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Abstract Background Acute hospital discharge delays are a pressing concern for many health care administrators. In Canada, a delayed discharge is defined by the alternate level of care (ALC) construct and has been the target of many provincial health care strategies. Little is known on the patient characteristics that influence acute ALC length of stay. This study examines which characteristics drive acute ALC length of stay for those awaiting nursing home admission. Methods Population-level administrative and assessment data were used to examine 17,111 acute hospital admissions designated as alternate level of care (ALC) from a large Canadian health region. Case level hospital records were linked to home care administrative and assessment records to identify and characterize those ALC patients that account for the greatest proportion of acute hospital ALC days. Results ALC patients waiting for nursing home admission accounted for 41.5% of acute hospital ALC bed days while only accounting for 8.8% of acute hospital ALC patients. Characteristics that were significantly associated with greater ALC lengths of stay were morbid obesity (27 day mean deviation, 99% CI = ±14.6), psychiatric diagnosis (13 day mean deviation, 99% CI = ±6.2), abusive behaviours (12 day mean deviation, 99% CI = ±10.7), and stroke (7 day mean deviation, 99% CI = ±5.0). Overall, persons with morbid obesity, a psychiatric diagnosis, abusive behaviours, or stroke accounted for 4.3% of all ALC patients and 23% of all acute hospital ALC days between April 1st 2009 and April 1st, 2011. ALC patients with the identified characteristics had unique clinical profiles. Conclusions A small number of patients with non-medical days waiting for nursing home admission contribute to a substantial proportion of total non-medical days in acute hospitals. Increases in nursing home capacity or changes to existing funding arrangements should target the sub-populations identified in this investigation to maximize effectiveness. Specifically, incentives should be introduced to encourage nursing homes to accept acute patients with the least prospect for community-based living, while acute patients with the greatest prospect for community-based living are discharged to transitional care or directly to community-based care.

Abstract Background This manuscript describes a method for adjustment of nursing home quality indicators (QIs) defined using the Center for Medicaid & Medicare Services (CMS) nursing home resident assessment system, the Minimum Data Set (MDS). QIs are intended to characterize quality of care delivered in a facility. Threats to the validity of the measurement of presumed quality of care include baseline resident health and functional status, pattern of comorbidities, and facility case mix. The goal of obtaining a valid facility-level estimate of true quality of care should include adjustment for resident- and facility-level sources of variability. Methods We present a practical and efficient method to achieve risk adjustment using restriction and indirect and direct standardization. We present information on validity by comparing QIs estimated with the new algorithm to one currently used by CMS. Results More than half of the new QIs achieved a "Moderate" validation level. Conclusions Given the comprehensive approach and the positive findings to date, research using the new quality indicators is warranted to provide further evidence of their validity and utility and to encourage their use in quality improvement activities.