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Mining Twitter to Assess the Determinants of Health Behavior towards Palliative Care in the United States.

ABSTRACT: Palliative care is a specialized service with proven efficacy in improving patients' quality-of-life. Nevertheless, lack of awareness and misunderstanding limits its adoption. Research is urgently needed to understand the determinants (e.g., knowledge) related to its adoption. Traditionally, these determinants are measured with questionnaires. In this study, we explored Twitter to reveal these determinants guided by the Integrated Behavioral Model. A secondary goal is to assess the feasibility of extracting user demographics from Twitter data-a significant shortcoming in existing studies that limits our ability to explore more fine-grained research questions (e.g., gender difference). Thus, we collected, preprocessed, and geocoded palliative care-related tweets from 2013 to 2019 and then built classifiers to: 1) categorize tweets into promotional vs. consumer discussions, and 2) extract user gender. Using topic modeling, we explored whether the topics learned from tweets are comparable to responses of palliative care-related questions in the Health Information National Trends Survey.

SUBMITTER: Zhao Y

PROVIDER: S-EPMC7233059 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Mining Twitter to Assess the Determinants of Health Behavior towards Palliative Care in the United States.

Zhao Yunpeng Y Zhang Hansi H Huo Jinhai J Guo Yi Y Wu Yonghui Y Prosperi Mattia M Bian Jiang J

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science 20200530

Palliative care is a specialized service with proven efficacy in improving patients' quality-of-life. Nevertheless, lack of awareness and misunderstanding limits its adoption. Research is urgently needed to understand the determinants (e.g., knowledge) related to its adoption. Traditionally, these determinants are measured with questionnaires. In this study, we explored Twitter to reveal these determinants guided by the Integrated Behavioral Model. A secondary goal is to assess the feasibility o ...[more]

PMID: 32477696

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Project description:Importance:Although palliative care (PC) historically focused on patients with cancer and those near the end of life, evidence increasingly demonstrates a benefit to patients with a broad range of serious illnesses and to those earlier in their illness. The field of PC has expanded and evolved rapidly, resulting in a need to characterize practice over time to understand whether it reflects evolving evidence and guidelines. Objective:To characterize current practice and trends among patients cared for and outcomes achieved by inpatient specialty PC services in the United States. Design, Setting, and Participants:This retrospective cohort study was performed from January 1, 2013, to December 31, 2017, at 88 US hospitals in which PC teams voluntarily participate in the Palliative Care Quality Network (PCQN), a national quality improvement collaborative. A total of 135 197 patients were referred to PCQN teams during the study period. Initial analyses of the study data were conducted from March 3 to March 21, 2018. Exposure:Inpatient PC consultation. Main Outcomes and Measures:A total of 23 standardized data elements collected by PCQN teams that provided information about the characteristics of referred patients, including age, sex, Palliative Performance Scale score, and primary diagnosis leading to PC consult; reason(s) given for the consultation; and processes of care provided by the PC team, including disciplines involved, number of family meetings held, advance care planning documentation completed, and screened for and intervened on needs. Results:A total of 135 197 patients were referred to inpatient PC (51.0% female; mean age, 71.3 years [range, 57.8-82.5 years]) and were significantly debilitated (mean Palliative Performance Scale score, 34.7%; range, 14.9%-56.8%). Cancer was the most common primary diagnosis (32.0%; range, 11.3%-93.9%), although rates decreased from 2013 to 2017 (odds ratio [OR], 0.84; 95% CI, 0.79-0.91; P < .001). Pain and other symptoms were common and improved significantly during the consultation period (pain: χ2 = 5234.4, P < .001; anxiety: χ2 = 2020.7, P < .001; nausea: χ2 = 1311.8, P < .001; dyspnea: χ2 = 1993.5, P < .001). Most patients were discharged alive (78.7%; range, 44.7%-99.4%), and this number increased over time (OR, 1.36; 95% CI, 1.27-1.46; P < .001). Compared with 2013, rates of discharge referral to clinic-based (OR, 4.00; 95% CI, 2.95-5.43; P < .001) and home-based PC (OR, 2.63; 95% CI, 1.92-3.61; P < .001) also increased significantly by 2017, whereas referrals to hospice decreased (OR, 0.56; 95% CI, 0.51-0.62; P < .001). Conclusions and Relevance:Inpatient PC teams cared for an increasing percentage of patients with diagnoses other than cancer and saw more patients discharged alive, consistent with guidelines recommending specialty PC for all patients with serious illness earlier in their illnesses. Most patients with symptoms improved quickly. Variation in practice and outcomes among PCQN members suggests that there are opportunities for further improvements in care.

Project description:Palliative care improves quality-of-life and extends survival, however, is underutilized among gynecological cancer patients in the United States (U.S.). Our objective was to evaluate associations between healthcare access (HCA) measures and palliative care utilization among U.S. gynecological cancer patients overall and by race/ethnicity. We used 2004-2016 data from the U.S. National Cancer Database and included patients with metastatic (stage III-IV at-diagnosis) ovarian, cervical, and uterine cancer (n = 176,899). Palliative care was defined as non-curative treatment and could include surgery, radiation, chemotherapy, and pain management, or any combination. HCA measures included insurance type, area-level socioeconomic measures, distance-to-care, and cancer treatment facility type. We evaluated associations of HCA measures with palliative care use overall and by race/ethnicity using multivariable logistic regression. Our population was mostly non-Hispanic White (72%), had ovarian cancer (72%), and 24% survived <6 months. Five percent of metastatic gynecological cancer patients utilized palliative care. Compared to those with private insurance, uninsured patients with ovarian (aOR: 1.80,95% CI: 1.53-2.12), and cervical (aOR: 1.45,95% CI: 1.26-1.67) cancer were more likely to use palliative care. Patients with ovarian (aOR: 0.58,95% CI: 0.48-0.70) or cervical cancer (aOR: 0.74,95% CI: 0.60-0.88) who reside >45 miles from their provider were less likely to utilize palliative care than those within <2 miles. Ovarian cancer patients treated at academic/research programs were less likely to utilize palliative care compared to those treated at community cancer programs (aOR: 0.70, 95%CI: 0.58-0.84). Associations between HCA measures and palliative care utilization were largely consistent across U.S. racial-ethnic groups. Insurance type, cancer treatment facility type, and distance-to-care may influence palliative care use among metastatic gynecological cancer patients in the U.S.

Dataset Information

Mining Twitter to Assess the Determinants of Health Behavior towards Palliative Care in the United States.

Publications

Mining Twitter to Assess the Determinants of Health Behavior towards Palliative Care in the United States.

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