Publication

• Title: Remote Monitoring Approaches to Reduce Readmissions After Infection and Sepsis: A Randomized Clinical Trial
• Acronym: ACCOMPLISH
• Year: 2026
• Journal published in: JAMA Network Open
• Citation: Yende S, Talisa VB, Mayes K, Williams K, Malito A, Mayr FB, et al. Remote Monitoring Approaches to Reduce Readmissions After Infection and Sepsis: A Randomized Clinical Trial. JAMA Netw Open. 2026;9(6):e2616641.

Context & Rationale

• Background

  • Patients discharged after sepsis, COVID-19, or lower respiratory tract infection are at high risk of death, readmission, functional decline, and fragmented care.
  • Sepsis and pneumonia are leading causes of unplanned readmission, and readmissions after sepsis are common, costly, and often related to recurrent infection, cardiovascular disease, respiratory disease, or decompensation of chronic illness. ¹
  • Patient and caregiver experience research shows that readmission after critical illness is often distressing, disruptive, and associated with uncertainty about who is responsible for postdischarge care. ²
  • Remote patient monitoring is increasingly reimbursed and promoted as a way to detect deterioration earlier after discharge.
  • Before ACCOMPLISH, remote monitoring had a stronger evidence base in selected chronic diseases such as heart failure than in sepsis or serious infection; its effectiveness in post-acute infectious illness remained uncertain. ³
  • The ACCOMPLISH design paper framed the trial as a pragmatic, adaptive comparative-effectiveness trial intended to determine not merely whether remote monitoring works, but which monitoring intensity and response-team model should be used. ⁴
• Research Question/Hypothesis

  • The trial tested whether app-based symptom monitoring after hospitalisation for serious infection would increase the number of days alive and at home within 90 days after discharge.
  • It also tested whether broader questionnaires, covering heart and lung disease as well as infection, would outperform narrower infection-focused questionnaires.
  • It further tested whether a nurse practitioner–led enhanced team with palliative-care expertise would outperform a standard nurse call-centre response model.
  • The implicit hypothesis was that earlier detection and response to postdischarge deterioration would reduce readmissions, reduce mortality, increase home time, and identify patients needing hospice or advanced illness care.
• Why This Matters

  • Remote monitoring is already being scaled and reimbursed in many health systems despite limited disease-specific randomised evidence outside selected chronic conditions.
  • Readmission reduction is a major payer and health-system target, but readmission is not always an unambiguously adverse event if it represents timely rescue of a deteriorating patient.
  • ACCOMPLISH is important because it tested several realistic, deployable remote-monitoring models against an active postdischarge usual-care programme.
  • The trial also directly addressed precision population health: whether subgroups defined by age, discharge destination, illness severity, diagnosis, health literacy, technology comfort, or social deprivation respond differently to remote monitoring.

Design & Methods

• Research Question:
  • Among adults discharged home after hospitalisation for sepsis or lower respiratory tract infection, does remote therapeutic monitoring using low- or high-intensity questionnaires with standard or enhanced response teams increase postdischarge home days at 90 days compared with usual structured telephone support?
• Study Type:
  • Pragmatic, mixed-methods, individually randomised, response-adaptive, multicentre comparative-effectiveness trial.
  • Five-arm design: usual care plus four active remote-monitoring strategies.
  • Conducted across 19 hospitals in western Pennsylvania: 13 UPMC hospitals and 6 independently owned hospitals.
  • Embedded in an integrated delivery and finance system, with outcome tracking through electronic health records and payer claims.
  • Recruitment ran from March 25, 2021, to September 3, 2024; the intervention period ended December 8, 2024.
• Population:
  • Adults aged ≥21 years.
  • Hospitalised for sepsis, COVID-19, or lower respiratory tract infection.
  • Living in western Pennsylvania.
  • Insured through UPMC Health Plan or traditional Medicare fee-for-service.
  • Had a smartphone or other internet-connected device.
  • No cognitive impairment preventing participation.
  • Moderate or high predicted risk of readmission at index hospitalisation admission using an internal predictive model.
  • Randomised on the first weekday at home after hospital discharge; patients discharged temporarily to a skilled nursing facility were randomised only if they returned home within 28 days.
  • Key exclusions included admission from a setting other than home or independent living, hospice at hospital admission, discharge to hospice or long-term acute care, skilled-nursing-facility stay >28 days, severe persistent cognitive impairment, no suitable device or internet connection, no participating primary care clinician, pregnancy, and current participation in UPMC Advanced Illness Care.
• Intervention:
  • Four remote patient monitoring strategies were tested.
  • RPM-low + standard response: twice-weekly infection-focused symptom questionnaires for up to 90 days, with alerts managed by a nurse-staffed remote-monitoring call centre.
  • RPM-high + standard response: twice-weekly broader questionnaires covering infection plus deterioration in underlying heart or lung disease, with alerts managed by the standard nurse response team.
  • RPM-low + enhanced response: low-intensity questionnaires plus an enhanced team led by certified registered nurse practitioners.
  • RPM-high + enhanced response: high-intensity questionnaires plus the enhanced team.
  • Questionnaire responses generated medium/yellow or high/red alerts.
  • The standard team consisted of 4 remote-monitoring nurses who responded to alerts and coordinated care with primary or specialty clinicians.
  • The enhanced team included 2 nurses and 2 certified registered nurse practitioners with palliative-care expertise and access to social workers.
  • The enhanced team could diagnose conditions, develop treatment plans, order tests, prescribe under collaborative agreement, conduct early virtual visits, perform medication reviews, and initiate advance-directive or resuscitation-status documentation.
  • Remote monitoring started when the patient returned home and was paused during readmissions.
• Comparison:
  • Usual care was structured telephone support, not absence of follow-up.
  • It included a nurse or care-manager call during the first week after discharge.
  • The call assessed clinical status, reviewed discharge instructions and home-care needs, reconciled medications, and ensured follow-up appointments were scheduled.
  • Usual care was based on the Agency for Healthcare Research and Quality Re-Engineered Discharge Toolkit.
  • Primary care follow-up was encouraged within 7 days after discharge.
• Blinding:
  • Open-label for patients, implementation teams, and study coordinators because the intervention required visible remote-monitoring enrolment and clinical response workflows.
  • Most study investigators and clinical teams making readmission decisions were blinded.
  • Primary outcome ascertainment relied on electronic health record and claims data, limiting detection bias for mortality, readmission, and facility-days outcomes.
  • Readmission remains partly behaviour-dependent and may be influenced by alert generation, patient reassurance, or clinician thresholds for hospital referral.
• Statistics:
  • A sample size of 1500 with 10% attrition was initially estimated to provide >85% power to detect a cumulative odds ratio of 1.50 if at least one intervention was effective, corresponding to approximately a 9% absolute increase in patients surviving to 90 days without readmission; in November 2023 the target was resized to 1281 because observed attrition was only 2.5%, preserving >80% power for most effectiveness scenarios.
  • The primary analysis followed the intention-to-treat principle.
  • The primary outcome was analysed using a Bayesian proportional odds model for postdischarge home days, with death assigned −1 and survivors assigned 0 to 90 days alive at home.
  • A cumulative odds ratio >1 favoured remote monitoring for the primary outcome.
  • The model adjusted for calendar time, illness severity, and discharge location.
  • Response-adaptive randomisation began after a 250-patient burn-in period; usual-care allocation remained fixed while active-arm allocation probabilities were updated quarterly.
  • Final success required posterior probability >99.1% that the cumulative odds ratio was >1, a threshold selected to control the overall type I error at 2.5% across active arms.
  • Secondary outcomes used Bayesian linear or generalised linear models; readmission was also analysed with Fine-Gray competing-risk methods accounting for death.
• Follow-Up Period:
  • Primary outcome: 90 days after discharge home.
  • For patients temporarily discharged to a skilled nursing facility, the 90-day clock began after discharge from that facility.
  • Remote monitoring continued for up to 90 days while patients were at home.
  • Patient-reported functional and quality-of-life outcomes were assessed at approximately 90 days.

Key Results

This trial was not stopped early for superiority or futility. It completed recruitment to the revised sample size after resizing for lower-than-expected attrition and recruitment constraints during the COVID-19 era; 1296 patients were randomised and 1286 were included in the final analysis.

• The central finding is that none of the four remote-monitoring strategies increased postdischarge home days compared with a relatively active usual-care pathway.
• The age and skilled-nursing-facility subgroup findings are clinically important: in older adults and patients recently discharged via skilled nursing facilities, remote monitoring was associated with fewer home days and higher readmission rates.
• The primary outcome had a marked ceiling effect, with median postdischarge home days of 90 in every arm and 765/1286 patients (59.5%) achieving 90 home days; the Bayesian cumulative odds model therefore carried more interpretive weight than the medians.

Internal Validity

• Randomisation and Allocation:
  • Randomisation was individual-level and response-adaptive after an initial 250-patient burn-in period.
  • Usual-care allocation remained fixed, while allocation among the four intervention arms was updated quarterly according to accumulating outcome data.
  • Study staff were blinded to adaptive randomisation probabilities, reducing the risk that enrolment behaviour was influenced by emerging treatment-performance information.
  • The response-adaptive design created unequal final arm sizes: usual care 399, RPM-low standard 204, RPM-high standard 129, RPM-low enhanced 383, and RPM-high enhanced 171.
  • The smallest active arm, RPM-high standard, therefore had wider credible intervals and less precision than the largest active arm.
• Dropout and Exclusions:
  • Of 10,066 screened patients, 1573 consented and 1286 entered the final analysis cohort.
  • Major exclusions among screened patients included 6531 not meeting eligibility criteria, 1337 declining participation, 717 lacking a suitable device, 625 not being approached, and 364 having severe cognitive impairment.
  • Of 1573 consented patients, 277 were excluded before randomisation because they were ineligible at hospital discharge.
  • Reasons for pre-randomisation exclusion included discharge to an excluded location (88), in-hospital death (83), skilled nursing facility stay >28 days (59), other reasons (27), enrolment in another RPM programme before randomisation (9), withdrawal (6), proxy refusal or inability to contact (4), and no primary care physician (1).
  • Ten patients were incorrectly randomised and excluded from the final analysis.
  • The main analysis therefore applies to patients who survived to return home and remained eligible for postdischarge monitoring, not to all patients hospitalised with serious infection.
• Performance and Detection Bias:
  • The intervention could not be blinded to patients or implementation teams.
  • Primary outcome components were largely objective and derived from claims and electronic records: death, readmission, facility days, and home days.
  • Readmission is nevertheless a behaviour-sensitive outcome because alert generation may increase clinician contact and lower the threshold for emergency department referral or hospitalisation.
  • Patient-reported outcomes, including PROMIS mobility and quality of life, were more vulnerable to missingness and response bias than mortality or readmission.
• Protocol Adherence:
  • Remote-monitoring enrolment was incomplete: 529/887 (59.6%) patients assigned to RPM enrolled in the remote-monitoring programme.
  • Among enrolled patients, 10,561 questionnaires were delivered, with 5922 responses (56.1%).
  • Questionnaire response generated 3166 yellow alerts and 425 red alerts.
  • Nurses responded to more than 94% of alerts, indicating high fidelity once alerts were generated.
  • In enhanced-team arms, a virtual visit was attempted in 234/328 patients (71%); 139 visits were completed, 100 medication reviews were completed, and 75 goals-of-care discussions were completed.
  • Usual care was also delivered actively: 257/399 (64.4%) usual-care patients received a first-week follow-up call, and 201/257 (78.2%) answered.
• Baseline Characteristics:
  • Baseline characteristics were broadly balanced across arms.
  • Median age was 63 years (IQR 54 to 71), and 665/1286 (51.7%) were female.
  • Race was predominantly White, 1029/1286 (80.0%), with 199/1286 (15.5%) Black patients.
  • Median Charlson Comorbidity Index was 6 (IQR 3 to 9), indicating substantial multimorbidity.
  • Admission diagnoses were sepsis in 606/1286 (47.1%), lower respiratory tract infection in 367/1286 (28.5%), and COVID-19 in 313/1286 (24.3%).
  • Intensive care was used in 386/1286 (32.6%), mechanical ventilation in 62/1286 (4.8%), vasopressors in 144/1286 (12.2%), and dialysis in 100/1286 (8.5%).
  • The population was sufficiently high risk to test postdischarge support: 494/1286 (38.4%) had at least one readmission and 89/1286 (6.9%) died by 90 days.
• Heterogeneity:
  • Clinical heterogeneity was substantial, spanning sepsis, COVID-19, and lower respiratory tract infection.
  • Comorbidity burden, discharge destination, age, health literacy, technology comfort, and social deprivation varied across the cohort.
  • The Bayesian model prespecified subgroup analyses and adjusted for key prognostic factors.
  • Evidence of differential treatment response was strongest for age and discharge destination, with probability of differential response 99.9% and 99.7% by age for standard and enhanced teams, and 97.1% and 99.9% by skilled-nursing-facility versus home discharge.
  • Differential response probabilities were below 95% for sex, race, comorbidity, comfort with technology, health literacy, area deprivation, diagnosis, illness severity, predicted RPM enrolment, and COVID-era enrolment.
• Timing:
  • Randomisation occurred only after patients returned home.
  • Patients discharged temporarily to skilled nursing facilities entered the intervention only after returning home within 28 days.
  • This timing is appropriate for testing home-based remote monitoring, but it excludes deterioration occurring before discharge home.
  • The exclusion of 83 patients who died in hospital after consent and 59 patients who remained in skilled nursing facilities for >28 days shows that the trial did not include the sickest post-acute trajectories.
• Dose:
  • The tested dose was symptom-questionnaire monitoring twice weekly for up to 90 days.
  • The trial did not test remote physiological monitoring using continuous or intermittent vital signs.
  • It did not test hospital-at-home, in-person home visits, home intravenous therapy, or direct home diagnostics.
  • Moderate patient engagement reduced the practical dose: only 529/887 (59.6%) assigned to RPM enrolled, and only 5922/10,561 questionnaires (56.1%) received responses.
  • High-intensity questionnaires did not produce better outcomes than low-intensity questionnaires: marginal COR 0.91 versus 0.99 compared with usual care.
• Separation of the Variable of Interest:
  • Remote-monitoring exposure was clearly different from usual care in terms of questionnaires and alerts.
  • However, usual care was not minimal: 64.4% received first-week structured telephone follow-up, 42.5% of UPMC Health Plan usual-care patients completed a primary care visit within 7 days, and 78.9% did so within 30 days.
  • Primary care visit rates were similar in RPM arms: 7-day rates ranged from 41.8% to 46.7%, and 30-day rates ranged from 77.0% to 81.4%.
  • This high background care likely reduced the incremental contrast between RPM and control.
  • The active intervention generated 3166 yellow alerts and 425 red alerts, but qualitative results suggest that alert follow-up often consisted of referral to primary care or the emergency department rather than direct problem resolution.
• Key Delivery Aspects:
  • The trial tested a real-world, scalable remote therapeutic monitoring model rather than an idealised, highly staffed research intervention.
  • The enhanced team was more resource-intensive but did not deliver meaningfully better outcomes than usual care or standard nurse response.
  • The lack of effect persisted despite high nurse response to alerts, suggesting that the limiting factor was not merely alert neglect.
  • The usual-care pathway included structured telephone support and timely primary care follow-up, making it a strong comparator.
• Crossover:
  • Classic treatment crossover was not central to the trial.
  • The major implementation issue was non-enrolment or partial engagement in RPM despite assignment.
  • Post hoc analyses found similar treatment estimates among patients predicted to be more or less likely to enrol in remote monitoring, so lack of engagement alone did not explain the overall result.
• Adjunctive Therapy Use:
  • Usual care incorporated structured telephone support, medication reconciliation, home-care assessment, and primary care follow-up.
  • This active comparator may have addressed many problems that RPM aimed to detect.
  • There was no evidence that the control group required substantially more rescue intervention to compensate for absence of remote monitoring.
• Outcome Assessment:
  • Postdischarge home days is patient-centred and avoids focusing narrowly on readmission alone.
  • Death was assigned −1, preventing early death from appearing favourable because it avoids prolonged hospital or facility stay.
  • The outcome combined mortality, readmission, skilled nursing, rehabilitation, long-term ventilatory facility use, and home time.
  • The median was 90 days in all groups, creating a ceiling effect and making distributional modelling essential.
  • Readmission was not adjudicated as avoidable, harmful, beneficial, or clinically necessary.
• Statistical Rigor:
  • The Bayesian adaptive design was appropriate for simultaneously testing four related service-delivery strategies.
  • The analysis matched the design and used prespecified adjustment for calendar time, illness severity, and discharge location.
  • The success threshold was stringent: posterior probability >99.1% for superiority, chosen to control type I error.
  • Ten interim analyses were conducted.
  • The trial was resized transparently because attrition was lower than expected and recruitment was slowed by COVID-era constraints.
  • Sensitivity analyses, including payer-type analyses and survivor-only home-days analyses, were broadly consistent with the primary result.

Conclusion on Internal Validity: Internal validity is moderate to strong for the pragmatic question tested. Randomisation, objective outcome capture, Bayesian modelling, and prespecified subgroup analyses support credibility, but open-label care, moderate intervention engagement, a strong active usual-care comparator, and readmission’s susceptibility to care-seeking behaviour limit mechanistic certainty.

External Validity

• Population Representativeness:
  • The cohort represents adults recovering at home after hospitalisation for serious infection in a US integrated delivery and finance system.
  • The median Charlson Comorbidity Index of 6 and 38.4% readmission frequency indicate a clinically relevant post-acute risk population.
  • The trial excluded patients without a suitable device, those with severe cognitive impairment, those admitted from non-home settings, those discharged to hospice or long-term acute care, and those remaining in skilled nursing facilities beyond 28 days.
  • Patients were predominantly White and from western Pennsylvania, with only 1.0% Hispanic ethnicity.
  • Patients without internet-connected devices were not represented; 717 otherwise potentially eligible patients were excluded for lack of device access.
• Applicability:
  • The results apply most directly to symptom-questionnaire remote therapeutic monitoring after serious infection, not to remote physiological monitoring, wearable sensors, hospital-at-home, or in-person transitional care.
  • The findings are especially relevant to health systems considering broad deployment of remote monitoring after sepsis or pneumonia primarily to reduce readmissions.
  • Generalisability is lower in systems without integrated claims and electronic health record infrastructure, without nurse call centres, or without comparable primary care access.
  • Generalisability is also lower in systems where usual care after discharge is much less structured than ACCOMPLISH usual care.
  • The subgroup findings argue against indiscriminate extension to older adults and patients transitioning through skilled nursing facilities without further tailoring.

Conclusion on External Validity: External validity is good for US-style, insured, device-enabled postdischarge patients managed by an integrated health system. It is limited for patients without digital access, cognitively impaired patients, long-term care populations, non-US health systems, and models using physiological monitoring or direct home-based clinical care.

Strengths & Limitations

• Strengths:
  • Large randomised trial in a clinically important post-acute infection population.
  • Pragmatic design using real clinical staff and deployable care pathways.
  • Adaptive randomisation allowed simultaneous evaluation of four intervention strategies.
  • Active, patient-centred primary outcome combining survival and time at home.
  • High-quality ascertainment through electronic health records and claims.
  • Intention-to-treat analysis included eligible randomised patients regardless of RPM engagement.
  • Detailed process and engagement data clarified whether the intervention was actually delivered.
  • Qualitative interviews contextualised why patients did or did not perceive benefit.
  • Prespecified subgroup analyses identified clinically important heterogeneity by age and discharge destination.
• Limitations:
  • Open-label intervention with possible behaviour-mediated effects on readmission.
  • Single regional health system, limiting generalisability.
  • Digital-device requirement excluded 717 potentially eligible patients.
  • Moderate RPM engagement: 59.6% enrolled and 56.1% of questionnaires were answered.
  • Strong usual care with structured telephone support and high primary-care follow-up reduced incremental contrast.
  • Primary outcome ceiling effect: median postdischarge home days was 90 in every arm.
  • Readmissions were not adjudicated as preventable, necessary, beneficial, or harmful.
  • The trial tested patient-reported symptom monitoring, not remote vital-sign monitoring.
  • The enhanced team was resource-intensive but did not show incremental benefit, leaving uncertainty about how best to deploy post-acute workforce.

Interpretation & Why It Matters

• Clinical practice

  Routine symptom-questionnaire remote monitoring after sepsis or lower respiratory tract infection should not be implemented broadly with the expectation that it will reduce readmissions or increase home days beyond structured telephone support and timely primary care follow-up.
• Older adults

  The subgroup signal in patients ≥65 years is practice-relevant: remote monitoring was associated with fewer home days and higher readmission rates in a population commonly targeted for Medicare-reimbursed remote monitoring.
• Mechanism

  The likely mechanism is not failure to respond to alerts, because nurses responded to >94% of alerts; the more plausible issue is that symptom alerts may generate care escalation without improving underlying post-acute recovery.
• Health systems

  The trial argues for tailoring remote monitoring rather than scaling a single generic model across all post-infection discharges.
• Previous assumptions

  ACCOMPLISH challenges the assumption that more surveillance after discharge necessarily means fewer readmissions or better home-time outcomes; monitoring must be paired with an intervention capable of solving the problems it detects.

Controversies & Subsequent Evidence

• Remote monitoring versus actual care delivery:
  • ACCOMPLISH tested remote therapeutic monitoring based on patient-reported symptoms and alerts.
  • It did not test remote physiological monitoring, wearable vital-sign monitoring, home visits, hospital-at-home, or direct home treatment.
  • The trial therefore refutes a specific remote-monitoring model, not all forms of technology-enabled post-acute care.
  • Systematic reviews in heart failure and COPD show that remote monitoring effects vary substantially by disease, intervention design, adherence, and response infrastructure. ³⁵
• Active usual care matters:
  • The comparator was structured telephone support plus high rates of primary care follow-up.
  • Usual-care primary care visits occurred in 42.5% within 7 days and 78.9% within 30 days among UPMC Health Plan patients.
  • The appropriate interpretation is that RPM did not improve outcomes beyond a comparatively strong transition-of-care programme.
  • The result should not be used to argue that post-acute sepsis patients need no follow-up.
• Readmission reduction may be the wrong sole goal:
  • The older-adult subgroup raises a difficult question: did RPM trigger unnecessary hospitalisation, or did it identify clinical deterioration that otherwise would have been missed?
  • ACCOMPLISH did not adjudicate readmissions as preventable, necessary, beneficial, or harmful.
  • The JAMA Internal Medicine editorial accompanying the STAR sepsis transition trial made the broader methodological point that readmission can sometimes represent rescue rather than failure, and composite outcomes can be misleading if readmission and death move in opposite directions. ⁶
• Postsepsis recovery interventions remain difficult to make effective:
  • The SMOOTH trial of primary-care management after sepsis did not establish a clear improvement in mental-health-related quality of life. ⁷
  • The ENCOMPASS/STAR trial, a 3548-patient stepped-wedge trial of navigator-led telehealth sepsis transition and recovery support, did not reduce the primary composite of 90-day readmission or mortality: 48.2% with STAR versus 48.0% with usual care; adjusted OR 1.05; 95% CI 0.90 to 1.24; P=.53. ⁸
  • STAR showed lower mortality but numerically higher readmission, reinforcing that readmission-centred endpoints are hard to interpret in postsepsis care. ⁸
  • ACCOMPLISH adds that even when remote monitoring is aligned with payer guidance and embedded in a mature health system, improved home-time outcomes are not guaranteed.
• Home days as an endpoint:
  • Postdischarge home days is more patient-centred than readmission alone because it incorporates survival and time outside institutions.
  • The concept of “days spent at home” has been advocated as a patient-centred outcome in health services research. ⁹
  • In ICU survivors, days alive and at home at 90 days is associated with long-term survival and functional status, supporting its clinical relevance. ¹⁰
  • In ACCOMPLISH, the endpoint was nevertheless highly skewed, with 59.5% of participants achieving 90 home days, so trial conclusions depend on the full distribution rather than median differences.
• Guideline context:
  • The 2026 Surviving Sepsis Campaign guidelines address sepsis care across hospital, prehospital, and immediate post-hospital settings, but they were published before ACCOMPLISH and do not provide evidence that symptom-questionnaire remote monitoring reduces readmissions after serious infection. ¹¹
  • ACCOMPLISH should therefore inform future postsepsis-care guidance, particularly where reimbursement policy encourages broad remote-monitoring deployment.

Further Reading

• 2026Prescott HC, Antonelli M, Alhazzani W, et al. Surviving Sepsis Campaign: international guidelines for management of sepsis and septic shock 2026.
• 2025Mayes K, Talisa VB, Malito A, et al. Design and methods of the ACCOMPLISH trial.
• 2025Taylor SP, Eaton T, Rios A, et al. Proactive telehealth-based sepsis transition and recovery support.
• 2025Grady D, Durant RW, Anderson TS. What if readmission prevents death?
• 2025McPeake J, MacTavish P, Puxty K, et al. Patient and family member experience of hospital readmission following critical illness.
• 2025Hu C, Liao X, Fang Y, et al. Telehealth-supported home oxygen therapy in COPD.
• 2024Masotta V, Dante A, Caponnetto V, et al. Telehealth care and remote monitoring in heart failure.
• 2023Taran S, Coiffard B, Huszti E, et al. Days alive and at home after ICU admission.
• 2017Mayr FB, Talisa VB, Balakumar V, et al. Unplanned readmissions after sepsis compared with other medical conditions.
• 2016Schmidt K, Worrack S, Von Korff M, et al. Primary care management intervention among survivors of sepsis.
• 2016Groff AC, Colla CH, Lee TH. Days spent at home as a patient-centred goal and outcome.

Summary

• ACCOMPLISH randomised 1286 postdischarge adults recovering from sepsis, COVID-19, or lower respiratory tract infection to usual care or one of four symptom-based remote-monitoring strategies.
• No remote-monitoring strategy increased postdischarge home days at 90 days; median home days were 90 in every arm, and all posterior probabilities of superiority were below 55%.
• Remote monitoring did not reduce 90-day readmission: readmission occurred in 37.8% with usual care and 36.3% to 44.2% across RPM arms.
• In patients aged ≥65 years and those discharged via skilled nursing facilities, remote monitoring was associated with fewer home days and higher readmission rates.
• The trial supports careful targeting and redesign of remote monitoring rather than broad deployment after serious infection.

Overall Takeaway

ACCOMPLISH is a practice-shaping comparative-effectiveness trial because it challenges the assumption that remote monitoring after serious infection automatically reduces readmissions or improves home time. Its message is not that postdischarge sepsis care is unnecessary, but that symptom-questionnaire monitoring added to active telephone and primary-care support is insufficient as a universal strategy and may be counterproductive in older or skilled-nursing-facility transition populations.

Bibliography

• 1.Mayr FB, Talisa VB, Balakumar V, Chang CH, Fine M, Yende S. Proportion and cost of unplanned 30-day readmissions after sepsis compared with other medical conditions. JAMA. 2017;317(5):530-531.
• 2.McPeake J, MacTavish P, Puxty K, Crook C, Quasim T. Patient and family member experience of hospital readmission following critical illness. Intensive Crit Care Nurs. 2025;87:103890.
• 3.Masotta V, Dante A, Caponnetto V, et al. Telehealth care and remote monitoring strategies in heart failure patients: a systematic review and meta-analysis. Heart Lung. 2024;64:149-167.
• 4.Mayes K, Talisa VB, Malito A, et al. Design and methods of an adaptive trial to test comparative effectiveness of readmission reduction approaches following infection and sepsis hospitalizations (ACCOMPLISH). Contemp Clin Trials Commun. 2025;46:101504.
• 5.Hu C, Liao X, Fang Y, Zhu S, Lan X, Cheng G. Clinical and cost-effectiveness of telehealth-supported home oxygen therapy on adherence, hospital readmission, and health-related quality of life in patients with chronic obstructive pulmonary disease: systematic review and meta-analysis of randomized controlled trials. J Med Internet Res. 2025;27:e73010.
• 6.Grady D, Durant RW, Anderson TS. What if readmission prevents death? The challenge of composite outcomes. JAMA Intern Med. 2025;185(10):1246-1247.
• 7.Schmidt K, Worrack S, Von Korff M, et al; SMOOTH Study Group. Effect of a primary care management intervention on mental health-related quality of life among survivors of sepsis: a randomized clinical trial. JAMA. 2016;315(24):2703-2711.
• 8.Taylor SP, Eaton T, Rios A, et al. Proactive telehealth-based sepsis transition and recovery support, hospital readmission, and mortality: a randomized clinical trial. JAMA Intern Med. 2025;185(10):1238-1246.
• 9.Groff AC, Colla CH, Lee TH. Days spent at home—a patient-centered goal and outcome. N Engl J Med. 2016;375(17):1610-1612.
• 10.Taran S, Coiffard B, Huszti E, et al. Association of days alive and at home at day 90 after intensive care unit admission with long-term survival and functional status among mechanically ventilated patients. JAMA Netw Open. 2023;6(3):e233265.
• 11.Prescott HC, Antonelli M, Alhazzani W, et al. Surviving Sepsis Campaign: international guidelines for management of sepsis and septic shock 2026. Crit Care Med. 2026;54(4):725-812.