Electronic health record feedback to improve antibiotic prescribing for acute respiratory infections.

OBJECTIVE: To examine whether the Acute Respiratory Infection (ARI) Quality Dashboard, an electronic health record (EHR)-based feedback system, changed antibiotic prescribing. STUDY DESIGN: Cluster randomized, controlled trial. METHODS: We randomly assigned 27 primary care practices to receive the ARI Quality Dashboard or usual care. The primary outcome was the intent-to-intervene antibiotic prescribing rate for ARI visits. We also compared antibiotic prescribing between ARI Quality Dashboard users and nonusers. RESULTS: During the 9-month intervention, there was no difference between intervention and control practices in antibiotic prescribing for all ARI visits (47% vs 47%; P = .87), antibiotic-appropriate ARI visits (65% vs 64%; P = .68), or non­antibiotic-appropriate ARI visits (38% vs 40%; P = .70). Among the 258 intervention clinicians, 72 (28%) used the ARI Quality Dashboard at least once. These clinicians had a lower overall ARI antibiotic prescribing rate (42% vs 50% for nonusers; P = .02). This difference was due to less antibiotic prescribing for non-antibiotic-appropriate ARIs (32% vs 43%; P = .004), including nonstreptococcal pharyngitis (31% vs 41%; P = .01) and nonspecific upper respiratory infections (19% vs 34%; P = .01). CONCLUSIONS: The ARI Quality Dashboard was not associated with an overall change in antibiotic prescribing for ARIs, although when used, it was associated with improved antibiotic prescribing. EHR-based quality reporting, as part of "meaningful use," may not improve care in the absence of other changes to primary care practice.

Documentation-based clinical decision support to improve antibiotic prescribing for acute respiratory infections in primary care: a cluster randomised controlled trial.

BACKGROUND AND OBJECTIVE: Clinical guidelines discourage antibiotic prescribing for many acute respiratory infections (ARIs), especially for non-antibiotic appropriate diagnoses. Electronic health record (EHR)-based clinical decision support has the potential to improve antibiotic prescribing for ARIs. METHODS: We randomly assigned 27 primary care clinics to receive an EHR-integrated, documentation-based clinical decision support system for the care of patients with ARIs - the ARI Smart Form - or to offer usual care. The primary outcome was the antibiotic prescribing rate for ARIs in an intent-to-intervene analysis based on administrative diagnoses. RESULTS: During the intervention period, patients made 21 961 ARI visits to study clinics. Intervention clinicians used the ARI Smart Form in 6% of 11 954 ARI visits. The antibiotic prescribing rate in the intervention clinics was 39% versus 43% in the control clinics (odds ratio (OR), 0.8; 95% confidence interval (CI), 0.6-1.2, adjusted for clustering by clinic). For antibiotic appropriate ARI diagnoses, the antibiotic prescribing rate was 54% in the intervention clinics and 59% in the control clinics (OR, 0.8; 95% CI, 0.5-1.3). For non-antibiotic appropriate diagnoses, the antibiotic prescribing rate was 32% in the intervention clinics and 34% in the control clinics (OR, 0.9; 95% CI, 0.6-1.4). When the ARI Smart Form was used, based on diagnoses entered on the form, the antibiotic prescribing rate was 49% overall, 88% for antibiotic appropriate diagnoses and 27% for non-antibiotic appropriate diagnoses. In an as-used analysis, the ARI Smart Form was associated with a lower antibiotic prescribing rate for acute bronchitis (OR, 0.5; 95% CI, 0.3-0.8). CONCLUSIONS: The ARI Smart Form neither reduced overall antibiotic prescribing nor significantly improved the appropriateness of antibiotic prescribing for ARIs, but it was not widely used. When used, the ARI Smart Form may improve diagnostic accuracy compared to administrative diagnoses and may reduce antibiotic prescribing for certain diagnoses.

Hybrid representation of hierarchical structures in point-of-care coded data capture platform.

Capturing structured clinical documentation remains a central challenge in clinical informatics. A solution which represented highly hierarchical data in a relational structure exhibited degradation in performance as complexity of hierarchies grew. To ameliorate the problem, we devised a hybrid approach whereby we commit a precompiled XML representation of hierarchical data as well as individual records to a relational database.

User interface accelerators for clinical documentation in Smart Form.

We have deployed a number of user interface accelerators within the text editor of a documentation-based clinical decision support application. These accelerators enhance the process of documenting a visit and promote closer integration of actionable decision support into the documentation workflow.

Supporting CMT and user customization in Clinical Documentation templates.

Clinical Documentation in the ambulatory care setting must support each clinician's unique workflow and data collection requirements. In addition the documentation system must also be the foundation for interoperability both within and external to the organization. Linking documentation to controlled medical terminologies (CMT) provides data sharing capability and centralized management and quality reporting. Separating codified content from its presentation allows clinicians to create templates and forms that meet these requirements while still ensuring data integrity.

Clinical decision support to improve antibiotic prescribing for acute respiratory infections: results of a pilot study.

Acute Respiratory Infections (ARIs) are the number one reason for antibiotic prescribing in the United States, and much antibiotic prescribing for ARIs is inappropriate. We designed an electronic health record-integrated, documentation-based clinical decision support system for the care of patients with ARIs, the ARI Smart Form. To evaluate the ARI Smart Form and assess the feasibility of performing a larger trial, we conducted a pilot study with 10 clinicians who used the ARI Smart Form with 26 patients. Clinicians prescribed antibiotics to 6 of 6 patients with antibiotic-appropriate diagnoses and to 3 of 20 (15%) patients with antibiotic-inappropriate diagnoses. The average duration of use of the ARI Smart Form was 7.5 (SD+/-4.5) minutes. Eight of 10 respondents reported that the ARI Smart Form was either time-neutral or timesaving. The ARI Smart Form requires further evaluation but has the potential to improve workflow and reduce inappropriate antibiotic prescribing.

Quality Dashboards: technical and architectural considerations of an actionable reporting tool for population management.

Quality Dashboards (QD) is a condition-specific, actionable web-based application for quality reporting and population management that is integrated into the Electronic Health Record (EHR). Using server-based graphic web controls in a .Net environment to construct Quality Dashboards allows customization of the reporting tool without the need to rely on commercial business intelligence tool. Quality Dashboards will improve patient care and quality outcomes as clinicians utilize the reporting tool for population management.

Smart Forms: building condition-specific documentation and decision support tools for ambulatory EHR.

Smart Forms are condition-specific documentation tools that integrate pertinent data review, guideline-based decision support, ambulatory order entry, patient education and coded data capture capabilities. Smart Forms are being developed as Web applications in a service oriented architecture and employ a rules engine for dynamic content generation.