What is stable pain control? A prospective longitudinal study to assess the clinical value of a personalized pain goal.

BACKGROUND: A universal consensus regarding standardized pain outcomes does not exist. The personalized pain goal has been suggested as a clinically relevant outcome measure. AIM: To assess the feasibility of obtaining a personalized pain goal and to compare a clinically based personalized pain goal definition versus a research-based study definition for stable pain. DESIGN: Prospective longitudinal descriptive study. MEASURES: The attending physician completed routine assessments, including a personalized pain goal and the Edmonton Classification System for Cancer Pain, and followed patients daily until stable pain control, death, or discharge. Stable pain for cognitively intact patients was defined as pain intensity less than or equal to desired pain intensity goal (personalized pain goal definition) or pain intensity ⩽3 (Edmonton Classification System for Cancer Pain study definition) for three consecutive days with <3 breakthroughs per day. SETTING/PARTICIPANTS: A total of 300 consecutive advanced cancer patients were recruited from two acute care hospitals and a tertiary palliative care unit. RESULTS: In all, 231/300 patients (77%) had a pain syndrome; 169/231 (73%) provided a personalized pain goal, with 113/169 (67%) reporting a personalized pain goal ⩽3 (median = 3, range = 0-10). Using the personalized pain goal definition as the gold standard, sensitivity and specificity of the Edmonton Classification System for Cancer Pain definition were 71.3% and 98.5%, respectively. For mild (0-3), moderate (4-6), and severe (7-10) pain, the highest sensitivity was for moderate pain (90.5%), with high specificity across all three categories (95%-100%). CONCLUSION: The personalized pain goal is a feasible outcome measure for cognitively intact patients. The Edmonton Classification System for Cancer Pain definition closely resembles patient-reported personalized pain goals for stable pain and would be appropriate for research purposes. For clinical pain management, it would be important to include the personalized pain goal as standard practice.

Impact of Adding a Pictorial Display to Enhance Recall of Cancer Patient Histories: A Randomized Trial.

CONTEXT: Current health care delivery models have increased the need for safe and concise patient handover. Handover interventions in the literature have focused on the use of structured tools but have not evaluated their ability to facilitate retention of patient information. OBJECTIVES: In this study, mock pictorial displays were generated in an attempt to create a snapshot of each patient's medical and social circumstances. These pictorial displays contained the patient's photograph and other disease- and treatment-related images. The objective of this randomized trial was to assess the ability of these snapshots to enhance delayed information recall by care providers. METHODS: Participating physicians were given four advanced cancer patient histories to review, two at a time over two weeks. Pictorial image displays, referred to as the Electronic Whiteboard (EWB) were added, in a randomized manner to half of the textual histories. The impact of the EWB on information recall was tested in immediate and delayed time frames. RESULTS: Overall, patient information recall declined significantly over time, with or without the EWB. Still, this trial demonstrates significantly higher test scores after 24 hours with the addition of pictures to textual patient information, compared with textual information alone (P = 0.0002). A more modest improvement was seen with the addition of the EWB for questionnaires administered immediately after history review (P = 0.008). Most participants agreed that the EWB was a useful enhancement and that seeing a patient's photograph improved their ability to retain information. CONCLUSION: Most studies examining the institution of handover protocols in the health care setting have failed to harness the power of pictures and other representative images. This study demonstrates the ability of pictorial displays to improve both immediate and delayed recall of patient histories without increasing review time. These types of displays may be amenable to generation by software programs and have the potential to enhance information transfer in various settings.

Clinical prediction survival of advanced cancer patients by palliative care: a multi-site study.

AIMS: This study examined (1) accuracy of clinician prediction of survival (CPS) by palliative practitioners on first assessment with the use of standardised palliative tools, (2) factors affecting accuracy, (3) potential impact on clinical care. METHODS: A multi-site prospective study (n=1530) was used. CPS was divided into four time periods (<=2wks, >2 to 6wks, >6 to 12wks and >12wks). Multivariate analysis was assessed on six predictor variables. RESULTS: Overall, median survival of the sample was only 5 weeks. CPS category was accurate only 38.6% of the time, with 44.6% patients dying before the predicted time period. Of six candidate variables, on multivariate analysis only (i) the clinical time periods themselves and (ii) Palliative Performance Scale <=50 predicted for prognostic accuracy. CONCLUSION: CPS, even by palliative practitioners, remains overly optimistic with the existence of the horizon effect. This raises the question in that these individuals may have been potentially overtreated.

A brief review of survival prediction of advanced cancer patients.

Survival prediction of advanced cancer patients remains an important task for palliative clinicians. It has transformed from an art form into a more scientific branch of the discipline with the evolution of palliative medicine and use of statistical estimates of survival. Both clinician predicted survival and actuarial estimation of survival have their uses and drawbacks. This article gives a practical and quick summary of the pros and cons of clinician survival prediction and actuarial-based prognostic tools used at the bedside.

Uncertain cancer diagnosis: the expanded role of the palliative care consultant.

BACKGROUND: As attending physicians in acute care hospitals consult palliative care services earlier for patients with a life-threatening illness, the role of the palliative care consultant (PCC) may expand, especially when there is diagnostic uncertainty. METHOD: The expanding role of the PCC and the complexities associated with earlier referral are illustrated by describing the case of a patient with an uncertain diagnosis. CONCLUSION: The diagnostic uncertainty that accompanies earlier palliative care consultation may hamper the PCC's ability to establish goals of care and the appropriateness of hospice palliative care unit admission. Attempts at resolving this diagnostic uncertainty may lead to an expanded role for the PCC, which ideally will occur in collaboration with the primary care team.

Impact of infections on the survival of hospitalized advanced cancer patients.

CONTEXT: Advanced cancer patients remain highly susceptible to infections, leading to significant morbidity and mortality. A lack of consensus on the management of infections in this population stems from the heterogeneity of the patient group, divergent goals of care, and unknown prognosis with antibiotic treatment. OBJECTIVES: This prospective single cohort study examined the impact of infection and its treatment on the survival of hospitalized advanced cancer patients compared with a similar cohort without infection. METHODS: A total of 441 patients were referred to the palliative care (PC) consult service in a tertiary hospital over a 12-month period. The occurrence of sepsis, organ-related infection, and antibiotic use were recorded on initial PC consult. Survival was calculated from the point of PC consult to the date of death. RESULTS: Of these patients, 16.6% suffered a recent episode of sepsis (with or without an identifiable organ-related infection) and 23.4% had a recent episode of organ-related infection without clinically evident sepsis. Among the patients with sepsis, organ-related infection, or both, 89.7% received antibiotics (intravenous, oral, or both). Median survival of septic and nonseptic patients was 15 and 42 days, respectively. Septic patients who responded poorly to treatment (nonresponders) had a median survival of five days vs. 142 days in good responders. This equates with a hazard ratio of 9.74 for death in antibiotic nonresponders (P<0.05). Median survival for patients with an untreated organ-related infection (no sepsis) was 27 days compared with 48 days in a similar cohort receiving antibiotic therapy. Among patients on IV antibiotics, nonresponders had a median survival of six days vs. 108 days in responders. For patients on oral antibiotics, nonresponders had a median survival of six days vs. 70 days in responders. CONCLUSION: These findings suggest that a recent episode of sepsis and/or organ-related infection significantly reduces overall patient survival. Favorable antibiotic response is associated with an increase in median survival. These findings suggest that antibiotic treatment may prolong survival, and a time-limited trial may be indicated contingent on goals of care.

Evaluation of the Palliative Prognostic Score (PaP) and routinely collected clinical data in prognostication of survival for patients referred to a palliative care consultation service in an acute care hospital.

CONTEXT: Patients, caregivers, and clinicians require high levels of information regarding prognosis when conditions are incurable. OBJECTIVES: 1) To validate the Palliative Prognostic Score (PaP) and 2) to evaluate prognostic capacity of used clinical tools and the diagnosis of delirium, in a population referred to a palliative care consultation service at a Canadian acute care hospital. METHODS: This was a prospective observational cohort study on survival prediction based on the PaP and routinely collected clinical data, including the Palliative Performance Scale (PPS) and the Folstein Mini-Mental State Examination (MMSE). Kaplan-Meier survival curves, log-rank tests for significant differences between survival curves, and the Cox proportional hazards model were used to identify the relationship between the hazard ratio for death and the above variables. RESULTS: Nine hundred fifty-eight cases underwent final analysis, of which 181 (19%) had a noncancer diagnosis. Median and mean survival were 35 and 131 days, respectively. The three groups, divided based on different ranges of PaP, had significantly different survival curves, with 30-day-survival rates of 78%, 55%, and 11%. Age, PPS, and PaP remained significantly associated with survival, whereas diagnosis group, MMSE, and delirium became insignificant, despite lower hazard of death for cancer vs. noncancer and higher hazard for abnormal vs. normal MMSE and presence vs. absence of delirium. CONCLUSION: The PaP was successfully validated in a population with characteristics that extend beyond those of the population in which it was originally developed. This is the largest sample in which the PaP has been validated to date.