Service Delivery Models to Maximize Quality of Life for Older People at the End of Life: A Rapid Review

Policy Points We identified two overarching classifications of integrated geriatric and palliative care to maximize older people's quality of life at the end of life. Both are oriented to person-centered care, but with differing emphasis on either function or symptoms and concerns. Policymakers should both improve access to palliative care beyond just the last months of life and increase geriatric care provision to maintain and optimize function. This would ensure that continuity and coordination for potentially complex care needs across the continuum of late life would be maintained, where the demarcation of boundaries between healthy aging and healthy dying become increasingly blurred. Our findings highlight the urgent need for health system change to improve end-of-life care as part of universal health coverage. The use of health services should be informed by the likelihood of benefits and intended outcomes rather than on prognosis.

CONTEXT

In an era of unprecedented global aging, a key priority is to align health and social services for older populations in order to support the dual priorities of living well while adapting to a gradual decline in function. We aimed to provide a comprehensive synthesis of evidence regarding service delivery models that optimize the quality of life (QoL) for older people at the end of life across health, social, and welfare services worldwide.

METHODS

We conducted a rapid scoping review of systematic reviews. We searched MEDLINE, CINAHL, EMBASE, and CDSR databases from 2000 to 2017 for reviews reporting the effectiveness of service models aimed at optimizing QoL for older people, more than 50% of whom were older than 60 and in the last one or two years of life. We assessed the quality of these included reviews using AMSTAR and synthesized the findings narratively.

RESULTS

Of the 2,238 reviews identified, we included 72, with 20 reporting meta-analysis. Although all the World Health Organization (WHO) regions were represented, most of the reviews reported data from the Americas (52 of 72), Europe (46 of 72), and/or the Western Pacific (28 of 72). We identified two overarching classifications of service models but with different target outcomes: Integrated Geriatric Care, emphasizing physical function, and Integrated Palliative Care, focusing mainly on symptoms and concerns. Areas of synergy across the overarching classifications included person-centered care, education, and a multiprofessional workforce. The reviews assessed 117 separate outcomes. A meta-analysis demonstrated effectiveness for both classifications on QoL, including symptoms such as pain, depression, and psychological well-being. Economic analysis and its implications were poorly considered.

CONCLUSIONS

Despite their different target outcomes, those service models classified as Integrated Geriatric Care or Integrated Palliative Care were effective in improving QoL for older people nearing the end of life. Both approaches highlight the imperative for integrating services across the care continuum, with service involvement triggered by the patient's needs and likelihood of benefits. To inform the sustainability of health system change we encourage economic analyses that span health and social care and examine all sources of finance to understand contextual inequalities.

AN EVOLUTIONARY ALGORITHM FOR PURE FUZZY FLOWSHOP SCHEDULING PROBLEMS

The pure flowshop scheduling problem is here investigated from a perspective considering me uncertainty associated with the execution of shop floor activities. Being the flowshop problem is NP complete, a large number of heuristic algorithms have been proposed in literature to determine an optimal solution. Unfortunately, these algorithms usually assume a simplifying hypothesis: the problem data are assumed as deterministic, i.e. job processing times and the due dates are expressed through a unique value, which does not reflect the real process variability. For this reason, some authors have recently proposed the use of a fuzzy set theory to model the uncertainty in scheduling problems. In this paper, a proper genetic algorithm has been developed for solving the fuzzy flowshop scheduling problem. The optimisation involves two different objectives: the completion time minimisation and the due date fulfilment; both the single and multi-objective configurations have been considered. A new ranking criterion has been proposed and its performance has been tested through a set of test problems. A numerical analysis confirms the efficiency of the proposed optimisation procedure.