Aims Improvement collaboratives consisting of various components are used throughout healthcare to improve quality, but no study has identified which components work best. This study tested the effectiveness of different components in addiction treatment services, hypothesizing that a combination of all components would be most effective. Design An unblinded cluster-randomized trial assigned clinics to one of four groups: interest circle calls (group teleconferences), clinic-level coaching, learning sessions (large face-to-face meetings), and a combination of all three. Interest circle calls functioned as a minimal intervention comparison group. Setting Outpatient addiction treatment clinics in the U.S. Participants 201 clinics in 5 states. Measurements Clinic data managers submitted data on three primary outcomes: waiting time (mean days between first contact and first treatment), retention (percent of patients retained from first to fourth treatment session), and annual number of new patients. State and group costs were collected for a cost-effectiveness analysis. Findings Waiting time declined significantly for 3 groups: coaching (an average of −4.6 days/clinic, P=0.001), learning sessions (−3.5 days/clinic, P=0.012), and the combination (−4.7 days/clinic, P=0.001). The coaching and combination groups significantly increased the number of new patients (19.5%, P=0.028; 8.9%, P=0.029; respectively). Interest circle calls showed no significant effects on outcomes. None of the groups significantly improved retention. The estimated cost/clinic was $2,878 for coaching versus $7,930 for the combination. Coaching and the combination of collaborative components were about equally effective in achieving study aims, but coaching was substantially more cost effective. Conclusions When trying to improve the effectiveness of addiction treatment services, clinic-level coaching appears to help improve waiting time and number of new patients while other components of improvement collaboratives (interest circles calls and learning sessions) do not seem to add further value.

BackgroundDespite the near ubiquity of mobile phones, little research has been conducted on the implementation of mobile health (mHealth) apps to treat patients in primary care. Although primary care clinicians routinely treat chronic conditions such as asthma and diabetes, they rarely treat addiction, a common chronic condition. Instead, addiction is most often treated in the US health care system, if it is treated at all, in a separate behavioral health system. mHealth could help integrate addiction treatment in primary care.ObjectiveThe objective of this paper was to report the effects of implementing an mHealth system for addiction in primary care on both patients and clinicians.MethodsIn this implementation research trial, an evidence-based mHealth system named Seva was introduced sequentially over 36 months to a maximum of 100 patients with substance use disorders (SUDs) in each of three federally qualified health centers (FQHCs; primary care clinics that serve patients regardless of their ability to pay). This paper reports on patient and clinician outcomes organized according to the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework.ResultsThe outcomes according to the RE-AIM framework are as follows: Reach—Seva reached 8.31% (268/3226) of appropriate patients. Reach was limited by our ability to pay for phones and data plans for a maximum of 100 patients per clinic. Effectiveness—Patients who were given Seva had significant improvements in their risky drinking days (44% reduction, (0.7-1.25)/1.25, P=.04), illicit drug-use days (34% reduction, (2.14-3.22)/3.22, P=.01), quality of life, human immunodeficiency virus screening rates, and number of hospitalizations. Through Seva, patients also provided peer support to one another in ways that are novel in primary care settings. Adoption—Patients sustained high levels of Seva use—between 53% and 60% of the patients at the 3 sites accessed Seva during the last week of the 12-month implementation period. Among clinicians, use of the technology was less robust than use by patients, with only a handful of clinicians using Seva in each clinic and behavioral health providers making most referrals to Seva in 2 of the 3 clinics. Implementation—At 2 sites, implementation plans were realized successfully; they were delayed in the third. Maintenance—Use of Seva dropped when grant funding stopped paying for the mobile phones and data plans. Two of the 3 clinics wanted to maintain the use of Seva, but they struggled to find funding to support this.ConclusionsImplementing an mHealth system can improve care among primary care patients with SUDs, and patients using the system can support one another in their recovery. Among clinicians, however, implementation requires figuring out how information from the mHealth system will be used and making mHealth data available in the electronic health (eHealth) record. In addition, paying for an mHealth system remains a challenge.

BackgroundExternal change agents can play an essential role in healthcare organizational change efforts. This systematic review examines the role that external change agents have played within the context of multifaceted interventions designed to promote organizational change in healthcare—specifically, in primary care settings.MethodsWe searched PubMed, CINAHL, Cochrane, Web of Science, and Academic Search Premier Databases in July 2016 for randomized trials published (in English) between January 1, 2005 and June 30, 2016 in which external agents were part of multifaceted organizational change strategies. The review was conducted according to PRISMA guidelines. A total of 477 abstracts were identified and screened by 2 authors. Full text articles of 113 studies were reviewed. Twenty-one of these studies were selected for inclusion.ResultsAcademic detailing (AD) is the most prevalently used organizational change strategy employed as part of multi-component implementation strategies. Out of 21 studies, nearly all studies integrate some form of audit and feedback into their interventions. Eleven studies that included practice facilitation into their intervention reported significant effects in one or more primary outcomes.ConclusionsOur results demonstrate that practice facilitation with regular, tailored follow up is a powerful component of a successful organizational change strategy. Academic detailing alone or combined with audit and feedback alone is ineffective without intensive follow up. Provision of educational materials and use of audit and feedback are often integral components of multifaceted implementation strategies. However, we didn’t find examples where those relatively limited strategies were effective as standalone interventions. System-level support through technology (such as automated reminders or alerts) is potentially helpful, but must be carefully tailored to clinic needs.

BackgroundThis paper reports on the feasibility, acceptability, and effectiveness of an innovative implementation strategy named “systems consultation” aimed at improving adherence to clinical guidelines for opioid prescribing in primary care. While clinical guidelines for opioid prescribing have been developed, they have not been widely implemented, even as opioid abuse reaches epidemic levels.MethodsWe tested a blended implementation strategy consisting of several discrete implementation strategies, including audit and feedback, academic detailing, and external facilitation. The study compares four intervention clinics to four control clinics in a randomized matched-pairs design. Each systems consultant aided clinics on implementing the guidelines during a 6-month intervention consisting of monthly site visits and teleconferences/videoconferences. The mixed-methods evaluation employs the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) framework. Quantitative outcomes are compared using time series analysis. Qualitative methods included focus groups, structured interviews, and ethnographic field techniques.ResultsSeven clinics were randomly approached to recruit four intervention clinics. Each clinic designated a project team consisting of six to eight staff members, each with at least one prescriber. Attendance at intervention meetings was 83%. More than 80% of staff respondents agreed or strongly agreed with the statements: “I am more familiar with guidelines for safe opioid prescribing” and “My clinic’s workflow for opioid prescribing is easier.” At 6 months, statistically significant improvements were noted in intervention clinics in the percentage of patients with mental health screens, treatment agreements, urine drug tests, and opioid-benzodiazepine co-prescribing. At 12 months, morphine-equivalent daily dose was significantly reduced in intervention clinics compared to controls. The cost to deliver the strategy was $7345 per clinic. Adaptations were required to make the strategy more acceptable for primary care. Qualitatively, intervention clinics reported that chronic pain was now treated using approaches similar to those employed for other chronic conditions, such as hypertension and diabetes.ConclusionsThe systems consultation implementation strategy demonstrated feasibility, acceptability, and effectiveness in a study involving eight primary care clinics. This multi-disciplinary strategy holds potential to mitigate the prevalence of opioid addiction and ultimately may help to improve implementation of clinical guidelines across healthcare.Trial registrationClinicalTrials.gov (NCT02433496). https://clinicaltrials.gov/ct2/show/NCT02433496Registered May 5, 2015Electronic supplementary materialThe online version of this article (10.1186/s13012-018-0713-1) contains supplementary material, which is available to authorized users.

BackgroundSymptom distress in patients toward the end of life can change rapidly. Family caregivers have the potential to help patients manage those symptoms, as well as their own stress, if they are equipped with the proper resources. Electronic health (eHealth) systems may be able to provide those resources. Very sick patients may not be able to use such systems themselves to report their symptoms but family caregivers could.ObjectiveThe aim of this paper was to assess the effects on cancer patient symptom distress of an eHealth system that alerts clinicians to significant changes in the patient’s symptoms, as reported by a family caregiver.MethodsA pooled analysis from two randomized clinical trials (NCT00214162 and NCT00365963) compared outcomes at 12 months for two unblinded groups: a control group (Comprehensive Health Enhancement Support System [CHESS]-Only) that gave caregivers access to CHESS, an online support system, and an experimental group (CHESS+CR [Clinician Report]), which also had CHESS but with a CR that automatically alerted clinicians if symptoms exceeded a predetermined threshold of severity. Participants were dyads (n=235) of patients with advanced lung, breast, or prostate cancer and their respective family caregivers from 5 oncology clinics in the United States of America. The proportion of improved patient threshold symptoms was compared between groups using area-under-the-curve analysis and binomial proportion tests. The proportion of threshold symptoms out of all reported symptoms was also examined.ResultsWhen severe caregiver-reported symptoms were shared with clinicians, the symptoms were more likely to be subsequently reported as improved than when the symptoms were not shared with clinicians (P<.001). Fewer symptom reports were completed in the group of caregivers whose reports went to clinicians than in the CHESS-Only group (P<.001), perhaps because caregivers, knowing their reports might be sent to a doctor, feared they might be bothering the clinician.ConclusionsThis study suggests that an eHealth system designed for caregivers that alerts clinicians to worrisome changes in patient health status may lead to reduced patient distress.Trial RegistrationClinicaltrials.gov NCT00214162; https://clinicaltrials.gov/ct2/show/NCT00214162 (Archived by WebCite at http://www.webcitation.org/6nmgdGfuD) and Clinicaltrials.gov NCT00365963; https://clinicaltrials.gov/ct2/show/NCT00365963 (Archived by WebCite at http://www.webcitation.org/6nmh0U8VP)