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Evaluation of a Hospital-in-Home Program Implemented Among Veterans
Shubing Cai, PhD; Patricia A. Laurel, MD; Rajesh Makineni, MS; Mary Lou Marks, RN; Bruce Kinosian, MD; Ciaran S. Phibbs, PhD; and Orna Intrator, PhD
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Evaluation of a Hospital-in-Home Program Implemented Among Veterans

Shubing Cai, PhD; Patricia A. Laurel, MD; Rajesh Makineni, MS; Mary Lou Marks, RN; Bruce Kinosian, MD; Ciaran S. Phibbs, PhD; and Orna Intrator, PhD
The Hospital-in-Home program implemented at the Veterans Affairs Pacific Islands Health Care System in Honolulu, Hawaii, is associated with reduced costs with no compromise in quality.

Objectives: To examine the outcomes (ie, costs, hospitalizations, and mortality) associated with a Hospital-in-Home (HIH) program implemented in 2010 by the Veterans Affairs (VA) Pacific Islands Healthcare System in Honolulu, Hawaii.

Study Design: Retrospective cohort study.

Methods: We obtained medical information for veterans who were enrolled in the HIH program in Honolulu, Hawaii, between 2010 and 2013. For purposes of comparison, we also gathered VA data to identify a cohort of hospitalized veterans in Honolulu who were eligible for, but not enrolled in, the HIH program. Using VA administrative data, we extracted a set of individual-level variables at baseline to account for the differences between program enrollees and comparators. In total, 99 HIH program enrollees and 322 unenrolled veterans were included. We identified 3 sets of outcome variables: total costs of care related to the index event (ie, HIH services for enrollees and hospitalizations for comparators), hospitalizations, and mortality after discharge from the index event. We used a propensity score-matching approach to examine the difference in related outcomes between enrollees and comparators.

Results: The average medical cost was $5150 per person for veterans receiving HIH services, and $8339 per person for veterans receiving traditional inpatient services. The difference was statistically significant (P <.01). There was no statistically significant difference in mortality or hospitalization rates after the index event.

Conclusions: This study provides evidence of the potential benefits of a model that delivers acute care in patients’ homes. Considering the emergence of accountable healthcare organizations, interest in broader implementation of such programs may be worthy of investigation.

Am J Manag Care. 2017;23(8):482-487
Takeaway Points

We evaluated a Hospital-in-Home (HIH) program implemented in Honolulu, Hawaii. Using Veterans Affairs administrative data and a propensity score-matching approach, this study provided further confirmation of the potential benefits of this new care delivery model.
  • The costs of HIH services were 38% less than that of comparable inpatient hospitalizations. 
  • There were no statistically significant differences in postdischarge hospitalization rates or mortality between HIH enrollees compared with veterans who were not enrolled in the program.
  • With the reform of Medicare payment models and the emergence of accountable care organizations, there may be more interest in implementing HIH programs.
The hospital is the traditional place to provide acute care. However, hospitalizations can be costly and may lead to further deterioration in health status among the elderly.1-4 The Hospital-in-Home (HIH) model offers an alternative approach to traditional hospital services.5-8 At the core of the HIH model is the goal of delivering hospital-level care to patients who have developed an acute episode that typically would require inpatient services, but who are medically stable enough to be treated at home.7-9 The common conditions that have been managed through HIH include congestive heart failure, chronic obstructive pulmonary disease, community-acquired pneumonia, and cellulitis.7,8,10-13 The HIH model has been associated with superior patient outcomes, such as reduced risks of delirium, improved functional status, improved satisfaction among patients and their family members, reduced mortality, reduced readmissions, and significantly lower costs.5,6,12,14-22 These studies vary in research design (eg, randomized trial or observational studies), study populations (eg, patients with different conditions in a variety of healthcare settings), and contrasting study methods and study outcomes. 

Despite promising findings, however, the HIH model has not been widely implemented in the United States. One of the barriers to the adoption of this model is the misalignment of financial incentives among patients, payers, and providers under the traditional fee-for-service payment system.7 Such disincentives may not be applicable to integrated healthcare delivery systems that are responsible for discrepancies in the costs and care of defined populations, such as managed care, accountable care, and the Veterans Health Administration (VHA) healthcare systems.7

The Veterans Affairs (VA) health system is America’s largest integrated healthcare system. Its highly integrated medical delivery system aligns both financial incentives and quality care delivery, and thus is motivated to promote an HIH model. In 2010, the VA Office of Geriatrics and Extended Care (GEC) community-based transformational (T-21) programs piloted the HIH model as an alternative to inpatient services. One of the HIH programs was implemented at the VA Pacific Islands Health Care System (VAPIHCS) in Honolulu, Hawaii. This program is unique in that it does not have its own acute care hospital, and instead relies on the Tripler Army Medical Center (TAMC) in Honolulu, to provide inpatient care to its veterans. A steady flow of resources is transferred from the VA to the Department of Defense to reimburse the Army as veterans receive inpatient care from the TAMC, making the financial incentive for the implementation of the HIH program apparent at the VAPIHCS. The aim of our study was to evaluate the costs and related outcomes of this program. It was conducted as an operationally requested quality improvement project that was exempt from Institutional Resource Board review. Approval to publish these results was obtained from the GEC. 


The Honolulu HIH Program

When the VAPIHCS implemented the HIH program in September of 2010, the main targeted conditions included heart failure, pneumonia, chronic obstructive pulmonary disease, and cellulitis. To recruit patients, the HIH program staff made repeated and frequent visits to the TAMC and the VA Ambulatory Care Center in Honolulu. The HIH staff communicated with hospitalists, medical residents, discharge planners, and social workers at the TAMC, as well as VHA providers, nurses, and other staff at the facility, and maintained a close working relationship with a home-based primary care (HBPC) facility whose staff would refer eligible patients. A pamphlet was developed with basic information regarding the HIH program and outlining the patient referral process. 

One of the components of the Honolulu HIH program was the substitutive model (ie, it provided hospital-equivalent care in the veteran’s home for those who would have otherwise been hospitalized). The requirement to enroll in the program was that the veteran was living at home and had 1 of the required admitting diagnoses. Veterans were referred to the HIH program from outpatient clinics and the VA HBPC, and were screened by physicians or registered nurses for appropriate diagnoses to ensure that care could be safely provided in the home. Once admitted to the program, veterans received required intravenous (IV) infusions, respiratory treatments, laboratory tests, x-rays, and wound care in the home. They also received daily nursing and physician visits, as needed, and had 24-hour access to an on-call geriatrician. Although no specific age limit was imposed in this study, the HIH program is listed under geriatrics service, and all of the physicians covering HIH are geriatric-trained physicians. 

HIH staff ordered and delivered required supplies and medications, scheduled medical transportation, and coordinated care to meet the medical needs of veterans, their families, and caregivers. The HIH nursing staff took calls during duty hours on weekends and holidays, and worked with an outside pharmacy to provide all needed IV medications. Veterans were discharged from the program once symptoms improved; ultimately, they transitioned to their usual primary care providers (PCPs) or HBPC, if necessary. A discharge summary was placed in the Computerized Patient Record System, the patient’s Patient Aligned Care Team was notified, and follow-up care appointments were made with the PCP.

Data source. To evaluate the program, we (the GEC Data Analyses Center) followed specific steps. First, basic information was requested from the HIH program director to identify veterans who received care through this program. Social security number (SSN), date of birth, and gender were used to obtain the veteran’s identifier number (ie, scrambled SSN) used in the VA data systems. Dates of HIH program enrollment and disenrollment were also used to define the “active” period within the program and to establish both the program pre-enrollment phase prior to the trial, and the follow-up period following the program’s completion. 

Data were then obtained from multiple VA administrative sources via the VA’s Corporate Data Warehouse. Specifically, data included vital status file, enrollment file, patient file, patient treatment file, outpatient file, Ward file, pharmacy file, inpatient treating specialty file, and fee-basis file from January 1, 2007, to September 30, 2013. These files contained demographic information (ie, age, gender, and race), VA enrollment status, and information about VA-provided services or VA-paid services, including the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes, dates of service, medication use, and the costs of VA-provided and VA-purchased services. These VA data were linked by individually scrambled SSNs and compiled chronologically into a single file to track veterans’ utilization of health services.

Study Populations

The study population included HIH enrollees who were admitted to the Honolulu HIH program from a noninstitutional location (eg, outpatient clinics or home) between September 2010 and June 2013, and they were compared with a group of veterans who were not enrolled in the program, but were comparable to the enrollees.  To identity potential comparators for the study, we used administrative data to include veterans who were not enrolled in the HIH program, but who were admitted to the TAMC for inpatient services from a noninstitutional location between January 2008 and September 2012 in Honolulu, Hawaii. We did not include nonenrollee veterans who had hospitalizations in fiscal year 2013 (FY13) as controls due to the concern of potential bias. Because of the expansion of the program, it is likely that the program enrolled most of the eligible veterans in FY13. Thus, those who were not enrolled during the same time period could be quite different from those who were enrolled. We then identified the primary diagnosis associated with hospital admissions and selected patients whose primary diagnosis was among the set of admission conditions stipulated for HIH enrollees. Furthermore, we identified the diagnosis-related group (DRG) and identified select hospital admissions with low-weight medical DRGs, with the assumption that the HIH enrollees did not have complications. This resulted in the 99 program enrollees and 322 nonenrolled veteran comparators who were identified for the study


Three sets of outcome variables were evaluated. The first outcome was the total cost of care, including inpatient, outpatient, or pharmacy costs, incurred during the index event. These services were either provided by the VA (ie, DSS data) or paid for by the VA (ie, TAMC-provided inpatient services were captured on fee-for-service files). The duration of the index event referred to the time between the admission and discharge dates of HIH services for enrollees and hospitalizations for nonenrollees. Costs were adjusted to 2013 dollars by the Consumer Price Index. The second set of outcomes included the incidence of 30- and 90-day hospitalizations after the discharge of the index event. The third set of outcomes entailed 30-, 90-, and 180-day mortality after the veteran had been discharged from the index event.

Based on VA administrative data, we extracted a set of individual-level variables at baseline (ie, the admission of the index event) to account for the potential differences between program enrollees and comparators. These variables included individual sociodemographic characteristics (eg, age, gender, race, and VA priority status that determined eligibility for Priority group 1 [veterans with 50% or more service-connected disabilities that precluded employment]), prior VA healthcare utilization (eg, number of inpatient events and total VA-paid costs in the 3, 6, and 12 months prior to the index event). In addition, we utilized VA claims data to obtain the ICD-9-CM codes recorded within the 1-year period prior to the admission of the index event, and identified a set of chronic conditions for each veteran. We also calculated the number of different drug classes used by the veterans within 1 year prior to the index event. We categorized the number of drug classes into 3 groups, including fewer than 5 drug classes (lower 25th percentile), 5 to 10 drug classes, and more than 10 drug classes (upper 25th percentile), to allow for the potential nonlinear relationship between the number of drug classes and outcomes. These individual-level characteristics could be correlated with the outcomes and, thus, the differences in each factor between enrollees and other subjects were considered.

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