Using data linkage methodologies to augment healthcare-associated infection surveillance data

Divergences between healthcare-associated infection administrative data and active surveillance data in Canada

BACKGROUND

Although Canada has both a national active surveillance system and administrative data for the passive surveillance of healthcare-associated infections (HAI), both have identified strengths and weaknesses in their data collection and reporting. Active and passive surveillance work independently, resulting in results that diverge at times. To understand the divergences between administrative health data and active surveillance data, a scoping review was performed.

METHOD

Medline, Embase and Cumulative Index to Nursing and Allied Health Literature along with grey literature were searched for studies in English and French that evaluated the use of administrative data, alone or in comparison with traditional surveillance, in Canada between 1995 and November 2, 2020. After extracting relevant information from selected articles, a descriptive summary of findings was provided with suggestions for the improvement of surveillance systems to optimize the overall data quality.

RESULTS

Sixteen articles met the inclusion criteria, including twelve observational studies and four systematic reviews. Studies showed that using a single source of administrative data was not accurate for HAI surveillance when compared with traditional active surveillance; however, combining different sources of data or combining administrative with active surveillance data improved accuracy. Electronic surveillance systems can also enhance surveillance by improving the ability to detect potential HAIs.

CONCLUSION

Although active surveillance of HAIs produced the most accurate results and remains the gold-standard, the integration between active and passive surveillance data can be optimized. Administrative data can be used to enhance traditional active surveillance. Future studies are needed to evaluate the feasibility and benefits of potential solutions presented for the use of administrative data for HAI surveillance and reporting in Canada.

CREATE: A New Data Resource to Support Cardiac Precision Health

Background

The initiatives of precision medicine and learning health systems require databases with rich and accurately captured data on patient characteristics. We introduce the Clinical Registry, AdminisTrative Data and Electronic Medical Records (CREATE) database, which includes linked data from 4 population databases: Alberta Provincial Project for Outcome Assessment in Coronary Heart Disease (APPROACH; a national clinical registry), Sunrise Clinical Manager (SCM) electronic medical record (city-wide), the Discharge Abstract Database (DAD), and the National Ambulatory Care Reporting System (NACRS). The intent of this work is to introduce a cardiovascular-specific database for pursuing precision health activities using big data analytics.

Methods

We used deterministic data linkage to link SCM electronic medical record data to APPROACH clinical registry data using patient identifier variables. The APPROACH-SCM data set was subsequently linked to DAD and NACRS to obtain inpatient and outpatient cohort data. We further validated the quality of the linkage, where applicable, in these databases by comparing against the Alberta Health Insurance Care Plan registry database.

Results

We achieved 99.96% linkage across these 4 databases. Currently, there are 30,984 patients with 35,753 catheterizations in the CREATE database. The inpatient cohort contained 65.75% (20,373/30,984) of the patient sample, whereas the outpatient cohort contained 29.78% (9226/30,984). The infrastructure and the process to update and expand the database has been established.

Conclusions

CREATE is intended to serve as a database for supporting big data analytics activities surrounding cardiac precision health. The CREATE database will be managed by the Centre for Health Informatics at the University of Calgary, and housed in a secure high-performance computing environment.

Characterizing Clostridioides difficile infections and hospital exposures in California using surveillance and administrative data, 2014-2015

OBJECTIVE

To evaluate a method to identify hospitals contributing to Clostridioides difficile infections (CDI) at subsequent hospitalizations.

DESIGN

Retrospective cohort study.

METHODS

We merged 2014-2015 National Healthcare Safety Network (NHSN) inpatient CDI laboratory-identified events with hospital patient discharge data. For patients with incident community-onset CDI (CO CDI), we identified immediately preceding admissions (within 12 weeks) unrelated to CDI at different (exposure) hospitals. We calculated an exposure rate, and we selected hospitals with the highest (90th-100th percentile) rates by hospital type and compared these rates with reported standardized infection ratios (SIR) for CDI.

RESULTS

We successfully matched 44,691 of 58,842 NHSN CDI records (76.0%) with a hospital discharge record. Among 36,215 unique matched records, 5,234 (14.5%) had an admission not related to CDI within 12 weeks prior to an incident CO CDI event, and 1,574 of these admissions (30.1%) occurred in a different hospital. For 33 hospitals with an exposure ranking within the 90th-100th percentile, CDI SIRs for 22 (66.7%) were not significantly different; 3 (9.1%) were lower; and 8 (24.2%) were higher than the national baseline. Also, 12 (36.4%) had an SIR ≤1.0.

CONCLUSIONS

The identification of high-ranked exposure hospitals presents an alternative to SIR for measuring the contribution of hospitals to the CDI burden across the continuum of care. Further exploration of the potential factors leading to high exposure rank, such as antibiotic use and infection control practices, is indicated and may inform CDI prevention outreach to healthcare facilities and provider networks in California and elsewhere.