Rationale, design, and implementation protocol of an electronic health record integrated clinical prediction rule (iCPR) randomized trial in primary care.

BACKGROUND: Clinical prediction rules (CPRs) represent well-validated but underutilized evidence-based medicine tools at the point-of-care. To date, an inability to integrate these rules into an electronic health record (EHR) has been a major limitation and we are not aware of a study demonstrating the use of CPR's in an ambulatory EHR setting. The integrated clinical prediction rule (iCPR) trial integrates two CPR's in an EHR and assesses both the usability and the effect on evidence-based practice in the primary care setting. METHODS: A multi-disciplinary design team was assembled to develop a prototype iCPR for validated streptococcal pharyngitis and bacterial pneumonia CPRs. The iCPR tool was built as an active Clinical Decision Support (CDS) tool that can be triggered by user action during typical workflow. Using the EHR CDS toolkit, the iCPR risk score calculator was linked to tailored ordered sets, documentation, and patient instructions. The team subsequently conducted two levels of 'real world' usability testing with eight providers per group. Usability data were used to refine and create a production tool. Participating primary care providers (n = 149) were randomized and intervention providers were trained in the use of the new iCPR tool. Rates of iCPR tool triggering in the intervention and control (simulated) groups are monitored and subsequent use of the various components of the iCPR tool among intervention encounters is also tracked. The primary outcome is the difference in antibiotic prescribing rates (strep and pneumonia iCPR's encounters) and chest x-rays (pneumonia iCPR only) between intervention and control providers. DISCUSSION: Using iterative usability testing and development paired with provider training, the iCPR CDS tool leverages user-centered design principles to overcome pervasive underutilization of EBM and support evidence-based practice at the point-of-care. The ongoing trial will determine if this collaborative process will lead to higher rates of utilization and EBM guided use of antibiotics and chest x-ray's in primary care. TRIAL REGISTRATION: ClinicalTrials.gov Identifier NCT01386047.

Lymph node ratio as a prognostic factor in elderly patients with pathological N1 non-small cell lung cancer.

BACKGROUND: Lymph node (LN) metastasis is an important predictor of survival for patients with non-small cell lung cancer (NSCLC). However, the prognostic significance of the extent of LN involvement among patients with N1 disease remains unknown. A study was undertaken to evaluate whether involvement of a higher number of N1 LNs is associated with worse survival independent of known prognostic factors. METHODS: Using the Surveillance, Epidemiology and End Results-Medicare database, 1682 resected patients with N1 NSCLC diagnosed between 1992 and 2005 were identified. As the number of positive LNs is confounded by the total number of LNs sampled, the cases were classified into three groups according to the ratio of positive to total number of LNs removed (LN ratio (LNR)): ≤0.15, 0.16-0.5 and >0.5. Lung cancer-specific and overall survival was compared between these groups using Kaplan-Meier curves. Stratified and Cox regression analyses were used to evaluate the relationship between the LNR and survival after adjusting for potential confounders. RESULTS: Lung cancer-specific and overall survival was lower among patients with a high LNR (p<0.0001 for both comparisons). Median lung cancer-specific survival was 47 months, 37 months and 21 months for patients in the ≤0.15, 0.16-0.5 and >0.5 LNR groups, respectively. In stratified and adjusted analyses, a higher LNR was also associated with worse lung cancer-specific and overall survival. CONCLUSIONS: The extent of LN involvement provides independent prognostic information in patients with N1 NSCLC. This information may be used to identify patients at high risk of recurrence who may benefit from aggressive postoperative therapy.

The Statin Choice decision aid in primary care: a randomized trial.

OBJECTIVE: To assess the impact of a decision aid on perceived risk of heart attacks and medication adherence among urban primary care patients with diabetes. METHODS: We randomly allocated 150 patients with diabetes to participate in a usual primary care visit either with or without the Statin Choice tool. Participants completed a questionnaire at baseline and telephone follow-up at 3 and 6 months. RESULTS: Intervention patients were more likely to accurately perceive their underlying risk for a heart attack without taking a statin (OR: 1.9, CI: 1.0-3.8) and with taking a statin (OR: 1.4, CI: 0.7-2.8); a decline in risk overestimation among patients receiving the decision aid accounts for this finding. There was no difference in statin adherence at 3 or 6 months. CONCLUSION: A decision aid about using statins to reduce coronary risk among patients with diabetes improved risk communication, beliefs, and decisional conflict, but did not improve adherence to statins. PRACTICE IMPLICATIONS: Decision aid enhanced communication about the risks and benefits of statins improved patient risk perceptions but did not alter adherence among patients with diabetes.

Improving continuity of care: success of a behavioral health program.

This article documents the quality improvement process implemented by HIP Health Plan of New York (HIP) for the behavioral health continuity-of-care measure, Follow-Up After Hospitalization for Mental Illness. This Health Plan Employer Data and Information Set (HEDIS) measure identifies the percentage of members who receive psychiatric follow-up care after their hospital discharge. Studies indicate that post-hospitalization psychiatric follow-up care is an effective method for reducing hospital readmissions. HIP's mental health services department pursued a number of improvement initiatives with this HEDIS measure. The development of a case management unit proved the most effective intervention as compliance rates for post-hospitalization after-care visits improved and hospital readmittance rates declined. These findings provide valuable resource information for behavioral health providers throughout the United States.