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The American Journal of Managed Care October 2015
Scalable Hospital at Home With Virtual Physician Visits: Pilot Study
Wm. Thomas Summerfelt, PhD; Suela Sulo, PhD; Adriane Robinson, RN; David Chess, MD; and Kate Catanzano, ACNP-BC
Health Coaching by Medical Assistants Improves Patients' Chronic Care Experience
David H. Thom, MD, PhD, MPH; Danielle Hessler, PhD; Rachel Willard-Grace, MPH; Denise DeVore, BA; Camille Prado, BA; Thomas Bodenheimer, MD, MPH; and Ellen H. Chen, MD
The Path to Value Through the Use of Holistic Care
Roy A. Beveridge, MD, Chief Medical Officer, Humana
Delivering Value by Focusing on Patient Experience
Paula Chatterjee, MD, MPH; Thomas C. Tsai, MD, MPH; and Ashish K. Jha, MD, MPH
Medication Adherence and Healthcare Disparities: Impact of Statin Co-Payment Reduction
Jennifer Lewey, MD; William H. Shrank, MD, MSHS; Jerry Avorn, MD; Jun Liu, MD, MPH; and Niteesh K. Choudhry, MD, PhD
Integrated Medicare and Medicaid Managed Care and Rehospitalization of Dual Eligibles
Hye-Young Jung, PhD; Amal N. Trivedi, MD, MPH; David C. Grabowski, PhD; and Vincent Mor, PhD
Solutions for Filling Gaps in Accountable Care Measure Sets
Tom Valuck, MD, JD, MHSA; Donna Dugan, PhD, MS; Robert W. Dubois, MD, PhD; Kimberly Westrich, MA; Jerry Penso, MD, MBA; and Mark McClellan, MD, PhD
The Impact of Kaua'i Care Transition Intervention on Hospital Readmission Rates
Fenfang Li, PhD; Jing Guo, PhD; Audrey Suga-Nakagawa, MPH; Ludvina K. Takahashi, BA; and June Renaud, BEd
Currently Reading
Are Chronically Ill Patients High Users of Homecare Services in Canada?
Donna M. Wilson, PhD, RN; Corrine D. Truman, PhD, RN; Jessica A. Hewitt, BScKin; and Charl Els, MBChB, FCPsych, MMedPsych, ABAM, MROCC
Antibiotic Use for Viral Acute Respiratory Tract Infections Remains Common
Mark H. Ebell, MD, MS; and Taylor Radke, MPH
Clinician Considerations When Selecting High-Risk Patients for Care Management
Vivian Haime, BS; Clemens Hong, MD, MPH; Laura Mandel, BA; Namita Mohta, MD; Lisa I. Iezzoni, MD, MSc; Timothy G. Ferris, MD, MPH; and Christine Vogeli, PhD
"Meaningful" Clinical Quality Measures for Primary Care Physicians
Cara B. Litvin, MD, MS; Steven M. Ornstein, MD; Andrea M. Wessell, PharmD; and Lynne S. Nemeth, RN, PhD

Are Chronically Ill Patients High Users of Homecare Services in Canada?

Donna M. Wilson, PhD, RN; Corrine D. Truman, PhD, RN; Jessica A. Hewitt, BScKin; and Charl Els, MBChB, FCPsych, MMedPsych, ABAM, MROCC
Assessments of self-care capacity and other measures were the most precise ways to identify individuals who could be classified as chronically ill, in their status as the highest users, both individually and collectively, of homecare services.
ABSTRACT

Objectives: Chronically ill patients often need healthcare and supportive services, with formal homecare services an important source of community-based assistance. Although people diagnosed with 1 or more chronic diseases are thought to be the most common homecare clients, and perhaps the highest users of homecare services, few studies have analyzed homecare services utilization by specific clients. A study was done to determine if a relationship exists between chronic illness and homecare services utilization.

Study Design: Descriptive-comparative, secondary analysis of population homecare data.

Methods: Three years (2003-2004, 2004-2005, and 2005-2006) of complete homecare client and services utilization data for 1 Canadian province were obtained and tested using 5 definitions of chronic illness to determine which clients among all 149,378 were high users in terms of annual homecare hours and service visits or episodes.

Results: Two definitions revealed clients with a disproportionately large share of homecare hours and service episodes: a) clients classified by homecare case managers as “long-term” and b) clients with service spans of ≥90 days. Definitions involving medical diagnoses and International Classification of Diseases, Ninth Revision, Clinical Modification codes or chapters did not reveal high users. Age and gender also did not predict services utilization.

Conclusions: The comprehensive pre-service assessment completed by homecare case managers was the most successful at distinguishing people with substantial homecare service needs—people who could then be described as chronically ill. This assessment should be studied to develop a standardized minimum data tool for consistent and fair assessments.

Am J Manag Care. 2015;21(10):e552-e559
Take-Away Points
 
Chronically ill patients are thought to be high users of homecare services. 
  • Few studies have distinguished high users of homecare services. 
  • There is no standard definition of chronic illness. 
  • This study found that homecare clients classified with long-term service needs used the most homecare services, as did those who received homecare services for spans of 90 days or more.
Most people have been diagnosed with at least 1 chronic disease by age 65.1-6 Those with chronic disease often need healthcare and supportive services, and although much care of the chronically ill can be provided in the home by family members, formal homecare services are an important potential source of assistance for maintaining health and well-being.7-13 Further, homecare services can also reduce hospital utilization and delay or prevent nursing home entry.14-19

For 3 decades, every Canadian province has provided publicly funded homecare services to maintain the health of chronically ill and frail elderly individuals, to attempt to prevent serious illnesses, which would require hospitalization.12 Increasingly, homecare services in Canada are being provided to facilitate early discharge of hospital patients, to prevent or delay nursing home entry, and for home-based death and dying.12 Despite having no length-of-care or care acuity restrictions, only a small proportion of total provincial healthcare system funding is devoted to homecare services (typically 5% or less in each province).12 Canadian homecare managers are thus charged with careful client selection and efficient service provision.

With an increase in chronic illnesses anticipated with population aging,20 planning ahead for homecare services expansion is important. This expansion should be evidence-based to ensure that the people most in need receive homecare services. Although individuals diagnosed with 1 or more chronic illnesses may be the most likely homecare clients and/or the highest users of homecare services, few studies have differentiated homecare services use among homecare clients.12 A research study was done in the Canadian province of Alberta to determine if a relationship exists between chronic illness and homecare services utilization.

STUDY DESIGN AND METHODS
Any health condition that lasts 3 months or more can be considered a chronic illness.20 Chronic illnesses are incurable or long term. The World Health Organization has named cardiovascular accident (stroke), cancer, chronic obstructive pulmonary disease (COPD), and diabetes as the most prevalent chronic illnesses worldwide.20 Every disease is distinguished by an International Classification of Diseases diagnostic code, in keeping with the Ninth Revision, Clinical Modification (ICD-9-CM) or the current Tenth Revision (ICD-10).21 These codes can be grouped into disease chapters, such as all respiratory or cardiovascular diseases, and sub-codes distinguish disease states. Unfortunately, chronic states are rarely indicated.

Consequently, for this study, 5 definitions were tested for use in identifying people with a large share (individually and/or collectively) of publicly funded homecare services provided in Alberta, a Canadian province. Each definition was confirmed as viable for testing during a preliminary analysis of the complete provincewide homecare data obtained for this study: 1) Clients with ICD-9-CM codes for stroke, cancer, COPD, and/or diabetes.20 Just over half of all clients were diagnosed with 1 or more conditions; 2) Clients with 40 or more ICD-9-CM diagnostic codes, as multiple comorbidities are said to have the greatest impact on healthcare systems.1 Nearly half of the clients had 40 or more ICD-9-CM codes; 3) Clients with 4 or more ICD-9-CM chapters; diseases affecting multiple organs or body systems are more likely to result in chronic illness. Four was the median ICD-9-CM chapter number among the studied clients; 4) Clients who received homecare services for 90 days or more. Over half of all clients studied had service spans of this length (counted from the first to last date of services each fiscal year); and 5) Clients classified by homecare case managers as having long-term homecare service needs compared with those assessed with acute (<30 days) service needs; 60% were classified as long-term clients.

Two types of data analyses were conducted for each definition: one of total homecare hours provided per client each fiscal year (FY) and one for total service episodes per client each fiscal year. Both measures are important for planning homecare service delivery. After research ethics approval was obtained from a University of Alberta health research ethics board, the 3 most recent consecutive complete years of homecare data were requested from Alberta Health, the government department responsible for healthcare data. Complete data on all publicly funded homecare services and clients for FYs 2003-2004, 2004-2005, and 2005-2006 were provided, with each data set defined by fiscal year, April 1 through March 31. For each client, care hours and service visits or episode data were provided, as well as matching individual-anonymous sociodemographic and ICD-9-CM data.

Data were received for 149,378 clients: 53,922 in FY 2003-2004; 60,597 in FY 2004-2005, and 34,859 in FY 2005-2006 (in that year, all data from 1 large city were missing). Because the FY 2005-2006 clients were similar in age, gender, and services utilization to those in the previous 2 years, FY 2005-2006 data was retained for some tests. A total of 8,438,520 diagnostic codes were recorded for these 149,378 clients (in total, over all 3 years combined); each code was classified as to whether it represented one of the 4 main chronic illnesses or not, and it was grouped into its respective ICD-9-CM chapter.

The data for each year were aggregated into a summary file containing a single record per homecare client that included total homecare hours and service episodes. The data were explored using the frequencies and summary functions of the SPSS version 20 data analysis program (IBM, Armonk, New York), including mean, median, mode, SD, and range. Similarities and differences across years were noted, and the data were further explored to compare mean scores and distribution probabilities and to assess for relationships between variables. The 5 definitions were tested to determine which definition identified clients (individually and/or collectively) with more homecare hours and/or substantial service episodes each year. Utilization shares by age and gender were also determined. The findings for the 2 years with complete data were compared for data quality assurance purposes. The FY 2003-2004 data set was then used for 2 multiple regression tests to examine the relationship between the independent sociodemographic variables and a single criterion variable (number of service episodes or number of care hours per client).

RESULTS
Table 1 shows the average age was consistent from year to year, with two-thirds of clients 65 years or older, although they ranged in age from 0 to 106 years. A stable client ratio of about 60 females to 40 males each year was found. Over half were not married, two-thirds lived with another person, and three-fourths received a healthcare insurance premium subsidy (indicating low income).

Table 2 outlines the most common ICD-9-CM codes. Few represented more than 5% of clients classified as acute, long-term, palliative, or all other. Some of the most common codes were nonspecific, indicating that the health problem was not yet diagnosed or that no disease could be diagnosed for the presenting health condition.

Table 3 outlines summary findings for the 5 operational definitions. For 2 years, clients each year who were not diagnosed with any of the 4 main chronic illnesses, clients with 1 to 39 ICD-9-CM codes, and clients with fewer than 4 ICD-9-CM chapters had a greater share of total service hours and service episodes each year. Similarly, on an individual basis, these same clients had longer homecare visits and more service episodes (on average) each year, with one exception: individuals with 4 or more chapter headings had more service episodes (on average) each year.

Table 3 also shows that long-span clients (those receiving services for 90 days or more) accounted for 95% of all care hours and service episodes each year compared with those receiving services over spans of 1 to 30 days (shown in Table 3), and 31 to 90 days (not shown in Table 3). Individual long-span clients also had longer homecare visits and more service episodes each year, on average, compared with short-span clients. Similarly, the clients classified by homecare nurses as needing long-term services accounted for 90% of all care hours and 85% of all service episodes each year, far more than clients classified as “acute” with <30-day service needs. Individual long-term clients also had longer homecare visits and more frequent service episodes each year, on average, than acute clients.

Once these 2 definitions identified clients with a large share of homecare services in 2 separate years, the definitions were further tested to describe clients. Table 4 shows that long-span clients were often older and female, with significantly more diagnostic codes and chapters than short-span clients. Table 5 shows that classified long-term clients were also often older and female, with significantly more ICD-9-CM chapters than acute clients. Acute clients had more diagnostic codes on average, however.

A multiple regression analysis performed to examine for relationships between the sociodemographic variables and the first dependent or criterion variable—the number of service episodes for individual clients in FY 2003-2004—revealed that no sociodemographic variable predicted service episodes, nor did these variables collectively predict homecare service episodes. The second multiple regression test performed to examine for relationships between the sociodemographic variables and the total hours of homecare provided to each individual client in the 2003-2004 year similarly revealed that no sociodemographic variable predicted homecare hours, nor did these variables collectively predict homecare hours.

DISCUSSION
The findings of this study are surprising. Although older female homecare clients were found to be higher users of homecare services, age and gender did not predict total annual homecare hours or service episodes. This is a major finding, as old age and female gender have often been identified as major criteria for disability and healthcare services utilization.22-24 Instead, the homecare pre-admission assessments conducted by homecare case managers, who are usually registered nurses, were identified as critical for determining each person’s need for homecare services. Clearly, this need varied. Previous research has also indicated considerable variability in supportive care needs among homecare clients.25,26

 
Copyright AJMC 2006-2017 Clinical Care Targeted Communications Group, LLC. All Rights Reserved.
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