Digital Outpatient Services for Adults: Development of an Intervention and Protocol for a Multicenter Non–Randomized Controlled Trial

Background: Health care services are being challenged by an increasing number of patients and limited resources. Hence, research investigating options to reduce costs and increase effectiveness is warranted. Digital outpatient services can provide flexible and tailored follow-up, improve patients’ health literacy, and facilitate the identification of adverse courses of disease. However, previous research largely focused on disease-specific contexts and outcomes. Therefore, research on digital services investigating generic outcomes such as health literacy is warranted. Objective: This article aims to describe the “digital outpatient service” intervention and present the protocol for an ongoing multicenter, nonrandomized trial evaluating this intervention. Methods: Based on previous experiences and evidence-based knowledge, we developed this intervention through patient-journey maps in collaboration with each clinical specialty. The patients gain access to a mobile app for self-monitoring and patient-reported outcomes and a chat for contact between the patients and health care workers. The health care workers’ dashboard includes a traffic light system to draw attention to the most urgent patient reports. In this multicenter, non–randomized controlled trial, patients are allocated to the control group receiving standard care or the 6-month intervention. Eligible patients are aged 18 years or older who receive outpatient care at the neurology, lung, pain, or cancer departments at 2 university hospitals in Norway. Our evaluation will include patient-reported outcomes, qualitative interviews, and clinical measures. The primary outcome will be health literacy using the Health Literacy Questionnaire. A sample size of 165 participants is split into a 1:2 ratio in favor of the intervention. We will analyze quantitative data in SPSS (IBM Corp) using descriptive statistics and logistic regression, and qualitative data using thematic analysis. Results: This trial started in September 2021, and the intervention started in January 2022. Recruitment has ended, with 55 patients in the control group and 107 patients in the intervention group. Follow-up is expected to end in July 2023, with results expected to be obtained in December 2023. Conclusions: This study will evaluate an intervention facilitated by an already certified digital multicomponent solution, with intervention content based on patient-reported outcomes, health literacy, and self-monitoring. The intervention is specifically tailored to each participating center and the needs of their patients using patient journey maps. The comprehensive and generic evaluation of this digital outpatient service intervention is a strength as it targets a heterogeneous sample of patients. Thus, this study will provide important knowledge about the applicability and effects of digital health care services. As a result, patients and health care workers will gain a new, evidence-based understanding of whether and how digital tools may be used in clinical care.Background: Health care services are being challenged by an increasing number of patients and limited resources. Hence, research investigating options to reduce costs and increase effectiveness is warranted. Digital outpatient services can provide flexible and tailored follow-up, improve patients’ health literacy, and facilitate the identification of adverse courses of disease. However, previous research largely focused on disease-specific contexts and outcomes. Therefore, research on digital services investigating generic outcomes such as health literacy is warranted.<p

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

Evidence synthesis to inform model-based cost-effectiveness evaluations of diagnostic tests: a methodological systematic review of health technology assessments

Background: Evaluations of diagnostic tests are challenging because of the indirect nature of their impact on patient outcomes. Model-based health economic evaluations of tests allow different types of evidence from various sources to be incorporated and enable cost-effectiveness estimates to be made beyond the duration of available study data. To parameterize a health-economic model fully, all the ways a test impacts on patient health must be quantified, including but not limited to diagnostic test accuracy. Methods: We assessed all UK NIHR HTA reports published May 2009-July 2015. Reports were included if they evaluated a diagnostic test, included a model-based health economic evaluation and included a systematic review and meta-analysis of test accuracy. From each eligible report we extracted information on the following topics: 1) what evidence aside from test accuracy was searched for and synthesised, 2) which methods were used to synthesise test accuracy evidence and how did the results inform the economic model, 3) how/whether threshold effects were explored, 4) how the potential dependency between multiple tests in a pathway was accounted for, and 5) for evaluations of tests targeted at the primary care setting, how evidence from differing healthcare settings was incorporated. Results: The bivariate or HSROC model was implemented in 20/22 reports that met all inclusion criteria. Test accuracy data for health economic modelling was obtained from meta-analyses completely in four reports, partially in fourteen reports and not at all in four reports. Only 2/7 reports that used a quantitative test gave clear threshold recommendations. All 22 reports explored the effect of uncertainty in accuracy parameters but most of those that used multiple tests did not allow for dependence between test results. 7/22 tests were potentially suitable for primary care but the majority found limited evidence on test accuracy in primary care settings. Conclusions: The uptake of appropriate meta-analysis methods for synthesising evidence on diagnostic test accuracy in UK NIHR HTAs has improved in recent years. Future research should focus on other evidence requirements for cost-effectiveness assessment, threshold effects for quantitative tests and the impact of multiple diagnostic tests

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

Effects of Anacetrapib in Patients with Atherosclerotic Vascular Disease

BACKGROUND: Patients with atherosclerotic vascular disease remain at high risk for cardiovascular events despite effective statin-based treatment of low-density lipoprotein (LDL) cholesterol levels. The inhibition of cholesteryl ester transfer protein (CETP) by anacetrapib reduces LDL cholesterol levels and increases high-density lipoprotein (HDL) cholesterol levels. However, trials of other CETP inhibitors have shown neutral or adverse effects on cardiovascular outcomes. METHODS: We conducted a randomized, double-blind, placebo-controlled trial involving 30,449 adults with atherosclerotic vascular disease who were receiving intensive atorvastatin therapy and who had a mean LDL cholesterol level of 61 mg per deciliter (1.58 mmol per liter), a mean non-HDL cholesterol level of 92 mg per deciliter (2.38 mmol per liter), and a mean HDL cholesterol level of 40 mg per deciliter (1.03 mmol per liter). The patients were assigned to receive either 100 mg of anacetrapib once daily (15,225 patients) or matching placebo (15,224 patients). The primary outcome was the first major coronary event, a composite of coronary death, myocardial infarction, or coronary revascularization. RESULTS: During the median follow-up period of 4.1 years, the primary outcome occurred in significantly fewer patients in the anacetrapib group than in the placebo group (1640 of 15,225 patients [10.8%] vs. 1803 of 15,224 patients [11.8%]; rate ratio, 0.91; 95% confidence interval, 0.85 to 0.97; P=0.004). The relative difference in risk was similar across multiple prespecified subgroups. At the trial midpoint, the mean level of HDL cholesterol was higher by 43 mg per deciliter (1.12 mmol per liter) in the anacetrapib group than in the placebo group (a relative difference of 104%), and the mean level of non-HDL cholesterol was lower by 17 mg per deciliter (0.44 mmol per liter), a relative difference of -18%. There were no significant between-group differences in the risk of death, cancer, or other serious adverse events. CONCLUSIONS: Among patients with atherosclerotic vascular disease who were receiving intensive statin therapy, the use of anacetrapib resulted in a lower incidence of major coronary events than the use of placebo. (Funded by Merck and others; Current Controlled Trials number, ISRCTN48678192 ; ClinicalTrials.gov number, NCT01252953 ; and EudraCT number, 2010-023467-18 .)

The Impact of Opioid Treatment on Regional Gastrointestinal Transit

BACKGROUND/AIMS: To employ an experimental model of opioid-induced bowel dysfunction in healthy human volunteers, and evaluate the impact of opioid treatment compared to placebo on gastrointestinal (GI) symptoms and motility assessed by questionnaires and regional GI transit times using the 3-dimensional (3D)-Transit system. METHODS: Twenty-five healthy males were randomly assigned to oxycodone or placebo for 5 days in a double blind, crossover design. Adverse GI effects were measured with the bowel function index, gastrointestinal symptom rating scale, patient assessment of constipation symptom questionnaire, and Bristol stool form scale. Regional GI transit times were determined using the 3D-Transit system, and segmental transit times in the colon were determined using a custom Matlab(®) graphical user interface. RESULTS: GI symptom scores increased significantly across all applied GI questionnaires during opioid treatment. Oxycodone increased median total GI transit time from 22.2 to 43.9 hours (P < 0.001), segmental transit times in the cecum and ascending colon from 5.7 to 9.9 hours (P = 0.012), rectosigmoid colon transit from 2.7 to 9.0 hours (P = 0.044), and colorectal transit time from 18.6 to 38.6 hours (P = 0.001). No associations between questionnaire scores and segmental transit times were detected. CONCLUSIONS: Self-assessed GI adverse effects and increased GI transit times in different segments were induced during oxycodone treatment. This detailed information about segmental changes in motility has great potential for future interventional head-to-head trials of different laxative regimes for prevention and treatment of constipation

The impact of opioid treatment on regional gastrointestinal transit

Abstract Aims To employ a human experimental model of opioid-induced bowel dysfunction (OIBD) in healthy volunteers, and evaluate the impact of opioid treatment compared to placebo on gastrointestinal (GI) symptoms and motility, assessed by questionnaires and regional GI transit times. Methods Twenty-five healthy males were randomly assigned to oxycodone or placebo for five days in a double-blind, crossover design. Adverse GI effects were measured with bowel function index, gastrointestinal symptom rating scale, patient assessment of constipation symptoms questionnaire, and bristol stool form scale. Regional GI transit times were determined using the 3D-Transit system and segmental colonic transit times were determined using a custom Matlab® graphical user interface. Results GI symptom scores increased significantly across all applied questionnaires during opioid treatment. Oxycodone increased median total GI transit time from 22.2 to 43.9 h (P&lt; 0.01), segmental transit times in the cecum and ascending colon from 5.7 to 9.9 h (P&lt;0.05), rectosigmoid transit time from 2.7 to 9.0 h (P&lt;0.05), and colorectal transit time from 18.6 to 38.6 h (P&lt;0.01). No association between questionnaire scores and segmental transit times were detected. Conclusions Self-assessed adverse GI effects and increased GI transit times in different segments were induced during oxycodone treatment. This detailed information about segmental changes in motility has great potential for future interventional head-to-head trials of different laxative regimes for prevention and treatment of OIBD. </jats:sec

Study of the mechanisms contributing to visceral hypersensitivity in a rat model of acute and postinflammatory colitis : focus on splanchnic afferent nerve signaling

Abstract of a poster presentation from NeuroGASTRO 2015Peer reviewe