Evaluation of the Acceptability and Usability of a Decision Support System to Encourage Safe and Effective Use of Opioid Therapy for Chronic, Noncancer Pain by Primary Care Providers

"It Has Improved My Practice to Be Able to Offer Alternative Treatments": A Longitudinal Qualitative Study of Oregon Medicaid Back Pain Providers

Introduction: This study aimed to understand health care providers' experiences implementing the Oregon Back Pain Policy (OBPP) over time. The Medicaid OBPP expanded coverage of evidence-based nonpharmacological therapy (NPT) for back pain and restricted access to opioid therapy and interventional approaches. Methods: The study included six online, asynchronous focus groups with providers in February 2020 (Time 1) and August 2022 (Time 2). Analysis was conducted with a longitudinal, recurrent cross-sectional approach. Analysis occurred in three stages: (1) An immersion/crystallization approach was used to analyze Time 1 focus group data, (2) reflexive thematic analysis was used to analyze Time 2 data, and (3) longitudinal analysis was used to integrate the findings across time points. Results: At Time 1, 48 clinicians and 44 NPT providers participated in the study. Time 2 included 63 clinicians and 59 NPT providers. The longitudinal analysis of the focus group data resulted in four themes: (1) general awareness of the policy, (2) providers support the policy and perceive a benefit to their patients, (3) barriers to NPT accessibility, and (4) barriers to referring patients to NPT. Conclusion: The goal of the OBPP was to improve back pain care for Oregon Medicaid members by increasing access to evidence-based NPT and decreasing reliance on opioid medications. This study revealed that, although clinicians and NPT providers supported the policy, they faced persistent implementation challenges related to referrals, prior authorizations, coverage limitations, low reimbursement rates, and a reduced workforce for NPT providers. In some cases, implementation barriers were removed during the COVID-19 pandemic, but other challenges were more prominent during the pandemic.

Use of the FallAkte Plus System as an IT Infrastructure for the North Rhine-Westphalian General Practice Research Network: Mixed Methods Usability Study

BACKGROUND

Primary care research networks can generate important information in the setting where most patients are seen and treated. However, this requires a suitable IT infrastructure (ITI), which the North Rhine-Westphalian general practice research network is looking to implement.

OBJECTIVE

This mixed methods research study aims to evaluate (study 1) requirements for an ITI and (study 2) the usability of an IT solution already available on the market, the FallAkte Plus (FA+) system for the North Rhine-Westphalian general practice research network, which comprises 8 primary care university institutes in Germany's largest state.

METHODS

In study 1, a survey was conducted among researchers from the institutes to identify the requirements for a suitable ITI. The questionnaire consisted of standardized questions with open-ended responses. In study 2, a mixed method approach combining a think-aloud approach and a quantitative survey was used to evaluate the usability and acceptance of the FA+ system among 3 user groups: researchers, general practitioners, and practice assistants. Respondents were asked to assess the usability with the validated system usability scale and to test a short questionnaire on vaccination management through FA+.

RESULTS

In study 1, five of 8 institutes participated in the requirements survey. A total of 32 user requirements related primarily to study management were identified, including data entry, data storage, and user access management. In study 2, a total of 36 participants (24 researchers and 12 general practitioners or practice assistants) were surveyed in the mixed methods study of an already existing IT solution. The tutorial video and handouts explaining how to use the FA+ system were well received. Researchers, unlike practice personnel, were concerned about data security and data protection regarding the system's emergency feature, which enables access to all patient data. The median overall system usability scale rating was 60 (IQR 33.0-85.0), whereby practice personnel (median 82, IQR 58.0-94.0) assigned higher ratings than researchers (median 44, IQR 14.0-61.5). Users appreciated the option to integrate data from practices and other health care facilities. However, they voted against the use of the FA+ system due to a lack of support for various study formats.

CONCLUSIONS

Usability assessments vary markedly by professional group and role. In its current stage of development, the FA+ system does not fully meet the requirements for a suitable ITI. Improvements in the user interface, performance, interoperability, security, and advanced features are necessary to make it more effective and user-friendly. Collaborating with end users and incorporating their feedback are crucial for the successful development of any practice network research ITI.

Exploring the role of professional identity in the implementation of clinical decision support systems-a narrative review

BACKGROUND

Clinical decision support systems (CDSSs) have the potential to improve quality of care, patient safety, and efficiency because of their ability to perform medical tasks in a more data-driven, evidence-based, and semi-autonomous way. However, CDSSs may also affect the professional identity of health professionals. Some professionals might experience these systems as a threat to their professional identity, as CDSSs could partially substitute clinical competencies, autonomy, or control over the care process. Other professionals may experience an empowerment of the role in the medical system. The purpose of this study is to uncover the role of professional identity in CDSS implementation and to identify core human, technological, and organizational factors that may determine the effect of CDSSs on professional identity.

METHODS

We conducted a systematic literature review and included peer-reviewed empirical studies from two electronic databases (PubMed, Web of Science) that reported on key factors to CDSS implementation and were published between 2010 and 2023. Our explorative, inductive thematic analysis assessed the antecedents of professional identity-related mechanisms from the perspective of different health care professionals (i.e., physicians, residents, nurse practitioners, pharmacists).

RESULTS

One hundred thirty-one qualitative, quantitative, or mixed-method studies from over 60 journals were included in this review. The thematic analysis found three dimensions of professional identity-related mechanisms that influence CDSS implementation success: perceived threat or enhancement of professional control and autonomy, perceived threat or enhancement of professional skills and expertise, and perceived loss or gain of control over patient relationships. At the technological level, the most common issues were the system's ability to fit into existing clinical workflows and organizational structures, and its ability to meet user needs. At the organizational level, time pressure and tension, as well as internal communication and involvement of end users were most frequently reported. At the human level, individual attitudes and emotional responses, as well as familiarity with the system, most often influenced the CDSS implementation. Our results show that professional identity-related mechanisms are driven by these factors and influence CDSS implementation success. The perception of the change of professional identity is influenced by the user's professional status and expertise and is improved over the course of implementation.

CONCLUSION

This review highlights the need for health care managers to evaluate perceived professional identity threats to health care professionals across all implementation phases when introducing a CDSS and to consider their varying manifestations among different health care professionals. Moreover, it highlights the importance of innovation and change management approaches, such as involving health professionals in the design and implementation process to mitigate threat perceptions. We provide future areas of research for the evaluation of the professional identity construct within health care.

The Application of Knowledge-Based Clinical Decision Support Systems to Enhance Adherence to Evidence-Based Medicine in Chronic Disease

Among the technology-based solutions, clinical decision support systems (CDSSs) have the ability to keep up with clinicians with the latest evidence in a smart way. Hence, the main objective of our study was to investigate the applicability and characteristics of CDSSs regarding chronic disease. The Web of Science, Scopus, OVID, and PubMed databases were searched using keywords from January 2000 to February 2023. The review was completed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist. Then, an analysis was done to determine the characteristics and applicability of CDSSs. The quality of the appraisal was assessed using the Mixed Methods Appraisal Tool checklist (MMAT). A systematic database search yielded 206 citations. Eventually, 38 articles from sixteen countries met the inclusion criteria and were accepted for final analysis. The main approaches of all studies can be classified into adherence to evidence-based medicine (84.2%), early and accurate diagnosis (81.6%), identifying high-risk patients (50%), preventing medical errors (47.4%), providing up-to-date information to healthcare providers (36.8%), providing patient care remotely (21.1%), and standardizing care (71.1%). The most common features among the knowledge-based CDSSs included providing guidance and advice for physicians (92.11%), generating patient-specific recommendations (84.21%), integrating into electronic medical records (60.53%), and using alerts or reminders (60.53%). Among thirteen different methods to translate the knowledge of evidence into machine-interpretable knowledge, 34.21% of studies utilized the rule-based logic technique while 26.32% of studies used rule-based decision tree modeling. For CDSS development and translating knowledge, diverse methods and techniques were applied. Therefore, the development of a standard framework for the development of knowledge-based decision support systems should be considered by informaticians.

Design and validation of a new Healthcare Systems Usability Scale (HSUS) for clinical decision support systems: a mixed-methods approach

OBJECTIVE

To develop and validate a questionnaire to assess the usability of clinical decision support systems (CDSS) and to assist in the early identification of usability issues that may impact patient safety and quality of care.

DESIGN

Mixed research methods were used to develop and validate the questionnaire. The qualitative study involved scale item development, content and face validity. Pilot testing established construct validity using factor analysis and facilitated estimates for reliability and internal consistency using the Cronbach's alpha coefficient.

SETTING

Two hospitals within a single National Health Service Trust.

PARTICIPANTS

We recruited a panel of 7 experts in usability and questionnaire writing for health purposes to test content validity; 10 participants to assess face validity and 78 participants for the pilot testing. To be eligible for this last phase, participants needed to be health professionals with at least 3 months experience using the local hospital electronic patient record system.

RESULTS

Feedback from the face and content validity phases contributed to the development and improvement of scale items. The final Healthcare Systems Usability Scale (HSUS) proved quick to complete, easy to understand and was mostly worded by potential users. Exploratory analysis revealed four factors related to patient safety, task execution, alerts or recommendations accuracy, the effects of the system on workflow and ease of system use. These separate into four subscales: patient safety and decision effectiveness (seven items), workflow integration (six items), work effectiveness (five items) and user control (four items). These factors affect the quality of care and clinician's ability to make informed and timely decisions when using CDSS. The HSUS has a very good reliability with global Cronbach's alpha 0.914 and between 0.702 and 0.926 for the four subscales.

CONCLUSION

The HSUS is a valid and reliable tool for usability testing of CDSS and early identification of usability issues that may cause medical adverse events.

Workload and workflow implications associated with the use of electronic clinical decision support tools used by health professionals in general practice: a scoping review

BACKGROUND

Electronic clinical decision support tools (eCDS) are increasingly available to assist General Practitioners (GP) with the diagnosis and management of a range of health conditions. It is unclear whether the use of eCDS tools has an impact on GP workload. This scoping review aimed to identify the available evidence on the use of eCDS tools by health professionals in general practice in relation to their impact on workload and workflow.

METHODS

A scoping review was carried out using the Arksey and O'Malley methodological framework. The search strategy was developed iteratively, with three main aspects: general practice/primary care contexts, risk assessment/decision support tools, and workload-related factors. Three databases were searched in 2019, and updated in 2021, covering articles published since 2009: Medline (Ovid), HMIC (Ovid) and Web of Science (TR). Double screening was completed by two reviewers, and data extracted from included articles were analysed.

RESULTS

The search resulted in 5,594 references, leading to 95 full articles, referring to 87 studies, after screening. Of these, 36 studies were based in the USA, 21 in the UK and 11 in Australia. A further 18 originated from Canada or Europe, with the remaining studies conducted in New Zealand, South Africa and Malaysia. Studies examined the use of eCDS tools and reported some findings related to their impact on workload, including on consultation duration. Most studies were qualitative and exploratory in nature, reporting health professionals' subjective perceptions of consultation duration as opposed to objectively-measured time spent using tools or consultation durations. Other workload-related findings included impacts on cognitive workload, "workflow" and dialogue with patients, and clinicians' experience of "alert fatigue".

CONCLUSIONS

The published literature on the impact of eCDS tools in general practice showed that limited efforts have focused on investigating the impact of such tools on workload and workflow. To gain an understanding of this area, further research, including quantitative measurement of consultation durations, would be useful to inform the future design and implementation of eCDS tools.

Study protocol: understanding pain after dental procedures, an observational study within the National Dental PBRN

BACKGROUND

Patient-reported outcome measures provide an essential perspective on the quality of health care provided. However, how data are collected, how providers value and make sense of the data, and, ultimately, use the data to create meaningful impact all influence the success of using patient-reported outcomes.

OBJECTIVES

The primary objective is to assess post-operative pain experiences by dental procedure type through 21 days post-procedure as reported by patients following dental procedures and assess patients' satisfaction with pain management following dental surgical procedures. Secondary objectives are to: 1) assess post-operative pain management strategies 1 week following dental surgical procedures, as recommended by practitioners and reported by patients, and 2) evaluate practitioner and patient acceptance of the FollowApp.Care post visit patient monitoring technology (FollowApp.Care). We will evaluate FollowApp.Care usage, perceived usefulness, ease of use, and impact on clinical workload.

DESIGN AND METHODS

We describe the protocol for an observational study involving the use of the FollowApp.Care platform, an innovative mobile application that collects dental patients' assessments of their post-operative symptoms (e.g., pain). The study will be conducted in collaboration with the National Dental Practice-based Research Network, a collective Network of dental practices that include private and group practices, public health clinics, community health centers and Federal Qualified Health Centers, academic institutional settings, and special patient populations. We will recruit a minimum of 150 and up to 215 dental providers and up to 3147 patients who will receive push notifications through text messages FollowApp.Care on their mobile phones at designated time intervals following dental procedures. This innovative approach of implementing an existing and tested mobile health system technology into the real-world dental office setting will actively track pain and other complications following dental procedures. Through patients' use of their mobile phones, we expect to promptly and precisely identify specific pain levels and other issues after surgical dental procedures. The study's primary outcome will be the patients' reported pain experiences. Secondary outcomes include pain management strategies and medications implemented by the patient and provider and perceptions of usefulness and ease of use by patients and providers.

Assessing the use of a clinical decision support tool for pain management in primary care

Objective

Given time constraints, poorly organized information, and complex patients, primary care providers (PCPs) can benefit from clinical decision support (CDS) tools that aggregate and synthesize problem-specific patient information. First, this article describes the design and functionality of a CDS tool for chronic noncancer pain in primary care. Second, we report on the retrospective analysis of real-world usage of the tool in the context of a pragmatic trial.

Materials and methods

The tool known as OneSheet was developed using user-centered principles and built in the Epic electronic health record (EHR) of 2 health systems. For each relevant patient, OneSheet presents pertinent information in a single EHR view to assist PCPs in completing guideline-recommended opioid risk mitigation tasks, review previous and current patient treatments, view patient-reported pain, physical function, and pain-related goals.

Results

Overall, 69 PCPs accessed OneSheet 2411 times (since November 2020). PCP use of OneSheet varied significantly by provider and was highly skewed (site 1: median accesses per provider: 17 [interquartile range (IQR) 9-32]; site 2: median: 8 [IQR 5-16]). Seven "power users" accounted for 70% of the overall access instances across both sites. OneSheet has been accessed an average of 20 times weekly between the 2 sites.

Discussion

Modest OneSheet use was observed relative to the number of eligible patients seen with chronic pain.

Conclusions

Organizations implementing CDS tools are likely to see considerable provider-level variation in usage, suggesting that CDS tools may vary in their utility across PCPs, even for the same condition, because of differences in provider and care team workflows.

Study protocol for a type III hybrid effectiveness-implementation trial to evaluate scaling interoperable clinical decision support for patient-centered chronic pain management in primary care

Background

The US continues to face public health crises related to both chronic pain and opioid overdoses. Thirty percent of Americans suffer from chronic noncancer pain at an estimated yearly cost of over $600 billion. Most patients with chronic pain turn to primary care clinicians who must choose from myriad treatment options based on relative risks and benefits, patient history, available resources, symptoms, and goals. Recently, with attention to opioid-related risks, prescribing has declined. However, clinical experts have countered with concerns that some patients for whom opioid-related benefits outweigh risks may be inappropriately discontinued from opioids. Unfortunately, primary care clinicians lack usable tools to help them partner with their patients in choosing pain treatment options that best balance risks and benefits in the context of patient history, resources, symptoms, and goals. Thus, primary care clinicians and patients would benefit from patient-centered clinical decision support (CDS) for this shared decision-making process.

Methods

The objective of this 3-year project is to study the adaptation and implementation of an existing interoperable CDS tool for pain treatment shared decision making, with tailored implementation support, in new clinical settings in the OneFlorida Clinical Research Consortium. Our central hypothesis is that tailored implementation support will increase CDS adoption and shared decision making. We further hypothesize that increases in shared decision making will lead to improved patient outcomes, specifically pain and physical function. The CDS implementation will be guided by the Exploration, Preparation, Implementation, Sustainment (EPIS) framework. The evaluation will be organized by the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. We will adapt and tailor PainManager, an open source interoperable CDS tool, for implementation in primary care clinics affiliated with the OneFlorida Clinical Research Consortium. We will evaluate the effect of tailored implementation support on PainManager’s adoption for pain treatment shared decision making. This evaluation will establish the feasibility and obtain preliminary data in preparation for a multi-site pragmatic trial targeting the effectiveness of PainManager and tailored implementation support on shared decision making and patient-reported pain and physical function.

Discussion

This research will generate evidence on strategies for implementing interoperable CDS in new clinical settings across different types of electronic health records (EHRs). The study will also inform tailored implementation strategies to be further tested in a subsequent hybrid effectiveness-implementation trial. Together, these efforts will lead to important new technology and evidence that patients, clinicians, and health systems can use to improve care for millions of Americans who suffer from pain and other chronic conditions.

Trial registration

ClinicalTrials.gov, NCT05256394, Registered 25 February 2022.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13012-022-01217-4.

A pilot trial of collaborative care with motivational interviewing to reduce opioid risk and improve chronic pain management

BACKGROUND AND AIMS

Opioid use and chronic pain are prevalent in the veteran population. Collaborative care enhances coordination between patients and their care teams, and motivational interviewing (MI) is a communication style designed to facilitate behavior change. This study evaluated the use of collaborative care with MI (CCMI) with patients with chronic pain and high-risk prescription opioid use.

DESIGN

Small pilot study of a randomized controlled trial.

SETTING

An urban Veterans Affairs (VA) Medical Center in the United States.

PARTICIPANTS

One hundred adult veterans with chronic pain currently enrolled into primary care and receiving long-term opioid therapy.

INTERVENTION AND COMPARATOR

During an initial 1-hour visit with a study primary-care physician (PCP), all veterans (n = 100) developed a personalized pain care plan, after which they were randomized to receive four sessions (at 4, 6, 8 and 12 weeks) of either CCMI (n = 51) or attention control psychoeducation (ACP; n = 49). Subsequently, participants had 30-minute follow-up visits with study PCPs and post-treatment assessment at 12 weeks.

MEASUREMENTS

Co-primary outcomes measures assessed opioid risk and pain interference; secondary measures assessed pain severity, PCP rating of opioid risk and pain management goals.

FINDINGS

At 12 weeks, intent-to-treat (ITT) analyses using multivariate mixed-effects linear regression were inconclusive regarding the between-group differences in primary and secondary outcomes at post-intervention (12 weeks). Bayes factors for opioid risk, pain interference, pain severity and PCP ratings were 1.96, 1.36, 0.45 and 0.82, respectively. Veterans in the CCMI group reported implementing more complementary integrative health (CIH) goals (e.g. yoga) than did those in the ACP group (d = 0.54).

CONCLUSIONS

US veterans with chronic pain who received collaborative care with motivational interviewing reduced their high-risk opioid use and showed improved pain interference and severity after an intake with a primary-care provider involving shared decision-making and the creation of a personalized pain care plan.

Barriers and facilitators influencing medication-related CDSS acceptance according to clinicians: A systematic review

BACKGROUND

A medication-related Clinical Decision Support System (CDSS) is an application that analyzes patient data to provide assistance in medication-related care processes. Despite its potential to improve the clinical decision-making process, evidence shows that clinicians do not always use CDSSs in such a way that their potential can be fully realized. This systematic literature review provides an overview of frequently-reported barriers and facilitators for acceptance of medication-related CDSS.

MATERIALS AND METHODS

Search terms and MeSH headings were developed in collaboration with a librarian, and database searches were conducted in Medline, Scopus, Embase and Web of Science Conference Proceedings. After screening 5404 records and 140 full papers, 63 articles were included in this review. Quality assessment was performed for all 63 included articles. The identified barriers and facilitators are categorized within the Human, Organization, Technology fit (HOT-fit) model.

RESULTS

A total of 327 barriers and 291 facilitators were identified. Results show that factors most often reported were related to (a lack of) usefulness and relevance of information, and ease of use and efficiency of the system.

DISCUSSION

This review provides a valuable insight into a broad range of barriers and facilitators for using a medication-related CDSS as perceived by clinicians. The results can be used as a stepping stone in future studies developing medication-related CDSSs.

Testing an individualized digital decision assist system for the diagnosis and management of mental and behavior disorders in children and adolescents

Background

Nearly half of all mental health disorders develop prior to the age of 15. Early assessments, diagnosis, and treatment are critical to shortening single episodes of care, reducing possible comorbidity and long-term disability. In Norway, approximately 20% of all children and adolescents are experiencing mental health problems. To address this, health officials in Norway have called for the integration of innovative approaches. A clinical decision support system (CDSS) is an innovative, computer-based program that provides health professionals with clinical decision support as they care for patients. CDSS use standardized clinical guidelines and big data to provide guidance and recommendations to clinicians in real-time. IDDEAS (Individualised Digital DEcision Assist System) is a CDSS for diagnosis and treatment of child and adolescent mental health disorders. The aim of IDDEAS is to enhance quality, competency, and efficiency in child and adolescent mental health services (CAMHS).

Methods/design

IDDEAS is a mixed-methods innovation and research project, which consists of four stages: 1) Assessment of Needs and Preparation of IDDEAS; 2) The Development of IDDEAS CDSS Model; 3) The Evaluation of the IDDEAS CDSS; and, 4) Implementation & Dissemination. Both qualitative and quantitative methods will be used for the evaluation of IDDEAS CDSS model. Child and adolescent psychologists and psychiatrists (n = 30) will evaluate the IDDEAS` usability, acceptability and relevance for diagnosis and treatment of attention-deficit/hyperactivity disorder.

Discussion

The IDDEAS CDSS model is the first guidelines and data-driven CDSS to improve efficiency of diagnosis and treatment of child and adolescent mental health disorders in Norway. Ultimately, IDDEAS will help to improve patient health outcomes and prevent long-term adverse outcomes by providing each patient with evidence-based, customized clinical care.

Trial registration

ISRCTN, ISRCTN12094788. Ongoing study, registered prospectively 8 April 2020 10.1186/ISRCTN12094788

An Electronic Clinical Decision Support System for the Management of Low Back Pain in Community Pharmacy: Development and Mixed Methods Feasibility Study

Background

People with low back pain (LBP) in the community often do not receive evidence-based advice and management. Community pharmacists can play an important role in supporting people with LBP as pharmacists are easily accessible to provide first-line care. However, previous research suggests that pharmacists may not consistently deliver advice that is concordant with guideline recommendations and may demonstrate difficulty determining which patients require prompt medical review. A clinical decision support system (CDSS) may enhance first-line care of LBP, but none exists to support the community pharmacist–client consultation.

Objective

This study aimed to develop a CDSS to guide first-line care of LBP in the community pharmacy setting and to evaluate the pharmacist-reported usability and acceptance of the prototype system.

Methods

A cross-platform Web app for the Apple iPad was developed in conjunction with academic and clinical experts using an iterative user-centered design process during interface design, clinical reasoning, program development, and evaluation. The CDSS was evaluated via one-to-one user-testing with 5 community pharmacists (5 case vignettes each). Data were collected via video recording, screen capture, survey instrument (system usability scale), and direct observation.

Results

Pharmacists’ agreement with CDSS-generated self-care recommendations was 90% (18/20), with medicines recommendations was 100% (25/25), and with referral advice was 88% (22/25; total 70 recommendations). Pharmacists expressed uncertainty when screening for serious pathology in 40% (10/25) of cases. Pharmacists requested more direction from the CDSS in relation to automated prompts for user input and page navigation. Overall system usability was rated as excellent (mean score 92/100, SD 6.5; 90th percentile compared with similar systems), with acceptance rated as good to excellent.

Conclusions

A novel CDSS (high-fidelity prototype) to enhance pharmacist care of LBP was developed, underpinned by clinical practice guidelines and informed by a multidisciplinary team of experts. User-testing revealed a high level of usability and acceptance of the prototype system, with suggestions to improve interface prompts and information delivery. The small study sample limits the generalizability of the findings but offers important insights to inform the next stage of system development.

Physician Responses to Enhanced Prescription Drug Monitoring Program Profiles

OBJECTIVE

Many states have begun implementing enhancements to PDMP patient profiles such as summaries or graphics to highlight issues of concern and enhance comprehension. The purpose of this study was to examine how physicians respond to sample enhanced PDMP profiles based on patient vignettes.

DESIGN

Brief semistructured interviews with physicians.

SETTING

Three national medical conferences for targeted specialties.

SUBJECTS

Ninety-three physicians practicing in primary care, emergency medicine, or pain management.

METHODS

We presented participants with one of three patient vignettes with corresponding standard and enhanced PDMP profiles and conducted brief interviews.

RESULTS

Findings indicated that enhanced profiles could increase ease of comprehension, reduce time burden, and aid in communicating with patients about opioid risks. Physicians also expressed concern about liability for prescribing when the enhanced profile indicates risk and cautioned against any implication that risk warnings should override clinical judgment based on the patient's complete medical history or presenting condition. Physicians emphasized the need for transparency of measures and evidence of validation of risk scores. We found little indication that enhanced profiles would change opioid prescribing decisions, though decisions varied by physician.

CONCLUSIONS

Our study underscores the importance of involving prescribers in developing and testing PDMP profile enhancements, as well as providing guidance in the interpretation and clinical use of enhanced profiles. Reduced time burden is an important benefit to consider as the number of states mandating PDMP use increases.

Implementing prescription drug monitoring and other clinical decision support for opioid risk mitigation in a military health care setting: a qualitative feasibility study

Objective

Chronic noncancer pain is a highly prevalent condition among service members returning from deployment overseas. The US Army has a higher rate of opioid misuse than the civilian population. Although most states and many health care systems have implemented prescription drug monitoring programs (PDMPs) or other clinician decision support (CDS) to aid providers in delivering guideline-recommended opioid therapy, similar tools are lacking in military health settings.

Materials and Methods

We conducted a pre-implementation feasibility and needs assessment guided by the Promoting Action Research in Health Services framework. Twenty-six semistructured interviews were conducted with providers from a large military health system (MHS) to assess baseline knowledge and practices in opioid risk mitigation and providers' preferences and needs for a military-based PDMP or other CDS.

Results

Military health care providers reported complex decision-making around opioid prescribing and monitoring, varied knowledge and use of existing clinical informatics, and concerns about the feasibility of implementing a military-based PDMP in their context. However, providers indicated a need for training and CDS to support opioid risk mitigation for their patients.

Discussion

This article describes providers' knowledge and behaviors around opioid risk mitigation in the MHS, and views on the potential usefulness of a military-based PDMP or other CDS. This pre-implementation study provides a model for using qualitative methods to assess feasibility and inform planning and development of CDS in complex health care settings.

Conclusion

Military providers were skeptical regarding the feasibility of MHS-based PDMP implementation, but provided important recommendations for CDS to support safe and appropriate opioid prescribing in military health care.

Integrating a safety smart list into the electronic health record decreases intensive care unit length of stay and cost

PURPOSE

To measure how an integrated smartlist developed for critically ill patients would change intensive care units (ICUs) length of stay (LOS), mortality, and charges.

MATERIALS AND METHODS

Propensity-score analysis of adult patients admitted to one of 14 surgical and medical ICUs between June 2017 and May 2018. The smart list aimed to certain preventative measures for all critical patients (e.g., removing unneeded catheters, starting thromboembolic prophylaxis, etc.) and was integrated into the electronic health record workflows at the hospitals under study.

RESULTS

During the study period, 11,979 patients were treated in the 14 participating ICUs by 518 unique providers. Patients who had the smart list used during ≥60% of their ICU stay (N = 432 patients, 3.6%) were significantly more likely to have a shorter ICU LOS (HR = 1.20, 95% CI:1.0 to 1.4, p = 0.015) with an average decrease of -$1218 (95% CI: -$1830 to -$607, P < 0.001) in the amount charged per day. The intervention cohort had fewer average ventilator days (3.05 vent days, SD = 2.55) compared to propensity score matched controls (3.99, SD = 4.68, p = 0.015), but no changes in mortality (16.7% vs 16.0%, p = 0.78).

CONCLUSIONS

An integrated smart list shortened LOS and lowered charges in a diverse cohort of critically ill patients.

Design Process and Utilization of a Novel Clinical Decision Support System for Neuropathic Pain in Primary Care: Mixed Methods Observational Study

Background

Computerized clinical decision support systems (CDSSs) have emerged as an approach to improve compliance of clinicians with clinical practice guidelines (CPGs). Research utilizing CDSS has primarily been conducted in clinical contexts with clear diagnostic criteria such as diabetes and cardiovascular diseases. In contrast, research on CDSS for pain management and more specifically neuropathic pain has been limited. A CDSS for neuropathic pain has the potential to enhance patient care as the challenge of diagnosing and treating neuropathic pain often leads to tension in clinician-patient relationships.

Objective

The aim of this study was to design and evaluate a CDSS aimed at improving the adherence of interprofessional primary care clinicians to CPG for managing neuropathic pain.

Methods

Recommendations from the Canadian CPGs informed the decision pathways. The development of the CDSS format and function involved participation of multiple stakeholders and end users in needs assessment and usability testing. Clinicians, including family medicine physicians, residents, and nurse practitioners, in three academic teaching clinics were trained in the use of the CDSS. Evaluation over one year included the measurement of utilization of the CDSS; change in reported awareness, agreement, and adoption of CPG recommendations; and change in the observed adherence to CPG recommendations.

Results

The usability testing of the CDSS was highly successful in the prototype environment. Deployment in the clinical setting was partially complete by the time of the study, with some limitations in the planned functionality. The study population had a high level of awareness, agreement, and adoption of guideline recommendations before implementation of CDSS. Nevertheless, there was a small and statistically significant improvement in the mean awareness and adoption scores over the year of observation (P=.01 for mean awareness scores at 6 and 12 months compared with baseline, for mean adoption scores at 6 months compared with baseline, and for mean adoption scores at 12 months). Documenting significant findings related to diagnosis of neuropathic pain increased significantly. Clinicians accessed CPG information more frequently than they utilized data entry functions. Nurse practitioners and first year family medicine trainees had higher utilization than physicians.

Conclusions

We observed a small increase in the adherence to CPG recommendations for managing neuropathic pain. Clinicians utilized the CDSS more as a source of knowledge and as a training tool than as an ongoing dynamic decision support.

Evaluating the Feasibility of a Software Prototype Supporting the Management of Multimorbid Seniors: Mixed Methods Study in General Practices

Background

Longitudinal, patient-centered care represents a challenge for general practices. Decision support and reminder systems can offer targeted support.

Objective

The objective of this study was to follow a user-oriented, stepwise approach to develop an add-on for German electronic health record (EHR) systems, which aims to support longitudinal care management of multimorbid seniors, using a flag system displaying patient-centered information relevant for comprehensive health care management. This study evaluated the prototype’s feasibility from both a technical and users’ perspective.

Methods

The study was conducted with 18 general practitioners (GPs) and practice assistants (PAs) from 9 general practices using a mixed methods approach. In all practices, 1 GP and 1 PA tested the software each for 4 multimorbid seniors selected from the practice patient data. Technical feasibility was evaluated by documenting all technical problems. To evaluate the feasibility from the users’ perspective, participants’ responses during the software test were documented. In addition, they completed a self-administered questionnaire, including the validated System Usability Scale (SUS). Data were merged by transforming qualitative data into quantitative data. Analyses were performed using univariate statistics in IBM SPSS statistics.

Results

From a technical perspective, the new software was easy to install and worked without problems. Difficulties during the installation occurred in practices lacking a 64-bit system or a current version of Microsoft .NET. As EHRs used in German practices do not provide an interface to extract the data needed, additional software was required. Incomplete flags for some laboratory data occurred, although this function was implemented in our software as shown in previous tests. From the users’ perspective, the new add-on provided a better overview of relevant patient information, reminded more comprehensively about upcoming examinations, and better supported guideline-based care when compared with their individual practice strategies. A total of 14 out of 18 participants (78%) were interested in using the software long-term. Furthermore, 8 of 9 GPs were willing to pay 5 to 25 Euros (mean 14.75, SD 5.93) monthly for its use. The usability was rated as 75% (43%-95%).

Conclusions

The new EHR add-on was well accepted and achieved a good usability rating measured by the validated SUS. In perspective, the legally consolidated, standardized interface to German EHRs will facilitate the technical integration. In view of the high feasibility, we plan to study the software’s effectiveness in everyday primary care.

Trial Registration

German Clinical Trials Register DRKS00008777; https://www.drks.de/drks_web/navigate.do? navigationId=trial.HTML&TRIAL_ID=DRKS00008777

Optimizing pain treatment interventions (OPTI): A pilot randomized controlled trial of collaborative care to improve chronic pain management and opioid safety-Rationale, methods, and lessons learned

Veterans seeking care in VA medical facilities have high rates of chronic pain, which often co-occur with mental health and substance use disorders, including prescription opioid misuse. The overall goal of the Optimizing Pain Treatment Interventions (OPTI) study was to pilot a 12-week Collaborative Care intervention to improve opioid safety, chronic pain disability, and use of non-pharmacological pain management strategies in veterans in VA primary care. Between November 2014 and January 2017, 100 veteran patients with chronic pain and high-risk prescription opioid use (e.g., high-dose therapy, early refills, etc.) were enrolled and completed an initial one-hour study visit with a primary care provider (PCP) within 4 weeks of enrollment. Study PCPs were guided by a web-based opioid management decision support program and templated notes in the VA electronic medical record. After assessment and education, study PCPs used Shared Decision-Making to formulate a Pain Care Plan aligned with a participant's personal values and goals. After the initial visit, patients randomized to Collaborative Care received one Motivational Interviewing (MI) session with a Care Manager followed by 3 Care Manager-delivered brief telephone MI sessions at 6, 8, and 12 weeks to reinforce Pain Care Plans; patients randomized to an Attention Control condition met with a Care Manager briefly, followed by 3 brief scripted telephone psychoeducation sessions at 6, 8, and 12 weeks. Masked evaluators assessed outcomes at baseline, end of intervention (12 weeks), and after eight weeks of no contact (20 weeks). We present study rationale, detailed methods, preliminary results and lessons learned.

Usability aspects of medication-related decision support systems in the outpatient setting: A systematic literature review

In this study, we evaluated the usability aspects of medication-related clinical decision support systems in the outpatient setting. Articles published between 2000 and 2016 in Scopus, PubMed and EMBASE were searched and classified into three usability aspects: Effectiveness, Efficiency and Satisfaction. Using Van Welie et al.’s usability model, we categorized usability aspects in terms of usage indicators and means. Out of the 1999 articles, 24 articles met the selection criteria of which the main focus was on reducing inappropriate medication, prescription rate and prescription errors. Evidence could mainly be found for Effectiveness and showed high rates of positive results in reducing medication errors. To date, the effects of Efficiency and Satisfaction of clinical decision support systems regarding medication prescription remain understudied. Usability aspects such as memorability, learnability, adaptability, shortcuts and consistency require more attention. Studies are needed for better insight into the user model and to design a knowledge/task model for clinical decision support systems regarding medication prescription.

Usability Study of Mainstream Wearable Fitness Devices: Feature Analysis and System Usability Scale Evaluation

Background

Wearable devices have the potential to promote a healthy lifestyle because of their real-time data monitoring capabilities. However, device usability is a critical factor that determines whether they will be adopted on a large scale. Usability studies on wearable devices are still scarce.

Objective

This study aims to compare the functions and attributes of seven mainstream wearable devices and to evaluate their usability.

Methods

The wearable devices selected were the Apple Watch, Samsung Gear S, Fitbit Surge, Jawbone Up3, Mi Band, Huawei Honor B2, and Misfit Shine. A mixed method of feature comparison and a System Usability Scale (SUS) evaluation based on 388 participants was applied; the higher the SUS score, the better the usability of the product.

Results

For features, all devices had step counting, an activity timer, and distance recording functions. The Samsung Gear S had a unique sports track recording feature and the Huawei Honor B2 had a unique wireless earphone. The Apple Watch, Samsung Gear S, Jawbone Up3, and Fitbit Surge could measure heart rate. All the devices were able to monitor sleep, except the Apple Watch. For product characteristics, including attributes such as weight, battery life, price, and 22 functions such as step counting, activity time, activity type identification, sleep monitoring, and expandable new features, we found a very weak negative correlation between the SUS scores and price (r=−.10, P=.03) and devices that support expandable new features (r=−.11, P=.02), and a very weak positive correlation between the SUS scores and devices that support the activity type identification function (r=.11, P=.02). The Huawei Honor B2 received the highest score of mean 67.6 (SD 16.1); the lowest Apple Watch score was only 61.4 (SD 14.7). No significant difference was observed among brands. The SUS score had a moderate positive correlation with the user’s experience (length of time the device was used) (r=.32, P<.001); participants in the medical and health care industries gave a significantly higher score (mean 61.1, SD 17.9 vs mean 68.7, SD 14.5, P=.03).

Conclusions

The functions of wearable devices tend to be homogeneous and usability is similar across various brands. Overall, Mi Band had the lowest price and the lightest weight. Misfit Shine had the longest battery life and most functions, and participants in the medical and health care industries had the best evaluation of wearable devices. The perceived usability of mainstream wearable devices is unsatisfactory and customer loyalty is not high. A consumer’s SUS rating for a wearable device is related to their personal situation instead of the device brand. Device manufacturers should put more effort into developing innovative functions and improving the usability of their products by integrating more cognitive behavior change techniques.

A statewide effort to reduce high-dose opioid prescribing through coordinated care organizations

BACKGROUND

Oregon's Medicaid program is delivered through 16 Coordinated Care Organizations (CCOs) participating in a statewide performance improvement program to reduce high-dose opioid prescribing. CCOs were allowed flexibility to develop their own dose targets and any policies, trainings, guidelines, and/or materials to meet these targets. In this study, we characterize CCO strategies to reduce high-dose opioid prescribing across the 16 CCOs.

METHODS

We reviewed relevant CCO documents and conducted semi-structured interviews with CCO administrators to acquire opioid-related policies, practices, timelines and contextual factors. We applied a systematic coding procedure to develop a comprehensive description of each CCO's strategy. We used administrative data from the state to summarize contextual utilization data for each CCO.

RESULTS

Most CCOs selected a target daily morphine milligram equivalent (MME) dose of 90 mg. Sixteen issued quantity limits related to dose, eight restricted specific drug formulations (short-acting or long-acting), and 11 allowed for time-limited taper plan periods for patients over threshold. Many CCOs also employed provider trainings, feedback reports, and/or onsite technical assistance. Other innovations included incentive measures, electronic health record alerts, and toolkits with materials on local alternative therapy resources and strategies for patient communication. CCOs leveraging collaborations with regional partners appeared to mount a greater intensity of interventions than independently operating CCOs.

CONCLUSIONS

CCOs developed a diversity of interventions to confront high-risk opioid prescribing within their organization. As healthcare systems mount interventions to reduce risky opioid prescribing, it is critical to carefully describe these activities and examine their impact on process and health outcomes.

Evidence-based usability design principles for medication alerting systems

Background

Usability flaws in medication alerting systems may have a negative impact on clinical use and patient safety. In order to prevent the release of alerting systems that contain such flaws, it is necessary to provide designers and evaluators with evidence-based usability design principles. The objective of the present study was to develop a comprehensive, structured list of evidence-based usability design principles for medication alerting systems.

Methods

Nine sets of design principles for medication alerting systems were analyzed, summarized, and structured. We then matched the summarized principles with a list of usability flaws in order to determine the level of underlying evidence.

Results

Fifty-eight principles were summarized from the literature and two additional principles were defined, so that each flaw was matched with a principle. We organized the 60 summarized usability design principles into 6 meta-principles, 38 principles, and 16 sub-principles. Only 15 principles were not matched with a usability flaw. The 6 meta-principles respectively covered the improvement of the signal-to-noise ratio, the support for collaborative working, the fit with a clinician’s workflow, the data display, the transparency of the alerting system, and the actionable tools to be provided within an alert.

Conclusions

It is possible to develop an evidence-based, structured, comprehensive list of usability design principles that are specific to medication alerting systems and are illustrated by the corresponding usability flaws. This list represents an improvement over the current literature. Each principle is now associated with the best available evidence of its violation. This knowledge may help to improve the usability of medication alerting systems and, ultimately, decrease the harmful consequences of the systems’ usability flaws.

Electronic supplementary material

The online version of this article (10.1186/s12911-018-0615-9) contains supplementary material, which is available to authorized users.

Comprehensive process model of clinical information interaction in primary care: results of a "best-fit" framework synthesis

Objective

To describe a new, comprehensive process model of clinical information interaction in primary care (Clinical Information Interaction Model, or CIIM) based on a systematic synthesis of published research.

Materials and Methods

We used the "best fit" framework synthesis approach. Searches were performed in PubMed, Embase, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycINFO, Library and Information Science Abstracts, Library, Information Science and Technology Abstracts, and Engineering Village. Two authors reviewed articles according to inclusion and exclusion criteria. Data abstraction and content analysis of 443 published papers were used to create a model in which every element was supported by empirical research.

Results

The CIIM documents how primary care clinicians interact with information as they make point-of-care clinical decisions. The model highlights 3 major process components: (1) context, (2) activity (usual and contingent), and (3) influence. Usual activities include information processing, source-user interaction, information evaluation, selection of information, information use, clinical reasoning, and clinical decisions. Clinician characteristics, patient behaviors, and other professionals influence the process.

Discussion

The CIIM depicts the complete process of information interaction, enabling a grasp of relationships previously difficult to discern. The CIIM suggests potentially helpful functionality for clinical decision support systems (CDSSs) to support primary care, including a greater focus on information processing and use. The CIIM also documents the role of influence in clinical information interaction; influencers may affect the success of CDSS implementations.

Conclusion

The CIIM offers a new framework for achieving CDSS workflow integration and new directions for CDSS design that can support the work of diverse primary care clinicians.

Traumatic Brain Injury and Receipt of Prescription Opioid Therapy for Chronic Pain in Iraq and Afghanistan Veterans: Do Clinical Practice Guidelines Matter?

Clinical practice guidelines admonish against prescribing opioids for individuals with chronic pain and traumatic brain injury (TBI) because of increased risk for adverse outcomes, yet no studies have described opioid prescribing patterns in these higher-risk patients. Between October 2007 and March 2015, 53,124 Iraq and Afghanistan veterans with chronic pain not prescribed opioids in the previous year were followed for 1 year after completing a Comprehensive TBI Evaluation within the Department of Veterans Affairs health care facilities. Veterans reporting the most severe TBI sequelae (eg, loss of consciousness >30 minutes) were significantly more likely to receive short-term and long-term opioid therapy than those with less severe or no TBI sequelae (P values < .001). In analyses adjusted for sociodemographic characteristics, military service, pain disability, and previous nonopioid treatment modalities, veterans with moderate to severe TBI had a significantly increased risk of receiving opioid therapy. Veterans with moderate to severe TBI and comorbid post-traumatic stress disorder and depression had an even greater risk of initiating long-term opioid therapy in the year after the Comprehensive TBI Evaluation (adjusted relative risk = 3.57 [95% confidence interval = 2.85-4.47]). Higher-risk patients with chronic pain and TBI with mental health comorbidities may benefit from improved access to behavioral health and nonpharmacological therapies for chronic pain.

PERSPECTIVE

Paradoxically, veterans with greater TBI severity and comorbid mental health burden are more likely to be prescribed opioids for chronic pain. More vulnerable veterans may benefit from improved access to behavioral health and nonpharmacological modalities for chronic pain, because of the health and safety risks of opioids.

Changes in User Perceptions of a Telemedicine System Over Time: From Initial Implementation to Everyday Use

BACKGROUND

Benefits associated with telemedicine are contingent upon positive user perceptions. Despite this, research on user perceptions of telemedicine remains limited.

INTRODUCTION

Usability approaches offer a robust way to assess user perceptions, but have rarely been applied in telemedicine. In this study, a usability approach was employed to examine how user perceptions toward a telemedicine system changed over the course of everyday use.

MATERIALS AND METHODS

A telemedicine system was introduced to a hospital in the home service. Ten mobile nurses completed the System Usability Scale (SUS) after initial use, then again after 18 months of everyday use. Results were compared. Analysis included Bangor et al.'s (2009) adjective rating scale.

RESULTS

The initial SUS mean was 83 (standard deviation [SD] = 7.98), indicating "excellent" usability. After 18 months, the SUS mean was 64.38, indicating "OK" usability (SD = 14.25, p < 0.05, 95% confidence interval [CI]). Over time, users had lower desire to use the system frequently (p < 0.05, 95% CI), found it more complex (p < 0.05, 95% CI), and perceived greater inconsistency in its design (p < 0.05, 95% CI).

DISCUSSION

Considered with existing evidence, our usability findings indicate that a temporary period of positive user perceptions occurs when new telemedicine systems are used for the first few months. This fades with everyday use, with design inconsistency and perceived complexity becoming more noticeable. Although other factors such as user satisfaction and efficiency may also contribute, further studies are needed for confirmation.

CONCLUSIONS

User perceptions of telemedicine vary with time. To help maximize the benefits and longevity of telemedicine systems, responding to intermittent user appraisal is desirable.

The impact of practice guidelines on opioid utilization for injured workers

BACKGROUND

Opioid use is rising in the US and may cause special problems in workers compensation cases, including addiction and preventing a return to work after an injury.

OBJECTIVE

This study evaluates a physician-level intervention to curb opioid usage. An insurer identified patients with out-of-guideline opioid utilization and called the prescribing physician to discuss the patient's treatment protocol.

RESEARCH DESIGN

This study uses a differences-in-differences study design with a propensity-score-matched control group. Medical and pharmaceutical claims data from 2005 to 2011 were used for analyses.

RESULTS

Following the intervention, the use of opioids increased for the intervention group and there is little impact on medical spending.

CONCLUSIONS

Counseling physicians about patients with high opioid utilization may focus more attention on their care, but did not impact short-term outcomes. More robust interventions may be needed to manage opioid use.

PERSPECTIVE

While the increasing use of opioids is of growing concern around the world, curbing the utilization of these powerfully addictive narcotics has proved elusive. This study examines a prescribing guidelines intervention designed to reduce the prescription of opioids following an injury. The study finds that there was little change in the opioid utilization after the intervention, suggesting interventions along other parts of the prescribing pathway may be needed.

Utilizing patient data from the veterans administration electronic health record to support web-based clinical decision support: informatics challenges and issues from three clinical domains

BACKGROUND

The US Veterans Administration (VA) has developed a robust and mature computational infrastructure in support of its electronic health record (EHR). Web technology offers a powerful set of tools for structuring clinical decision support (CDS) around clinical care. This paper describes informatics challenges and design issues that were confronted in the process of building three Web-based CDS systems in the context of the VA EHR.

METHODS

Over the course of several years, we implemented three Web-based CDS systems that extract patient data from the VA EHR environment to provide patient-specific CDS. These were 1) the VACS (Veterans Aging Cohort Study) Index Calculator which estimates prognosis for HIV+ patients, 2) Neuropath/CDS which assists in the medical management of patients with neuropathic pain, and 3) TRIM (Tool to Reduce Inappropriate Medications) which identifies potentially inappropriate medications in older adults and provides recommendations for improving the medication regimen.

RESULTS

The paper provides an overview of the VA EHR environment and discusses specific informatics issues/challenges that arose in the context of each of the three Web-based CDS systems. We discuss specific informatics methods and provide details of approaches that may be useful within this setting.

CONCLUSIONS

Informatics issues and challenges relating to data access and data availability arose because of the particular architecture of the national VA infrastructure and the need to link to that infrastructure from local Web-based CDS systems. Idiosyncrasies of VA patient data, especially the medication data, also posed challenges. Other issues related to specific functional needs of individual CDS systems. The goal of this paper is to describe these issues so that our experience may serve as a useful foundation to assist others who wish to build such systems in the future.

Using m-health tools to reduce the misuse of opioid pain relievers

BACKGROUND

Emergency department (ED) patients are among the many groups at risk for prescription drug overdose. There is limited research on how best to communicate with ED patients about options for pain management and the risks of opioids. The aim of this study is to pilot test a web-based, patient-centred educational programme that encourages the patient to have an informed discussion about pain medication options with their ED provider.

METHODS

This multisite, randomised trial will evaluate an m-health programme designed to aid the patient in making an informed decision about their pain treatment. Patients reporting to the ED with an injury-related or pain- related chief complaint who agree to participate are randomised to receive the intervention programme, My Healthy Choices, or an attention-matched control. My Healthy Choices pairs tailored education with a patient decision aid to describe what opioid and non-opioid pain medications are, assess the patient's risk factors for opioid-related adverse effects, and produce a tailored report that patients are encouraged to share with their doctor. Data are collected through surveys at three time points during the ED encounter (baseline, immediately after the intervention and just before discharge), and at a 6-week follow-up survey. The primary outcomes are whether the patient prefers an opioid pain reliever (OPR) and whether the patient takes an OPR.

DISCUSSION

We hope this programme will facilitate patient-provider communication, as well as reduce the number of prescriptions written for OPRs and thus the number of patients exposed to prescription opioids and the associated risks of addiction and overdose.

TRIAL REGISTRATION NUMBER

NCT03012087; Pre-results.

Moving From Discovery to System-Wide Change: The Role of Research in a Learning Health Care System: Experience from Three Decades of Health Systems Research in the Veterans Health Administration

The Veterans Health Administration is unique, functioning as an integrated health care system that provides care to more than six million veterans annually and as a home to an established scientific enterprise that conducts more than $1 billion of research each year. The presence of research, spanning the continuum from basic health services to translational research, has helped the Department of Veterans Affairs (VA) realize the potential of a learning health care system and has contributed to significant improvements in clinical quality over the past two decades. It has also illustrated distinct pathways by which research influences clinical care and policy and has provided lessons on challenges in translating research into practice on a national scale. These lessons are increasingly relevant to other health care systems, as the issues confronting the VA—the need to provide timely access, coordination of care, and consistent high quality across a diverse system—mirror those of the larger US health care system.

National Action Plan for Adverse Drug Event Prevention: Recommendations for Safer Outpatient Opioid Use

INTRODUCTION

Adverse drug events (ADEs) have been highlighted as a major patient safety and public health challenge by the National Action Plan for Adverse Drug Event Prevention (ADE Action Plan), which was released by the Office of Disease Prevention and Health Promotion (ODPHP) in August 2014. The ADE Action Plan focuses on surveillance, evidence-based prevention, incentives, and oversights, additional research needs as well as possible measures and metrics to track progress of ADE prevention within three drug classes: anticoagulants, diabetes agents, and opioids.Objectives and Recommendations. With outpatient opioid prescriptions being a great concern among many healthcare providers, this article focuses on recommendations from the ADE Action Plan to help guide safer opioid use in healthcare delivery settings. Its aim is to discuss current federal methods in place to prevent opioid ADEs while also providing evidence to encourage providers and hospitals to innovate new systems and practices to increase prevention.

Clinical Decision Support Tools for Selecting Interventions for Patients with Disabling Musculoskeletal Disorders: A Scoping Review

Purpose We aimed to identify and inventory clinical decision support (CDS) tools for helping front-line staff select interventions for patients with musculoskeletal (MSK) disorders. Methods We used Arksey and O'Malley's scoping review framework which progresses through five stages: (1) identifying the research question; (2) identifying relevant studies; (3) selecting studies for analysis; (4) charting the data; and (5) collating, summarizing and reporting results. We considered computer-based, and other available tools, such as algorithms, care pathways, rules and models. Since this research crosses multiple disciplines, we searched health care, computing science and business databases. Results Our search resulted in 4605 manuscripts. Titles and abstracts were screened for relevance. The reliability of the screening process was high with an average percentage of agreement of 92.3 %. Of the located articles, 123 were considered relevant. Within this literature, there were 43 CDS tools located. These were classified into 3 main areas: computer-based tools/questionnaires (n = 8, 19 %), treatment algorithms/models (n = 14, 33 %), and clinical prediction rules/classification systems (n = 21, 49 %). Each of these areas and the associated evidence are described. The state of evidentiary support for CDS tools is still preliminary and lacks external validation, head-to-head comparisons, or evidence of generalizability across different populations and settings. Conclusions CDS tools, especially those employing rapidly advancing computer technologies, are under development and of potential interest to health care providers, case management organizations and funders of care. Based on the results of this scoping review, we conclude that these tools, models and systems should be subjected to further validation before they can be recommended for large-scale implementation for managing patients with MSK disorders.

Prescription reporting with immediate medication utilization mapping (PRIMUM): development of an alert to improve narcotic prescribing

BACKGROUND

Prescription narcotic overdoses and abuse have reached alarming numbers. To address this epidemic, integrated clinical decision support within the electronic medical record (EMR) to impact prescribing behavior was developed and tested.

METHODS

A multidisciplinary Expert Panel identified risk factors for misuse, abuse, or diversion of opioids or benzodiazepines through literature reviews and consensus building for inclusion in a rule within the EMR. We ran the rule "silently" to test the rule and collect baseline data.

RESULTS

Five criteria were programmed to trigger the alert; based on data collected during a "silent" phase, thresholds for triggers were modified. The alert would have fired in 21.75 % of prescribing encounters (1.30 % of all encounters; n = 9998), suggesting the alert will have a low prescriber burden yet capture a significant number of at-risk patients.

CONCLUSIONS

While the use of the EMR to provide clinical decision support is not new, utilizing it to develop and test an intervention is novel. We successfully built an alert system to address narcotic prescribing by providing critical, objective information at the point of care. The silent phase data were useful to appropriately tune the alert and obtain support for widespread implementation. Future healthcare initiatives can utilize similar methodology to collect data prospectively via the electronic medical record to inform the development, delivery, and evaluation of interventions.

Advancing the Pain Agenda in the Veteran Population

The Veterans Health Administration (VHA) provides medical care for Veterans after leaving the military. The combination of multiple deployments and battlefield exposures to physical and psychological trauma results in a higher prevalence and complexity of chronic pain in Veterans than in the general public. The VHA and the Department of Defense work together to develop a single standard of stepped pain management appropriate for all settings from moment of injury or disease onset. This article describes the education, academic detailing, and clinical programs and policies that are transforming pain care in the VHA.

A systematic review of mixed methods research on human factors and ergonomics in health care

This systematic literature review provides information on the use of mixed methods research in human factors and ergonomics (HFE) research in health care. Using the PRISMA methodology, we searched four databases (PubMed, PsycInfo, Web of Science, and Engineering Village) for studies that met the following inclusion criteria: (1) field study in health care, (2) mixing of qualitative and quantitative data, (3) HFE issues, and (4) empirical evidence. Using an iterative and collaborative process supported by a structured data collection form, the six authors identified a total of 58 studies that primarily address HFE issues in health information technology (e.g., usability) and in the work of healthcare workers. About two-thirds of the mixed methods studies used the convergent parallel study design where quantitative and qualitative data were collected simultaneously. A variety of methods were used for collecting data, including interview, survey and observation. The most frequent combination involved interview for qualitative data and survey for quantitative data. The use of mixed methods in healthcare HFE research has increased over time. However, increasing attention should be paid to the formal literature on mixed methods research to enhance the depth and breadth of this research.

[Identifying Usability Level and Factors Affecting Electronic Nursing Record Systems: A Multi-institutional Time-motion Approach]

PURPOSE

The usability, user satisfaction, and impact of electronic nursing record (ENR) systems were investigated.

METHODS

This mixed-method research was performed as a time-motion (TM) study and a survey which were carried out at six hospitals between August and November 2013. The TM study involved 108 nurses from medical, surgical, and intensive care units at each hospital, plus an additional 48 nurses who served as nonparticipating observers. In the survey, 1879 volunteer nurses completed the Impact of ENR Systems Scale, the System Usability Scale, and a global satisfaction scale. Qualitative and quantitative analyses were performed.

RESULTS

The mean scores for the ENR impact, system usability, and satisfaction were 4.28 (out of 6), 58.62 (out of 100), and 74.31 (out of 100), respectively, and they differed significantly between hospitals (F=43.43, p<.001, F=53.08 and p<.001, and F=29.13 and p<.001, respectively). A workflow fragmentation assessment revealed different patterns of ENR system use among the included hospitals. Three user characteristics-educational background, practice period, and experience of using paper records-significantly affected the system usability and satisfaction scores.

CONCLUSION

The system quality varied widely among the ENR systems. The generally low-to-moderate levels of system usability and user satisfaction suggest many opportunities for improvement.

Baseline Variation in Use of VA/DOD Clinical Practice Guideline Recommended Opioid Prescribing Practices Across VA Health Care Systems

OBJECTIVES

The purpose of this study was to determine baseline adherence to key recommendations from the 2010 VA/DOD Clinical Practice Guideline for Opioid Therapy for Chronic Pain at Veterans Health Administration (VA) facilities. We hoped to understand practice patterns at the time of guideline release to guide quality improvement and implementation efforts.

METHODS

Overall practice patterns were examined at each of the 140 VA Health Care Systems based on quality metrics developed to assess adherence to the VA/DOD Clinical Practice Guideline.

RESULTS

Clinical practice varied widely across facilities on measures of use of urine drug screens, substance use disorder treatment for diagnosed substance use disorder patients, and use of rehabilitative treatments. Less variation was observed in measures of sedative coprescription and use of adjunctive pharmacotherapy. Use of guideline recommended practices was generally more frequent for patients prescribed long-acting opioid formulations and those with chronic use. Relative facility-level implementation was correlated across most measures. Overall implementation of guideline recommended practices was lower at less complex facilities and facilities in the Western United States.

DISCUSSION

In 2010, guideline-recommended practices for opioid prescribing were variably used across VA health care systems. Efforts to disseminate practices used at high-performing sites, and increase consistency of use of recommended practices across patients and facilities should be considered to improve pain management and reduce adverse events.

Usability Flaws in Medication Alerting Systems: Impact on Usage and Work System

OBJECTIVES

Previous research has shown that medication alerting systems face usability issues. There has been no previous attempt to systematically explore the consequences of usability flaws in such systems on users (i.e. usage problems) and work systems (i.e. negative outcomes). This paper aims at exploring and synthesizing the consequences of usability flaws in terms of usage problems and negative outcomes on the work system.

METHODS

A secondary analysis of 26 papers included in a prior systematic review of the usability flaws in medication alerting was performed. Usage problems and negative outcomes were extracted and sorted. Links between usability flaws, usage problems, and negative outcomes were also analyzed.

RESULTS

Poor usability generates a large variety of consequences. It impacts the user from a cognitive, behavioral, emotional, and attitudinal perspective. Ultimately, usability flaws have negative consequences on the workflow, the effectiveness of the technology, the medication management process, and, more importantly, patient safety. Only few complete pathways leading from usability flaws to negative outcomes were identified.

CONCLUSION

Usability flaws in medication alerting systems impede users, and ultimately their work system, and negatively impact patient safety. Therefore, the usability dimension may act as a hidden explanatory variable that could explain, at least partly, the (absence of) intended outcomes of new technology.

Decision support for chronic pain care: how do primary care physicians decide when to prescribe opioids? a qualitative study

BACKGROUND

Primary care physicians struggle to treat chronic noncancer pain while limiting opioid misuse, abuse, and diversion. The objective of this study was to understand how primary care physicians perceive their decisions to prescribe opioids in the context of chronic noncancer pain management. This question is important because interventions, such as decision support tools, must be designed based on a detailed understanding of how clinicians use information to make care decisions.

METHODS

We conducted in-depth qualitative interviews with family medicine and general internal medicine physicians until reaching saturation in emergent themes. We used a funneling approach to ask a series of questions about physicians' general decision making challenges and use of information when considering chronic opioids. We then used an iterative, open-coding approach to identify and characterize themes in the data.

RESULTS

We interviewed fifteen physicians with diverse clinical experiences, demographics, and practice affiliations. Physicians said that general decision making challenges in providing pain management included weighing risks and benefits of opioid therapies and time and resource constraints. Also, some physicians described their active avoidance of chronic pain treatment due to concerns about opioid risks. In their decision making, physicians described the importance of objective and consistent information, the importance of identifying "red flags" related to risks of opioids, the importance of information about physical function as an outcome, and the importance of information that engenders trust in patients.

CONCLUSIONS

This study identified and described primary care physicians' struggles to deliver high quality care as they seek and make decisions based on an array of incomplete, conflicting, and often untrusted patient information. Decision support systems, education, and other interventions that address these challenges may alleviate primary care physicians' struggles and improve outcomes for patients with chronic pain and other challenging conditions.

Unintentional home injuries across the life span: problems and solutions

Home injuries cause more than 30,000 deaths and 12 million nonfatal injuries annually in the United States. They generate an estimated $222 billion in lifetime costs annually. Despite some data limitations in documenting home as the location of an injury, much progress has been made in identifying effective prevention strategies that reduce injury or mitigate risk behaviors. The current interest in public health in the role of housing in health offers unparalleled opportunities for injury prevention professionals concerned with home injuries. Sharing the science of injury prevention with the wide array of professionals-such as architects, home builders, home visitors, and fire and emergency medical services providers-who create home environments and interact with residents could be a useful approach. A collaborative national effort to reduce the burden of home injuries is needed.

Exploring a clinically friendly web-based approach to clinical decision support linked to the electronic health record: design philosophy, prototype implementation, and framework for assessment

BACKGROUND

Computer-based clinical decision support (CDS) is an important component of the electronic health record (EHR). As an increasing amount of CDS is implemented, it will be important that this be accomplished in a fashion that assists in clinical decision making without imposing unacceptable demands and burdens upon the provider's practice.

OBJECTIVE

The objective of our study was to explore an approach that allows CDS to be clinician-friendly from a variety of perspectives, to build a prototype implementation that illustrates features of the approach, and to gain experience with a pilot framework for assessment.

METHODS

The paper first discusses the project's design philosophy and goals. It then describes a prototype implementation (Neuropath/CDS) that explores the approach in the domain of neuropathic pain and in the context of the US Veterans Administration EHR. Finally, the paper discusses a framework for assessing the approach, illustrated by a pilot assessment of Neuropath/CDS.

RESULTS

The paper describes the operation and technical design of Neuropath/CDS, as well as the results of the pilot assessment, which emphasize the four areas of focus, scope, content, and presentation.

CONCLUSIONS

The work to date has allowed us to explore various design and implementation issues relating to the approach illustrated in Neuropath/CDS, as well as the development and pilot application of a framework for assessment.

The ecology of prescription opioid abuse in the USA: geographic variation in patients' use of multiple prescribers ("doctor shopping")

PURPOSE

This study estimates the prevalence in US counties of opioid patients who use large numbers of prescribers, the amounts of opioids they obtain, and the extent to which their prevalence is predicted by ecological attributes of counties, including general medical exposure to opioids.

METHODS

Finite mixture models were used to estimate the size of an outlier subpopulation of patients with suspiciously large numbers of prescribers (probable doctor shoppers), using a sample of 146 million opioid prescriptions dispensed during 2008. Ordinary least squares regression models of county-level shopper rates included independent variables measuring ecological attributes of counties, including rates of patients prescribed opioids, socioeconomic characteristics of the resident population, supply of physicians, and measures of healthcare service utilization.

RESULTS

The prevalence of shoppers varied widely by county, with rates ranging between 0.6 and 2.5 per 1000 residents. Shopper prevalence was strongly correlated with opioid prescribing for the general population, accounting for 30% of observed county variation in shopper prevalence, after adjusting for physician supply, emergency department visits, in-patient hospital days, poverty rates, percent of county residents living in urban areas, and racial/ethnic composition of resident populations. Approximately 30% of shoppers obtained prescriptions in multiple states.

CONCLUSIONS

The correlation between prevalence of doctor shoppers and opioid patients in a county could indicate either that easy access to legitimate medical treatment raises the risk of abuse or that drug abusers take advantage of greater opportunities in places where access is easy. Approaches to preventing excessive use of different prescribers are discussed.