The 4Cs of Disaster Partnering: Communication, Coordination, Cooperation and Collaboration

Public, nonprofit and private organisations respond to large-scale disasters domestically and overseas. Critics of these assistance efforts, as well as those involved, often cite poor interorganisational partnering as an obstacle to successful disaster response. Observers frequently call for ‘more’ and ‘better’ partnering. We found important qualitative distinctions existed within partnering behaviours. We identified four different types of interorganisational partnering activities often referred to interchangeably: communication, cooperation, coordination and collaboration—the Four Cs. We derived definitions of the Four Cs from the partnering literature. We then tested them in a case study of the response to the 2010 Haiti earthquake. We suggest that the Four Cs are distinct activities, that organisations are typically strong or weak in one or more for various reasons, and that the four terms represent a continuum of increased interorganisational embeddedness in partnering activities.

An evaluation of palliative care services for cancer patients in the Southern Health and Social Services Board of Northern Ireland.

An interview study of 55 lay carers of people who died from cancer in the Southern Board of Northern Ireland was undertaken using a combination of closed-format and open-ended questions. The aim of the study was to evaluate palliative care services delivered in the last six months of their lives to cancer patients who died either at home or in hospital. Two-thirds of the deaths (36) occurred in the domestic home, 45 of the deceased were admitted as hospital inpatients, and the great majority were in receipt of community nursing (53) and general practitioner (54) services. Open-ended questions were used to allow respondents to give their views about services in some detail and their views about good and bad aspects of services were sought. While they were generally satisfied with services specific areas of difficulty were identified in each aspect of care addressed by the study. The most favourable assessments were made of community nursing with the greatest number of negative comments being made about inpatient hospital care. Differing interests between some of those who were dying and their lay carers were found in two areas: the receipt of help from nonfamily members and the information that the deceased received about their terminal status.

The Effect of Community-Based Specialist Palliative Care Teams on Place of Care

BACKGROUND: Prior research on community-based specialist palliative care teams used outcome measures of place of death and/or dichotomous outcome measures of acute care use in the last two weeks of life. However, existing research seldom measured the diverse places of care used and their timing prior to death.

OBJECTIVE: The study objective was to examine the place of care in the last 30 days of life.

METHODS: In this retrospective cohort study, patients who received care from a specialist palliative care team (exposed) were matched by propensity score to patients who received usual care in the community (unexposed) in Ontario, Canada. Measured was the percentage of patients in each place of care in the last month of life as a proportion of the total cohort.

RESULTS: After matching, 3109 patients were identified in each group, where 79% had cancer and 77% received end-of-life home care. At 30 days compared to 7 days before death, the exposed group's proportions rose from 33% to 41% receiving home care and 14% to 15% in hospital, whereas the unexposed group's proportions rose from 28% to 32% receiving home care and 16% to 22% in hospital. Linear trend analysis (proportion over time) showed that the exposed group used significantly more home care services and fewer hospital days (p < 0.001) than the unexposed group. On the last day of life (place of death), the exposed group had 18% die in an in-patient hospital bed compared to 29% in usual care.

CONCLUSION: Examining place of care in the last month can effectively illustrate the service use trajectory over time.