# Personalized Clinical Decision Support to Improve Participation in Hospital at Home

> **NIH AHRQ R21** · CAROLINAS MEDICAL CENTER · 2022 · $101,781

## Abstract

PROJECT SUMMARY
Inpatient hospitalization is costly – accounting for $1.1 trillion in health care spending annually in the United
States – and is associated with high morbidity and mortality risks. Hospital at Home (HaH) is an alternative
care model where care teams provide acute hospital-level care in a patient’s home. Despite decades of data
that support HaH efficacy relevant to key patient-centered outcomes, barriers to HaH participation limit its
widespread adoption and population health impact. Our central hypothesis is that providers and patients
require Clinical Decision Support (CDS) integrating data from disparate sources and a Shared Decision Making
(SDM) framework to help inform point-of-care decisions regarding HaH and surmount low participation rates.
The overarching goal of our work is to improve value-driven care by helping patients engage in the decision of
which acute-level care option best meets their needs. The objective of this study is to evaluate whether a
Health Information Technology (IT)-enabled SDM solution incorporating expected patient outcomes and
preferences and deployed at the point-of-care improves patient and provider participation in HaH as a care
model. To achieve this objective, we will: 1) characterize patient, caregiver, and provider perceptions of the risk
tradeoffs, needs, and care preferences for HaH; 2) partner with patients, caregivers, and providers to iteratively
design Hospital-level Outpatient Management Evaluation and Decision Support (HOME-DS), a Health IT-
enabled SDM solution that incorporates risk-model probabilities and patient and caregiver preferences; and 3)
evaluate the feasibility of implementing HOME-DS in acute care and establish the acceptance rate of HaH. We
will focus HOME-DS on adults aged 18 and older hospitalized with suspected pneumonia, a prevelant
condition that has been commonly included in HaH models. We will apply the previously validated and broadly
accepted Pneumonia Severity Index (PSI) as the quantitative risk score input for HOME-DS. User personas
and needs for the initial HOME-DS prototype will be defined through key informant interviews with patients
hospitalized with pneumonia, their caregivers, and providers (Aim1); user-centric design principles will further
guide iterative development of the HOME-DS prototype (Aim 2); and we will test the feasibility of implementing
HOME-DS in acute care to guide patient and caregiver decision making in selecting hospital level care in the
home or traditional hospital (Aim 3). We hypothesize HOME-DS is feasible to implement within the provider
workflow for hospital admission and can yield participation rates in HaH of 50%. The proposed project will
engage a heterogeneous population with pneumonia, as this is a population with substantial acute care
utilization costs and a large gap in understanding implementation challenges to explain why alternatives to
traditional hospitalization are not used more widely. Results will demonstrate...

## Key facts

- **NIH application ID:** 10428461
- **Project number:** 5R21HS027248-02
- **Recipient organization:** CAROLINAS MEDICAL CENTER
- **Principal Investigator:** Marc Kowalkowski
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** AHRQ
- **Fiscal year:** 2022
- **Award amount:** $101,781
- **Award type:** 5
- **Project period:** 2021-06-15 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10428461

## Citation

> US National Institutes of Health, RePORTER application 10428461, Personalized Clinical Decision Support to Improve Participation in Hospital at Home (5R21HS027248-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10428461. Licensed CC0.

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