Em casos onde há discrepância de resultados obtidos e/ou até discordância entre a equipe, deve-se levar em conta e avaliar: - Método utilizado ( que seja a última versão atualizada) - Treinamento da equipe ( todos devem falar a mesma linguagem) - Condições ambientais ( que sejam as ideais para a análise) - Reagentes e padrões (verificar data de validade) - Curva de calibração se for o caso - Calibração dos equipamentos - Verificar tendência do equipamento com avaliação da carta de controle - Avaliar os protocolos de análise E acima de tudo diálogo franco e aberto com toda equipe para entender o motivo da discordância de modo a assegurar confiabilidade do resultado e que todos possam contribuir para a melhoria dos processos.

To navigate the challenge of test result discrepancies in our lab, I would take the following steps: 1. Reassign Specialists: Rotate specialists between different sections, such as moving the hematology specialist to the biochemistry section. This helps minimize personal errors that often contribute to discrepancies. 2. Quality Control Checks: Conduct thorough quality control checks on all aspects, from control products to equipment. Ensuring that all processes and tools meet the required standards is crucial. 3. Instrument Troubleshooting: If the issue is identified as being related to instruments, such as an auto-analyzer or hematology cell counter, contact the manufacturer for support. In most cases, this will resolve the problem.

When something like this situation happened in the past during my thesis projects it was useful to redo the tests with which we had discrepancies, always double-checking protocol. When the issue persisted, asking another expert on the matter or reviewing bibliography of the same line of investigation and looking for similarities in test results can be very useful to solve the problem.

When faced with a situation like this, consider taking the following steps: - Review the reagent protocols and verify the device settings. - Have an open discussion with your team members, ensuring a judgment-free environment. - If the results are still unsatisfactory, consult with an external expert for advice. - Create a protocol to address similar issues spontaneously in the future.

- Der Test kann von einer zweiten Laborkraft nochmals durchgeführt werden - 2 Laborkräfte machen den Test gemeinsam - die einzelnen Schritte werden gemeinsam diskutiert - die Führungskraft mit genug Erfahrung macht den Laborversuch selber - Erfahrungen und Ergebnisse werden gemeinsam diskutiert (alle gemeinsam auf Augenhöhe)

Inicialmente, é necessário fazer um rastreio detalhado do método e sua realização. Desde conferir os reagentes até a verificação do treinamento da equipe envolvida. Geralmente, ao realizar esse detalhamento, é possível encontrar os desvios que levam às discrepâncias. Por este motivo, as auditorias internas se fazem tão necessárias, para avaliar continuamente a eficiência do laboratório como um todo. Como um segundo passo, é necessária a correção dos desvios identificados junto à equipe, de forma colaborativa e dinâmica. Para que se torne um aprendizado mútuo e todos possam adquirir maturidade técnica e fomentar o trabalho em equipe.

In my humble limited opinion, when a team faces conflicts over test result discrepancies - they should - Reach a consensus on the goal with SMART framework. - Have consensus on the rules of engagement and how to interpret what potential result. - Build consensus on the protocols and rationales that shall be included in the work-up to it. - Keep a thorough record of EVERY particular detail in the RnD process. Even the failed experiments. - Have regular frank and free discussions without personal EGOs in the room on the PROS and CONS of the work, the rationale and the methodology. - Generate regular summarised reports that provide insights into last 'n' number of activities, individually and on a team level to guide future actions.

To address test result discrepancies, I would: Investigate Root Causes: Review processes, equipment, and protocols to pinpoint issues. Promote Open Communication: Facilitate transparent, solution-focused discussions. Strengthen Quality Control: Enhance procedures and benchmark with external standards. Provide Training: Ensure staff are updated on protocols and best practices. Document Results: Keep detailed records for accountability and improvement. Focus on Continuous Improvement: Use strategies like Lean Six Sigma to optimize workflows. This approach fosters collaboration, trust, and lab reliability.