Reviewer's report
Title:The Effect of Hospital Volume on Patient Outcomes in Severe Acute
Pancreatitis
Version: 3Date:29 May 2012
Reviewer: Gilaad Kaplan
Reviewer's report:
Overall, the manuscript is well written, draws from a good data source, makes
some important exclusions (e.g. readmissions), and utilizes appropriate statistical
analyses. The data source is particularly exceptional because the authors are
able to follow patients in the database. Most administrative databases are based
on discharge abstracts that cannot exclude readmissions to hospital, which
would clearly negatively influence any hospital-volume relationship. The key
message of the paper is that high volume hospitals lead to decreased mortality,
LOS, and charges for acute pancreatitis, which follows along a long line of
literature that supports excellence in high volume centers. While the impact of
hospital volume on health outcomes is not novel, the authors justify that the
novelty of their work by highlighting some methodologics issues that may have
led to inaccurate conclusions in prior studies.
I do have a few concerns to raise:
1. Hospital Volume was modeled as both a continuous variable (i.e. Table 2) and
as quartiles (i.e. Table 3). I am not convinced that modeling hospital volume as a
continuous variable is valuable. One case per hospital year most likely follows a
skewed rather than a linear relationship (e.g. a plateau at 3 cases per year is not
linear). Furthermore, the clinical meaningfulness of the effect of hospital volume
when increased by 1 case per year is not intuitive. In contrast, Table 3, which
uses quartiles, comprises the main findings of the paper. Clinically quartiles are
much more meaningful because a hospital can determine which quartile they fall
into. Consider dropping the continuous model and focus on the quartile analysis.
At minimum I would shift the focus to the quartile analysis. For example, quartile
numbers (rather than continuous) should be reported in the abstract.
2. I did not understand the following statement in the methods: " Patients were
allocated essentially in decentile except the two extremes due to the skewed
nature of the volume."
3. One interesting finding is that "treatment" related covariates attenuated the
effect of Hospital Volume - in fact, these factors may explain why hospital volume
is an important indicator for SAP outcomes. For example, high volume hospitals
likely have more advanced ICU that are critical in saving lives of pancretitis
patients. However, in Table 2 and 3, the other variables that may influence the
HV relationship are not provided - consider adding covariates to the Table.
4. I would be cautious in over subscribing to the finding that 3 cases per year has
the maximal effect given that it is well within the margin of error of other values of
cases per year (see Figure 3). At minimum, the authors should indicate in the
discussion that this value requires future validation.
5. Generalizability of findings relative to the underlying prevalence of causes of
acute pancreaitis. The hospital volume relationship may be more important for
bilary causes (e.g. expertise in ERCP) of pancreatitis as compared to alcoholic
causes. The prevalence of causes may be different in other regions in the world
and thus, the findings not completely generalizable.
6. The authors conclude that SAP with low volume (less than 3 cases per year)
should be transferred to a high volume center; however, the paper does not
demonstrate that transfer of SAP to high volume would improve outcomes, nor is
this policy necessarily cost-effective (e.g. maybe greater investment in ICU in a
low volume hospital would improve SAP as well as other outcomes in these
hospitals).
7. Table 1 could be enhanced with univariate statistics comparing each row.
8. Paper should be carefully proofread for grammar and flow.
Reviewer's report
Title:The Effect of Hospital Volume on Patient Outcomes in Severe Acute
Pancreatitis
Version: 3Date:29 May 2012
Reviewer: Gilaad Kaplan
Reviewer's report:
Overall, the manuscript is well written, draws from a good data source, makes
some important exclusions (e.g. readmissions), and utilizes appropriate statistical
analyses. The data source is particularly exceptional because the authors are
able to follow patients in the database. Most administrative databases are based
on discharge abstracts that cannot exclude readmissions to hospital, which
would clearly negatively influence any hospital-volume relationship. The key
message of the paper is that high volume hospitals lead to decreased mortality,
LOS, and charges for acute pancreatitis, which follows along a long line of
literature that supports excellence in high volume centers. While the impact of
hospital volume on health outcomes is not novel, the authors justify that the
novelty of their work by highlighting some methodologics issues that may have
led to inaccurate conclusions in prior studies.
I do have a few concerns to raise:
1. Hospital Volume was modeled as both a continuous variable (i.e. Table 2) and
as quartiles (i.e. Table 3). I am not convinced that modeling hospital volume as a
continuous variable is valuable. One case per hospital year most likely follows a
skewed rather than a linear relationship (e.g. a plateau at 3 cases per year is not
linear). Furthermore, the clinical meaningfulness of the effect of hospital volume
when increased by 1 case per year is not intuitive. In contrast, Table 3, which
uses quartiles, comprises the main findings of the paper. Clinically quartiles are
much more meaningful because a hospital can determine which quartile they fall
into. Consider dropping the continuous model and focus on the quartile analysis.
At minimum I would shift the focus to the quartile analysis. For example, quartile
numbers (rather than continuous) should be reported in the abstract.
2. I did not understand the following statement in the methods: " Patients were
allocated essentially in decentile except the two extremes due to the skewed
nature of the volume."
3. One interesting finding is that "treatment" related covariates attenuated the
effect of Hospital Volume - in fact, these factors may explain why hospital volume
is an important indicator for SAP outcomes. For example, high volume hospitals
likely have more advanced ICU that are critical in saving lives of pancretitis
patients. However, in Table 2 and 3, the other variables that may influence the
HV relationship are not provided - consider adding covariates to the Table.
4. I would be cautious in over subscribing to the finding that 3 cases per year has
the maximal effect given that it is well within the margin of error of other values of
cases per year (see Figure 3). At minimum, the authors should indicate in the
discussion that this value requires future validation.
5. Generalizability of findings relative to the underlying prevalence of causes of
acute pancreaitis. The hospital volume relationship may be more important for
bilary causes (e.g. expertise in ERCP) of pancreatitis as compared to alcoholic
causes. The prevalence of causes may be different in other regions in the world
and thus, the findings not completely generalizable.
6. The authors conclude that SAP with low volume (less than 3 cases per year)
should be transferred to a high volume center; however, the paper does not
demonstrate that transfer of SAP to high volume would improve outcomes, nor is
this policy necessarily cost-effective (e.g. maybe greater investment in ICU in a
low volume hospital would improve SAP as well as other outcomes in these
hospitals).
7. Table 1 could be enhanced with univariate statistics comparing each row.
8. Paper should be carefully proofread for grammar and flow.
Please review this paper.
user
Reviewer's report
Title:The Effect of Hospital Volume on Patient Outcomes in Severe Acute
Pancreatitis
Version: 3Date:29 May 2012
Reviewer: Gilaad Kaplan
Reviewer's report:
Overall, the manuscript is well written, draws from a good data source, makes
some important exclusions (e.g. readmissions), and utilizes appropriate statistical
analyses. The data source is particularly exceptional because the authors are
able to follow patients in the database. Most administrative databases are based
on discharge abstracts that cannot exclude readmissions to hospital, which
would clearly negatively influence any hospital-volume relationship. The key
message of the paper is that high volume hospitals lead to decreased mortality,
LOS, and charges for acute pancreatitis, which follows along a long line of
literature that supports excellence in high volume centers. While the impact of
hospital volume on health outcomes is not novel, the authors justify that the
novelty of their work by highlighting some methodologics issues that may have
led to inaccurate conclusions in prior studies.
I do have a few concerns to raise:
1. Hospital Volume was modeled as both a continuous variable (i.e. Table 2) and
as quartiles (i.e. Table 3). I am not convinced that modeling hospital volume as a
continuous variable is valuable. One case per hospital year most likely follows a
skewed rather than a linear relationship (e.g. a plateau at 3 cases per year is not
linear). Furthermore, the clinical meaningfulness of the effect of hospital volume
when increased by 1 case per year is not intuitive. In contrast, Table 3, which
uses quartiles, comprises the main findings of the paper. Clinically quartiles are
much more meaningful because a hospital can determine which quartile they fall
into. Consider dropping the continuous model and focus on the quartile analysis.
At minimum I would shift the focus to the quartile analysis. For example, quartile
numbers (rather than continuous) should be reported in the abstract.
2. I did not understand the following statement in the methods: " Patients were
allocated essentially in decentile except the two extremes due to the skewed
nature of the volume."
3. One interesting finding is that "treatment" related covariates attenuated the
effect of Hospital Volume - in fact, these factors may explain why hospital volume
is an important indicator for SAP outcomes. For example, high volume hospitals
likely have more advanced ICU that are critical in saving lives of pancretitis
patients. However, in Table 2 and 3, the other variables that may influence the
HV relationship are not provided - consider adding covariates to the Table.
4. I would be cautious in over subscribing to the finding that 3 cases per year has
the maximal effect given that it is well within the margin of error of other values of
cases per year (see Figure 3). At minimum, the authors should indicate in the
discussion that this value requires future validation.
5. Generalizability of findings relative to the underlying prevalence of causes of
acute pancreaitis. The hospital volume relationship may be more important for
bilary causes (e.g. expertise in ERCP) of pancreatitis as compared to alcoholic
causes. The prevalence of causes may be different in other regions in the world
and thus, the findings not completely generalizable.
6. The authors conclude that SAP with low volume (less than 3 cases per year)
should be transferred to a high volume center; however, the paper does not
demonstrate that transfer of SAP to high volume would improve outcomes, nor is
this policy necessarily cost-effective (e.g. maybe greater investment in ICU in a
low volume hospital would improve SAP as well as other outcomes in these
hospitals).
7. Table 1 could be enhanced with univariate statistics comparing each row.
8. Paper should be carefully proofread for grammar and flow.
assistant