Infection Prevention in Home Health Care (InHOME)

This study has the potential to make clinical and policy-relevant contributions by promoting infection prevention and control in-home health care (HHC) and reducing infection risk for the millions of Americans using HHC services.

This study is conducted by the Columbia University School of Nursing in partnership with the RAND Corporation and Thomas Jefferson University and has been approved by an IRB at all three institutions.

It is funded by NIH’s National Institute Of Nursing Research (NINR) & Office of the Director (OD) (R01NR016865), the National Institute on Aging (3R01NR016865-03S1) and the Alliance for Home Health Quality and Innovation (AHHQI).

Background

Defined as health care provided to persons in their own home, the home health care (HHC) sector is one of the most important health care services in the nation with increasingly complex care being provided.1 Over 4.9 million patients received care from 12,400 HHC agencies between 2013-2014,2 and most HHC patients (83%) are elderly.3

Many older patients at risk for infections are receiving HHC services. More recently, infection outbreaks among HHC patients have captured national attention, and new infections are emerging.4-9 In 2014, because of the importance of infection prevention, the Centers for Medicare and Medicaid Services (CMS) issued a memo to HHC surveyors outlining infection control breaches that should be reported to state Departments of Health.10 The Joint Commission has also identified infection prevention and control as a national patient safety goal for HHC.11 Furthermore, in 2017, the Home Health Conditions of Participation (CoPs) were significantly revised by the Centers for Medicare and Medicaid Services (CMS) with a focus on quality improvement. However, even with increased attention, little is known about infections occurring while patients are enrolled in HHC and how best to mitigate infection risk for these vulnerable patients.12

In a recent systematic review, we found that infection rates in HHC varied dramatically (range 5% to 80%) based on the type of infection studied and the patient populations included.12,13 We also found that most researchers focused on patients receiving parenteral nutrition treatment. Furthermore, no researchers estimated the long-term health outcomes and health care utilization associated with infections that occur while patients receive HHC services.

In subsequent pilot work (R03 NR013966), using 2010 national Outcome and Assessment Information Set (OASIS) data, we found infections to be a common reason for unplanned hospitalizations among HHC patients.3 However, OASIS data are limited and likely underestimate the true infection rate. We also found agency-level infection rates varied greatly across the country. The variation across agencies may indicate that recommended guidelines are not being adopted and/or that there are limitations in the guidelines themselves.

Main Study Goals

Informed by our systematic review, pilot work, and Andersen’s Behavioral Model for Vulnerable Populations14, we will use the most current (2013-2015) administrative data (e.g., OASIS and Medicare claims) from 3,333 randomly sampled HHC agencies to describe the incidence of infections that occur while patients are receiving HHC and the relationship with patients’ predisposing, enabling, and need characteristics.

We will complement our secondary data analyses with a national survey of HHC agencies (expected sample n = 1,333), and qualitative data from interviews with up to 80 HHC staff across the nation to better understand current infection prevention and control infrastructure and policies in HHC agencies. We will also link our survey data with the most current patient (n = 133,300) and agency-level (n = 1,333) data to compare the effectiveness of various infection prevention and control infrastructures and policies in preventing infections in HHC. Finally, we will use longitudinal data (2013-2017) on up to one million patients to conduct econometric analyses; the analyses will estimate survival and health care utilization associated with infections in HHC patients.

Main Study Aims

  1. Describe the incidence of infections that occur while patients are receiving HHC and the relationship with patients’ predisposing, enabling, and need characteristics.
  2. Describe the current infection prevention and control infrastructure and policies in HHC agencies.
  3. Compare the effectiveness of various infection prevention and control infrastructures and policies in preventing infections in HHC.
  4. Estimate survival and health care utilization associated with infections in HHC patients.

Focus on Alzheimer's Disease

Advanced illness due to Alzheimer’s disease and its related dementias (AD/ADRD) is a growing problem in HHC patients. Unless another fatal illness intervenes, all patients with AD/ADRD will reach the advanced stages of this disease. Furthermore, suspected infectious episodes are hallmarks of advanced illness in AD/ADRD. Limited research has demonstrated extensive antibiotic use and transfers to hospitals among patients with advanced AD/ADRD, both of which are often burdensome, result in limited to no symptom relief and/or survival benefit, and incur high costs. A supplemental grant will allow us to develop measures for advanced illness using administrative data from HHC AD/ADRD patients, and to examine how best to care for this growing population.

Sub-Study Goals

Leveraging analytical data sets, research infrastructure and personnel from the InHOME project and guided by the Andersen Behavioral Model for Vulnerable Populations and the Positive Deviance Approach,14,15 we will determine how HHC agencies are responding to the changing regulatory landscape and identify best practices. To achieve this, we will 1) interview HHC personnel across the nation about VBP and quality improvement initiatives in the home health environment, 2) conduct a national survey of HHC agencies, and 3) conduct multivariate analyses using a combined dataset of survey, OASIS, Medicare, Census, and AHRF data.

Sub-Study Aims

  1. Explore how HHC agencies have responded to various quality and VBP initiatives.
  2. Conduct a survey to describe agency QAPI programs and identify the types of HHC agencies that respond to VBP incentives.
  3. Identify best practices by examining factors associated with HHC outcomes (e.g., emergency services, hospital admission, and readmission rates)

References

  1. Thome B, Dykes AK, Hallberg IR. Home care with regard to definition, care recipients, content and outcome: systematic literature review. J Clinical Nursing. 2003;12(6):860-872.
  2. Harris-Kojetin L, Sengupta M, Park-Lee E, al. e. Long-term care providers and services users in the United States: Data from the National Study of Long-Term Care Providers, 2013–2014. Vol 3. VitalHealth Stat National Center for Health Statistics; 2016.
  3. Shang J, Larson E, Liu J, Stone P. Infection in home health care: Results from national Outcome and Assessment Information Set data. Am J Infect Control. 2015;43(5):454-459.
  4. Danzig LE, Short LJ, Collins K, et al. Bloodstream infections associated with a needleless intravenous infusion system in patients receiving home infusion therapy. J Am Med Assoc. 1995;273(23):1862-1864.
  5. Do AN, Ray BJ, Banerjee SN, et al. Bloodstream infection associated with needleless device use and the importance of infection-control practices in the home health care setting. J Infect Dis.1999;179(2):442-448.
  6. Kellerman S, Shay DK, Howard J, et al. Bloodstream infections in home infusion patients: the influence of race and needleless intravascular access devices. J Pediatr. 1996;129(5):711-717.
  7. Anderson TC, Marsden-Haug N, Morris JF, et al. Multistate Outbreak of Human Salmonella Typhimurium Infections Linked to Pet Hedgehogs - United States, 2011-2013. Zoonoses Pub Health. 2016.
  8. Niederman MS, Zumla A. Understanding community-acquired respiratory tract infections: new concepts of disease pathogenesis and new management strategies. Curr Opin Pulm Med. 2016;22(3):193-195.
  9. Zumla A, Goodfellow I, Kasolo F, et al. Zika virus outbreak and the case for building effective and sustainable rapid diagnostics laboratory capacity globally. Int J Infect Dis. 2016;45:92-94.
  10. Centers for Medicare & Medicaid Services. Memorandum: Infection Control Breaches Which Warrant Referral to Public Health Authorities. 2014; Accessed February 23, 2016.
  11. The Joint Commission Accreditation of Healthcare Organizations. 2015 Home Care National Patient Safety Goals. 2015; Accessed February 20, 2016.
  12. Shang J, Ma C, Poghosyan L, Dowding D, Stone P. The prevalence of infections and patient risk factors in home health care: A systematic review. Am J Infect Control. 2014;42(5):479-484.
  13. Shang J, Liu J. Infections and risk factors among Home Health Care Patients. AcademyHealth Annual Research Meeting; 2014; San Diego, CA.
  14. Gelberg L, Andersen RM, Leake BD. The Behavioral Model for Vulnerable Populations: application to medical care use and outcomes for homeless people. Health Services Research. 2000;34(6):1273-1302.
  15. Marsh DR, Schroeder DG, Dearden KA, Sternin J, Sternin M. The power of positive deviance. BMJ. 2004;329(7475):1177-1179.
Columbia School of Nursing
RAND Corporation
Jefferson: Thomas Jefferson University, Home of Sidney Kimmel Medical College