The effectiveness of a nurse practitioner-led pain management team in long-term care: A mixed methods study

BACKGROUND: Considering the high rates of pain as well as its under-management in long-term care (LTC) settings, research is needed to explore innovations in pain management that take into account limited resource realities. It has been suggested that nurse practitioners, working within an inter-professional model, could potentially address the under-management of pain in LTC.

OBJECTIVES: This study evaluated the effectiveness of implementing a nurse practitioner-led, inter-professional pain management team in LTC in improving (a) pain-related resident outcomes; (b) clinical practice behaviours (e.g., documentation of pain assessments, use of non-pharmacological and pharmacological interventions); and, (c) quality of pain medication prescribing practices.

METHODS: A mixed method design was used to evaluate a nurse practitioner-led pain management team, including both a quantitative and qualitative component. Using a controlled before-after study, six LTC homes were allocated to one of three groups: 1) a nurse practitioner-led pain team (full intervention); 2) nurse practitioner but no pain management team (partial intervention); or, 3) no nurse practitioner, no pain management team (control group). In total, 345 LTC residents were recruited to participate in the study; 139 residents for the full intervention group, 108 for the partial intervention group, and 98 residents for the control group. Data was collected in Canada from 2010 to 2012.

RESULTS: Implementing a nurse practitioner-led pain team in LTC significantly reduced residents' pain and improved functional status compared to usual care without access to a nurse practitioner. Positive changes in clinical practice behaviours (e.g., assessing pain, developing care plans related to pain management, documenting effectiveness of pain interventions) occurred over the intervention period for both the nurse practitioner-led pain team and nurse practitioner-only groups; these changes did not occur to the same extent, if at all, in the control group. Qualitative analysis highlighted the perceived benefits of LTC staff about having access to a nurse practitioner and benefits of the pain team, along with barriers to managing pain in LTC.

CONCLUSIONS: The findings from this study showed that implementing a nurse practitioner-led pain team can significantly improve resident pain and functional status as well as clinical practice behaviours of LTC staff. LTC homes should employ a nurse practitioner, ideally located onsite as opposed to an offsite consultative role, to enhance inter-professional collaboration and facilitate more consistent and timely access to pain management.

Coupling short-term (B2G model) and long-term (g-function) models for ground source heat exchanger simulation in TRNSYS. Application in a real installation

Ground-source heat pump (GSHP) systems represent one of the most promising techniques for heating and cooling in buildings. These systems use the ground as a heat source/sink, allowing a better efficiency thanks to the low variations of the ground temperature along the seasons. The ground-source heat exchanger (GSHE) then becomes a key component for optimizing the overall performance of the system. Moreover, the short-term response related to the dynamic behaviour of the GSHE is a crucial aspect, especially from a regulation criteria perspective in on/off controlled GSHP systems. In this context, a novel numerical GSHE model has been developed at the Instituto de Ingeniería Energética, Universitat Politècnica de València. Based on the decoupling of the short-term and the long-term response of the GSHE, the novel model allows the use of faster and more precise models on both sides. In particular, the short-term model considered is the B2G model, developed and validated in previous research works conducted at the Instituto de Ingeniería Energética. For the long-term, the g-function model was selected, since it is a previously validated and widely used model, and presents some interesting features that are useful for its combination with the B2G model. The aim of the present paper is to describe the procedure of combining these two models in order to obtain a unique complete GSHE model for both short- and long-term simulation. The resulting model is then validated against experimental data from a real GSHP installation.