|
BACKGROUND/RATIONALE:
Although cancer is a complex and increasingly chronic condition that seriously impairs quality of life, robust tools to evaluate the quality of supportive care have been lacking. Despite VA national leadership in implementing palliative care services, the quality of pain and other symptom management and the extent to which cancer care addresses the informational needs of veterans is not known. Performance data would inform integration of palliative, oncology, primary care, and other services caring for veterans with cancer.
OBJECTIVE(S):
The Cancer Quality-ASSIST (Assessing Symptoms Side Effects and Indicators of Supportive Treatment) indicators address a critical gap in quality measurement, and they are being piloted by the National Cancer Institute (NCI) and the Agency for Healthcare Research and Quality (AHRQ) at Johns Hopkins University. We propose to build on the tool implemented in the NCI/AHRQ pilot of ASSIST using the VA Greater Los Angeles Healthcare System (GLAHS) as a single-site pilot in order to: Aim 1.Pilot test the current NCI / AHRQ abstraction tool to evaluate the feasibility of abstracting data required for scoring the ASSIST inpatient and outpatient quality indicators from VA electronic medical records, and
Aim 2.Evaluate the validity (nurse abstractor-physician), test-retest reliability, relevance (frequency of triggering), and completeness of the ASSIST quality indicators to specify an optimal VA-ASSIST indicator set.
Aim 3.Develop and validate an administrative-data strategy of cohort identification, using cancer registry data as the gold standard
METHODS:
We will use the VA GLAHS cancer registry to identify patients for (1) the chart abstraction cohort for Aims 1 and 2 and (2) as a gold standard cohort to validate the algorithm for case identification using administrative data for Aim 3. We will focus on veterans newly diagnosed with one of the ten most commonly diagnosed solid tumors. We will use the existing medical record abstraction instrument specifically developed to collect the data elements necessary to score the ASSIST Quality Indicators from CPRS. In addition to assessing the validity and reliability of the quality indicators, we will construct a patient-level report of quality of supportive cancer care in order to assess the impact of the number and types of indicators for which a veteran is eligible on an overall assessment of the quality of supportive care.
Concurrent to and independent of medical record abstraction, we will develop an administrative-data algorithm for use in a future national VA study of the quality of supportive care using data elements drawn from the VISN 22 data warehouse and linked to cancer registry data. We will compare the validity (sensitivity, specificity, positive predictive value) of including different data elements in the algorithm using cancer registry data as the gold standard.
FINDINGS/RESULTS:
No results at this time.
IMPACT:
The proposed research will provide the tools necessary to conduct a national VA study of the quality of supportive care.
PUBLICATIONS:
None at this time.
DRA:
Chronic Diseases, Health Services and Systems
DRE:
Quality of Care, Treatment
Keywords:
Cancer, End-of-life, Quality Measure
MeSH Terms:
none
|
