The study, published in Frontiers in Health Services on October 21, 2026, evaluated the Long COVID and Fatiguing Illnesses Recovery Program as a two-arm, single-blind, professional cluster randomized controlled trial registered as NCT05167227. Clinicians were individually assigned at a 1:1 ratio. The intervention group received weekly ECHO sessions in addition to the educational opportunities available to both groups, while the control group received monthly interactive webinars and quarterly online short courses. One clinician from each arm withdrew after baseline data collection, leaving 18 participants and 92 repeated clinician observations for the primary survey analysis.

Each weekly ECHO meeting combined a presentation on emerging clinical topics and recommended practices with an interactive discussion and a case presented by a participating clinician. Subject-matter experts included specialists in pulmonology, physical medicine and rehabilitation, cardiology, neurology, nutrition, and ME/CFS, many based at academic medical centers. People with lived experience took part in every session, adding perspectives on symptom trajectories, stigma, and patient priorities. Across the study, which ran from December 2021 through October 2024, investigators conducted 89 weekly ECHO sessions, 34 monthly webinars, and nine quarterly courses. The monthly webinars averaged about 300 participants and reached audiences in the United States and more than 62 countries.

Clinicians reported their knowledge, confidence or self-efficacy, and changes to practice through quarterly surveys. The researchers constructed standardized composite scores for each outcome and used generalized linear models to account for repeated observations within clinicians. The preferred adjusted model controlled for time since baseline, clinician sex, years of experience, possession of a medical degree, and baseline confidence. In this model, the intervention was associated with a 0.77-standard-deviation increase in knowledge, with a 95% confidence interval from 0.20 to 1.33, and a 0.48-standard-deviation increase in confidence, with a 95% confidence interval from 0.09 to 0.88. The corresponding estimate for self-reported practice change was 0.52, but its interval ranged from -0.08 to 1.12 and included no effect.

The absence of a statistically significant between-group difference in self-reported practice change was important because clinicians in both arms improved. The investigators said it may reflect the design of the program, which deliberately converted lessons from the small weekly ECHO sessions into monthly webinars and short courses so that control clinicians received many of the same recommendations. Contamination was also possible because clinicians could not be blinded to their assignments and sometimes worked in the same clinics. Administrators reported that intervention clinicians shared information in staff meetings, training sessions, and informal consultations. Such exchanges would tend to improve control-group performance and reduce the measured difference between arms rather than exaggerate it, although the study did not directly quantify how much contamination occurred.

Objective electronic health record data nevertheless supported a change in behavior. Intervention clinicians made significantly fewer specialist referrals for each patient assigned to them with Long COVID or a related condition: the adjusted estimate was -0.44 referrals per patient, with a 95% confidence interval from -0.62 to -0.26. They also made fewer referrals when assigned and unassigned patients were combined, with an estimate of -0.33 and a 95% confidence interval from -0.50 to -0.15. The reduction for unassigned patients alone did not reach statistical significance. There was no significant difference in the number of patients seen each month or in average visit duration. Among 806 clinical recommendations made by multidisciplinary experts during weekly ECHO sessions, 178 were subsequently applied by intervention clinicians to patient care.

Participation appeared related to the size of the clinician outcomes. Across the pooled sample, each additional learning session was associated with an improvement of about 0.013 standard deviations on each of the three main outcome scales, and the corresponding standardized regression coefficients ranged from 0.34 to 0.37. Intervention clinicians attended an average of 51.3 learning sessions, compared with 16.6 among controls, accumulating about 27 more hours of educational exposure. An exploratory, unregistered analysis estimated that marginal gains began to plateau at approximately 65 sessions for knowledge and 74 sessions for confidence and practice change. The researchers cautioned that these thresholds should not be treated as definitive because the analysis was exploratory, the maximum observed attendance was 97 sessions, and the intervention-only estimate for knowledge was not statistically significant.

The ECHO approach uses a hub-and-spoke structure in which specialist teams interact with frontline clinicians through case-based learning. Its goal is to strengthen primary care capacity for conditions in which patients may otherwise wait months for specialty appointments or travel long distances. The program pairs access to multidisciplinary expertise with structured discussion of real cases and lived-experience input. In this clinician-outcomes report, the measured referral result is consistent with intervention clinicians managing more aspects of these cases themselves. The broader recovery program included separate analyses of patient outcomes; this paper reports the clinician results and does not by itself establish that reduced referral use improved symptoms, quality of life, or other patient health outcomes.

The evidence remains constrained by the trial’s scale and setting. It included only 20 clinicians from one health system, had approximately 66% power to detect a standardized mean effect of 0.5, and had limited external validity for clinicians, specialties, and communities operating in different systems. Most clinician outcomes were self-reported and therefore vulnerable to response bias, while knowledge improvement and practice change could only be measured after baseline because they were defined as changes from baseline. The control group received active education rather than no intervention, and knowledge sharing between colleagues was inherent to the pragmatic clinical setting. The results therefore support weekly ECHO sessions as a promising means of improving clinician knowledge and confidence and reducing specialist referral for complex chronic conditions, but they do not show that every health system will obtain the same effects.

Subject of Research: Randomized trial of weekly virtual ECHO clinician education for Long COVID and other infection-associated chronic conditions

Article Title: Effectiveness of an Extension for Community Health Outcomes case-based virtual community of practice model on clinician outcomes for the management of long COVID and fatiguing illnesses: a randomized control trial

Article References: Zuber, A., Rothwell, J. T., Samaniego, J. C., Sharp, S. P., Taren, D., Unger, E. R., Bertolli, J., Lin, J.-M. S., Regan, J. J., Armistad, A. J., Scott, J. D., Struminger, B. B., Godino, J. G., & Ramers, C. B. (2026). Effectiveness of an Extension for Community Health Outcomes case-based virtual community of practice model on clinician outcomes for the management of long COVID and fatiguing illnesses: a randomized control trial. Frontiers in Health Services, 6, Article 1912262. https://doi.org/10.3389/frhs.2026.1912262

Image Credits: AI Generated

DOI: 10.3389/frhs.2026.1912262

Keywords: Long COVID, ME/CFS, ECHO model, randomized controlled trial, primary care, clinician education, specialist referrals, telehealth, community health centers, infection-associated chronic conditions, Effectiveness, Extension

The scale of the problem the region set out to solve is familiar to health systems everywhere. Emergency department overcrowding is driven in large part by high volumes of low-complexity cases, patients with conditions that need prompt attention but not the full apparatus of a hospital emergency service. In 2023, Emilia-Romagna launched a network of community-based Urgent Care Centers, or UCCs, designed to intercept these visits before they reached hospital doors. By April 2025, 43 such centers were operating across the region, and the new study set out to measure what happened to emergency department traffic as they came online.

The research team, led by Daniela Fortuna and Dario Tedesco of the Emilia-Romagna regional health directorate along with collaborators from the universities of Bologna and Parma, took advantage of a natural experiment. Because the centers opened at staggered times across different districts, the investigators could apply an interrupted time-series design, using segmented regression models to compare observed daily low-acuity emergency visit volumes against the trajectory that would have been expected based on pre-opening trends, while adjusting for annual and weekly seasonality. The data came from routinely collected regional health databases spanning January 2022 to April 2025.

The headline finding is striking. On average, after the opening of the first urgent care center in a district, daily low-acuity emergency department visits ran 13.5 percent lower than expected, with a confidence interval running from minus 13.9 to minus 13.0 percent. And the effect grew as the regional network expanded. In the later periods of the study, the shortfall deepened to 22.5 percent and then 23.6 percent below expected levels, suggesting that the centers became more effective at diverting appropriate patients as coverage and public familiarity spread.

But the most consequential result is not the average. It is the enormous spread across organizational models. Urgent care centers that shared a pre-triage pathway with the emergency department, so that patients arriving at the hospital could be redirected on the spot to the adjacent urgent care service, cut low-acuity emergency visits by 42.2 percent. Community-based centers located far from hospitals, without that shared access point, achieved only a modest 9.5 percent reduction. And centers physically adjacent to hospitals but lacking the shared pre-triage arrangement showed essentially no reduction at all, at minus 0.7 percent, a figure statistically indistinguishable from zero.

That pattern carries a clear message for planners: physical proximity to a hospital is not enough, and neither is simply adding urgent care capacity somewhere in the community. What appears to matter is integration, the deliberate engineering of a single front door through which patients with urgent but low-complexity needs are sorted and routed. A shared pre-triage model means the patient who shows up at the emergency department with a sprained ankle or a fever does not need to know in advance where to go; the system redirects them. Community sites, by contrast, depend on patients self-selecting, which the data suggest happens far less reliably.

The study’s multilevel logistic regression analysis reinforced that point from the patient side. The strongest predictor of whether a resident used an urgent care center rather than an emergency department was simply whether a center existed in the municipality of residence, which raised the odds of urgent care use roughly sevenfold. Convenience and geographic access, in other words, shape urgent care behavior powerfully, but they operate most effectively when combined with system-level routing rather than left to individual navigation.

The case mix comparison between urgent care centers and low-acuity emergency visits adds further texture. The centers, nearly half of which were embedded in Community Health Centers and roughly 37 percent located within hospitals, with 46.5 percent offering round-the-clock coverage, were handling precisely the kind of urgent-but-not-emergent presentations that clog emergency departments. That alignment between what the centers treat and what the emergency departments were shedding is what makes the volume shifts interpretable as diversion rather than mere displacement.

The authors are appropriately careful about causal claims. Because no contemporaneous untreated comparator region was available, they caution that the observed differences should not be interpreted as effects attributable solely to the urgent care implementation. Secular trends, concurrent policy changes, or shifts in patient behavior could in principle contribute to the pattern. Still, the dose-response relationship, with effects strengthening as the network expanded and concentrating where integration was deepest, is difficult to explain without invoking the centers themselves.

For health systems grappling with emergency department overcrowding, the Emilia-Romagna experience offers a concrete design lesson wrapped in rigorous time-series evidence. Urgent care centers are not interchangeable widgets; their impact on emergency department load depends on whether they are stitched into a shared access and pre-triage pathway or left as isolated alternatives. As regions elsewhere consider similar investments, the Italian data suggest that the architecture of the network, not just the number of centers, will determine whether the emergency department finally gets the relief it needs.

Subject of Research: Effect of urgent care center integration into primary care networks on low-acuity emergency department utilization

Article Title: Integrating urgent care centers into primary care networks to reduce emergency department overcrowding: a real-world implementation and evaluation

Article References: Fortuna, D., Golinelli, D., Caranci, N., Grilli, R., Donatini, A., Alberani, M., Marinelli, S., Berti, E., Tedesco, D., Emilia-Romagna UCC Working Group, Barbagallo, V., Bartoli, S., Casoni, F., Cisbani, L., Clo, M., Fabbri, E., Gentili, A., Lama, B., Marino, M., … Camplone, I. (2026). Integrating urgent care centers into primary care networks to reduce emergency department overcrowding: a real-world implementation and evaluation. BMC Health Services Research. https://doi.org/10.1186/s12913-026-15566-z

Image Credits: AI Generated

DOI: 10.1186/s12913-026-15566-z

Keywords: emergency department overcrowding, urgent care centers, primary care, interrupted time series, health services research, pre-triage, Emilia-Romagna, low-acuity visits, health policy, community health centers, patient diversion, Italy

The review, conducted by Alexandra K. Lersten and Carrie B. Dolan, followed the Arksey and O’Malley methodological framework and the PRISMA-ScR reporting guidelines. The team searched PubMed, Scopus, CINAHL, and Google Scholar for studies published between 2001 and 2025, ultimately including 19 sources: 17 identified through database searches and two grey literature sources providing policy and health-system context. Because the search deliberately restricted keywords to article titles to keep the screening workload manageable and reproducible, the authors caution that the findings represent a mapping of a high-specificity evidence base rather than an exhaustive inventory of all relevant research.

The scale of the problem is documented across multiple national data sources. An analysis of the 2002–2008 National Health Interview Survey found persistent socioeconomic disparities in eye care accessibility and usage. In 2017, nine percent of people who reported needing glasses also said they could not afford them. Data from the National Health and Nutrition Examination Survey showed that households earning more than $75,000 had lower odds of visual impairment, and children in families below the federal poverty line were twice as likely to have visual impairment as children in families earning at least 200 percent of that threshold.

Financial barriers extend well beyond household income into the architecture of insurance coverage itself. In many states, Medicaid treats eye care as an auxiliary benefit rather than an essential health service. More than six million Medicaid enrollees live in states that lack comprehensive vision exam coverage, and more than 14 million live in states without coverage for eyeglasses. Even where coverage exists on paper, practical access can falter: one study found that obtaining an eye care appointment was more difficult for patients with Medicaid than for those with private insurance, a disparity the authors link to reimbursement levels and provider participation.

The health care safety net shows similar cracks. Federally qualified health centers, or FQHCs, are often the only accessible entry point to care for uninsured and low-income patients—nearly seven in ten FQHC patients have incomes at or below the federal poverty level—yet 69 percent of these centers do not provide on-site comprehensive eye exams. The consequences ripple outward. Research on emergency department visits suggests that lack of insurance coverage is associated with emergent eye-related cases, and that improving access to ophthalmologic care in uninsured communities could reduce the progression of untreated chronic eye disease into costly emergency visits.

Informational and geographic barriers compound the financial ones. A 2014 nationwide online poll of 2,044 U.S. adults found that 25 percent were unfamiliar with any eye conditions, 37.3 percent had never heard of diabetic retinopathy, and half did not know macular degeneration existed. Among patients with glaucoma, low health literacy has been linked to missed appointments and lower medication use. Geography matters too: an analysis of 2012 Medicare data found that rural cataract patients traveled significantly farther for ophthalmic care than their urban and suburban counterparts, reflecting an uneven distribution of providers that persists across the country.

The stakes of these barriers extend far beyond eyesight itself. Visual impairment has been associated with depression, lost productivity, injuries, and premature death, and vision loss and socioeconomic disadvantage are tightly intertwined—people with visual impairment are more than twice as likely to rely on Medicaid as those without it. Delayed care also means later detection of disease: observational studies report a higher prevalence of diabetic retinopathy among lower-income populations, a condition that is far more manageable when caught early through routine screening.

To organize this fragmented evidence, the researchers applied Kingdon’s Multiple Streams Framework, a policy science model that conceptualizes change as the alignment of three streams: problem recognition, available policy solutions, and political conditions. Coding the 19 included sources against these streams revealed a telling imbalance. Seventeen sources, or 89 percent, contributed evidence to the problem stream, 16, or 84 percent, to the policy stream, but only nine, or 47 percent, to the politics stream. The authors stress that this pattern reflects the characteristics of the peer-reviewed evidence base rather than an absence of political activity, since government and advocacy literature was not systematically searched.

The policy stream does contain promising approaches. Community-based vision screening, integrated eye care within community health centers, and teleophthalmology have all been associated with improved access or service utilization in specific populations. Yet the review finds these interventions are typically localized and resource-dependent, sustained by temporary funding or individual health systems rather than embedded in broader policy. A screening program for underserved adults, for example, identified high rates of visual problems requiring comprehensive treatment, but follow-up rates after referral remained consistently low—a breakdown in linkage to care that limits the real-world impact of well-intentioned programs.

The authors conclude that closing these gaps will likely require coordinated, system-level change: expanded adult vision coverage in Medicaid and other public insurance, greater standardization of benefits across states, stronger integration of vision screening into primary care, and sustained federal investment in community health centers. They point to Rwanda’s integration of eye care into a national community-based health insurance scheme as an illustrative, if not directly transferable, international model. Emerging tools such as artificial intelligence-based screening systems and teleophthalmology may also help expand capacity where providers are scarce, though questions of cost, connectivity, and patient acceptance remain. What the evidence makes clear is that recognizing the problem has never been the missing ingredient—aligning needs, solutions, and political will is the harder task ahead.

Subject of Research: Income-related and structural disparities in access to eye care in the United States

Article Title: Blinded by inequity: a scoping review of income-related and structural disparities in eye care in the United States

Article References: Lersten, A. K., & Dolan, C. B. (2026). Blinded by inequity: a scoping review of income-related and structural disparities in eye care in the United States. Frontiers in Public Health, 14, Article 1885854. https://doi.org/10.3389/fpubh.2026.1885854

Image Credits: AI Generated

DOI: 10.3389/fpubh.2026.1885854

Keywords: eye care, health disparities, vision impairment, Medicaid, healthcare access, scoping review, socioeconomic factors, teleophthalmology, community health centers, health policy, Kingdon Multiple Streams Framework, public health

The study drew on a nationally representative survey of community health center patients designed by the Health Resources and Services Administration in partnership with RTI International and fielded in 2022. The survey achieved an unusually high response rate of 85 percent, lending credibility to the findings. From that dataset, the researchers identified 2,942 adults aged 18 to 74 who had at least one cardiometabolic risk condition and had completed a primary care visit. The burden in this population was striking: 62.8 percent had obesity, 60.1 percent had hypertension, 50.9 percent had dyslipidemia, and 25.3 percent were living with type 2 diabetes. These are precisely the conditions for which daily self-management, more than any single clinical intervention, determines long-term outcomes.

To measure communication quality, the team used five adapted questions from the Consumer Assessment of Healthcare Providers and Systems survey, the standard instrument used across the United States to capture patient experience. Patients rated their physician on a Likert scale from zero to three for each item, and the scores were aggregated into a composite patient-centered communication score ranging from zero to twenty. The researchers validated this composite using exploratory factor analysis, confirming that the items tapped a single underlying construct rather than unrelated impressions. The mean score in the sample was 17.7, with a median of 20, indicating that most patients rated their physicians favorably, though with meaningful variation across the population.

The outcome measure was equally rigorous. Each patient’s adoption of self-management behaviors was scored across five domains: weight management, dietary change, physical activity, reducing sedentary time, and smoking reduction. Weighted fraction scores for behaviors in each domain were summed and multiplied by one hundred, producing a ratio-scale self-management score with a possible range from minus thirty to 470. The observed mean was 246.3 with a standard deviation of 82 and a median of 250, meaning that even in this motivated safety-net population, patients were achieving roughly half of the possible behavior-change score. The scoring scheme was developed to capture the partial, incremental nature of lifestyle change, recognizing that patients rarely adopt every recommended behavior at once.

After adjusting for demographic variables, chronic conditions, and patient-reported measures of their enabling environment, including opportunities for physical activity, food security, and physical or mental health disability, the association held firm. Each one-point increase in the patient-centered communication score was associated with a 1.8-point increase in the cardiometabolic self-management score, with a standard error of 0.5 and a p-value below 0.001. In practical terms, a patient whose physician scored at the top of the communication scale would be expected to adopt substantially more self-management behaviors than a comparable patient whose physician scored lower, independent of how easy or difficult their daily circumstances made healthy living.

Why should conversation style matter so much for behavior as concrete as diet, exercise, and smoking? The answer lies in the psychology of behavior change. Cardiometabolic self-management requires patients to make dozens of small decisions every day, often in the absence of any clinician. Patient-centered communication, which involves eliciting the patient’s own concerns, tailoring advice to their life circumstances, checking understanding, and sharing decision-making, builds the patient’s confidence and sense of ownership over their health plan. For patients with limited health literacy, a common characteristic of community health center populations, this style of communication can be the difference between understanding a recommendation and merely hearing it. Prior meta-analytic work has already linked physician communication to medication adherence; the new study extends that logic to the harder domain of lifestyle behavior.

The setting matters as much as the mechanism. Community health centers serve more than thirty million people in the United States, disproportionately low-income patients, racial and ethnic minorities, and rural residents who carry the heaviest burden of cardiometabolic disease and have the least access to specialists. National data suggest that only a small fraction of American adults maintain optimal cardiometabolic health, and disparities have widened over recent decades. If the modest but reliable boost associated with patient-centered communication could be scaled across the health center program, the population-level effect on diabetes complications, cardiovascular events, and healthcare costs could be substantial. Unlike expensive new therapies, communication training is a comparatively low-cost intervention, and recent trials have shown that targeted communication training for clinicians can change patient outcomes, including vaccine uptake in underserved outpatient populations.

The study’s design has limitations worth noting. Because it is cross-sectional, relying on patient reports at a single point in time, it cannot definitively prove that communication causes better self-management; it is possible that patients who are already more engaged with their health both perceive their physicians as more communicative and adopt healthier behaviors. The self-management measure also depends on patient self-report, which can be imperfect. Yet the strength of the design, a nationally representative sample, a high response rate, validated measurement instruments, and statistical adjustment for the environmental factors that typically confound such analyses, makes the association difficult to dismiss. The researchers also note that the dataset is publicly available through HRSA, allowing other teams to test and extend the findings.

For clinicians and health system leaders, the message is deceptively simple: the way physicians talk is part of the treatment. Health systems that invest in communication skills, protect visit time for genuine dialogue, and use patient-experience feedback not as a bureaucratic exercise but as a clinical quality measure may see returns far beyond satisfaction scores. For patients managing diabetes, hypertension, obesity, or high cholesterol, the study offers a practical prompt: bring your questions to the visit, say what is hard about following the plan, and ask for advice tailored to your life. The evidence suggests that when the conversation is truly centered on the patient, the effects follow the patient home, into the kitchen, the neighborhood walk, and the daily choices that ultimately decide whether cardiometabolic disease progresses or is held at bay.

Subject of Research: The association between physician patient-centered communication and cardiometabolic disease self-management among community health center patients

Article Title: Does Patient-Centered Communication by Physicians Facilitate Cardiometabolic Disease Self-management Among Community Health Center Patients? A Nationwide Study

Article References: Xirasagar, S., Nan, Z., Platonova, E., Merrell, M., & Natafgi, N. (2026). Does Patient-Centered Communication by Physicians Facilitate Cardiometabolic Disease Self-management Among Community Health Center Patients? A Nationwide Study. Journal of General Internal Medicine. https://doi.org/10.1007/s11606-026-10928-z

Image Credits: AI Generated

DOI: 10.1007/s11606-026-10928-z

Keywords: patient-centered communication, community health centers, cardiometabolic disease, type 2 diabetes, hypertension, obesity, dyslipidemia, self-management, CAHPS, primary care, health communication, health literacy

The work is part of a larger pragmatic randomized trial called InSPIRED, short for Implementation Strategies for Self-Measured Blood Pressure Monitoring in Racially and Ethnically Diverse Populations. The trial registered as NCT06871462 spans six community health centers within two safety-net healthcare systems, the San Francisco Health Network and Alameda Health System. Before any intervention could be tested, the team needed to understand precisely where the process of home blood pressure monitoring breaks down, both for patients who are asked to measure themselves and for clinicians who are asked to prescribe, train, and document. Their answer was to borrow methods from human-centered design, the same iterative, empathy-driven approach that technology companies use to build products around real user behavior.

The patient-facing side of the research was extensive. The investigators conducted nine focus groups and eighteen individual interviews in English, Spanish, and Chinese, reaching a total of sixty patients. This multilingual design mattered: safety-net populations include large numbers of patients whose primary language is not English, and implementation strategies built only around English-language materials routinely fail them. The interviews probed three domains: the challenges patients face when trying to engage with home blood pressure monitoring, their preferences for training and hypertension education, and their attitudes toward involving peers, family members, or friends in their hypertension care.

The findings on training were strikingly consistent. Patients said they preferred in-person, language-concordant instruction on how to perform self-measured blood pressure monitoring and how to use mobile health applications that support it. A single demonstration at the pharmacy counter or a printed leaflet was not enough. Patients wanted ongoing access to training resources, such as videos they could revisit whenever they forgot a step or a family member needed to learn the technique. This preference for refreshable, on-demand education reflects a well-known problem in digital health: initial training decays quickly, and without reinforcement, correct technique, including proper cuff placement, resting posture, and timing of measurements, drifts within weeks.

Perhaps the most socially interesting result concerned peer support. Patients expressed genuine enthusiasm for joining virtual or in-person support groups focused on hypertension, provided the groups were led by trained research staff and used vetted discussion content. The idea of harnessing community for a chronic condition that is otherwise managed alone at home resonated with participants. But when it came to family and friends, patients drew a clear boundary. Most preferred low-touch approaches that would not burden their loved ones, such as giving family members access to the same educational materials the patients received, rather than asking relatives to take on active caregiving tasks like tracking readings or managing medications. The distinction is subtle but important for intervention designers: patients want their social networks informed, not conscripted.

On the clinic side, the researchers convened seven focus groups with sixty-two clinicians to map the obstacles that arise across the entire self-measured blood pressure workflow. The list was long and revealing. Clinicians described the absence of standardized workflows for educating patients about home monitoring, uncertainty about how to confirm that a patient’s home device is clinically validated and fitted with the correct cuff size, difficulty training patients on measurement technique within the constraints of a brief visit, and inconsistent documentation of monitoring plans in the electronic health record. Each of these friction points may seem minor in isolation, but together they form a gauntlet that a home monitoring program must survive, and in busy, under-resourced clinics, the path of least resistance is often simply not to start.

Device validation deserves particular attention because it is a technical detail with real clinical consequences. Blood pressure monitors sold for home use vary enormously in accuracy, and inaccurate devices produce readings that can lead to misdiagnosis or inappropriate treatment. Clinicians in the focus groups flagged that confirming validation and appropriate cuff size, which differs by arm circumference, was a recurring and poorly supported task. Any implementation strategy that ignores this step risks building a monitoring program on unreliable data.

Having gathered this evidence, the team prioritized pragmatic, low-cost strategies built around two pillars. The first was training care teams and clinical champions, embedding expertise within each clinic so that knowledge about validated devices, proper technique, and patient education does not depend on a single enthusiastic individual. The second was a suite of electronic health record tools designed to smooth the clinical workflow. These included reminders that surface the core teaching content for self-measured blood pressure monitoring and instructions for validating home monitors, standardized documentation templates known as smartphrases that let clinicians record monitoring plans quickly and consistently, and patient-facing instructions in the patient’s own language that clinicians can print or send with minimal effort.

The elegance of the approach lies in its economy. Rather than proposing expensive new platforms or additional staffing that safety-net systems cannot sustain, the co-design process surfaced interventions that piggyback on infrastructure already in place: the electronic health record that clinicians already use, the educational materials that can be produced once and reused indefinitely, and the social networks that patients already trust. Human-centered design served as the filter that separated plausible-on-paper strategies from ones that patients and clinicians said they would actually adopt, and the multilingual engagement ensured the resulting tools would work for the diverse populations these centers serve.

The study, funded by the Agency for Healthcare Research and Quality with additional support from the National Institutes of Health, offers a template that extends beyond blood pressure. As remote monitoring expands to diabetes, heart failure, and pregnancy-related hypertension, the same implementation challenges will recur: who trains the patient, how the technique is verified, how the data flows into the record, and how the plan is communicated. The InSPIRED team’s answer, co-design with patients and clinicians in their own languages before building anything, is a deceptively simple prescription. Whether the co-designed strategies ultimately raise blood pressure control rates will be answered by the ongoing randomized trial, but the study already demonstrates that the people closest to the problem can articulate solutions that experts might never imagine, from peer support groups with vetted content to the quiet insistence that family should be informed but not burdened.

Subject of Research: Co-designed implementation strategies for self-measured blood pressure monitoring in community health centers

Article Title: Co-Designing Pragmatic implementation strategies to improve adoption of self-measured blood pressure monitoring by patients and clinicians in community health centers

Article References: Kim, H. C., Li, J., Garcia, F., Larreynaga, J., Luna, I., Mejia-Lopez, A., Yang, A., Curtis, N. C., Lyles, C. R., Sarkar, U., & Khoong, E. C. (2026). Co-Designing Pragmatic implementation strategies to improve adoption of self-measured blood pressure monitoring by patients and clinicians in community health centers. BMC Health Services Research. https://doi.org/10.1186/s12913-026-15825-z

Image Credits: AI Generated

DOI: 10.1186/s12913-026-15825-z

Keywords: hypertension, self-measured blood pressure, community health centers, human-centered design, implementation science, electronic health records, health equity, patient education, digital health, safety-net care, pragmatic clinical trial, remote monitoring

The research team interviewed eleven care management staff from four geographically diverse health centers and five subject matter experts in health information technology, all drawn from OCHIN, a nonprofit that hosts a shared instance of the Epic EHR for more than 2,000 community health center clinics across 37 states, the largest such network in the country. In 2022, OCHIN activated Epic’s care management module, called Compass Rose, which is designed to support care coordination activities including the tracking of contextual drivers such as food, housing, and transportation insecurity. Yet at the time of the study, fewer than 10 percent of OCHIN member clinics had ever used the module to make and track referrals for these needs, a striking adoption gap that motivated the investigation.

Methodologically, the study was a formative evaluation informed by human-centered design principles, conducted between September 2023 and July 2024. The researchers used semi-structured interviews paired with a virtual “guided tour” technique, in which participants shared their screens and demonstrated how they actually navigated the EHR to document screening, make referrals, and follow up, using a dummy patient record. Transcripts were analyzed with a rapid qualitative analytic approach organized around the Integrated Technology Implementation Model, and the findings were distilled into a care manager journey map that traces each step of addressing contextual drivers, the tasks involved, and the barriers that surface at each one. Preliminary findings were shared back with participants to verify accuracy.

Step one of the journey, screening, is the system’s relative bright spot. Health centers screen for contextual needs at check-in, rooming, or care management enrollment, and results are captured in EHR flowsheets that support longitudinal tracking. Some centers have configured alerts that prompt any staff member opening a chart to screen, and shortcuts allow quick insertion of relevant text into notes. Once documented, social risk data appear as color-coded icons in the EHR’s patient summary and within the care management module itself, giving care managers a consolidated view. One care manager described the appeal plainly: everything from screenings to disease-specific questions is “all right there,” eliminating the need to hunt across the chart for information relevant to care planning.

Step two, making referrals, is where the machinery begins to grind. For internal referrals to social workers or community health workers, care managers can use EHR messaging and referral ordering. For external referrals to community-based organizations such as food pantries or transportation services, some centers use community resource referral systems like Findhelp or Unite Us, platforms increasingly integrated with EHRs to enable closed-loop communication with registered organizations. But adoption of these platforms is hampered by two major challenges the participants identified: the effort and cost required for both clinics and community organizations to establish the referral model, and the fact that many community-based organizations lack the technological infrastructure to engage in the required data exchange at all. Relationships, participants stressed, matter as much as software; one expert recounted how a center’s referrals went unaccepted because the organizations it wanted to reach had never been onboarded to the platform.

Documentation of referrals proved equally problematic. Most EHR tools as configured at the participating centers offer no discrete field for referral documentation outside a specific referral work queue, and that work queue demands extensive manual entry and is not linked to care management care plans. Within the care management module, care plans include only pre-set, general referral options that must be customized by hand, a task one care manager called a “huge slowdown” that is “very, very time-consuming.” Worse, care plans built inside the module do not propagate to other views of the chart, forcing care managers to re-enter the same information elsewhere so that other care team members can see it. As one staff member explained, the care plan exists only in the module and “doesn’t cross over into any other part” of the record, so visibility elsewhere requires duplicative documentation. The practical result is that much referral information ends up in free-text notes, where it cannot be systematically tracked.

Step three, tracking whether patients actually connected with services, exposes the deepest gaps. Community resource referral systems could in principle close the loop by letting community providers report service receipt back into the EHR, but their limited adoption leaves most centers without that capability. Only referrals routed through the standard EHR referral work queue can be followed longitudinally, and even then, the lack of integration with care management care plans means outcome dispositions must be re-entered in multiple locations. Referrals documented in care plans through free text or shortcuts were not reliably trackable at all. One staff member admitted that after years of doing this work, the center had no formal referral pathway to community partners and could barely “fathom how that would work” given the scale of capturing and closing referrals. Notably, the care management module contains a “tasking” dashboard feature that could support referral tracking, but care managers reported they rarely use it for this purpose simply because they never received adequate training on how.

The study’s authors argue that these barriers can be sorted into three categories: technical, organizational, and those requiring implementation support rather than tool redesign. On the technical side, structured data fields for referrals, care plans customized to each center’s specific programs and reimbursement requirements, and alignment with emerging documentation standards such as those promoted by the Gravity Project could make referral data visible, actionable, and reportable. On the organizational side, the findings highlight a structural tension: health centers are investing heavily in EHR tools and workflows, but the community organizations receiving referrals are often under-resourced to participate in electronic exchange. Without investment in the infrastructure and readiness of those partners, even well-designed platforms will be underused, a problem likely to be most acute in communities with the fewest available services. The authors suggest implementation strategies that include assessing community organization readiness, mapping feasible referral pathways, and building backup workflows when electronic exchange is not possible.

Implementation support emerges as the study’s central prescription. Participants described their training on the care management module as something they “learned as we went,” with comments like “there wasn’t much training available” and wishes for “a much better training program.” Experts confirmed that hands-on, step-by-step guidance with demonstration and practice is the single biggest lever for improving uptake, and that support must be ongoing, since staff reported questions persisting even one or two years after adopting the tools. Leadership backing, workflow redesign coaching, and site-specific configuration assessments before training begins round out the recommended support package. These findings will now feed directly into a cluster-randomized trial, registered on ClinicalTrials.gov, that will test implementation strategies aimed at helping care management teams adopt EHR-based tools for social care coordination, an effort the researchers describe as the first of its kind. The study’s limitations are acknowledged: a small sample, a single EHR system, and the absence of community organization perspectives, though the authors note that Epic’s dominance in health centers and the breadth of roles interviewed strengthen the findings’ relevance.

The broader significance is hard to overstate. Federal and state programs, from Medicare’s Chronic Care Management codes to California’s CalAIM Enhanced Care Management, increasingly require the screening of social needs and linkage to services, and value-based payment models tie reimbursement to that documentation. If the electronic backbone meant to support this work remains siloed and untracked, centers risk both missed interventions for vulnerable patients and unfulfillable reporting obligations. This evaluation offers a precise map of where the technology works, where it breaks, and what a coordinated fix would require: better configuration, shared visibility across teams, genuine two-way infrastructure with community partners, and sustained, hands-on support for the people asked to use it.

Subject of Research: Adoption of electronic health record-based care management technologies for addressing social needs in community health centers

Article Title: Community Health Center Adoption of Enabling Technologies to Address Contextual Drivers of Health for Care-Managed Patients: Formative Evaluation

Article References: Owens-Jasey, C., Gunn, R., Cook, N., Fein, H. L., Pisciotta, M., Fee, C., Larson, Z., Templeton, A., & Gold, R. (2026). Community Health Center Adoption of Enabling Technologies to Address Contextual Drivers of Health for Care-Managed Patients: Formative Evaluation. Journal of General Internal Medicine. https://doi.org/10.1007/s11606-026-10735-6

Image Credits: AI Generated

DOI: 10.1007/s11606-026-10735-6

Keywords: community health centers, electronic health records, care management, social needs, care coordination, health information technology, referrals, implementation science, contextual drivers, social determinants of health, qualitative research, health informatics

The study draws on data from 1,326 FQHCs operating in the United States as of 2024, excluding U.S. territories and facilities serving fewer than 100 adult women. Together, the included centers represent the vast majority of the FQHC system and serve about eight million females of reproductive age. Investigators assessed whether prenatal care is delivered on-site versus handled through outside referral pathways.

Overall, about two-thirds of FQHCs provide on-site prenatal care, while roughly one in three do not. That gap matters because prenatal visits are not just check-ins; they structure risk detection, chronic condition management, patient education, and continuity of care—elements that influence birth outcomes and maternal safety. When services are absent locally, patients may face delays in scheduling, transportation barriers, or fragmented handoffs.

The geographic pattern is especially striking. “Maternity desert” regions—areas with limited maternal health resources—often lacked FQHC presence entirely or included centers that did not offer prenatal care on-site. The result is a double bind: fewer local options and fewer direct services when women need them most.

Importantly, the study also finds that centers serving higher proportions of Black and Hispanic patients, Medicaid populations, individuals with limited English proficiency, and urban communities were more likely to provide on-site prenatal care. In other words, where prenatal services exist within the safety-net system, they disproportionately reach groups that face the greatest access barriers.

Researchers emphasize that the findings identify a practical expansion target: growing on-site capacity within FQHCs while strengthening coordinated external referral systems where on-site care is unavailable. The authors argue that addressing workforce and financial constraints will be essential for making maternal care coverage consistent.

The study further suggests a strategy for closing regional shortages, including expanding FQHC capacity in maternity care deserts using Health Resources and Services Administration (HRSA) “New Access Point” style grants. If implemented, these investments could shift prenatal access from “mostly available” to broadly dependable—especially in communities already at risk of delayed or disrupted care.

Ultimately, the work reframes FQHCs as both a critical platform and a measurable opportunity. For maternal health equity, the question is no longer whether safety-net infrastructure exists, but whether prenatal care is delivered where patients live, in the form patients can reliably reach.

Subject of Research: Prenatal care service availability at federally qualified health centers (FQHCs)
Article Title: Provision of Onsite Prenatal Care Services at U.S. Federally Qualified Health Centers
News Publication Date: 15-Jul-2026
Web References: http://dx.doi.org/10.7326/ANNALS-26-00381
References: Cole MB, Auty S, Zi Jin G, Safon C, Gordon SH. Annals of Internal Medicine. Published July 14, 2026. doi:10.7326/ANNALS-26-00381
Image Credits: Not provided in the provided content

Keywords: FQHC, prenatal care, maternal health equity, maternity deserts, Medicaid, workforce capacity, health access disparities