Validation for using electronic health records to identify community acquired pneumonia hospitalization among people with and without HIV
Background Cohort studies identifying the incidence, complications and co-morbidities associated with community acquired pneumonia (CAP) are largely based on administrative datasets and rely on International Classification of Diseases (ICD) codes; however, the reliability of ICD codes for hospital a...
Ausführliche Beschreibung
Autor*in: |
Rodriguez-Barradas, Maria C. [verfasserIn] McGinnis, Kathleen A. [verfasserIn] Akgün, Kathleen [verfasserIn] Tate, Janet P. [verfasserIn] Brown, Sheldon T. [verfasserIn] Butt, Adeel A. [verfasserIn] Fine, Michael [verfasserIn] Goetz, Matthew Bidwell [verfasserIn] Graber, Christopher J. [verfasserIn] Huang, Laurence [verfasserIn] Rimland, David [verfasserIn] Justice, Amy [verfasserIn] Crothers, Kristina [verfasserIn] |
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Englisch |
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2020 |
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Übergeordnetes Werk: |
Enthalten in: Pneumonia - [London] : BioMed Central, 2012, 12(2020), 1 vom: 25. Juli |
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Übergeordnetes Werk: |
volume:12 ; year:2020 ; number:1 ; day:25 ; month:07 |
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DOI / URN: |
10.1186/s41479-020-00068-1 |
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Katalog-ID: |
SPR040447200 |
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520 | |a Background Cohort studies identifying the incidence, complications and co-morbidities associated with community acquired pneumonia (CAP) are largely based on administrative datasets and rely on International Classification of Diseases (ICD) codes; however, the reliability of ICD codes for hospital admissions for CAP in people with HIV (PWH) has not been systematically assessed. Methods We used data from the Veterans Aging Cohort Study survey sample (N = 6824; 3410 PWH and 3414 uninfected) to validate the use of electronic health records (EHR) data to identify CAP hospitalizations when compared to chart review and to compare the performance in PWH vs. uninfected patients. We used different EHR algorithms that included a broad set of CAP ICD-9 codes, a set restricted to bacterial and viral CAP codes, and algorithms that included pharmacy data and/or other ICD-9 diagnoses frequently associated with CAP. We also compared microbiologic workup and etiologic diagnosis by HIV status among those with CAP. Results Five hundred forty-nine patients were identified as having an ICD-9 code compatible with a CAP diagnosis (13% of PWH and 4% of the uninfected, p < 0.01). The EHR algorithm with the best overall positive predictive value (82%) was obtained by using the restricted set of ICD-9 codes (480–487) in primary position or secondary only to selected codes as primary (HIV disease, respiratory failure, sepsis or bacteremia) with the addition of EHR pharmacy data; this algorithm yielded PPVs of 83% in PWH and 73% in uninfected (P = 0.1) groups. Adding aspiration pneumonia (ICD-9 code 507) to any of the ICD-9 code/pharmacy combinations increased the number of cases but decreased the overall PPV. Allowing COPD exacerbation in the primary position improved the PPV among the uninfected group only (to 76%). More PWH than uninfected patients underwent microbiologic evaluation or had respiratory samples submitted. Conclusions ICD-9 code-based algorithms perform similarly to identify CAP in PLWH and uninfected individuals. Adding antimicrobial use data and allowing as primary diagnoses ICD-9 codes frequently used in patients with CAP improved the performance of the algorithms in both groups of patients. The algorithms consistently performed better among PWH. | ||
650 | 4 | |a Community-acquired pneumonia |7 (dpeaa)DE-He213 | |
650 | 4 | |a HIV |7 (dpeaa)DE-He213 | |
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700 | 1 | |a McGinnis, Kathleen A. |e verfasserin |4 aut | |
700 | 1 | |a Akgün, Kathleen |e verfasserin |4 aut | |
700 | 1 | |a Tate, Janet P. |e verfasserin |4 aut | |
700 | 1 | |a Brown, Sheldon T. |e verfasserin |4 aut | |
700 | 1 | |a Butt, Adeel A. |e verfasserin |4 aut | |
700 | 1 | |a Fine, Michael |e verfasserin |4 aut | |
700 | 1 | |a Goetz, Matthew Bidwell |e verfasserin |4 aut | |
700 | 1 | |a Graber, Christopher J. |e verfasserin |4 aut | |
700 | 1 | |a Huang, Laurence |e verfasserin |4 aut | |
700 | 1 | |a Rimland, David |e verfasserin |4 aut | |
700 | 1 | |a Justice, Amy |e verfasserin |4 aut | |
700 | 1 | |a Crothers, Kristina |e verfasserin |4 aut | |
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10.1186/s41479-020-00068-1 doi (DE-627)SPR040447200 (SPR)s41479-020-00068-1-e DE-627 ger DE-627 rakwb eng 610 ASE Rodriguez-Barradas, Maria C. verfasserin aut Validation for using electronic health records to identify community acquired pneumonia hospitalization among people with and without HIV 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background Cohort studies identifying the incidence, complications and co-morbidities associated with community acquired pneumonia (CAP) are largely based on administrative datasets and rely on International Classification of Diseases (ICD) codes; however, the reliability of ICD codes for hospital admissions for CAP in people with HIV (PWH) has not been systematically assessed. Methods We used data from the Veterans Aging Cohort Study survey sample (N = 6824; 3410 PWH and 3414 uninfected) to validate the use of electronic health records (EHR) data to identify CAP hospitalizations when compared to chart review and to compare the performance in PWH vs. uninfected patients. We used different EHR algorithms that included a broad set of CAP ICD-9 codes, a set restricted to bacterial and viral CAP codes, and algorithms that included pharmacy data and/or other ICD-9 diagnoses frequently associated with CAP. We also compared microbiologic workup and etiologic diagnosis by HIV status among those with CAP. Results Five hundred forty-nine patients were identified as having an ICD-9 code compatible with a CAP diagnosis (13% of PWH and 4% of the uninfected, p < 0.01). The EHR algorithm with the best overall positive predictive value (82%) was obtained by using the restricted set of ICD-9 codes (480–487) in primary position or secondary only to selected codes as primary (HIV disease, respiratory failure, sepsis or bacteremia) with the addition of EHR pharmacy data; this algorithm yielded PPVs of 83% in PWH and 73% in uninfected (P = 0.1) groups. Adding aspiration pneumonia (ICD-9 code 507) to any of the ICD-9 code/pharmacy combinations increased the number of cases but decreased the overall PPV. Allowing COPD exacerbation in the primary position improved the PPV among the uninfected group only (to 76%). More PWH than uninfected patients underwent microbiologic evaluation or had respiratory samples submitted. Conclusions ICD-9 code-based algorithms perform similarly to identify CAP in PLWH and uninfected individuals. Adding antimicrobial use data and allowing as primary diagnoses ICD-9 codes frequently used in patients with CAP improved the performance of the algorithms in both groups of patients. The algorithms consistently performed better among PWH. Community-acquired pneumonia (dpeaa)DE-He213 HIV (dpeaa)DE-He213 Electronic health records (dpeaa)DE-He213 McGinnis, Kathleen A. verfasserin aut Akgün, Kathleen verfasserin aut Tate, Janet P. verfasserin aut Brown, Sheldon T. verfasserin aut Butt, Adeel A. verfasserin aut Fine, Michael verfasserin aut Goetz, Matthew Bidwell verfasserin aut Graber, Christopher J. verfasserin aut Huang, Laurence verfasserin aut Rimland, David verfasserin aut Justice, Amy verfasserin aut Crothers, Kristina verfasserin aut Enthalten in Pneumonia [London] : BioMed Central, 2012 12(2020), 1 vom: 25. Juli (DE-627)812500563 (DE-600)2803296-2 2200-6133 nnns volume:12 year:2020 number:1 day:25 month:07 https://dx.doi.org/10.1186/s41479-020-00068-1 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2020 1 25 07 |
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10.1186/s41479-020-00068-1 doi (DE-627)SPR040447200 (SPR)s41479-020-00068-1-e DE-627 ger DE-627 rakwb eng 610 ASE Rodriguez-Barradas, Maria C. verfasserin aut Validation for using electronic health records to identify community acquired pneumonia hospitalization among people with and without HIV 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background Cohort studies identifying the incidence, complications and co-morbidities associated with community acquired pneumonia (CAP) are largely based on administrative datasets and rely on International Classification of Diseases (ICD) codes; however, the reliability of ICD codes for hospital admissions for CAP in people with HIV (PWH) has not been systematically assessed. Methods We used data from the Veterans Aging Cohort Study survey sample (N = 6824; 3410 PWH and 3414 uninfected) to validate the use of electronic health records (EHR) data to identify CAP hospitalizations when compared to chart review and to compare the performance in PWH vs. uninfected patients. We used different EHR algorithms that included a broad set of CAP ICD-9 codes, a set restricted to bacterial and viral CAP codes, and algorithms that included pharmacy data and/or other ICD-9 diagnoses frequently associated with CAP. We also compared microbiologic workup and etiologic diagnosis by HIV status among those with CAP. Results Five hundred forty-nine patients were identified as having an ICD-9 code compatible with a CAP diagnosis (13% of PWH and 4% of the uninfected, p < 0.01). The EHR algorithm with the best overall positive predictive value (82%) was obtained by using the restricted set of ICD-9 codes (480–487) in primary position or secondary only to selected codes as primary (HIV disease, respiratory failure, sepsis or bacteremia) with the addition of EHR pharmacy data; this algorithm yielded PPVs of 83% in PWH and 73% in uninfected (P = 0.1) groups. Adding aspiration pneumonia (ICD-9 code 507) to any of the ICD-9 code/pharmacy combinations increased the number of cases but decreased the overall PPV. Allowing COPD exacerbation in the primary position improved the PPV among the uninfected group only (to 76%). More PWH than uninfected patients underwent microbiologic evaluation or had respiratory samples submitted. Conclusions ICD-9 code-based algorithms perform similarly to identify CAP in PLWH and uninfected individuals. Adding antimicrobial use data and allowing as primary diagnoses ICD-9 codes frequently used in patients with CAP improved the performance of the algorithms in both groups of patients. The algorithms consistently performed better among PWH. Community-acquired pneumonia (dpeaa)DE-He213 HIV (dpeaa)DE-He213 Electronic health records (dpeaa)DE-He213 McGinnis, Kathleen A. verfasserin aut Akgün, Kathleen verfasserin aut Tate, Janet P. verfasserin aut Brown, Sheldon T. verfasserin aut Butt, Adeel A. verfasserin aut Fine, Michael verfasserin aut Goetz, Matthew Bidwell verfasserin aut Graber, Christopher J. verfasserin aut Huang, Laurence verfasserin aut Rimland, David verfasserin aut Justice, Amy verfasserin aut Crothers, Kristina verfasserin aut Enthalten in Pneumonia [London] : BioMed Central, 2012 12(2020), 1 vom: 25. Juli (DE-627)812500563 (DE-600)2803296-2 2200-6133 nnns volume:12 year:2020 number:1 day:25 month:07 https://dx.doi.org/10.1186/s41479-020-00068-1 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2020 1 25 07 |
allfields_unstemmed |
10.1186/s41479-020-00068-1 doi (DE-627)SPR040447200 (SPR)s41479-020-00068-1-e DE-627 ger DE-627 rakwb eng 610 ASE Rodriguez-Barradas, Maria C. verfasserin aut Validation for using electronic health records to identify community acquired pneumonia hospitalization among people with and without HIV 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background Cohort studies identifying the incidence, complications and co-morbidities associated with community acquired pneumonia (CAP) are largely based on administrative datasets and rely on International Classification of Diseases (ICD) codes; however, the reliability of ICD codes for hospital admissions for CAP in people with HIV (PWH) has not been systematically assessed. Methods We used data from the Veterans Aging Cohort Study survey sample (N = 6824; 3410 PWH and 3414 uninfected) to validate the use of electronic health records (EHR) data to identify CAP hospitalizations when compared to chart review and to compare the performance in PWH vs. uninfected patients. We used different EHR algorithms that included a broad set of CAP ICD-9 codes, a set restricted to bacterial and viral CAP codes, and algorithms that included pharmacy data and/or other ICD-9 diagnoses frequently associated with CAP. We also compared microbiologic workup and etiologic diagnosis by HIV status among those with CAP. Results Five hundred forty-nine patients were identified as having an ICD-9 code compatible with a CAP diagnosis (13% of PWH and 4% of the uninfected, p < 0.01). The EHR algorithm with the best overall positive predictive value (82%) was obtained by using the restricted set of ICD-9 codes (480–487) in primary position or secondary only to selected codes as primary (HIV disease, respiratory failure, sepsis or bacteremia) with the addition of EHR pharmacy data; this algorithm yielded PPVs of 83% in PWH and 73% in uninfected (P = 0.1) groups. Adding aspiration pneumonia (ICD-9 code 507) to any of the ICD-9 code/pharmacy combinations increased the number of cases but decreased the overall PPV. Allowing COPD exacerbation in the primary position improved the PPV among the uninfected group only (to 76%). More PWH than uninfected patients underwent microbiologic evaluation or had respiratory samples submitted. Conclusions ICD-9 code-based algorithms perform similarly to identify CAP in PLWH and uninfected individuals. Adding antimicrobial use data and allowing as primary diagnoses ICD-9 codes frequently used in patients with CAP improved the performance of the algorithms in both groups of patients. The algorithms consistently performed better among PWH. Community-acquired pneumonia (dpeaa)DE-He213 HIV (dpeaa)DE-He213 Electronic health records (dpeaa)DE-He213 McGinnis, Kathleen A. verfasserin aut Akgün, Kathleen verfasserin aut Tate, Janet P. verfasserin aut Brown, Sheldon T. verfasserin aut Butt, Adeel A. verfasserin aut Fine, Michael verfasserin aut Goetz, Matthew Bidwell verfasserin aut Graber, Christopher J. verfasserin aut Huang, Laurence verfasserin aut Rimland, David verfasserin aut Justice, Amy verfasserin aut Crothers, Kristina verfasserin aut Enthalten in Pneumonia [London] : BioMed Central, 2012 12(2020), 1 vom: 25. Juli (DE-627)812500563 (DE-600)2803296-2 2200-6133 nnns volume:12 year:2020 number:1 day:25 month:07 https://dx.doi.org/10.1186/s41479-020-00068-1 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2020 1 25 07 |
allfieldsGer |
10.1186/s41479-020-00068-1 doi (DE-627)SPR040447200 (SPR)s41479-020-00068-1-e DE-627 ger DE-627 rakwb eng 610 ASE Rodriguez-Barradas, Maria C. verfasserin aut Validation for using electronic health records to identify community acquired pneumonia hospitalization among people with and without HIV 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background Cohort studies identifying the incidence, complications and co-morbidities associated with community acquired pneumonia (CAP) are largely based on administrative datasets and rely on International Classification of Diseases (ICD) codes; however, the reliability of ICD codes for hospital admissions for CAP in people with HIV (PWH) has not been systematically assessed. Methods We used data from the Veterans Aging Cohort Study survey sample (N = 6824; 3410 PWH and 3414 uninfected) to validate the use of electronic health records (EHR) data to identify CAP hospitalizations when compared to chart review and to compare the performance in PWH vs. uninfected patients. We used different EHR algorithms that included a broad set of CAP ICD-9 codes, a set restricted to bacterial and viral CAP codes, and algorithms that included pharmacy data and/or other ICD-9 diagnoses frequently associated with CAP. We also compared microbiologic workup and etiologic diagnosis by HIV status among those with CAP. Results Five hundred forty-nine patients were identified as having an ICD-9 code compatible with a CAP diagnosis (13% of PWH and 4% of the uninfected, p < 0.01). The EHR algorithm with the best overall positive predictive value (82%) was obtained by using the restricted set of ICD-9 codes (480–487) in primary position or secondary only to selected codes as primary (HIV disease, respiratory failure, sepsis or bacteremia) with the addition of EHR pharmacy data; this algorithm yielded PPVs of 83% in PWH and 73% in uninfected (P = 0.1) groups. Adding aspiration pneumonia (ICD-9 code 507) to any of the ICD-9 code/pharmacy combinations increased the number of cases but decreased the overall PPV. Allowing COPD exacerbation in the primary position improved the PPV among the uninfected group only (to 76%). More PWH than uninfected patients underwent microbiologic evaluation or had respiratory samples submitted. Conclusions ICD-9 code-based algorithms perform similarly to identify CAP in PLWH and uninfected individuals. Adding antimicrobial use data and allowing as primary diagnoses ICD-9 codes frequently used in patients with CAP improved the performance of the algorithms in both groups of patients. The algorithms consistently performed better among PWH. Community-acquired pneumonia (dpeaa)DE-He213 HIV (dpeaa)DE-He213 Electronic health records (dpeaa)DE-He213 McGinnis, Kathleen A. verfasserin aut Akgün, Kathleen verfasserin aut Tate, Janet P. verfasserin aut Brown, Sheldon T. verfasserin aut Butt, Adeel A. verfasserin aut Fine, Michael verfasserin aut Goetz, Matthew Bidwell verfasserin aut Graber, Christopher J. verfasserin aut Huang, Laurence verfasserin aut Rimland, David verfasserin aut Justice, Amy verfasserin aut Crothers, Kristina verfasserin aut Enthalten in Pneumonia [London] : BioMed Central, 2012 12(2020), 1 vom: 25. Juli (DE-627)812500563 (DE-600)2803296-2 2200-6133 nnns volume:12 year:2020 number:1 day:25 month:07 https://dx.doi.org/10.1186/s41479-020-00068-1 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2020 1 25 07 |
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10.1186/s41479-020-00068-1 doi (DE-627)SPR040447200 (SPR)s41479-020-00068-1-e DE-627 ger DE-627 rakwb eng 610 ASE Rodriguez-Barradas, Maria C. verfasserin aut Validation for using electronic health records to identify community acquired pneumonia hospitalization among people with and without HIV 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background Cohort studies identifying the incidence, complications and co-morbidities associated with community acquired pneumonia (CAP) are largely based on administrative datasets and rely on International Classification of Diseases (ICD) codes; however, the reliability of ICD codes for hospital admissions for CAP in people with HIV (PWH) has not been systematically assessed. Methods We used data from the Veterans Aging Cohort Study survey sample (N = 6824; 3410 PWH and 3414 uninfected) to validate the use of electronic health records (EHR) data to identify CAP hospitalizations when compared to chart review and to compare the performance in PWH vs. uninfected patients. We used different EHR algorithms that included a broad set of CAP ICD-9 codes, a set restricted to bacterial and viral CAP codes, and algorithms that included pharmacy data and/or other ICD-9 diagnoses frequently associated with CAP. We also compared microbiologic workup and etiologic diagnosis by HIV status among those with CAP. Results Five hundred forty-nine patients were identified as having an ICD-9 code compatible with a CAP diagnosis (13% of PWH and 4% of the uninfected, p < 0.01). The EHR algorithm with the best overall positive predictive value (82%) was obtained by using the restricted set of ICD-9 codes (480–487) in primary position or secondary only to selected codes as primary (HIV disease, respiratory failure, sepsis or bacteremia) with the addition of EHR pharmacy data; this algorithm yielded PPVs of 83% in PWH and 73% in uninfected (P = 0.1) groups. Adding aspiration pneumonia (ICD-9 code 507) to any of the ICD-9 code/pharmacy combinations increased the number of cases but decreased the overall PPV. Allowing COPD exacerbation in the primary position improved the PPV among the uninfected group only (to 76%). More PWH than uninfected patients underwent microbiologic evaluation or had respiratory samples submitted. Conclusions ICD-9 code-based algorithms perform similarly to identify CAP in PLWH and uninfected individuals. Adding antimicrobial use data and allowing as primary diagnoses ICD-9 codes frequently used in patients with CAP improved the performance of the algorithms in both groups of patients. The algorithms consistently performed better among PWH. Community-acquired pneumonia (dpeaa)DE-He213 HIV (dpeaa)DE-He213 Electronic health records (dpeaa)DE-He213 McGinnis, Kathleen A. verfasserin aut Akgün, Kathleen verfasserin aut Tate, Janet P. verfasserin aut Brown, Sheldon T. verfasserin aut Butt, Adeel A. verfasserin aut Fine, Michael verfasserin aut Goetz, Matthew Bidwell verfasserin aut Graber, Christopher J. verfasserin aut Huang, Laurence verfasserin aut Rimland, David verfasserin aut Justice, Amy verfasserin aut Crothers, Kristina verfasserin aut Enthalten in Pneumonia [London] : BioMed Central, 2012 12(2020), 1 vom: 25. Juli (DE-627)812500563 (DE-600)2803296-2 2200-6133 nnns volume:12 year:2020 number:1 day:25 month:07 https://dx.doi.org/10.1186/s41479-020-00068-1 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2020 1 25 07 |
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Validation for using electronic health records to identify community acquired pneumonia hospitalization among people with and without HIV |
abstract |
Background Cohort studies identifying the incidence, complications and co-morbidities associated with community acquired pneumonia (CAP) are largely based on administrative datasets and rely on International Classification of Diseases (ICD) codes; however, the reliability of ICD codes for hospital admissions for CAP in people with HIV (PWH) has not been systematically assessed. Methods We used data from the Veterans Aging Cohort Study survey sample (N = 6824; 3410 PWH and 3414 uninfected) to validate the use of electronic health records (EHR) data to identify CAP hospitalizations when compared to chart review and to compare the performance in PWH vs. uninfected patients. We used different EHR algorithms that included a broad set of CAP ICD-9 codes, a set restricted to bacterial and viral CAP codes, and algorithms that included pharmacy data and/or other ICD-9 diagnoses frequently associated with CAP. We also compared microbiologic workup and etiologic diagnosis by HIV status among those with CAP. Results Five hundred forty-nine patients were identified as having an ICD-9 code compatible with a CAP diagnosis (13% of PWH and 4% of the uninfected, p < 0.01). The EHR algorithm with the best overall positive predictive value (82%) was obtained by using the restricted set of ICD-9 codes (480–487) in primary position or secondary only to selected codes as primary (HIV disease, respiratory failure, sepsis or bacteremia) with the addition of EHR pharmacy data; this algorithm yielded PPVs of 83% in PWH and 73% in uninfected (P = 0.1) groups. Adding aspiration pneumonia (ICD-9 code 507) to any of the ICD-9 code/pharmacy combinations increased the number of cases but decreased the overall PPV. Allowing COPD exacerbation in the primary position improved the PPV among the uninfected group only (to 76%). More PWH than uninfected patients underwent microbiologic evaluation or had respiratory samples submitted. Conclusions ICD-9 code-based algorithms perform similarly to identify CAP in PLWH and uninfected individuals. Adding antimicrobial use data and allowing as primary diagnoses ICD-9 codes frequently used in patients with CAP improved the performance of the algorithms in both groups of patients. The algorithms consistently performed better among PWH. |
abstractGer |
Background Cohort studies identifying the incidence, complications and co-morbidities associated with community acquired pneumonia (CAP) are largely based on administrative datasets and rely on International Classification of Diseases (ICD) codes; however, the reliability of ICD codes for hospital admissions for CAP in people with HIV (PWH) has not been systematically assessed. Methods We used data from the Veterans Aging Cohort Study survey sample (N = 6824; 3410 PWH and 3414 uninfected) to validate the use of electronic health records (EHR) data to identify CAP hospitalizations when compared to chart review and to compare the performance in PWH vs. uninfected patients. We used different EHR algorithms that included a broad set of CAP ICD-9 codes, a set restricted to bacterial and viral CAP codes, and algorithms that included pharmacy data and/or other ICD-9 diagnoses frequently associated with CAP. We also compared microbiologic workup and etiologic diagnosis by HIV status among those with CAP. Results Five hundred forty-nine patients were identified as having an ICD-9 code compatible with a CAP diagnosis (13% of PWH and 4% of the uninfected, p < 0.01). The EHR algorithm with the best overall positive predictive value (82%) was obtained by using the restricted set of ICD-9 codes (480–487) in primary position or secondary only to selected codes as primary (HIV disease, respiratory failure, sepsis or bacteremia) with the addition of EHR pharmacy data; this algorithm yielded PPVs of 83% in PWH and 73% in uninfected (P = 0.1) groups. Adding aspiration pneumonia (ICD-9 code 507) to any of the ICD-9 code/pharmacy combinations increased the number of cases but decreased the overall PPV. Allowing COPD exacerbation in the primary position improved the PPV among the uninfected group only (to 76%). More PWH than uninfected patients underwent microbiologic evaluation or had respiratory samples submitted. Conclusions ICD-9 code-based algorithms perform similarly to identify CAP in PLWH and uninfected individuals. Adding antimicrobial use data and allowing as primary diagnoses ICD-9 codes frequently used in patients with CAP improved the performance of the algorithms in both groups of patients. The algorithms consistently performed better among PWH. |
abstract_unstemmed |
Background Cohort studies identifying the incidence, complications and co-morbidities associated with community acquired pneumonia (CAP) are largely based on administrative datasets and rely on International Classification of Diseases (ICD) codes; however, the reliability of ICD codes for hospital admissions for CAP in people with HIV (PWH) has not been systematically assessed. Methods We used data from the Veterans Aging Cohort Study survey sample (N = 6824; 3410 PWH and 3414 uninfected) to validate the use of electronic health records (EHR) data to identify CAP hospitalizations when compared to chart review and to compare the performance in PWH vs. uninfected patients. We used different EHR algorithms that included a broad set of CAP ICD-9 codes, a set restricted to bacterial and viral CAP codes, and algorithms that included pharmacy data and/or other ICD-9 diagnoses frequently associated with CAP. We also compared microbiologic workup and etiologic diagnosis by HIV status among those with CAP. Results Five hundred forty-nine patients were identified as having an ICD-9 code compatible with a CAP diagnosis (13% of PWH and 4% of the uninfected, p < 0.01). The EHR algorithm with the best overall positive predictive value (82%) was obtained by using the restricted set of ICD-9 codes (480–487) in primary position or secondary only to selected codes as primary (HIV disease, respiratory failure, sepsis or bacteremia) with the addition of EHR pharmacy data; this algorithm yielded PPVs of 83% in PWH and 73% in uninfected (P = 0.1) groups. Adding aspiration pneumonia (ICD-9 code 507) to any of the ICD-9 code/pharmacy combinations increased the number of cases but decreased the overall PPV. Allowing COPD exacerbation in the primary position improved the PPV among the uninfected group only (to 76%). More PWH than uninfected patients underwent microbiologic evaluation or had respiratory samples submitted. Conclusions ICD-9 code-based algorithms perform similarly to identify CAP in PLWH and uninfected individuals. Adding antimicrobial use data and allowing as primary diagnoses ICD-9 codes frequently used in patients with CAP improved the performance of the algorithms in both groups of patients. The algorithms consistently performed better among PWH. |
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title_short |
Validation for using electronic health records to identify community acquired pneumonia hospitalization among people with and without HIV |
url |
https://dx.doi.org/10.1186/s41479-020-00068-1 |
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author2 |
McGinnis, Kathleen A. Akgün, Kathleen Tate, Janet P. Brown, Sheldon T. Butt, Adeel A. Fine, Michael Goetz, Matthew Bidwell Graber, Christopher J. Huang, Laurence Rimland, David Justice, Amy Crothers, Kristina |
author2Str |
McGinnis, Kathleen A. Akgün, Kathleen Tate, Janet P. Brown, Sheldon T. Butt, Adeel A. Fine, Michael Goetz, Matthew Bidwell Graber, Christopher J. Huang, Laurence Rimland, David Justice, Amy Crothers, Kristina |
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10.1186/s41479-020-00068-1 |
up_date |
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Methods We used data from the Veterans Aging Cohort Study survey sample (N = 6824; 3410 PWH and 3414 uninfected) to validate the use of electronic health records (EHR) data to identify CAP hospitalizations when compared to chart review and to compare the performance in PWH vs. uninfected patients. We used different EHR algorithms that included a broad set of CAP ICD-9 codes, a set restricted to bacterial and viral CAP codes, and algorithms that included pharmacy data and/or other ICD-9 diagnoses frequently associated with CAP. We also compared microbiologic workup and etiologic diagnosis by HIV status among those with CAP. Results Five hundred forty-nine patients were identified as having an ICD-9 code compatible with a CAP diagnosis (13% of PWH and 4% of the uninfected, p < 0.01). The EHR algorithm with the best overall positive predictive value (82%) was obtained by using the restricted set of ICD-9 codes (480–487) in primary position or secondary only to selected codes as primary (HIV disease, respiratory failure, sepsis or bacteremia) with the addition of EHR pharmacy data; this algorithm yielded PPVs of 83% in PWH and 73% in uninfected (P = 0.1) groups. Adding aspiration pneumonia (ICD-9 code 507) to any of the ICD-9 code/pharmacy combinations increased the number of cases but decreased the overall PPV. Allowing COPD exacerbation in the primary position improved the PPV among the uninfected group only (to 76%). More PWH than uninfected patients underwent microbiologic evaluation or had respiratory samples submitted. Conclusions ICD-9 code-based algorithms perform similarly to identify CAP in PLWH and uninfected individuals. 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