Integrating data from an online diabetes prevention program into an electronic health record and clinical workflow, a design phase usability study

Tools to guide clinical discussions on physical activity, sedentary behaviour, and/or sleep for health promotion between primary care providers and adults accessing care: a scoping review

BACKGROUND

Health care providers have reported low knowledge, skill, and confidence for discussing movement behaviours (i.e., physical activity, sedentary behaviour, and sleep), which may be improved with the use of tools to guide movement behaviour discussions in their practice. Past reviews have examined the psychometric properties, scoring, and behavioural outcomes of physical activity discussion tools. However, the features, perceptions, and effectiveness of discussion tools for physical activity, sedentary behaviour, and/or sleep have not yet been synthesized. The aim of this review was to report and appraise tools for movement behaviour discussions between health care providers and adults 18 + years in a primary care context within Canada or analogous countries.

METHODS

An integrated knowledge translation approach guided this review, whereby a working group of experts in medicine, knowledge translation, communications, kinesiology, and health promotion was engaged from research question formation to interpretation of findings. Three search approaches were used (i.e., peer-reviewed, grey literature, and forward searches) to identify studies reporting on perceptions and/or effectiveness of tools for physical activity, sedentary behaviour, and/or sleep. The quality of included studies was assessed using the Mixed Methods Appraisal Tool.

RESULTS

In total, 135 studies reporting on 61 tools (i.e., 51 on physical activity, one on sleep, and nine combining two movement behaviours) met inclusion criteria. Included tools served the purposes of assessment (n = 57), counselling (n = 50), prescription (n = 18), and/or referral (n = 12) of one or more movement behaviour. Most tools were used or intended for use by physicians, followed by nurses/nurse practitioners (n = 11), and adults accessing care (n = 10). Most tools were also used or intended to be used with adults without chronic conditions aged 18-64 years (n = 34), followed by adults with chronic conditions (n = 18). The quality of the 116 studies that evaluated tool effectiveness varied.

CONCLUSIONS

Many tools were positively perceived and were deemed effective at enhancing knowledge of, confidence for, ability in, and frequency of movement behaviour discussions. Future tools should guide discussions of all movement behaviours in an integrated manner in line with the 24-Hour Movement Guidelines. Practically, this review offers seven evidence-based recommendations that may guide future tool development and implementation.

Recommendations for the Quality Management of Patient-Generated Health Data in Remote Patient Monitoring: Mixed Methods Study

BACKGROUND

Patient-generated health data (PGHD) collected from innovative wearables are enabling health care to shift to outside clinical settings through remote patient monitoring (RPM) initiatives. However, PGHD are collected continuously under the patient's responsibility in rapidly changing circumstances during the patient's daily life. This poses risks to the quality of PGHD and, in turn, reduces their trustworthiness and fitness for use in clinical practice.

OBJECTIVE

Using a sociotechnical health informatics lens, we developed a data quality management (DQM) guideline for PGHD captured from wearable devices used in RPM with the objective of investigating how DQM principles can be applied to ensure that PGHD can reliably inform clinical decision-making in RPM.

METHODS

First, clinicians, health information specialists, and MedTech industry representatives with experience in RPM were interviewed to identify DQM challenges. Second, these stakeholder groups were joined by patient representatives in a workshop to co-design potential solutions to meet the expectations of all the stakeholders. Third, the findings, along with the literature and policy review results, were interpreted to construct a guideline. Finally, we validated the guideline through a Delphi survey of international health informatics and health information management experts.

RESULTS

The guideline constructed in this study comprised 19 recommendations across 7 aspects of DQM. It explicitly addressed the needs of patients and clinicians but implied that there must be collaboration among all stakeholders to meet these needs.

CONCLUSIONS

The increasing proliferation of PGHD from wearables in RPM requires a systematic approach to DQM so that these data can be reliably used in clinical care. The developed guideline is an important next step toward safe RPM.

Implementing Exercise = Medicine in routine clinical care; needs for an online tool and key decisions for implementation of Exercise = Medicine within two Dutch academic hospitals

Background

There is much evidence to implement physical activity interventions for medical reasons in healthcare settings. However, the prescription of physical activity as a treatment, referring to as ‘Exercise is Medicine’ (E = M) is currently mostly absent in routine hospital care in The Netherlands. To support E = M prescription by clinicians in hospitals, this study aimed: (1) to develop an E = M-tool for physical activity advice and referrals to facilitate the E = M prescription in hospital settings; and (2) to provide an E = M decision guide on key decisions for implementation to prepare for E = M prescription in hospital care.

Methods

A mixed method design was used employing a questionnaire and face-to-face interviews with clinicians, lifestyle coaches and hospital managers, a patient panel and stakeholders to assess the needs regarding an E = M-tool and key decisions for implementation of E = M. Based on the needs assessment, a digital E = M-tool was developed. The key decisions informed the development of an E = M decision guide.

Results

An online supportive tool for E = M was developed for two academic hospitals. Based on the needs assessment, linked to the different patients’ electronic medical records and tailored to the two local settings (University Medical Center Groningen, Amsterdam University Medical Centers). The E = M-tool existed of a tool algorithm, including patient characteristics assessed with a digital questionnaire (age, gender, PA, BMI, medical diagnosis, motivation to change physical activity and preference to discuss physical activity with their doctor) set against norm values. The digital E = M-tool provided an individual E = M-prescription for patients and referral options to local PA interventions in- and outside the hospital. An E = M decision guide was developed to support the implementation of E = M prescription in hospital care.

Conclusions

This study provided insight into E = M-tool development and the E = M decision-making to support E = M prescription and facilitate tailoring towards local E = M treatment options, using strong stakeholder participation. Outcomes may serve as an example for other decision support guides and interventions aimed at E = M implementation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12911-022-01993-5.

Understanding Patients' Intention to Use Digital Health Apps That Support Postdischarge Symptom Monitoring by Providers Among Patients With Acute Coronary Syndrome: Survey Study

Background

After hospital discharge, patients with acute coronary syndrome (ACS) often experience symptoms that prompt them to seek acute medical attention. Early evaluation of postdischarge symptoms by health care providers may reduce unnecessary acute care utilization. However, hospital-initiated follow-up encounters are insufficient for timely detection and assessment of symptoms. While digital health tools can help address this issue, little is known about the intention to use such tools in ACS patients.

Objective

This study aimed to assess ACS patients’ intention to use digital health apps that support postdischarge symptom monitoring by health care providers and identify patient-perceived facilitators and barriers to app use.

Methods

Using email invitations or phone calls, we recruited ACS patients discharged from a central Massachusetts health care system between December 2020 and April 2021, to participate in the study. Surveys were delivered online or via phone to individual participants. Demographics and access to technology were assessed. The intention to use a symptom monitoring app was assessed using 5-point Likert-type (from strongly agree to strongly disagree) items, such as “If this app were available to me, I would use it.” Responses were compared across demographic subgroups and survey delivery methods. Two open-ended questions assessed perceived facilitators and barriers to app use, with responses analyzed using qualitative content analysis.

Results

Among 100 respondents (response rate 8.1%), 45 (45%) completed the survey by phone. The respondents were on average 68 years old (SD 13 years), with 90% (90/100) White, 39% (39/100) women, and 88% (88/100) having access to the internet or a mobile phone. Most participants (65/100, 65%) agreed or strongly agreed that they would use the app, among which 53 (82%) would use the app as often as possible. The percentage of participants with the intention to use the app was 75% among those aged 65-74 years and dropped to 44% among those older than 75 years. The intention to use was higher in online survey respondents (vs phone survey respondents; odds ratio 3.07, 95% CI 1.20-7.88) after adjusting for age and access to technology. The analysis of open-ended questions identified the following 4 main facilitators (motivations): (1) easily reaching providers, (2) accessing or providing information, (3) quickly reaching providers, and (4) consulting providers for symptoms, and the following 4 main barriers: (1) privacy/security concerns, (2) uncomfortable using technology, (3) user-unfriendly app interface, and (4) preference for in-person/phone care.

Conclusions

There was a strong intention to use a symptom monitoring app postdischarge among ACS patients. However, this intent decreased in patients older than 75 years. The survey identified barriers related to technology use, privacy/security, and the care delivery mode. Further research is warranted to determine if such intent translates into app use, and better symptom management and health care quality.

Effectiveness of an Integrated Engagement Support System to Facilitate Patient Use of Digital Diabetes Prevention Programs: Protocol for a Randomized Controlled Trial

Background

Digital diabetes prevention programs (dDPPs) are effective behavior change tools to prevent disease progression in patients at risk for diabetes. At present, these programs are poorly integrated into existing health information technology infrastructure and clinical workflows, resulting in barriers to provider-level knowledge of, interaction with, and support of patients who use dDPPs. Tools that can facilitate patient-provider interaction around dDPPs may contribute to improved patient engagement and adherence to these programs and improved health outcomes.

Objective

This study aims to use a rigorous, user-centered design (UCD) methodology to develop a theory-driven system that supports patient engagement with dDPPs and their primary care providers with their care.

Methods

This study will be conducted in 3 phases. In phase 1, we will use systematic UCD, Agile software development, and qualitative research methods to identify key user (patients, providers, clinical staff, digital health technologists, and content experts) requirements, constraints, and prioritization of high-impact features to design, develop, and refine a viable intervention prototype for the engagement system. In phase 2, we will conduct a single-arm feasibility pilot of the engagement system among patients with prediabetes and their primary care providers. In phase 3, we will conduct a 2-arm randomized controlled trial using the engagement system. Primary outcomes will be weight, BMI, and A_1c at 6 and 12 months. Secondary outcomes will be patient engagement (use and activity) in the dDPP. The mediator variables (self-efficacy, digital health literacy, and patient-provider relationship) will be measured.

Results

The project was initiated in 2018 and funded in September 2019. Enrollment and data collection for phase 1 began in September 2019 under an Institutional Review Board quality improvement waiver granted in July 2019. As of December 2020, 27 patients have been enrolled and first results are expected to be submitted for publication in early 2021. The study received Institutional Review Board approval for phases 2 and 3 in December 2020, and phase 2 enrollment is expected to begin in early 2021.

Conclusions

Our findings will provide guidance for the design and development of technology to integrate dDPP platforms into existing clinical workflows. This will facilitate patient engagement in digital behavior change interventions and provider engagement in patients’ use of dDPPs. Integrated clinical tools that can facilitate patient-provider interaction around dDPPs may contribute to improved patient adherence to these programs and improved health outcomes by addressing barriers faced by both patients and providers. Further evaluation with pilot testing and a clinical trial will assess the effectiveness and implementation of these tools.

Trial Registration

ClinicalTrials.gov NCT04049500; https://clinicaltrials.gov/ct2/show/NCT04049500

International Registered Report Identifier (IRRID)

DERR1-10.2196/26750

Who Are the Undiagnosed? Disparities in Hypertension Diagnoses in Vulnerable Populations

This study builds upon a project that developed clinical criteria to identify undiagnosed hypertension patients "hiding in plain sight" (HIPS) by examining patient characteristics to understand whether there are disparities in hypertension diagnosis. We examined electronic health record demographic data for patients identified by the HIPS criteria and subgroups at 3 Missouri health centers. Identified patients who returned for a follow-up visit and were subsequently diagnosed with hypertension tended to be older, black/African American, uninsured, and classified as having obesity. Younger, white, healthy weight females were less likely to be diagnosed. These findings point to exploring possible biases/other nonclinical factors in hypertension diagnosis.

Automated analysis of free-text comments and dashboard representations in patient experience surveys: a multimethod co-design study

Background

Patient experience surveys (PESs) often include informative free-text comments, but with no way of systematically, efficiently and usefully analysing and reporting these. The National Cancer Patient Experience Survey (CPES), used to model the approach reported here, generates > 70,000 free-text comments annually.

Main aim

To improve the use and usefulness of PES free-text comments in driving health service changes that improve the patient experience.

Secondary aims

(1) To structure CPES free-text comments using rule-based information retrieval (IR) (‘text engineering’), drawing on health-care domain-specific gazetteers of terms, with in-built transferability to other surveys and conditions; (2) to display the results usefully for health-care professionals, in a digital toolkit dashboard display that drills down to the original free text; (3) to explore the usefulness of interdisciplinary mixed stakeholder co-design and consensus-forming approaches in technology development, ensuring that outputs have meaning for all; and (4) to explore the usefulness of Normalisation Process Theory (NPT) in structuring outputs for implementation and sustainability.

Design

A scoping review, rapid review and surveys with stakeholders in health care (patients, carers, health-care providers, commissioners, policy-makers and charities) explored clinical dashboard design/patient experience themes. The findings informed the rules for the draft rule-based IR [developed using half of the 2013 Wales CPES (WCPES) data set] and prototype toolkit dashboards summarising PES data. These were refined following mixed stakeholder, concept-mapping workshops and interviews, which were structured to enable consensus-forming ‘co-design’ work. IR validation used the second half of the WCPES, with comparison against its manual analysis; transferability was tested using further health-care data sets. A discrete choice experiment (DCE) explored which toolkit features were preferred by health-care professionals, with a simple cost–benefit analysis. Structured walk-throughs with NHS managers in Wessex, London and Leeds explored usability and general implementation into practice.

Key outcomes

A taxonomy of ranked PES themes, a checklist of key features recommended for digital clinical toolkits, rule-based IR validation and transferability scores, usability, and goal-oriented, cost–benefit and marketability results. The secondary outputs were a survey, scoping and rapid review findings, and concordance and discordance between stakeholders and methods.

Results

(1) The surveys, rapid review and workshops showed that stakeholders differed in their understandings of the patient experience and priorities for change, but that they reached consensus on a shortlist of 19 themes; six were considered to be core; (2) the scoping review and one survey explored the clinical toolkit design, emphasising that such toolkits should be quick and easy to use, and embedded in workflows; the workshop discussions, the DCE and the walk-throughs confirmed this and foregrounded other features to form the toolkit design checklist; and (3) the rule-based IR, developed using noun and verb phrases and lookup gazetteers, was 86% accurate on the WCPES, but needs modification to improve this and to be accurate with other data sets. The DCE and the walk-through suggest that the toolkit would be well accepted, with a favourable cost–benefit ratio, if implemented into practice with appropriate infrastructure support.

Limitations

Small participant numbers and sampling bias across component studies. The scoping review studies mostly used top-down approaches and focused on professional dashboards. The rapid review of themes had limited scope, with no second reviewer. The IR needs further refinement, especially for transferability. New governance restrictions further limit immediate use.

Conclusions

Using a multidisciplinary, mixed stakeholder, use of co-design, proof of concept was shown for an automated display of patient experience free-text comments in a way that could drive health-care improvements in real time. The approach is easily modified for transferable application.

Future work

Further exploration is needed of implementation into practice, transferable uses and technology development co-design approaches.

Funding

The National Institute for Health Research Health Services and Delivery Research programme.

Designing for implementation: user-centered development and pilot testing of a behavioral economic-inspired electronic health record clinical decision support module

Background

Current guidelines recommend less aggressive target hemoglobin A1c (HbA1c) levels based on older age and lower life expectancy for older adults with diabetes. The effectiveness of electronic health record (EHR) clinical decision support (CDS) in promoting guideline adherence is undermined by alert fatigue and poor workflow integration. Integrating behavioral economics (BE) and CDS tools is a novel approach to improving adherence to guidelines while minimizing clinician burden.

Methods

We will apply a systematic, user-centered design approach to incorporate BE “nudges” into a CDS module and will perform user testing in two “vanguard” sites. To accomplish this, we will conduct (1) semi-structured interviews with key informants (n = 8), (2) a 2-h, design-thinking workshop to derive and refine initial module ideas, and (3) semi-structured group interviews at each site with clinic leaders and clinicians to elicit feedback on three proposed nudge module components (navigator section, inbasket refill protocol, medication preference list). Detailed field notes will be summarized by module idea and usability theme for rapid iteration. Frequency of firing and user action taken will be assessed in the first month of implementation via EHR reporting to confirm that module components and related reporting are working as expected as well as assess utilization. To assess the utilization and feasibility of the new tools and generate estimates of clinician compliance with the Choosing Wisely guideline for diabetes management in older adults, a 6-month, single-arm pilot study of the BE-EHR module will be conducted in six outpatient primary care clinics.

Discussion

We hypothesize that a low burden, user-centered approach to design will yield a BE-driven, CDS module with relatively high utilization by clinicians. The resulting module will establish a platform for exploring the ability of BE concepts embedded within the EHR to affect guideline adherence for other use cases.

Electronic supplementary material

The online version of this article (10.1186/s40814-019-0403-z) contains supplementary material, which is available to authorized users.

Usability Challenges for Health and Wellness Mobile Apps: Mixed-Methods Study Among mHealth Experts and Consumers

BACKGROUND

By 2019, there will be an estimated 4.68 billion mobile phone users globally. This increase comes with an unprecedented proliferation in mobile apps, a plug-and-play product positioned to improve lives in innumerable ways. Within this landscape, medical apps will see a 41% compounded annual growth rate between 2015 and 2020, but paradoxically, prevailing evidence indicates declining downloads of such apps and decreasing "stickiness" with the intended end users.

OBJECTIVE

As usability is a prerequisite for success of health and wellness mobile apps, this paper aims to provide insights and suggestions for improving usability experience of the mobile health (mHealth) app by exploring the degree of alignment between mHealth insiders and consumers.

METHODS

Usability-related major themes were selected from over 20 mHealth app development studies. The list of themes, grouped into 5 categories using the Nielsen usability model, was then used as a framework to identify and classify the responses from mHealth expert (insider) interviews. Responses from the qualitative phase were integrated into some questions for a quantitative consumer survey. Subsequently, categorical data from qualitative mHealth insider interviews and numerical data from a quantitative consumer survey were compared in order to identify common usability themes and areas of divergence.

RESULTS

Of the 5 usability attributes described in Nielsen model,  Satisfaction ranked as the top attribute for both mHealth insiders and consumers. Satisfaction refers to user likability, comfort, and pleasure. The consumer survey yielded 451 responses. Out of 9 mHealth insiders' top concerns, 5 were similar to those of the consumers. On the other hand, consumers did not grade themes such as Intuitiveness as important, which was deemed vital by mHealth insiders. Other concerns of the consumers include in-app charges and advertisements.

CONCLUSIONS

This study supports and contributes to the existing pool of mixed-research studies. Strengthening the connectivity between suppliers and users (through the designed research tool) will help increase uptake of mHealth apps. In a holistic manner, this will have a positive overall outcome for the mHealth app ecosystem.

Factors for Supporting Primary Care Physician Engagement With Patient Apps for Type 2 Diabetes Self-Management That Link to Primary Care: Interview Study

BACKGROUND

The health burden of type 2 diabetes can be mitigated by engaging patients in two key aspects of diabetes care: self-management and regular contact with health professionals. There is a clear benefit to integrating these aspects of care into a single clinical tool, and as mobile phone ownership increases, apps become a more feasible platform. However, the effectiveness of online health interventions is contingent on uptake by health care providers, which is typically low. There has been little research that focuses specifically on barriers and facilitators to health care provider uptake for interventions that link self-management apps to the user's primary care physician (PCP).

OBJECTIVE

This study aimed to explore PCP perspectives on proposed features for a self-management app for patients with diabetes that would link to primary care services.

METHODS

Researchers conducted 25 semistructured interviews. The interviewer discussed potential features that would link in with the patient's primary care services. Interviews were audio-recorded, transcribed, and coded. Framework analysis and the Consolidated Criteria for Reporting Qualitative Research checklist were employed to ensure rigor.

RESULTS

Our analysis indicated that PCP attitudes toward proposed features for an app were underpinned by perceived roles of (1) diabetes self-management, (2) face-to-face care, and (3) the anticipated burden of new technologies on their practice. Theme 1 explored PCP perceptions about how an app could foster patient independence for self-management behaviors but could also increase responsibility and liability for the PCP. Theme 2 identified beliefs underpinning a commonly expressed preference for face-to-face care. PCPs perceived information was more motivating, better understood, and presented with greater empathy when delivered face to face rather than online. Theme 3 described how most PCPs anticipated an initial increase in workload while they learned to use a new clinical tool. Some PCPs accepted this burden on the basis that the change was inevitable as health care became more integrated. Others reported potential benefits were outweighed by effort to implement an app. This study also identified how app features can be positively framed, highlighting potential benefits for PCPs to maximize PCP engagement, buy-in, and uptake. For example, PCPs were more positive when they perceived that an app could facilitate communication and motivation between consultations, focus on building capacity for patient independence, and reinforce rather than replace in-person care. They were also more positive about app features that were automated, integrated with existing software, flexible for different patients, and included secondary benefits such as improved documentation.

CONCLUSIONS

This study provided insight into PCP perspectives on a diabetes app integrated with primary care services. This was observed as more than a technological change; PCPs were concerned about changes in workload, their role in self-management, and the nature of consultations. Our research highlighted potential facilitators and barriers to engaging PCPs in the implementation process.

Five key strategic priorities of integrating patient generated health data into United Kingdom electronic health records

The integration of patient/person generated health data into clinical applications is a key strategic priority internationally. However, despite agreement on the overall direction of travel, there are still a range of challenges that inhibit progress in this area. These include technology-related factors (such as interoperability), use-related factors (such as data overload) and characteristics of the strategic environment (such as existing standards). Building on important policy deliberations from the United States that aim to navigate these challenges, we here apply emerging policy frameworks to the United Kingdom and outline five key priority areas that are intended to help policy makers make important strategic decisions in attempting to integrate patient/person generated data into electronic health records.

Innovating From Within: A Process Model for User-Centered Digital Development in Academic Medical Centers

Background

Design thinking and human-centered design approaches have become increasingly common in health care literature, particularly in relation to health information technology (HIT), as a pathway toward the development of usable, diffusible tools and processes. There is a need in academic medical centers tasked with digital innovation for a comprehensive process model to guide development that incorporates current industry trends, including design thinking and lean and agile approaches to digital development.

Objective

This study aims to describe the foundations and phases of our model for user-centered HIT development.

Methods

Based on our experience, we established an integrated approach and rigorous process for HIT development that leverages design thinking and lean and agile strategies in a pragmatic way while preserving methodological integrity in support of academic research goals.

Results

A four-phased pragmatic process model was developed for user-centered digital development in HIT.

Conclusions

The model for user-centered HIT development that we developed is the culmination of diverse innovation projects and represents a multiphased, high-fidelity process for making more creative, flexible, efficient, and effective tools. This model is a critical step in building a rigorous approach to HIT design that incorporates a multidisciplinary, pragmatic perspective combined with academic research practices and state-of-the-art approaches to digital product development to meet the unique needs of health care.

The Use of Health Information Exchange to Augment Patient Handoff in Long-Term Care: A Systematic Review

BACKGROUND

Legislation aimed at increasing the use of a health information exchange (HIE) in healthcare has excluded long-term care facilities, resulting in a vulnerable patient population that can benefit from the improvement of communication and reduction of waste.

OBJECTIVE

The purpose of this review is to provide a framework for future research by identifying themes in the long-term care information technology sector that could function to enable the adoption and use of HIE mechanisms for patient handoff between long-term care facilities and other levels of care to increase communication between providers, shorten length of stay, reduce 60-day readmissions, and increase patient safety.

METHODS

The authors conducted a systematic search of literature through CINAHL, PubMed, and Discovery Services for Texas A&M University Libraries. Search terms used were ("health information exchange" OR "healthcare information exchange" OR "HIE") AND ("long term care" OR "long-term care" OR "nursing home" OR "nursing facility" OR "skilled nursing facility" OR "SNF" OR "residential care" OR "assisted living"). Articles were eligible for selection if they were published between 2010 and 2017, published in English, and published in academic journals. All articles were reviewed by all reviewers and literature not relevant to the research objective was excluded.

RESULTS

Researchers selected and reviewed 22 articles for common themes. Results concluded that the largest facilitator and barrier to the adoption of HIE mechanisms is workflow integration/augmentation and the organizational structure/culture, respectively. Other identified facilitator themes were enhanced communication, increased effectiveness of care, and patient safety. The additional barriers were missing/incomplete data, inefficiency, and market conditions.

CONCLUSION

The long-term care industry has been left out of incentives from which the industry could have benefited tremendously. Organizations that are not utilizing health information technology mechanisms, such as electronic health records and HIEs, are at a disadvantage as insurers switch to capitated forms of payment that rely on reduced waste to generate a profit.

Improving Identification and Diagnosis of Hypertensive Patients Hiding in Plain Sight (HIPS) in Health Centers

BACKGROUND

Hypertension is the most prevalent chronic condition diagnosed among patients served in the safety net in the United States; however, many safety-net patients with hypertension are not formally diagnosed and may remain untreated and at increased risk for cardiovascular events. Identifying undiagnosed hypertension using algorithmic logic programmed into clinical decision support (CDS) approaches is a promising practice but has not been broadly tested in the safety-net setting.

METHODS

The project used a quality improvement approach wherein information flows and actions related to blood pressure measurement were modified to include algorithm criteria to identify patients who might have undiagnosed hypertension. Identified patients were recalled for evaluation and hypertension diagnosis, if appropriate. Ten health centers in Arkansas, California, Kentucky, and Missouri were selected to participate in the project on the basis of high hypertension prevalence (compared to national average), demographic and geographic diversity, mature information systems infrastructure, and executive support. The project targeted patients from 18 to 85 years of age.

RESULTS

After implementation of algorithm-based interventions, diagnosed hypertension prevalence increased significantly from 34.5% to 36.7% (p <0.05). A cohort of patients was tracked from 8 of the 10 health centers to assess follow-up evaluation and diagnosis rates; 65.2% completed a follow-up evaluation, of which 31.9% received a hypertension diagnosis.

CONCLUSION

Using algorithmic logic and other CDS-enabled care process improvements appears to be an effective way health centers can identify and engage patients at risk for undiagnosed hypertension. Appropriately diagnosing all hypertensive patients ensures that hypertension control efforts yield maximal improvements in population health.

Patients' perspectives on social and goal-based comparisons regarding their diabetes health status

OBJECTIVE

Social comparisons (ie, self-evaluation in comparison with others) influence patients' perspectives of their disease and may impact motivation and health behavior; however, little is known about patients' perspectives toward receiving such information in a clinical context (eg, from their doctor's office or health system). This study aims to understand patients' perspectives and anticipated responses to receiving social comparison information regarding measures of their diabetes-related health status (eg, A1C) and how receiving such information would compare with goal-based comparisons (ie, self-evaluation in comparison with goal).

RESEARCH DESIGN AND METHODS

We conducted semistructured interviews with 25 patients with type 2 diabetes mellitus (T2DM) regarding social and goal-based comparisons involving their diabetes health status and qualitatively analyzed interviews for themes.

RESULTS

We identified seven major themes: self-relevance, motivation, self-concept, emotions, information seeking, medical care, and self-care. Participants commonly anticipated increased motivation and improved health behaviors in response to both social and goal-based comparisons. Subthemes unique to social comparisons included belief that this information would be motivating by engaging some patients' competitiveness, perception that this information was more 'personalized' than comparisons with a standard goal (eg, A1C<7), and desire to learn from individuals similar to oneself who were doing better.

CONCLUSIONS

Our findings provide significant insights into the anticipated response of patients with T2DM to receiving social and goal-based comparison information regarding their diabetes health status. Providing patients with diabetes with social and goal-based comparison information may affect motivation, mood, and self-concept in ways that may improve or sustain diabetes self-care behaviors for some patients.

Impact of an Electronic Health Record-Integrated Personal Health Record on Patient Participation in Health Care: Development and Randomized Controlled Trial of MyHealthKeeper

Background

Personal health record (PHR)–based health care management systems can improve patient engagement and data-driven medical diagnosis in a clinical setting.

Objective

The purpose of this study was (1) to demonstrate the development of an electronic health record (EHR)–tethered PHR app named MyHealthKeeper, which can retrieve data from a wearable device and deliver these data to a hospital EHR system, and (2) to study the effectiveness of a PHR data-driven clinical intervention with clinical trial results.

Methods

To improve the conventional EHR-tethered PHR, we ascertained clinicians’ unmet needs regarding PHR functionality and the data frequently used in the field through a cocreation workshop. We incorporated the requirements into the system design and architecture of the MyHealthKeeper PHR module. We constructed the app and validated the effectiveness of the PHR module by conducting a 4-week clinical trial. We used a commercially available activity tracker (Misfit) to collect individual physical activity data, and developed the MyHealthKeeper mobile phone app to record participants’ patterns of daily food intake and activity logs. We randomly assigned 80 participants to either the PHR-based intervention group (n=51) or the control group (n=29). All of the study participants completed a paper-based survey, a laboratory test, a physical examination, and an opinion interview. During the 4-week study period, we collected health-related mobile data, and study participants visited the outpatient clinic twice and received PHR-based clinical diagnosis and recommendations.

Results

A total of 68 participants (44 in the intervention group and 24 in the control group) completed the study. The PHR intervention group showed significantly higher weight loss than the control group (mean 1.4 kg, 95% CI 0.9-1.9; P<.001) at the final week (week 4). In addition, triglyceride levels were significantly lower by the end of the study period (mean 2.59 mmol/L, 95% CI 17.6-75.8; P=.002).

Conclusions

We developed an innovative EHR-tethered PHR system that allowed clinicians and patients to share lifelog data. This study shows the effectiveness of a patient-managed and clinician-guided health tracker system and its potential to improve patient clinical profiles.

Trial Registration

ClinicalTrials.gov NCT03200119; https://clinicaltrials.gov/ct2/show/NCT03200119 (Archived by WebCite at http://www.webcitation.org/6v01HaCdd)

Iterative User Interface Design for Automated Sequential Organ Failure Assessment Score Calculator in Sepsis Detection

Background

The new sepsis definition has increased the need for frequent sequential organ failure assessment (SOFA) score recalculation and the clerical burden of information retrieval makes this score ideal for automated calculation.

Objective

The aim of this study was to (1) estimate the clerical workload of manual SOFA score calculation through a time-motion analysis and (2) describe a user-centered design process for an electronic medical record (EMR) integrated, automated SOFA score calculator with subsequent usability evaluation study.

Methods

First, we performed a time-motion analysis by recording time-to-task-completion for the manual calculation of 35 baseline and 35 current SOFA scores by 14 internal medicine residents over a 2-month period. Next, we used an agile development process to create a user interface for a previously developed automated SOFA score calculator. The final user interface usability was evaluated by clinician end users with the Computer Systems Usability Questionnaire.

Results

The overall mean (standard deviation, SD) time-to-complete manual SOFA score calculation time was 61.6 s (33). Among the 24% (12/50) usability survey respondents, our user-centered user interface design process resulted in >75% favorability of survey items in the domains of system usability, information quality, and interface quality.

Conclusions

Early stakeholder engagement in our agile design process resulted in a user interface for an automated SOFA score calculator that reduced clinician workload and met clinicians’ needs at the point of care. Emerging interoperable platforms may facilitate dissemination of similarly useful clinical score calculators and decision support algorithms as “apps.” A user-centered design process and usability evaluation should be considered during creation of these tools.