Laboratory medicine best practices: systematic evidence review and evaluation methods for quality improvement.

OBJECTIVE: To develop methods for systematically reviewing evidence for identifying effective laboratory medicine (LM) practices associated with improved healthcare quality outcomes. RELEVANCE: Although many evidence-evaluation systems have been developed, none are designed to include and rate healthcare quality improvement studies to identify evidence-based practices that improve patient safety and LM quality. METHODS: Validated evidence-based medicine methods established by governmental agencies, the Guide to Community Preventive Services, and others were adapted for the LM field. Key methods modifications included (a) inclusion of quality improvement study designs; (b) mechanisms for inclusion of unpublished evidence, (c) combining of individual ratings of study quality, effect size, and relevance of outcome measures to evaluate consistency of practice evidence; and (d) deriving an overall strength rating to support evidence-based best practice recommendations. The methods follow the process steps of: ask; acquire; appraise; analyze; apply; and assess. Expert panels used the systematic evidence review results on practice effectiveness for improving healthcare quality outcomes consistent with the Institute of Medicine's healthcare quality aims (safe, timely, effective, equitable, efficient, and patient-centered). CONCLUSIONS: Adapting and developing methods from validated systems and applying them to systematically review and evaluate practices in LM by using published and unpublished studies is feasible. With these methods, evidence from quality improvement studies can be systematically synthesized and summarized to identify effective LM practices. Practical and scientifically validated demonstration of a positive impact on outcomes ensures that practitioners, policy makers, and decision makers at all levels have the evidence needed for improving healthcare quality and public health.

Lipoprotein Biomarkers and Risk of Cardiovascular Disease: A Laboratory Medicine Best Practices (LMBP) Systematic Review.

BACKGROUND: Controversy exists about the incremental utility of nontraditional lipid biomarkers [e.g., apolipoprotein (apo) B, apo A-I, and non-HDL-C] in improving cardiovascular disease (CVD) risk prediction when added to a conventional model of traditional risk factors (e.g., total cholesterol, LDL cholesterol, HDL cholesterol, sex, age, smoking status, and blood pressure). Here we present a systematic review that was conducted to assess the use of nontraditional lipid biomarkers including apo B, apo A-I, apo B/A-I ratio, and non-HDL-C in improving CVD risk prediction after controlling for the traditional risk factors in populations at risk for cardiovascular events. CONTENT: This systematic review used the Laboratory Medicine Best Practices (LMBP™) A-6 methods. A total of 9 relevant studies published before and including July 2015 comprised the evidence base for this review. Results from this systematic review indicated that after the adjustment for standard nonlipid and lipid CVD risk factors, nontraditional apolipoprotein biomarkers apo B (overall effect = relative risk: 1.31; 95% CI, 1.22-1.40; 4 studies) and apo B/apo A-I ratio (overall effect = relative risk: 1.31; 95% CI, 1.11-1.38; 7 studies) resulted in significant improvement in long-term CVD risk assessment. SUMMARY: Available evidence showed that nontraditional lipid biomarkers apo B and apo B/apo I ratio can improve the risk prediction for cardiovascular events after controlling for the traditional risk factors for the populations at risk. However, because of insufficient evidence, no conclusions could be made for the effectiveness of apo A-I and non-HDL-C lipid markers to predict the CVD events, indicating a need for more research in this field.

Effectiveness of practices to reduce blood culture contamination: a Laboratory Medicine Best Practices systematic review and meta-analysis.

OBJECTIVES: This article is a systematic review of the effectiveness of three practices for reducing blood culture contamination rates: venipuncture, phlebotomy teams, and prepackaged preparation/collection (prep) kits. DESIGN AND METHODS: The CDC-funded Laboratory Medicine Best Practices Initiative systematic review methods for quality improvement practices were used. RESULTS: Studies included as evidence were: 9 venipuncture (vs. versus intravenous catheter), 5 phlebotomy team; and 7 prep kit. All studies for venipuncture and phlebotomy teams favored these practices, with meta-analysis mean odds ratios for venipuncture of 2.69 and phlebotomy teams of 2.58. For prep kits 6 studies' effect sizes were not statistically significantly different from no effect (meta-analysis mean odds ratio 1.12). CONCLUSIONS: Venipuncture and the use of phlebotomy teams are effective practices for reducing blood culture contamination rates in diverse hospital settings and are recommended as evidence-based "best practices" with high overall strength of evidence and substantial effect size ratings. No recommendation is made for or against prep kits based on uncertain improvement.

Effectiveness of barcoding for reducing patient specimen and laboratory testing identification errors: a Laboratory Medicine Best Practices systematic review and meta-analysis.

OBJECTIVES: This is the first systematic review of the effectiveness of barcoding practices for reducing patient specimen and laboratory testing identification errors. DESIGN AND METHODS: The CDC-funded Laboratory Medicine Best Practices Initiative systematic review methods for quality improvement practices were used. RESULTS: A total of 17 observational studies reporting on barcoding systems are included in the body of evidence; 10 for patient specimens and 7 for point-of-care testing. All 17 studies favored barcoding, with meta-analysis mean odds ratios for barcoding systems of 4.39 (95% CI: 3.05-6.32) and for point-of-care testing of 5.93 (95% CI: 5.28-6.67). CONCLUSIONS: Barcoding is effective for reducing patient specimen and laboratory testing identification errors in diverse hospital settings and is recommended as an evidence-based "best practice." The overall strength of evidence rating is high and the effect size rating is substantial. Unpublished studies made an important contribution comprising almost half of the body of evidence.