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1. Dairyaustralia.com.au. (n.d). MILK . milk-tanker-operator-information-kit-2020.pdf (dairyaustralia.com.au)
2. FAO. (2023). Quality and testing. Dairy production and products: Quality and testing (fao.org)
3. talend.com. (n,d). 8 Ways to Reduce Data Integrity Risk. 8 Ways to Reduce Data Integrity Risk | Talend
4. Gilis.S.A. (July,2019) . quality assurance (QA). https://www.techtarget.com/searchsoftwarequality/definition/quality-assurance
5. LCS. (January 20, 2021). Laboratory Accreditation. Laboratory Accreditation: What is It and Why is it Important? (laboratorycalibrationservices.com)
6. Irjala.M.K. & Grönroos.E.P. (August28, 2009) . Preanalytical and analytical factors affecting laboratory results. Preanalytical and analytical factors affecting laboratory results (tandfonline.com)
7. Kaushik.N. (May 18, 2014). Pre-analytical errors. Pre-analytical errors: their impact and how to minimize them | Medical Laboratory Observer (mlo-online.com)
8. Nadeau.K. (Sept. 21, 2022). Specimen collection and handling best practices and pitfalls. Specimen collection and handling best practices and pitfalls | Medical Laboratory Observer (mlo-online.com)
9. Westland.J. (Dec 23, 2022). The Quality Assurance Process. The Quality Assurance Process: Roles, Methods & Tools - ProjectManager

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This resource paper provides an overview of quality metrics and standards for laboratory testing and reporting, covering essential aspects like accuracy, dependability, timeliness, efficiency, effectiveness, safety, compliance, accountability, satisfaction, and confidence. It covers internal and external quality measures, accreditation, certification, and proficiency testing. This aims to provide best practices for implementing quality measures and standards in laboratory testing and reporting, including good hygiene, reliable methods, staff training, monitoring results, and identifying errors.

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Quality measurements ensure continuous improvement and standard adherence in laboratories.This is because it assits in enhance test reliability, validity, timeliness, efficiency, safety, reduce errors, increase satisfaction, and foster a quality culture in the laboratory.

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Factors that might influence the quality during processing and reporting

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Factors that might influence the quality during processing and reporting

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1. Errors in milk processing and reporting affect quality, safety, fair pricing, and revenue for milk farmers and processors throughout the dairy chain.
2. Common errors in milk processing and reporting include adulteration, incorrect measurement, contamination, and improper handling, storage, and preservation.
3. Mistakes cause inaccuracies, delays, and faults in test findings, impacting customer satisfaction. (talend.com, n.d)

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Factors that might influence the quality of results 

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Factors that might influence the quality of results 

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1. Analytical Error: Mistakes in milk analysis can affect accuracy and precision by affecting procedures, apparatus,  and standards.
2. Reporting errors : Misreporting milk test findings can impact interpretation and use, potentially affecting results accuracy.
3. Contaminated samples impact test accuracy, sensitivity, and specificity due to foreign chemicals or microbes.
4. Unsuitable samples for transportation and storage problems: Samples may show errors due to adverse conditions during transportation or storage, impacting their integrity, viability, or activity. These conditions can affect the quality of the samples. (FAO,2023)

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Factors affecting the quality of results

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Factors affecting the quality of results

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1. Poor hygiene and handling procedures can cause milk contamination and destruction, depending on type and content.
2. Milk's physicochemical properties, including pH, fat, protein, lactose, density, and freezing point, impact shelf life and nutritional value.

3. Temperature and timing are crucial for milk quality and safety, as high temperatures can increase microbe and enzyme activity, causing spoilage, souring, coagulation, or curdling.

4. Packing material type and standard can impact milk quality by protecting it from physical and chemical hazards. (FAO,2023)

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Measures to minimize the factors that influence on result integrity

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Measures to minimize the factors that influence on result integrity

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1.Use good hygiene and handling methods to avoid microbial contamination and spoiling of milk. This involves cleaning the milker,the milking equipment, the milk containers and the transport trucks.
2.Properly cool milk to 4°C or below for preservation and transportation to prevent bacteria and enzyme degradation.  3.Transport the milk samples as soon as possible after collection, ideally within 24 hours.
4.Use proper packaging material of a suitable type and quality to protect the milk from physical, chemical dangers.(dairyaustralia.com.au, n.d)

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Quality assurance is a management process defining standards, rules, and processes to prevent concerns and maintain product integrity. (Westland.J,2022)

It helps businesses meet consumer needs, expectations, and requirements, fostering trust and loyalty while preventing product problems. (Gilis.S.A,2019)

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 Effective measures to minimize the influence of factors on result integrity

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 Effective measures to minimize the influence of factors on result integrity

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1. Ensure dairy supply chain hygiene by cleaning equipment, disinfecting utensils, washing hands, and avoiding contact with animals.
2. Utilizing reliable testing procedures and equipment.
3. Staff training in milk testing, quality control, sample collection, labeling, transportation, storage, analysis, evaluation, and error resolution.
4. Analyzing outcomes and performance using methods like quality control, testing, audits, and feedback. (Kaushik.N. , 2014)

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Mistake management in laboratory environments involves identifying, reporting, analyzing, and resolving errors to prevent future issues and implement corrective actions.
Error management and remedial measures are crucial for enhancing test accuracy, efficiency, safety, compliance, and fostering a learning and improvement culture. These measures improve laboratory operations, reduce injury risks, and maintain high-quality services that meet customer, stakeholder, and regulatory expectations.

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Measures to minimize the influence of factors on result integrity

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Measures to minimize the influence of factors on result integrity

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1. Preanalytical variation: To prevent microbial contamination and spoilage of samples, use proper cleanliness and handling methods, sterilize containers and equipment, and use cooling equipment to maintain stable temperature and reduce bacteria and enzyme activity.
2. Analytical Variation: Regulation of equipment performance using quality control samples and statistical approaches to identify and address analytical variation.
3. To reduce postanalytical variance, present data in concise formats like tables, graphs, charts and create informative reports, abstracts. Share findings securely via electronic systems.
4. Minimize biological variation by using identical sample collection techniques and adjusting reference ranges and criteria. (Irjala.M.K. & Grönroos.E.P. , 2009)

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• Clause 7.3: Sampling
• Clause 7.6: Ensuring the validity of results
• Clause 7.7: Reporting results
1. FAO. (2023). Quality and testing. Dairy production and products: Quality and testing (fao.org)
2. dairyaustralia.com.au. (n.d). MILK . milk-tanker-operator-information-kit-2020.pdf (dairyaustralia.com.au)

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This procedure involves evaluating and testing labs against strict and widely acknowledged standards for quality, accuracy, dependability, and efficiency.

This process aims to ensure that laboratories deliver accurate findings while also reducing the likelihood of testing mistakes.(LCS,2021)

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Factors that affect the quality of results during the receiving and storage of samples

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Factors that affect the quality of results during the receiving and storage of samples

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1. Misidentification errors: Mislabeled samples can cause misunderstandings, misinterpretation, or loss due to incorrect labeling, matching, and documentation.
2. Test transcription errors: Mistakes in test requests due to inadequate submission, communication, or reception can lead to inaccurate, missing, delayed, or duplicated tests.
3. Incorrect sample type: Mistakes in sample collection and storage can affect quality, stability, and compatibility, affecting testing results.
4. Incorrect fill level: Mistakes occur when containers or tubes are not filled to the correct volume, affecting test results. (Nadeau.K,2022)

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Clause 4.2: Structural requirements
Clause 7.2: Review of requests, tenders, and controls.
Clause 7.5: Technical records
Clause 7.6: Validity of the results.
1. Irjala.M.K. & Grönroos.E.P. (August28, 2009) . Preanalytical and analytical factors affecting laboratory results. Preanalytical and analytical factors affecting laboratory results (tandfonline.com)
2. FAO. (2023). Quality and testing. Dairy production and products: Quality and testing (fao.org)

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• Clause 5.1: Impartiality and confidentiality
• Clause 5.4: Use of standard methods and non-standard methods
• Clause 7.5: Technical records
• Clause 7.6: Ensuring the validity of results
Clause 7.7: Reporting results
1. talend.com. (n,d). 8 Ways to Reduce Data Integrity Risk. 8 Ways to Reduce Data Integrity Risk | Talend
2. Kaushik.N. (May 18, 2014). Pre-analytical errors. Pre-analytical errors: their impact and how to minimize them | Medical Laboratory Observer (mlo-online.com)

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Clauses: 5.1.5, 5.1.6, 7.2.2.
Clauses: 5.10.1, 5.10.2, 7.6.
Clauses: 5.5, 5.6, 7.5.2.
Clauses: 5.4.2, 5.4.3, 5.4.4, 7.7.
1. Westland.J. (Dec 23, 2022). The Quality Assurance Process. The Quality Assurance Process: Roles, Methods & Tools - ProjectManager
2. Gilis.S.A. (July,2019) . quality assurance (QA). https://www.techtarget.com/searchsoftwarequality/definition/quality-assurance
3. LCS. (January 20, 2021). Laboratory Accreditation. Laboratory Accreditation: What is It and Why is it Important? (laboratorycalibrationservices.com)

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Effective measures to minimize the influence of the factors on result integrity

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Effective measures to minimize the influence of the factors on result integrity

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1. Avoid misidentification mistakes by following labeling, verification, and tracking processes.
2. Computerized ordering systems reduce test transcription mistakes.
3. Avoid sample type mistakes by following test requirements and storage instructions.
4. Avoid incorrect fill level problems by using correct containers, tubes, and following fill markings. (Nadeau.K,2022)

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Clause 5.1: General requirements for impartiality and confidentiality.
Clause 5.4: Use of standard methods and non-methods.
Clause 7.1: Ensuring laboratory activities are controlled.
Clause 7.4: Handling of test and calibration items.
1. Nadeau.K. (Sept. 21, 2022). Specimen collection and handling best practices and pitfalls. Specimen collection and handling best practices and pitfalls | Medical Laboratory Observer (mlo-online.com)