Target Populations for Pathways

Defining a pathway’s target population is an evolving process. At our institution, we are experimenting with an approach that supports our goal of developing a clinical intelligence reporting platform. This blog presents one method to clearly define the population of patients a pathway is intended to support.

Clinical Pathways are established for specific diseases to standardize care and reduce clinical variability. Within pathways for oncology, stages of the disease as well as phases of care, such as initial evaluation and surveillance, are identified to address the unique considerations of the disease state or phase of treatment. As pathways continue to evolve and become more integrated into different facets of the patient experience, they may also include other dimensions of care, such as supportive care, palliative care, and survivorship. Together, these dimensions can help produce comprehensive population health strategies.

One way of defining target populations for pathways is by their clinical diagnosis. For example, patients with non-small cell lung cancer would be a group eligible for a Non-Small Cell Lung Cancer Clinical Pathway. Using electronic medical records, clinicians are able to document the diagnosis of non-small cell lung cancer using the acronym “NSCLC” or by the specific histologic subtype a patient has, such as adenocarcinoma, large cell, or squamous cell. This variation in EMR documentation—whether in a clinic note or a pathology report—represents a challenge to the process of designating a particular patient as being included in the target population or being eligible for a pathway.

At Seattle Cancer Alliance, our development approach to pathways focuses on defining the standard of care and establishing optimizations for superior outcomes, patient experience, and the mitigation of variation. To achieve this goal, we have worked with our pathways development team to develop a process we are currently evaluating.  

During the development of a pathway, we define with our providers, pathologist, pathway associates, data abstractors, and allied healthcare team, three data elements that help to determine a target population: 1) primary site, 2) histology code with description, and 3) clinical diagnosis. A clinical diagnosis is one that is abstracted from a primary oncologist’s clinic note, in combination with a pathology report, and is used to confirm the histology and a patient’s eligibility for a pathway. The three elements also address gaps that can appear in our clinical data systems and clinical notes. For example, we found that histology site and histology code (we use the International Classification of Diseases for Oncology [ICD-O] scale) are not sufficient to clearly define patient populations in all cases. This means that pathology reports may not stage a patient’s disease, which makes our analysis unable to place a patient on a pathway without considering a diagnosis with stage from a clinical note.

Consider a pathway that is developed for non-small cell lung cancer. The histology site and code will indicate that the patient has non-small cell lung cancer, but not which stage. Some pathways, depending on their intent, scope, or development status, may not address all stages or metastasis status. We discovered that ICD-O codes do not include stage of disease in their definition. Further, the codes, in our implementation, do not indicate in the case of solid tumors whether the tumor is primary or a metastatic secondary mass. ICD-O–3 codes do contain morphology modifiers /6 and /9 which do indicate metastatic state, but our implementation of ICD-O follows Facility Oncology Registry Data Standards (FORDS) page 124 guidance to not use code modifiers beyond /3. In order to designate a patient as eligible for a non-small cell lung cancer pathway and a specific stage—Stage IV for example—the ICD-O codes for primary histology site and tissue type may not be sufficient due to lack of stage information and metastatic status in some pathology reports.

There are likely opportunities to single source the information needed to determine patient eligibility to a pathway. In fact, some institutions are implementing templated notes or discrete information entry via an EMR that captures necessary histology, stage, and clinical diagnosis with stage. Alternatively, similar approaches to discrete data entry may require a provider to designate which pathway a patient should be considered for and ultimately whether they meet all inclusion criteria. Our approach works within the constraints of how our data is captured and abstracted currently. However, our process only determines patient target population. We have another process that considers our exclusion and inclusion criteria for a pathway and whether eligible patients are ultimately placed on a pathway. That process is the topic for a future blog post.

I am interested in how your institutions establish pathway target populations and how your approaches address the nature of your clinical data availability.