A regional informatics platform for coordinated antibiotic-resistant infection tracking, alerting, and prevention.

BACKGROUND: We developed and assessed the impact of a patient registry and electronic admission notification system relating to regional antimicrobial resistance (AMR) on regional AMR infection rates over time. We conducted an observational cohort study of all patients identified as infected or colonized with methicillin-resistant Staphylococcus aureus (MRSA) and/or vancomycin-resistant enterococci (VRE) on at least 1 occasion by any of 5 healthcare systems between 2003 and 2010. The 5 healthcare systems included 17 hospitals and associated clinics in the Indianapolis, Indiana, region. METHODS: We developed and standardized a registry of MRSA and VRE patients and created Web forms that infection preventionists (IPs) used to maintain the lists. We sent e-mail alerts to IPs whenever a patient previously infected or colonized with MRSA or VRE registered for admission to a study hospital from June 2007 through June 2010. RESULTS: Over a 3-year period, we delivered 12 748 e-mail alerts on 6270 unique patients to 24 IPs covering 17 hospitals. One in 5 (22%-23%) of all admission alerts was based on data from a healthcare system that was different from the admitting hospital; a few hospitals accounted for most of this crossover among facilities and systems. CONCLUSIONS: Regional patient registries identify an important patient cohort with relevant prior antibiotic-resistant infection data from different healthcare institutions. Regional registries can identify trends and interinstitutional movement not otherwise apparent from single institution data. Importantly, electronic alerts can notify of the need to isolate early and to institute other measures to prevent transmission.

Use of a regional health information exchange to detect crossover of patients with MRSA between urban hospitals.

BACKGROUND: A significant portion of patients already known to be colonized or infected with Methicillin-Resistant Staphylococcus aureus (MRSA) may not be identified at admission by neighboring hospitals. METHODS: We utilized data from a Regional Health Information Exchange to assess the frequency that patients known to have MRSA at one healthcare system are admitted to a neighboring healthcare system unaware of their MRSA status. We conducted a retrospective, registry trial from January 1999 through January 2006 involving three healthcare systems in central Indianapolis, representing six hospitals. RESULTS: Over one year, 286 unique patients generated 587 admissions accounting for 4,335 inpatient days where the receiving hospital was not aware of the prior history of MRSA. The patients accounted for an additional 10% of MRSA admissions received by study hospitals over one year and over 3,600 inpatient days without contact isolation. CONCLUSIONS: Information exchange could improve timely identification of known MRSA patients within an urban setting.

Connecting the dots: creation of an electronic regional infection control network.

The prevalence of Methicillin-resistant Staphylococcus aureus (MRSA) and Vancomycin-resistant Enterococci (VRE) continues to increase dramatically worldwide. Successful programs to reduce infection rates of resistant organisms require regional or national compliance with strict infection control measures and feedback on implementation and reduced rates. We partnered with local infection control professionals (ICPs) and leveraged our existing electronic network to create a comprehensive city-wide network to track and uniformly respond to patients admitted with a history of MRSA or VRE. We successfully standardized and included electronic data from four out of six of the major healthcare systems within Indianapolis. We created tailored abstracts to deliver key infection control data to ICPs when a MRSA patient is admitted to a participating hospital. We created web-based data entry forms for ICPs to modify and enter new infection control data. This paper describes our design and initial implementation of a working electronic regional infection control network.

Nascent regional system for alerting infection preventionists about patients with multidrug-resistant gram-negative bacteria: implementation and initial results.

OBJECTIVE: To build and to begin evaluating a regional automated system to notify infection preventionists (IPs) when a patient with a history of gram-negative rod multidrug-resistant organism (GNRMDRO) is admitted to an emergency department (ED) or inpatient setting. DESIGN: Observational, retrospective study. SETTING: Twenty-seven hospitals, mostly in the Indianapolis metropolitan area, in a health information exchange (HIE). PATIENTS: During testing of the new system: 80,180 patients with microbiology cultures between October 1, 2013, and December 31, 2013; 573 had a GNRMDRO. METHODS/INTERVENTION: A Health Level Seven (HL7) data feed from the HIE was obtained, corrected, enhanced, and used for decision support (secure e-mail notification to the IPs). Retrospective analysis of patients with microbiology data (October 1, 2013, through December 31, 2013) and subsequent healthcare encounters (through February 6, 2014). RESULTS: The 573 patients (median age, 66 years; 68% women) had extended-spectrum ß-lactamase-producing Enterobacteriaceae (78%), carbapenem-resistant Enterobacteriaceae (7%), Pseudomonas aeruginosa (9%), Acinetobacter baumannii (3%), or other GNR (3%). Body sources were urine (68%), sputum/trachea/bronchoalveolar lavage (13%), wound/skin (6%), blood (6%), or other/unidentified (7%). Between October 1, 2013, and February 6, 2014, 252 (44%) of 573 had an ED or inpatient encounter after the GNRMDRO culture, 47 (19% of 252) at an institution different from where the culture was drawn. During the first 7 weeks of actual alerts (January 29, 2014, through March 19, 2014), alerts were generated regarding 67 patients (19 of 67 admitted elsewhere from where the culture was drawn). CONCLUSIONS: It proved challenging but ultimately feasible to create a regional microbiology-based alert system. Even in a few months, we observed substantial crossover between institutions. This system, if it contributes to timely isolation, may help reduce the spread of GNRMDROs.

An operational citywide electronic infection control network: results from the first year.

The prevalence of drug resistant bacteria such as Methicillin-resistant Staphylococcus aureus (MRSA) continues to increase nationwide. Infection control is a regional problem, particularly in urban settings, requiring a coordinated effort. To enable coordinated infection control efforts, we created a citywide electronic notification system to prospectively track and share information regarding all known patients with MRSA. We currently track almost 17,000 patients with a history of MRSA infection or colonization across the Indianapolis region. Since May 2007, we have delivered 2698 admission alerts on patients with a history of MRSA, one-fifth of which (19%) were based on data from another institution. Our system delivers alerts to 20 infection control providers (ICPs) spanning 16 hospital in five different systems across Indianapolis. Electronic coordination of regional infection control information appears to be a critical step to reduce infection rates across an urban population.

A modern optical character recognition system in a real world clinical setting: some accuracy and feasibility observations.

Advances in optical character recognition (OCR) software and computer hardware have stimulated a reevaluation of the technology and its ability to capture structured clinical data from preexisting paper forms. In our pilot evaluation, we measured the accuracy and feasibility of capturing vitals data from a pediatric encounter form that has been in use for over twenty years. We found that the software had a digit recognition rate of 92.4% (95% confidence interval: 91.6 to 93.2) overall. More importantly, this system was approximately three times as fast as our existing method of data entry. These preliminary results suggest that with further refinements in the approach and additional development, we may be able to incorporate OCR as another method for capturing structured clinical data.