Home Visits by Health Teams Cut Hospital Readmissions for Older Patients, Swedish Study Finds

For millions of older adults, the journey home from the hospital is the most dangerous leg of their medical care. The first days and weeks after discharge are a well-documented period of vulnerability, when medication errors, missed follow-up appointments, and the sudden loss of round-the-clock monitoring can spiral into complications severe enough to send patients straight back through the emergency department doors. Health systems around the world have tried to blunt this risk with transitional care programs of every description, from pharmacist-led medication reconciliation to intensive home visits, yet the evidence base remains stubbornly mixed. Now a Swedish study offers a fresh and cautiously encouraging data point: a time-limited, interprofessional home care intervention known as Safe homecoming was associated with a substantially lower risk of hospital readmission among patients aged 75 and older, at least in the critical first three months after leaving the hospital.

The study, published in BMC Geriatrics by researchers affiliated with Örebro University and Region Örebro County, took advantage of a natural experiment in Swedish primary care. Between November 2016 and May 2019, a single primary health care centre in Örebro County implemented the Safe homecoming intervention, a structured program in which physicians, nurses, occupational therapists, and other professionals work together to plan and deliver tailored home health care for older patients in the immediate aftermath of a hospital stay. The intervention is deliberately time-limited and interprofessional, designed to catch avoidable complications early, coordinate medication management, and ensure that the transition from hospital to home does not leave patients falling through the cracks between specialist and primary care. Until now, however, the program had never been formally evaluated, leaving its designers without scientific evidence of whether it actually changed outcomes.

To fill that gap, the research team led by Ulrika Westerling assembled an unusually large comparison framework. Drawing on administrative registers and medical records spanning 2013 to 2020, they identified a source cohort of 38,338 patients aged 75 or older who had been hospitalized for at least one day in Örebro County. From this pool, 128 patients who had received the Safe homecoming intervention at the participating centre were matched, using propensity scores, to 512 controls from across the county who received standard care. Propensity score matching is a statistical technique that pairs treated and untreated patients on the basis of observed characteristics, in this case variables such as age, sex, comorbidity burden measured by the weighted Charlson Comorbidity Index, medication use classified by the Anatomical Therapeutic Chemical system, and diagnostic history coded under ICD-10. The goal is to make the two groups as comparable as possible, mimicking the balance of a randomized trial even though patients were not randomly assigned.

The matching appears to have worked well. The mean age in both groups was 85.5 years, and 60.9 percent of patients in each group were women, reflecting the demographics of the very old hospital population in Sweden. Standardized mean differences, the metric researchers use to quantify balance between matched groups, were used to confirm that the intervention and control patients were comparable on the measured covariates. Still, the authors are careful to note the inherent limits of observational designs: patients who received the intervention may have differed from controls in ways the registers could not capture, such as functional status, social support, or the simple fact of being enrolled at a primary care centre motivated enough to run an innovative program. These unmeasured differences, known as residual confounding, always loom over propensity score studies.

The headline result concerns readmissions. At 90 days after discharge, the cumulative incidence of a first hospital readmission was 20.3 percent in the intervention group compared with 33.6 percent among controls, a difference the authors tested with Gray’s test, yielding a p-value of 0.005. In plain terms, roughly one in five older patients who received Safe homecoming ended up back in the hospital within three months, versus one in three of those receiving usual care. Because death is a competing event that precludes readmission, the team employed the statistical machinery of competing-risk analysis, calculating Fine-Gray subdistribution hazard ratios that account for the fact that some patients died before they could be readmitted. The resulting subdistribution hazard ratio at 90 days was 0.57, with a 95 percent confidence interval of 0.37 to 0.86 and a p-value of 0.008, indicating a statistically significant reduction in readmission risk of roughly 43 percent. A parallel cause-specific Cox model, which treats deaths as censoring events rather than competing risks, produced a nearly identical hazard ratio of 0.55, with a confidence interval of 0.36 to 0.84.

The picture changes, however, when the follow-up window stretches to a full year. At 365 days, the Fine-Gray estimate was 0.79, with a confidence interval of 0.59 to 1.05 and a p-value of 0.098, a result that just misses conventional thresholds for statistical significance and suggests the intervention’s protective effect may fade over time. This pattern is biologically plausible. Transitional care interventions are, by design, time-limited; once the intensive home visits and coordinated planning end, older patients return to the same baseline risks of disease progression, frailty, and acute illness that precipitated their original hospitalization. The intervention may succeed at preventing the avoidable complications of a poorly managed discharge, but it cannot permanently insulate patients from the chronic conditions that put them in the hospital in the first place.

Mortality tells a more equivocal story. Across all the follow-up time points the researchers evaluated, the mortality estimates numerically favoured the intervention group, hinting that Safe homecoming might also be associated with longer survival. But the confidence intervals at every time point included the null value of one, meaning the observed differences could easily have arisen by chance. With only 128 patients in the intervention arm, the study simply lacked the statistical power to detect anything but a very large effect on death. The authors are explicit on this point: there is no clear evidence of an association between the intervention and mortality, and the numerical trend should be read as hypothesis-generating rather than confirmatory.

The study’s limitations deserve as much attention as its findings. Beyond the small intervention sample and the retrospective design, the researchers evaluated multiple follow-up time points, which raises the possibility that at least one of the reported results could reflect chance variation across the many analyses performed. The single-centre nature of the intervention also raises questions about generalizability; Safe homecoming was delivered by one primary health care centre with a particular team and a particular patient population, and other settings might implement the model differently or serve patients with different needs. The authors themselves conclude that the findings should be considered exploratory and require confirmation in larger prospective studies, ideally randomized trials that can eliminate confounding altogether and enroll enough patients to detect effects on mortality as well as readmission.

Even with those caveats, the study arrives at a moment when health systems across the high-income world are grappling with the twin pressures of aging populations and strained hospital capacity. Readmissions among older adults are enormously costly, both in financial terms and in the toll they take on patients, for whom each hospitalization brings risks of delirium, functional decline, and loss of independence. If a structured, interprofessional home care program delivered through ordinary primary care can cut 90-day readmissions by more than 40 percent, the potential public health payoff is substantial, particularly in countries like Sweden where primary health care centres already serve as the backbone of the system. The Swedish model examined here, which builds on coordinated individual planning and leverages existing primary care infrastructure rather than requiring new institutions, could be relatively straightforward to scale, though the authors’ call for larger prospective studies makes clear that the evidence is not yet strong enough to justify wholesale adoption. What the study does establish is a rigorous, registry-based template for evaluating such programs, one that other regions could replicate as they experiment with their own versions of a safer homecoming.

Subject of Research: Effects of a transitional home care intervention on mortality and hospital readmission among older adults after hospital discharge

Article Title: Safe homecoming intervention after hospital discharge: a retrospective cohort study of mortality and readmission among patients 75 years or older in Sweden

Article References: Westerling, U., Taj, T., Nilsing Strid, E., Hermansson, L., & Hellgren, M. (2026). Safe homecoming intervention after hospital discharge: a retrospective cohort study of mortality and readmission among patients 75 years or older in Sweden. BMC Geriatrics. https://doi.org/10.1186/s12877-026-08367-w

Image Credits: AI Generated

DOI: 10.1186/s12877-026-08367-w

Keywords: transitional care, older adults, hospital readmission, primary health care, propensity score matching, competing-risk analysis, geriatrics, home health care, Sweden, mortality, frail elderly, continuity of care