A tool called MASCC TIME measures documented healthcare encounter time in cancer care, using dates, timestamps and structured information from medical records. Its purpose is to give more detail than counting every day with healthcare contact equally. Internal validation found more accurate extraction of several encounter details, but the tool still leaves travel, caregiver time and other parts of a patient’s lived burden outside the record. Original JAMA Network Open study
The distinction matters when time itself becomes part of the discussion about cancer care. A better way to measure recorded hours is a step towards understanding that burden; it is not a demonstration that a patient’s care has become less time-consuming.
A contact day cannot describe every kind of encounter
A brief blood draw and a long hospital encounter can each count as one healthcare contact day. The study’s authors argue that this can conceal meaningful differences in how much time care occupies. Hour-based information provides a more detailed view of recorded contact, without making every minute equally burdensome for every patient.
The Multinational Association of Supportive Care in Cancer’s Time Intensity and Measurement of Encounters tool standardizes eight variables: the encounter’s start date, start time, end date, end time, purpose, planned or unplanned status, mode of contact and primary clinician. Tool design and Figure 1
These fields describe both duration and context. They can distinguish, for example, the recorded format and purpose of encounters rather than treating them as an undifferentiated number of days. They do not assign a universal threshold at which care time becomes unacceptable.
International input and local validation are different strengths
Development involved 16 oncology trialists from nine countries in a three-round consensus process. That brought international and multidisciplinary input to the choice and definition of fields.
Internal validation was more geographically specific: 367 encounters from a cohort of 46 patients with prostate cancer at a tertiary centre in Toronto. The same cohort had been used to identify candidate variables. Two reviewers’ earlier unstructured extraction was compared with two other reviewers’ extraction using the tool, with investigator consensus serving as the reference. Methods and validation
The 367 encounters are not 367 patients, and the nine-country design panel is not a nine-country external validation study. The authors explicitly call for validation in other cancer populations, healthcare settings and record systems.
Start times improved, but remained difficult
In the results table, start-time extraction accuracy rose from 31% to 66% with the tool. The absolute difference was 35 percentage points, with a 95% confidence interval of 30–40 percentage points. End-time accuracy rose from 69% to 95%. Results table
Those findings concern whether reviewers extracted the intended information correctly against the study’s consensus reference. They are not estimates of how precisely every electronic timestamp represents the patient’s experience.
Start and end times remained harder to extract consistently than several other fields. The authors relate that problem to inconsistent documentation. A structured form cannot restore a timestamp that was never documented, or establish the quality of a missing record.
Seven of eight variables showed statistically significant accuracy improvements; the change for encounter purpose did not. That variation is more informative than describing the tool as having one accuracy percentage that applies to every field.
The study measures two different kinds of time
Reviewers estimated that extracting one encounter took an average of ten minutes without the tool and five minutes with it. That is reviewer abstraction time: the work of turning records into research data. It does not mean patients spent five fewer minutes receiving care. Feasibility results
The patient-time measure and the reviewer-work measure can both be useful. Keeping their owners explicit prevents a research-efficiency result from becoming an unsupported patient-benefit claim.
The paper discloses scholarship support for the lead researcher and industry relationships for several coauthors. Its reference standard was investigator consensus, and validation involved a limited number of reviewers at one centre.
The next layer is time outside the encounter
The tool does not capture the entire burden often described as “time toxicity”. The paper identifies travel, waiting outside direct documented contact, caregiver burden, lost work and other opportunity costs as remaining gaps. Nor can the tool resolve the personal value someone places on different encounters.
The University of Toronto’s 27 October account of the work says there is not yet a patient-facing component. Its interview with lead author Ronald Chow describes further work to understand the broader experience and meaningful thresholds for different patient groups. That is a research direction, rather than an available calculator that can tell someone how much time their treatment will take. University interview
TIME offers a more consistent way to study documented care hours. Demonstrating that a redesigned service reduces patients’ overall burden—and does so without losing useful care—remains a separate evaluation.