MyPreventiveCare: implementation and dissemination of an interactive preventive health record in three practice-based research networks serving disadvantaged patients--a randomized cluster trial

Personalized Disease Prevention (PDP): study protocol for a cluster-randomized clinical trial

BACKGROUND

The US Preventive Services Task Force recommends 25 primary preventive services for middle-aged adults, but it can be difficult to do them all.

METHODS

The Personalized Disease Prevention (PDP) cluster-randomized clinical trial will evaluate whether patients and their providers benefit from an evidence-based decision tool to prioritize preventive services based on their potential to improve quality-adjusted life expectancy. The decision tool will be individualized for patient risk factors and available in the electronic health record. This Phase III trial seeks to enroll 60 primary care providers (clusters) and 600 patients aged 40-75 years. Half of providers will be assigned to an intervention to utilize the decision tool with approximately 10 patients each, and half will be assigned to usual care. Mixed-methods follow-up will include collection of preventive care utilization from electronic health records, patient and physician surveys, and qualitative interviews. We hypothesize that quality-adjusted life expectancy will increase by more in patients who receive the intervention, as compared with controls.

DISCUSSION

PDP will test a novel, holistic approach to help patients and providers prioritize the delivery of preventive services, based on patient risk factors in the electronic health record.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05463887. Registered on July 19, 2022.

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

Background

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

Objective

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

Methods

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

Results

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

Conclusions

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

Scaling Up Public Health Interventions: Engaging Partners Across Multiple Levels

Advancing the science of intervention scale-up is essential to increasing the impact of effective interventions at the regional and national levels. In contrast with work in high-income countries (HICs), where scale-up research has been limited, researchers in low- and middle-income countries (LMICs) have conducted numerous studies on the regional and national scale-up of interventions. In this article, we review the state of the science on intervention scale-up in both HICs and LMICs. We provide an introduction to the elements of scale-up followed by a description of the scale-up process, with an illustrative case study from our own research. We then present findings from a scoping review comparing scale-up studies in LMIC and HIC settings. We conclude with lessons learned and recommendations for improving scale-up research. Expected final online publication date for the Annual Review of Public Health, Volume 43 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Effect of Individualized Preventive Care Recommendations vs Usual Care on Patient Interest and Use of Recommendations: A Pilot Randomized Clinical Trial

Importance

This randomized clinical trial examines the feasibility and acceptability of a decision-making tool for increasing patient interest in individualized recommendations for preventive care services.

Objective

To pilot a tool to help patients compare life expectancy gains from evidence-based preventive services.

Design, Setting, and Participants

This randomized clinical trial examined patient and physician responses to a pilot decision tool incorporating personalized risk factors at 3 US primary care clinics between 2017 and 2020. Eligible patients were between ages 45 to 70 years with 2 or more high-risk factors. Patients were followed-up after 1 year.

Interventions

The gain in life expectancy associated with guideline adherence to each recommended preventive service was estimated. Personalized estimates incorporating risk factors in electronic health records were displayed in a physician-distributed visual aid. During development, physicians discussed individualized results with patients using shared decision-making (SDM). During the trial, patients were randomized to receive individualized recommendations or usual care (nonmasked, parallel, 1:1 ratio).

Main Outcomes and Measures

Primary outcome was patient interest in individualized recommendations, assessed by survey. Secondary outcomes were use of SDM, decisional comfort, readiness to change, and preventive services received within 1 year.

Results

The study enrolled 104 patients (31 development, 39 intervention, 34 control), of whom 101 were included in analysis (mean [SD] age, 56.5 [5.3] years; 73 [72.3%] women; 80 [79.2%] Black patients) and 20 physicians. Intervention patients found the tool helpful and wanted to use it again, rating it a median 9 of 10 (IQR, 8-10) and 10 of 10 (8-10), respectively. Compared with the control group, intervention patients more often correctly identified the service least likely (18 [46%] vs 0; P = .03) to improve their life expectancy. A greater number of patients also identified the service most likely to improve their life expectancy (26 [69%] vs 10 [30%]; P = .07), although this result was not statistically significant. Intervention patients reported greater mean [SD] improvement in SDM (4.7 [6.9] points) and near-term readiness to change (13.8 points for top-3-ranked recommendations). Point estimates indicated that patients in the intervention group experienced greater, although non-statistically significant, reductions in percentage of body weight (-2.96%; 95% CI, -8.18% to 2.28%), systolic blood pressure (-6.42 mm Hg; 95% CI, -16.12 to 3.27 mm Hg), hemoglobin A1c (-0.68%; 95% CI, -1.82% to 0.45%), 10-year atherosclerotic cardiovascular disease risk score (-1.20%; 95% CI, -3.65% to 1.26%), and low-density lipoprotein cholesterol (-8.46 mg/dL; 95% CI, -26.63 to 9.70 mg/dL) than the control group. Nineteen of 20 physicians wanted to continue using the decision tool in the future.

Conclusions and Relevance

In this clinical trial, an individualized preventive care decision support tool improved patient understanding of primary prevention and demonstrated promise for improved shared decision-making and preventive care utilization.

Trial Registration

ClinicalTrials.gov Identifier: NCT03023813.

Uptake of Statin Guidelines to Prevent and Treat Cardiovascular Disease

INTRODUCTION

In December 2013, cholesterol treatment guidelines changed the approach to statin therapy by recommending fixed doses of low-, medium-, or high-intensity statins based on cardiovascular risk. We sought to evaluate the guideline's adoption in a diverse group of practices.

METHODS

Using a mixed-methods approach, we analyzed electronic health record data the year before and 2 years following guideline publication in 45 practices across 8 states. We examined associations based on patient, clinician, and practice characteristics and interviewed 24 clinicians and practice leaders to inform findings.

RESULTS

The proportion of patients adherent with all recommendations 2 years after the guideline only increased from 18.5% to 20.3% (P < .01). There were clinically insignificant increases in statin use across risk strata (1.7% to 3.5%) and small increases in high-intensity statin use (2.6% to 4.6%). Only half of patients with cardiovascular disease (52.9%) were on any statin, not much different from patients at moderate (49.6% to 50.9%) or low (41.6% to 48.7%) risk. Multiple patient (risk, use of health care), clinician (age), and practice (type, rurality) factors were associated with statin use. Clinicians reported patient resistance to statins but liked having a risk calculator to guide discussions.

CONCLUSION

Despite general agreement with statin benefit, the guideline was poorly implemented. Marginal differences in statin use between the highest and lower risk strata of patients is concerning. Rather than intensifying statin potency and recommending more patients take statins, guidelines may want to focus on ensuring that those who will benefit most get treatment.

Patient, Clinician, and Communication Factors Associated with Colorectal Cancer Screening

INTRODUCTION

Screening for colorectal cancer is beneficial. Yet, screening remains suboptimal, and underserved populations are at greater risk for not being appropriately screened. Although many barriers to screening are understood, less is known about how the decision-making process on whether to receive colonoscopy or stool testing influences screening.

METHODS

As part of a randomized controlled trial to test engaging underserved populations in preventive care through online, personalized, educational material, 2417 patients aged 50 to 74 years were randomly selected from the 70,998 patients with an office visit the year prior and mailed a survey to assess decision-making for colorectal cancer screening. Twenty practices in practice-based research networks from 5 diverse states participated. Survey data were supplemented with electronic health record data.

RESULTS

Among respondents, 64% were or became up to date with screening within 3 months of their office visit. The main factor associated with being up to date was the length of the patient-clinician relationship (<6 months vs 5+ years: odds ratio [OR], 0.49; 95% CI, 0.30-0.80). Sharing the decision about screening options with the clinician was a predictor for being up to date compared with patients who made the decision for themselves (OR, 1.75; 95% CI, 1.27-2.44). Only 36% of patients reported being given a choice about screening options. Traditional factors like race, employment, insurance, and education were not associated with screening.

CONCLUSIONS

Having a long-term relationship with a primary care clinician and sharing decisions may be key drivers to ensure evidence-based preventive care for underserved populations.

Assessment of Physician Priorities in Delivery of Preventive Care

IMPORTANCE

Primary care physicians have limited time to discuss preventive care, but it is unknown how they prioritize recommended services.

OBJECTIVE

To understand primary care physicians' prioritization of preventive services.

DESIGN, SETTING, AND PARTICIPANTS

This online survey was administered to primary care physicians in a large health care system from March 17 to May 12, 2017. Physicians were asked whether they prioritize preventive services and which factors contribute to their choice (5-point Likert scale). Results were analyzed from July 8, 2017, to September 19, 2019.

EXPOSURES

A 2 × 2 factorial design of 2 hypothetical patients: (1) a 50-year-old white woman with hypertension, type 2 diabetes, hyperlipidemia, obesity, a 30-pack-year history of smoking, and a family history of breast cancer; and (2) a 45-year-old black man with hypertension, hyperlipidemia, obesity, a 30-pack-year history of smoking, and a family history of colorectal cancer. Two visit lengths (40 minutes vs 20 minutes) were given. Each patient was eligible for at least 11 preventive services.

MAIN OUTCOMES AND MEASURES

Physicians rated their likelihood of discussing each service during the visit and reported their top 3 priorities for patients 1 and 2. Physician choices were compared with the preventive services most likely to improve life expectancy, using a previously published mathematical model.

RESULTS

Of 241 physicians, 137 responded (57%), of whom 74 (54%) were female and 85 (62%) were younger than 50 years. Physicians agreed they prioritized preventive services (mean score, 4.27 [95% CI, 4.12-4.42] of 5.00), mostly by ability to improve quality (4.56 [95% CI, 4.44-4.68] of 5.00) or length (4.53 [95% CI, 4.40-4.66] of 5.00) of life. Physicians reported more prioritization in the 20- vs 40-minute visit, indicating that they were likely to discuss fewer services during the shorter visit (median, 5 [interquartile range {IQR}, 3-8] vs 11 [IQR, 9-13] preventive services for patient 1, and 4 [IQR, 3-6] vs 9 [IQR, 8-11] for patient 2). Physicians reported similar top 3 priorities for both patients: smoking cessation, hypertension control, and glycemic control for patient 1 and smoking cessation, hypertension control, and colorectal cancer screening for patient 2. Physicians' top 3 priorities did not usually include diet and exercise or weight loss (ranked in their top 3 recommendations for either patient by only 48 physicians [35%]), although these were among the 3 preventive services most likely to improve life expectancy based on the mathematical model.

CONCLUSIONS AND RELEVANCE

In this survey study, physicians prioritized preventive services under time constraints, but priorities did not vary across patients. Physicians did not prioritize lifestyle interventions despite large potential benefits. Future research should consider whether physicians and patients would benefit from guidance on preventive care priorities.

Practice, clinician, and patient factors associated with the adoption of lung cancer screening

OBJECTIVES

Lung cancer remains the leading cause of cancer-related deaths in the United States. In 2013, the US Preventive Services Task Force recommended annual screening for lung cancer with low-dose computed tomography in adults meeting certain criteria. This study seeks to assess lung cancer screening uptake in three health systems.

SETTING

This study was part of a randomized controlled trial to engage underserved populations in preventive care and includes 45 primary care practices in eight states.

METHODS

Practice and clinician characteristics were manually collected. Lung cancer was measured from electronic health record data. A generalized linear mixed model was used to assess characteristics associated with screening.

RESULTS

Patient records between 2012 and 2016 were examined. Lung cancer screening uptake overall increased only slightly after the guideline change (2.8-5.6%, p < 0.01). One health system did not show an increase in uptake (0.2-0.1%, p = 0.32), another had a clinically insignificant increase (1.5-2.9%, p < 0.01), and the third nearly doubled its higher baseline screening rate (10.4-19.1%, p < 0.01). Within the third health system, patients more likely to be screened were older, male, had more comorbid conditions, visited the office more frequently, were seen in practices closer to the screening clinic, or were uninsured or covered by Medicare or Medicaid.

CONCLUSIONS

Certain patients appeared more likely to be screened. The only health system with increased lung cancer screening explicitly promoted screening rather than relying on clinicians to implement the new guideline. Systems approaches may help increase the low uptake of lung cancer screening.

Adherence to Electronic Health Tools Among Vulnerable Groups: Systematic Literature Review and Meta-Analysis

Background

Electronic health (eHealth) tools are increasingly being applied in health care. They are expected to improve access to health care, quality of health care, and health outcomes. Although the advantages of using these tools in health care are well described, it is unknown to what extent eHealth tools are effective when used by vulnerable population groups, such as the elderly, people with low socioeconomic status, single parents, minorities, or immigrants.

Objective

This study aimed to examine whether the design and implementation characteristics of eHealth tools contribute to better use of these tools among vulnerable groups.

Methods

In this systematic review, we assessed the design and implementation characteristics of eHealth tools that are used by vulnerable groups. In the meta-analysis, we used the adherence rate as an effect size measure. The adherence rate is defined as the number of people who are repetitive users (ie, use the eHealth tool more than once). We also performed a meta-regression analysis to examine how different design and implementation characteristics influenced the adherence rate.

Results

Currently, eHealth tools are continuously used by vulnerable groups but to a small extent. eHealth tools that use multimodal content (such as videos) and have the possibility for direct communication with providers show improved adherence among vulnerable groups.

Conclusions

eHealth tools that use multimodal content and provide the possibility for direct communication with providers have a higher adherence among vulnerable groups. However, most of the eHealth tools are not embedded within the health care system. They are usually focused on specific problems, such as diabetes or obesity. Hence, they do not provide comprehensive services for patients. This limits the use of eHealth tools as a replacement for existing health care services.

Delivering clinical preventive services in the Islamic Republic of Iran: A model for screening and behavior consultation practices

Background: Screening and behavior consultation are considered to be limited, dispersed and expensive services across the country. To deliver efficient and equitable services current disordered practices need to be consolidated.

Methods: An analysis of current situation, learned lessons and future scopes of country’s preventive care delivery, along with a review of international experience and generous participation of various stakeholders, led to proposing a model for screening and behavior consultation practices in IR. Iran.

Results: Upon the results of the previous steps, the desired model was based on the network system and family physician. Comprehensive health centers and other centers affiliated to the network are the most appropriate service positions. However, private and academic preventive centers are playing their rules.

Conclusion: The proposed model matches the overall pattern of service delivery in the health system (network system with the private sector and the educational sector).

Leveraging Implementation Science to Address Health Disparities in Genomic Medicine: Examples from the Field

The integration of genomic data into screening, prevention, diagnosis, and treatment for clinical and public health practices has been slow and challenging. Implementation science can be applied in tackling the barriers and challenges as well as exploring opportunities and best practices for integrating genomic data into routine clinical and public health practice.In this article, we define the state of disparities in genomic medicine and focus predominantly on late-stage research findings. We use case studies from genetic testing for cardiovascular diseases (familial hypercholesterolemia) and cancer (Lynch syndrome and hereditary breast and ovarian cancer syndrome) in high-risk populations to consider current disparities and related barriers in turning genomic advances into population health impact to advance health equity. Finally, we address how implementation science can address these translational barriers and we discuss the strategic importance of collaborative multi-stakeholder approaches that engage public health agencies, professional societies, academic health and research centers, community clinics, and patients and their families to work collectively to improve population health and reduce or eliminate health inequities.

Randomised trial to evaluate the effectiveness and impact of offering postvisit decision support and assistance in obtaining physician-recommended colorectal cancer screening: the e-assist: Colon Health study-a protocol study

INTRODUCTION

How to provide practice-integrated decision support to patients remains a challenge. We are testing the effectiveness of a practice-integrated programme targeting patients with a physician recommendation for colorectal cancer (CRC) screening.

METHODS AND ANALYSIS

In partnership with healthcare teams, we developed 'e-assist: Colon Health', a patient-targeted, postvisit CRC screening decision support programme. The programme is housed within an electronic health record (EHR)-embedded patient portal. It leverages a physician screening recommendation as the cue to action and uses the portal to enrol and intervene with patients. Programme content complements patient-physician discussions by encouraging screening, addressing common questions and assisting with barrier removal. For evaluation, we are using a randomised trial in which patients are randomised to receive e-assist: Colon Health or one of two controls (usual care plus or usual care). Trial participants are average-risk, aged 50-75 years, due for CRC screening and received a physician order for stool testing or colonoscopy. Effectiveness will be evaluated by comparing screening use, as documented in the EHR, between trial enrollees in the e-assist: Colon Health and usual care plus (CRC screening information receipt) groups. Secondary outcomes include patient-perceived benefits of, barriers to and support for CRC screening and patient-reported CRC screening intent. The usual care group will be used to estimate screening use without intervention and programme impact at the population level. Differences in outcomes by study arm will be estimated with hierarchical logit models where patients are nested within physicians.

ETHICS AND DISSEMINATION

All trial aspects have been approved by the Institutional Review Board of the health system in which the trial is being conducted. We will disseminate findings in diverse scientific venues and will target clinical and quality improvement audiences via other venues. The intervention could serve as a model for filling the gap between physician recommendations and patient action.

TRIAL REGISTRATION NUMBER

NCT02798224; Pre-results.

Patients' adoption of and feature access within electronic patient portals

OBJECTIVES

We describe online portal account adoption and feature access among subgroups of patients who traditionally have been disadvantaged or represent those with high healthcare needs.

STUDY DESIGN

Retrospective cohort study of insured primary care patients 18 years and older (N = 20,282) receiving care from an integrated health system.

METHODS

Using data from an electronic health record repository, portal adoption was defined by 1 or more online sessions. Feature access (ie, messaging, appointment management, visit/admission summaries, and medical record access and management) was defined by user-initiated "clicks." Multivariable regression methods were used to identify patient factors associated with portal adoption and feature access among adopters.

RESULTS

One-third of patients were portal adopters, with African Americans (odds ratio [OR], 0.50; 95% CI, 0.46-0.56), Hispanics (OR, 0.63; 95% CI, 0.47-0.84), those 70 years and older (OR, 0.48; 95% CI, 0.44-0.52), and those preferring a language other than English (OR, 0.43; 95% CI, 0.31-0.59) less likely to be adopters. On the other hand, the likelihood of portal adoption increased with a higher number of comorbidities (OR, 1.04; 95% CI, 1.02-1.07). Among adopters, record access and management features (95.9%) were accessed most commonly. The majority of adopters also accessed appointment management (76.6%) and messaging (59.1%) features. Similar race and age disparities were found in feature access among adopters.

CONCLUSIONS

The diversity of portal features accessed may bode well for the ability of portals to engage some patients, but without purposeful intervention, reliance on portals alone for patient engagement may exacerbate known social disparities-even among those with an activated portal account.

Gaps in Well-Child Care Attendance Among Primary Care Clinics Serving Low-Income Families

BACKGROUND AND OBJECTIVES

It is unclear which specific well-child visits (WCVs) are most frequently missed and whether age-specific patterns of attendance differ by race or insurance type.

METHODS

We conducted a retrospective cohort study of children 0 to 6 years old between 2011 and 2016 within 2 health networks spanning 20 states. WCVs were identified by using International Classification of Diseases, Ninth and 10th Revisions and Current Procedural Terminology codes. We calculated adherence to the 13 American Academy of Pediatrics-recommended WCVs from birth to age 6 years. To address data completeness, we made 2 adherence calculations after a child's last recorded WCV: 1 in which we assumed all subsequent WCVs were attended outside the network and 1 in which we assumed none were.

RESULTS

We included 152 418 children in our analysis. Most children were either publicly insured (77%) or uninsured (14%). The 2-, 4-, and 6-month visits were the most frequently attended (63% [assuming no outside care after the last recorded WCV] to 90% [assuming outside care]), whereas the 15- and 18-months visits (41%-75%) and 4-year visit (19%-49%) were the least frequently attended. Patients who were publicly insured and uninsured (versus privately insured) had higher odds of missing WCVs. Hispanic and Asian American (versus non-Hispanic white) patients had higher odds of attending WCVs.

DISCUSSION

The 15- and 18-month WCVs as well as the 4-year WCV are the least frequently attended WCVs. The former represent opportunities to identify developmental delays, and the latter represents an opportunity to assess school readiness.

Shared decision-making using personal health record technology: a scoping review at the crossroads

Objective

This scoping review aims to determine the size and scope of the published literature on shared decision-making (SDM) using personal health record (PHR) technology and to map the literature in terms of system design and outcomes.

Materials and Methods

Literature from Medline, Google Scholar, Cumulative Index to Nursing and Allied Health Literature, Engineering Village, and Web of Science (2005-2015) using the search terms "personal health records," "shared decision making," "patient-provider communication," "decision aid," and "decision support" was included. Articles ( n  = 38) addressed the efficacy or effectiveness of PHRs for SDM in engaging patients in self-care and decision-making or ways patients can be supported in SDM via PHR.

Results

Analysis resulted in an integrated SDM-PHR conceptual framework. An increased interest in SDM via PHR is apparent, with 55% of articles published within last 3 years. Sixty percent of the literature originates from the United States. Twenty-six articles address a particular clinical condition, with 10 focused on diabetes, and one-third offer empirical evidence of patient outcomes. The tethered and standalone PHR architectural types were most studied, while the interconnected PHR type was the focus of more recently published methodological approaches and discussion articles.

Discussion

The study reveals a scarcity of rigorous research on SDM via PHR. Research has focused on one or a few of the SDM elements and not on the intended complete process.

Conclusion

Just as PHR technology designed on an interconnected architecture has the potential to facilitate SDM, integrating the SDM process into PHR technology has the potential to drive PHR value.

Evaluation of the first fracture liaison service in the Greek healthcare setting

We evaluated the first implementation of FLS in the Greek healthcare setting, at the 251 Hellenic Air Force and VA General Hospital of Athens. Participation rate was moderate (54.5%) and needs improvement; osteoporosis medication was either suggested or reviewed in 74 out of the 116 patients recruited.

PURPOSE

The purpose of this study was to evaluate the first implementation of a fracture liaison service (FLS) in Greece, at the 251 Hellenic Air Force and VA General Hospital, Athens.

METHODS

Single-center, prospective study from May 1, 2013 to April 30, 2015 (first year-second year follow-up) was conducted. Patients of both genders aged 40-90 years old, with a history of a low trauma fracture and willing to participate, were included after identification by an FLS nurse. Following recruitment, osteoporosis risk factors were assessed, FRAX score was calculated for treatment-naïve patients, bone mineral density (BMD) was measured by dual-energy x-ray absorptiometry (DXA), and osteoporosis treatment was suggested where applicable. The rate of participation, the indication of osteoporosis treatment, and the difficulties met were evaluated.

RESULTS

Of the eligible 213 patients, 97 (45.5%) were reluctant to participate for personal reasons. From the 116 initially recruited patients (mean age 74.8 ± 12 years), 77 (66.4%) discontinued their participation at some point for various reasons and 39 patients concluded the study. All 116 patients were assessed for osteoporosis risk factors and given a tailor-made exercise and education program, while FRAX score was assessed in all treatment-naïve patients (74 patients, 63.8%). Osteoporosis medication was suggested or reviewed in 74 patients; however, an adherence rate of 100% is only available for the 24 who concluded the study.

CONCLUSIONS

We report the first implementation of FLS in the Greek healthcare setting. The participation rate is moderate and definitely needs improvement.

Measuring Health Literacy Levels of a Patient Portal Using the CDC's Clear Communication Index

Once promised to revolutionize health care, patient portals have yet to fully achieve their potential of improving communication between patients and clinicians. In fact, their use can be detrimental to many consumers due to their limited literacy and numeracy skills. This study demonstrates how applying the Centers for Disease Control and Prevention's Clear Communication Index to a patient portal can be used to identify opportunities for better patient communication and engagement. The Clear Communication Index contains 20 scored items grounded in communication science to enhance patients' understanding of health information. The Index was applied to one portal used by over 80,000 patients in 12 primary care practices: MyPreventiveCare. This portal was selected because of its ability to personalize preventive and chronic care information by internally using content featuring health literacy principles and linking patients' externally to trusted materials. Thirty-seven frequently visited portal pages (17 internal and 20 external) were evaluated based on the Index's four main variables. The overall score for the portal was 72%, which falls below the 90% threshold to be considered clear communication. Internal content scored higher than external (75% vs. 69%). Specific changes to improve the score include simpler language, more specific examples, and clearer numerical explanations.

A new role for primary care teams in the United States after "Obamacare:" Track and improve health insurance coverage rates

Maintaining continuous health insurance coverage is important. With recent expansions in access to coverage in the United States after "Obamacare," primary care teams have a new role in helping to track and improve coverage rates and to provide outreach to patients. We describe efforts to longitudinally track health insurance rates using data from the electronic health record (EHR) of a primary care network and to use these data to support practice-based insurance outreach and assistance. Although we highlight a few examples from one network, we believe there is great potential for doing this type of work in a broad range of family medicine and community health clinics that provide continuity of care. By partnering with researchers through practice-based research networks and other similar collaboratives, primary care practices can greatly expand the use of EHR data and EHR-based tools targeting improvements in health insurance and quality health care.

The McMaster Optimal Aging Portal: Usability Evaluation of a Unique Evidence-Based Health Information Website

Background

Increasingly, older adults and their informal caregivers are using the Internet to search for health-related information. There is a proliferation of health information online, but the quality of this information varies, often based on exaggerated or dramatic findings, and not easily comprehended by consumers. The McMaster Optimal Aging Portal (Portal) was developed to provide Internet users with high-quality evidence about aging and address some of these current limitations of health information posted online. The Portal includes content for health professionals coming from three best-in-class resources (MacPLUS, Health Evidence, and Health Systems Evidence) and four types of content specifically prepared for the general public (Evidence Summaries, Web Resource Ratings, Blog Posts, and Twitter messages).

Objective

Our objectives were to share the findings of the usability evaluation of the Portal with particular focus on the content features for the general public and to inform designers of health information websites and online resources for older adults about key usability themes.

Methods

Data analysis included task performance during usability testing and qualitative content analyses of both the usability sessions and interviews to identify core themes.

Results

A total of 37 participants took part in 33 usability testing sessions and 21 focused interviews. Qualitative analysis revealed common themes regarding the Portal’s strengths and challenges to usability. The strengths of the website were related to credibility, applicability, browsing function, design, and accessibility. The usability challenges included reluctance to register, process of registering, searching, terminology, and technical features.

Conclusions

The study reinforced the importance of including end users during the development of this unique, dynamic, evidence-based health information website. The feedback was applied to iteratively improve website usability. Our findings can be applied by designers of health-related websites.