Assessing Advance Care Planning in Individuals with Lynch Syndrome.
Victoria FentonLauren FletcherJennifer BowlesKelsey HennigAllison M Burton-ChasePublished in: SN comprehensive clinical medicine (2021)
Lynch syndrome (LS) is a hereditary cancer syndrome characterized by an increased risk of multiple cancers, predominantly endometrial and colorectal, at a younger age (typically < 50). In prior research, high death anxiety and a lack of provider-initiated communication about advance care planning (ACP) have been shown to decrease a patient's likelihood of having advance directives. Providers often have gaps in knowledge and are uncomfortable with these conversations. We used a mixed methods approach (quantitative survey with a follow-up telephone interview) to assess knowledge, preferences, and attitudes regarding ACP in individuals with LS (n = 20). This study also assessed which ACP documents individuals already had in place and which persons (providers, family, or friends) an individual made aware of the documentation and/or preferences. These data were analyzed to determine patient preferences for who is responsible for initiating these conversations, identify motivating factors and barriers to these conversations, and determine whether the current conversations are adequate to meet the needs of this patient population. Participants recognized the importance of ACP and expressed interest in creating these documents. However, knowledge and confidence about these topics were lacking, with many participants attributing this to their young age and lack of experience. Although uncomfortable, many patients want to have ACP discussions with their providers, but frequently patients were only asked if these documents are completed with no further discussion. These findings can inform educational efforts to improve knowledge of ACP and interventional research to increase use of ACP by individuals with LS.
Keyphrases
- advance care planning
- case report
- end stage renal disease
- healthcare
- ejection fraction
- newly diagnosed
- chronic kidney disease
- primary care
- machine learning
- prognostic factors
- peritoneal dialysis
- study protocol
- high resolution
- depressive symptoms
- middle aged
- big data
- physical activity
- mass spectrometry
- randomized controlled trial
- data analysis