Trends in opioid use over time: 1997 to 1999

Substantial resources have been spent to improve pain control for dying patients, and increased opioid administration has been presumed. Oregon has been a consistent leading state in per capita use for morphine for the past 10 years, as recorded by the Automation of Reports and Consolidated Orders System (ARCOS). Health policy experts, extrapolating from World Health Organization methods, have suggested these data are indicative of the quality of end-of-life care in Oregon. To determine whether trends in opioid prescription at the state and national levels reflect increased opioid use for inpatients during the final week of life, chart reviews were conducted to record all opioid medications administered in the last week of life to 877 adult inpatients who died from natural causes between January 1, 1997 and December 31, 1999. Inpatient morphine use did not increase significantly for dying patients from 1997 to 1999. However, overall morphine use for both Oregon and the United States as measured by ARCOS data increased significantly. Comparisons revealed no significant difference between linear trends for Oregon and U.S. morphine use, but both were significantly greater than the dying inpatients. This pattern was also found for all other opioids. These findings suggest that ARCOS data do not necessarily provide information about opioid use for specific subpopulations of patients and raise questions about the meaning of observed increases in ARCOS data

Adherence and Concordance between Serious Illness Care Planning Conversations and Oncology Clinician Documentation among Patients with Advanced Cancer

Background:Serious illness conversations are part of advance care planning (ACP) and focus on prognosis, values, and goals in patients who are seriously ill. To be maximally effective, such conversations must be documented accurately and be easily accessible. Objectives:The two coprimary objectives of the study were to assess concordance between written documentation and recorded audiotaped conversations, and to evaluate adherence to the Serious Illness Conversation Guide questions. Methods:Data were obtained as part of a trial in patients with advanced cancer. Clinicians were trained to use a guide to conduct and document serious illness conversations. Conversations were audiotaped. Two researchers independently compared audiorecordings with the corresponding documentation in an electronic health record (EHR) template and free-text progress notes, and rated the degree of concordance and adherence. Results:We reviewed a total of 25 audiorecordings. Clinicians addressed 87% of the conversation guide elements. Prognosis was discussed least frequently, only in 55% of the patients who wanted that information. Documentation was fully concordant with the conversation 43% of the time. Concordance was best when documenting family matters and goals, and least frequently concordant when documenting prognostic communication. Most conversations (64%) were documented in the template, a minority (28%) only in progress notes and two conversations (8%) were not documented. Concordance was better when the template was used (62% vs. 28%). Conclusion:Clinicians adhered well to the conversation guide. However, key information elicited was documented and fully concordant less than half the time. Greater concordance was observed when clinicians used a prespecified template. The combined use of a guide and EHR template holds promise for ACP conversations

A Qualitative Study of Serious Illness Conversations in Patients with Advanced Cancer

BACKGROUND: Conversations with seriously ill patients about their values and goals have been associated with reduced distress, a better quality of life, and goal-concordant care near the end of life. Yet, little is known about how such conversations are conducted. OBJECTIVE: To characterize the content of serious illness conversations and identify opportunities for improvement. DESIGN: Qualitative analysis of audio-recorded, serious illness conversations using an evidence-based guide and obtained through a cluster randomized controlled trial in an outpatient oncology setting. Setting/Measurements: Clinicians assigned to the intervention arm received training to use the "Serious Illness Conversation Guide" to have a serious illness conversation about values and goals with advanced cancer patients. Conversations were de-identified, transcribed verbatim, and independently coded by two researchers. Key themes were analyzed. RESULTS: A total of 25 conversations conducted by 16 clinicians were evaluated. The median conversation duration was 14 minutes (range 4-37), with clinicians speaking half of the time. Thematic analyses demonstrated five key themes: (1) supportive dialogue between patients and clinicians; (2) patients' openness to discuss emotionally challenging topics; (3) patients' willingness to articulate preferences regarding life-sustaining treatments; (4) clinicians' difficulty in responding to emotional or ambiguous patient statements; and (5) challenges in discussing prognosis. CONCLUSIONS: Data from this exploratory study suggest that seriously ill patients are open to discussing values and goals with their clinician. Yet, clinicians may struggle when disclosing a time-based prognosis and in responding to patients' emotions. Such skills should be a focus for additional training for clinicians caring for seriously ill patients

Antimicrobial Use for Symptom Management in Patients Receiving Hospice and Palliative Care: A Systematic Review

BACKGROUND: Patients receiving hospice or palliative care often receive antimicrobial therapy; however the effectiveness of antimicrobial therapy for symptom management in these patients is unknown. OBJECTIVE: The study’s objective was to systematically review and summarize existing data on the prevalence and effectiveness of antimicrobial therapy to improve symptom burden among hospice or palliative care patients. DESIGN: Systematic review of articles on microbial use in hospice and palliative care patients published from January 1, 2001 through June 30, 2011. MEASUREMENTS: We extracted data on patients’ underlying chronic condition and health care setting, study design, prevalence of antimicrobial use, whether symptom response following antimicrobial use was measured, and the method for measuring symptom response. RESULTS: Eleven studies met our inclusion criteria in which prevalence of antimicrobial use ranged from 4% to 84%. Eight studies measured symptom response following antimicrobial therapy. Methods of symptom assessment were highly variable and ranged from clinical assessment from patients’ charts to the Edmonton Symptom Assessment Scale. Symptom improvement varied by indication, and patients with urinary tract infections (two studies) appeared to experience the greatest improvement following antimicrobial therapy (range 67% to 92%). CONCLUSION: Limited data are available on the use of antimicrobial therapy for symptom management among patients receiving palliative or hospice care. Future studies should systematically measure symptom response and control for important confounders to provide useful data to guide antimicrobial use in this population

Frequency of Outpatient Antibiotic Prescription on Discharge to Hospice Care

The use of antibiotics is common in hospice care despite limited evidence that it improves symptoms or quality of life. Patients receiving antibiotics upon discharge from a hospital may be more likely to continue use following transition to hospice care despite a shift in the goals of care. We quantified the frequency and characteristics for receiving a prescription for antibiotics on discharge from acute care to hospice care. This was a cross-sectional study among adult inpatients (≥18 years old) discharged to hospice care from Oregon Health & Science University (OHSU) from 1 January 2010 to 31 December 2012. Data were collected from an electronic data repository and from the Department of Care Management. Among 62,792 discharges, 845 (1.3%) patients were discharged directly to hospice care (60.0% home and 40.0% inpatient). Most patients discharged to hospice were >65 years old (50.9%) and male (54.6%) and had stayed in the hospital for ≤7 days (56.6%). The prevalence of antibiotic prescription upon discharge to hospice was 21.1%. Among patients discharged with an antibiotic prescription, 70.8% had a documented infection during their index admission. Among documented infections, 40.3% were bloodstream infections, septicemia, or endocarditis, and 38.9% were pneumonia. Independent risk factors for receiving an antibiotic prescription were documented infection during the index admission (adjusted odds ratio [AOR]=7.00; 95% confidence interval [95% CI]=4.68 to 10.46), discharge to home hospice care (AOR=2.86; 95% CI=1.92 to 4.28), and having a cancer diagnosis (AOR=2.19; 95% CI=1.48 to 3.23). These data suggest that a high proportion of patients discharged from acute care to hospice care receive an antibiotic prescription upon discharge

Patient Identification for Serious Illness Conversations : A Scoping Review

Serious illness conversations aim to align medical care and treatment with patients' values, goals, priorities, and preferences. Timely and accurate identification of patients for serious illness conversations is essential; however, existent methods for patient identification in different settings and population groups have not been compared and contrasted. This study aimed to examine the current literature regarding patient identification for serious illness conversations within the context of the Serious Illness Care Program and/or the Serious Illness Conversation Guide. A scoping review was conducted using the Joanna Briggs Institute guidelines. A comprehensive search was undertaken in four databases for literature published between January 2014 and September 2021. In total, 39 articles met the criteria for inclusion. This review found that patients were primarily identified for serious illness conversations using clinical/diagnostic triggers, the 'surprise question', or a combination of methods. A diverse assortment of clinicians and non-clinical resources were described in the identification process, including physicians, nurses, allied health staff, administrative staff, and automated algorithms. Facilitators and barriers to patient identification are elucidated. Future research should test the efficacy of adapted identification methods and explore how clinicians inform judgements surrounding patient identification