Free-text analysis of general practice out-of-hours (GPOOH) use by people with advanced cancer: an analysis of coded and uncoded free-text data.

BACKGROUND: People with advanced cancer frequently use the GP out-of-hours (GPOOH) service. Considerable amounts of routine GPOOH data are uncoded. Therefore, these data are omitted from existing healthcare datasets. AIM: To conduct a free-text analysis of a GPOOH dataset, to identify reasons for attendance and care delivered through GPOOH to people with advanced cancer. DESIGN AND SETTING: An analysis of a GPOOH healthcare dataset was undertaken. It contained all coded and free- text information for 5749 attendances from a cohort of 2443 people who died from cancer in Tayside, Scotland, from 2013-2015. METHOD: Random sampling methods selected 575 consultations for free-text analysis. Each consultation was analysed by two independent reviewers to determine the following: assigned presenting complaints; key and additional palliative care symptoms recorded in free text; evidence of anticipatory care planning; and free-text recording of dispensed medications. Inter-rater reliability concordance was established through Kappa testing. RESULTS: More than half of all coded reasons for attendance (n = 293; 51.0%) were 'other' or 'missing'. Free-text analysis demonstrated that nearly half (n = 284; 49.4%) of GPOOH attendances by people with advanced cancer were for pain or palliative care. More than half of GPOOH attendances (n = 325; 56.5%) recorded at least one key or additional palliative care symptom in free text, with the commonest being breathlessness, vomiting, cough, and nausea. Anticipatory care planning was poorly recorded in both coded and uncoded records. Uncoded medications were dispensed in more than one- quarter of GPOOH consultations. CONCLUSION: GPOOH delivers a substantial amount of pain management and palliative care, much of which is uncoded. Therefore, it is unrecognised and under-reported in existing large healthcare data analyses.

Real time remote symptom monitoring during chemotherapy for cancer: European multicentre randomised controlled trial (eSMART).

OBJECTIVE: To evaluate effects of remote monitoring of adjuvant chemotherapy related side effects via the Advanced Symptom Management System (ASyMS) on symptom burden, quality of life, supportive care needs, anxiety, self-efficacy, and work limitations. DESIGN: Multicentre, repeated measures, parallel group, evaluator masked, stratified randomised controlled trial. SETTING: Twelve cancer centres in Austria, Greece, Norway, Republic of Ireland, and UK. PARTICIPANTS: 829 patients with non-metastatic breast cancer, colorectal cancer, Hodgkin's disease, or non-Hodgkin's lymphoma receiving first line adjuvant chemotherapy or chemotherapy for the first time in five years. INTERVENTION: Patients were randomised to ASyMS (intervention; n=415) or standard care (control; n=414) over six cycles of chemotherapy. MAIN OUTCOME MEASURES: The primary outcome was symptom burden (Memorial Symptom Assessment Scale; MSAS). Secondary outcomes were health related quality of life (Functional Assessment of Cancer Therapy-General; FACT-G), Supportive Care Needs Survey Short-Form (SCNS-SF34), State-Trait Anxiety Inventory-Revised (STAI-R), Communication and Attitudinal Self-Efficacy scale for cancer (CASE-Cancer), and work limitations questionnaire (WLQ). RESULTS: For the intervention group, symptom burden remained at pre-chemotherapy treatment levels, whereas controls reported an increase from cycle 1 onwards (least squares absolute mean difference -0.15, 95% confidence interval -0.19 to -0.12; P<0.001; Cohen's D effect size=0.5). Analysis of MSAS sub-domains indicated significant reductions in favour of ASyMS for global distress index (-0.21, -0.27 to -0.16; P<0.001), psychological symptoms (-0.16, -0.23 to -0.10; P<0.001), and physical symptoms (-0.21, -0.26 to -0.17; P<0.001). FACT-G scores were higher in the intervention group across all cycles (mean difference 4.06, 95% confidence interval 2.65 to 5.46; P<0.001), whereas mean scores for STAI-R trait (-1.15, -1.90 to -0.41; P=0.003) and STAI-R state anxiety (-1.13, -2.06 to -0.20; P=0.02) were lower. CASE-Cancer scores were higher in the intervention group (mean difference 0.81, 0.19 to 1.43; P=0.01), and most SCNS-SF34 domains were lower, including sexuality needs (-1.56, -3.11 to -0.01; P<0.05), patient care and support needs (-1.74, -3.31 to -0.16; P=0.03), and physical and daily living needs (-2.8, -5.0 to -0.6; P=0.01). Other SCNS-SF34 domains and WLQ were not significantly different. Safety of ASyMS was satisfactory. Neutropenic events were higher in the intervention group. CONCLUSIONS: Significant reduction in symptom burden supports the use of ASyMS for remote symptom monitoring in cancer care. A "medium" Cohen's effect size of 0.5 showed a sizable, positive clinical effect of ASyMS on patients' symptom experiences. Remote monitoring systems will be vital for future services, particularly with blended models of care delivery arising from the covid-19 pandemic. TRIAL REGISTRATION: Clinicaltrials.gov NCT02356081.