Penelope S. Pekow, PhD

METHODS

RESULTS

DISCUSSION

CONCLUSIONS

METHODS

RESULTS

DISCUSSION

CONCLUSIONS

METHODS

RESULTS

DISCUSSION

CONCLUSIONS

Improvement in the quality of hospital care in the United States is a national priority, both to advance patient safety and because our expenditures exceed any other nation's, but our health outcomes lag behind.[1, 2] Healthcare spending for children is growing at a faster rate than any other age group, with hospital care accounting for more than 40% of pediatric healthcare expenditures.[3] Inpatient healthcare comprises a greater proportion of healthcare costs for children than for adults, yet we have limited knowledge about where this care is provided.[4]

There is substantial variability in the settings in which children are hospitalized. Children may be hospitalized in freestanding children's hospitals, where all services are designed for children and which operate independently of adult‐focused institutions. They may also be hospitalized in general hospitals where care may be provided in a general inpatient bed, on a dedicated pediatric ward, or in a children's hospital nested within a hospital, which may have specialized nursing and physician care but often shares other resources such as laboratory and radiology with the primarily adult‐focused institution. Medical students and residents may be trained in all of these settings. We know little about how these hospital types differ with respect to patient populations, disease volumes, and resource utilization, and this knowledge is important to inform clinical programs, implementation research, and quality improvement (QI) priorities. To this end, we aimed to describe the volume and characteristics of pediatric hospitalizations at acute care general hospitals and freestanding children's hospitals in the United States.

METHODS

RESULTS

Overall, 3866 hospitals were categorized as a GH, whereas 70 hospitals were categorized as FCHs. Following exclusion of specialty hospitals, 3758 GHs and 50 FCHs were retained in this study. The geographic distribution of hospitals was similar, but although GHs included those in both urban and rural regions, all FCHs were located in urban regions (Table 1).

A total of 1,407,822 (SD 50,456) hospitalizations occurred at GHs, representing 71.7% of pediatric hospitalizations, whereas 554,458 (SD 45,046) hospitalizations occurred at FCHs. Hospitalizations at GHs accounted for 63.6% of days in hospital and 50.0% of pediatric inpatient healthcare costs. Eighty percent of the GHs had total pediatric patient volumes of less than 375 hospitalizations yearly; 11.1% of pediatric hospitalizations occurred at these lower‐volume centers. At FCHs, the median volume of pediatric hospitalizations was 12,001 (interquartile range [IQR]: 583815,448). A total of 36 GHs had pediatric hospitalization volumes in this IQR.

The median age for pediatric patients was slightly higher at GHs, whereas gender, race/ethnicity, primary payer, and median household income for zip code did not differ significantly between hospital types (Table 2). Medical complexity differed between hospital types: children with complex chronic diseases represented 20.2% of hospitalizations at GHs and 35.6% of hospitalizations at FCHs. Severity of illness differed between hospital types, with fewer hospitalizations categorized at the highest level of severity at GHs than FCHs. There were no significant differences between hospital types with respect to the proportion of hospitalizations categorized as neonatal hospitalizations or as elective hospitalizations. The median LOS was shorter at GHs than FCHs. Approximately 1 in 5 children hospitalized at GHs had LOS greater than 4 days, whereas almost 30% of children hospitalized at FCHs had LOS of this duration.

The most common pediatric medical, mental health, and surgical conditions are shown in Figure 1, together representing 32% of pediatric hospitalizations during the study period. For these medical conditions, 77.9% of hospitalizations occurred at GHs, ranging from 52.6% of chemotherapy hospitalizations to 89.0% of hospitalizations for neonatal hyperbilirubinemia. Sixty‐two percent of total hospital costs for these conditions were incurred at GHs. For the common mental health hospitalizations, 86% of hospitalizations occurred at GHs. The majority of hospitalizations and aggregate hospital costs for common surgical conditions also occurred at GHs.

Figure 1

Whereas pneumonia, asthma, and bronchiolitis were the most common reasons for hospitalization at both GHs and FCHs, the most costly conditions differed (see Supporting Table 1 in the online version of this article). At GHs, these respiratory diseases were responsible for the highest condition‐specific total hospital costs. At FCHs, the highest aggregate costs were due to respiratory distress syndrome and chemotherapy. Congenital heart diseases, including hypoplastic left heart syndrome, transposition of the great vessels, tetralogy of Fallot, endocardial cushion defects, coarctation of the aorta and ventricular septal defects accounted for 6 of the 20 most costly conditions at FCHs.

Figure 2 illustrates the volume of hospitalizations, per hospital, at GHs and FCHs for the most common medical hospitalizations. The median number of hospitalizations, per hospital, was consistently significantly lower at GHs than at FCHs (all P values <0.001). Similar results for surgical and mental health hospitalizations are shown as Supporting Figures 1 and 2 in the online version of this article. In our sensitivity analyses that included all hospitals classified as GH and FCH, all results were essentially unchanged.

Figure 2

Recognizing the wide range of pediatric volumes at GHs (Table 1) and our inability to differentiate children's hospitals nested within GHs from GHs with pediatric beds, we examined differences in patient and hospitalization characteristics at GHs with volumes 5838 hospitalizations (the 25th percentile for FCH volume) and GHs with pediatric volumes <5838/year (see Supporting Table 2 in the online version of this article). We also compared patient and hospitalization characteristics at FCHs and the higher‐volume GHs. A total of 36 GHs had pediatric volumes 5838, with hospitalizations at these sites together accounting for 15.4% of all pediatric hospitalizations. Characteristics of patients hospitalized at these higher‐volume GHs were similar to patients hospitalized at FCHs, but they had significantly lower disease severity, fewer neonatal hospitalizations, shorter LOS, and more high‐turnover hospitalizations than patients hospitalized at FCHs. We also observed several differences between children hospitalized at higher‐ and lower‐volume GHs (see Supporting Table 2 in the online version of this article). Children hospitalized at the lower‐volume GHs were more likely to have public health insurance and less likely to have complex chronic diseases, although overall, 39.0% of all hospitalizations for children with complex chronic diseases occurred at these lower‐volume GHs. Compared to children hospitalized at higher‐volume GHs, children hospitalized at the lower‐volume hospitals had significantly lower disease severity, shorter LOS, more direct admissions, and a greater proportion of routine discharges.

DISCUSSION

Of the 2 million pediatric hospitalizations in the United States in 2012, more than 70% occurred at GHs. We observed considerable heterogeneity in pediatric volumes across GHs, with 11% of pediatric hospitalizations occurring at hospitals with pediatric volumes of <375 hospitalizations annually, whereas 15% of pediatric hospitalizations occurred at GHs with volumes similar to those observed at FCHs. The remaining pediatric hospitalizations at GHs occurred at centers with intermediate volumes. The most common reasons for hospitalization were similar at GHs and FCHs, but the most costly conditions differed substantially. These findings have important implications for pediatric clinical care programs, research, and QI efforts.

Our finding that more than 70% of pediatric hospitalizations occurred at GHs speaks to the importance of quality measurement at these hospitals, whereas low per‐hospital pediatric volumes at the majority of GHs makes such measurement particularly challenging. Several previous studies have illustrated that volumes of pediatric hospitalizations are too small to detect meaningful differences in quality between hospitals using established condition‐specific metrics.[13, 14, 15] Our finding that more than 10% of pediatric hospitalizations occurred at GHs with pediatric volumes <375 year supports previous research suggesting that cross‐cutting, all‐condition quality metrics, composite measures, and/or multihospital reporting networks may be needed to enable quality measurement at these sites. In addition, the heterogeneity in patient volumes and characteristics across GHs raise questions about the applicability of quality metrics developed and validated at FCHs to the many GH settings. Field‐testing quality measures to ensure their validity at diverse GHs, particularly those with patient volumes and infrastructure different from FCHs, will be important to meaningful pediatric quality measurement.

Our results illustrating differences in the most common and costly conditions at GHs and FCHs have further implications for prioritization and implementation of research and QI efforts. Implementation research and QI efforts focused on cardiac and neurosurgical procedures, as well as neonatal intensive care, may have considerable impact on cost and quality at FCHs. At GHs, research and QI efforts focused on common conditions are needed to increase our knowledge of contextually relevant barriers to and facilitators of high‐quality pediatric care. This, however, can be made more difficult by small sample sizes, limited resources, and infrastructure, and competing priorities in adult‐focused GH settings.[16, 17, 18] Multihospital learning collaboratives and partnerships between FCHs and GHs can begin to address these challenges, but their success is contingent upon national advocacy and funding to support pediatric research and quality measures at GHs.

One of the most notable differences in the characteristics of pediatric hospitalizations at GHs and FCHs was the proportion of hospitalizations attributable to children with medical complexity (CMC); more than one‐third of hospitalizations at FCHs were for CMC compared to 1 in 5 at GHs. These findings align with the results of several previous studies describing the substantial resource utilization attributed to CMC, and with growing research, innovation, and quality metrics focused on improving both inpatient and outpatient care for these vulnerable children.[19, 20, 21, 22] Structured complex care programs, developed to improve care coordination and healthcare quality for CMC, are common at FCHs, and have been associated with decreased resource utilization and improved outcomes.[23, 24, 25] Notably, however, more than half of all hospitalizations for CMC, exceeding 250,000 annually, occurred at GHs, and almost 40% of hospitalizations for CMC occurred at the lower‐volume GHs. These findings speak to the importance of translating effective and innovative programs of care for CMC to GHs as resources allow, accompanied by robust evaluations of their effectiveness. Lower patient volume at most GHs, however, may be a barrier to dedicated CMC programs. As a result, decentralized community‐based programs of care for CMC, linking primary care programs with regional and tertiary care hospitals, warrant further consideration.[26, 27, 28]

This analysis should be interpreted in light of several limitations. First, we were unable to distinguish between GHs with scant pediatric‐specific resources from those with a large volume of dedicated pediatric resources, such as children's hospitals nested within GHs. We did identify 36 GHs with pediatric volumes similar to those observed at FCHs (see Supporting Table 2 in the online version of this article); patient and hospitalization characteristics at these higher‐volume GHs were similar in many ways to children hospitalized at FCHs. Several of these higher‐volume GHs may have considerable resources dedicated to the care of children, including subspecialty care, and may represent children's hospitals nested within GHs. Because nested children's hospitals are included in the GH categorization, our results may have underestimated the proportion of children cared for at children's hospitals. Further work is needed to identify the health systems challenges and opportunities that may be unique to these institutions. Second, because the 2012 KID does not include a specialty hospital indicator, we developed a proxy method for identifying these hospitals, which may have resulted in some misclassification. We are reassured that the results of our analyses did not change substantively when we included all hospitals. Similarly, although we are reassured that the number of hospitals classified in our analysis as acute care FCHs aligns, approximately, with the number of hospitals classified as such by the Children's Hospital Association, we were unable to assess the validity of this variable within the KID. Third, the KID does not link records at the patient level, so we are unable to report the number of unique children included in this analysis. In addition, the KID includes only inpatient stays with exclusion of observation status stays; potential differences between GH and FCH in the use of observation status could have biased our findings. Fifth, we used the PMCA to identify CMC; although this algorithm has been shown to have excellent sensitivity in identifying children with chronic diseases, using up to 3 years of Medicaid claims data, the sensitivity using the KID, where only 1 inpatient stay is available for assessment, is unknown.[8, 29] Similarly, use of Keren's pediatric diagnosis grouper to classify reasons for hospitalization may have resulted in misclassification, though there are few other nonproprietary pediatric‐specific diagnostic groupers available.

In 2012, more than 70% of pediatric hospitalizations occurred at GHs in the United States. The considerably higher pediatric volumes at FCHs makes these institutions well suited for research, innovation, and the development and application of disease‐specific QI initiatives. Recognizing that the majority of pediatric hospitalizations occurred at GHs, there is a clear need for implementation research, program development, and quality metrics that align with the characteristics of hospitalizations at these centers. National support for research and quality improvement that reflects the diverse hospital settings where children receive their hospital care is critical to further our nation's goal of improving hospital quality for children.

Improvement in the quality of hospital care in the United States is a national priority, both to advance patient safety and because our expenditures exceed any other nation's, but our health outcomes lag behind.[1, 2] Healthcare spending for children is growing at a faster rate than any other age group, with hospital care accounting for more than 40% of pediatric healthcare expenditures.[3] Inpatient healthcare comprises a greater proportion of healthcare costs for children than for adults, yet we have limited knowledge about where this care is provided.[4]

There is substantial variability in the settings in which children are hospitalized. Children may be hospitalized in freestanding children's hospitals, where all services are designed for children and which operate independently of adult‐focused institutions. They may also be hospitalized in general hospitals where care may be provided in a general inpatient bed, on a dedicated pediatric ward, or in a children's hospital nested within a hospital, which may have specialized nursing and physician care but often shares other resources such as laboratory and radiology with the primarily adult‐focused institution. Medical students and residents may be trained in all of these settings. We know little about how these hospital types differ with respect to patient populations, disease volumes, and resource utilization, and this knowledge is important to inform clinical programs, implementation research, and quality improvement (QI) priorities. To this end, we aimed to describe the volume and characteristics of pediatric hospitalizations at acute care general hospitals and freestanding children's hospitals in the United States.

METHODS

RESULTS

Overall, 3866 hospitals were categorized as a GH, whereas 70 hospitals were categorized as FCHs. Following exclusion of specialty hospitals, 3758 GHs and 50 FCHs were retained in this study. The geographic distribution of hospitals was similar, but although GHs included those in both urban and rural regions, all FCHs were located in urban regions (Table 1).

A total of 1,407,822 (SD 50,456) hospitalizations occurred at GHs, representing 71.7% of pediatric hospitalizations, whereas 554,458 (SD 45,046) hospitalizations occurred at FCHs. Hospitalizations at GHs accounted for 63.6% of days in hospital and 50.0% of pediatric inpatient healthcare costs. Eighty percent of the GHs had total pediatric patient volumes of less than 375 hospitalizations yearly; 11.1% of pediatric hospitalizations occurred at these lower‐volume centers. At FCHs, the median volume of pediatric hospitalizations was 12,001 (interquartile range [IQR]: 583815,448). A total of 36 GHs had pediatric hospitalization volumes in this IQR.

The median age for pediatric patients was slightly higher at GHs, whereas gender, race/ethnicity, primary payer, and median household income for zip code did not differ significantly between hospital types (Table 2). Medical complexity differed between hospital types: children with complex chronic diseases represented 20.2% of hospitalizations at GHs and 35.6% of hospitalizations at FCHs. Severity of illness differed between hospital types, with fewer hospitalizations categorized at the highest level of severity at GHs than FCHs. There were no significant differences between hospital types with respect to the proportion of hospitalizations categorized as neonatal hospitalizations or as elective hospitalizations. The median LOS was shorter at GHs than FCHs. Approximately 1 in 5 children hospitalized at GHs had LOS greater than 4 days, whereas almost 30% of children hospitalized at FCHs had LOS of this duration.

The most common pediatric medical, mental health, and surgical conditions are shown in Figure 1, together representing 32% of pediatric hospitalizations during the study period. For these medical conditions, 77.9% of hospitalizations occurred at GHs, ranging from 52.6% of chemotherapy hospitalizations to 89.0% of hospitalizations for neonatal hyperbilirubinemia. Sixty‐two percent of total hospital costs for these conditions were incurred at GHs. For the common mental health hospitalizations, 86% of hospitalizations occurred at GHs. The majority of hospitalizations and aggregate hospital costs for common surgical conditions also occurred at GHs.

Figure 1

Whereas pneumonia, asthma, and bronchiolitis were the most common reasons for hospitalization at both GHs and FCHs, the most costly conditions differed (see Supporting Table 1 in the online version of this article). At GHs, these respiratory diseases were responsible for the highest condition‐specific total hospital costs. At FCHs, the highest aggregate costs were due to respiratory distress syndrome and chemotherapy. Congenital heart diseases, including hypoplastic left heart syndrome, transposition of the great vessels, tetralogy of Fallot, endocardial cushion defects, coarctation of the aorta and ventricular septal defects accounted for 6 of the 20 most costly conditions at FCHs.

Figure 2 illustrates the volume of hospitalizations, per hospital, at GHs and FCHs for the most common medical hospitalizations. The median number of hospitalizations, per hospital, was consistently significantly lower at GHs than at FCHs (all P values <0.001). Similar results for surgical and mental health hospitalizations are shown as Supporting Figures 1 and 2 in the online version of this article. In our sensitivity analyses that included all hospitals classified as GH and FCH, all results were essentially unchanged.

Figure 2

Recognizing the wide range of pediatric volumes at GHs (Table 1) and our inability to differentiate children's hospitals nested within GHs from GHs with pediatric beds, we examined differences in patient and hospitalization characteristics at GHs with volumes 5838 hospitalizations (the 25th percentile for FCH volume) and GHs with pediatric volumes <5838/year (see Supporting Table 2 in the online version of this article). We also compared patient and hospitalization characteristics at FCHs and the higher‐volume GHs. A total of 36 GHs had pediatric volumes 5838, with hospitalizations at these sites together accounting for 15.4% of all pediatric hospitalizations. Characteristics of patients hospitalized at these higher‐volume GHs were similar to patients hospitalized at FCHs, but they had significantly lower disease severity, fewer neonatal hospitalizations, shorter LOS, and more high‐turnover hospitalizations than patients hospitalized at FCHs. We also observed several differences between children hospitalized at higher‐ and lower‐volume GHs (see Supporting Table 2 in the online version of this article). Children hospitalized at the lower‐volume GHs were more likely to have public health insurance and less likely to have complex chronic diseases, although overall, 39.0% of all hospitalizations for children with complex chronic diseases occurred at these lower‐volume GHs. Compared to children hospitalized at higher‐volume GHs, children hospitalized at the lower‐volume hospitals had significantly lower disease severity, shorter LOS, more direct admissions, and a greater proportion of routine discharges.

DISCUSSION

Of the 2 million pediatric hospitalizations in the United States in 2012, more than 70% occurred at GHs. We observed considerable heterogeneity in pediatric volumes across GHs, with 11% of pediatric hospitalizations occurring at hospitals with pediatric volumes of <375 hospitalizations annually, whereas 15% of pediatric hospitalizations occurred at GHs with volumes similar to those observed at FCHs. The remaining pediatric hospitalizations at GHs occurred at centers with intermediate volumes. The most common reasons for hospitalization were similar at GHs and FCHs, but the most costly conditions differed substantially. These findings have important implications for pediatric clinical care programs, research, and QI efforts.

Our finding that more than 70% of pediatric hospitalizations occurred at GHs speaks to the importance of quality measurement at these hospitals, whereas low per‐hospital pediatric volumes at the majority of GHs makes such measurement particularly challenging. Several previous studies have illustrated that volumes of pediatric hospitalizations are too small to detect meaningful differences in quality between hospitals using established condition‐specific metrics.[13, 14, 15] Our finding that more than 10% of pediatric hospitalizations occurred at GHs with pediatric volumes <375 year supports previous research suggesting that cross‐cutting, all‐condition quality metrics, composite measures, and/or multihospital reporting networks may be needed to enable quality measurement at these sites. In addition, the heterogeneity in patient volumes and characteristics across GHs raise questions about the applicability of quality metrics developed and validated at FCHs to the many GH settings. Field‐testing quality measures to ensure their validity at diverse GHs, particularly those with patient volumes and infrastructure different from FCHs, will be important to meaningful pediatric quality measurement.

Our results illustrating differences in the most common and costly conditions at GHs and FCHs have further implications for prioritization and implementation of research and QI efforts. Implementation research and QI efforts focused on cardiac and neurosurgical procedures, as well as neonatal intensive care, may have considerable impact on cost and quality at FCHs. At GHs, research and QI efforts focused on common conditions are needed to increase our knowledge of contextually relevant barriers to and facilitators of high‐quality pediatric care. This, however, can be made more difficult by small sample sizes, limited resources, and infrastructure, and competing priorities in adult‐focused GH settings.[16, 17, 18] Multihospital learning collaboratives and partnerships between FCHs and GHs can begin to address these challenges, but their success is contingent upon national advocacy and funding to support pediatric research and quality measures at GHs.

One of the most notable differences in the characteristics of pediatric hospitalizations at GHs and FCHs was the proportion of hospitalizations attributable to children with medical complexity (CMC); more than one‐third of hospitalizations at FCHs were for CMC compared to 1 in 5 at GHs. These findings align with the results of several previous studies describing the substantial resource utilization attributed to CMC, and with growing research, innovation, and quality metrics focused on improving both inpatient and outpatient care for these vulnerable children.[19, 20, 21, 22] Structured complex care programs, developed to improve care coordination and healthcare quality for CMC, are common at FCHs, and have been associated with decreased resource utilization and improved outcomes.[23, 24, 25] Notably, however, more than half of all hospitalizations for CMC, exceeding 250,000 annually, occurred at GHs, and almost 40% of hospitalizations for CMC occurred at the lower‐volume GHs. These findings speak to the importance of translating effective and innovative programs of care for CMC to GHs as resources allow, accompanied by robust evaluations of their effectiveness. Lower patient volume at most GHs, however, may be a barrier to dedicated CMC programs. As a result, decentralized community‐based programs of care for CMC, linking primary care programs with regional and tertiary care hospitals, warrant further consideration.[26, 27, 28]

This analysis should be interpreted in light of several limitations. First, we were unable to distinguish between GHs with scant pediatric‐specific resources from those with a large volume of dedicated pediatric resources, such as children's hospitals nested within GHs. We did identify 36 GHs with pediatric volumes similar to those observed at FCHs (see Supporting Table 2 in the online version of this article); patient and hospitalization characteristics at these higher‐volume GHs were similar in many ways to children hospitalized at FCHs. Several of these higher‐volume GHs may have considerable resources dedicated to the care of children, including subspecialty care, and may represent children's hospitals nested within GHs. Because nested children's hospitals are included in the GH categorization, our results may have underestimated the proportion of children cared for at children's hospitals. Further work is needed to identify the health systems challenges and opportunities that may be unique to these institutions. Second, because the 2012 KID does not include a specialty hospital indicator, we developed a proxy method for identifying these hospitals, which may have resulted in some misclassification. We are reassured that the results of our analyses did not change substantively when we included all hospitals. Similarly, although we are reassured that the number of hospitals classified in our analysis as acute care FCHs aligns, approximately, with the number of hospitals classified as such by the Children's Hospital Association, we were unable to assess the validity of this variable within the KID. Third, the KID does not link records at the patient level, so we are unable to report the number of unique children included in this analysis. In addition, the KID includes only inpatient stays with exclusion of observation status stays; potential differences between GH and FCH in the use of observation status could have biased our findings. Fifth, we used the PMCA to identify CMC; although this algorithm has been shown to have excellent sensitivity in identifying children with chronic diseases, using up to 3 years of Medicaid claims data, the sensitivity using the KID, where only 1 inpatient stay is available for assessment, is unknown.[8, 29] Similarly, use of Keren's pediatric diagnosis grouper to classify reasons for hospitalization may have resulted in misclassification, though there are few other nonproprietary pediatric‐specific diagnostic groupers available.

In 2012, more than 70% of pediatric hospitalizations occurred at GHs in the United States. The considerably higher pediatric volumes at FCHs makes these institutions well suited for research, innovation, and the development and application of disease‐specific QI initiatives. Recognizing that the majority of pediatric hospitalizations occurred at GHs, there is a clear need for implementation research, program development, and quality metrics that align with the characteristics of hospitalizations at these centers. National support for research and quality improvement that reflects the diverse hospital settings where children receive their hospital care is critical to further our nation's goal of improving hospital quality for children.

Improvement in the quality of hospital care in the United States is a national priority, both to advance patient safety and because our expenditures exceed any other nation's, but our health outcomes lag behind.[1, 2] Healthcare spending for children is growing at a faster rate than any other age group, with hospital care accounting for more than 40% of pediatric healthcare expenditures.[3] Inpatient healthcare comprises a greater proportion of healthcare costs for children than for adults, yet we have limited knowledge about where this care is provided.[4]

There is substantial variability in the settings in which children are hospitalized. Children may be hospitalized in freestanding children's hospitals, where all services are designed for children and which operate independently of adult‐focused institutions. They may also be hospitalized in general hospitals where care may be provided in a general inpatient bed, on a dedicated pediatric ward, or in a children's hospital nested within a hospital, which may have specialized nursing and physician care but often shares other resources such as laboratory and radiology with the primarily adult‐focused institution. Medical students and residents may be trained in all of these settings. We know little about how these hospital types differ with respect to patient populations, disease volumes, and resource utilization, and this knowledge is important to inform clinical programs, implementation research, and quality improvement (QI) priorities. To this end, we aimed to describe the volume and characteristics of pediatric hospitalizations at acute care general hospitals and freestanding children's hospitals in the United States.

METHODS

RESULTS

Overall, 3866 hospitals were categorized as a GH, whereas 70 hospitals were categorized as FCHs. Following exclusion of specialty hospitals, 3758 GHs and 50 FCHs were retained in this study. The geographic distribution of hospitals was similar, but although GHs included those in both urban and rural regions, all FCHs were located in urban regions (Table 1).

A total of 1,407,822 (SD 50,456) hospitalizations occurred at GHs, representing 71.7% of pediatric hospitalizations, whereas 554,458 (SD 45,046) hospitalizations occurred at FCHs. Hospitalizations at GHs accounted for 63.6% of days in hospital and 50.0% of pediatric inpatient healthcare costs. Eighty percent of the GHs had total pediatric patient volumes of less than 375 hospitalizations yearly; 11.1% of pediatric hospitalizations occurred at these lower‐volume centers. At FCHs, the median volume of pediatric hospitalizations was 12,001 (interquartile range [IQR]: 583815,448). A total of 36 GHs had pediatric hospitalization volumes in this IQR.

The median age for pediatric patients was slightly higher at GHs, whereas gender, race/ethnicity, primary payer, and median household income for zip code did not differ significantly between hospital types (Table 2). Medical complexity differed between hospital types: children with complex chronic diseases represented 20.2% of hospitalizations at GHs and 35.6% of hospitalizations at FCHs. Severity of illness differed between hospital types, with fewer hospitalizations categorized at the highest level of severity at GHs than FCHs. There were no significant differences between hospital types with respect to the proportion of hospitalizations categorized as neonatal hospitalizations or as elective hospitalizations. The median LOS was shorter at GHs than FCHs. Approximately 1 in 5 children hospitalized at GHs had LOS greater than 4 days, whereas almost 30% of children hospitalized at FCHs had LOS of this duration.

The most common pediatric medical, mental health, and surgical conditions are shown in Figure 1, together representing 32% of pediatric hospitalizations during the study period. For these medical conditions, 77.9% of hospitalizations occurred at GHs, ranging from 52.6% of chemotherapy hospitalizations to 89.0% of hospitalizations for neonatal hyperbilirubinemia. Sixty‐two percent of total hospital costs for these conditions were incurred at GHs. For the common mental health hospitalizations, 86% of hospitalizations occurred at GHs. The majority of hospitalizations and aggregate hospital costs for common surgical conditions also occurred at GHs.

Figure 1

Whereas pneumonia, asthma, and bronchiolitis were the most common reasons for hospitalization at both GHs and FCHs, the most costly conditions differed (see Supporting Table 1 in the online version of this article). At GHs, these respiratory diseases were responsible for the highest condition‐specific total hospital costs. At FCHs, the highest aggregate costs were due to respiratory distress syndrome and chemotherapy. Congenital heart diseases, including hypoplastic left heart syndrome, transposition of the great vessels, tetralogy of Fallot, endocardial cushion defects, coarctation of the aorta and ventricular septal defects accounted for 6 of the 20 most costly conditions at FCHs.

Figure 2 illustrates the volume of hospitalizations, per hospital, at GHs and FCHs for the most common medical hospitalizations. The median number of hospitalizations, per hospital, was consistently significantly lower at GHs than at FCHs (all P values <0.001). Similar results for surgical and mental health hospitalizations are shown as Supporting Figures 1 and 2 in the online version of this article. In our sensitivity analyses that included all hospitals classified as GH and FCH, all results were essentially unchanged.

Figure 2

Recognizing the wide range of pediatric volumes at GHs (Table 1) and our inability to differentiate children's hospitals nested within GHs from GHs with pediatric beds, we examined differences in patient and hospitalization characteristics at GHs with volumes 5838 hospitalizations (the 25th percentile for FCH volume) and GHs with pediatric volumes <5838/year (see Supporting Table 2 in the online version of this article). We also compared patient and hospitalization characteristics at FCHs and the higher‐volume GHs. A total of 36 GHs had pediatric volumes 5838, with hospitalizations at these sites together accounting for 15.4% of all pediatric hospitalizations. Characteristics of patients hospitalized at these higher‐volume GHs were similar to patients hospitalized at FCHs, but they had significantly lower disease severity, fewer neonatal hospitalizations, shorter LOS, and more high‐turnover hospitalizations than patients hospitalized at FCHs. We also observed several differences between children hospitalized at higher‐ and lower‐volume GHs (see Supporting Table 2 in the online version of this article). Children hospitalized at the lower‐volume GHs were more likely to have public health insurance and less likely to have complex chronic diseases, although overall, 39.0% of all hospitalizations for children with complex chronic diseases occurred at these lower‐volume GHs. Compared to children hospitalized at higher‐volume GHs, children hospitalized at the lower‐volume hospitals had significantly lower disease severity, shorter LOS, more direct admissions, and a greater proportion of routine discharges.

DISCUSSION

Of the 2 million pediatric hospitalizations in the United States in 2012, more than 70% occurred at GHs. We observed considerable heterogeneity in pediatric volumes across GHs, with 11% of pediatric hospitalizations occurring at hospitals with pediatric volumes of <375 hospitalizations annually, whereas 15% of pediatric hospitalizations occurred at GHs with volumes similar to those observed at FCHs. The remaining pediatric hospitalizations at GHs occurred at centers with intermediate volumes. The most common reasons for hospitalization were similar at GHs and FCHs, but the most costly conditions differed substantially. These findings have important implications for pediatric clinical care programs, research, and QI efforts.

Our finding that more than 70% of pediatric hospitalizations occurred at GHs speaks to the importance of quality measurement at these hospitals, whereas low per‐hospital pediatric volumes at the majority of GHs makes such measurement particularly challenging. Several previous studies have illustrated that volumes of pediatric hospitalizations are too small to detect meaningful differences in quality between hospitals using established condition‐specific metrics.[13, 14, 15] Our finding that more than 10% of pediatric hospitalizations occurred at GHs with pediatric volumes <375 year supports previous research suggesting that cross‐cutting, all‐condition quality metrics, composite measures, and/or multihospital reporting networks may be needed to enable quality measurement at these sites. In addition, the heterogeneity in patient volumes and characteristics across GHs raise questions about the applicability of quality metrics developed and validated at FCHs to the many GH settings. Field‐testing quality measures to ensure their validity at diverse GHs, particularly those with patient volumes and infrastructure different from FCHs, will be important to meaningful pediatric quality measurement.

Our results illustrating differences in the most common and costly conditions at GHs and FCHs have further implications for prioritization and implementation of research and QI efforts. Implementation research and QI efforts focused on cardiac and neurosurgical procedures, as well as neonatal intensive care, may have considerable impact on cost and quality at FCHs. At GHs, research and QI efforts focused on common conditions are needed to increase our knowledge of contextually relevant barriers to and facilitators of high‐quality pediatric care. This, however, can be made more difficult by small sample sizes, limited resources, and infrastructure, and competing priorities in adult‐focused GH settings.[16, 17, 18] Multihospital learning collaboratives and partnerships between FCHs and GHs can begin to address these challenges, but their success is contingent upon national advocacy and funding to support pediatric research and quality measures at GHs.

One of the most notable differences in the characteristics of pediatric hospitalizations at GHs and FCHs was the proportion of hospitalizations attributable to children with medical complexity (CMC); more than one‐third of hospitalizations at FCHs were for CMC compared to 1 in 5 at GHs. These findings align with the results of several previous studies describing the substantial resource utilization attributed to CMC, and with growing research, innovation, and quality metrics focused on improving both inpatient and outpatient care for these vulnerable children.[19, 20, 21, 22] Structured complex care programs, developed to improve care coordination and healthcare quality for CMC, are common at FCHs, and have been associated with decreased resource utilization and improved outcomes.[23, 24, 25] Notably, however, more than half of all hospitalizations for CMC, exceeding 250,000 annually, occurred at GHs, and almost 40% of hospitalizations for CMC occurred at the lower‐volume GHs. These findings speak to the importance of translating effective and innovative programs of care for CMC to GHs as resources allow, accompanied by robust evaluations of their effectiveness. Lower patient volume at most GHs, however, may be a barrier to dedicated CMC programs. As a result, decentralized community‐based programs of care for CMC, linking primary care programs with regional and tertiary care hospitals, warrant further consideration.[26, 27, 28]

This analysis should be interpreted in light of several limitations. First, we were unable to distinguish between GHs with scant pediatric‐specific resources from those with a large volume of dedicated pediatric resources, such as children's hospitals nested within GHs. We did identify 36 GHs with pediatric volumes similar to those observed at FCHs (see Supporting Table 2 in the online version of this article); patient and hospitalization characteristics at these higher‐volume GHs were similar in many ways to children hospitalized at FCHs. Several of these higher‐volume GHs may have considerable resources dedicated to the care of children, including subspecialty care, and may represent children's hospitals nested within GHs. Because nested children's hospitals are included in the GH categorization, our results may have underestimated the proportion of children cared for at children's hospitals. Further work is needed to identify the health systems challenges and opportunities that may be unique to these institutions. Second, because the 2012 KID does not include a specialty hospital indicator, we developed a proxy method for identifying these hospitals, which may have resulted in some misclassification. We are reassured that the results of our analyses did not change substantively when we included all hospitals. Similarly, although we are reassured that the number of hospitals classified in our analysis as acute care FCHs aligns, approximately, with the number of hospitals classified as such by the Children's Hospital Association, we were unable to assess the validity of this variable within the KID. Third, the KID does not link records at the patient level, so we are unable to report the number of unique children included in this analysis. In addition, the KID includes only inpatient stays with exclusion of observation status stays; potential differences between GH and FCH in the use of observation status could have biased our findings. Fifth, we used the PMCA to identify CMC; although this algorithm has been shown to have excellent sensitivity in identifying children with chronic diseases, using up to 3 years of Medicaid claims data, the sensitivity using the KID, where only 1 inpatient stay is available for assessment, is unknown.[8, 29] Similarly, use of Keren's pediatric diagnosis grouper to classify reasons for hospitalization may have resulted in misclassification, though there are few other nonproprietary pediatric‐specific diagnostic groupers available.

In 2012, more than 70% of pediatric hospitalizations occurred at GHs in the United States. The considerably higher pediatric volumes at FCHs makes these institutions well suited for research, innovation, and the development and application of disease‐specific QI initiatives. Recognizing that the majority of pediatric hospitalizations occurred at GHs, there is a clear need for implementation research, program development, and quality metrics that align with the characteristics of hospitalizations at these centers. National support for research and quality improvement that reflects the diverse hospital settings where children receive their hospital care is critical to further our nation's goal of improving hospital quality for children.

Breathlessness, or dyspnea, is defined as a subjective experience of breathing discomfort that is comprised of qualitatively distinct sensations that vary in intensity.[1] Dyspnea is a leading reason for patients presenting for emergency care,[2] and it is an important predictor for hospitalization and mortality in patients with cardiopulmonary disease.[3, 4, 5]

Several professional societies' guidelines recommend that patients should be asked to quantify the intensity of their breathlessness using a standardized scale, and that these ratings should be documented in medical records to guide dyspnea awareness and management.[1, 6, 7] During the evaluation and treatment of patients with acute cardiopulmonary conditions, the clinician estimates the severity of the illness and response to therapy based on multiple objective measures as well as the patient's perception of dyspnea. A patient‐centered care approach depends upon the physicians having a shared understanding of what the patient is experiencing. Without this appreciation, the healthcare provider cannot make appropriate treatment decisions to ensure alleviation of presenting symptoms. Understanding the severity of patients' dyspnea is critical to avoid under‐ or overtreatment of patients with acute cardiopulmonary conditions, but only a few studies have compared patient and provider perceptions of dyspnea intensity.[8, 9] Discordance between physician's impression of severity of dyspnea and patient's perception may result in suboptimal management and patient dissatisfaction with care. Furthermore, several studies have shown that, when physicians and patients agree with the assessment of well‐being, treatment adherence and outcomes improve.[10, 11]

Therefore, we evaluated the extent and directionality of agreement between patients' perception and healthcare providers' impression of dyspnea and explored which factors contribute to discordance. Additionally, we examined how healthcare providers document dyspnea severity.

METHODS

RESULTS

Patient Characteristics

Among the 219 patients who met the screening criteria, 81 were not enrolled (Figure 1). Data from 138 patients, with both patient information and provider data on dyspnea assessment, were included. The median age of the patients was 72 years (IQR, 5880 years), 56.5% were women, 75.4% were white, and 28.3% were current smokers. Approximately 30% had a diagnosis of HF, 30% of COPD, and 13.0% of pneumonia. The median comorbidity score was 4 (IQR, 26), and 37.0% of the patients had a BMI 30. At admission, the median oxygen saturation index was 346 (IQR, 287.5460) indicating mild to moderate levels of hypoxia. (Table 1).

Table 1.Patient Characteristics (N = 138)

	Value
NOTE: Abbreviations: BMI, body mass index; COPD, chronic obstructive pulmonary disease; IQR, interquartile range; NRS, numerical rating scale.
Age, median (IQR), y	72 (5880)
Gender
Female	78 (56.5)
Male	60 (43.5)
Race
White	104 (75.4)
Black	16 (11.6)
Hispanic	17 (12.3)
Other	1 (0.7)
Body mass index, median (IQR)	28 (23.334.6)
Obese (BMI 30)	51 (37.0)
Smoker, current	39 (28.3)
Admitting diagnosis
Heart failure	46 (33.3)
COPD/asthma	41 (29.7)
Pneumonia	18 (13.0)
Other	33 (23.9)
Depression	32 (23.2)
Comorbidity score, median (IQR)	4 (26)
Respiratory rate at admission, median (IQR)	20 (1924)
Oxygen saturation index at admission, median (IQR)	346.4 (287.5460)
Patient NRS, median (IQR)
At admission	9 (710)
At discharge	2 (14)
Discharged on home oxygen	45 (32.6)
Respiratory rate at discharge, median (IQR)	20 (1820)
Oxygen saturation index at discharge, median (IQR)	475 (350485)

Figure 1

Agreement Between Patients' Self‐Assessment and Providers' Assessment of Dyspnea Severity

Not all patients had complete data points, and more nurses were interviewed than physicians. Overall, 96 patient‐physician and 138 patient‐nurse pairs participated in the study. A total of 336 patient‐nurse rating dyad assessments of dyspnea and 124 patient‐physician rating dyads assessments were collected (Figure 1). The mean difference between patient and physicians and patient and nurses assessments of dyspnea was 1.23 (IQR, 3 to 0) and 0.21 (IQR, 2 to 2) respectively (a negative score means underestimation by the provider, a positive score means overestimation).

The unadjusted agreement on the severity of dyspnea was 36.3% for the patient‐physician dyads and 44.1% for the patient‐nurse dyads. Physicians underestimated their patients' dyspnea 37.9% of the time and overestimated it 25.8% of the time; nurses underestimated it 43.5% of the time and overestimated it in 12.4% of the study patients (Table 2). In 28.2% of the time, physicians were discordant more than 4 points of the patient assessment. Bland‐Altman plots show that there is greater variation in differences of dyspnea assessments with increase in shortness of breath scores (Figure 2). Nurses underestimated more when the dyspnea score was on the lower end. Physicians also tended to estimate either lower or higher when compared to patients when the dyspnea scores were <2 (Figure 2A,B).

Table 2.Underestimation and Overestimation and Concordance of Dyspnea

	Underestimation			Concordance			Overestimation
	3	2	%*	0	1	%	2	3	%
NOTE: NRS scores by nurses and physicians as compared with patients *Percent underestimation out of all dyads. Percent concordance out of all dyads. Percent overestimation out of all dyads.
Patient‐nurse dyads	110	48	43.5	82	78	44.1	17	28	12.4
Patient‐physician dyads	33	14	37.9	21	24	36.3	12	20	25.8

Figure 2

The weighted kappa coefficient for agreement was 0.11 (95% confidence interval [CI]: 0.01 to 0.21) for patient‐physician assessment, 0.18 (95% CI: 0.12 to 0.24) for patient‐nurse, and 0.09 (0.02 to 0.20) for physician‐nurse indicating poor agreement. In a sensitivity analysis in which we used a higher threshold for defining discordance (difference of more than 2 points), the kappa coefficient increased to 0.21 (95% CI: 0.06 to 0.36) for patient‐physician assessments, to 0.24 (95% CI: 0.15 to 0.33) for patient‐nurse, and to 0.24 (95% CI: 0.09 to 0.39) for nurse‐physician assessments.

DISCUSSION

In this prospective study of 138 patients hospitalized with cardiopulmonary disease, we found that the agreement between patient's experience of dyspnea and providers' assessment was poor, and the discordance was higher for physicians than for nurses. In more than half of the cases, differences between patient and healthcare providers' assessment of dyspnea were present. One‐third of the time, both physicians and nurses underestimated patients' reported levels of dyspnea. Admitting diagnosis was the only patient factor predicting lack of agreement, and patients with COPD were more likely to have their dyspnea underestimated by nurses. Healthcare providers predominantly documented the presence or absence of dyspnea and rarely used a more nuanced scale.

Discrepancies between patient and provider assessments for pain, depression, and overall health have been reported.[8, 18, 19, 20, 21] One explanation is that patients and healthcare providers measure different factors despite using the same terminology. Furthermore, patient's assessment may be confounded by other symptoms such as anxiety, fatigue, or pain. Physicians and nurses may underevaluate and underestimate the level of breathlessness; however, from the physician perspective, dyspnea is only 1 data point, and providers rely on other measures, such as oxygen saturation, heart rate, respiratory rate, evidence of increasing breathing effort, and arterial blood gas to drive decision making. In a recent study that evaluated the attitudes and beliefs of hospitalists regarding the assessment and management of dyspnea, we found that most hospitalists indicated that awareness of dyspnea severity influences their decision for treatment, diagnostic testing, and timing of the discharge. Moreover, whereas less than half of the respondents reported experience with standardized assessment of dyspnea severity, most stated that such data would be very useful in their practice.[22]

What is the clinical significance of having discordance between patients self‐assessment and providers impression of the patient's severity of dyspnea? First, inaccurate assessment of dyspnea by providers can lead to inadequate treatment and workup. For example, a physician who underestimates the severity of dyspnea may fail to recognize when a complication of the underlying disease develops or may underutilize symptomatic methods for relief of dyspnea. In contrast, a physician who overestimates dyspnea may continue with aggressive treatment when this is not necessary. Second, lack of awareness of dyspnea severity experienced by the patient may result in premature discharge and patient's frustration with the provider, as was shown in several studies evaluating physician‐patient agreement for pain perception.[21, 23] We found that discrepancy between patients and healthcare providers was more pronounced for patients with COPD. In another study using the same patient cohort, we reported that compared to patients with congestive heart failure, those with COPD had more residual dyspnea at discharge; 1 in 4 patients was discharged with a dyspnea score of 5 of greater, and almost half reported symptoms above their baseline.[24] The results from the current study may explain in part why patients with COPD are discharged with higher levels of dyspnea and should alert healthcare providers on the importance of patient‐reported breathlessness. Third, the high level of discordance between healthcare providers and patients may explain the undertreatment of dyspnea in patients with advanced disease. This is supported by our findings that the discordance between patients and physicians was higher if the patient was discharged on oxygen.

One key role of the provider during a clinical encounter is to elicit the patient's symptoms and achieve a shared understanding of what the patient is experiencing. From the patient's perspective, their self‐assessment of dyspnea is more important that the physician's assessment. Fortunately, there is a growing recognition and emphasis on using outcomes that matter to patients, such as dyspnea, to inform judgment about patient care and for clinical research. Numerical measures for assessment of dyspnea exist, are easy to use, and are sensitive to change in patients' dyspnea.[6, 25, 26, 27] Still, it is not standard practice for healthcare providers to ask patients to provide a rating of their dyspnea. When we examined the documentation of dyspnea in the medical record, we found that the description was vague, and providers did not use a standardized validated assessment. Although the dyspnea score decreased during hospitalization, the respiratory rate did not significantly change, indicating that this objective measure may not be reliable in patient assessment. The providers' knowledge of the intensity of the symptom expressed by patients will enable them to track improvement in symptoms over time or in response to therapy. In addition, in this era of multiple handoffs within a hospitalization or from primary care to the hospital, a more uniform assessment could allow providers to follow the severity and time course of dyspnea. The low level of agreement we found between patients and the providers lends support to recommendations regarding a structured dyspnea assessment into routine hospital practice.

CONCLUSION

We found that the extent of agreement between a structured patient self‐assessment of dyspnea and healthcare providers' assessment was low. Future studies should prospectively test whether routine assessment of dyspnea results in better acute and long‐term patient outcomes.

Breathlessness, or dyspnea, is defined as a subjective experience of breathing discomfort that is comprised of qualitatively distinct sensations that vary in intensity.[1] Dyspnea is a leading reason for patients presenting for emergency care,[2] and it is an important predictor for hospitalization and mortality in patients with cardiopulmonary disease.[3, 4, 5]

Several professional societies' guidelines recommend that patients should be asked to quantify the intensity of their breathlessness using a standardized scale, and that these ratings should be documented in medical records to guide dyspnea awareness and management.[1, 6, 7] During the evaluation and treatment of patients with acute cardiopulmonary conditions, the clinician estimates the severity of the illness and response to therapy based on multiple objective measures as well as the patient's perception of dyspnea. A patient‐centered care approach depends upon the physicians having a shared understanding of what the patient is experiencing. Without this appreciation, the healthcare provider cannot make appropriate treatment decisions to ensure alleviation of presenting symptoms. Understanding the severity of patients' dyspnea is critical to avoid under‐ or overtreatment of patients with acute cardiopulmonary conditions, but only a few studies have compared patient and provider perceptions of dyspnea intensity.[8, 9] Discordance between physician's impression of severity of dyspnea and patient's perception may result in suboptimal management and patient dissatisfaction with care. Furthermore, several studies have shown that, when physicians and patients agree with the assessment of well‐being, treatment adherence and outcomes improve.[10, 11]

Therefore, we evaluated the extent and directionality of agreement between patients' perception and healthcare providers' impression of dyspnea and explored which factors contribute to discordance. Additionally, we examined how healthcare providers document dyspnea severity.

METHODS

RESULTS

Patient Characteristics

Among the 219 patients who met the screening criteria, 81 were not enrolled (Figure 1). Data from 138 patients, with both patient information and provider data on dyspnea assessment, were included. The median age of the patients was 72 years (IQR, 5880 years), 56.5% were women, 75.4% were white, and 28.3% were current smokers. Approximately 30% had a diagnosis of HF, 30% of COPD, and 13.0% of pneumonia. The median comorbidity score was 4 (IQR, 26), and 37.0% of the patients had a BMI 30. At admission, the median oxygen saturation index was 346 (IQR, 287.5460) indicating mild to moderate levels of hypoxia. (Table 1).

Table 1.Patient Characteristics (N = 138)

	Value
NOTE: Abbreviations: BMI, body mass index; COPD, chronic obstructive pulmonary disease; IQR, interquartile range; NRS, numerical rating scale.
Age, median (IQR), y	72 (5880)
Gender
Female	78 (56.5)
Male	60 (43.5)
Race
White	104 (75.4)
Black	16 (11.6)
Hispanic	17 (12.3)
Other	1 (0.7)
Body mass index, median (IQR)	28 (23.334.6)
Obese (BMI 30)	51 (37.0)
Smoker, current	39 (28.3)
Admitting diagnosis
Heart failure	46 (33.3)
COPD/asthma	41 (29.7)
Pneumonia	18 (13.0)
Other	33 (23.9)
Depression	32 (23.2)
Comorbidity score, median (IQR)	4 (26)
Respiratory rate at admission, median (IQR)	20 (1924)
Oxygen saturation index at admission, median (IQR)	346.4 (287.5460)
Patient NRS, median (IQR)
At admission	9 (710)
At discharge	2 (14)
Discharged on home oxygen	45 (32.6)
Respiratory rate at discharge, median (IQR)	20 (1820)
Oxygen saturation index at discharge, median (IQR)	475 (350485)

Figure 1

Agreement Between Patients' Self‐Assessment and Providers' Assessment of Dyspnea Severity

Not all patients had complete data points, and more nurses were interviewed than physicians. Overall, 96 patient‐physician and 138 patient‐nurse pairs participated in the study. A total of 336 patient‐nurse rating dyad assessments of dyspnea and 124 patient‐physician rating dyads assessments were collected (Figure 1). The mean difference between patient and physicians and patient and nurses assessments of dyspnea was 1.23 (IQR, 3 to 0) and 0.21 (IQR, 2 to 2) respectively (a negative score means underestimation by the provider, a positive score means overestimation).

The unadjusted agreement on the severity of dyspnea was 36.3% for the patient‐physician dyads and 44.1% for the patient‐nurse dyads. Physicians underestimated their patients' dyspnea 37.9% of the time and overestimated it 25.8% of the time; nurses underestimated it 43.5% of the time and overestimated it in 12.4% of the study patients (Table 2). In 28.2% of the time, physicians were discordant more than 4 points of the patient assessment. Bland‐Altman plots show that there is greater variation in differences of dyspnea assessments with increase in shortness of breath scores (Figure 2). Nurses underestimated more when the dyspnea score was on the lower end. Physicians also tended to estimate either lower or higher when compared to patients when the dyspnea scores were <2 (Figure 2A,B).

Table 2.Underestimation and Overestimation and Concordance of Dyspnea

	Underestimation			Concordance			Overestimation
	3	2	%*	0	1	%	2	3	%
NOTE: NRS scores by nurses and physicians as compared with patients *Percent underestimation out of all dyads. Percent concordance out of all dyads. Percent overestimation out of all dyads.
Patient‐nurse dyads	110	48	43.5	82	78	44.1	17	28	12.4
Patient‐physician dyads	33	14	37.9	21	24	36.3	12	20	25.8

Figure 2

The weighted kappa coefficient for agreement was 0.11 (95% confidence interval [CI]: 0.01 to 0.21) for patient‐physician assessment, 0.18 (95% CI: 0.12 to 0.24) for patient‐nurse, and 0.09 (0.02 to 0.20) for physician‐nurse indicating poor agreement. In a sensitivity analysis in which we used a higher threshold for defining discordance (difference of more than 2 points), the kappa coefficient increased to 0.21 (95% CI: 0.06 to 0.36) for patient‐physician assessments, to 0.24 (95% CI: 0.15 to 0.33) for patient‐nurse, and to 0.24 (95% CI: 0.09 to 0.39) for nurse‐physician assessments.

DISCUSSION

In this prospective study of 138 patients hospitalized with cardiopulmonary disease, we found that the agreement between patient's experience of dyspnea and providers' assessment was poor, and the discordance was higher for physicians than for nurses. In more than half of the cases, differences between patient and healthcare providers' assessment of dyspnea were present. One‐third of the time, both physicians and nurses underestimated patients' reported levels of dyspnea. Admitting diagnosis was the only patient factor predicting lack of agreement, and patients with COPD were more likely to have their dyspnea underestimated by nurses. Healthcare providers predominantly documented the presence or absence of dyspnea and rarely used a more nuanced scale.

Discrepancies between patient and provider assessments for pain, depression, and overall health have been reported.[8, 18, 19, 20, 21] One explanation is that patients and healthcare providers measure different factors despite using the same terminology. Furthermore, patient's assessment may be confounded by other symptoms such as anxiety, fatigue, or pain. Physicians and nurses may underevaluate and underestimate the level of breathlessness; however, from the physician perspective, dyspnea is only 1 data point, and providers rely on other measures, such as oxygen saturation, heart rate, respiratory rate, evidence of increasing breathing effort, and arterial blood gas to drive decision making. In a recent study that evaluated the attitudes and beliefs of hospitalists regarding the assessment and management of dyspnea, we found that most hospitalists indicated that awareness of dyspnea severity influences their decision for treatment, diagnostic testing, and timing of the discharge. Moreover, whereas less than half of the respondents reported experience with standardized assessment of dyspnea severity, most stated that such data would be very useful in their practice.[22]

What is the clinical significance of having discordance between patients self‐assessment and providers impression of the patient's severity of dyspnea? First, inaccurate assessment of dyspnea by providers can lead to inadequate treatment and workup. For example, a physician who underestimates the severity of dyspnea may fail to recognize when a complication of the underlying disease develops or may underutilize symptomatic methods for relief of dyspnea. In contrast, a physician who overestimates dyspnea may continue with aggressive treatment when this is not necessary. Second, lack of awareness of dyspnea severity experienced by the patient may result in premature discharge and patient's frustration with the provider, as was shown in several studies evaluating physician‐patient agreement for pain perception.[21, 23] We found that discrepancy between patients and healthcare providers was more pronounced for patients with COPD. In another study using the same patient cohort, we reported that compared to patients with congestive heart failure, those with COPD had more residual dyspnea at discharge; 1 in 4 patients was discharged with a dyspnea score of 5 of greater, and almost half reported symptoms above their baseline.[24] The results from the current study may explain in part why patients with COPD are discharged with higher levels of dyspnea and should alert healthcare providers on the importance of patient‐reported breathlessness. Third, the high level of discordance between healthcare providers and patients may explain the undertreatment of dyspnea in patients with advanced disease. This is supported by our findings that the discordance between patients and physicians was higher if the patient was discharged on oxygen.

One key role of the provider during a clinical encounter is to elicit the patient's symptoms and achieve a shared understanding of what the patient is experiencing. From the patient's perspective, their self‐assessment of dyspnea is more important that the physician's assessment. Fortunately, there is a growing recognition and emphasis on using outcomes that matter to patients, such as dyspnea, to inform judgment about patient care and for clinical research. Numerical measures for assessment of dyspnea exist, are easy to use, and are sensitive to change in patients' dyspnea.[6, 25, 26, 27] Still, it is not standard practice for healthcare providers to ask patients to provide a rating of their dyspnea. When we examined the documentation of dyspnea in the medical record, we found that the description was vague, and providers did not use a standardized validated assessment. Although the dyspnea score decreased during hospitalization, the respiratory rate did not significantly change, indicating that this objective measure may not be reliable in patient assessment. The providers' knowledge of the intensity of the symptom expressed by patients will enable them to track improvement in symptoms over time or in response to therapy. In addition, in this era of multiple handoffs within a hospitalization or from primary care to the hospital, a more uniform assessment could allow providers to follow the severity and time course of dyspnea. The low level of agreement we found between patients and the providers lends support to recommendations regarding a structured dyspnea assessment into routine hospital practice.

CONCLUSION

We found that the extent of agreement between a structured patient self‐assessment of dyspnea and healthcare providers' assessment was low. Future studies should prospectively test whether routine assessment of dyspnea results in better acute and long‐term patient outcomes.

Breathlessness, or dyspnea, is defined as a subjective experience of breathing discomfort that is comprised of qualitatively distinct sensations that vary in intensity.[1] Dyspnea is a leading reason for patients presenting for emergency care,[2] and it is an important predictor for hospitalization and mortality in patients with cardiopulmonary disease.[3, 4, 5]

Several professional societies' guidelines recommend that patients should be asked to quantify the intensity of their breathlessness using a standardized scale, and that these ratings should be documented in medical records to guide dyspnea awareness and management.[1, 6, 7] During the evaluation and treatment of patients with acute cardiopulmonary conditions, the clinician estimates the severity of the illness and response to therapy based on multiple objective measures as well as the patient's perception of dyspnea. A patient‐centered care approach depends upon the physicians having a shared understanding of what the patient is experiencing. Without this appreciation, the healthcare provider cannot make appropriate treatment decisions to ensure alleviation of presenting symptoms. Understanding the severity of patients' dyspnea is critical to avoid under‐ or overtreatment of patients with acute cardiopulmonary conditions, but only a few studies have compared patient and provider perceptions of dyspnea intensity.[8, 9] Discordance between physician's impression of severity of dyspnea and patient's perception may result in suboptimal management and patient dissatisfaction with care. Furthermore, several studies have shown that, when physicians and patients agree with the assessment of well‐being, treatment adherence and outcomes improve.[10, 11]

Therefore, we evaluated the extent and directionality of agreement between patients' perception and healthcare providers' impression of dyspnea and explored which factors contribute to discordance. Additionally, we examined how healthcare providers document dyspnea severity.

METHODS

RESULTS

Patient Characteristics

Among the 219 patients who met the screening criteria, 81 were not enrolled (Figure 1). Data from 138 patients, with both patient information and provider data on dyspnea assessment, were included. The median age of the patients was 72 years (IQR, 5880 years), 56.5% were women, 75.4% were white, and 28.3% were current smokers. Approximately 30% had a diagnosis of HF, 30% of COPD, and 13.0% of pneumonia. The median comorbidity score was 4 (IQR, 26), and 37.0% of the patients had a BMI 30. At admission, the median oxygen saturation index was 346 (IQR, 287.5460) indicating mild to moderate levels of hypoxia. (Table 1).

Table 1.Patient Characteristics (N = 138)

	Value
NOTE: Abbreviations: BMI, body mass index; COPD, chronic obstructive pulmonary disease; IQR, interquartile range; NRS, numerical rating scale.
Age, median (IQR), y	72 (5880)
Gender
Female	78 (56.5)
Male	60 (43.5)
Race
White	104 (75.4)
Black	16 (11.6)
Hispanic	17 (12.3)
Other	1 (0.7)
Body mass index, median (IQR)	28 (23.334.6)
Obese (BMI 30)	51 (37.0)
Smoker, current	39 (28.3)
Admitting diagnosis
Heart failure	46 (33.3)
COPD/asthma	41 (29.7)
Pneumonia	18 (13.0)
Other	33 (23.9)
Depression	32 (23.2)
Comorbidity score, median (IQR)	4 (26)
Respiratory rate at admission, median (IQR)	20 (1924)
Oxygen saturation index at admission, median (IQR)	346.4 (287.5460)
Patient NRS, median (IQR)
At admission	9 (710)
At discharge	2 (14)
Discharged on home oxygen	45 (32.6)
Respiratory rate at discharge, median (IQR)	20 (1820)
Oxygen saturation index at discharge, median (IQR)	475 (350485)

Figure 1

Agreement Between Patients' Self‐Assessment and Providers' Assessment of Dyspnea Severity

Not all patients had complete data points, and more nurses were interviewed than physicians. Overall, 96 patient‐physician and 138 patient‐nurse pairs participated in the study. A total of 336 patient‐nurse rating dyad assessments of dyspnea and 124 patient‐physician rating dyads assessments were collected (Figure 1). The mean difference between patient and physicians and patient and nurses assessments of dyspnea was 1.23 (IQR, 3 to 0) and 0.21 (IQR, 2 to 2) respectively (a negative score means underestimation by the provider, a positive score means overestimation).

The unadjusted agreement on the severity of dyspnea was 36.3% for the patient‐physician dyads and 44.1% for the patient‐nurse dyads. Physicians underestimated their patients' dyspnea 37.9% of the time and overestimated it 25.8% of the time; nurses underestimated it 43.5% of the time and overestimated it in 12.4% of the study patients (Table 2). In 28.2% of the time, physicians were discordant more than 4 points of the patient assessment. Bland‐Altman plots show that there is greater variation in differences of dyspnea assessments with increase in shortness of breath scores (Figure 2). Nurses underestimated more when the dyspnea score was on the lower end. Physicians also tended to estimate either lower or higher when compared to patients when the dyspnea scores were <2 (Figure 2A,B).

Table 2.Underestimation and Overestimation and Concordance of Dyspnea

	Underestimation			Concordance			Overestimation
	3	2	%*	0	1	%	2	3	%
NOTE: NRS scores by nurses and physicians as compared with patients *Percent underestimation out of all dyads. Percent concordance out of all dyads. Percent overestimation out of all dyads.
Patient‐nurse dyads	110	48	43.5	82	78	44.1	17	28	12.4
Patient‐physician dyads	33	14	37.9	21	24	36.3	12	20	25.8

Figure 2

The weighted kappa coefficient for agreement was 0.11 (95% confidence interval [CI]: 0.01 to 0.21) for patient‐physician assessment, 0.18 (95% CI: 0.12 to 0.24) for patient‐nurse, and 0.09 (0.02 to 0.20) for physician‐nurse indicating poor agreement. In a sensitivity analysis in which we used a higher threshold for defining discordance (difference of more than 2 points), the kappa coefficient increased to 0.21 (95% CI: 0.06 to 0.36) for patient‐physician assessments, to 0.24 (95% CI: 0.15 to 0.33) for patient‐nurse, and to 0.24 (95% CI: 0.09 to 0.39) for nurse‐physician assessments.

DISCUSSION

In this prospective study of 138 patients hospitalized with cardiopulmonary disease, we found that the agreement between patient's experience of dyspnea and providers' assessment was poor, and the discordance was higher for physicians than for nurses. In more than half of the cases, differences between patient and healthcare providers' assessment of dyspnea were present. One‐third of the time, both physicians and nurses underestimated patients' reported levels of dyspnea. Admitting diagnosis was the only patient factor predicting lack of agreement, and patients with COPD were more likely to have their dyspnea underestimated by nurses. Healthcare providers predominantly documented the presence or absence of dyspnea and rarely used a more nuanced scale.

Discrepancies between patient and provider assessments for pain, depression, and overall health have been reported.[8, 18, 19, 20, 21] One explanation is that patients and healthcare providers measure different factors despite using the same terminology. Furthermore, patient's assessment may be confounded by other symptoms such as anxiety, fatigue, or pain. Physicians and nurses may underevaluate and underestimate the level of breathlessness; however, from the physician perspective, dyspnea is only 1 data point, and providers rely on other measures, such as oxygen saturation, heart rate, respiratory rate, evidence of increasing breathing effort, and arterial blood gas to drive decision making. In a recent study that evaluated the attitudes and beliefs of hospitalists regarding the assessment and management of dyspnea, we found that most hospitalists indicated that awareness of dyspnea severity influences their decision for treatment, diagnostic testing, and timing of the discharge. Moreover, whereas less than half of the respondents reported experience with standardized assessment of dyspnea severity, most stated that such data would be very useful in their practice.[22]

What is the clinical significance of having discordance between patients self‐assessment and providers impression of the patient's severity of dyspnea? First, inaccurate assessment of dyspnea by providers can lead to inadequate treatment and workup. For example, a physician who underestimates the severity of dyspnea may fail to recognize when a complication of the underlying disease develops or may underutilize symptomatic methods for relief of dyspnea. In contrast, a physician who overestimates dyspnea may continue with aggressive treatment when this is not necessary. Second, lack of awareness of dyspnea severity experienced by the patient may result in premature discharge and patient's frustration with the provider, as was shown in several studies evaluating physician‐patient agreement for pain perception.[21, 23] We found that discrepancy between patients and healthcare providers was more pronounced for patients with COPD. In another study using the same patient cohort, we reported that compared to patients with congestive heart failure, those with COPD had more residual dyspnea at discharge; 1 in 4 patients was discharged with a dyspnea score of 5 of greater, and almost half reported symptoms above their baseline.[24] The results from the current study may explain in part why patients with COPD are discharged with higher levels of dyspnea and should alert healthcare providers on the importance of patient‐reported breathlessness. Third, the high level of discordance between healthcare providers and patients may explain the undertreatment of dyspnea in patients with advanced disease. This is supported by our findings that the discordance between patients and physicians was higher if the patient was discharged on oxygen.

One key role of the provider during a clinical encounter is to elicit the patient's symptoms and achieve a shared understanding of what the patient is experiencing. From the patient's perspective, their self‐assessment of dyspnea is more important that the physician's assessment. Fortunately, there is a growing recognition and emphasis on using outcomes that matter to patients, such as dyspnea, to inform judgment about patient care and for clinical research. Numerical measures for assessment of dyspnea exist, are easy to use, and are sensitive to change in patients' dyspnea.[6, 25, 26, 27] Still, it is not standard practice for healthcare providers to ask patients to provide a rating of their dyspnea. When we examined the documentation of dyspnea in the medical record, we found that the description was vague, and providers did not use a standardized validated assessment. Although the dyspnea score decreased during hospitalization, the respiratory rate did not significantly change, indicating that this objective measure may not be reliable in patient assessment. The providers' knowledge of the intensity of the symptom expressed by patients will enable them to track improvement in symptoms over time or in response to therapy. In addition, in this era of multiple handoffs within a hospitalization or from primary care to the hospital, a more uniform assessment could allow providers to follow the severity and time course of dyspnea. The low level of agreement we found between patients and the providers lends support to recommendations regarding a structured dyspnea assessment into routine hospital practice.

CONCLUSION

We found that the extent of agreement between a structured patient self‐assessment of dyspnea and healthcare providers' assessment was low. Future studies should prospectively test whether routine assessment of dyspnea results in better acute and long‐term patient outcomes.

Pneumonia is the most common cause of unplanned hospitalization in the United States.[1] Despite its clinical toll, the management of this disease has evolved markedly. Expanding vaccination programs, efforts to improve timeliness of antibiotic therapy, and improved processes of care are but a few developments that have improved outcomes for patients afflicted with this illness.[2, 3]

Use of peripherally inserted central catheters (PICCs) is an example of a modern development in the management of patients with pneumonia.[4, 5, 6, 7] PICCs provide many of the benefits associated with central venous catheters (CVCs) including reliable venous access for delivery of antibiotics, phlebotomy, and invasive hemodynamic monitoring. However, as they are placed in veins of the upper extremity, PICCs bypass insertion risks (eg, injury to the carotid vessels or pneumothorax) associated with placement of traditional CVCs.[8] Because they offer durable venous access, PICCs also facilitate care transitions while continuing intravenous antimicrobial therapy in patients with pneumonia.

However, accumulating evidence also suggests that PICCs are associated with important complications, including central lineassociated bloodstream infectionand venous thromboembolism.[9, 10] Furthermore, knowledge gaps in clinicians regarding indications for appropriate use and management of complications associated with PICCs have been recognized.[10, 11] These elements are problematic because reports of unjustified and inappropriate PICC use are growing in the literature.[12, 13] Such concerns have prompted a number of policy calls to improve PICC use, including Choosing Wisely recommendations by various professional societies.[14, 15]

As little is known about the prevalence or patterns of PICC use in adults hospitalized with pneumonia, we conducted a retrospective cohort study using data from a large network of US hospitals.

METHODS

RESULTS

Between July 2007 and November 2011, 634,285 admissions representing 545,250 unique patients from 495 hospitals met eligibility criteria and were included in the study (Figure 1). Included patients had a median age of 71 years (interquartile range [IQR]: 5782), and 53.0% were female. Most patients were Caucasian (69.2%), unmarried (51.6%), and insured by Medicare (67.9%). Patients were admitted to the hospital by internal medicine providers (43.4%), hospitalists (21.4%), and family practice providers (14.7%); notably, critical care and pulmonary medicine providers admitted 6.5% of patients. The median Gagne comorbidity score was 2 (IQR: 15). Hypertension, chronic obstructive pulmonary disease, diabetes, and congestive heart failure were among the most common comorbidities observed (Table 1).

Figure 1

Among eligible patients, 41,849 (7.7%) received a PICC during hospitalization. Approximately a quarter of all patients who received PICCs did so by hospital day 2; 90% underwent insertion by hospital day 11 (mean = 5.4 days, median = 4 days). Patients who received PICCs were younger (median IQR: 69 years, 5780 years) but otherwise demographically similar to those that did not receive PICCs (median IQR: 72 years, 5782 years). Compared to other specialties, patients admitted by critical care/pulmonary providers were twice as likely to receive PICCs (12.3% vs 6.1%, P < .001). Patients who received PICCs had higher comorbidity scores than those who did not (median Gagne comorbidity score 4 vs 2, P < 0.001) and were more likely to be diagnosed with HCAP (43.1% vs 29.9%, P < 0.001) than CAP (56.9% vs 70.1%, P < 0.001).

PICC recipients were also more likely to receive intensive care unit (ICU) level of care (41.4% vs 16%, P < 0.001) and both noninvasive (17.5% vs 8.1%, P < 0.001) and invasive ventilation (28.6% vs 8.8%, P < 0.001) upon admission. Vasopressor use was also significantly more frequent in patients who received PICCs (24.7% vs 7.6%, P < 0.001) compared to those who did not receive these devices. Patients with PICCs were more often discharged to skilled nursing facilities (34.5% vs 19.3%) than those without PICCs.