If annual funding is approved at the first-year level, the initiative represents nearly $25 million in investment in rural Colorado over five years. Approximately $1.42 million of the first-year award is budgeted to support CU Anschutz Pharmacy’s role in the project, an investment that could total more than $7 million over the full five-year span, making STREAM one of the largest awards in the history of the Skaggs School. Denver Recovery Group serves as the lead grantee, working in partnership with CU Anschutz Pharmacy, The Steadman Group, and community and healthcare partners across the state to develop and implement the new model. The scale of the collaboration reflects a deliberate design choice: rather than building new infrastructure from scratch, STREAM aims to connect the healthcare resources and trusted relationships that already exist in Colorado’s small communities into a single coordinated network of care.

The scale of the problem the initiative confronts is stark. Nearly 722,000 Coloradans live in rural communities, and 47 of the state’s 64 counties are classified as rural or frontier. Many residents face chronic healthcare provider shortages, long travel distances and limited access to specialty and behavioral health services. Those barriers become particularly consequential for people seeking treatment for opioid use disorder, a condition for which rural communities often have few treatment providers and limited behavioral health resources, and where transportation difficulties and fragmented care can make it hard for patients to begin and remain in treatment. At the same time, rural populations carry significant burdens from chronic conditions such as diabetes, hypertension and cardiovascular disease, illnesses that demand consistent monitoring, careful medication management and ongoing clinical follow-up that distant clinics struggle to provide.

Colorado STREAM’s answer to this geography of scarcity is a hub-and-spoke architecture built around the local pharmacy. The model will create connections among regional treatment hubs, community pharmacy networks, telehealth services and coordinated whole-person care. Concretely, the initiative will work to expand access to evidence-based medications and support for opioid use disorder; connect patients and rural pharmacy teams with treatment specialists and other clinicians through telehealth and coordinated referrals; increase access to medication management for chronic diseases such as diabetes, hypertension and cardiovascular disease; and build rural healthcare workforce capacity by training pharmacists, pharmacy technicians, students, preceptors and collaborating healthcare professionals. The program will also develop sustainable models that allow community pharmacies to play a larger role in delivering and coordinating healthcare, and it will use data and evaluation to measure outcomes, improve care and refine a model that can be sustained and expanded over time.

The logic of placing pharmacies at the center of the network is grounded in both trust and logistics. Community pharmacists are among the most accessible healthcare professionals in rural America, often the only clinically trained providers physically present in a town, and they already hold medication expertise and established relationships with the patients they serve. By connecting them with treatment specialists, technology and coordinated care networks, the initiative aims to bring critical services closer to patients rather than asking patients to travel long distances to find care. Telehealth links and structured referral pathways are intended to extend the reach of regional treatment centers into communities where recruiting physicians and behavioral health clinicians has proven persistently difficult, converting existing pharmacy counters into access points for a far broader continuum of care.

The partnership behind the project is deliberately broad. Denver Recovery Group, led on the ground by Regional Director Denise Vincioni, served as the lead applicant and brings evidence-based treatment expertise for opioid use disorder, including medications for opioid use disorder, counseling, case management and care coordination. The Steadman Group, led on the project by JK Costello, MD, MPH, contributes program design and evaluation capacity, while the CU Anschutz team, led by Rob Valuck, PhD, RPh, Wes Nuffer, PharmD, and Dean Brian Tsuji, PharmD, adds academic depth in pharmacy practice, addiction science and experiential training. The collaboration also includes national and regional pharmacy operators Albertsons-Safeway and Kroger/City Market, independent rural pharmacies such as Downtown Drug in Glenwood Springs and Buena Vista Drug, and CPESN Colorado, a statewide network focused on expanding community pharmacy-based patient care. Emily Zadvorny, PharmD, Executive Director of the Colorado Pharmacists Society, brings additional statewide pharmacy leadership to the effort, a roster designed to ensure the model is informed by the realities of delivering care in communities of very different sizes and regions.

Leaders involved in the project have framed it as a rethinking of how healthcare can reach places the traditional system has left behind. Dean Brian Tsuji has described the investment as an extraordinary opportunity to rethink rural care delivery, noting that community pharmacists are already trusted professionals embedded in these communities and that connecting them with treatment specialists, technology and coordinated networks can bring services to patients instead of forcing patients toward services. Denise Vincioni has emphasized that people in rural Colorado should be able to receive high-quality treatment and coordinated healthcare closer to home, and that STREAM connects treatment expertise with trusted community pharmacies, academic partners, technology and local care resources so that distance is less of a barrier to recovery and better health. Rob Valuck has argued that where a person lives should not determine whether they can get the care they need, and that the strength of the hub-and-spoke model lies in not trying to recreate an entire healthcare system in every rural community, but in connecting regional expertise with pharmacists already caring for patients close to home.

Wes Nuffer has added a practical dimension to that vision, observing that for many rural Coloradans the community pharmacy may be one of the most accessible points of healthcare in their community, and that STREAM builds on that existing relationship rather than creating entirely new infrastructure. From the university’s perspective, the initiative also carries an educational mission: preparing future pharmacists to practice in rural and frontier settings and demonstrating how pharmacists can contribute more broadly to the healthcare team. Tsuji has noted that pharmacists have always been medication experts but that their potential contribution to rural healthcare extends much further, and that STREAM offers a chance both to improve access today and to train the next generation of pharmacists to become an integral part of the rural healthcare workforce, a tangible example of combining education, innovation, clinical expertise and community partnerships to tackle complex healthcare challenges.

The award sits within a much larger wave of federal investment. Colorado’s Rural Health Transformation Program is supported through the federal Rural Health Transformation Program administered by the Centers for Medicare & Medicaid Services, a five-year initiative authorized under Section 71401 of H.R. 1, Public Law 119-21, which provides grants totaling $50 billion in federal funding nationwide from Federal Fiscal Year 2026 through FFY 2030. Colorado is directing $169,587,181 in RHTP grants to rural healthcare providers across the state, and through a highly competitive application process, 91 applicants and approximately 250 projects were selected to receive funding across 52 rural or frontier counties and three rural census tract counties. Colorado’s first-year award totals $200,105,604.17 and is 100 percent funded by CMS. The state program’s priorities include expanding the rural healthcare workforce, strengthening rural healthcare networks, increasing preventive care capacity, integrating telehealth and technology, and developing new approaches to rural care delivery, priorities that STREAM touches on nearly every front.

For the communities involved, the measure of success will be practical: whether a person with opioid use disorder in a frontier county can start evidence-based medication without a multi-hour drive, whether a diabetic patient can get consistent medication management from a pharmacist they already know, and whether the network can sustain itself financially beyond the grant period. The award remains subject to execution of the Grant Agreement and annual funding is subject to continued approval, so the five-year horizon is not yet guaranteed. But if the model performs as its architects hope, Colorado STREAM could offer a template for a national question: how to convert the most trusted and most accessible healthcare professionals in rural America into the connective tissue of a system that has long struggled to reach them. The initiative’s own data and evaluation work will determine whether that template is ready to travel beyond the Rockies.

Subject of Research: Pharmacy-based rural healthcare access and opioid use disorder treatment in Colorado through the Rural Health Transformation Program

Article Title: $4.9M RHTP award will expand pharmacy-based healthcare access across rural Colorado

Article References: $4.9M RHTP award will expand pharmacy-based healthcare access across rural Colorado. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: rural health, community pharmacy, opioid use disorder, telehealth, Colorado, Rural Health Transformation Program, CU Anschutz, medication management, hub-and-spoke model, healthcare workforce, chronic disease, CMS

The research team drew on data from the 2023 wave of the China Longitudinal Aging Social Survey, a nationwide survey conducted by Renmin University of China. The descriptive sample comprised 11,670 adults aged 60 years or older, of whom 11,655 had usable data on chronic conditions. Multimorbidity was defined in a deliberately strict and clinically meaningful way: a participant was considered to have multimorbidity only if they reported two or more chronic conditions that had each been diagnosed by a physician. This physician-confirmed definition matters, because self-reported disease labels can be unreliable, and anchoring the definition to clinical diagnosis reduces the risk of inflating disease burden estimates.

The headline numbers are striking. Among the 11,655 participants with available chronic-condition data, 5,311 people, or 45.6 percent, met the definition of multimorbidity. In other words, nearly one in two older Chinese adults in the survey was living with at least two diagnosed chronic diseases. Against that backdrop, 573 participants, or 4.9 percent of the sample, reported difficulty taking medications independently. That figure was derived from a single functional item asking respondents whether they could take medications by themselves, a deceptively simple question that captures a complex chain of abilities: opening containers, reading labels, remembering schedules, and physically manipulating pills.

To test whether multimorbidity was genuinely associated with medication-taking difficulty rather than merely correlated with it, the researchers used multivariable logistic regression, a statistical technique that estimates the odds of an outcome while adjusting for other characteristics that could confound the relationship. The primary model produced an adjusted odds ratio of 2.682, with a 95 percent confidence interval of 2.163 to 3.324. Because that confidence interval sits entirely above 1, the finding is statistically robust: older adults with multimorbidity had roughly 2.7 times the odds of reporting difficulty taking medications independently compared with those without multimorbidity, after accounting for other measured factors.

Yet the single most powerful predictor in the analysis was not disease count but functional limitation. Participants with functional limitation showed an adjusted odds ratio of 16.495 for difficulty taking medications independently, with a 95 percent confidence interval of 13.140 to 20.708. That is an enormous effect by epidemiological standards, and it makes intuitive sense: taking medication is itself a physical and cognitive task, so impairments in mobility, dexterity, vision or memory translate directly into difficulty managing a pill regimen. The finding reframes medication-taking not as a purely medical behavior but as a functional one, sitting squarely within the domain of daily living activities.

The most technically intriguing result concerns the interaction between multimorbidity and functional limitation. The multiplicative interaction term was statistically significant, with an interaction odds ratio of 0.219 and a 95 percent confidence interval of 0.120 to 0.398. On its face, an interaction odds ratio below 1 might suggest that functional limitation weakens the association between multimorbidity and medication difficulty. But the authors caution against a naive reading of that number. When the team calculated adjusted probabilities of medication-taking difficulty across the combined-status profiles, the highest probability was found among participants who had both multimorbidity and functional limitation. The statistical interaction reflects the way odds ratios behave on a multiplicative scale, where ceiling effects can compress ratios even as absolute risk continues to climb. In practical terms, the two vulnerabilities compound rather than cancel each other out.

This distinction between multiplicative interaction and absolute risk is more than a statistical footnote; it carries real consequences for how screening tools should be built. If analysts looked only at the interaction odds ratio, they might conclude that multimorbidity matters less for people who are already functionally limited. The adjusted probabilities tell the opposite story: the combined-vulnerability group represents the highest-risk profile in the population. For clinicians and policymakers, the lesson is that disease burden and functional status must be assessed together, because each amplifies the practical impact of the other on a person’s ability to manage treatment at home.

The study then took a second analytical step that distinguishes it from much of the existing multimorbidity literature: it connected these health profiles to the use of community healthcare services. Among participants who reported at least one community healthcare service need, the researchers examined whether combined-status profiles predicted unmet need. The result was clear. Older adults with both multimorbidity and difficulty taking medications independently had significantly higher odds of unmet community healthcare service needs, with an adjusted odds ratio of 2.197 and a 95 percent confidence interval of 1.604 to 3.008. The people least able to manage their own medications were also the people most likely to fall through the cracks of the community care system.

This service-gap finding lands at a delicate moment for China’s health system. The country is aging at a pace unmatched in modern history, and its policy response has emphasized strengthening primary and community-level care so that chronic disease management can happen close to home rather than in overcrowded tertiary hospitals. Medication adherence and safe self-administration are central to that vision, because most chronic disease treatment is delivered through daily pharmaceutical regimens. If nearly half of older adults carry multiple chronic conditions and a meaningful minority cannot manage their medications without help, then community health services become the load-bearing infrastructure of the entire chronic disease strategy. The study’s evidence that the combined-vulnerability group faces doubled odds of unmet need suggests that current service planning may not be reaching precisely the people who depend on it most.

The authors argue that their findings support integrating disease burden, functional status and medication-taking ability into a unified assessment of service-related vulnerability, and into needs-based planning for community health services. In practice, that could mean screening for medication-taking difficulty during routine community health visits, flagging older adults who combine multimorbidity with functional limitation for enhanced support such as medication management services, home visits or caregiver training. As with all cross-sectional research, the study captures a single moment in time and cannot establish whether multimorbidity causes medication difficulty or vice versa; the single-item measure of medication-taking ability also leaves room for more granular measurement in future work. But the scale of the dataset, the physician-anchored definition of multimorbidity and the careful layered analysis make a compelling case that the intersection of chronic disease, disability and medication management is where community healthcare in aging societies will be won or lost. For the hundreds of millions of older adults navigating multiple prescriptions across Asia and beyond, the pill bottle, it turns out, is a frontline of healthcare.

Subject of Research: Multimorbidity, functional limitation and medication-taking difficulty among older adults in China

Article Title: Multimorbidity, functional limitation, difficulty taking medications independently, and unmet community healthcare service needs among older adults in China: a cross-sectional analysis of the 2023 CLASS wave

Article References: Mao, W., Chen, Z., Shao, Z., Jiang, W., Gao, L., & Tian, K. (2026). Multimorbidity, functional limitation, difficulty taking medications independently, and unmet community healthcare service needs among older adults in China: a cross-sectional analysis of the 2023 CLASS wave. BMC Health Services Research. https://doi.org/10.1186/s12913-026-15736-z

Image Credits: AI Generated

DOI: 10.1186/s12913-026-15736-z

Keywords: multimorbidity, older adults, medication management, functional limitation, community health services, China, CLASS survey, unmet healthcare needs, cross-sectional study, logistic regression, aging, health services research

The review team searched four major biomedical databases, PubMed, CINAHL, the Cochrane Library, and Scopus, for studies published in English from 2010 onward that involved adults aged 65 or older and evaluated programs designed to carry patients from hospital to home. The methodological net was deliberately wide, capturing randomized controlled trials, cohort studies, and qualitative investigations alike. From 42 initial records, the researchers removed 12 duplicates, screened 22 full-text articles, and ultimately included 15 studies in the synthesis. Two independent reviewers extracted study characteristics, intervention components, outcome measures, and implementation factors, a dual-extraction approach that reduces the risk of single-reviewer bias creeping into the evidence base.

What emerged from the synthesis is a remarkably consistent picture of what a transitional care program looks like when it is done well. Across the included studies, the authors identified a recurring set of core components: patient-centred assessment, comprehensive discharge planning, care coordination, patient and family education, medication management, follow-up monitoring, home-care services, and multidisciplinary team involvement. None of these elements is exotic. They are, in essence, the plumbing of continuity of care, the deliberate engineering of information flow and human contact across the boundary between two very different care environments. The review’s contribution lies in showing how frequently these components co-occur in successful programs and how their combination, rather than any single element, appears to drive benefit.

The reported outcomes give the components their weight. Programs built on this template were associated with improved functional status, better quality of life, higher patient satisfaction, and improved medication management. Perhaps most striking for health system planners, the studies documented reductions in hospital readmissions, fewer emergency department visits, and shorter lengths of stay. These are the metrics that hospital administrators watch most closely, because readmissions within 30 days of discharge have long served as a proxy for fragmented care and a driver of avoidable cost. The review’s findings align with a broader literature, including landmark randomized trials of comprehensive discharge planning with home follow-up and pharmacist-led medication reconciliation programs, which have repeatedly shown that structured post-discharge support changes hard clinical endpoints rather than merely softening patient experience.

Behind the headline outcomes sits a technical question that the review confronts directly: why do some programs succeed where others fail? The authors point to variation in intervention intensity and implementation across settings as a critical moderating factor. A transitional care program that assigns an advanced practice nurse to make home visits within 72 hours of discharge is a fundamentally different intervention from one that consists of a phone call a week later, even if both are labelled with the same name. This heterogeneity, sometimes called the black box problem in implementation science, makes it difficult to know which dose of care, in terms of contact frequency, duration, and professional skill mix, produces the measured effect. The review found that reporting of intervention fidelity and dose was limited across the included studies, meaning that even the positive results come with an asterisk about reproducibility.

The review also identifies a persistent structural blind spot: family caregivers. Older adults with multiple chronic conditions rarely manage their recovery alone, yet the analysis found insufficient integration of family caregivers into discharge planning and follow-up across the included programs. This finding echoes a growing body of evidence, including meta-analytic work showing that caregiver engagement enhances outcomes in randomized trials of transitional care interventions. Caregivers are, in functional terms, the only members of the care team who are present around the clock. When they are not taught to recognize warning signs, not included in medication conversations, and not given a direct line back to the clinical team, the transitional care model loses its most continuous sensor. Programs that treat caregivers as trained partners rather than passive recipients of instructions appear to perform measurably better.

Measurement inconsistency poses a further challenge to the field. The review notes that outcome measurement varied across studies, complicating any attempt to pool effects or compare programs head to head. One trial may report readmission rates at 30 days while another tracks functional status at 90 days; a third may rely on patient-reported satisfaction without capturing utilization at all. Without standardized outcome domains and time points, the evidence base resembles a collection of portraits rather than a single landscape. The authors argue that future models should standardize intervention delivery and outcome measurement, a recommendation that aligns with international movements toward core outcome sets in geriatric research and with the World Health Organization’s integrated care for older people framework, which emphasizes person-centred assessment pathways in primary care.

The clinical logic underlying these programs is worth unpacking for readers unfamiliar with the mechanics of care transitions. Hospital discharge represents a handoff of responsibility from an environment with continuous monitoring, standardized medication administration, and immediate access to diagnostics, to an environment with none of these safeguards. Physiologically vulnerable patients, particularly those with heart failure, frailty, or polypharmacy, are discharged into a period of heightened risk that begins the moment they leave the ward. Transitional care programs work by extending elements of the hospital’s safety architecture into the home: a structured assessment identifies who is at highest risk, discharge planning ensures the receiving environment is prepared, education equips patients and families to act on early symptoms, medication reconciliation prevents the dangerous discontinuities that arise when inpatient and outpatient medication lists diverge, and scheduled follow-up creates a feedback loop that catches deterioration before it becomes a 911 call.

The review’s conclusions are measured but constructive. Transitional care programs, the authors write, can facilitate safer and more effective transitions for older adults. The prescription for the next generation of models is threefold: strengthen family engagement, standardize intervention delivery and outcome measurement, and ensure continued post-discharge follow-up rather than support that evaporates after the first week. That last point deserves emphasis, because the risk window after discharge does not close neatly at 30 days, and several of the most successful models in the broader literature have extended nurse-led follow-up across weeks or months for patients with complex needs.

As populations age worldwide, the stakes of getting this right will only climb. Older adults with multiple chronic conditions account for a disproportionate share of hospital utilization, and each transition between settings is an opportunity for error, omission, or decline. What this review offers is not a single breakthrough therapy but something arguably more useful for health systems: a validated checklist of the components that repeatedly appear in programs that work, paired with an honest accounting of the gaps, in fidelity reporting, caregiver integration, and measurement, that still separate the evidence from a fully reproducible blueprint. The task now, the authors suggest, is to move from knowing that transitional care can work to specifying exactly how, for whom, and at what intensity, so that the safest room in the hospital is the one the patient has already left.

Subject of Research: Core components and outcomes of transitional care programs for older adults moving from hospital to home

Article Title: Transitioning to Care: Core Components and Outcomes of Transitional Care Programs for Older Adults

Article References: Ray Panda, S., Shetty, A. P., & Dwibedi, B. (2026). Transitioning to Care: Core Components and Outcomes of Transitional Care Programs for Older Adults. Ageing International, 51(4), Article 41. https://doi.org/10.1007/s12126-026-09679-3

Image Credits: AI Generated

DOI: 10.1007/s12126-026-09679-3

Keywords: transitional care, older adults, hospital discharge, care coordination, readmissions, family caregivers, medication management, systematic review, geriatrics, continuity of care, discharge planning, home care

The research team, led by Reina Taguchi of the Institute for Health Economics and Policy in Tokyo along with colleagues at the University of Tokyo and other Japanese institutions, asked a deceptively simple question: does the size of a pharmacy’s visiting practice shape the kind of patients it serves, the resources it deploys, and the medication outcomes those patients experience? To answer it, the investigators turned to an unusually rich data source — linked medical and long-term care insurance claims from a single city in Tokyo, allowing them to track both health care use and care needs for the same individuals over time.

The study population consisted of adults aged 65 and older who began using visiting pharmacist services between fiscal years 2015 and 2018. In total, 2,699 older adults were identified. Rather than treating all pharmacies as interchangeable, the researchers grouped them into tertiles according to their annual patient volume, creating low-, medium-, and high-volume categories. This design allowed the team to compare patient characteristics, medication profiles, and pharmacy attributes across the spectrum of practice scale, and then to follow medication counts over time using sophisticated statistical modeling.

The first striking finding concerns who ends up on the caseloads of busy pharmacies. High-volume pharmacies were not simply scaled-up versions of their smaller counterparts; they served a categorically different patient population. Their patients were younger but clinically far more complex, and the proportion of patients with terminal cancer was dramatically higher — 21.2 percent at high-volume pharmacies compared with just 6.3 percent at low-volume ones, a difference that was highly statistically significant. In other words, the largest visiting pharmacy practices have become de facto hubs for patients at the most fragile and medically demanding end of the home care spectrum.

That concentration of complexity is mirrored, and quite plausibly enabled, by the pharmacies’ staffing. High-volume pharmacies employed a median of nine full-time pharmacists, compared with a median of just three at low-volume practices — again a difference that reached statistical significance at p less than 0.001. This is not a trivial distinction in a field where round-the-clock availability, rapid response to symptom changes, and coordination with physicians and home nurses all demand substantial personnel. The pattern suggests a structural division of labor: larger practices, with deeper staffing reserves, absorb the patients whose conditions change fastest and whose medication regimens are most demanding to manage.

The longitudinal heart of the study focused on a subset of 2,005 participants for whom complete medication trajectory data were available. The researchers modeled the number of medications each patient was taking over time using linear mixed-effects models — a statistical framework well suited to repeated measures nested within individuals, who are themselves nested within pharmacies. The models included random intercepts at both levels and adjusted for recent hospitalization, a critical control because hospital discharges are precisely the moments when medication lists balloon. Potentially inappropriate medications were assessed with tools including the Japanese Anticholinergic Risk Scale, reflecting the particular risks of anticholinergic burden in older adults.

What the trajectories revealed is perhaps the study’s most consequential result. Before visiting pharmacist services began, patients’ medication counts were climbing steadily, at a rate of roughly 0.16 additional drugs per month — a familiar and worrying pattern of prescribing cascade in deteriorating patients. After service initiation, that climb all but stopped: medication counts rose by only about 0.03 drugs per month. The change in slope, a reduction of 0.13 drugs per month with a 95 percent confidence interval of −0.16 to −0.10, was statistically robust. In plain terms, the introduction of a visiting pharmacist marked a turning point at which runaway polypharmacy was brought under control.

Equally important is what did not differ. This stabilization effect held consistently across all three pharmacy volume groups, from the smallest practices to the largest hubs. Whatever advantages scale confers in staffing and patient mix, the fundamental benefit of a pharmacist regularly entering the home — reconciling medication lists, deprescribing where appropriate, coordinating with prescribers after hospitalizations — appears to operate regardless of practice size. The authors interpret this as evidence that visiting pharmacists engage at key care-transition points, the moments when patients are most vulnerable to medication errors and accumulation.

The findings arrive at a moment when health systems worldwide are scrambling to design sustainable home care workforces. Japan, one of the fastest-aging societies on Earth, has built an elaborate architecture of home medical care including home care support clinics and hospitals, and visiting pharmacist services are an explicit pillar of that system. By showing that patient volume is strongly associated with case complexity and staffing depth, the study provides empirical input for workforce planning: reimbursement models that assume all visiting pharmacies are interchangeable may systematically undervalue the high-volume hubs that shoulder the most complex, end-of-life cases.

There are limits worth keeping in mind. The study is retrospective and draws on claims data from a single Japanese city, Hachioji, whose data infrastructure made the analysis possible; generalization to other health systems requires care. Claims data also capture what was dispensed rather than every nuance of clinical decision-making. Yet the core message stands on solid ground: in aging societies, the pharmacies that visit the most patients tend to care for the sickest, and they do it with proportionally larger full-time teams — while the act of bringing a pharmacist into the home reliably halts the relentless growth of medication burden. As other nations expand home-based care, that combination of structural insight and clinical reassurance is exactly the kind of evidence policy will need.

Subject of Research: Visiting pharmacist services and medication management among older adults receiving home-based care in Japan

Article Title: Pharmacy patient volume and visiting Pharmacist services: variation in patient characteristics, pharmacy attributes, and medication changes

Article References: Taguchi, R., Okada, A., Tsuchiya-Ito, R., Kitamura, S., Ishikawa, T., & Hamada, S. (2026). Pharmacy patient volume and visiting Pharmacist services: variation in patient characteristics, pharmacy attributes, and medication changes. BMC Health Services Research. https://doi.org/10.1186/s12913-026-15673-x

Image Credits: AI Generated

DOI: 10.1186/s12913-026-15673-x

Keywords: visiting pharmacist services, polypharmacy, home-based care, aging population, long-term care, potentially inappropriate medications, pharmacy patient volume, claims data, care transitions, Japan, health services research, medication management