The clinically-integrated randomized trial: proposed novel method for conducting large trials at low cost

Framework of the strengths and challenges of clinically integrated trials: An expert panel report

The limitations of the explanatory clinical trial framework include the high expense of implementing explanatory trials, restrictive entry criteria for participants, and redundant logistical processes. These limitations can result in slow evidence generation that is not responsive to population health needs, yielding evidence that is not generalizable. Clinically integrated trials, which integrate clinical research into routine care, represent a potential solution to this challenge and an opportunity to support learning health systems. The operational and design features of clinically integrated trials include a focused scope, simplicity in design and requirements, the leveraging of existing data structures, and patient participation in the entire trial process. These features are designed to minimize barriers to participation and trial execution and reduce additional research burdens for participants and clinicians alike. Broad adoption and scalability of clinically integrated trials are dependent, in part, on continuing regulatory, healthcare system, and payer support. This analysis presents a framework of the strengths and challenges of clinically integrated trials and is based on a multidisciplinary expert "Think Tank" panel discussion that included representatives from patient populations, academia, non-profit funding agencies, the U.S. Food and Drug Administration, and industry.

Optimizing accrual to a large-scale, clinically integrated randomized trial in anesthesiology: A 2-year analysis of recruitment

BACKGROUND

Performing large randomized trials in anesthesiology is often challenging and costly. The clinically integrated randomized trial is characterized by simplified logistics embedded into routine clinical practice, enabling ease and efficiency of recruitment, offering an opportunity for clinicians to conduct large, high-quality randomized trials under low cost. Our aims were to (1) demonstrate the feasibility of the clinically integrated trial design in a high-volume anesthesiology practice and (2) assess whether trial quality improvement interventions led to more balanced accrual among study arms and improved trial compliance over time.

METHODS

This is an interim analysis of recruitment to a cluster-randomized trial investigating three nerve block approaches for mastectomy with immediate implant-based reconstruction: paravertebral block (arm 1), paravertebral plus interpectoral plane blocks (arm 2), and serratus anterior plane plus interpectoral plane blocks (arm 3). We monitored accrual and consent rates, clinician compliance with the randomized treatment, and availability of outcome data. Assessment after the initial year of implementation showed a slight imbalance in study arms suggesting areas for improvement in trial compliance. Specific improvement interventions included increasing the frequency of communication with the consenting staff and providing direct feedback to clinician investigators about their individual recruitment patterns. We assessed overall accrual rates and tested for differences in accrual, consent, and compliance rates pre- and post-improvement interventions.

RESULTS

Overall recruitment was extremely high, accruing close to 90% of the eligible population. In the pre-intervention period, there was evidence of bias in the proportion of patients being accrued and receiving the monthly block, with higher rates in arm 3 (90%) compared to arms 1 (81%) and 2 (79%, p = 0.021). In contrast, in the post-intervention period, there was no statistically significant difference between groups (p = 0.8). Eligible for randomization rate increased from 89% in the pre-intervention period to 95% in the post-intervention period (difference 5.7%; 95% confidence interval = 2.2%-9.4%, p = 0.002). Consent rate increased from 95% to 98% (difference of 3.7%; 95% confidence interval = 1.1%-6.3%; p = 0.004). Compliance with the randomized nerve block approach was maintained at close to 100% and availability of primary outcome data was 100%.

CONCLUSION

The clinically integrated randomized trial design enables rapid trial accrual with a high participant compliance rate in a high-volume anesthesiology practice. Continuous monitoring of accrual, consent, and compliance rates is necessary to maintain and improve trial conduct and reduce potential biases. This trial methodology serves as a template for the implementation of other large, low-cost randomized trials in anesthesiology.

A brief mind-body intervention to reduce pain and anxiety during prostate needle biopsy: a clinically integrated randomized controlled trial with 2-staged consent

OBJECTIVES

Many patients experience pain, anxiety, and discomfort with prostate biopsy, which may discourage enrollment in active surveillance programs or follow-up biopsy. Guided meditation can significantly reduce pain and anxiety during percutaneous biopsy. We sought to evaluate the effectiveness of a brief mind-body intervention on patient-reported outcomes after prostate biopsy.

METHODS AND MATERIALS

We performed a clinically-integrated randomized controlled trial of a brief mind-body intervention during biopsy compared to usual care at a single tertiary care center from 2018 to 2022. All patients offered transrectal ultrasound-guided prostate biopsy in the clinic with local anesthesia were eligible for enrollment. This clinically integrated trial was conducted simultaneously with a randomized controlled trial of 1-stage and 2-stage consent. The primary outcome was patient-reported pain, anxiety, discomfort, and tolerability on a visual-analog scale (0-10). A 15% improvement was prespecified as clinically relevant. We compared the proportion of men in each arm reporting a severe score (7-10) on any of the 4 scales using Fisher's exact test and then compared means for each scale separately using ANCOVA with randomization stratum (first vs. prior biopsy) as a covariate.

RESULTS

Of 263 eligible patients, 238 enrolled (119 per arm). One hundred seventy-two (72%) enrolled with 2-stage consent. A total of 37/94 (39%) and 38/102 (37%) patients randomized to usual care and intervention, respectively, reported severe scores in any of the 4 domains, a difference of 2.1% (95% confidence interval [CI] -13, 17%, P = 0.8). There was no evidence of a difference in mean postbiopsy anxiety (P = 0.3), discomfort (P = 0.09), pain (P = 0.4) or tolerability scores (P = 0.2).

CONCLUSIONS

A clinically meaningful benefit for this brief mind-body intervention during prostate biopsy is unlikely. Robust patient enrollment is feasible using 2-stage consent.

Leveraging Artificial Intelligence and Synthetic Data Derivatives for Spine Surgery Research

STUDY DESIGN

Retrospective cohort study.

OBJECTIVES

Leveraging electronic health records (EHRs) for spine surgery research is impeded by concerns regarding patient privacy and data ownership. Synthetic data derivatives may help overcome these limitations. This study's objective was to validate the use of synthetic data for spine surgery research.

METHODS

Data came from the EHR from 15 hospitals. Patients that underwent anterior cervical or posterior lumbar fusion (2010-2020) were included. Real data were obtained from the EHR. Synthetic data was generated to simulate the properties of the real data, without maintaining a one-to-one correspondence with real patients. Within each cohort, ability to predict 30-day readmissions and 30-day complications was evaluated using logistic regression and extreme gradient boosting machines (XGBoost).

RESULTS

We identified 9,072 real and 9,088 synthetic cervical fusion patients. Descriptive characteristics were nearly identical between the 2 datasets. When predicting readmission, models built using real and synthetic data both had c-statistics of .69-.71 using logistic regression and XGBoost. Among 12,111 real and 12,126 synthetic lumbar fusion patients, descriptive characteristics were nearly the same for most variables. Using logistic regression and XGBoost to predict readmission, discrimination was similar with models built using real and synthetic data (c-statistics .66-.69). When predicting complications, models derived using real and synthetic data showed similar discrimination in both cohorts. Despite some differences, the most influential predictors were similar in the real and synthetic datasets.

CONCLUSION

Synthetic data replicate most descriptive and predictive properties of real data, and therefore may expand EHR research in spine surgery.

Pragmatic Comparative Effectiveness Trials and Learning Health Systems in Pain Medicine: Opportunities and Challenges

Large randomized clinical trials or aggregates of clinical trials represent the highest levels of clinical evidence because they minimize different sources of confounding and bias. The current review provides an in-depth discussion of the challenges faced and methods we can use to overcome these obstacles to tailor novel designs of pragmatic effectiveness trials to pain medicine. The authors describe their experiences with an open-source learning health system to collect high-quality evidence and conduct pragmatic clinical trials within a busy academic pain center.

Artificial intelligence in spine surgery

The continuous progress of research and clinical trials has offered a wide variety of information concerning the spine and the treatment of the different spinal pathologies that may occur. Planning the best therapy for each patient could be a very difficult and challenging task as it often requires thorough processing of the patient's history and individual characteristics by the clinician. Clinicians and researchers also face problems when it comes to data availability due to patients' personal information protection policies. Artificial intelligence refers to the reproduction of human intelligence via special programs and computers that are trained in a way that simulates human cognitive functions. Artificial intelligence implementations to daily clinical practice such as surgical robots that facilitate spine surgery and reduce radiation dosage to medical staff, special algorithms that can predict the possible outcomes of conservative versus surgical treatment in patients with low back pain and disk herniations, and systems that create artificial populations with great resemblance and similar characteristics to real patients are considered to be a novel breakthrough in modern medicine. To enhance the body of the related literature and inform the readers on the clinical applications of artificial intelligence, we performed this review to discuss the contribution of artificial intelligence in spine surgery and pathology.

Integrated rapid-cycle comparative effectiveness trials using flexible point of care randomisation in electronic health record systems

Whilst the Randomised Controlled Trial remains the gold standard for deriving robust causal estimates of treatment efficacy, too often a traditional design proves prohibitively expensive or cumbersome when it comes to assessing questions regarding the comparative effectiveness of routinely used treatments. As a result, patients experience variation in practice as clinicians lack the evidence needed to personalise treatments effectively. This variation may be classified as unwarranted, where existing evidence is ignored, or legitimate where in the absence of evidence, clinicians rely on experience, expert opinion, and inferred principles from basic science to make decisions. We argue that within the right ethical and technological framework, legitimate variation can be transformed into a mechanism for evidence generation and learning. Learning Health Systems which harness existing variation in practice, represent a novel approach for generating evidence from everyday clinical practice. The development of these systems has gained traction due to the increased availability of modern Electronic Health Record Systems. However, despite their promise, overcoming hurdles to successfully integrating clinical trials within Learning Health Systems has proven challenging. This article describes the origins of integrated clinical trials and explores two main barriers to their further implementation - how best to obtain informed consent from patients to participate in routine comparative effectiveness research, and how to automate and integrate randomisation into a clinical workflow. Having described these barriers, we present a potential solution in the form of a research pipeline using a novel form of flexible point-of-care randomisation to allow clinicians and patients to participate in studies where there is clinical equipoise.

Embedded point of care randomisation for evaluating comparative effectiveness questions: PROSPECTOR-critical care feasibility study protocol

INTRODUCTION

Many routinely administered treatments lack evidence as to their effectiveness. When treatments lack evidence, patients receive varying care based on the preferences of clinicians. Standard randomised controlled trials are unsuited to comparisons of different routine treatment strategies, and there remains little economic incentive for change.Integrating clinical trial infrastructure into electronic health record systems offers the potential for routine treatment comparisons at scale, through reduced trial costs. To date, embedded trials have automated data collection, participant identification and eligibility screening, but randomisation and consent remain manual and therefore costly tasks.This study will investigate the feasibility of using computer prompts to allow flexible randomisation at the point of clinical decision making. It will compare the effectiveness of two prompt designs through the lens of a candidate research question-comparing liberal or restrictive magnesium supplementation practices for critical care patients. It will also explore the acceptability of two consent models for conducting comparative effectiveness research.

METHODS AND ANALYSIS

We will conduct a single centre, mixed-methods feasibility study, aiming to recruit 50 patients undergoing elective surgery requiring postoperative critical care admission. Participants will be randomised to either 'Nudge' or 'Preference' designs of electronic point-of-care randomisation prompt, and liberal or restrictive magnesium supplementation.We will judge feasibility through a combination of study outcomes. The primary outcome will be the proportion of prompts displayed resulting in successful randomisation events (compliance with the allocated magnesium strategy). Secondary outcomes will evaluate the acceptability of both prompt designs to clinicians and ascertain the acceptability of pre-emptive and opt-out consent models to patients.

ETHICS AND DISSEMINATION

This study was approved by Riverside Research Ethics Committee (Ref: 21/LO/0785) and will be published on completion.

TRIAL REGISTRATION NUMBER

NCT05149820.

Design of a pragmatic clinical trial embedded in the Electronic Health Record: The VA's Diuretic Comparison Project

BACKGROUND

Recent US guidelines recommend chlorthalidone over other thiazide-type diuretics for the treatment of hypertension based on its long half-life and proven ability to reduce CVD events. Despite recommendations most clinicians prescribe hydrochlorothiazide (HCTZ) over chlorthalidone (CTD). No randomized controlled data exist comparing these two diuretics on cardiovascular outcomes.

METHODS

The Diuretic Comparison Project (DCP) is a multicenter, two-arm, parallel, Prospective Randomized Open, Blinded End-point (PROBE) trial testing the primary hypothesis that CTD is superior to HCTZ in the prevention of non-fatal CVD events and non-cancer death. Patients with hypertension taking HCTZ 25 or 50 mg were randomly assigned to either continue their current HCTZ or switch to an equipotent dose of CTD. The primary outcome is time to the first occurrence of a composite outcome consisting of a non-fatal CVD event (stroke, myocardial infarction, urgent coronary revascularization because of unstable angina, or hospitalization for acute heart failure) or non-cancer death. The trial randomized 13,523 patients at 72 VA medical centers. The study is conducted by a centralized research team with site procedures embedded in the electronic health record and all data collected through administrative claims data, with no study related visits for participants. The trial will have 90% power to detect an absolute reduction in the composite event rate of 2.4%.

RESULTS

Enrollment ended in November 2021. There are 4128 participting primary care providers and 16,595 patients individually consented to participate, 13,523 of whom were randomized.

CONCLUSIONS

DCP should provide much needed evidence as to whether CTD is superior to HCTZ in preventing cardiovascular events in hypertensive patients.

CLINICAL TRIAL REGISTRATION

NCT02185417 [https://clinicaltrials.gov/ct2/show/NCT02185417].

An Electronic Health Record-Compatible Model to Predict Personalized Treatment Effects From the Diabetes Prevention Program: A Cross-Evidence Synthesis Approach Using Clinical Trial and Real-World Data

OBJECTIVE

To develop an electronic health record (EHR)-based risk tool that provides point-of-care estimates of diabetes risk to support targeting interventions to patients most likely to benefit.

PATIENTS AND METHODS

A risk prediction model was developed and validated in a large observational database of patients with an index visit date between January 1, 2012, and December 31, 2016, with treatment effect estimates from risk-based reanalysis of clinical trial data. The risk model development cohort included 1.1 million patients with prediabetes from the OptumLabs Data Warehouse (OLDW); the validation cohort included a distinct sample of 1.1 million patients in OLDW. The randomly assigned clinical trial cohort included 3081 people from the Diabetes Prevention Program (DPP) study.

RESULTS

Eleven variables reliably obtainable from the EHR were used to predict diabetes risk. This model validated well in the OLDW (C statistic = 0.76; observed 3-year diabetes rate was 1.8% (95% confidence interval [CI], 1.7 to 1.9) in the lowest-risk quarter and 19.6% (19.4 to 19.8) in the highest-risk quarter). In the DPP, the hazard ratio (HR) for lifestyle modification was constant across all levels of risk (HR, 0.43; 95% CI, 0.35 to 0.53), whereas the HR for metformin was highly risk dependent (HR, 1.1; 95% CI, 0.61 to 2.0 in the lowest-risk quarter vs HR, 0.45; 95% CI, 0.35 to 0.59 in the highest-risk quarter). Fifty-three percent of the benefits of population-wide dissemination of the DPP lifestyle modification and 73% of the benefits of population-wide metformin therapy can be obtained by targeting the highest-risk quarter of patients.

CONCLUSION

The Tufts-Predictive Analytics and Comparative Effectiveness DPP Risk model is an EHR-compatible tool that might support targeted diabetes prevention to more efficiently realize the benefits of the DPP interventions.

ProjectFlow: a configurable workflow management application for point of care research

Objective

To best meet our point-of-care research (POC-R) needs, we developed ProjectFlow, a configurable, clinical research workflow management application. In this article, we describe ProjectFlow and how it is used to manage study processes for the Diuretic Comparison Project (DCP) and the Research Precision Oncology Program (RePOP).

Materials and methods

The Veterans Health Administration (VHA) is the largest integrated health care system in the United States. ProjectFlow is a flexible web-based workflow management tool specifically created to facilitate conduct of our clinical research initiatives within the VHA. The application was developed using the Grails web framework and allows researchers to create custom workflows using Business Process Model and Notation.

Results

As of January 2021, ProjectFlow has facilitated management of study recruitment, enrollment, randomization, and drug orders for over 10 000 patients for the DCP clinical trial. It has also helped us evaluate over 3800 patients for recruitment and enroll over 370 of them into RePOP for use in data sharing partnerships and predictive analytics aimed at optimizing cancer treatment in the VHA.

Discussion

The POC-R study design embeds research processes within day-to-day clinical care and leverages longitudinal electronic health record (EHR) data for study recruitment, monitoring, and outcome reporting. Software that allows flexibility in study workflow creation and integrates with enterprise EHR systems is critical to the success of POC-R.

Conclusions

We developed a flexible web-based informatics solution called ProjectFlow that supports custom research workflow configuration and has ability to integrate data from existing VHA EHR systems.

Limited versus Extended Pelvic Lymph Node Dissection for Prostate Cancer: A Randomized Clinical Trial

BACKGROUND

Pelvic lymph node dissection (PLND) is the most reliable procedure for lymph node staging. However, the therapeutic benefit remains unproven; although most radical prostatectomies at academic centers are accompanied by PLND, there is no consensus regarding the optimal anatomical extent of PLND.

OBJECTIVE

To evaluate whether extended PLND results in a lower biochemical recurrence rate.

DESIGN, SETTING, AND PARTICIPANTS

We conducted a single-center randomized trial. Patients, enrolled between October 2011 and March 2017, were scheduled to undergo radical prostatectomy and PLND. Patients were assigned to limited or extended PLND by cluster randomization. Specifically, surgeons were randomized to perform limited or extended PLND for 3-mo periods.

INTERVENTION

Randomization to limited (external iliac nodes) or extended (external iliac, obturator fossa and hypogastric nodes) PLND.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The primary endpoint was the rate of biochemical recurrence.

RESULTS AND LIMITATIONS

Of 1440 patients included in the final analysis, 700 were randomized to limited PLND and 740 to extended PLND. The median number of nodes retrieved was 12 (interquartile range [IQR] 8-17) for limited PLND and 14 (IQR 10-20) extended PLND; the corresponding rate of positive nodes was 12% and 14% (difference -1.9%, 95% confidence interval [CI] -5.4% to 1.5%; p = 0.3). With median follow-up of 3.1 yr, there was no significant difference in the rate of biochemical recurrence between the groups (hazard ratio 1.04, 95% CI 0.93-1.15; p = 0.5). Rates for grade 2 and 3 complications were similar at 7.3% for limited versus 6.4% for extended PLND; there were no grade 4 or 5 complications.

CONCLUSIONS

Extended PLND did not improve freedom from biochemical recurrence over limited PLND for men with clinically localized prostate cancer. However, there were smaller than expected differences in nodal count and the rate of positive nodes between the two templates. A randomized trial comparing PLND to no node dissection is warranted.

PATIENT SUMMARY

In this clinical trial we did not find a difference in the rate of biochemical recurrence of prostate cancer between limited and extended dissection of lymph nodes in the pelvis. This study is registered on ClinicalTrials.gov as NCT01407263.

Informed consent rates for neonatal randomized controlled trials in low- and lower middle-income versus high-income countries: A systematic review

OBJECTIVE

Legal, ethical, and regulatory requirements of medical research uniformly call for informed consent. We aimed to characterize and compare consent rates for neonatal randomized controlled trials in low- and lower middle-income countries versus high-income countries, and to evaluate the influence of study characteristics on consent rates.

METHODS

In this systematic review, we searched MEDLINE, EMBASE and Cochrane for randomized controlled trials of neonatal interventions in low- and lower middle-income countries or high-income countries published 01/01/2013 to 01/04/2018. Our primary outcome was consent rate, the proportion of eligible participants who consented amongst those approached, extracted from the article or email with the author. Using a generalised linear model for fractional dependent variables, we analysed the odds of consenting in low- and lower middle-income countries versus high-income countries across control types and interventions.

FINDINGS

We screened 3523 articles, yielding 300 eligible randomized controlled trials with consent rates available for 135 low- and lower middle-income country trials and 65 high-income country trials. Median consent rates were higher for low- and lower middle-income countries (95.6%; interquartile range (IQR) 88.2-98.9) than high-income countries (82.7%; IQR 68.6-93.0; p<0.001). In adjusted regression analysis comparing low- and lower middle-income countries to high-income countries, the odds of consent for no placebo-drug/nutrition trials was 3.67 (95% Confidence Interval (CI) 1.87-7.19; p = 0.0002) and 6.40 (95%CI 3.32-12.34; p<0.0001) for placebo-drug/nutrition trials.

CONCLUSION

Neonatal randomized controlled trials in low- and lower middle-income countries report consistently higher consent rates compared to high-income country trials. Our study is limited by the overrepresentation of India among randomized controlled trials in low- and lower middle-income countries. This study raises serious concerns about the adequacy of protections for highly vulnerable populations recruited to clinical trials in low- and lower middle-income countries.

Pragmatic Trials in Genomic Medicine: The Integrating Pharmacogenetics In Clinical Care (I-PICC) Study

Pragmatic clinical trials (PCTs) have an established presence in clinical research and yet have only recently garnered attention within the landscape of genomic medicine. Using the PRagmatic-Explanatory Continuum Indicator Summary 2 (PRECIS-2) as a framework, this paper illustrates the application of PCT principles to The Integrating Pharmacogenetics In Clinical Care (I-PICC) Study, a trial of pharmacogenetic testing prior to statin initiation for cardiovascular disease prevention in primary care. The trial achieved high engagement with providers (85% enrolled of those approached) and enrolled a representative sample of participants for which statin therapy would be recommended. The I-PICC Study has a high level of pragmatism, which should enhance the generalizability of its findings. The PRECIS-2 may be useful in the design and evaluation of PCTs of genomic medicine interventions, contributing to the generation of evidence that can bridge the gap between genomics innovation and clinical adoption.

The Predictive Approaches to Treatment effect Heterogeneity (PATH) Statement

Heterogeneity of treatment effect (HTE) refers to the nonrandom variation in the magnitude or direction of a treatment effect across levels of a covariate, as measured on a selected scale, against a clinical outcome. In randomized controlled trials (RCTs), HTE is typically examined through a subgroup analysis that contrasts effects in groups of patients defined "1 variable at a time" (for example, male vs. female or old vs. young). The authors of this statement present guidance on an alternative approach to HTE analysis, "predictive HTE analysis." The goal of predictive HTE analysis is to provide patient-centered estimates of outcome risks with versus without the intervention, taking into account all relevant patient attributes simultaneously. The PATH (Predictive Approaches to Treatment effect Heterogeneity) Statement was developed using a multidisciplinary technical expert panel, targeted literature reviews, simulations to characterize potential problems with predictive approaches, and a deliberative process engaging the expert panel. The authors distinguish 2 categories of predictive HTE approaches: a "risk-modeling" approach, wherein a multivariable model predicts the risk for an outcome and is applied to disaggregate patients within RCTs to define risk-based variation in benefit, and an "effect-modeling" approach, wherein a model is developed on RCT data by incorporating a term for treatment assignment and interactions between treatment and baseline covariates. Both approaches can be used to predict differential absolute treatment effects, the most relevant scale for clinical decision making. The authors developed 4 sets of guidance: criteria to determine when risk-modeling approaches are likely to identify clinically important HTE, methodological aspects of risk-modeling methods, considerations for translation to clinical practice, and considerations and caveats in the use of effect-modeling approaches. The PATH Statement, together with its explanation and elaboration document, may guide future analyses and reporting of RCTs.

The Predictive Approaches to Treatment effect Heterogeneity (PATH) Statement: Explanation and Elaboration

The PATH (Predictive Approaches to Treatment effect Heterogeneity) Statement was developed to promote the conduct of, and provide guidance for, predictive analyses of heterogeneity of treatment effects (HTE) in clinical trials. The goal of predictive HTE analysis is to provide patient-centered estimates of outcome risk with versus without the intervention, taking into account all relevant patient attributes simultaneously, to support more personalized clinical decision making than can be made on the basis of only an overall average treatment effect. The authors distinguished 2 categories of predictive HTE approaches (a "risk-modeling" and an "effect-modeling" approach) and developed 4 sets of guidance statements: criteria to determine when risk-modeling approaches are likely to identify clinically meaningful HTE, methodological aspects of risk-modeling methods, considerations for translation to clinical practice, and considerations and caveats in the use of effect-modeling approaches. They discuss limitations of these methods and enumerate research priorities for advancing methods designed to generate more personalized evidence. This explanation and elaboration document describes the intent and rationale of each recommendation and discusses related analytic considerations, caveats, and reservations.

Quality improvement and practice-based research in sleep medicine using structured clinical documentation in the electronic medical record

Background:

We developed and implemented a structured clinical documentation support (SCDS) toolkit within the electronic medical record, to optimize patient care, facilitate documentation, and capture data at office visits in a sleep medicine/neurology clinic for patient care and research collaboration internally and with other centers.

Methods:

To build our SCDS toolkit, physicians met frequently to develop content, define the cohort, select outcome measures, and delineate factors known to modify disease progression. We assigned tasks to the care team and mapped data elements to the progress note. Programmer analysts built and tested the SCDS toolkit, which included several score tests. Auto scored and interpreted tests included the Generalized Anxiety Disorder 7-item, Center for Epidemiological Studies Depression Scale, Epworth Sleepiness Scale, Pittsburgh Sleep Quality Index, Insomnia Severity Index, and the International Restless Legs Syndrome Study Group Rating Scale. The SCDS toolkits also provided clinical decision support (untreated anxiety or depression) and prompted enrollment of patients in a DNA biobank.

Results:

The structured clinical documentation toolkit captures hundreds of fields of discrete data at each office visit. This data can be displayed in tables or graphical form. Best practice advisories within the toolkit alert physicians when a quality improvement opportunity exists. As of May 1, 2019, we have used the toolkit to evaluate 18,105 sleep patients at initial visit. We are also collecting longitudinal data on patients who return for annual visits using the standardized toolkits. We provide a description of our development process and screenshots of our toolkits.

Conclusions:

The electronic medical record can be structured to standardize Sleep Medicine office visits, capture data, and support multicenter quality improvement and practice-based research initiatives for sleep patients at the point of care.

Point-of-Care Clinical Trials in Sports Medicine Research: Identifying Effective Treatment Interventions Through Comparative Effectiveness Research

CONTEXT

Recently, calls to conduct comparative effectiveness research (CER) in athletic training to better support patient care decisions have been circulated. Traditional research methods (eg, randomized controlled trials [RCTs], observational studies) may be ill suited for CER. Thus, innovative research methods are needed to support CER efforts.

OBJECTIVES

To discuss the limitations of traditional research designs in CER studies, describe a novel methodologic approach called the point-of-care clinical trial (POC-CT), and highlight components of the POC-CT (eg, incorporation of an electronic medical record [EMR], Bayesian adaptive feature) that allow investigators to conduct scientifically rigorous studies at the point of care.

DESCRIPTION

Practical concerns (eg, high costs and limited generalizability of RCTs, the inability to control for bias in observational studies) may stall CER efforts in athletic training. In short, the aim of the POC-CT is to embed a randomized pragmatic trial into routine care; thus, patients are randomized to minimize potential bias, but the study is conducted at the point of care to limit cost and improve the generalizability of the findings. Furthermore, the POC-CT uses an EMR to replace much of the infrastructure associated with a traditional RCT (eg, research team, patient and clinician reminders) and a Bayesian adaptive feature to help limit the number of patients needed for the study. Together, the EMR and Bayesian adaptive feature can improve the overall feasibility of the study and preserve the typical clinical experiences of the patient and clinician.

CLINICAL ADVANTAGES

The POC-CT includes the basic tenets of practice-based research because studies are conducted at the point of care, in real-life settings, and during routine clinical practice. If implemented effectively, the POC-CT can be seamlessly integrated into daily clinical practice, allowing investigators to establish patient-reported evidence that may be quickly applied to patient care decisions. This design appears to be a promising approach for CER investigations and may help establish a "learning health care system" in the sports medicine community.

Perspective: Limiting Dependence on Nonrandomized Studies and Improving Randomized Trials in Human Nutrition Research: Why and How

A large majority of human nutrition research uses nonrandomized observational designs, but this has led to little reliable progress. This is mostly due to many epistemologic problems, the most important of which are as follows: difficulty detecting small (or even tiny) effect sizes reliably for nutritional risk factors and nutrition-related interventions; difficulty properly accounting for massive confounding among many nutrients, clinical outcomes, and other variables; difficulty measuring diet accurately; and suboptimal research reporting. Tiny effect sizes and massive confounding are largely unfixable problems that narrowly confine the scenarios in which nonrandomized observational research is useful. Although nonrandomized studies and randomized trials have different priorities (assessment of long-term causality compared with assessment of treatment effects), the odds for obtaining reliable information with the former are limited. Randomized study designs should therefore largely replace nonrandomized studies in human nutrition research going forward. To achieve this, many of the limitations that have traditionally plagued most randomized trials in nutrition, such as small sample size, short length of follow-up, high cost, and selective reporting, among others, must be overcome. Pivotal megatrials with tens of thousands of participants and lifelong follow-up are possible in nutrition science with proper streamlining of operational costs. Fixable problems that have undermined observational research, such as dietary measurement error and selective reporting, need to be addressed in randomized trials. For focused questions in which dietary adherence is important to maximize, trials with direct observation of participants in experimental in-house settings may offer clean answers on short-term metabolic outcomes. Other study designs of randomized trials to consider in nutrition include registry-based designs and "N-of-1" designs. Mendelian randomization designs may also offer some more reliable leads for testing interventions in trials. Collectively, an improved randomized agenda may clarify many things in nutrition science that might never be answered credibly with nonrandomized observational designs.

Using a meta-narrative literature review and focus groups with key stakeholders to identify perceived challenges and solutions for generating robust evidence on the effectiveness of treatments for rare diseases

INTRODUCTION

For many rare diseases, strong analytic study designs for evaluating the efficacy and effectiveness of interventions are challenging to implement because of small, geographically dispersed patient populations and underlying clinical heterogeneity. The objective of this study was to integrate perspectives from published literature and key rare disease stakeholders to better understand the perceived challenges and proposed methodological approaches to research on clinical interventions for rare diseases.

METHODS

We used a meta-narrative literature review and focus group interviews with key rare disease stakeholders to better understand the perceived challenges in generating and synthesizing treatment effectiveness evidence, and to describe various research methods for mitigating these identified challenges. Data from both components of this study were synthesized narratively according to research paradigms that emerged from our data.

RESULTS

Results from our meta-narrative literature review and focus group interviews revealed three fundamental challenges in generating robust treatment effectiveness evidence for rare diseases: i) limitations in recruiting a sufficient sample size to achieve planned statistical power; ii) inability to account for clinical heterogeneity and assess treatment effects across a clinical spectrum; and iii) reliance on short-term, surrogate outcomes whose clinical relevance is often unclear. We mapped these challenges and associated solutions to three interrelated research paradigms: i) explanatory evidence generation; ii) comparative effectiveness/pragmatic evidence generation; and iii) patient-oriented evidence generation. Within each research paradigm, numerous criticisms and potential solutions have been described with respect to overcoming these challenges from a research study design perspective.

CONCLUSIONS

Over time, discussions about clinical research for interventions for rare diseases have moved beyond methodological approaches to overcome challenges related to explanatory evidence generation, with increased recognition of the importance of pragmatic and patient-oriented evidence. Future directions for our work include developing a framework to expand current evidence synthesis practices to take into consideration many of the concepts discussed in this paper.

Design and implementation of pragmatic clinical trials using the electronic medical record and an adaptive design

Objectives

To demonstrate the feasibility of pragmatic clinical trials comparing the effectiveness of treatments using the electronic medical record (EMR) and an adaptive assignment design.

Methods

We have designed and are implementing pragmatic trials at the point-of-care using custom-designed structured clinical documentation support and clinical decision support tools within our physician's typical EMR workflow. We are applying a subgroup based adaptive design (SUBA) that enriches treatment assignments based on baseline characteristics and prior outcomes. SUBA uses information from a randomization phase (phase 1, equal randomization, 120 patients), to adaptively assign treatments to the remaining participants (at least 300 additional patients total) based on a Bayesian hierarchical model. Enrollment in phase 1 is underway in our neurology clinical practices for 2 separate trials using this method, for migraine and mild cognitive impairment (MCI).

Results

We are successfully collecting structured data, in the context of the providers' clinical workflow, necessary to conduct our trials. We are currently enrolling patients in 2 point-of-care trials of non-inferior treatments. As of March 1, 2018, we have enrolled 36% of eligible patients into our migraine study and 63% of eligible patients into our MCI study. Enrollment is ongoing and validation of outcomes has begun.

Discussion

This proof of concept article demonstrates the feasibility of conducting pragmatic trials using the EMR and an adaptive design.

Conclusion

The demonstration of successful pragmatic clinical trials based on a customized EMR and adaptive design is an important next step in achieving personalized medicine and provides a framework for future studies of comparative effectiveness.

Veterans Healthcare Administration providers' attitudes and perceptions regarding pragmatic trials embedded at the point of care

Background The Veterans Healthcare Administration (VA) is implementing an adaptation of a pragmatic trial program, Point of Care Research (POC-R). The goal of POC-R is to embed research into clinical practice, contributing to a Learning Healthcare System. Provider acceptance and participation in POC-R is essential to its successful implementation. The purpose of this study is to evaluate provider's perceptions and beliefs regarding the POC-R program. Methods Provider focus groups and interviews were conducted at seven VA medical facilities involving 62 providers. A semi-structured script was used that included descriptions of four use cases and targeted questions regarding perceptions, concerns, and attitudes about the POC-R program. Sessions were audio-taped, de-identified, transcribed, and analyzed using systematic qualitative techniques to create response categories and overarching themes. Results The emergent themes were as follows: (1) POC-R is a valuable component of evidence-based practice, providing an opportunity to base clinical practice on more generalizable evidence as well as providing tools to improve local practice; (2) POC-R highlights the tension between the need for autonomy of practice and compliance with protocols; (3) POC-R may create increased time and burden resulting from added research responsibilities; (4) concern about the scientific validity and reliability of results; (5) potential for a negative impact on the provider-patient relationship; and (6) uncertainty regarding what constitutes equipoise, given differences in provider knowledge and preferences. Despite substantive concerns, barriers were generally felt to be solvable. Implementation should include provider education, careful attention to workflow for all arms of the study, inclusion of the entire team, and adequate oversight. Limitations The study design is qualitative with limited implications for causal inference. Participants are from the VA and may not be representative of other clinicians. Conclusion VA providers are supportive of the importance and value of pragmatic trials in general and of POC-R in particular. However, providers have significant concerns regarding the burden, ethics, and evidence regarding equipoise. Results are discussed in terms of implementation recommendations.

Establishing core outcome sets for phenylketonuria (PKU) and medium-chain Acyl-CoA dehydrogenase (MCAD) deficiency in children: study protocol for systematic reviews and Delphi surveys

BACKGROUND

Inherited metabolic diseases (IMD) are a large group of rare single-gene disorders that are typically diagnosed early in life. There are important evidence gaps related to the comparative effectiveness of therapies for IMD, which are in part due to challenges in conducting randomized controlled trials (RCTs) for rare diseases. Registry-based RCTs present a unique opportunity to address these challenges provided the registries implement standardized collection of outcomes that are important to patients and their caregivers and to clinical providers and healthcare systems. Currently there is no core outcome set (COS) for studies evaluating interventions for paediatric IMD. This protocol outlines a study that will establish COS for each of two relatively common IMD in children, phenylketonuria (PKU) and medium-chain acyl-CoA dehydrogenase (MCAD) deficiency.

METHODS

This two-part study is registered with the Core Outcome Measures in Effectiveness Trials (COMET) initiative. Part 1 includes a rapid review and development of an evidence map to identify a comprehensive listing of outcomes reported in past studies of PKU and MCAD deficiency. The review follows established methods for knowledge synthesis, including a comprehensive search strategy, two stages of screening citations against inclusion/exclusion criteria by two reviewers working independently, and extraction of important data elements from eligible studies, including details of the outcomes collected and outcome measurement instruments. The review findings will inform part 2 of our study, a set of Delphi surveys to establish consensus on the highest priority outcomes for each condition. Healthcare providers, families of children with PKU or MCAD deficiency, and health system decision-makers will be invited to participate in two to three rounds of Delphi surveys. The design of the surveys will involve parents of children with IMD who are part of a family advisory forum.

DISCUSSION

This protocol is a crucial step in developing the capacity to launch RCTs with meaningful outcomes that address comparative effectiveness questions in the field of paediatric IMD. Such trials will contribute high-quality evidence to inform decision-making by patients and their family members, clinicians, and policy-makers.

A systematic literature review of evidence-based clinical practice for rare diseases: what are the perceived and real barriers for improving the evidence and how can they be overcome?

BACKGROUND

Evidence-based clinical practice is challenging in all fields, but poses special barriers in the field of rare diseases. The present paper summarises the main barriers faced by clinical research in rare diseases, and highlights opportunities for improvement.

METHODS

Systematic literature searches without meta-analyses and internal European Clinical Research Infrastructure Network (ECRIN) communications during face-to-face meetings and telephone conferences from 2013 to 2017 within the context of the ECRIN Integrating Activity (ECRIN-IA) project.

RESULTS

Barriers specific to rare diseases comprise the difficulty to recruit participants because of rarity, scattering of patients, limited knowledge on natural history of diseases, difficulties to achieve accurate diagnosis and identify patients in health information systems, and difficulties choosing clinically relevant outcomes.

CONCLUSIONS

Evidence-based clinical practice for rare diseases should start by collecting clinical data in databases and registries; defining measurable patient-centred outcomes; and selecting appropriate study designs adapted to small study populations. Rare diseases constitute one of the most paradigmatic fields in which multi-stakeholder engagement, especially from patients, is needed for success. Clinical research infrastructures and expertise networks offer opportunities for establishing evidence-based clinical practice within rare diseases.

Identification of Acute Decompensated Heart Failure Hospitalizations Using Administrative Data

Hospitalization for acute decompensated heart failure (ADHF) is an important outcome in clinical trials and heart failure registries; however, the optimal strategy to identify these hospitalizations using International Classification of Diseases, Ninth Revision (ICD-9) codes is uncertain. We sought to identify diagnostic codes that improve ascertainment of ADHF hospitalizations. Heart failure-related ICD-9 principal discharge codes were used to identify 2,202 hospitalizations within the Minneapolis Veterans Affairs Medical Center from 2009 to 2014. Two independent reviewers adjudicated 447 of these hospitalizations to determine the accuracy of each code. We then applied our findings to an unadjusted nationwide sample containing the same ICD-9 codes of interest, from which overall positive predictive value (PPV), sensitivity, and accuracy were calculated. Use of 428.x alone resulted in a PPV of 91.3% (95% confidence interval [CI] 91.0 to 91.7), sensitivity of 97.5% (95% CI 97.3 to 97.6), and accuracy of 89.7% (95% CI 89.4 to 90.0). Combining 428.x with 402.x1, 404.x1, 415, and 518.4 resulted in improved sensitivity (99.2%; 95% CI 99.0 to 99.3) and accuracy (90.7%; 95% CI 90.4 to 91.1) while maintaining a PPV of 91.1% (95% CI 90.7 to 91.4). Excluding chronic heart failure codes (428.22, 428.32, and 428.42) from the proposed strategy resulted in an improvement of PPV to 92.3% (95% CI 92.0 to 92.6), although sensitivity and accuracy decreased to 96.6% (95% CI 96.3 to 96.8) and 90.0% (95% CI 89.6 to 90.3), respectively. In conclusion, a combination of codes including 428.x, 402.x1, 404.x1, 415, and 518.4 improves sensitivity and overall accuracy in ascertaining ADHF events compared with 428.x alone. This strategy could be further improved by manual adjudication of chronic heart failure codes.

Improving public health by improving clinical trial guidelines and their application

Evidence generated from randomized controlled trials forms the foundation of cardiovascular therapeutics and has led to the adoption of numerous drugs and devices that prolong survival and reduce morbidity, as well as the avoidance of interventions that have been shown to be ineffective or even unsafe. Many aspects of cardiovascular research have evolved considerably since the first randomized trials in cardiology were conducted. In order to be large enough to provide reliable evidence about effects on major outcomes, cardiovascular trials may now involve thousands of patients recruited from hundreds of clinical sites in many different countries. Costly infrastructure has developed to meet the increasingly complex organizational and operational requirements of these clinical trials. Concerns have been raised that this approach is unsustainable, inhibiting the reliable evaluation of new and existing treatments, to the detriment of patient care. These issues were considered by patients, regulators, funders, and trialists at a meeting of the European Society of Cardiology Cardiovascular Roundtable in October 2015. This paper summarizes the key insights and discussions from the workshop, highlights subsequent progress, and identifies next steps to produce meaningful change in the conduct of cardiovascular clinical research.

Predictors of patient's intentions to participate in pragmatic clinical trials: An initial exploration

The Veterans Health Administration is implementing a pragmatic trial research program, called Point of Care Research (POC-R). The purpose of this telephone survey in which respondents were randomized to different framing conditions of the purpose of POC-R was to determine the impact of differing frames of the purpose of POC-R on attitudes towards the program and intentions to participate; and the relative importance of different beliefs and attitudes in discriminating low vs. high intenders to participate in POC-R. The survey addressed veterans' perceptions and attitudes towards POC-R, and their willingness to participate in a pragmatic trial. Overall, respondents felt positively towards POC-R and intended to participate. Differing frames of the purpose of POC-R were not associated with either attitudes (towards the program) or intentions to participate. However, specific beliefs and attitudes toward POC-R program were predictive of intentions to participate.

Electronic Health Record-Enabled Research in Children Using the Electronic Health Record for Clinical Discovery

Initially described more than 50 years ago, electronic health records (EHRs) are now becoming ubiquitous throughout pediatric health care settings. The confluence of increased EHR implementation and the exponential growth of digital data within them, the development of clinical informatics tools and techniques, and the growing workforce of experienced EHR users presents new opportunities to use EHRs to augment clinical discovery and improve pediatric patient care. This article reviews the basic concepts surrounding EHR-enabled research and clinical discovery, including the types and fidelity of EHR data elements, EHR data validation/corroboration, and the steps involved in analytical interrogation.

Text Mining for Precision Medicine: Bringing Structure to EHRs and Biomedical Literature to Understand Genes and Health

The key question of precision medicine is whether it is possible to find clinically actionable granularity in diagnosing disease and classifying patient risk. The advent of next-generation sequencing and the widespread adoption of electronic health records (EHRs) have provided clinicians and researchers a wealth of data and made possible the precise characterization of individual patient genotypes and phenotypes. Unstructured text-found in biomedical publications and clinical notes-is an important component of genotype and phenotype knowledge. Publications in the biomedical literature provide essential information for interpreting genetic data. Likewise, clinical notes contain the richest source of phenotype information in EHRs. Text mining can render these texts computationally accessible and support information extraction and hypothesis generation. This chapter reviews the mechanics of text mining in precision medicine and discusses several specific use cases, including database curation for personalized cancer medicine, patient outcome prediction from EHR-derived cohorts, and pharmacogenomic research. Taken as a whole, these use cases demonstrate how text mining enables effective utilization of existing knowledge sources and thus promotes increased value for patients and healthcare systems. Text mining is an indispensable tool for translating genotype-phenotype data into effective clinical care that will undoubtedly play an important role in the eventual realization of precision medicine.

Quality improvement and practice-based research in neurology using the electronic medical record

We describe quality improvement and practice-based research using the electronic medical record (EMR) in a community health system-based department of neurology. Our care transformation initiative targets 10 neurologic disorders (brain tumors, epilepsy, migraine, memory disorders, mild traumatic brain injury, multiple sclerosis, neuropathy, Parkinson disease, restless legs syndrome, and stroke) and brain health (risk assessments and interventions to prevent Alzheimer disease and related disorders in targeted populations). Our informatics methods include building and implementing structured clinical documentation support tools in the EMR; electronic data capture; enrollment, data quality, and descriptive reports; quality improvement projects; clinical decision support tools; subgroup-based adaptive assignments and pragmatic trials; and DNA biobanking. We are sharing EMR tools and deidentified data with other departments toward the creation of a Neurology Practice-Based Research Network. We discuss practical points to assist other clinical practices to make quality improvements and practice-based research in neurology using the EMR a reality.

The rise of big clinical databases

BACKGROUND

The routine collection of large amounts of clinical data, 'big data', is becoming more common, as are research studies that make use of these data source. The aim of this paper is to provide an overview of the uses of data from large multi-institution clinical databases for research.

METHODS

This article considers the potential benefits, the types of data source, and the use to which the data is put. Additionally, the main challenges associated with using these data sources for research purposes are considered.

RESULTS

Common uses of the data include: providing population characteristics; identifying risk factors and developing prediction (diagnostic or prognostic) models; observational studies comparing different interventions; exploring variation between healthcare providers; and as a supplementary source of data for another study. The main advantages of using such big data sources are their comprehensive nature, the relatively large number of patients they comprise, and the ability to compare healthcare providers. The main challenges are demonstrating data quality and confidently applying a causal interpretation to the study findings.

CONCLUSION

Large clinical database research studies are becoming ubiquitous and offer a number of potential benefits. However, the limitations of such data sources must not be overlooked; each research study needs to be considered carefully in its own right, together with the justification for using the data for that specific purpose.

Comparing alternative design options for chronic disease prevention interventions

BACKGROUND

While the randomized clinical trial is considered to provide the highest level of evidence in clinical medicine, its superiority to other study designs in the context of prevention studies is debated. The purpose of this review was (i) to gather evidence about challenges facing both randomized controlled trials and observational designs for the conduct of population-based chronic disease prevention interventions and (ii) to consider the suitability of recently proposed hybrid designs for population-based prevention intervention studies.

METHODS

Rapid review methods were employed for this study. Articles published within 2007-2012, were included if they: (i) discussed challenges or benefits related to any intervention study design, (ii) compared randomized controlled trials (RCT) and observational designs or (iii) introduced a new study design potentially applicable to population-based interventions. After initial screening, papers retained for inclusion were subjected to content analysis and synthesis.

RESULTS

A total of 35 included articles were reviewed and used for synthesis. Both RCTs and observational studies are subject to multiple challenges, the main being external and internal validity for RCTs and observational designs, respectively. Four new hybrid designs identified.

CONCLUSION

Although any high quality design can produce high level of evidence, multiple challenges with prevention intervention RCTs or observational studies identified. New hybrid designs that carry benefits of randomized and observational methods may be the road ahead for to assess the effects of population-based interventions.

Pragmatic trials can be designed as optimal medical care: principles and methods of care trials

OBJECTIVES

The way clinical research and care are currently separated encourages the practice of unverifiable medicine. Some pragmatic trials can be designed (1) to guide proper medical conduct in the presence of uncertainty and (2) to govern the distinction between unvalidated and validated care.

METHODS

Care trials are simple randomized trials integrated into a practice they regulate in the interest of present patients. The fundamental principle guiding the design of a care trial is the protection of the patient being offered medical care that has not yet been validated. Selection criteria are inclusive, to assist most current patients confronted with the problem. The trial entails no extra tests or risks beyond what is proven beneficial. Endpoints are pre-defined, simple, valuable and resistant to bias. Follow-up visits and tests are routine. Data is collected in simple case-report forms.

RESULTS

Care trials protect present patients from both unverifiable medicine and research performed for extraneous interests. They provide prudent care when evidence is lacking. They should not be obstructed by the need for separate funding, or by bureaucracy.

CONCLUSION

Care trials can identify which medical alternative should be standard therapy. In the meantime, they provide optimal care in the presence of uncertainty.

Clinical trials in crisis: Four simple methodologic fixes

There is growing consensus that the US clinical trials system is broken, with trial costs and complexity increasing exponentially, and many trials failing to accrue. Yet, concerns about the expense and failure rate of randomized trials are only the tip of the iceberg; perhaps what should worry us most is the number of trials that are not even considered because of projected costs and poor accrual. Several initiatives, including the Clinical Trials Transformation Initiative and the "Sensible Guidelines Group" seek to push back against current trends in clinical trials, arguing that all aspects of trials-including design, approval, conduct, monitoring, analysis, and dissemination-should be based on evidence rather than contemporary norms. Proposed here are four methodologic fixes for current clinical trials. The first two aim to simplify trials, reducing costs, and increasing patient acceptability by dramatically reducing eligibility criteria-often to the single criterion that the consenting physician is uncertain which of the two randomized arms is optimal-and by clinical integration, investment in data infrastructure to bring routinely collected data up to research grade to be used as endpoints in trials. The second two methodologic fixes aim to shed barriers to accrual, either by cluster randomization of clinicians (in the case of modifications to existing treatment) or by early consent, where patients are offered the chance of being randomly selected to be offered a novel intervention if disease progresses at a subsequent point. Such solutions may be partial, or result in a new set of problems of their own. Yet, the current crisis in clinical trials mandates innovative approaches: randomized trials have resulted in enormous benefits for patients, and we need to ensure that they continue to do so.

Design considerations for point-of-care clinical trials comparing methadone and buprenorphine treatment for opioid dependence in pregnancy and for neonatal abstinence syndrome

RATIONALE

In recent years, the U.S. has experienced a significant increase in the prevalence of pregnant opioid-dependent women and of neonatal abstinence syndrome (NAS), which is caused by withdrawal from in-utero drug exposure. While methadone-maintenance currently is the standard of care for opioid dependence during pregnancy, research suggests that buprenorphine-maintenance may be associated with shorter infant hospital lengths of stay (LOS) relative to methadone-maintenance. There is no "gold standard" treatment for NAS but there is evidence that buprenorphine, relative to morphine or methadone, treatment may reduce LOS and length of treatment.

DESIGN

Point-of-care clinical trial (POCCT) designs, maximizing external validity while reducing cost and complexity associated with classic randomized clinical trials, were selected for two planned trials to compare methadone to buprenorphine treatment for opioid dependence during pregnancy and for NAS. This paper describes design considerations for the Medication-assisted treatment for Opioid-dependent expecting Mothers (MOMs; estimated N = 370) and Investigation of Narcotics for Ameliorating Neonatal abstinence syndrome on Time in hospital (INFANTs; estimated N = 284) POCCTs, both of which are randomized, intent-to-treat, two-group trials. Outcomes would be obtained from participants' electronic health record at three participating hospitals. Additionally, a subset of infants in the INFANTs POCCT would be from mothers in the MOMs POCCT and, thus, potential interaction between medication treatment of mother and infant could be evaluated.

CONCLUSION

This pair of planned POCCTs would evaluate the comparative effectiveness of treatments for opioid dependence during pregnancy and for NAS. The results could have a significant impact on practice.

Electronic health records for intervention research: a cluster randomized trial to reduce antibiotic prescribing in primary care (eCRT study)

PURPOSE

This study aimed to implement a point-of-care cluster randomized trial using electronic health records. We evaluated the effectiveness of electronically delivered decision support tools at reducing antibiotic prescribing for respiratory tract infections in primary care.

METHODS

Family practices from England and Scotland participating in the Clinical Practice Research Datalink (CPRD) were included in the trial; 53 family practices were allocated to intervention and 51 practices were allocated to usual care. Patients aged 18 to 59 years consulting for respiratory tract infections were eligible. The intervention was through remotely installed, computer-delivered decision support tools accessed during the consultations. Control practices provided usual care. The primary outcome was the proportion of consultations for respiratory tract infections with an antibiotic prescribed based on electronic health records. Family practice-specific proportions were included in a cluster-level analysis.

RESULTS

Data were analyzed for 603,409 patients: 317,717 at intervention practices and 285,692 at control practices. Use of the intervention was less than anticipated, varying among practices. There was a reduction in proportion of consultations with antibiotics prescribed of 1.85% (95% CI, 0.10%-3.59%, P=.038) and in the rate of antibiotic prescribing for respiratory tract infections (9.69%; 95% CI, 0.75%-18.63%, fewer prescriptions per 1,000 patient-years, P=.034). There were no adverse events.

CONCLUSIONS

Cluster randomized trials may be implemented efficiently in large samples from routine care settings by using primary care electronic health records. Future studies should develop and test multicomponent methods for remotely delivered intervention.

Multimorbidity and evidence generation

Most people with a chronic disease actually have more than one, a condition known as multimorbidity. Despite this, the evidence base to prevent adverse disease outcomes has taken a disease-specific approach. Drawing on a conference, Improving Guidelines for Multimorbid Patients, the goal of this paper is to identify challenges to the generation of evidence to support the care of people with multimorbidity and to make recommendations for improvement. We identified three broad categories of challenges: 1) challenges to defining and measuring multimorbidity; 2) challenges related to the effects of multimorbidity on study design, implementation and analysis; and 3) challenges inherent in studying heterogeneity of treatment effects in patients with differing comorbid conditions. We propose a set of recommendations for consideration by investigators and others (reviewers, editors, funding agencies, policymaking organizations) involved in the creation of evidence for this common type of person that address each of these challenges. The recommendations reflect a general approach that emphasizes broader inclusion (recruitment and retention) of patients with multimorbidity, coupled with more rigorous efforts to measure comorbidity and comorbidity burden and the influence of multimorbidity on outcomes and the effects of therapy. More rigorous examination of heterogeneity of treatment effects requires careful attention to prioritizing the most important comorbid-related questions, and also requires studies that provide greater statistical power than conventional trials have provided. Relatively modest changes in the orientation of current research along these lines can be helpful in pointing to and partially addressing selected knowledge gaps. However, producing a robust evidence base to support patient-centered decision making in complex individuals with multimorbidity, exposed to many different combinations of potentially interacting factors that can modify the risks and benefits of therapies, is likely to require a clinical research enterprise fundamentally restructured to be more fully integrated with routine clinical practice.

Rapid learning for precision oncology

The emerging paradigm of Precision Oncology 3.0 uses panomics and sophisticated methods of statistical reverse engineering to hypothesize the putative networks that drive a given patient's tumour, and to attack these drivers with combinations of targeted therapies. Here, we review a paradigm termed Rapid Learning Precision Oncology wherein every treatment event is considered as a probe that simultaneously treats the patient and provides an opportunity to validate and refine the models on which the treatment decisions are based. Implementation of Rapid Learning Precision Oncology requires overcoming a host of challenges that include developing analytical tools, capturing the information from each patient encounter and rapidly extrapolating it to other patients, coordinating many patient encounters to efficiently search for effective treatments, and overcoming economic, social and structural impediments, such as obtaining access to, and reimbursement for, investigational drugs.

[Public clinical trials: which kind of monitoring should be used?]

OBJECTIVE

Sponsors must take responsibility for the quality of trials at the best possible cost. Our objective was to describe the most frequent quality failures, how they impact trial results, and identify the most efficient monitoring strategies using published articles and reports.

RESULTS

Errors affecting clinical trials include conception, procedures, data management, and data analysis. The consequences are usually an overestimation of the treatment effect. No study shows that monitoring reduces the risk of errors, and there is no comparison of monitoring methods. Many research organisations advocate for monitoring based on risk analysis and recommend an extensive use of centralised monitoring.

CONCLUSIONS

Trial quality depends on trial conception and design. Study conduct should guarantee a maximum level of quality level. This should be done using risk management and extensive centralised monitoring.

General practice-based clinical trials in Germany - a problem analysis

BACKGROUND

In Germany, clinical trials and comparative effectiveness studies in primary care are still very rare, while their usefulness has been recognised in many other countries. A network of researchers from German academic general practice has explored the reasons for this discrepancy.

METHODS

Based on a comprehensive literature review and expert group discussions, problem analyses as well as structural and procedural prerequisites for a better implementation of clinical trials in German primary care are presented.

RESULTS

In Germany, basic biomedical science and technology is more reputed than clinical or health services research. Clinical trials are funded by industry or a single national programme, which is highly competitive, specialist-dominated, exclusive of pilot studies, and usually favours innovation rather than comparative effectiveness studies. Academic general practice is still not fully implemented, and existing departments are small. Most general practitioners (GPs) work in a market-based, competitive setting of small private practices, with a high case load. They have no protected time or funding for research, and mostly no research training or experience. Good Clinical Practice (GCP) training is compulsory for participation in clinical trials. The group defined three work packages to be addressed regarding clinical trials in German general practice: (1) problem analysis, and definition of (2) structural prerequisites and (3) procedural prerequisites. Structural prerequisites comprise specific support facilities for general practice-based research networks that could provide practices with a point of contact. Procedural prerequisites consist, for example, of a summary of specific relevant key measures, for example on a web platform. The platform should contain standard operating procedures (SOPs), templates, checklists and other supporting materials for researchers.

CONCLUSION

All in all, our problem analyses revealed that a substantial number of barriers contribute to the low implementation of clinical research in German general practice. Some issues are deeply rooted in Germany's market-based healthcare and academic systems and traditions. However, new developments may facilitate change: recent developments in the German research landscape are encouraging.

The role for pragmatic randomized controlled trials (pRCTs) in comparative effectiveness research

There is a growing appreciation that our current approach to clinical research leaves important gaps in evidence from the perspective of patients, clinicians, and payers wishing to make evidence-based clinical and health policy decisions. This has been a major driver in the rapid increase in interest in comparative effectiveness research (CER), which aims to compare the benefits, risks, and sometimes costs of alternative health-care interventions in 'the real world'. While a broad range of experimental and nonexperimental methods will be used in conducting CER studies, many important questions are likely to require experimental approaches - that is, randomized controlled trials (RCTs). Concerns about the generalizability, feasibility, and cost of RCTs have been frequently articulated in CER method discussions. Pragmatic RCTs (or 'pRCTs') are intended to maintain the internal validity of RCTs while being designed and implemented in ways that would better address the demand for evidence about real-world risks and benefits for informing clinical and health policy decisions. While the level of interest and activity in conducting pRCTs is increasing, many challenges remain for their routine use. This article discusses those challenges and offers some potential ways forward.

The role of comparative effectiveness research in transfusion medicine clinical trials: proceedings of a National Heart, Lung, and Blood Institute workshop

Comparative effectiveness research (CER) is the study of existing treatments or ways to deliver health care to determine what intervention works best under specific circumstances. CER evaluates evidence from existing studies or generates new evidence, in different populations and under specific conditions in which the treatments are actually used. CER does not embrace one research design over another but compares treatments and variations in practice using methods that are most likely to yield widely generalizable results that are directly relevant to clinical practice. Treatments used in transfusion medicine (TM) are among the most widely used in clinical practice, but are among the least well studied. High-quality evidence is lacking for most transfusion practices, with research efforts hampered by regulatory restrictions and ethical barriers. To begin addressing these issues, the National Heart, Lung, and Blood Institute convened a workshop in June 2011 to address the potential role of CER in the generation of high-quality evidence for TM decision making. Workshop goals were to: 1) evaluate the current landscape of clinical research, 2) review the potential application of CER methods to clinical research, 3) assess potential barriers to the use of CER methodology, 4) determine whether pilot or vanguard studies can be used to facilitate planning of future CER research, and 5) consider the need for and delivery of training in CER methods for researchers.

Feasibility study of a clinically-integrated randomized trial of modifications to radical prostatectomy

Abstract

Trial registration

ClinicalTrials.gov NCT00928850