A population-based study of administrative data linkage to measure melanoma surgical and pathology quality

Background — Continuous quality improvement is important for cancer systems. However, collecting and compiling quality indicator data can be time-consuming and resource-intensive. Here we explore the utility and feasibility of linked routinely collected health data to capture key elements of quality of care for melanoma in a single-payer, universal healthcare setting.

Method — This pilot study utilized a retrospective population-based cohort from a previously developed linked administrative data set, with a 65% random sample of all invasive cutaneous melanoma cases diagnosed 2007–2012 in the province of Ontario. Data from the Ontario Cancer Registry was utilized, supplemented with linked pathology report data from Cancer Care Ontario, and other linked administrative data describing healthcare utilization. Quality indicators identified through provincial guidelines and international consensus were evaluated for potential collection with administrative data and measured where possible.

Results — A total of 7,654 cases of melanoma were evaluated. Ten of 25 (40%) candidate quality indicators were feasible to be collected with the available administrative data. Many indicators (8/25) could not be measured due to unavailable clinical information (e.g. width of clinical margins). Insufficient pathology information (6/25) or health structure information (1/25) were less common reasons. Reporting of recommended variables in pathology reports varied from 65.2% (satellitosis) to 99.6% (body location). For stage IB-II or T1b-T4a melanoma patients where SLNB should be discussed, approximately two-thirds met with a surgeon experienced in SLNB. Of patients undergoing full lymph node dissection, 76.2% had adequate evaluation of the basin.

Conclusions — We found that use of linked administrative data sources is feasible for measurement of melanoma quality in some cases. In those cases, findings suggest opportunities for quality improvement. Consultation with surgeons offering SLNB was limited, and pathology report completeness was sub-optimal, but was prior to routine synoptic reporting. However, to measure more quality indicators, text-based data sources will require alternative approaches to manual collection such as natural language processing or standardized collection. We recommend development of robust data platforms to support continuous re-evaluation of melanoma quality indicators, with the goal of optimizing quality of care for melanoma patients on an ongoing basis.