See the published version of this preprint at BMC Medical Informatics and Decision Making.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research article
Maki Komamine
Department of Biostatistics, Kyoto University School of Public Health, Kyoto, Japan bOffice of Medical Informatics and Epidemiology, Pharmaceuticals and Medical Devices Agency, Tokyo, Japan
Corresponding Author
ORCiD: https://orcid.org/0000-0002-8390-0922
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: In Japan, a multiple-hospital observational database system, the Medical Information Database Network (MID-NET®), was launched for post-marketing drug safety assessments. These assessments will be based on datasets with missing laboratory results. The characteristics of missing data considering hospital differences have not been evaluated. We assessed the missing proportion and the association between missingness and a factor through case studies using a database system, a part of MID-NET®.
Methods: Seven scenarios using laboratory results before the prescription of the assessed drug as baseline covariates and data from 10 hospitals of Tokushukai Medical Group were used. The missing proportion and the association between missingness and patient background were investigated per hospital. The associations were assessed using the log of adjusted odds ratio (log-aOR). Additionally, an ad hoc survey was conducted to explore other factors affecting the missingness.
Results: For some laboratory tests, missing proportions varied among hospitals, such as 7.4%–44.4% of alkaline phosphatase (ALP) and 8.1%–31.2% of triglyceride (TG) among statin users. The association between missingness and affecting factors also differed among hospitals for some factors; example, the log-aOR of hospitalization associated with missingness of TG was -0.41 (95% CI, -1.06 to 0.24) in hospital 3 and 1.84 (95% CI, 1.34 to 2.34) in hospital 4. In the ad hoc survey focusing on ALP, hospital-dependent differences in the ordering system settings were observed.
Conclusions: Hospital differences in missing data appeared in some laboratory tests in our multi-hospital observational database, which could be attributed to the affecting factors, including the patient background.
Keywords
Drug safety, clinical laboratory test, database, missing data, observational study, pharmacoepidemiology
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
This preprint is available for download as a PDF.
This is a list of supplementary files associated with this preprint. Click to download.
Loading...
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at BMC Medical Informatics and Decision Making.
Version 1
Posted 21 Sep, 2020
No community comments so far
Editorial decision: Major revision
On 03 Jan, 2021
Reviewer #3 agreed
On 30 Nov, 2020
Reviewer #2 agreed
On 30 Nov, 2020
Reviewer #1 agreed
On 30 Nov, 2020
Review #2 received
Received 30 Nov, 2020
Review #1 received
Received 30 Nov, 2020
Editor assigned
On 18 Sep, 2020
Reviewers invited
Invitations sent on 18 Sep, 2020
Submission checks complete
On 17 Sep, 2020
Editor invited
On 16 Sep, 2020
First submitted
On 08 Sep, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Medical Informatics
Learn more about our company.
See the published version of this preprint at BMC Medical Informatics and Decision Making.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research article
Maki Komamine
Department of Biostatistics, Kyoto University School of Public Health, Kyoto, Japan bOffice of Medical Informatics and Epidemiology, Pharmaceuticals and Medical Devices Agency, Tokyo, Japan
Corresponding Author
ORCiD: https://orcid.org/0000-0002-8390-0922
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at BMC Medical Informatics and Decision Making.
Version 1
Posted 21 Sep, 2020
No community comments so far
Editorial decision: Major revision
On 03 Jan, 2021
Reviewer #3 agreed
On 30 Nov, 2020
Reviewer #2 agreed
On 30 Nov, 2020
Reviewer #1 agreed
On 30 Nov, 2020
Review #2 received
Received 30 Nov, 2020
Review #1 received
Received 30 Nov, 2020
Editor assigned
On 18 Sep, 2020
Reviewers invited
Invitations sent on 18 Sep, 2020
Submission checks complete
On 17 Sep, 2020
Editor invited
On 16 Sep, 2020
First submitted
On 08 Sep, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Medical Informatics
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at BMC Medical Informatics and Decision Making.
Background: In Japan, a multiple-hospital observational database system, the Medical Information Database Network (MID-NET®), was launched for post-marketing drug safety assessments. These assessments will be based on datasets with missing laboratory results. The characteristics of missing data considering hospital differences have not been evaluated. We assessed the missing proportion and the association between missingness and a factor through case studies using a database system, a part of MID-NET®.
Methods: Seven scenarios using laboratory results before the prescription of the assessed drug as baseline covariates and data from 10 hospitals of Tokushukai Medical Group were used. The missing proportion and the association between missingness and patient background were investigated per hospital. The associations were assessed using the log of adjusted odds ratio (log-aOR). Additionally, an ad hoc survey was conducted to explore other factors affecting the missingness.
Results: For some laboratory tests, missing proportions varied among hospitals, such as 7.4%–44.4% of alkaline phosphatase (ALP) and 8.1%–31.2% of triglyceride (TG) among statin users. The association between missingness and affecting factors also differed among hospitals for some factors; example, the log-aOR of hospitalization associated with missingness of TG was -0.41 (95% CI, -1.06 to 0.24) in hospital 3 and 1.84 (95% CI, 1.34 to 2.34) in hospital 4. In the ad hoc survey focusing on ALP, hospital-dependent differences in the ordering system settings were observed.
Conclusions: Hospital differences in missing data appeared in some laboratory tests in our multi-hospital observational database, which could be attributed to the affecting factors, including the patient background.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
This preprint is available for download as a PDF.
This is a list of supplementary files associated with this preprint. Click to download.
Loading...