Automated conversation system before pediatric primary care visits: a randomized trial

The AI Will See You Now: Feasibility and Acceptability of a Conversational AI Medical Interviewing System

Background

Primary care physicians (PCPs) are often limited in their ability to collect detailed medical histories from patients, which can lead to errors or delays in diagnosis. Recent advances in artificial intelligence (AI) show promise in augmenting current human-driven methods of collecting personal and family histories; however, such tools are largely unproven.

Objective

The main aim of this pilot study was to evaluate the feasibility and acceptability of a conversational AI medical interviewing system among patients.

Methods

The study was conducted among adult patients empaneled at a family medicine clinic within a large academic medical center in Northern California. Participants were asked to test an AI medical interviewing system, which uses a conversational avatar and chatbot to capture medical histories and identify patients with risk factors. After completing an interview with the AI system, participants completed a web-based survey inquiring about the performance of the system, the ease of using the system, and attitudes toward the system. Responses on a 7-point Likert scale were collected and evaluated using descriptive statistics.

Results

A total of 20 patients with a mean age of 50 years completed an interview with the AI system, including 12 females (60%) and 8 males (40%); 11 were White (55%), 8 were Asian (40%), and 1 was Black (5%), and 19 had at least a bachelor’s degree (95%). Most participants agreed that using the system to collect histories could help their PCPs have a better understanding of their health (16/20, 80%) and help them stay healthy through identification of their health risks (14/20, 70%). Those who reported that the system was clear and understandable, and that they were able to learn it quickly, tended to be younger; those who reported that the tool could motivate them to share more comprehensive histories with their PCPs tended to be older.

Conclusions

In this feasibility and acceptability pilot of a conversational AI medical interviewing system, the majority of patients believed that it could help clinicians better understand their health and identify health risks; however, patients were split on the effort required to use the system, and whether AI should be used for medical interviewing. Our findings suggest areas for further research, such as understanding the user interface factors that influence ease of use and adoption, and the reasons behind patients’ attitudes toward AI-assisted history-taking.

Digital Health Interventions to Enhance Prevention in Primary Care: Scoping Review

Background

Disease prevention is a central aspect of primary care practice and is comprised of primary (eg, vaccinations), secondary (eg, screenings), tertiary (eg, chronic condition monitoring), and quaternary (eg, prevention of overmedicalization) levels. Despite rapid digital transformation of primary care practices, digital health interventions (DHIs) in preventive care have yet to be systematically evaluated.

Objective

This review aimed to identify and describe the scope and use of current DHIs for preventive care in primary care settings.

Methods

A scoping review to identify literature published from 2014 to 2020 was conducted across multiple databases using keywords and Medical Subject Headings terms covering primary care professionals, prevention and care management, and digital health. A subgroup analysis identified relevant studies conducted in US primary care settings, excluding DHIs that use the electronic health record (EHR) as a retrospective data capture tool. Technology descriptions, outcomes (eg, health care performance and implementation science), and study quality as per Oxford levels of evidence were abstracted.

Results

The search yielded 5274 citations, of which 1060 full-text articles were identified. Following a subgroup analysis, 241 articles met the inclusion criteria. Studies primarily examined DHIs among health information technologies, including EHRs (166/241, 68.9%), clinical decision support (88/241, 36.5%), telehealth (88/241, 36.5%), and multiple technologies (154/241, 63.9%). DHIs were predominantly used for tertiary prevention (131/241, 54.4%). Of the core primary care functions, comprehensiveness was addressed most frequently (213/241, 88.4%). DHI users were providers (205/241, 85.1%), patients (111/241, 46.1%), or multiple types (89/241, 36.9%). Reported outcomes were primarily clinical (179/241, 70.1%), and statistically significant improvements were common (192/241, 79.7%). Results were summarized across the following 5 topics for the most novel/distinct DHIs: population-centered, patient-centered, care access expansion, panel-centered (dashboarding), and application-driven DHIs. The quality of the included studies was moderate to low.

Conclusions

Preventive DHIs in primary care settings demonstrated meaningful improvements in both clinical and nonclinical outcomes, and across user types; however, adoption and implementation in the US were limited primarily to EHR platforms, and users were mainly clinicians receiving alerts regarding care management for their patients. Evaluations of negative results, effects on health disparities, and many other gaps remain to be explored.

Coordinating Healthcare with Artificial intelligence-supported Technology for Atrial Fibrillation patients (CHAT-AF): Protocol for a Randomised Controlled Trial (Preprint)

Background

Atrial fibrillation (AF) is an increasingly common chronic health condition for which integrated care that is multidisciplinary and patient-centric is recommended yet challenging to implement.

Objective

The aim of Coordinating Health Care With Artificial Intelligence–Supported Technology in AF is to evaluate the feasibility and potential efficacy of a digital intervention (AF-Support) comprising preprogrammed automated telephone calls (artificial intelligence conversational technology), SMS text messages, and emails, as well as an educational website, to support patients with AF in self-managing their condition and coordinate primary and secondary care follow-up.

Methods

Coordinating Health Care With Artificial Intelligence–Supported Technology in AF is a 6-month randomized controlled trial of adult patients with AF (n=385), who will be allocated in a ratio of 4:1 to AF-Support or usual care, with postintervention semistructured interviews. The primary outcome is AF-related quality of life, and the secondary outcomes include cardiovascular risk factors, outcomes, and health care use. The 4:1 allocation design enables a detailed examination of the feasibility, uptake, and process of the implementation of AF-Support. Participants with new or ongoing AF will be recruited from hospitals and specialist-led clinics in Sydney, New South Wales, Australia. AF-Support has been co-designed with clinicians, researchers, information technologists, and patients. Automated telephone calls will occur 7 times, with the first call triggered to commence 24 to 48 hours after enrollment. Calls follow a standard flow but are customized to vary depending on patients’ responses. Calls assess AF symptoms, and participants’ responses will trigger different system responses based on prespecified protocols, including the identification of red flags requiring escalation. Randomization will be performed electronically, and allocation concealment will be ensured. Because of the nature of this trial, only outcome assessors and data analysts will be blinded. For the primary outcome, groups will be compared using an analysis of covariance adjusted for corresponding baseline values. Randomized trial data analysis will be performed according to the intention-to-treat principle, and qualitative data will be thematically analyzed.

Results

Ethics approval was granted by the Western Sydney Local Health District Human Ethics Research Committee, and recruitment started in December 2020. As of December 2021, a total of 103 patients had been recruited.

Conclusions

This study will address the gap in knowledge with respect to the role of postdischarge digital care models for supporting patients with AF.

Trial Registration

Australian New Zealand Clinical Trials Registry ACTRN12621000174886; https://www.australianclinicaltrials.gov.au/anzctr/trial/ACTRN12621000174886

International Registered Report Identifier (IRRID)

DERR1-10.2196/34470

The Use and Promise of Conversational Agents in Digital Health

OBJECTIVES

To describe the use and promise of conversational agents in digital health-including health promotion andprevention-and how they can be combined with other new technologies to provide healthcare at home.

METHOD

A narrative review of recent advances in technologies underpinning conversational agents and their use and potential for healthcare and improving health outcomes.

RESULTS

By responding to written and spoken language, conversational agents present a versatile, natural user interface and have the potential to make their services and applications more widely accessible. Historically, conversational interfaces for health applications have focused mainly on mental health, but with an increase in affordable devices and the modernization of health services, conversational agents are becoming more widely deployed across the health system. We present our work on context-aware voice assistants capable of proactively engaging users and delivering health information and services. The proactive voice agents we deploy, allow us to conduct experience sampling in people's homes and to collect information about the contexts in which users are interacting with them.

CONCLUSION

In this article, we describe the state-of-the-art of these and other enabling technologies for speech and conversation and discuss ongoing research efforts to develop conversational agents that "live" with patients and customize their service offerings around their needs. These agents can function as 'digital companions' who will send reminders about medications and appointments, proactively check in to gather self-assessments, and follow up with patients on their treatment plans. Together with an unobtrusive and continuous collection of other health data, conversational agents can provide novel and deeply personalized access to digital health care, and they will continue to become an increasingly important part of the ecosystem for future healthcare delivery.

The Effectiveness of Artificial Intelligence Conversational Agents in Health Care: Systematic Review

BACKGROUND

The high demand for health care services and the growing capability of artificial intelligence have led to the development of conversational agents designed to support a variety of health-related activities, including behavior change, treatment support, health monitoring, training, triage, and screening support. Automation of these tasks could free clinicians to focus on more complex work and increase the accessibility to health care services for the public. An overarching assessment of the acceptability, usability, and effectiveness of these agents in health care is needed to collate the evidence so that future development can target areas for improvement and potential for sustainable adoption.

OBJECTIVE

This systematic review aims to assess the effectiveness and usability of conversational agents in health care and identify the elements that users like and dislike to inform future research and development of these agents.

METHODS

PubMed, Medline (Ovid), EMBASE (Excerpta Medica dataBASE), CINAHL (Cumulative Index to Nursing and Allied Health Literature), Web of Science, and the Association for Computing Machinery Digital Library were systematically searched for articles published since 2008 that evaluated unconstrained natural language processing conversational agents used in health care. EndNote (version X9, Clarivate Analytics) reference management software was used for initial screening, and full-text screening was conducted by 1 reviewer. Data were extracted, and the risk of bias was assessed by one reviewer and validated by another.

RESULTS

A total of 31 studies were selected and included a variety of conversational agents, including 14 chatbots (2 of which were voice chatbots), 6 embodied conversational agents (3 of which were interactive voice response calls, virtual patients, and speech recognition screening systems), 1 contextual question-answering agent, and 1 voice recognition triage system. Overall, the evidence reported was mostly positive or mixed. Usability and satisfaction performed well (27/30 and 26/31), and positive or mixed effectiveness was found in three-quarters of the studies (23/30). However, there were several limitations of the agents highlighted in specific qualitative feedback.

CONCLUSIONS

The studies generally reported positive or mixed evidence for the effectiveness, usability, and satisfactoriness of the conversational agents investigated, but qualitative user perceptions were more mixed. The quality of many of the studies was limited, and improved study design and reporting are necessary to more accurately evaluate the usefulness of the agents in health care and identify key areas for improvement. Further research should also analyze the cost-effectiveness, privacy, and security of the agents.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/16934.

Designing a paediatric hospital information tool with children, parents, and healthcare staff: a UX study

BACKGROUND

The hospital patient pathway for having treatment procedures can be daunting for younger patients and their family members, especially when they are about to undergo a complex intervention. Opportunities to mentally prepare young patients for their hospital treatments, e.g. for surgical procedures, include tools such as therapeutic clowns, medical dolls, or books and board games. However, while promising in reducing pre-operative anxiety and negative behaviours, they may be resource intensive, costly, and not always readily available. In this study, we co-designed a digital hospital information system with children, parents and clinicians, in order to prepare children undergoing medical treatment.

METHOD

The study took place in the UK and consisted of two parts: In part 1, we purposively sampled 37 participants (n=22 parents, and n=15 clinicians) to understand perceptions and concerns of an hospital information platform specifically design for and addressed to children. In part 2, 14 children and 11 parents attended an audio and video recorded co-design workshop alongside a graphic designer and the research team to have their ideas explored and reflected on for the design of such information technology. Consequently, we used collected data to conduct thematic analysis and narrative synthesis.

RESULTS

Findings from the survey were categorised into four themes: (1) the prospect of a hospital information system (parents' inputs); (2) content-specific information needed for the information system (parents' and clinicians' inputs); (3) using the virtual information system to connect young patients and parents (parents' inputs); and (4) how to use the virtual hospital information system from a clinician's perspective (clinicians' inputs). In contrast, the workshop highlighted points in times children were most distressed/relaxed, and derived the ideal hospital visit in both their and their parents' perspectives.

CONCLUSIONS

The findings support the use of virtual information systems for children, in particular to explore and learn about the hospital, its facilities, and the responsibilities of healthcare professionals. Our findings call for further investigations and experiments in developing safer and more adequate delivery of care for specific age groups of healthcare users. Practical and theoretical implications for improving the quality and safety in healthcare delivery are discussed.

Pediatrician Attitudes toward Digital Voice Assistant Technology Use in Clinical Practice

OBJECTIVE

Digital voice assistant technology provides unique opportunities to enhance clinical practice. We aimed to understand factors influencing pediatric providers' current and potential use of this technology in clinical practice.

METHODS

We surveyed pediatric providers regarding current use and interest in voice technology in the workplace. Regression analyses evaluated provider characteristics associated with voice technology use. Among respondents not interested in voice technology, we elicited individual concerns.

RESULTS

Among 114 respondents, 19 (16.7%) indicated current use of voice technology in clinical practice, and 51 (44.7%) indicated use of voice technology for nonclinical purposes. Fifty-four (47.4%) reported willingness to try digital voice assistant technology in the clinical setting. Providers who had longer clinic visits (odds ratio [OR], 3.11, 95% confidence interval [CI], 1.04, 9.33, p = 0.04), fewer patient encounters per day (p = 0.02), and worked in hospital-based practices (OR, 2.95, 95% CI, 1.08, 8.07, p = 0.03) were more likely to currently use voice technology in the office. Younger providers (p = 0.02) and those confident in the accuracy of voice technology (OR, 3.05, 95% CI, 1.38, 6.74, p = 0.005) were more willing to trial digital voice assistants in the clinical setting. Among respondents unwilling or unsure about trying voice assistant technology, the most common reasons elicited were concerns related to its accuracy (35%), efficiency (33%), and privacy (28%).

CONCLUSION

This national survey evaluating use and attitudes toward digital voice assistant technology by pediatric providers found that while only one-eighth of pediatric providers currently use digital voice assistant technology in the clinical setting, almost half are interested in trying it in the future. Younger provider age and confidence in the accuracy of voice technology are associated with provider interest in using voice technology in the clinical setting. Future development of voice technology for clinical use will need to consider accuracy of information, efficiency of use, and patient privacy for successful integration into the workplace.

Patient-mediated interventions to improve professional practice

BACKGROUND

Healthcare professionals are important contributors to healthcare quality and patient safety, but their performance does not always follow recommended clinical practice. There are many approaches to influencing practice among healthcare professionals. These approaches include audit and feedback, reminders, educational materials, educational outreach visits, educational meetings or conferences, use of local opinion leaders, financial incentives, and organisational interventions. In this review, we evaluated the effectiveness of patient-mediated interventions. These interventions are aimed at changing the performance of healthcare professionals through interactions with patients, or through information provided by or to patients. Examples of patient-mediated interventions include 1) patient-reported health information, 2) patient information, 3) patient education, 4) patient feedback about clinical practice, 5) patient decision aids, 6) patients, or patient representatives, being members of a committee or board, and 7) patient-led training or education of healthcare professionals.

OBJECTIVES

To assess the effectiveness of patient-mediated interventions on healthcare professionals' performance (adherence to clinical practice guidelines or recommendations for clinical practice).

SEARCH METHODS

We searched MEDLINE, Ovid in March 2018, Cochrane Central Register of Controlled Trials (CENTRAL) in March 2017, and ClinicalTrials.gov and the International Clinical Trials Registry (ICTRP) in September 2017, and OpenGrey, the Grey Literature Report and Google Scholar in October 2017. We also screened the reference lists of included studies and conducted cited reference searches for all included studies in October 2017.

SELECTION CRITERIA

Randomised studies comparing patient-mediated interventions to either usual care or other interventions to improve professional practice.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed studies for inclusion, extracted data and assessed risk of bias. We calculated the risk ratio (RR) for dichotomous outcomes using Mantel-Haenszel statistics and the random-effects model. For continuous outcomes, we calculated the mean difference (MD) using inverse variance statistics. Two review authors independently assessed the certainty of the evidence (GRADE).

MAIN RESULTS

We included 25 studies with a total of 12,268 patients. The number of healthcare professionals included in the studies ranged from 12 to 167 where this was reported. The included studies evaluated four types of patient-mediated interventions: 1) patient-reported health information interventions (for instance information obtained from patients about patients' own health, concerns or needs before a clinical encounter), 2) patient information interventions (for instance, where patients are informed about, or reminded to attend recommended care), 3) patient education interventions (intended to increase patients' knowledge about their condition and options of care, for instance), and 4) patient decision aids (where the patient is provided with information about treatment options including risks and benefits). For each type of patient-mediated intervention a separate meta-analysis was produced.Patient-reported health information interventions probably improve healthcare professionals' adherence to recommended clinical practice (moderate-certainty evidence). We found that for every 100 patients consulted or treated, 26 (95% CI 23 to 30) are in accordance with recommended clinical practice compared to 17 per 100 in the comparison group (no intervention or usual care). We are uncertain about the effect of patient-reported health information interventions on desirable patient health outcomes and patient satisfaction (very low-certainty evidence). Undesirable patient health outcomes and adverse events were not reported in the included studies and resource use was poorly reported.Patient information interventions may improve healthcare professionals' adherence to recommended clinical practice (low-certainty evidence). We found that for every 100 patients consulted or treated, 32 (95% CI 24 to 42) are in accordance with recommended clinical practice compared to 20 per 100 in the comparison group (no intervention or usual care). Patient information interventions may have little or no effect on desirable patient health outcomes and patient satisfaction (low-certainty evidence). We are uncertain about the effect of patient information interventions on undesirable patient health outcomes because the certainty of the evidence is very low. Adverse events and resource use were not reported in the included studies.Patient education interventions probably improve healthcare professionals' adherence to recommended clinical practice (moderate-certainty evidence). We found that for every 100 patients consulted or treated, 46 (95% CI 39 to 54) are in accordance with recommended clinical practice compared to 35 per 100 in the comparison group (no intervention or usual care). Patient education interventions may slightly increase the number of patients with desirable health outcomes (low-certainty evidence). Undesirable patient health outcomes, patient satisfaction, adverse events and resource use were not reported in the included studies.Patient decision aid interventions may have little or no effect on healthcare professionals' adherence to recommended clinical practice (low-certainty evidence). We found that for every 100 patients consulted or treated, 32 (95% CI 24 to 43) are in accordance with recommended clinical practice compared to 37 per 100 in the comparison group (usual care). Patient health outcomes, patient satisfaction, adverse events and resource use were not reported in the included studies.

AUTHORS' CONCLUSIONS

We found that two types of patient-mediated interventions, patient-reported health information and patient education, probably improve professional practice by increasing healthcare professionals' adherence to recommended clinical practice (moderate-certainty evidence). We consider the effect to be small to moderate. Other patient-mediated interventions, such as patient information may also improve professional practice (low-certainty evidence). Patient decision aids may make little or no difference to the number of healthcare professionals' adhering to recommended clinical practice (low-certainty evidence).The impact of these interventions on patient health and satisfaction, adverse events and resource use, is more uncertain mostly due to very low certainty evidence or lack of evidence.

Tailored communications for obesity prevention in pediatric primary care: a feasibility study

Recommendations for the prevention of childhood obesity encourage providers to counsel parents and their children on healthy diet and activity behaviors. This study evaluated the feasibility of a theory-based, tailored communication intervention for obesity prevention (Team Up for Health) delivered during a well-child visit. A two-armed randomized controlled trial was used. Parents of children aged 4-10 years were recruited from a list of patients due for a well-child visit at a pediatric primary care clinic. Parents were randomized to either the 'immediate' condition (parent and pediatrician received the tailored report at the well-child visit) or the 'delayed' condition (parent received the report at the end of the study). Self-report measures assessed physical activity, fruits, vegetables, television time, sugary drinks, and 100% fruit juice. Parents completed assessments at baseline, <48 h and 4-week follow-up. Providers were interviewed at the end of the study. Independent t-tests were used to examine between group differences. Seven areas of feasibility were evaluated: Recruitment, randomization, measurement, retention, acceptability, implementation and demand. Results showed high rates of measurement (85%) and acceptability (89%) and implementation (80%) of the intervention. In conclusion, Team Up for Health was feasible; however, a larger study is needed to evaluate its efficacy.

Supporting health-related parenting: A scoping review of programs assisted by the Internet and related technologies

Abstract eHealth interventions have been proposed as a possible solution to overcome major obstacles associated with low adherence rates, low accessibility, and high costs of parenting programs. Due to the number and variety of interventions found in the literature, this study aimed to conduct a scoping review of parenting interventions directed at supporting parents in promoting their child’s health and carrying out disease-related tasks. The scoping review identified 119 technology-based programs directed both at universal, preventive objectives and at the management and adaptation to chronic or severe acute health conditions. Several different web-based applications have been creatively used in healthrelated parenting interventions. Most programs use evidence-based psychological methodologies to promote parental self-management, build specific parenting skills, and provide customized feedback and social support. Further studies are needed to assess the contribution of the Internet and mobile applications to enhance the effectiveness of health-related parenting interventions and the dissemination of empirically validated programs.

Health Information Technology Coordination to Support Patient-centered Care Coordination

OBJECTIVE

To select papers published in 2014, illustrating how information technology can contribute to and improve patient-centered care coordination.

METHOD

The two section editors performed a literature review from Medline and Web of Science to select a list of candidate best papers on the use of information technology for patient-centered care coordination. These papers were peer-reviewed by external reviewers and three of them were selected as "best papers".

RESULTS

The first selected paper reports a qualitative study exploring the gap between current practices of care coordination in various settings and idealized longitudinal care plans. The second selected paper illustrates several unintended consequences of HIT designed to improve care coordination. The third selected paper shows that advanced analytic techniques in medical informatics can be instrumental in studying patient-centered care coordination.

CONCLUSIONS

The realization of true patient-centered care coordination is dependent upon a number of factors. Standardization of clinical documentation and HIT interoperability across organization and settings is a critical prerequisite for HIT to support patient-centered care coordination. Enabling patient involvement is an efficient means for goal setting and health information sharing. Additionally, unintended consequences of HIT tools (both positive and negative) must be measured and taken into account for quality improvement.

Automated telephone communication systems for preventive healthcare and management of long-term conditions

BACKGROUND

Automated telephone communication systems (ATCS) can deliver voice messages and collect health-related information from patients using either their telephone's touch-tone keypad or voice recognition software. ATCS can supplement or replace telephone contact between health professionals and patients. There are four different types of ATCS: unidirectional (one-way, non-interactive voice communication), interactive voice response (IVR) systems, ATCS with additional functions such as access to an expert to request advice (ATCS Plus) and multimodal ATCS, where the calls are delivered as part of a multicomponent intervention.

OBJECTIVES

To assess the effects of ATCS for preventing disease and managing long-term conditions on behavioural change, clinical, process, cognitive, patient-centred and adverse outcomes.

SEARCH METHODS

We searched 10 electronic databases (the Cochrane Central Register of Controlled Trials; MEDLINE; Embase; PsycINFO; CINAHL; Global Health; WHOLIS; LILACS; Web of Science; and ASSIA); three grey literature sources (Dissertation Abstracts, Index to Theses, Australasian Digital Theses); and two trial registries (www.controlled-trials.com; www.clinicaltrials.gov) for papers published between 1980 and June 2015.

SELECTION CRITERIA

Randomised, cluster- and quasi-randomised trials, interrupted time series and controlled before-and-after studies comparing ATCS interventions, with any control or another ATCS type were eligible for inclusion. Studies in all settings, for all consumers/carers, in any preventive healthcare or long term condition management role were eligible.

DATA COLLECTION AND ANALYSIS

We used standard Cochrane methods to select and extract data and to appraise eligible studies.

MAIN RESULTS

We included 132 trials (N = 4,669,689). Studies spanned across several clinical areas, assessing many comparisons based on evaluation of different ATCS types and variable comparison groups. Forty-one studies evaluated ATCS for delivering preventive healthcare, 84 for managing long-term conditions, and seven studies for appointment reminders. We downgraded our certainty in the evidence primarily because of the risk of bias for many outcomes. We judged the risk of bias arising from allocation processes to be low for just over half the studies and unclear for the remainder. We considered most studies to be at unclear risk of performance or detection bias due to blinding, while only 16% of studies were at low risk. We generally judged the risk of bias due to missing data and selective outcome reporting to be unclear.For preventive healthcare, ATCS (ATCS Plus, IVR, unidirectional) probably increase immunisation uptake in children (risk ratio (RR) 1.25, 95% confidence interval (CI) 1.18 to 1.32; 5 studies, N = 10,454; moderate certainty) and to a lesser extent in adolescents (RR 1.06, 95% CI 1.02 to 1.11; 2 studies, N = 5725; moderate certainty). The effects of ATCS in adults are unclear (RR 2.18, 95% CI 0.53 to 9.02; 2 studies, N = 1743; very low certainty).For screening, multimodal ATCS increase uptake of screening for breast cancer (RR 2.17, 95% CI 1.55 to 3.04; 2 studies, N = 462; high certainty) and colorectal cancer (CRC) (RR 2.19, 95% CI 1.88 to 2.55; 3 studies, N = 1013; high certainty) versus usual care. It may also increase osteoporosis screening. ATCS Plus interventions probably slightly increase cervical cancer screening (moderate certainty), but effects on osteoporosis screening are uncertain. IVR systems probably increase CRC screening at 6 months (RR 1.36, 95% CI 1.25 to 1.48; 2 studies, N = 16,915; moderate certainty) but not at 9 to 12 months, with probably little or no effect of IVR (RR 1.05, 95% CI 0.99, 1.11; 2 studies, 2599 participants; moderate certainty) or unidirectional ATCS on breast cancer screening.Appointment reminders delivered through IVR or unidirectional ATCS may improve attendance rates compared with no calls (low certainty). For long-term management, medication or laboratory test adherence provided the most general evidence across conditions (25 studies, data not combined). Multimodal ATCS versus usual care showed conflicting effects (positive and uncertain) on medication adherence. ATCS Plus probably slightly (versus control; moderate certainty) or probably (versus usual care; moderate certainty) improves medication adherence but may have little effect on adherence to tests (versus control). IVR probably slightly improves medication adherence versus control (moderate certainty). Compared with usual care, IVR probably improves test adherence and slightly increases medication adherence up to six months but has little or no effect at longer time points (moderate certainty). Unidirectional ATCS, compared with control, may have little effect or slightly improve medication adherence (low certainty). The evidence suggested little or no consistent effect of any ATCS type on clinical outcomes (blood pressure control, blood lipids, asthma control, therapeutic coverage) related to adherence, but only a small number of studies contributed clinical outcome data.The above results focus on areas with the most general findings across conditions. In condition-specific areas, the effects of ATCS varied, including by the type of ATCS intervention in use.Multimodal ATCS probably decrease both cancer pain and chronic pain as well as depression (moderate certainty), but other ATCS types were less effective. Depending on the type of intervention, ATCS may have small effects on outcomes for physical activity, weight management, alcohol consumption, and diabetes mellitus. ATCS have little or no effect on outcomes related to heart failure, hypertension, mental health or smoking cessation, and there is insufficient evidence to determine their effects for preventing alcohol/substance misuse or managing illicit drug addiction, asthma, chronic obstructive pulmonary disease, HIV/AIDS, hypercholesterolaemia, obstructive sleep apnoea, spinal cord dysfunction or psychological stress in carers.Only four trials (3%) reported adverse events, and it was unclear whether these were related to the interventions.

AUTHORS' CONCLUSIONS

ATCS interventions can change patients' health behaviours, improve clinical outcomes and increase healthcare uptake with positive effects in several important areas including immunisation, screening, appointment attendance, and adherence to medications or tests. The decision to integrate ATCS interventions in routine healthcare delivery should reflect variations in the certainty of the evidence available and the size of effects across different conditions, together with the varied nature of ATCS interventions assessed. Future research should investigate both the content of ATCS interventions and the mode of delivery; users' experiences, particularly with regard to acceptability; and clarify which ATCS types are most effective and cost-effective.

The electronic medication complete communication (EMC2) study: Rationale and methods for a randomized controlled trial of a strategy to promote medication safety in ambulatory care

BACKGROUND

Adverse drug events (ADEs) affect millions of patients annually and place a significant burden on the healthcare system. The Food and Drug Administration (FDA) has developed patient safety information for high-risk medications that pose serious public health concerns. However, there are currently few assurances that patients receive this information or are able to identify or respond correctly to ADEs.

OBJECTIVE

To evaluate the effectiveness of the Electronic Medication Complete Communication (EMC²) Strategy to promote safe medication use and reporting of ADEs in comparison to usual care.

METHODS

The automated EMC² Strategy consists of: 1) provider alerts to counsel patients on medication risks, 2) the delivery of patient-friendly medication information via the electronic health record, and 3) an automated telephone assessment to identify potential medication concerns or ADEs. The study will take place in two community health centers in Chicago, IL. Adult, English or Spanish-speaking patients (N=1200) who have been prescribed a high-risk medication will be enrolled and randomized to the intervention arm or usual care based upon practice location. The primary outcomes of the study are medication knowledge, proper medication use, and reporting of ADEs; these will be measured at baseline, 4weeks, and three months. Intervention fidelity as well as barriers and costs of implementation will be evaluated.

CONCLUSIONS

The EMC² Strategy automates a patient-friendly risk communication and surveillance process to promote safe medication use while minimizing clinic burden. This trial seeks to evaluate the effectiveness and feasibility of this strategy in comparison to usual care.

A Narrative Review of Patient and Family Engagement: The "Foundation" of the Medical "Home"

BACKGROUND

Patient and family engagement (PFE) is vital to the spirit of the medical home. This article reflects the efforts of an expert consensus panel, the Patient and Family Engagement Workgroup, as part of the Society of General Internal Medicine's 2013 Research Conference.

OBJECTIVE

To review extant literature on PFE in pediatric and adult medicine and quality improvement, highlight emerging best practices and models, suggest questions for future research, and provide references to tools and resources to facilitate implementation of PFE strategies.

METHODS

We conducted a narrative review of relevant articles published from 2000 to 2015. Additional information was retrieved from personal contact with experts and recommended sources from workgroup members.

RESULTS

Despite the theoretical importance of PFE and policy recommendations that PFE occurs at all levels across the health care system, evidence of effectiveness is limited, particularly for quality improvement. There is some evidence that PFE is effective, mostly related to engagement in the care of individual patients, but the evidence is mixed and few studies have assessed the effect of PFE on health outcomes. Measurement issues and the lack of a single comprehensive conceptual model pose challenges to progress in this field. Recommendations for future research and a list of practical tools and resources to facilitate PFE are provided.

CONCLUSIONS

Although PFE appeals to patients, families, providers, and policy-makers, research is needed to assess outcomes beyond satisfaction, address implementation barriers, and support engagement in practice redesign and quality improvement. Partnering with patients and families has great potential to support high-quality health care and optimize outcomes.