MAPLe provides an empirically sound decision-support system that will allow case managers to make more systematic evaluations of the needs of clients and the urgency with which they should respond to those needs. Using three different outcomes, with validation results in six countries, MAPLe clearly differentiated the risk of adverse outcomes, including institutionalization. Case managers who have completed an RAI-HC assessment can obtain the MAPLe results automatically from software in which the algorithm is embedded and these results then provide a context against which person-specific service recommendations may be made. It should be noted, however, that the intent is not to use MAPLe as an automated decision-making system devoid of clinical judgment. Instead, case managers considering MAPLe scores should also engage in a full discussion with the client, family, and other formal service providers to develop person-specific recommendations that take into account the individual's strengths, preferences, and needs. For example, some clients who score low on the MAPLe algorithm may rate themselves as being in poor health, may be showing signs of depression, or may have had an overnight hospital stay or frequent emergency room visits. It would be inappropriate to treat such an individual as an 'information and referral only' client if the case manager believes these other clinical considerations to be of critical importance. On the other hand, individuals in the very high MAPLe category do not necessarily require immediate nursing home placement because, for example, they may have family members who are both willing and able to address their current level of need in the community. Similarly, alternative housing arrangements may provide these individuals with the appropriate resources to remain relatively independent with access to formal supports when needed.
While MAPLe may be used to make person-centered resource allocation decisions at the individual level, it may also be used as a monitoring system at the regional, organizational, national, and international levels to evaluate practice patterns. That is, one may stratify populations according to MAPLe levels and then compare the performance of home care agencies with respect to outcomes of care within MAPLe levels. Such a benchmarking system may be used to identify jurisdictions where MAPLe-adjusted nursing home admissions, for example, are higher than expected based on the experience of other regions. Similarly, MAPLe levels at intake can be used to examine regional variations in access to services by level of need.
The introduction of MAPLe into normal, daily use in home care can be expected to have an impact on the nature of services provided by agencies. That is, clients with lower MAPLe levels will be less likely to receive services than they may have been in the past, and clients with higher MAPLe levels will presumably be more likely to access those services because they are more readily identifiable. That being said, it is not necessarily true that subgroups of home care clients need to be excluded from all services based on low MAPLe scores. The choice of who receives services and what type of services are provided remains a value-based decision to be made by policymakers and clinicians in each jurisdiction. In that regard, the cross-national results for MAPLe shown in Table 3 do not imply that some countries are providing services correctly while other countries erroneously target light-care clients. The main benefit of implementing MAPLe would be that persons with higher levels of need should be at a relatively higher level of priority for access to services than those with lower-level needs. That does not preclude the possibility of persons at the lowest level receiving appropriate services.
The present study made some important decisions regarding the role of informal support in the development of the prioritization system for community and institutional services. The choice to include measures of the informal support system (that is, caregiver stress) as a dependent variable rather than as an independent variable was important for methodological, clinical, and policy-related reasons. From a methodological perspective, the use of measures of informal support as independent variables would create a situation where those variables become highly vulnerable to systematic response bias in order to gain access to desired services when used in normal clinical practice. That is, if family members believe that saying they could do more to help a client would place their relative in a lower priority level, there would be a strong disincentive to making such claims. Therefore, any items reflecting the capacity of the informal network to provide care could become less valid after the implementation of such a system. The introduction of this type of bias will make it more difficult to differentiate between families who are showing clear signs of distress and those who have continued capacity to provide more services. From a policy perspective, one must be concerned about the potential unintended consequences of a steering effect that would result in family members being less likely to provide informal care. The capacity of the home care system to function adequately is heavily dependent on the provision of informal care by family members. Extreme caution should be taken with the introduction of policy measures that may provide disincentives to families to be involved. At the same time, distress among caregivers should be a concern to home care service providers and policy makers.
Although the present study showed that the MAPLe system is related to both the formal costs of service provision and hours of informal care, MAPLe is not intended to be an alternative to case-mix systems (for example, as an alternative to the RUG-III/HC  system). That being said, the introduction of MAPLe will have important implications for case-mix distributions in both home care and in long-term care facilities. As MAPLe begins to be used, one might expect the relative resource intensity of home care clients to increase because greater priority will be given to clients with higher levels of need. Similarly, to the extent that MAPLe is used as a decision-support system for nursing home placement, it is likely to result in a shifting of the distribution of new admissions to long-term care settings towards those community-based clients with the highest levels of need. Therefore, the introduction of MAPLe may have the effect of increasing case-mix or resource intensity in both home care and nursing home settings.
This study also demonstrates the benefits of using a grouping methodology, as with decision-tree analysis, compared with indexing systems that simply assign a linear increase in scores for any combination of variables. Unlike systems such as the RRIT or INST-RISK, MAPLe is able to consider the impact of specific combinations of variables (for example, cognitive impairment combined with functional impairment).
There was a remarkable level of cross-jurisdictional consistency in the MAPLe results. Although the slope of the relationship between the MAPLe scores and the dependent variables of interest were not always identical between jurisdictions, the relative increments in risk between MAPLe levels was very consistent in all of the countries examined. This is particularly surprising given the value differences underlying the provision of community-based services in these jurisdictions. Japan and Italy, for example, tend to be traditional in their expectation that family members will provide the bulk of care. It is therefore not surprising to see lower absolute levels of ratings that clients would be rated by themselves or by others as being better off elsewhere in these jurisdictions, compared with the Canadian results. On the other hand, in all jurisdictions, there was a rather consistent increase in the proportion of clients rated as being better off elsewhere with each increment in the MAPLe level. It would be useful to conduct future research in these other countries to determine the extent to which MAPLe is indeed predictive of actual institutionalization in those settings. In addition, it is important to recognize that clients, family members, and home care professionals may not always share the same view about the most appropriate care setting. These potentially different perspectives should be taken into account when determining what services would be most appropriate for a given client.
An important next step for research with the MAPLe system is to conduct intervention studies to determine the extent to which the level of risk associated with a given MAPLe category can be reduced. For example, could additional measures be put in place that would have the result of yielding a lower than expected institutionalization rate within a MAPLe category, or could the risk factors that have placed the client in that MAPLe category be reversed? For instance, falling is a major factor contributing to higher MAPLe scores. If a falls intervention was put in place that actually prevented future falls, conceivably, the individual's MAPLe scores would decline over time.
It will also be important to conduct research into the extent to which MAPLe is relevant to home care outcomes other than caregiver distress or nursing home placement. For example, it is not necessarily the case that clients with higher MAPLe scores feel more socially isolated or lonely or that they would benefit from interventions such as friendly visiting programs or transportation services. Therefore, it would be helpful to consider what comprises the full spectrum of benefits that could be realized through high-quality home care. This might be done through qualitative studies of home care clients, caregivers, case managers, and administrators. Once these benefits are identified, further research should be conducted on the effectiveness of MAPLe as a targeting system for persons at risk of adverse outcomes in other domain areas.
MAPLe also has potential benefits for the support of cross-national research. The problem that population-level information cannot be equated across jurisdictions is an important limitation of any home care research that is not based on individual-level observations. Indeed, results in Table 1 show that it would be a faulty assumption to believe that home care clients in Italy are comparable with home care clients in Ontario, for example. However, by using the MAPLe system to stratify samples with individual-level data, one could be more confident in the equivalence of samples being compared across two or more jurisdictions.