The MAPLe-AC algorithm predicts both positive and adverse outcomes and time to death for older people, 75 years of age or older, in acute care at discharge and at one year follow-up, regardless of the country. In addition to cognitive and physical limitations, chronic conditions are of importance with regards to outcomes, especially at one year. The predictive accuracy was higher for outcomes at discharge, but lower for outcomes after one year. There were some differences between Nordic and Canadian hospitals for predicting discharge outcome. The MAPLe-AC predicted slightly better for discharge home outcome for Canadian hospitals, but for Nordic hospitals for adverse outcome at discharge.
When case-mix indexes for acute hospital care have been tested and outcomes assessed, one of the most predictive factors has been functional capacity, including both physical and cognitive function [2, 15, 16, 18]. In calculation of the MAPLe-AC algorithm, ADLs and cognitive performance are included as they are the basic classifiers along with behavioral symptoms. In many studies, co-morbidity, falls, incontinence, nutrition, pressure ulcers, and instrumental activities of daily living (IADLs) have also been found to contribute to the explanation of use of services and outcomes of hospital care. By using these as hierarchical classifiers, MAPLe-AC takes advantage of standardized data collection and creates a hierarchical priority level decision making tree .
MAPLe-AC algorithm is not intended to be as a case-mix system, but rather a decision-support tool for allocation of geriatric services in acute care. The need for equivalent measures for different care providers to integrate the care of frail older people is met by this algorithm. Measures of clinical complexity like MAPLe-AC are likely to be associated with quality and costs of care over care pathways. Managing factors contributing to complexity is critical to the independence of elderly people, coordinating and funding services.
The MAPLe-AC was tested at three different time points and the question is if one of them is more suitable for use than another. Pre-morbid status reflects the status when the person was able to live at home, and it sets the baseline that possibly could be reached again after the hospital episode. Admission status has multiple variables that are in a dynamic transition between health, illness, and recovery, so the algorithm is not as stable as it is when it is based on pre-morbid status or on day 7 or discharge status. The discharge assessment is affected by many actions initiated during the hospital stay, and it occurs after a few days of improvement from the acute condition that resulted in the admission.
The Area Under ROC curves for MAPLe-AC seem to be higher for discharge status than one year outcomes. They were also higher for adverse outcomes. There may be several reasons for this. Although the MAPLe-AC algorithm does not include information on the acute illness, discharge outcome might be easier to predict due to shorter follow-up time. At one year, especially among older people, several acute episodes either for same or different reason might change the situation of the person. Additionally, chronic illnesses and/or their life conditions might change during one year. To adjust for such changes, monitoring during the ensuing year would be needed. In cases where the person enters home care services after hospital discharge this monitoring might be more easily provided. The MAPLe-AC algorithm is created based on functioning irrespective of diagnosis or treatment of the acute condition. However, in the case of older people differentiating between frailty and diagnoses is difficult  and thus having information on both would be helpful.
If MAPLe-AC is applied for use as a discharge planning tool in acute care hospitals for determining discharge destination it might indicate a better chance to discharge home those in low or mild priority levels at admission. The MAPLe-AC might also act as a stimulus for potential problems and also for highlighting need for rehabilitation and preventive services either during the care episode in hospital or after discharge. However, when MAPLe-AC indicates high or very high priority level, there might be an increased risk of the older person to die or end up in long-term institutional care or end up waiting for the next site of care, particularly when informal support networks are not available. Those with moderate or high priority levels might benefit from more focused support systems for them and their informal caregiver on discharge.
A combination of pre-morbid and admission status MAPLe-AC information could be considered for discharge planning - the pre-morbid status to set the priority level that might be achieved on discharge, and admission status which would reflect improvement from worsened admission status because of the acute illness. From the clinician's point of view, the earliest possible time point is desirable in predicting outcomes for triage and planning care interventions. Using pre-morbid and admission information elderly patients with higher and persistent care needs can be identified in the beginning of the acute care episode.
Decision making tools of this nature require standardized assessments and systematic data collection during each acute hospital stay. Active seeking of pre-morbid information is crucial. Well-designed integrated electronic records might be helpful. In cases where earlier admissions exist or home care services are already in use, it is easier to receive relevant information, especially if systematic and integrated assessment systems have been adopted.
There are some limitations in our study. The data were collected from different hospitals, one in each Nordic country and eight in Ontario, Canada. There may be differences in both who and how the patients are admitted to hospital and also regarding discharge what kind of support systems are available in the communities. There are country specific differences in availability of informal care, which seemed to be higher among older patients in Canadian hospitals. That might reflect to our results in which discharge home had higher predictions (AUC's where higher) for Canadian than Nordic hospitals. There might be also differences in the overall health of older population in different countries which might affect the results. However, based on the frailty and other risk factors, it seems that the MAPLe-AC algorithm can set priority levels for acute care patients, and there is certain tendency for predicting the discharge destination or death during one year.
The MAPLe-AC algorithm uses fewer items than in the original MAPLe-HC. The home environment questions, wandering, and dressing were not available in interRAI-AC instrument. The environmental questions are important when planning discharge and should be taken into consideration in addition to MAPLe-AC information, especially after a stroke or a hip fracture and among high and very high priority clients.
Further research is needed to define how best to use the information the MAPLe-AC algorithm provides for decision making in clinical practice. The MAPLe-AC algorithm should not be an automatic decision-making tool, but instead provide a chance to combine important information over different periods during the acute hospital episode, and provide information for the use of the professionals in the care pathway of the older person with acute illness.