Define 'survival analysis' in healthcare research.

In healthcare research, survival analysis is specifically focused on the statistical methods used to evaluate the time until an event of interest occurs. This can include critical events such as death, disease progression, recovery, or other significant endpoints. The primary aim is to estimate the expected duration until these outcomes are realized, often taking into consideration censored data where the event has not occurred for all subjects during the observation period.

Survival analysis involves various techniques, including Kaplan-Meier estimators and Cox proportional hazards models, to analyze survival data. These methods help researchers understand factors that influence survival and the likelihood of an event occurring over a given timeframe, which is vital for clinical decision-making and treatment planning.

In contrast, the other options do not accurately describe survival analysis. The first option pertains to financial aspects of healthcare rather than time-to-event data. The third option focuses on disease identification rather than the timing of events. The fourth option relates to qualitative analysis, which emphasizes understanding sentiments and experiences rather than quantitative time-to-event data. Thus, the definition provided in the correct answer encapsulates the essence of survival analysis in a healthcare research context.