.4 | 59.5 |
| Depression | 24.6 | 30.9 |
| Disorders of fluid/electrolyte/acid–base | 35.6 | 47.3 |
| Fibrosis of lung or other chronic lung disorders | 13.6 | 12.2 |
| Hemiplegia, paraplegia, paralysis, functional disability | 8.5 | 20.1 |
| History of coronary artery bypass graft surgery | 9.3 | 8.0 |
| History of percutaneous transluminal coronary angioplasty | 7.9 | 5.7 |
| History of pneumonia | 43.3 | 54.6 |
| Hypertension | 87.4 | 87.5 |
| Iron deficiency or other unspecified anemias and blood disease | 57.1 | 65.1 |
| Major psychiatric disorders | 13.8 | 21.8 |
| Metastatic cancer, acute leukemia, and other severe cancers | 9.5 | 7.1 |
| Other acute/subacute forms of ischemic heart disease | 5.8 | 5.9 |
| Parkinson or Huntington diseases | 3.9 | 11.0 |
| Protein-calorie malnutrition | 12.8 | 28.1 |
| Renal failure | 30.7 | 34.7 |
| Respirator dependence/tracheostomy | 0.9 | 1.7 |
| Seizure disorders and convulsions | 5.6 | 12.3 |
| Septicemia/sepsis | 8.2 | 15.0 |
| Severe hematological disorders | 2.2 | 1.9 |
| Stroke | 8.6 | 18.2 |
| Trauma in last year | 40.8 | 51.1 |
| Vascular disease and complications | 31.0 | 35.4 |
| Vertebral fractures | 5.2 | 6.4 |
We observed a large amount of variation between hospitals in the percentage of elderly patients with pneumonia who received a principal diagnosis of aspiration pneumonia. Within the mortality cohort, at the median hospital, 13.6% of patients with pneumonia received a principal diagnosis of aspiration. The proportion of patients coded as aspiration pneumonia varied more than sixfold, from 4.2% of cases at hospitals at the 10th percentile to 26% of cases at the 90th percentile. Even after adjusting for differences in age, race, and comorbidities, coding of aspiration pneumonia varied from 9 to 30% among hospitals between the 10th and 90th percentile (Figure 1). A similar pattern was observed in the readmission cohort (Figure E1).
Figure 1. Risk-adjusted proportion of pneumonia cases coded as aspiration pneumonia across 4,263 U.S. hospitals in the mortality measure cohort.
[More] [Minimize]In the traditional pneumonia cohort, when compared with institutions that applied the aspiration pneumonia diagnosis less frequently, hospitals where a higher percentage of patients were diagnosed with aspiration pneumonia had lower observed and risk-standardized mortality (Figure 2) and were more likely to be categorized as performing better than the national rate (Table 2). For example, among hospitals in the quintile with the lowest percentage of patients with aspiration pneumonia (<7% of cases receiving this diagnosis), the median RSMR was 12.0%. There was a monotonic decline in the RSMR as the percentage of patients having an aspiration pneumonia code increased. Hospitals in the highest coding quintile (>21% of cases) had a median RSMR of 11.0% (Figure 2). These results translated into a positive association between hospital diagnosis and coding practices and the likelihood that they would be considered to have performance better or worse than the national average. For example, among hospitals in the highest quintile of aspiration pneumonia coding, 8.5% of institutions were considered to have better than the national average performance, whereas only 2.4% were considered to be worse than the national average (Table 2). In other words, hospitals that applied the aspiration pneumonia diagnosis to the largest percentage of cases were more than three times as likely to be considered better than the national average than worse than the national average. In contrast, for hospitals in the lowest coding quintile, only one hospital (0.1%) was considered better than the national average, and 3.1% were considered worse than average—that is, 30 times more likely to be considered worse than average.
Figure 2. Association between the proportions of pneumonia cases coded as aspiration pneumonia and hospital risk-standardized mortality rates in the traditional pneumonia cohort.
[More] [Minimize]| Mortality Performance Categories | Lowest Coding (≤7%) (N = 841) | Low Coding (8–11%) (N = 848) | Moderate Coding (12–16%) (N = 838) | High Coding (17–21%) (N = 849) | Highest Coding (≥22%) (N = 833) |
|---|---|---|---|---|---|
| Better than the U.S. national rate | 1 (0.1) | 11 (1.3) | 26 (3.1) | 52 (6.1) | 71 (8.5) |
| No different than the U.S. national rate | 814 (96.8) | 791 (93.3) | 780 (93.1) | 773 (91.1) | 742 (89.1) |
| Worse than the U.S. national rate | 26 (3.1) | 46 (5.4) | 32 (3.8) | 24 (2.8) | 20 (2.4) |
| Readmission Performance Categories | Lowest Coding (≤6%) (N = 849) | Low Coding (7–11%) (N = 853) | Moderate Coding (12–15%) (N = 845) | High Coding (16–21%) (N = 841) | Highest Coding (≥22%) (N = 839) |
| Better than the U.S. national rate | 1 (0.1) | 4 (0.5) | 6 (0.7) | 3 (0.4) | 7 (0.8) |
| No different than the U.S. national rate | 840 (99.0) | 834 (97.8) | 819 (96.9) | 822 (97.7) | 817 (97.4) |
| Worse than the U.S. national rate | 8 (0.9) | 15 (1.7) | 20 (2.4) | 16 (1.9) | 15 (1.8) |
When the pneumonia cohort was expanded to include patients with aspiration pneumonia, the association between hospital coding frequency and hospital risk-standardized mortality rates was no longer apparent (Figure 3). In addition, inclusion of these patients also largely attenuated the association between coding frequency and hospital performance categorization (Table 3). For example, among hospitals in the quintile with the highest aspiration pneumonia coding frequency, 8.8% were considered to have better-than-average performance, and 7.4% had worse-than-average performance. Among hospitals in the lowest coding quintile, 0.4% were considered better than the national average, and 1.8% were worse than average.
Figure 3. Association between the proportions of pneumonia cases coded as aspiration pneumonia and hospital risk-standardized mortality rates in the expanded pneumonia cohort.
[More] [Minimize]| Mortality Performance Categories | Lowest Coding (≤7%) (N = 841) | Low Coding (8–11%) (N = 848) | Moderate Coding (12–16%) (N = 838) | High Coding (17–21%) (N = 849) | Highest Coding (≥22%) (N = 833) |
|---|---|---|---|---|---|
| Better than the U.S. national rate | 3 (0.4) | 17 (2.0) | 41 (4.9) | 56 (6.6) | 73 (8.8) |
| No different than the U.S. national rate | 823 (97.8) | 798 (94.0) | 764 (91.2) | 757 (89.2) | 698 (83.8) |
| Worse than the U.S. national rate | 15 (1.8) | 33 (4.0) | 33 (3.9) | 36 (4.2) | 62 (7.4) |
| Readmission Performance Categories | Lowest Coding (≤6%) (N = 849) | Low Coding (7–11%) (N = 853) | Moderate Coding (12–15%) (N = 845) | High Coding (16–21%) (N = 841) | Highest Coding (≥22%) (N = 839) |
| Better than the U.S. national rate | 1 (0.1) | 6 (0.7) | 12 (1.4) | 14 (1.7) | 14 (1.7) |
| No different than the U.S. national rate | 840 (98.9) | 827 (97.0) | 805 (95.3) | 796 (94.6) | 788 (93.9) |
| Worse than the U.S. national rate | 8 (1.0) | 20 (2.3) | 28 (3.3) | 31 (3.7) | 37 (4.4) |
Patients with a diagnosis of aspiration pneumonia had only modestly higher readmission rates than other patients with pneumonia. Consequently, there was little to no association between aspiration pneumonia coding frequency and risk-standardized readmission rates or performance category (Table 2, Figure E2). Accordingly, expanding the cohort had a negligible impact on the readmission measure, where coding had only a weak association with performance (Table 3, Figure E3).
In this analysis of hospital diagnostic and coding practices for elderly patients with pneumonia, we found that, between 2012 and 2015, more than 17% of Medicare beneficiaries received a principal diagnosis of aspiration pneumonia, a diagnosis that was associated with a nearly threefold increased risk of death within 30 days of admission and a modestly higher risk of readmission compared with other forms of pneumonia. The variation between hospitals in both the observed and risk-adjusted proportions of pneumonia cases coded as being due to aspiration was striking, suggesting that this variation stemmed less from differences in patient case mix and more from local hospital diagnosis and coding practices. Hospitals that applied the aspiration pneumonia code more frequently had lower observed and risk-standardized 30-day mortality rates under the traditional pneumonia quality measure and were more likely to be identified as performing better than the national rate. Expansion of the pneumonia measure cohort to include patients with aspiration pneumonia attenuated the association between hospital coding and outcomes and performance categorization. These findings support the conclusion that U.S. Centers for Medicare and Medicaid Services’ recent changes to the pneumonia outcome measures reduce biases associated with variation in hospital diagnosis and coding practices (15).
A number of prior investigators have compared the outcomes of patients with aspiration pneumonia to those with other forms of pneumonia (13, 16, 17). In a recent multicenter, international study of some 5,185 patients with community-acquired pneumonia, Lanspa and colleagues reported that 8.7% were given a diagnosis of aspiration pneumonia (13). Although 8.7% is lower than the 17% we observed, their database included all adult patients, whereas we limited the analysis to individuals 65 years or older. As in our study, Lanspa and colleagues found that patients diagnosed with aspiration pneumonia were older, had more comorbidity, and had higher observed (23 vs. 9%) and adjusted (odds ratio, 2.3) risk of in-hospital mortality (13). Our study confirms the findings of Lanspa and colleagues in a national dataset of exclusively elderly patients.
More than just replicating earlier studies using a larger dataset, this study illuminates differences in diagnosis and coding practices across hospitals and analyzes the impact of those differences on hospital performance measures. In this way, our study has strong parallels to recent research that examined variation in the use of the principal diagnosis of sepsis and respiratory failure in the setting of pneumonia. In a 2014 study of 329 U.S. hospitals, Rothberg and colleagues found that the percentage of patients with pneumonia who received a principal diagnosis of sepsis or respiratory failure varied widely between hospitals (9). This pattern was driven largely by differences between hospitals in the threshold for applying a diagnosis of sepsis or respiratory failure, rather than by differences in underlying disease severity. As in the present study, these diagnosis and coding practices had important implications for quality measures, because patients with pneumonia who received those alternative principal diagnoses (sepsis and respiratory failure) have also traditionally been excluded from pneumonia quality measures. More recently, Sjoding and colleagues performed a series of simulation studies using Medicare claims to determine the degree to which hospitals could potentially “game” mortality or readmission measures to change their performance rankings by legitimately recoding patients with pneumonia to a principal diagnosis of sepsis or respiratory failure (18). As in our study, Sjoding and colleagues found that hospital performance on the U.S. Centers for Medicare and Medicaid Services mortality measure, and to a lesser extent the readmission measure, were quite sensitive to hospital coding practices. These and other studies provided the motivation for recent changes to the U.S. Centers for Medicare and Medicaid Services pneumonia measures that led to the inclusion of patients with a principal diagnosis of sepsis to better capture the full spectrum of pneumonia severity.
What might explain the large differences we observed in case-mix–adjusted rates of aspiration pneumonia across hospitals? First, in the absence of sensitive and specific markers of aspiration, aspiration pneumonia is a clinical diagnosis, often made based on risk factors such as a history of stroke and dementia (14, 19, 20). Second, physicians have difficulty distinguishing aspiration pneumonia from aspiration pneumonitis, an acute condition that can be associated with fever, hypoxia, and chest radiograph infiltrates but is noninfectious (12, 21–23). Together, these factors create uncertainty on the part of treating physicians that may lead some to make a diagnosis of aspiration pneumonia when others would not, manifesting in local or regional variation in rates of aspiration pneumonia.
In the context of this uncertainty, some diagnostic and coding practices may be influenced by the higher payment rates associated with aspiration pneumonia. Although the Medicare Severity Diagnosis-Related Group for simple pneumonia (Medicare Severity Diagnosis-Related Group 193–195) has payment weights ranging from 0.71 to 1.42, patients coded as having aspiration pneumonia are assigned to Medicare Severity Diagnosis-Related Group 177 to 179 (respiratory infections and inflammations), with payment weights ranging from 0.97 to 1.90 (24). This difference translates into thousands of dollars per case. Many hospitals have Clinical Documentation Improvement programs, in which nurses or medical coders send queries to physicians to increase awareness and documentation of aspiration pneumonia (and other coding-sensitive conditions) as a strategy to enhance hospital reimbursement (25). Beyond the immediate impact that these programs have on hospital Diagnosis-Related Group payments, they have far-reaching consequences on hospital outcome measurement. Once a hospital begins coding a large proportion of pneumonia cases as being due to aspiration, they systematically remove the patients at highest risk of mortality from the measure cohort. As we have demonstrated, this skews the remaining pneumonia cases toward those with lower risk.
Our study has a number of strengths. First, to our knowledge, this is the first analysis of hospital diagnosis and coding practices focused on aspiration pneumonia. Second, our findings have immediate policy implications, because they strongly suggest that the traditional pneumonia outcome measures have been biased by the variation in coding practice we described. In fact, our preliminary analyses were the catalysts for recent changes to the U.S. Centers for Medicare and Medicaid Services pneumonia outcomes measures that have expanded these cohorts to include patients with aspiration pneumonia (15). Finally, our use of a sample that includes all hospitalizations for pneumonia among Medicare fee-for-service beneficiaries maximizes the generalizability of our findings.
Although our findings were striking, our results should be interpreted in light of several limitations. First, we used diagnosis codes to identify patients with pneumonia and aspiration pneumonia, which have less than ideal operating characteristics. In particular, International Classification of Diseases, Ninth Revision codes do not differentiate aspiration pneumonia from pneumonitis, and given our large sample size we did not have a way to validate the accuracy of the clinical diagnosis of aspiration pneumonia. This is inherently challenging, because there is no gold standard diagnosis for aspiration pneumonia. However, the wide variation we observed in risk-adjusted rates of aspiration pneumonia across hospitals suggests that variation was a hospital cultural phenomenon rather than one due to differences in patient mix. Moreover, although the United States has now transitioned from International Classification of Diseases, Ninth Revision to International Classification of Diseases, Tenth Revision, there have been no substantive changes to coding options for aspiration pneumonia. Regardless of coding challenges themselves, our methods mirrored those used in federal public reporting programs, ensuring that our results are highly relevant to measures used in practice (26, 27). Similarly, in keeping with current U.S. Centers for Medicare and Medicaid Services measure methodology, we did not exclude patients with immunosuppression, malignancy, or other risk factors for unusual or resistant pathogens. Third, although we observed a positive association between the percentage of patients receiving a diagnosis of aspiration pneumonia and lower hospital mortality rates, we cannot rule out the possibility that hospitals that had higher rates of aspiration pneumonia diagnosis might also provide better care to patients with pneumonia. Nevertheless, we are unable to identify a mechanism that would support this hypothesis. Last, we cannot differentiate the effects of physician diagnosis from hospital coding practices. However, because hospital coders must rely on physician documentation, our results suggest physician practice with regard to the diagnosis of aspiration pneumonia varies considerably, even if some of this variation may be the result of prompts from hospital coding departments.
In conclusion, wide variation between hospitals in the diagnosis and coding of aspiration pneumonia among the elderly appears to have biased national efforts to compare hospital performance. Expanding the diagnosis codes used to define pneumonia to include patients with a principal diagnosis of aspiration pneumonia can overcome bias in quality measures related to variation in coding between hospitals.
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Supported by a contract from the Centers for Medicare and Medicaid Services to develop and maintain hospital outcome measures.
Author Contributions: P.K.L., K.M.S., J.S.R., and K.D. conceived of the study. K.M.S. and J.N.G. analyzed the data. All authors contributed to the interpretation of the results. P.K.L. drafted the manuscript. All authors contributed to revising the manuscript critically for important intellectual content. All authors give final approval of the version to be published. All authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
This article has an online supplement, which is accessible from this issue’s table of contents at www.atsjournals.org.
Author disclosures are available with the text of this article at www.atsjournals.org.
