Electronic Health Record-Based Strategy to Promote Medication Adherence Among Patients With Diabetes: Longitudinal Observational Study

Delayed opportunities for patient-provider communication about medication overuse headache: Mixed methods perspectives from patients and neurologists

Objectives

Medication overuse headache (MOH) is a common, debilitating condition occurring when migraine patients overuse pain relief medications. We conducted a convergent mixed methods study examining patient-provider communication on MOH.

Methods

Migraine patients were identified from one academic health center via electronic health records. Research staff recruited patients and administered a remote survey on MOH awareness, knowledge, and communication; descriptive and bivariate analyses were conducted. Neurologists from the same health center were invited to participate in qualitative interviews; analysis drew from the Rapid Identification of Themes from Audio Recordings procedures. A side-by-side comparison of results followed.

Results

Participants included 200 patients and 13 neurologists. More than one third of patients (39.5 %) had never heard of 'medication overuse headache.' Among those who had, 38.4 % learned about MOH ≥ 5 years after their migraine diagnosis. Neurologists similarly reported limited patient awareness of MOH and suggested communication was provider-initiated, reactive to patient-reported symptoms and behaviors. Participants agreed MOH was described as a 'consequence' of frequent medication taking, though specific terminology varied with neurologists suggesting they choose terms they perceive to be easier to understand and less stigmatizing to patients. Neurologists felt they lacked effective patient education resources.

Conclusions

Findings reveal delayed opportunities to inform patients about MOH. Standardized education supporting early preventive communication is needed, perhaps in primary care where many patients seek initial care for migraine symptoms.

Current communication practices for biomarker testing in non-small cell lung cancer: Exploring patient and clinician perspectives

OBJECTIVES

We qualitatively explored patient and clinician experiences with biomarker testing in one academic health system to identify current communication practices and unmet testing information needs.

METHODS

We conducted 1:1 in-depth interviews with 15 clinicians (i.e., nurses, oncologists, pathologists) and 12 patients diagnosed with non-small cell lung cancer between January and May 2022. Participants described experiences with biomarker testing as well as associated communication practices and needs. Interviews were audio-recorded and transcribed. Analysis was informed by the Framework Method.

RESULTS

Patients described challenges retaining information early in their patient journey. While patients were generally aware of biomarkers and their effect on treatment options, they expressed limited knowledge of expected time delays between testing and receiving results. Additionally, many did not know their testing results. Clinicians and patients both noted no standard education material on biomarker testing is currently available. They suggested such materials could support patient knowledge and decision-making.

CONCLUSIONS

Communication between patients and clinicians about biomarker testing is largely delivered through verbal counseling at a time when patients may be cognitively compromised. All participants supported the idea of delivering standard, tangible education materials on biomarker testing to patients.

PRACTICE IMPLICATIONS

Education materials may enhance counseling efforts and patient knowledge.

Patient-Centered Digital Health Records and Their Effects on Health Outcomes: Systematic Review

BACKGROUND

eHealth tools such as patient portals and personal health records, also known as patient-centered digital health records, can engage and empower individuals with chronic health conditions. Patients who are highly engaged in their care have improved disease knowledge, self-management skills, and clinical outcomes.

OBJECTIVE

We aimed to systematically review the effects of patient-centered digital health records on clinical and patient-reported outcomes, health care utilization, and satisfaction among patients with chronic conditions and to assess the feasibility and acceptability of their use.

METHODS

We searched MEDLINE, Cochrane, CINAHL, Embase, and PsycINFO databases between January 2000 and December 2021. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed. Eligible studies were those evaluating digital health records intended for nonhospitalized adult or pediatric patients with a chronic condition. Patients with a high disease burden were a subgroup of interest. Primary outcomes included clinical and patient-reported health outcomes and health care utilization. Secondary outcomes included satisfaction, feasibility, and acceptability. Joanna Briggs Institute critical appraisal tools were used for quality assessment. Two reviewers screened titles, abstracts, and full texts. Associations between health record use and outcomes were categorized as beneficial, neutral or clinically nonrelevant, or undesired.

RESULTS

Of the 7716 unique publications examined, 81 (1%) met the eligibility criteria, with a total of 1,639,556 participants across all studies. The most commonly studied diseases included diabetes mellitus (37/81, 46%), cardiopulmonary conditions (21/81, 26%), and hematology-oncology conditions (14/81, 17%). One-third (24/81, 30%) of the studies were randomized controlled trials. Of the 81 studies that met the eligibility criteria, 16 (20%) were of high methodological quality. Reported outcomes varied across studies. The benefits of patient-centered digital health records were most frequently reported in the category health care utilization on the "use of recommended care services" (10/13, 77%), on the patient-reported outcomes "disease knowledge" (7/10, 70%), "patient engagement" (13/28, 56%), "treatment adherence" (10/18, 56%), and "self-management and self-efficacy" (10/19, 53%), and on the clinical outcome "laboratory parameters," including HbA_1c and low-density lipoprotein (LDL; 16/33, 48%). Beneficial effects on "health-related quality of life" were seen in only 27% (4/15) of studies. Patient satisfaction (28/30, 93%), feasibility (15/19, 97%), and acceptability (23/26, 88%) were positively evaluated. More beneficial effects were reported for digital health records that predominantly focus on active features. Beneficial effects were less frequently observed among patients with a high disease burden and among high-quality studies. No unfavorable effects were observed.

CONCLUSIONS

The use of patient-centered digital health records in nonhospitalized individuals with chronic health conditions is potentially associated with considerable beneficial effects on health care utilization, treatment adherence, and self-management or self-efficacy. However, for firm conclusions, more studies of high methodological quality are required.

TRIAL REGISTRATION

PROSPERO (International Prospective Register of Systematic Reviews) CRD42020213285; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=213285.

Development and Validation of a Useful Taxonomy of Patient Portals Based on Characteristics of Patient Engagement

Objective  Taxonomies are classification systems used to reduce complexity and better understand a domain. The present research aims to develop a useful taxonomy for health information managers to classify and compare patient portals based on characteristics appropriate to promote patient engagement. As a result, the taxonomy should contribute to understanding the differences and similarities of the portals. Further, the taxonomy shall support health information managers to more easily define which general type and functionalities of patient portals they need and to select the most suitable solution offered on the market.

Methods  We followed the formal taxonomy-building method proposed by Nickerson et al. Based on a literature review, we created a preliminary taxonomy following the conceptional approach of the model. We then evaluated each taxa's appropriateness by analyzing and classifying 17 patient portals offered by software vendors and 11 patient portals offered by health care providers. After each iteration, we examined the achievement of the determined objective and subjective ending conditions.

Results  After two conceptional approaches to create our taxonomy, and two empirical approaches to evaluate it, the final taxonomy consists of 20 dimensions and 49 characteristics. To make the taxonomy easy to comprehend, we assigned to the dimensions seven aspects related to patient engagement. These aspects are (1) portal design, (2) management, (3) communication, (4) instruction, (5) self-management, (6) self-determination, and (7) data management. The taxonomy is considered finished and useful after all ending conditions that defined beforehand have been fulfilled. We demonstrated that the taxonomy serves to understand the differences and similarities by comparing patient portals. We call our taxonomy “Taxonomy of Patient Portals based on Characteristics of Patient Engagement (TOPCOP).”

Conclusion  We developed the first useful taxonomy for health information managers to classify and compare patient portals. The taxonomy is based on characteristics promoting patient engagement. With 20 dimensions and 49 characteristics, our taxonomy is particularly suitable to discriminate among patient portals and can easily be applied to compare portals. The TOPCOP taxonomy enables health information managers to better understand the differences and similarities of patient portals. Further, the taxonomy may help them to define the type and general functionalities needed. But it also supports them in searching and comparing patient portals offered on the market to select the most suitable solution.

Patient Portal Barriers and Group Differences: Cross-Sectional National Survey Study

BACKGROUND

Past studies examining barriers to patient portal adoption have been conducted with a small number of patients and health care settings, limiting generalizability.

OBJECTIVE

This study had the following two objectives: (1) to assess the prevalence of barriers to patient portal adoption among nonadopters and (2) to examine the association between nonadopter characteristics and reported barriers in a nationally representative sample.

METHODS

Data from this study were obtained from the 2019 Health Information National Trends Survey. We calculated descriptive statistics to determine the most prevalent barriers and conducted multiple variable logistic regression analysis to examine which characteristics were associated with the reported barriers.

RESULTS

The sample included 4815 individuals. Among these, 2828 individuals (58.73%) had not adopted a patient portal. Among the nonadopters (n=2828), the most prevalent barriers were patient preference for in-person communication (1810/2828, 64.00%), no perceived need for the patient portal (1385/2828, 48.97%), and lack of comfort and experience with computers (735/2828, 25.99%). Less commonly, individuals reported having no patient portal (650/2828, 22.98%), no internet access (650/2828, 22.98%), privacy concerns (594/2828, 21.00%), difficulty logging on (537/2828, 18.99%), and multiple patient portals (255/2828, 9.02%) as barriers. Men had significantly lower odds of indicating a preference for speaking directly to a provider compared with women (odds ratio [OR] 0.75, 95% CI 0.60-0.94; P=.01). Older age (OR 1.01, 95% CI 1.00-1.02; P<.001), having a chronic condition (OR 1.83, 95% CI 1.44-2.33; P<.001), and having an income lower than US $20,000 (OR 1.61, 95% CI 1.11-2.34; P=.01) were positively associated with indicating a preference for speaking directly to a provider. Hispanic individuals had significantly higher odds of indicating that they had no need for a patient portal (OR 1.59, 95% CI 1.24-2.05; P<.001) compared with non-Hispanic individuals. Older individuals (OR 1.05, 95% CI 1.04-1.06; P<.001), individuals with less than a high school diploma (OR 3.15, 95% CI 1.79-5.53; P<.001), and individuals with a household income of less than US $20,000 (OR 2.78, 95% CI 1.88-4.11; P<.001) had significantly higher odds of indicating that they were uncomfortable with a computer.

CONCLUSIONS

The most common barriers to patient portal adoption are preference for in-person communication, not having a need for the patient portal, and feeling uncomfortable with computers, which are barriers that are modifiable and can be intervened upon. Patient characteristics can help predict which patients are most likely to experience certain barriers to patient portal adoption. Further research is needed to tailor implementation approaches based on patients' needs and preferences.

The Need to Develop Standard Measures of Patient Adherence for Big Data: Viewpoint

Despite half a century of dedicated studies, medication adherence remains far from perfect, with many patients not taking their medications as prescribed. The magnitude of this problem is rising, jeopardizing the effectiveness of evidence-based therapies. An important reason for this is the unprecedented demographic change at the beginning of the 21st century. Aging leads to multimorbidity and complex therapeutic regimens that create a fertile ground for nonadherence. As this scenario is a global problem, it needs a worldwide answer. Could this answer be provided, given the new opportunities created by the digitization of health care? Daily, health-related information is being collected in electronic health records, pharmacy dispensing databases, health insurance systems, and national health system records. These big data repositories offer a unique chance to study adherence both retrospectively and prospectively at the population level, as well as its related factors. In order to make full use of this opportunity, there is a need to develop standardized measures of adherence, which can be applied globally to big data and will inform scientific research, clinical practice, and public health. These standardized measures may also enable a better understanding of the relationship between adherence and clinical outcomes, and allow for fair benchmarking of the effectiveness and cost-effectiveness of adherence-targeting interventions. Unfortunately, despite this obvious need, such standards are still lacking. Therefore, the aim of this paper is to call for a consensus on global standards for measuring adherence with big data. More specifically, sound standards of formatting and analyzing big data are needed in order to assess, uniformly present, and compare patterns of medication adherence across studies. Wide use of these standards may improve adherence and make health care systems more effective and sustainable.