The Hospital Readmissions Reduction Program and Observation Hospitalizations

Rationale and design of healthy at home for COPD: an integrated remote patient monitoring and virtual pulmonary rehabilitation pilot study

Chronic obstructive pulmonary disease (COPD) is a common, costly, and morbid condition. Pulmonary rehabilitation, close monitoring, and early intervention during acute exacerbations of symptoms represent a comprehensive approach to improve outcomes, but the optimal means of delivering these services is uncertain. Logistical, financial, and social barriers to providing healthcare through face-to-face encounters, paired with recent developments in technology, have stimulated interest in exploring alternative models of care. The Healthy at Home study seeks to determine the feasibility of a multimodal, digitally enhanced intervention provided to participants with COPD longitudinally over 6 months. This paper details the recruitment, methods, and analysis plan for the study, which is recruiting 100 participants in its pilot phase. Participants were provided with several integrated services including a smartwatch to track physiological data, a study app to track symptoms and study instruments, access to a mobile integrated health program for acute clinical needs, and a virtual comprehensive pulmonary support service. Participants shared physiologic, demographic, and symptom reports, electronic health records, and claims data with the study team, facilitating a better understanding of their symptoms and potential care needs longitudinally. The Healthy at Home study seeks to develop a comprehensive digital phenotype of COPD by tracking and responding to multiple indices of disease behavior and facilitating early and nuanced responses to changes in participants' health status. This study is registered at Clinicaltrials.gov (NCT06000696).

Outcomes and Cost-Effectiveness of an EHR-Embedded AI Screener for Identifying Hospitalized Adults at Risk for Opioid Use Disorder

Hospitalized adults with opioid use disorder (OUD) are at high risk for adverse events and rehospitalizations. This pre-post quasi-experimental study evaluated whether an AI-driven OUD screener embedded in the electronic health record (EHR) was non-inferior to usual care in identifying patients for Addiction Medicine consults, aiming to provide a similarly effective but more scalable alternative to human-led ad hoc consultations. The AI screener analyzed EHR notes in real-time with a convolutional neural network to identify patients at risk and recommend consultation. The primary outcome was the proportion of patients receiving consults, comparing a 16-month pre-intervention period to an 8-month post-intervention period with the AI screener. Consults did not change between periods (1.35% vs 1.51%, p < 0.001 for non-inferiority). The AI screener was associated with a reduction in 30-day readmissions (OR: 0.53, 95% CI: 0.30-0.91, p = 0.02) with an incremental cost of $6,801 per readmission avoided, demonstrating its potential as a scalable, cost-effective solution for OUD care. ClinicalTrials.gov ID : NCT05745480.

Rationale and Design of Healthy at Home for COPD: an Integrated Remote Patient Monitoring and Virtual Pulmonary Rehabilitation Pilot Study

Chronic Obstructive Pulmonary Disease (COPD) is a common, costly, and morbid condition. Pulmonary rehabilitation, close monitoring, and early intervention during acute exacerbations of symptoms represent a comprehensive approach to improve outcomes, but the optimal means of delivering these services is uncertain. Logistical, financial, and social barriers to providing healthcare through face-to-face encounters, paired with recent developments in technology, have stimulated interest in exploring alternative models of care. The Healthy at Home study seeks to determine the feasibility of a multimodal, digitally enhanced intervention provided to participants with COPD longitudinally over six months. This paper details the recruitment, methods, and analysis plan for the study, which is recruiting 100 participants in its pilot phase. Participants were provided with several integrated services including a smartwatch to track physiological data, a study app to track symptoms and study instruments, access to a mobile integrated health program for acute clinical needs, and a virtual comprehensive pulmonary support service. Participants shared physiologic, demographic, and symptom reports, electronic health records, and claims data with the study team, facilitating a better understanding of their symptoms and potential care needs longitudinally. The Healthy at Home study seeks to develop a comprehensive digital phenotype of COPD by tracking and responding to multiple indices of disease behavior and facilitating early and nuanced responses to changes in participants' health status. This study is registered at Clinicaltrials.gov (NCT06000696).

Programmatic quality measures: a new model to promote surgical quality

Health care performance metrics are offered predominantly in terms of outcomes, processes, or structural components of health care delivery. However, measurement is limited by variability in data sources, definitions, and workarounds. The American College of Surgeons has recently developed a new type of performance metric known as a "programmatic measure". These metrics align structures, processes, and outcomes to better coordinate quality measurement with support of frontline care teams. In this multifaceted way, these measures differ from current "single" measures such as targeting surgical site infection. The thematic focus of these measures and alignment of structure-resource components to support processes and outcomes also sets these measures apart from contemporary composite measures. Importantly, structural elements of these measures reflect minimum resources required for patient care, addressing staffing and resource barriers felt by local institutions in addressing numerous existing quality metrics. These metrics will streamline quality reporting to improve care navigation for patients. Clinicians will find more appropriately aligned goals and responsibilities, resulting in increased teamwork and communication. These measures are designed to address the current burdens of overabundant metrics, priority misalignment, and low resources in a patient-centric fashion to better align health care quality and measurement.

Drug-Related Problems in Elderly Patients Attended to by Emergency Services

The progressive aging and comorbidities of the population have led to an increase in the number of patients with polypharmacy attended to in the emergency department. Drug-related problems (DRPs) have become a major cause of admission to these units, as well as a high rate of short-term readmissions. Anticoagulants, antibiotics, antidiabetics, and opioids have been shown to be the most common drugs involved in this issue. Inappropriate polypharmacy has been pointed out as one of the major causes of these emergency visits. Different ways of conducting chronic medication reviews at discharge, primary care coordination, and phone contact with patients at discharge have been shown to reduce new hospitalizations and new emergency room visits due to DRPs, and they are key elements for improving the quality of care provided by emergency services.

Hospital Performance Under Alternative Readmission Measures Incorporating Observation Stays

OBJECTIVE

To determine the extent to which counting observation stays changes hospital performance on 30-day readmission measures.

METHODS

This was a retrospective study of inpatient admissions and observation stays among fee-for-service Medicare enrollees in 2017. We generated 3 specifications of 30-day risk-standardized readmissions measures: the hospital-wide readmission (HWR) measure utilized by the Centers for Medicare and Medicaid Services, which captures inpatient readmissions within 30 days of inpatient discharge; an expanded HWR measure, which captures any unplanned hospitalization (inpatient admission or observation stay) within 30 days of inpatient discharge; an all-hospitalization readmission (AHR) measure, which captures any unplanned hospitalization following any hospital discharge (observation stays are included in both the numerator and denominator of the measure). Estimated excess readmissions for hospitals were compared across the 3 measures. High performers were defined as those with a lower-than-expected number of readmissions whereas low performers had higher-than-expected or excess readmissions. Multivariable logistic regression identified hospital characteristics associated with worse performance under the measures that included observation stays.

RESULTS

Our sample had 2586 hospitals with 5,749,779 hospitalizations. Observation stays ranged from 0% to 41.7% of total hospitalizations. Mean (SD) readmission rates were 16.6% (5.4) for the HWR, 18.5% (5.7) for the expanded HWR, and 17.9% (5.7) in the all-hospitalization readmission measure. Approximately 1 in 7 hospitals (14.9%) would switch from being classified as a high performer to a low performer or vice-versa if observation stays were fully included in the calculation of readmission rates. Safety-net hospitals and those with a higher propensity to use observation would perform significantly worse.

CONCLUSIONS

Fully incorporating observation stays in readmission measures would substantially change performance in value-based programs for safety-net hospitals and hospitals with high rates of observation stays.

Medicare's hospital readmissions reduction program and the rise in observation stays

OBJECTIVE

To evaluate whether Medicare's Hospital Readmissions Reduction Program (HRRP) is associated with increased observation stay use.

DATA SOURCES AND STUDY SETTING

A nationally representative sample of fee-for-service Medicare claims, January 2009-September 2016.

STUDY DESIGN

Using a difference-in-difference (DID) design, we modeled changes in observation stays as a proportion of total hospitalizations, separately comparing the initial (acute myocardial infarction, pneumonia, heart failure) and subsequent (chronic obstructive pulmonary disease) target conditions with a control group of nontarget conditions. Each model used 3 time periods: baseline (15 months before program announcement), an intervening period between announcement and implementation, and a 2-year post-implementation period, with specific dates defined by HRRP policies.

DATA COLLECTION/EXTRACTION METHODS

We derived a 20% random sample of all hospitalizations for beneficiaries continuously enrolled for 12 months before hospitalization (N = 7,162,189).

PRINCIPAL FINDINGS

Observation stays increased similarly for the initial HRRP target and nontarget conditions in the intervening period (0.01% points per month [95% CI -0.01, 0.3]). Post-implementation, observation stays increased significantly more for target versus nontarget conditions, but the difference is quite small (0.02% points per month [95% CI 0.002, 0.04]). Results for the COPD analysis were statistically insignificant in both policy periods.

CONCLUSIONS

The increase in observation stays is likely due to other factors, including audit activity and clinical advances.

Traditional Medicare Spending on Inpatient Episodes as Hospitalizations Decline

OBJECTIVE

To describe Medicare inpatient episode spending trends between 2009 and 2017 as inpatient use declined among traditional Medicare beneficiaries.

METHODS

Inpatient episodes included claims for all traditional Medicare inpatient, outpatient, and Part D services provided during the 30 days prehospitalization, the inpatient stay, and the 90 subsequent days. We describe the mean number of episodes per 1000 beneficiaries, mean episode-related spending per beneficiary, and mean spending per episode for all beneficiaries and for specific populations and types of episodes. Spending measures are reported with and without adjustment for payment rate increases over the study period.

RESULTS

The number of inpatient-initiated episodes per 1000 beneficiaries declined by 18.2% between 2009 and 2017 from 326 to 267. After adjusting for payment rate increases, Medicare spending per beneficiary on episode- related care declined by 8.9%, although spending per episode increased by 11.4% over this period. Between 2009 and 2017, all subgroups defined by age, sex, race, or Medicaid status experienced declines in inpatient use accompanied by decreased overall episode-related spending per beneficiary and increased spending per episode. Larger declines in the number of episodes per 1000 beneficiaries were seen among episodes that began with a planned admission (28.8%) or involved no use of post-acute care services (23.9%). When comparing admissions according to medical diagnosis, the largest decline occurred for episodes initiated by a hospitalization for a cardiac or circulatory condition (31.8%).

CONCLUSION

Medicare inpatient episodes per beneficiary decreased, but spending decreases due to declining volume were offset by increased spending per episode.