Predictors of Hospital Re-admission and Surgical Site Infection in the United States, Denmark and Japan

Is Risk Stratification a Universal Language?

Steven Glassman, Leah Y. Carreon, Mikkel Andersen, Anthony Asher, Soren Eiskjær, Martin Gehrchen, Shiro Imagama, Ken Ishii, Takahashi Kaito, Yukihiro Matsuyama, Hiroshi Moridaira, Praveen Mummaneni, Christopher Shaffrey, Morio Matsumoto

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

STUDY DESIGN.: Retrospective review of three spine surgery databases. OBJECTIVES.: The purpose of this study is to determine if predictors of hospital readmission and Surgical Site Infection (SSI) after lumbar fusion will be the same in US, Denmark and Japan. SUMMARY OF BACKGROUND DATA.: As clinical decision-making becomes more data driven, risk stratification will be crucial to minimize complications. Spine surgeons world-wide face this issue, leading to parallel efforts to address risk stratification. This raises the question as to whether pooled data would be valuable and whether models generated in one country would be applicable to other populations. METHODS.: Predictors of SSI and 30-day readmission from 3 prospective databases (N2QOD N?=?2653, DaneSpine N?=?1993, JAMSD N?=?3798) were determined and compared to identify common or divergent predictive risks. RESULTS.: Predictive variables differed in the 3 databases, for both readmission and SSI. Factors predictive for hospital readmission were ASA grade in N2QOD, (p?=?0.013, OR 2.08), fusion levels in DaneSpine (p?=?0.005, OR 1.67) and gender in JAMSD (p?=?0.001, OR?=?2.81). Associated differences in demographics and procedural factors included mean ASA grade (N2QOD?=?2.45, JAMSD?=?1.72) and fusion levels (N2QOD?=?1.39, DaneSpine?=?1.52, JAMSD?=?1.34). For SSI, gender (p?=?0.000, OR?=?3.30), diabetes (p?=?0.000, OR?=?2.90) and Length of Stay (p?=?0.000, OR?=?1.02) were predictive in JAMSD. No predictors were identified in N2QOD or DaneSpine. CONCLUSIONS.: Predictors of SSI and hospital readmission differ in the US, Denmark and Japan, suggesting that risk stratification models may need to be population specific or adjusted. Some differences in measured parameters exist in the 3 databases analyzed, however, patient and procedure selection also appear to differ and may limit the ability to directly pool data from different regions. Therefore, risk stratification models developed in one country may not be directly applicable to other countries.Level of Evidence: 2

Original languageEnglish
JournalSpine
DOIs
Publication statusAccepted/In press - 2017 Jan 31

Fingerprint

Surgical Wound Infection
Denmark
Japan
Language
Patient Readmission
Databases
Spine
Patient Selection
Population
Length of Stay
Demography

ASJC Scopus subject areas

  • Orthopedics and Sports Medicine
  • Clinical Neurology

Cite this

Predictors of Hospital Re-admission and Surgical Site Infection in the United States, Denmark and Japan : Is Risk Stratification a Universal Language? / Glassman, Steven; Carreon, Leah Y.; Andersen, Mikkel; Asher, Anthony; Eiskjær, Soren; Gehrchen, Martin; Imagama, Shiro; Ishii, Ken; Kaito, Takahashi; Matsuyama, Yukihiro; Moridaira, Hiroshi; Mummaneni, Praveen; Shaffrey, Christopher; Matsumoto, Morio.

In: Spine, 31.01.2017.

Research output: Contribution to journalArticle

Glassman, S, Carreon, LY, Andersen, M, Asher, A, Eiskjær, S, Gehrchen, M, Imagama, S, Ishii, K, Kaito, T, Matsuyama, Y, Moridaira, H, Mummaneni, P, Shaffrey, C & Matsumoto, M 2017, 'Predictors of Hospital Re-admission and Surgical Site Infection in the United States, Denmark and Japan: Is Risk Stratification a Universal Language?', Spine. https://doi.org/10.1097/BRS.0000000000002082
Glassman, Steven ; Carreon, Leah Y. ; Andersen, Mikkel ; Asher, Anthony ; Eiskjær, Soren ; Gehrchen, Martin ; Imagama, Shiro ; Ishii, Ken ; Kaito, Takahashi ; Matsuyama, Yukihiro ; Moridaira, Hiroshi ; Mummaneni, Praveen ; Shaffrey, Christopher ; Matsumoto, Morio. / Predictors of Hospital Re-admission and Surgical Site Infection in the United States, Denmark and Japan : Is Risk Stratification a Universal Language?. In: Spine. 2017.
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title = "Predictors of Hospital Re-admission and Surgical Site Infection in the United States, Denmark and Japan: Is Risk Stratification a Universal Language?",
abstract = "STUDY DESIGN.: Retrospective review of three spine surgery databases. OBJECTIVES.: The purpose of this study is to determine if predictors of hospital readmission and Surgical Site Infection (SSI) after lumbar fusion will be the same in US, Denmark and Japan. SUMMARY OF BACKGROUND DATA.: As clinical decision-making becomes more data driven, risk stratification will be crucial to minimize complications. Spine surgeons world-wide face this issue, leading to parallel efforts to address risk stratification. This raises the question as to whether pooled data would be valuable and whether models generated in one country would be applicable to other populations. METHODS.: Predictors of SSI and 30-day readmission from 3 prospective databases (N2QOD N?=?2653, DaneSpine N?=?1993, JAMSD N?=?3798) were determined and compared to identify common or divergent predictive risks. RESULTS.: Predictive variables differed in the 3 databases, for both readmission and SSI. Factors predictive for hospital readmission were ASA grade in N2QOD, (p?=?0.013, OR 2.08), fusion levels in DaneSpine (p?=?0.005, OR 1.67) and gender in JAMSD (p?=?0.001, OR?=?2.81). Associated differences in demographics and procedural factors included mean ASA grade (N2QOD?=?2.45, JAMSD?=?1.72) and fusion levels (N2QOD?=?1.39, DaneSpine?=?1.52, JAMSD?=?1.34). For SSI, gender (p?=?0.000, OR?=?3.30), diabetes (p?=?0.000, OR?=?2.90) and Length of Stay (p?=?0.000, OR?=?1.02) were predictive in JAMSD. No predictors were identified in N2QOD or DaneSpine. CONCLUSIONS.: Predictors of SSI and hospital readmission differ in the US, Denmark and Japan, suggesting that risk stratification models may need to be population specific or adjusted. Some differences in measured parameters exist in the 3 databases analyzed, however, patient and procedure selection also appear to differ and may limit the ability to directly pool data from different regions. Therefore, risk stratification models developed in one country may not be directly applicable to other countries.Level of Evidence: 2",
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T1 - Predictors of Hospital Re-admission and Surgical Site Infection in the United States, Denmark and Japan

T2 - Is Risk Stratification a Universal Language?

AU - Glassman, Steven

AU - Carreon, Leah Y.

AU - Andersen, Mikkel

AU - Asher, Anthony

AU - Eiskjær, Soren

AU - Gehrchen, Martin

AU - Imagama, Shiro

AU - Ishii, Ken

AU - Kaito, Takahashi

AU - Matsuyama, Yukihiro

AU - Moridaira, Hiroshi

AU - Mummaneni, Praveen

AU - Shaffrey, Christopher

AU - Matsumoto, Morio

PY - 2017/1/31

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N2 - STUDY DESIGN.: Retrospective review of three spine surgery databases. OBJECTIVES.: The purpose of this study is to determine if predictors of hospital readmission and Surgical Site Infection (SSI) after lumbar fusion will be the same in US, Denmark and Japan. SUMMARY OF BACKGROUND DATA.: As clinical decision-making becomes more data driven, risk stratification will be crucial to minimize complications. Spine surgeons world-wide face this issue, leading to parallel efforts to address risk stratification. This raises the question as to whether pooled data would be valuable and whether models generated in one country would be applicable to other populations. METHODS.: Predictors of SSI and 30-day readmission from 3 prospective databases (N2QOD N?=?2653, DaneSpine N?=?1993, JAMSD N?=?3798) were determined and compared to identify common or divergent predictive risks. RESULTS.: Predictive variables differed in the 3 databases, for both readmission and SSI. Factors predictive for hospital readmission were ASA grade in N2QOD, (p?=?0.013, OR 2.08), fusion levels in DaneSpine (p?=?0.005, OR 1.67) and gender in JAMSD (p?=?0.001, OR?=?2.81). Associated differences in demographics and procedural factors included mean ASA grade (N2QOD?=?2.45, JAMSD?=?1.72) and fusion levels (N2QOD?=?1.39, DaneSpine?=?1.52, JAMSD?=?1.34). For SSI, gender (p?=?0.000, OR?=?3.30), diabetes (p?=?0.000, OR?=?2.90) and Length of Stay (p?=?0.000, OR?=?1.02) were predictive in JAMSD. No predictors were identified in N2QOD or DaneSpine. CONCLUSIONS.: Predictors of SSI and hospital readmission differ in the US, Denmark and Japan, suggesting that risk stratification models may need to be population specific or adjusted. Some differences in measured parameters exist in the 3 databases analyzed, however, patient and procedure selection also appear to differ and may limit the ability to directly pool data from different regions. Therefore, risk stratification models developed in one country may not be directly applicable to other countries.Level of Evidence: 2

AB - STUDY DESIGN.: Retrospective review of three spine surgery databases. OBJECTIVES.: The purpose of this study is to determine if predictors of hospital readmission and Surgical Site Infection (SSI) after lumbar fusion will be the same in US, Denmark and Japan. SUMMARY OF BACKGROUND DATA.: As clinical decision-making becomes more data driven, risk stratification will be crucial to minimize complications. Spine surgeons world-wide face this issue, leading to parallel efforts to address risk stratification. This raises the question as to whether pooled data would be valuable and whether models generated in one country would be applicable to other populations. METHODS.: Predictors of SSI and 30-day readmission from 3 prospective databases (N2QOD N?=?2653, DaneSpine N?=?1993, JAMSD N?=?3798) were determined and compared to identify common or divergent predictive risks. RESULTS.: Predictive variables differed in the 3 databases, for both readmission and SSI. Factors predictive for hospital readmission were ASA grade in N2QOD, (p?=?0.013, OR 2.08), fusion levels in DaneSpine (p?=?0.005, OR 1.67) and gender in JAMSD (p?=?0.001, OR?=?2.81). Associated differences in demographics and procedural factors included mean ASA grade (N2QOD?=?2.45, JAMSD?=?1.72) and fusion levels (N2QOD?=?1.39, DaneSpine?=?1.52, JAMSD?=?1.34). For SSI, gender (p?=?0.000, OR?=?3.30), diabetes (p?=?0.000, OR?=?2.90) and Length of Stay (p?=?0.000, OR?=?1.02) were predictive in JAMSD. No predictors were identified in N2QOD or DaneSpine. CONCLUSIONS.: Predictors of SSI and hospital readmission differ in the US, Denmark and Japan, suggesting that risk stratification models may need to be population specific or adjusted. Some differences in measured parameters exist in the 3 databases analyzed, however, patient and procedure selection also appear to differ and may limit the ability to directly pool data from different regions. Therefore, risk stratification models developed in one country may not be directly applicable to other countries.Level of Evidence: 2

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