Diagnosis of Exclusion vs Inclusion

When evaluating startups, we talk alot about product-market fit, founder-market fit, problem-solution fit, and all other fits that asses a startups’ likelihood of success.

One particular fit that healthcare investors should think about is the company is a fit for the diagnostic workflow they’re involved in (diagnostic type - company fit?). The approach they take has profound implications for their business model, clinical efficacy, and market potential. For investors, understanding these differences is crucial to evaluating whether a company is tackling the right problem with the right approach.

So what are the two types of diagnostic processes, and why does it matter?

Diagnosis of Inclusion

Diagnosis of inclusion is a method where specific tests or markers confirm the presence of a disease directly, without the need to rule out other conditions first. This type of diagnosis relies on objective, measurable evidence—such as tissue samples, blood tests, or imaging—that directly shows the presence of the disease. Examples include:

1. Cancer: Certain cancers can be identified through tissue biopsies, which allow doctors to examine cells directly for malignancy. For example, in breast cancer, a lump detected by a mammogram can be biopsied to check for cancer cells. This biopsy provides concrete evidence confirming or ruling out cancer, allowing for an accurate diagnosis.

2. Diabetes: Diabetes diagnosis relies on direct measurements of blood glucose levels, providing an inclusion-based diagnosis. Blood tests for fasting glucose, HbA1c (a marker of average blood sugar over three months), or an oral glucose tolerance test reveal elevated glucose levels that confirm diabetes directly

3. Cardiovascular Disease: For acute disorders such as coronary artery disease (CAD) and acute myocardial infarction (AMI or heart attack), imaging tests such as coronary angiography or biomarker tests such as troponin ensures rapid and targeted treatment, such as stenting or bypass surgery, to restore blood flow and prevent further damage.

By providing specific answers, inclusion-based diagnostics can guide treatment promptly, helping doctors to act decisively.

Diagnosis of Exclusion:

Diagnosis by exclusion, on the other hand, involves ruling out other possible conditions before confirming a diagnosis. This approach is often necessary when specific markers for a disease are lacking, or when symptoms overlap significantly with other conditions. Examples include:

1. Mental Health: Depression or anxiety are typically diagnosed by exclusion. Symptoms of these conditions, such as fatigue, mood changes, and lack of motivation, can mimic those of other medical issues, including thyroid disorders, vitamin deficiencies, or chronic infections. Even the widely used DSM-5 relies on self-reported, symptom-based clues to rule out physical causes.

2. Neurodegenerative Diseases: Neurodegenerative diseases often share symptoms with other neurological or psychiatric conditions, requiring a diagnosis by exclusion. For Alzheimer’s disease, for example, doctors first rule out reversible causes of memory loss, like vitamin B12 deficiency or infections, through blood tests and brain scans. In Parkinson’s disease, they exclude other movement disorders and neurological issues before settling on a diagnosis, as there is no single test to directly confirm these diseases.

3. Early-Stage Cancer (No Clear Tumor Present): Even though we highlighted cancer as a prime example of diagnosis by inclusion, when there is no clear tumor that can be biopsied, doctors start by ruling out other causes. For instance, early-stage pancreatic cancer may initially present with symptoms similar to gastrointestinal issues. Doctors might test for common gastrointestinal issues, infections, or metabolic disorders first. Cancer only becomes a consideration after these other potential causes are excluded, making it a diagnosis by exclusion.

In these cases, doctors systematically eliminate other possibilities to reach a diagnosis, which can be a longer, more complex process.

Why does this matter for investors?

Ready to go on an (Diagnostic) Odyssey?

Like Odysseus’s journey in Homer’s The Odyssey, where the hero encounters endless challenges, detours, and unexpected obstacles before reaching his destination, patients facing a diagnostic odyssey encounter repeated tests, conflicting opinions, and an often uncertain path toward an accurate diagnosis.

Patients may consult numerous specialists, endure various tests, and grapple with delays in receiving treatment. This prolonged journey isn’t just a drain on healthcare costs; the longer these trips take, the more patient trust and patience is eroded, which is a net negative for all stakeholders involved, especially for the startup providing the diagnostic product or service.

For investors, focus on not just the product being developed; understand the full journey of what the patient (and doctor) needs to go through in order to get to the correct diagnostic, and understand how the company’s product will impact that workflow.

Tech-oriented or Service-oriented solution?

Healthcare startups often fall into two categories: technology-driven or tech-enabled services. For healthcare startups involved in any clinical work, it’s critical for investors to evaluate whether the company’s diagnostic model aligns with the type of diagnosis it is targeting: inclusion or exclusion. Generally speaking:

Technology is Best Positioned for Inclusion-Based Diagnostics

Tech-driven solutions, such as imaging systems, biomarker tests, or AI-enabled tools, excel at inclusion-based diagnostics. Inclusion-based diagnostics yield faster and more definitive clinical outcomes, making them cost-effective by minimizing additional tests or directing patients to the right treatment faster.

Tech-oriented solutions’ biggest strength is that a well-designed standalone product can be easily plugged into an existing diagnostic workflow, providing immediate ROI for the healthcare provider, whether it be through preventing diagnostic odysseys with a definitive test, or testing a patient for whether they’re a candidate for a particular treatment, if a disease diagnosis is already known.

Services Are Best Leveraged for Exclusion-Based Diagnostics

Exclusion-based diagnostics often require a nuanced, consultative process to rule out other conditions, making service-oriented models a better fit. However, traditional service approaches—relying heavily on professionals, physical facilities, and manual processes—can have limited financial margins. A tech-enabled service approach can enhance these margins by streamlining workflows, integrating AI for preliminary analyses, or providing virtual consultations to reduce reliance on costly in-person visits.

Misalignment here can lead to unrealistic expectations for the investor, whether it’s service-oriented companies being valued like tech company (diagnosis is straightforward, no professionals needed!), or tech companies attempting to tackle a service-oriented problem (we have the one test of rule them all!). Investors would do well to understand this distinction and pay special attention to the company’s understanding of the diagnostic journey.

Evidence Needed to Prove Efficacy of Diagnostic Test

The regulatory and clinical burden of proof differs between inclusion-based and exclusion-based diagnostics. Inclusion diagnostics often require specific, measurable evidence (e.g., biomarker validation or imaging accuracy) that confirms a condition, which can be more straightforward to prove in clinical trials.

Conversely, exclusion-based diagnostics must demonstrate their ability to reliably rule out a range of other conditions, which can demand extensive data and longer trials to ensure efficacy and safety. For investors, assessing the level of evidence required for a startup’s diagnostic solution is crucial, as this affects time-to-market, development costs, and reimbursement potential.

Conclusion:

In healthcare, how a diagnosis is achieved—through inclusion or exclusion—has a major impact on patient outcomes, costs, and the overall effectiveness of a healthcare startup’s diagnostic solution. Understanding this process is essential as investors evaluate the potential value and challenges associated with building a healthcare company, and understand the likely investment outcome for the company.

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