Evaluation of data quality of interRAI assessments in home and community care

• Published in: BMC medical informatics and decision making Vol. 17; no. 1; pp. 150 - 15
• Main Authors: Hogeveen, Sophie E, Chen, Jonathan, Hirdes, John P
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 30.10.2017; BioMed Central; BMC
• Subjects: Aging; Analysis; Assessment; Caregivers; Cognition; Communities; Community Health Assessment; Community health care; Community support; Convergence; Datasets; Decision making; Evaluation; Home care; Home health care; Information management; interRAI; interRAI CHA; Jurisdiction; Long term care; Long term health care; Medical care quality; Medicare; Nursing homes; Older people; Population; Population characteristics; Provinces; Quality; Quality assessment; Quality of life; RAI-HC; Reliability analysis; Resident Assessment Instrument – Home care; Trends; Validity; Canada; interRAI; Quality; interRAI CHA; Assessment; Resident Assessment Instrument – Home care; RAI-HC; Community Health Assessment
• ISSN: 1472-6947; 1472-6947
• DOI: 10.1186/s12911-017-0547-9

The aim of this project is to describe the quality of assessment data regularly collected in home and community, with techniques adapted from an evaluation of the quality of long-term care data in Canada. Data collected using the Resident Assessment Instrument - Home Care (RAI-HC) in Ontario and British Columbia (BC) as well as the interRAI Community Health Assessment (CHA) in Ontario were analyzed using descriptive statistics, Pearson's r correlation, and Cronbach's alpha in order to assess trends in population characteristics, convergent validity, and scale reliability. Results indicate that RAI-HC data from Ontario and BC behave in a consistent manner, with stable trends in internal consistency providing evidence of good reliability (alpha values range from 0.72-0.94, depending on the scale and province). The associations between various scales, such as those reflecting functional status and cognition, were found to be as expected and stable over time within each setting (r values range from 0.42-0.45 in Ontario and 0.41-0.43 in BC). These trends in convergent validity demonstrate that constructs in the data behave as they should, providing evidence of good data quality. In most cases, CHA data quality matches that of RAI-HC data quality and shows evidence of good validity and reliability. The findings are comparable to the findings observed in the evaluation of data from the long-term care sector. Despite an increasingly complex client population in the home and community care sectors, the results from this work indicate that data collected using the RAI-HC and the CHA are of an overall quality that may be trusted when used to inform decision-making at the organizational- or policy-level. High quality data and information are vital when used to inform steps taken to improve quality of care and enhance quality of life. This work also provides evidence that a method used to evaluate the quality of data obtained in the long-term care setting may be used to evaluate the quality of data obtained through community-based measures.