Student Name
Chamberlain University
NR-706: Healthcare Informatics & Information Systems
Prof. Name:
Date
Does frequent rounding and close monitoring of newly admitted patients in a post-acute care setting, as compared to current guideline recommendations, reduce hospital readmission rates over a period of eight weeks?
The PICOT framework is widely used in nursing research and clinical practice to clearly define practice problems and establish measurable, evidence-based solutions.
| Element | Description |
|---|---|
| P (Population) | Older adults admitted to post-acute care facilities |
| I (Intervention) | Frequent rounding, continuous monitoring, and regular clinician assessments |
| C (Comparison) | Standard practice guidelines currently followed |
| O (Outcome) | Lower hospital readmission rates |
| T (Timeframe) | Eight weeks |
This systematic approach provides a foundation to examine whether increased surveillance and early interventions can reduce avoidable rehospitalizations in vulnerable patient populations.
Hospital readmissions in post-acute care patients continue to pose clinical and financial challenges. Research indicates that rehospitalizations account for nearly $40 billion annually, with an estimated 5–79% being preventable (Harris et al., 2018). Even a modest reduction of 10% could save healthcare systems more than $1 billion per year.
The impact of frequent readmissions extends beyond economic consequences. Patients face higher risks of infection, delayed recovery, and a diminished quality of life. Moreover, rehospitalizations can result in loss of independence, functional decline, and increased caregiver burden. These outcomes underscore the importance of preventive strategies such as frequent rounding and close patient monitoring (Harris et al., 2018).
Does consistent rounding and clinician oversight reduce hospital readmissions compared to guideline-based practices over eight weeks for recently discharged post-acute patients?
Key interventions include:
Comprehensive patient assessments conducted regularly by nurses and physicians.
Early detection of complications before escalation.
Evaluation of the effectiveness of frequent rounding versus existing practice guidelines.
Measurement of rehospitalization rates over an eight-week period (March & Mennella, 2018).
The Centers for Medicare & Medicaid Services (CMS, 2019) developed measures to evaluate outcomes related to hospital readmissions from post-acute settings. These measures help balance cost-effectiveness with patient-centered care.
| Measure | Key Focus |
|---|---|
| Unplanned rehospitalization within 31 days | Identifies unnecessary readmissions soon after discharge |
| Medical necessity vs. 30-day rounding | Compares adequacy of guideline-based monitoring to more frequent assessments |
| National average rehospitalization (27%) | Serves as a benchmark for evaluating facility performance |
| Patient-centered care | Promotes individualized, holistic treatment |
| Insurance coverage inclusion | Ensures equitable access for all patient groups |
These measures provide benchmarks to guide healthcare organizations in reducing avoidable readmissions while maintaining safety and quality of care.
The Hospital Readmission Reduction Program (HRRP) identifies six major conditions where standardized 30-day readmission risk management is required (HatipoÄŸlu et al., 2018):
Acute Myocardial Infarction (AMI)
Congestive Heart Failure (CHF)
Pneumonia
Coronary Artery Bypass Graft (CABG)
Chronic Obstructive Pulmonary Disease (COPD)
Elective Total Hip or Knee Arthroplasty
By targeting these conditions, HRRP creates financial incentives for hospitals to implement strategies that reduce unnecessary readmissions, ultimately improving patient outcomes.
A sustainable reduction in rehospitalizations requires a collaborative, patient-centered approach that emphasizes prevention and timely interventions. Key aspects of this model include:
Empowering patients and providers with evidence-based tools for decision-making.
Allowing state and local organizations flexibility in implementing care strategies.
Supporting innovative practices that improve affordability and accessibility.
Prioritizing early intervention to prevent complications and improve long-term outcomes.
This approach ensures that post-acute care not only reduces readmissions but also enhances overall patient well-being.
FMEA is a structured method for identifying potential causes of failure in care processes that may contribute to hospital readmissions.
| Failure Mode | Failure Cause | Potential Effect |
|---|---|---|
| Missed handoff reports | Poor communication during transition of care | Delayed treatment or overlooked issues |
| Delayed assessment post-admission | Providers unaware of patient transfer or admission | Higher likelihood of hospitalization |
| Low rounding frequency | Missed early signs of complications | Increased risk of readmissions |
These failure points emphasize the need for improved handoff communication, timely assessments, and consistent provider presence (Harris et al., 2018).
Factors contributing to higher readmission rates include (LUCA, 2016; March & Mennella, 2018):
Medical staff variability: Differences in physician and nurse practitioner follow-up care.
Skilled nursing facilities: Inconsistent rounding schedules.
Electronic health record (EHR) challenges: Platforms like PointClickCare and Gherimed may miss critical alerts.
Monitoring gaps: Inadequate surveillance and lack of standardized assessment protocols.
Identifying these root causes provides opportunities for targeted quality improvement interventions.
Frequent provider rounding and close monitoring in post-acute care facilities have the potential to:
Detect patient deterioration earlier and enable timely intervention.
Lower preventable readmission rates.
Enhance patient outcomes and improve quality of life.
Shorten rehabilitation timeframes, promoting faster return to community living.
Evidence strongly supports proactive monitoring and structured interventions as cost-effective and patient-centered approaches that benefit patients, providers, and healthcare systems alike (UpToDate, 2019; Agarwal & Werner, 2018).
Agarwal, D., & Werner, R. M. (2018). Effect of hospital and post-acute care provider participation in accountable care organizations on patient outcomes and Medicare spending. Health Services Research, 53(6), 5035–5056. https://doi.org/10.1111/1475-6773.13023
Centers for Medicare & Medicaid Services. (2019). Skilled Nursing Facility 30-Day Potential Preventable Readmission Measure (SNFPPR). https://cmit.cms.gov/CMIT_public/ViewMeasure?MeasureId=2801
Harris, C., Garrubba, M., Melder, A., Voutier, C., Waller, C., King, R., & Ramsey, W. (2018). Sustainability in health care by allocating resources effectively (SHARE) 8: Developing, implementing and evaluating an evidence dissemination service in a local healthcare setting. BMC Health Services Research, 18(1), 151. https://doi.org/10.1186/s12913-018-2961-8
Hatipoğlu, U., Wells, B. J., Chagin, K., Joshi, D., Milinovich, A., & Rothberg, M. B. (2018). Predicting 30-day all-cause readmission risk for subjects admitted with pneumonia at the point of care. Respiratory Care, 63(1), 43–49. https://doi.org/10.4187/respcare.05719
LUCA, L. (2016). A study on quality analysis measuring process. Fiability & Durability, 2, 68–72.
March, P. P., & Mennella, H. D. A.-B. (2018). Quality improvement in long-term care. CINAHL Nursing Guide.
UpToDate. (2019). Hospital discharge and readmission. https://www.uptodate.com/contents/hospital-discharge-and-readmission
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