Use of Electronic Administrative Databases to Measure Quality Indicators of Breast Cancer Care: Experience of Five Regional Oncology Networks in Italy

Abstract

PURPOSE: Assuring quality of care, while maintaining sustainability, in complex conditions such as breast cancer (BC) is an important challenge for health systems. Here, we describe a methodology to define a set of quality indicators, assess their computability from administrative data, and apply them to a large cohort of BC cases. MATERIALS AND METHODS: Clinical professionals from the Italian Regional Oncology Networks identified 46 clinically relevant indicators of BC care; 22 were potentially computable using administrative data. Incident cases of BC diagnosed in 2016 in five Italian regions were identified using administrative databases from regional repositories. Each indicator was calculated through record linkage of anonymized individual data. RESULTS: A total of 15,342 incident BC cases were identified. Nine indicators were actually computable from administrative data (two structure and seven process indicators). Although most indicators were consistent with guidelines, for one indicator (blood tumor markers in the year after surgery, 44.2% to 64.5%; benchmark ≤ 20%), deviation was evident throughout the five regions, highlighting systematic overlooking of clinical recommendations. Two indicators (radiotherapy within 4 months after surgery if no adjuvant chemotherapy; 42% to 83.8%; benchmark ≥ 90%; and mammography 6 to 18 months after surgery, 55.1% to 72.6%; benchmark ≥ 90%) showed great regional variability and were lower than expected, possibly as result of an underestimation in indicator calculation by administrative data. CONCLUSION: Despite highlighting some limitations in the use of administrative data to measure health care performance, this study shows that evaluating the quality of BC care at a population level is possible and potentially useful for guiding quality improvement interventions.

Use of Routine Health Datasets to Assess the Appropriateness of Diagnostic Tests in the Follow-Up of Breast Cancer Patients: A Population-Based Study on 3930 Patients

“… 37–39 Several groups have proposed quality performance indicators for BC, but a very limited number of them concerns the appropriate use of diagnostic tests in the follow-up. 21–25 , 40 , 41 The proposed indicators that we found published are “% of patients testing serum tumour markers (CA15.3) in the 12 months after surgery” 40 and “Receiving chest CT or bone scans or liver US/CT/MR or tumour markers measurement in the year following surgery, excluding patients developing metastasis”. 41 …”

“…Our findings are comparable to those of some authors, which found an intensive follow-up applied to 79% of patients, 41 , 45 but different from others, who found lower rates of TM orders. 40 Differences in the geographic area examined, in the years of recruitment of patients and in the length of the follow-up may possibly explain the discrepancy. However, the major difference between the present and previous studies consists in the fact that we subdivided prevalent cases according to their clinical status at follow-up.…”

Identifying transient ischemic attack (TIA) patients at high-risk of adverse outcomes: development and validation of an approach using electronic health record data

“…Several approaches to learning from data are consistent with the Learning Healthcare System paradigm. For example, some systems use electronic health record data to develop and report e-quality metrics, which may or may not be reported with risk adjustment [ 19 , 20 ]. Other systems examine observed outcomes relative to risk-adjusted expected rates [ 21 , 22 ].…”

The pilot project of the National Cancer Network in Poland: Assessment of the functioning of the National Cancer Network and results from quality indicators for lung cancer (2019–2021)

“…The data suggest a correlation between the quality of the medical process, its organisation, and the therapeutic effect [7][8][9][10]. Moreover, an idea of quality indicators in oncology is introduced in different areas of cancer care [11][12][13]. Until now, Poland has had no unified system for managing a large database containing data on cancer patients, which would make it possible to use such data to calculate indicators related to outcomes and internal processes, i.e.…”