PHSkb: A knowledgebase to support notifiable disease surveillance

BACKGROUND: Notifiable disease surveillance in the United States is predominantly a passive process that is often limited by poor timeliness and low sensitivity. Interoperable tools are needed that interact more seamlessly with existing clinical and laboratory data to improve notifiable disease surveillance. DESCRIPTION: The Public Health Surveillance Knowledgebase (PHSkb™) is a computer database designed to provide quick, easy access to domain knowledge regarding notifiable diseases and conditions in the United States. The database was developed using Protégé ontology and knowledgebase editing software. Data regarding the notifiable disease domain were collected via a comprehensive review of state health department websites and integrated with other information used to support the National Notifiable Diseases Surveillance System (NNDSS). Domain concepts were harmonized, wherever possible, to existing vocabulary standards. The knowledgebase can be used: 1) as the basis for a controlled vocabulary of reportable conditions needed for data aggregation in public health surveillance systems; 2) to provide queriable domain knowledge for public health surveillance partners; 3) to facilitate more automated case detection and surveillance decision support as a reusable component in an architecture for intelligent clinical, laboratory, and public health surveillance information systems. CONCLUSIONS: The PHSkb provides an extensible, interoperable system architecture component to support notifiable disease surveillance. Further development and testing of this resource is needed

Developing a risk stratification model for surgical site infection after abdominal hysterectomy

OBJECTIVE: The incidence of surgical site infection (SSI) ranges widely from 2-21% after hysterectomy. There is insufficient understanding of risk factors to build a specific risk stratification index. METHODS: Retrospective case-control study of 545 abdominal and 275 vaginal hysterectomies from 7/1/03 - 6/30/05 at four institutions. SSIs were defined using CDC/NNIS criteria. Independent risk factors for abdominal hysterectomy were identified by logistic regression. RESULTS: There were 13 deep incisional, 53 superficial incisional, and 18 organ-space SSI after abdominal and 14 organ-space SSI after vaginal hysterectomy. Because risk factors for organ-space SSI were different in univariate analysis, further analyses focused on incisional SSI after abdominal hysterectomy. The maximum serum glucose within 5 days after operation was highest in patients with deep incisional SSI, lower in patients with superficial incisional SSI and lowest in uninfected patients (median 189, 156, and 141mg/dL, p = .005). Independent risk factors for incisional SSI included blood transfusion (odds ratio (OR) 2.4) and morbid obesity (body mass index (BMI) > 35, OR 5.7). Duration of operation > 75th percentile (OR 1.7), obesity (BMI 30-35, OR 3.0), and lack of private health insurance (OR 1.7) were marginally associated with increased odds of SSI. CONCLUSIONS: Incisional SSI after abdominal hysterectomy was associated with increased BMI and blood transfusion. Longer operative time and lack of private health insurance were marginally associated with SSI. A specific risk stratification index could help to more accurately predict the risk of incisional SSI following abdominal hysterectomy

Enhanced Identification of Postoperative Infections among Outpatients

Claims data complement other data sources for identification of surgical site infections following breast surgery and cesarean section

A multicenter study of Clostridium difficile infection-related colectomy, 2000-2006

BACKGROUND: The incidence of Clostridium difficile infection (CDI) has been increasing. Previous studies report that the number of colectomies for CDI is also rising. Outside of a few notable outbreaks, there are few published data documenting increasing severity of CDI. The specific aims of this multiyear, multicenter study were to assess CDI-related colectomy rates and compare CDI-related colectomy rates by CDI surveillance definition. METHODS: Cases of CDI and patients who underwent colectomy were identified electronically from 5 US tertiary-care centers from July 2000 through June 2006. Chart review was performed to determine if a colectomy was for CDI. Monthly CDI-related colectomy rates were calculated as the number of CDI-related colectomies per 1,000 CDI cases. Data between observational groups were compared using χ(2) and Mann-Whitney U tests. Logistic regression was performed to evaluate risk factors for CDI-related colectomy. RESULTS: 8569 cases of CDI were identified and 75 patients had CDI-related colectomy. The overall colectomy rate was 8.7/1,000 CDI cases. The CDI-related colectomy rate ranged from 0 to 23 per 1,000 CDI episodes across hospitals. The colectomy rates for healthcare facility (HCF)-onset CDI was 4.3/1000 CDI cases and 16.5 /1000 CDI cases for community-onset CDI (p <.05). There were significantly more CDI-related colectomies at hospitals B and C (p<.05). CONCLUSIONS: The overall CDI-related colectomy rate was low, and there was no significant change in the CDI-related colectomy rate over time. Onset of disease outside of the study hospital was an independent risk factor for colectomy

Multicenter study of the impact of community-onset Clostridium difficile infection on surveillance for C. difficile infection

OBJECTIVE: To evaluate the influence of community-onset/healthcare facility-associated cases on Clostridium difficile infection (CDI) incidence and outbreak detection. DESIGN: Retrospective cohort. SETTING: Five acute-care healthcare facilities in the United States. METHODS: Positive stool C. difficile toxin assays from July 2000 through June 2006 and healthcare facility exposure information were collected. CDI cases were classified as hospital-onset (HO) if they were diagnosed > 48 hours after admission or community-onset/healthcare facility-associated if they were diagnosed ≤ 48 hours from admission and had recently been discharged from the healthcare facility. Four surveillance definitions were compared: HO cases only and HO plus community-onset/healthcare facility-associated cases diagnosed within 30 (HCFA-30), 60 (HCFA-60) and 90 (HCFA-90) days after discharge from the study hospital. Monthly CDI rates were compared. Control charts were used to identify potential CDI outbreaks. RESULTS: The HCFA-30 rate was significantly higher than the HO rate at two healthcare facilities (p<0.01). The HCFA-30 rate was not significantly different from the HCFA-60 or HCFA-90 rates at any healthcare facility. The correlations between each healthcare facility’s monthly rates of HO and HCFA-30 CDI were almost perfect (range, 0.94–0.99, p<0.001). Overall, 12 time points had a CDI rate >3 SD above the mean, including 11 by the HO definition and 9 by the HCFA-30 definition, with discordant results at 4 time points (κ = 0.794, p<0.001). CONCLUSIONS: Tracking community-onset/healthcare facility-associated cases in addition to HO cases captures significantly more CDI cases but surveillance of HO CDI alone is sufficient to detect an outbreak

Implementing automated surveillance for tracking Clostridium difficile infection at multiple healthcare facilities

Automated surveillance utilizing electronically available data has been found to be accurate and save time. An automated CDI surveillance algorithm was validated at four CDC Prevention Epicenters hospitals. Electronic surveillance was highly sensitive, specific, and showed good to excellent agreement for hospital-onset; community-onset, study facility associated; indeterminate; and recurrent CDI