Identifying routes of transmission among hospitalized patients during a healthcare-associated outbreak can be tedious, particularly among patients with complex hospital stays and multiple exposures. Data mining of the electronic health record (EHR) has the potential to rapidly identify common exposures among patients suspected of being part of an outbreak.

We retrospectively analyzed 9 hospital outbreaks that occurred during 2011–2016 and that had previously been characterized both according to transmission route and by molecular characterization of the bacterial isolates. We determined (1) the ability of data mining of the EHR to identify the correct route of transmission, (2) how early the correct route was identified during the timeline of the outbreak, and (3) how many cases in the outbreaks could have been prevented had the system been running in real time.

Correct routes were identified for all outbreaks at the second patient, except for one outbreak involving >1 transmission route that was detected at the eighth patient. Up to 40 or 34 infections (78% or 66% of possible preventable infections, respectively) could have been prevented if data mining had been implemented in real time, assuming the initiation of an effective intervention within 7 or 14 days of identification of the transmission route, respectively.

Data mining of the EHR was accurate for identifying routes of transmission among patients who were part of the outbreak. Prospective validation of this approach using routine whole-genome sequencing and data mining of the EHR for both outbreak detection and route attribution is ongoing.

To determine risk factors for the development of surgical site infections (SSIs) in neurosurgery patients undergoing spinal fusion.

Retrospective case-control study.

Large, academic, quaternary care center.

The study population included all neurosurgery patients who underwent spinal fusion between August 1, 2009, and August 31, 2013. Cases were defined as patients in the study cohort who developed an SSI. Controls were patients in the study cohort who did not develop an SSI.

To achieve 80% power with an ability to detect an odds ratio (OR) of 2, we performed an unmatched case-control study with equal numbers of cases and controls.

During the study period, 5,473 spinal fusion procedures were performed by neurosurgeons in our hospital. With 161 SSIs recorded during the study period, the incidence of SSIs associated with these procedures was 2.94%. While anterior surgical approach was found to be a protective factor (OR, 0.20; 95% confidence interval [CI], 0.08–0.52), duration of procedure (OR, 1.58; 95% CI, 1.29–1.93), American Society of Anesthesiologists score of 3 or 4 (OR, 1.79; 95% CI, 1.00–3.18), and hospitalization within the prior 30 days (OR, 5.8; 95% CI, 1.37–24.57) were found in multivariate analysis to be independent predictors of SSI following spinal fusion. Prior methicillin-resistant Staphylococcus aureus (MRSA) nares colonization was highly associated with odds 20 times higher of SSI following spinal fusion (OR, 20.30; 95% CI, 4.64–8.78).

In additional to nonmodifiable risk factors, prior colonization with MRSA is a modifiable risk factor very strongly associated with development of SSI following spinal fusion.

Infect Control Hosp Epidemiol 2017;38:348–352

Determining risk factors for acquisition of methicillin-resistant Staphylococcus aureus (MRSA) in hospitals is important for defining infection-control measures that may lead to fewer hospital-acquired infections.

To determine patient-associated risk factors for acquisition of MRSA in a tertiary care hospital with the goal of identifying modifiable risk factors.

A retrospective matched case-control study was performed. Case patients who acquired MRSA during hospitalization and 2 matched control patients were selected among inpatients admitted to target units during the period from 2001 through 2008. The odds of exposure to potential risk factors were compared between case patients and control patients, using matched univariate conditional logistic regression. A single multivariate conditional logistic regression model identifying independent patient-specific risk factors was generated.

A total of 451 case patients and 866 control patients were analyzed. Factors positively associated with MRSA acquisition were as follows: target unit stay before index culture; primary diagnosis of respiratory disease, digestive tract disease, injury or trauma, or other diagnosis compared with cardiocirculatory disease; peripheral vascular disease; mechanical ventilation with pneumonia; ventricular shunting or ventriculostomy; and ciprofloxacin use. Factors associated with decreased risk were receipt of a solid-organ transplant and use of penicillins, cephalosporins, rifamycins, daptomycin or linezolid, and proton pump inhibitors.

Among the factors associated with increased risk, few are modifiable. Patients with at-risk conditions could be targeted for intensive surveillance to detect acquisition sooner. The association of MRSA acquisition with target unit exposure argues for rigorous application of hand hygiene, appropriate barriers, environmental control, and strict aseptic technique for all procedures performed on such Patients. Our findings support focusing efforts to prevent MRSA transmission and restriction of ciprofloxacin use.