Using inpatient electronic medical records to study influenza for pandemic preparedness

4.1 Main findings

In this exploratory analysis of influenza-related data in a large inpatient EMR data source, we identified hospitalizations with influenza diagnoses and administrations of antiviral treatments. As ordinal-scale endpoints reflecting increasing levels of illness severity have been advocated as useful for evaluating treatment of hospitalized influenza patients19-21 and during the COVID-19 pandemic,22 we explored the feasibility of capturing these endpoints and reported unadjusted rates to inform future studies. We found that using coded data to capture severe endpoints such as in-hospital death, ICU stays, and MV during influenza hospitalizations was feasible.

We found the majority (85%) of hospitalizations with an influenza diagnosis had record of an antiviral treatment administration during their stay, and 64% had evidence of treatment within 2 days of admission (29% on admission date, 35% ≤ 2 days following admission). Patients treated >2 days after admission had more comorbidities than patients treated earlier. Similar to another recent study, severe endpoints were lowest among those treated on admission, and highest among patients treated >2 days after admission or not treated during their stay.23 The exception was death, which occurred most frequently in patients not treated during their stay.

There was no evidence of influenza antiviral administration in 15% of hospitalizations with influenza diagnosis, and we observed frequent documentation of cardiovascular conditions (e.g., ischemic heart disease and heart failure), obesity, and smoking among these patients. In addition, just 16% of hospitalizations without antiviral administrations had influenza as the principal diagnosis code. It is possible some patients without evidence of antiviral treatment during hospitalization did not truly have influenza, and influenza was a differential diagnosis. However, we were unable to confirm this hypothesis due to the lack of available influenza testing data at the time of this analysis.

The FDA plays a key role in ensuring access to safe and effective medical countermeasures (MCMs; e.g., diagnostic and treatments) during a public health emergency.1 Information about MCM safety and effectiveness becomes even more important when an investigational MCM is made available during an emergency. However, capturing and analyzing real-time information during an emergency remains a challenge. Our study established the capacity for these inpatient EMR data to be used in an emergency while also providing important information about seasonal influenza for future work.

In our study, we were able to capture influenza antiviral treatments along with administration dates and times. This bodes well for future studies using inpatient EMR data to examine medications administered in the hospital. However, it is important that future studies explore medications of interest within their data source. Understanding how medications are captured in data sources used for future studies, and recognizing situations when they may not be completely captured, especially within specific care settings (e.g., intra-operatively administered medications)24 is not a challenge unique to this study. Considerations for ensuring real-world data are fit for purpose have been commented on previously.2, 25

We examined oxygen delivery as well as ordinal endpoints in hospitalizations with influenza diagnosis codes. Although we found that up to 40% of influenza non-ICU hospitalizations had evidence of supplemental oxygen use, we understand that oxygen use may be underestimated if only procedure codes are relied upon.26 We were unable to identify BiPAP in this study, which was not unexpected, as billing practices may bundle this with other care and our study identified oxygen delivery based on diagnosis and procedure codes. We expect that both oxygen supplementation and BiPAP use are included in nursing documentation within many EMR systems, and thus it may be possible to extract such information as needed. Future studies in similar inpatient datasets should consider exploring the feasibility of retrieving and analyzing nursing documentation to examine the capture of and ability to attain more specific information regarding type and duration of oxygen therapy.

4.2 Strengths and limitations

The major strength of this study was the size of the data source. We identified hospitalizations with influenza diagnoses in an inpatient EMR database that included 140 hospitals and over 5 million inpatient hospitalizations. These data can be refreshed frequently, and we were able to attain data that were updated through March 31, 2020, at the time of our final analyses in late April 2020. The Sentinel System's partnership with HCA Healthcare provides the FDA opportunities to rapidly examine MCM use and other questions of concern during a public health emergency. Although we did not use it extensively in this analysis, the ability to access the rich clinical information collected during a hospitalization such as procedure dates and medication administration dates and times during a hospitalization is often necessary. Inpatient EMR data allow for capture and examination of information not routinely available in other electronic sources such as claims.

We restricted our analysis to only discharged patients with complete billing information. While this means the data were not as “fresh” as possible, it also means the data are complete. Others have asserted that during an evolving public health emergency, information used for decision making should be stable and complete.2

There are several details to consider when interpreting our study results. We were unable to examine patient characteristics, medication use, or care delivered before or after the hospitalization and relied on conditions coded during hospitalization to examine baseline and high-risk conditions. We used diagnosis and procedure codes to examine conditions and procedures and used revenue codes to define ICU stays. We did not have access to laboratory results to confirm influenza diagnosis at the time of this study, although such data are available in this source. Illness onset dates were also not available, a limitation that will be common in claims data sources as well as other EMR data relying on standardized information only (such detail may be captured in notes). Rates of endpoints are unadjusted and not informed by symptom onset. As influenza antivirals are recommended for use within 2 days of symptom onset, this limits conclusions that can be drawn regarding antiviral treatment timing. Patients are often not well tracked across hospitals, and thus our unit of analysis was limited to the individual hospitalization. The study did not include children, but future studies could explore expanding the dataset to include pediatric patients. Finally, the majority of data used in this study were collected prior to the COVD-19 pandemic beginning in early 2020. Data collected in situations where healthcare systems are strained due to a public health emergency should be interpreted with consideration of circumstances under which clinical care was provided. It is possible that usual coding practices may not be adhered to,2 which could influence future analyses using similar data sources during a public health emergency.

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