Classification and rates of adverse events in a Malawi male circumcision program: impact of quality improvement training
Formulary
DOI:
10.1186/s12913-016-1305-x
Publication Date:
2016-02-17T06:42:09Z
AUTHORS (12)
ABSTRACT
Assessing safety outcomes is critical to inform optimal scale-up of voluntary medical male circumcision (VMMC) programs. Clinical trials demonstrated adverse event (AE) rates from 1.5 8 %, but we have limited data on AEs VMMC programs.A group problem-solving, quality improvement (QI) project involving retrospective chart audits, case-conference AE classification, and provider training was conducted at a clinic in Malawi. For each identified potential AE, the timing, assessment, treatment, resolution recorded, then clinical team classified for type severity. During discussions, providers were queried regarding lessons learned challenges providing care. After baseline evaluation, clinicians managers initiated QI plan improve assessment management. A repeat audit 6 months later used similar methods assess proportions severity after intervention.Baseline audits 3000 charts 418 possible (13.9 %), including 152 (5.1 %) excluded determination misclassification. Of 266 remaining AEs, concluded that 257 procedure-related (8.6 per 100 procedures), (0.2 as mild, 218 (7.3 moderate, 33 (1.1 severe. Structural factors found contribute misclassification included: management post-operative inflammation consistent with national guidelines urethral discharge; available antibiotics STI formulary; felt well-trained surgical skills insecure implementation plan, process evaluating 2540 cases 115 (4.5 67 (2.6 28 20 (0.8 Reports decreased by 48 % (from 8.6 4.5 procedures, p < 0.001). moderate-plus-severe (program-reportable) 75 8.4 1.9 0.001).AE our program site within range trial experiences. problem-solving intervention improved management, reporting. Our significantly led more accurate reporting overall program-reportable AEs.
SUPPLEMENTAL MATERIAL
Coming soon ....
REFERENCES (23)
CITATIONS (22)
EXTERNAL LINKS
PlumX Metrics
RECOMMENDATIONS
FAIR ASSESSMENT
Coming soon ....
JUPYTER LAB
Coming soon ....