Implementing Frailty Measures in the Canadian Healthcare System.

Canadian healthcare is changing to include individuals living with frailty, but frailty must be better operationalized and better framed by sound data standards and policy. Frailty results from deficit accumulation in multiple body systems, with exaggerated vulnerability to external stressors. A growing consensus on defining frailty sets the stage for consensus on operationalization and widespread implementation in care settings. Frailty measurement is not yet integrated into daily clinical practice in Canada. Here, we will present how this integration might occur. We hope to demonstrate that implementation must appeal to inter-professional practice needs in different settings or circumstances. In some settings, methods for frailty case finding are expected to evolve as deemed to be most appropriate to the front-line users. In this "hands-off" approach, care providers, supported by emerging knowledge translation on frailty operationalization, would be informed by their setting and local practices to establish patterns of ad hoc case finding and component definition of frailty. This more nimble case finding strategy would be opportunistic, and would appeal to expert clinicians and self-directed teams who emphasize an individualized health care experience for their patients. In other settings, we can shape frailty case finding by building care algorithms around existing standardized practices and data repositories, leading to a systematic application of frailty measures and a more coordinated process of component definition and care protocols. Here, recommended instruments and data standards must be endorsed by health networks locally, provincially and nationally. The interRAI suite of assessment instruments has pan-Canadian standards in place and its pervasiveness makes it the most obvious starting point, especially in home care and long-term care. We anticipate the evolution of an integrated model informed by stakeholders and settings, where policy makers focus on system supports for frailty case finding, while front-line clinicians use case finding strategies to pinpoint and act on key frailty components.

Incidence and risk factors for delirium and other adverse outcomes in older adults after coronary artery bypass graft surgery.

OBJECTIVE: To determine the incidence and risk factors for delirium after coronary artery bypass graft (CABG) surgery. DESIGN: Prospective cohort. SETTING: Cardiac surgery units of a tertiary care hospital. PARTICIPANTS: Consecutive patients over age 65 years undergoing elective CABG surgery. Exclusion criteria included preoperative sensory or language barriers. INTERVENTIONS: Each patient was assessed within 24 h before surgery for baseline demographic, medical and functional data. Incident delirium (within four postoperative days) was diagnosed by a study physician. Nine potential risk factors for delirium were subjected to univariate and multivariate analysis. MAIN RESULTS: Of 75 consenting patients, three died during or soon after surgery and one was still comatose at follow-up. Of the remaining 71 participants, 23 (32%) experienced delirium. Those with delirium were more likely than those without delirium to have a history of a stroke (21% versus 4%, respectively, P=0.032) and to have had a longer duration of cardiopulmonary bypass (CPB) (113 mins versus 95 mins, respectively, P=0.025). A tendency to have experienced low cardiac output (83% versus 58%, respectively, P=0.061) postoperatively was also noted. Multivariate analysis confirmed past stroke and duration of cardiopulmonary bypass as risk factors. CONCLUSIONS: Delirium in the elderly after CABG surgery is common. Its occurrence may be predisposed by a history of a stroke and precipitated by a longer duration of CPB.

Validity of the confusion assessment method in detecting postoperative delirium in the elderly.

In this prospective cohort of 71 elderly patients undergoing cardiac surgery, each subject was interviewed before and after surgery to detect incident delirium using the Confusion Assessment Method (CAM), the Mini-Mental State Examination (MMSE), the Clock Test, and a health record review. The first 41 were assessed by a physician and the remaining 30 by two study nurses. Delirium was then diagnosed by a physician using DSM-III-R criteria. Delirium was present in 23 subjects (32.4%). The sensitivity of the CAM differed significantly when administered by physicians compared to nurses (1.00 vs. .13). When standard cutoffs were used, neither the MMSE nor the Clock Test were found to be sensitive markers for delirium (.30 and .09, respectively). Recognition of delirium by charting was superior in nurses compared to physicians (.83 vs. .30). We conclude that the sensitivity of markers for delirium, such as the CAM and health record documentation, is dependent on the training background of the operator.