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What biases can you avoid when evaluating case management outcomes?

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Case management is a collaborative process that aims to improve the quality, efficiency, and effectiveness of services for clients with complex needs. However, evaluating the outcomes of case management interventions can be challenging, as there are many factors that can influence the results, such as client characteristics, case manager skills, service availability, and contextual variables. Moreover, there are potential biases that can affect the validity and reliability of outcome measurement and evaluation in case management, which can compromise the quality of evidence and decision-making. In this article, we will discuss some of the common biases that can occur when evaluating case management outcomes, and how you can avoid or minimize them.

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1 Selection bias

Selection bias occurs when the sample of clients or cases that are included in the outcome evaluation is not representative of the target population or the intervention group. This can lead to skewed or inaccurate results, as the sample may have different characteristics, needs, preferences, or responses than the population or the group that received the case management intervention. To avoid selection bias, you should use appropriate sampling methods, such as randomization, stratification, or matching, to ensure that the sample is comparable to the population or the intervention group in terms of relevant variables, such as demographics, diagnoses, severity, or service use.

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Dr. Joey (The Traveling Social Workers)? Pagano, DSW, LSW, CRS, FPS, Life Coach

?? 2024 Mental Health America, Pittsburgh Recovery Walk Advocate, NASW Emerging Leader, & PA Peer Support Coalition Award Winner?? | 2 X #1 Best-Seller & Pulitzer Contender ??? | Pioneer in SUD Education ??
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When evaluating case management outcomes, avoid biases like confirmation bias, where preconceptions influence interpretation of results. Be wary of cultural bias, ensuring evaluations are culturally sensitive and inclusive. Avoid overgeneralization, recognizing each case's unique aspects. Be mindful of outcome bias, judging the process's quality, not just the end result. Ensure objectivity by seeking diverse perspectives and involving peers in reviews. Regularly reflect on personal biases, striving for impartial and holistic evaluations of case management outcomes.

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2 Attrition bias

Attrition bias occurs when there is a loss of clients or cases from the outcome evaluation due to dropouts, withdrawals, deaths, or missing data. This can affect the validity and reliability of the results, as the clients or cases that remain in the evaluation may differ from those that left in terms of outcomes, characteristics, or intervention effects. To avoid attrition bias, you should try to minimize the loss of clients or cases by using retention strategies, such as reminders, incentives, follow-ups, or flexible schedules, to encourage their participation and engagement in the evaluation. You should also use appropriate methods to handle missing data, such as imputation, analysis of complete cases, or sensitivity analysis, to account for the potential impact of attrition on the results.

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3 Performance bias

Performance bias occurs when there are differences in the delivery or receipt of the case management intervention or the comparison intervention between the groups or clients that are being evaluated. This can affect the validity and reliability of the results, as the differences in performance may confound or mask the true effects of the intervention. To avoid performance bias, you should ensure that the case management intervention and the comparison intervention are well-defined, standardized, and consistent across the groups or clients that are being evaluated. You should also monitor and document the fidelity and quality of the intervention delivery and receipt, and adjust for any variations or deviations that may occur.

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4 Detection bias

Detection bias occurs when there are differences in the measurement or assessment of the outcomes between the groups or clients that are being evaluated. This can affect the validity and reliability of the results, as the differences in detection may introduce errors or inconsistencies in the outcome data. To avoid detection bias, you should use valid, reliable, and relevant outcome measures that are aligned with the goals and objectives of the case management intervention and the evaluation. You should also use the same outcome measures, methods, and time points across the groups or clients that are being evaluated, and blind the assessors and the clients to the intervention status, if possible.

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5 Reporting bias

Reporting bias occurs when there are differences in the reporting or dissemination of the results between the groups or clients that are being evaluated. This can affect the validity and reliability of the results, as the differences in reporting may distort or omit the findings or the implications of the evaluation. To avoid reporting bias, you should report and disseminate the results in a transparent, comprehensive, and accurate manner, following the standards and guidelines for outcome evaluation in case management. You should also report and disseminate both positive and negative results, and address any limitations, challenges, or uncertainties that may affect the interpretation or generalization of the results.

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6 Confirmation bias

Confirmation bias occurs when there are differences in the interpretation or utilization of the results between the groups or clients that are being evaluated. This can affect the validity and reliability of the results, as the differences in confirmation may influence or bias the conclusions or recommendations of the evaluation. To avoid confirmation bias, you should interpret and utilize the results in a critical, objective, and evidence-based manner, considering the strengths and weaknesses of the evaluation design, methods, and data. You should also seek feedback and input from multiple sources, such as clients, case managers, stakeholders, or experts, to validate and verify the results, and to identify and address any gaps, discrepancies, or conflicts that may arise.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Lokesh (Loki) Thondavada

Risk Advisory l Life Coach l Author of The True Self
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Human beings are bought up with biases, likes and dislikes, good and bad, all through childhood to adulthood. Our society community and schooling condition us with what is acceptable and not acceptable. 1- First step is to acknowledge your bias. 2- The second step in defeating unconscious bias is to be honest with ourselves 3- Self enquiry by being own critic of own thoughts. Ask a trusted friend or colleague for candid feedback, the truth. 4- Admit mistakes and know that your own ego is driving decision making process. Ego is the root cause of all biases. 5- Take responsibility for mitigating bias. Before we try to change the world around us, we need to change our own self first, to see a world of non biased.

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What biases can you avoid when evaluating case management outcomes?

1

2

3

4

5

6

7

1 Selection bias

2 Attrition bias

3 Performance bias

4 Detection bias

5 Reporting bias

6 Confirmation bias

7 Here’s what else to consider

Case Management

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What biases can you avoid when evaluating case management outcomes?

1

2

3

4

5

6

7

1 Selection bias

2 Attrition bias

3 Performance bias

4 Detection bias

5 Reporting bias

6 Confirmation bias

7 Here’s what else to consider

Case Management

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