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Continuity in Home Health Care: Is Consistency in Nursing Personnel Associated with Better Patient Outcomes?

  • VNA Health Group

Abstract and Figures

A growing body of evidence suggests that patients who receive coordinated and uninterrupted health care services have better outcomes, more efficient resource utilization, and lower costs of health care. However, limited research has considered whether attributes of continuity in home health care service delivery are associated with improved patient outcomes. The present study examines the relationship between one dimension of continuity of care, consistency in nursing personnel, and three patient outcomes: hospitalization, emergent care, and improvement in activities of daily living. Analyses of data from a large population of home health patients (N=59,854) suggest that greater consistency in nursing personnel decreases the probability of hospitalization and emergent care, and increases the likelihood of improved functioning in activities of daily living between admission and discharge from home health care. These results provide preliminary evidence that efforts to decrease dispersion of nursing personnel across a series of home visits to patients may lead to improved outcomes. The implications of these findings for clinical practice and further research are discussed in the paper.
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Continuity in Home Health Care: Is
Consistency in Nursing Personnel
Associated with Better Patient Outcomes?
David Russell, Robert J. Rosati, Peri Rosenfeld, Joan M. Marren
Home health care encompasses a range of
professional and supportive services (e.g.,
skilled nursing, rehabilitation, home health
aides) that aim to help individuals manage
their conditions and remain at home, avoiding
admission to a hospital or an institutional long-
term care setting. As one of the most rapidly
expanding sectors of the health care system,
research and policy experts have begun paying
greater attention to the quality of these home
health services. Recent efforts to improve
home health care quality have largely focused
on preventing hospital readmissions (Rosati &
Huang, 2007). Far less attention has been paid
to the more proximal characteristics of home
health services, including whether visits to
patients are coordinated and delivered in a
consistent manner. In an attempt to address
these issues, we use electronic health records
and other staffing data to: (1) describe the
level of continuity in home health patient care,
and (2) examine the relationship between con-
tinuity of care and patient outcomes.
The term continuity of care is used by health
services researchers to describe patient–
provider relationships that are connected and
coordinated across time and settings (Donald-
son, 2001; Sparbel & Anderson, 2000). Prior
research suggests that ensuring continuity in
the process through which patients receive
health care improves safety, reduces costs, and
lowers the rate of emergency department utili-
zation (Christakis, Wright, Koepsell, Emerson,
& Connell, 1999). While several studies have
focused on the relationship between continuity
of care and patient outcomes in the hospital or
psychiatric setting, relatively little research has
examined this issue as it relates to home health
services (Bell et al., 2009; Christakis et al., 1999;
Saultz & Lochner, 2005; Ware, Tugenberg,
Dickey, & McHorney, 1999). Home health
patients tend to have multiple chronic condi-
tions and cognitive impairments that present
challenges to care planning and management,
and that often lead to longer lengths of stay
(Murtaugh et al., 2009). Inconsistent or unco-
ordinated care can compromise rapport and
decrease the provider’s ability to observe and
interpret changes in a patient’s appearance or
behavior (Woodward, Abelson, Tedford, &
Hutchison, 2004). Lapses in observation, ap-
propriate knowledge and skills, and trust
between the patient and provider may affect
the quality of home health services, possibly
leading to poorer patient outcomes (Wood-
ward et al., 2004). The present study tests the
hypothesis that patients who received home
health care by as many of the same nursing
personnel as possible would have a lower risk of
being hospitalized or receiving emergent care,
and have a greater chance of improving func-
tioning in activities of daily living between
admission and discharge from home health
Study Design and Methods
Patient Population
This study is based on retrospective data from a
large urban not-for-profit home health care
Abstract: A growing body of evidence suggests that patients who
receive coordinated and uninterrupted health care services have
better outcomes, more efficient resource utilization, and lower
costs of health care. However, limited research has considered
whether attributes of continuity in home health care service
delivery are associated with improved patient outcomes. The
present study examines the relationship between one dimension
of continuity of care, consistency in nursing personnel, and three
patient outcomes: hospitalization, emergent care, and
improvement in activities of daily living. Analyses of data from
a large population of home health patients (N559,854) suggest
that greater consistency in nursing personnel decreases the
probability of hospitalization and emergent care, and increases
the likelihood of improved functioning in activities of daily living
between admission and discharge from home health care. These
results provide preliminary evidence that efforts to decrease
dispersion of nursing personnel across a series of home visits to
patients may lead to improved outcomes. The implications of
these findings for clinical practice and further research are
discussed in the paper.
continuity of care
emergent care
functional limitations
home health care
patient outcomes
Vol. 33 No. 6 November/December 2011 33
Journal for Healthcare Quality
Vol. 33, No. 6, pp. 33–39
&2011 National Association for
Healthcare Quality
Journal for Healthcare Quality
agency. The Outcomes and Assessment Infor-
mation Set and administrative records are
utilized from a population of home health
care patients with acute care needs who meet
the following eligibility criteria: (1) patients
who received two or more skilled nursing visits
and (2) patients who were admitted and dis-
charged during the 2008 calendar year. The
analysis was limited to nursing services pro-
vided by RNs and excluded other types of
professional and paraprofessional services
(e.g., physical therapy, clinical social work,
home health aides). These criteria produced
a sample of 59,854 cases. The total number of
nursing visits provided to patients in this pop-
ulation ranged from 2 to 461, with the mean
and median at nine and six visits, respectively.
Measuring Continuity of Care
The measure used to estimate continuity in
home health care services is based on a for-
mula that was initially developed to model
dispersion in patient–provider contact across a
number of sources (Bice & Boxerman, 1977;
Shortell, 1976). This measure is preferable to
other quantitative indicators of continuity of
care, because it takes into account the number
of providers, the number of interactions with
each provider, and the total number of inter-
actions with all providers. The formula was
adapted for use in the current study as a mea-
sure of consistency in nursing personnel across
a series of home health care visits. While pa-
tients receive their skilled nursing services from
a single source (i.e., a local home health
agency), they may receive visits from multiple
providers of care (i.e., different nurses).
The formula produces scores that range be-
tween 0 and 1. Higher scores are indicative of
greater continuity in home health care services,
while lower scores suggest less continuity. Fig-
ure 1 presents an illustration of how these
scores are computed for hypothetical patients
with a series of 15 home care visits (the full
computation of each patient’s score is shown in
the notes below the figure). In the first case, a
hypothetical patient (Patient A) received all 15
visits from the same nurse and is assigned a
perfect score of 1. A second hypothetical pa-
tient (Patient B), who had 11 home visits from
Nurse E and 4 visits from Nurse F, is assigned a
score of 0.58. Hypothetical Patients C and D
received even fewer visits from the same
nurse(s), and have scores (0.15 and 0.06, re-
spectively) that reflect the greater dispersion of
service providers across their series of home
health care visits.
where nis the total number of home visits, n
the number of home visits by nurse j, and sis
the total number of nurses.
Patients in the analytic sample tended to fall
in the middle range of the scoring distribution
on this measure. The mean sample score is
0.54 (SD 50.34) and the median value is 0.50.
In comparison with the examples in Figure 1,
the average case in the analytic sample most
closely resembles hypothetical Patient B. How-
Case Nurse Dispersion Continuity Score
Figure 1. Examples of Scores Based on Nurse Dispersion
All patients received a total of 15 nursing visits. Patients and nurses are represented by different letters.
Patient A continuity score 5[(15
)15]/[15(15 1)] 5210/210 51.00;
Patient B continuity score 5[(11
15]/[15(15 1)] 5122/210 50.58;
Patient C continuity score 5[(4
)15]/[15(15 1)] 5
32/210 50.15; and
Patient D continuity score 5[(1
)15]/[15(15 1)] 5
12/210 50.06.
Journal for Healthcare Quality
ever, a substantial proportion of patients had
scores on opposite ends of the measurement
distribution. Twenty-six percent of patients re-
ceived visits from the same nurse (a score of 1)
over the course of their length of stay, while
10% of patients never saw the same visiting
nurse over their entire period of home care (a
score of 0). Based on the nonnormal distribu-
tion of the continuity measure, cases were
divided into three groups: low continuity of
care (scores between 0.00 and 0.39), moderate
continuity of care (scores between 0.40 and
0.79), and high continuity of care (scores be-
tween 0.80 and 1.00; reference category in
logistic regression analyses).
Measuring Patient Outcomes and
Statistical Controls
Three patient outcomes are measured, includ-
ing hospitalization, emergency room visits, and
improved functioning in activities of daily liv-
ing. In accordance with prior research on
home health episodes, hospitalizations and
emergency room visits are counted only if they
occurred within 60 days of admission to home
health care (Rosati & Huang, 2007). Improved
functioning in activities of daily living is de-
fined as a dichotomous variable representing
whether there is a difference between admis-
sion and discharge from home health care in
the number of activities of daily living that a
patient needed assistance with or to perform.
Patients who required assistance with fewer
activities of daily living at discharge from
home health care compared with admission
to home health care are assigned a value of 1.
Those who required assistance with the same
number of activities of daily living, or a higher
number of activities of daily living, at dis-
charge from home health care compared with
admission to home health care are assigned a
value of 0.
To assess the association between continuity
in home health care and patient outcomes, we
estimate three logistic regression equations
that include dummy variables for low and mod-
erate levels of continuity. The regression
equations control for a range of demographic
and clinical factors, including geographic re-
gion of service, age, gender, race/ethnicity,
living arrangement, length of stay, diagnosis
(based on the International Classification of
Diseases, 9th Revision; Iezzoni, 1997), comor-
bidity (measured as the number of diagnoses in
addition to the primary diagnosis), number of
activities of daily living that the patient requires
assistance, estimated life expectancy (measured
as a dichotomous variable where o6 months is
coded as 1) and overall prognosis (measured as
a dichotomous variable where poor is coded as
1). Descriptive statistics for each demographic
and clinical variable stratified by level of con-
tinuity in home health care (low, moderate,
and high) are presented in Table 1.
Table 2 presents adjusted odds ratios that
estimate the likelihood of certain patient out-
comes (hospitalization, emergency room
visitation, and improved functioning in activi-
ties of daily living) across three levels of
continuity in home health care, controlling
for a wide range of demographic and clinical
characteristics. Patients with high levels of con-
tinuity in home health care are compared with
patients with moderate and low levels of con-
tinuity. The results in Table 2 are consistent
with previous research that links greater con-
tinuity of care to improved patient outcomes.
For instance, patients with a low level of con-
tinuity are 1.4 times more likely to be
hospitalized and 1.3 times more likely to visit
the emergency room compared with those with
a higher level of continuity. Patients with low
continuity of care are 0.8 times less likely (20%
less likely) to have improved functioning in ac-
tivities of daily living at discharge from home
health care compared with patients with high
continuity of care. Patients with a moderate
level of continuity are 1.1 times more likely
than those with high continuity in their pro-
viders of home care to be hospitalized or to
visit the ER, but are not significantly different
in their likelihood of improved functioning in
activities of daily living. Presented another way,
Figure 2 displays a graph of predicted proba-
bilities for each of the three patient outcomes
across values of the continuity of care measure.
The predicted probabilities, which include
controls for demographic and clinical charac-
teristics, indicate a statistically significant linear
trend in the relationship between consistency
of nursing personnel and patient outcomes.
Researchers have argued that efforts to in-
crease the continuity of patient care are central
to improving patient outcomes across health
Vol. 33 No. 6 November/December 2011 35
care settings (Bell et al., 2009; Christakis et al.,
1999; Saultz & Lochner, 2005; Ware et al.,
1999). This study offers preliminary evidence
that providing home health care patients with
consistent nursing personnel may reduce the
rate of episodes ending in hospitalization or a
visit to the emergency room, and increase the
likelihood of improving functioning in activi-
ties of daily living between admission and
discharge from home health care. Given the
significant associations observed with patient
outcomes, consistency in nursing personnel
may be an important indicator for home health
agencies to track as part of their quality im-
provement efforts. While other measures of
continuity in home health care should be con-
sidered, our results suggest that the measure
used in the present study could be used as a
tool to drive aggregate changes in patient out-
Some lapses in continuity in the provision of
home health care services are expected due to
scheduling conflicts and other staffing issues
such as patient caseloads with daily or twice
daily nursing visits (e.g., for wound treat-
ments). However, a low level of consistency in
the provider of care clearly compromises the
stability and therapeutic benefits of the rela-
tionship between nurse and patient. Patients
are likely to become frustrated when they must
constantly reexplain their situation and service
delivery needs to a clinician with whom they do
Table 1. Demographic and Clinical Characteristics Stratified by Continuity of Care
Total Sample
Low Continuity
Mod Continuity
High Continuity
Age (SD) 70.4 (16.3) 68.8
(16.7) 71.7 (16.0) 71.1 (16.0)
Gender (% female) 61.4 60.6
62.3 61.6
Race (% White) 30.5 30.5 30.8 30.0
Payer (%)
Medicare fee-for-service 34.5 31.1
39.0 34.4
Medicaid fee-for-service 4.4 4.3
4.9 3.9
Dually eligible 12.0 10.5
14.4 11.7
Managed care 45.1 49.8
38.2 46.0
Other 3.5 4.0
3.0 3.5
Living arrangements (% alone) 32.4 30.3
34.7 32.9
Mean length of stay (SD) 36.1 (32.4) 32.9
(31.9) 44.7 (35.7) 31.4 (27.7)
Mean number of visits (SD) 9.3 (13.1) 9.5
(15.8) 11.9 (13.4) 6.4 (6.6)
ICD-9 classifications (%)
Congestive heart failure 14.8 13.6
15.8 15.2
Coronary heart disease 0.8 0.9 0.7 0.7
Dementia 8.4 7.5
9.0 9.1
Diabetes 2.3 2.4 2.4 2.0
Functional limitations 1.1 1.2 1.1 1.0
Liver disease 1.1 1.0 1.0 1.1
Lymphoma 2.0 2.1 1.9 1.9
Nutritional issues 0.2 0.2 0.2 0.2
Pulmonary disease 13.7 12.9
14.3 14.1
Renal failure 3.3 3.4 3.3 3.2
Vascular disease 4.5 4.4
4.9 4.0
Comorbidity (% 4 or more) 91.4 90.8
91.9 91.8
ADL (% 1 or more limitations) 91.4 90.9
91.9 91.6
Life expectancy (% o6 months) 3.4 3.6 3.2 3.3
Overall prognosis (% poor) 12.3 12.5 12.5 11.6
Hospitalization (%) 18.9 21.2
18.7 16.1
Emergency room visit (%) 15.3 16.8
15.4 13.3
Improvement in ADL (%) 53.4 51.1
54.7 55.1
Note. ADL 5activities of daily living.
International Classification of Diseases—9th Revision; Diagnostic groups are based on those described by Iezzoni (1997).
Significant difference (po.001) across groups stratified by continuity of care.
Journal for Healthcare Quality
not have an established level of rapport and
trust. The period of orientation reduces the
amount of time available for the clinician to
provide care (Woodward et al., 2004). Lapses
in the consistency of nursing personnel may
also effect the nurse’s ability to detect subtle
changes in a patient’s condition or care needs
(Woodward et al., 2004), potentially increasing
the likelihood of hospitalization or emergent
care. The results suggest that targeting a group
of patients with very low levels of consistency in
their nursing personnel, and intervening to in-
crease their level of consistency to a more
moderate level, would have the most measur-
able impact on patient outcomes.
Study Limitations
There are several study limitations that should
be noted. First, descriptive results indicated
variability in demographic and clinical charac-
teristics across patients stratified by continuity
of care. For example, patients with lower levels
of continuity of care tended to be younger and
have a shorter length of stay than patients with
higher continuity of care. However, these fac-
tors were adjusted for in logistic regression
equations when examining the impact of con-
tinuity of care on patient outcomes. Further,
this study focused on a single indicator of con-
tinuity in home health care—consistency in
nursing personnel. Ethnographic research of
Table 2. Adjusted Odds Ratios
for Selected Patient Outcomes
Hospitalization ER Visitation ADL Functioning
High continuity of care (0.80–1.00) (Reference) (Reference) (Reference)
Moderate continuity of care (0.40–0.79) 1.13 1.13 1.00
(1.07–1.20) (1.06–1.20) (0.95–1.04)
Low continuity of care (0.00–0.39) 1.43 1.33 0.80
(1.35–1.50) (1.25–1.41) (0.77–0.83)
Log likelihood ratio 3075.45
Note. ADL functioning 5improved functioning in activities of daily living.
Estimates are adjusted for geographic region, length of stay, level of functioning in activities of daily living,
comorbidity, life expectancy, overall prognosis, diagnosis, payer type, age, gender, race/ethnicity, and living
po.001; estimates are presented with 95% confidence intervals; significant odds ratios are highlighted in
bold text; for ease of interpretation, continuity of care scores were stratified into three groups: high continuity of
care (0.80 x1), moderate continuity of care (0.79 x0.40), and low continuity of care (0 x0.39).
Continuity of Care
Predicted Probability
ER Visit Hospitalization ADL Improvement
Figure 2. Predicted Probabilities for Patient Outcomes Across Continuity of Care
Note. The magnitudes of the relationships observed in this graph between continuity of care and patient outcomes
are statistically significant (po.001). Hospitalizations and visits to the emergency room are counted within 60 days of
admission to home health care. Improvement in functioning of activities of daily living is calculated between
admission and discharge from home health care. The predicted probabilities for each outcome are adjusted for
demographic and clinical characteristics.
Vol. 33 No. 6 November/December 2011 37
home health patients suggests that uninter-
rupted service delivery is only one component
of a continuous relationship between patient
and provider, while other characteristics such
as care planning and coordination are equally
important to patients’ experiences of continu-
ity (Ware et al., 1999; Woodward et al., 2004).
The level of coordination of patient transitions
into home health from other health care set-
tings (e.g., hospital, physician office) is also a
component in the continuum of care. Com-
munication between providers in different
health care settings is likely to be an impor-
tant determinant of outcomes among patients
who have complex health care needs and/or
challenging self-care responsibilities (Coleman,
2003; Kripalani, Jackson, Shnipper, & Cole-
man, 2007). More research is needed to
understand the ways in which these different
aspects of continuity overlap, and how they are
interrelated with outcomes among patients
who receive home health care services. Addi-
tional work is also needed to replicate these
findings in other home health care agencies,
and to determine if the level of continuity in
care is influenced by the size of the patient
population or nursing workforce. A related
question concerns whether continuity in home
care is influenced by the type of services pro-
vided (e.g., rehabilitation therapy compared
with skilled nursing or home health aide ser-
vices) and/or neighborhood characteristics.
Additional research is needed to understand
how scheduling conflicts or the frequency of
nursing visits influences consistency in the pro-
viders of care. As the number of nurses age 55
and older increases, a greater proportion of
the nursing workforce is likely to seek flexible
hours and weekly schedule changes, such as
6-hr shifts or 4-day work weeks (Hart, 2007).
Given these contextual factors, it will be im-
portant to identify a level of consistency in the
provision of home care services that can be
used by agencies as a target for their opera-
tions. Finally, further research should replicate
the findings observed in the present study and
continue to examine the relationship between
continuity of home-based nursing services and
other outcomes, such as patient satisfaction
with care.
Bell, C. M., Schnipper, J. L., Auerbach, A. D., Kaboli, P. J.,
Wetterneck, T. B., Gonzales, D. V., et al. (2009). Asso-
ciation of communication between hospital-based
physicians and primary care providers with patient out-
comes. Journal of General Internal Medicine, 24, 381–386.
Bice, T. W., & Boxerman, S. B. (1977). A quantitative mea-
sure of continuity of care. Medical Care, 15, 347–349.
Christakis, D. A., Wright, J. A., Koepsell, T. D., Emerson, S.,
& Connell, F. A. (1999). Is greater continuity of care
associated with less emergency department utilization?
Pediatrics, 103, 738–742.
Coleman, E. A. (2003). Falling through the cracks: Chal-
lenges and opportunities for improving transitional care
for persons with continuous complex care needs. Journal
of the American Geriatrics Society, 51, 549–555.
Donaldson, M. S. (2001). Continuity of care: A reconcep-
tualization. Medical Care Research and Review, 58, 255–290.
Hart, K. A. (2007). The aging workforce: Implications for
health care organizations. Nursing Economics, 25, 101–
Iezzoni, L. I. (1997). Assessing quality using administrative
data. Annals of Internal Medicine, 127, 666–674.
Kripalani, S., Jackson, A. T., Shnipper, J. L., & Coleman, E.
A. (2007). Promoting effective transitions of care at
hospital discharge: A review of key issues for hospitalists.
Journal of Hospital Medicine, 2, 314–323.
Murtaugh, C., Peng, T., Totten, A., Costello, B., Moore, S.,
& Aykan, H. (2009). Complexity in geriatric home care.
Journal for Healthcare Quality, 31, 34–43.
Rosati, R. J., & Huang, L. (2007). Development and testing
of an analytic model to identify home healthcare pa-
tients at risk for a hospitalization within the first 60 days
of care. Home Health Care Services Quarterly, 26, 21–36.
Saultz, J. W., & Lochner, J. (2005). Interpersonal continuity
of care and care outcomes: A critical review. Annals of
Family Medicine, 3, 159–166.
Shortell, S. M. (1976). Continuity of medical care: Con-
ceptualization and measurement. Medical Care, 14, 377–
Sparbel, K. J. H., & Anderson, M. A. (2000). Integrated
literature review of continuity of care: Part 1, conceptual
issues. Journal of Nursing Scholarship, 32, 17–24.
Ware, N. C., Tugenberg, T., Dickey, B., & McHorney, C. A.
(1999). An ethnographic study of the meaning of con-
tinuity of care in mental health services. Psychiatric
Services, 50, 395–400.
Woodward, C. A., Abelson, J., Tedford, S., & Hutchison, B.
(2004). What is important to continuity in home care?
Perspectives of key stakeholders. Social Science and Med-
icine, 58, 177–192.
Authors’ Biographies
David Russell, PhD, is an Evaluation Scientist at the
Center for Home Care Policy & Research, Visiting Nurse
Service of New York. Dr. Russell works with research and
administrative staff at the agency to design and implement
evaluation studies of new programs and initiatives. His
research interests include health services, medical sociology,
and aging.
Robert J. Rosati, PhD, is Vice President of Clinical
Informatics at the Center for Home Care Policy & Research,
Visiting Nurse Service of New York. At the Center,
Dr. Rosati is responsible for evaluating care delivery and
reporting on clinical outcomes for all patients served by
VNSNY. Dr. Rosati has over 20 years experience in
healthcare and is currently on the faculty of Weill Cornell
Medical College and Hofstra University. He also is a
member of the JHQ Review Panel and Editorial Board.
Peri Rosenfeld, PhD, is a Senior Evaluation Scientist at the
Center for Home Care Policy & Research, Visiting Nurse
Service of New York. Dr. Rosenfeld’s areas of research
Journal for Healthcare Quality
interest include aging, nursing workforce, access to care,
and information literacy. She has published widely in these
areas and is a review editor for several journals including
CIN: Computers, Informatics and Nursing; Politics, Policy
and Nursing Practice; and Medical Care. She is also a
faculty member at the New York University College of
Joan M. Marren, RN, MA, MEd, serves as Chief
Operating Officer of the Visiting Nurse Service of New
York and President, VNSNY Home Care. In her role, Ms.
Marren ensures consistency in, and accountability for,
implementation of agency strategy across the organization
and its subsidiaries; serves as primary advocate and
standard-bearer of quality; and directs service delivery,
organizational design change and QI efforts. Her leader-
ship is characterized by a strong focus on innovation and
practice improvement and she plays a significant role in
shaping public policy. Ms. Marren was a 2004–2007
Robert Wood Johnson Executive Nurse Fellow.
For more information on this article, contact David Russell,
Vol. 33 No. 6 November/December 2011 39
... In comparison with integration and care coordination, there is far less hard evidence that links continuity with positive outcomes in the documents we reviewed. Three effectiveness-focused studies identified continuity as a characteristic associated with desirable outcomes 49,53,54 while two other more analytical articles 55,56 discuss its importance in high-performing home care models. However, 34 of the documents we reviewed (30%) mention continuity -most often relational continuity, with informational continuity as a more secondary focus -as a desirable feature of home care interventions and a core process leading to high quality services. ...
... Most of the literature we reviewed is written using role-based terms (the doctor, the nurse, the care coordinator, the occupational therapist) often without specifying how much, if any, relational continuity exists between these individuals and the client or family. One exception is a study by Russell, Rosati, Rosenfeld, et al. 54 which directly focused on this element. It found that the level of relational continuity varied considerably between recipients of home care services and that it was strongly correlated with functional capacity and risk of hospitalization. ...
Rationale, aims and objectives: There is a large body of literature from all over the world that describes, analyzes, or evaluates home care models and interventions. The present article aims to identify the practical lessons that can be gained from a systematic examination of that literature. Method: We conducted a three-step sequential search process from which 113 documents were selected. That corpus was then narratively analysed according to a realist review approach. Results: A first level of observation is that there are multiple blind spots in the existing literature on home care. The definition and delimitation of what constitutes home care services is generally under-discussed. In the same way, the composition of the basket of care provided and its fit with the need of recipients is under-addressed. Finally, the literature relies heavily on RCTs whose practical contribution to decisions or policy is disputable. At a second level, our analysis suggests that three mechanisms (system integration, case management and relational continuity) are core characteristics of home care models' effectiveness. Conclusion: We conclude by providing advice for supporting the design and implementation of stronger home care delivery systems. Our analysis suggests that doing so implies a series of sequential steps: identify what system-level goals the model should achieve and which populations it should serve; identify what type of services are likely to achieve those goals in order to establish a basket of services; and finally, identify the best ways and specific means to effectively and efficiently provide those services. Those same steps can also support ex-post evaluations of existing home care systems.
... Healthcare systems worldwide face new health and organizational challenges as a result of two distinct phenomena: an aging population with an increased prevalence of chronic diseases and the need for healthcare systems to migrate outside of hospitals to promote proactive medicine and community support [37][38][39]. Chronic patients are, in fact, challenged with both an increase in their overall health needs and the necessity to guarantee continuity of care [40,41]. Primary care settings can help achieve these objectives by granting patients access to healthcare services and facilitating continuity of care [42]. ...
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Promoting self-care is one of the most promising strategies for managing chronic conditions. This overview aimed to investigate the effectiveness of eHealth interventions at improving self-care in patients with type-2 diabetes mellitus, cardiovascular disease, and chronic obstructive pulmonary disease when compared to standard care. We carried out a review of systematic reviews on PubMed, Scopus, Cochrane, PsychInfo, and CINAHL. AMSTAR-2 was used for quality appraisal. Eight systematic reviews (six with meta-analysis) were included, involving a total of 41,579 participants. eHealth interventions were categorized into three subgroups: (i) reminders via messaging apps, emails, and apps; (ii) telemonitoring and online operator support; (iii) internet and web-based educational programs. Six systematic reviews showed an improvement in self-care measurements through eHealth interventions, which also led to a better quality of life and clinical outcomes (HbA1C, blood pressure, hospitalization, cholesterol, body weight). This overview provided some implications for practice and research: eHealth is effective in increasing self-care in chronic patients; however, it is required to designate the type of eHealth intervention based on the needed outcome (e.g., implementing telemonitoring to increase self-monitoring of blood pressure). In addition, there is a need to standardize self-care measures through increased use of validated assessment tools.
... This approach is the most used in practice by HHC providers, especially because it builds the patient-caregiver relationship and empowers the caregivers. The literature enforces that aging of the population and complexity of cases necessitate that the continuity of care constraint is handled carefully (den Herder-van der Eerden et al., 2017;Russell et al., 2011;Senot, 2019). However, it does not consider the efficiency related to routing and scheduling while providing the care. ...
Home health care (HHC) is a very popular service that plays an important role in reducing hospitalization costs and improving the quality of life for patients. Human resource planning is one of the most important processes in HHC facilities, and service providers must deal with several operational problems, e.g., the assignment of nurses to patients and the nurse routing. These two problems in HHC are intrinsically related. In the literature, they are solved simultaneously or sequentially, by exploiting First Assign Second Route (FASR) decomposition approaches in which the assignment problem is solved first and the routing problem is solved second. However, on the one hand, the simultaneous approach focuses primarily on the routing component of the problem but fails to offer continuity of care to the patients. On the other hand, FASR is more adequate to enforce the continuity of care constraint but is less effective towards the routing part. In this paper, we propose a novel decomposition approach that combines the advantages of each these approaches, which is based on the First Route Second Assign (FRSA) paradigm. To validate our FRSA approach and compare with a benchmark FASR decomposition, we also develop an instance generator that is inspired by real HHC settings with different sizes and travel time ratios. Experiments show the effectiveness of the FRSA decomposition and improvements with respect to the classical FASR, especially when travel times constitute a relevant part of the workload and the routing component of the problem is predominant; moreover, continuity of care is fully respected. Thus, FRSA can be effectively implemented by HHC providers for an efficient planning of resources and visits, especially where patients are spread in a vast territory.
... Three types of consistency are found in the literature; (i) visiting time consistency, (ii) person consistency and (iii) quantity consistency. VRPs with consistency attributes have been used to model various real-life applications, such as parcel delivery (Groër et al., 2009), home healthcare (Rusell et al., 2011), the transportation of disabled (Feillet et al., 2014) and elderly people (Braekers and Kovacs, 2016), pharmaceutical distribution (Campelo et al., 2019), home meal delivery (Hewitt et al., 2015), home groceries delivery (Song et al., 2020), retail distribution , soft drinks distribution (Rodríguez-Martín et al., 2018), aircraft fleet scheduling (Ioachim et al., 1999) as well as cleaning services (Tarantilis et al., 2012). The existing variants of VRPs with consistency considerations make the assumption that an unlimited number of identical vehicles is available at a central depot. ...
Customer relationship management is of high importance as it strengthens customer satisfaction. Providing consistent customer service cultivates customer retention and brand loyalty. This paper examines a new customer-oriented routing problem, the Consistent Vehicle Routing Problem with heterogeneous fleet. The objective is to create cost-efficient routing plans, utilising a fixed fleet of vehicles with heterogeneous operational characteristics, variable and fixed costs, while providing consistent customer service over multiple periods. Service consistency consists in person and visiting time consistency. A mathematical model capturing all the attributes of the problem is developed and utilised to solve small-scale instances to optimality. To address larger instances, a hierarchical Tabu Search framework is proposed. The proposed metaheuristic utilises an upper-level Tabu Search and an underlying Variable Neighbourhood Descent algorithm. Computational experiments conducted on existing and new benchmark instances show the flexibility, effectiveness and efficiency of the proposed framework. Various managerial insights are derived by examining the cost of imposing customer service consistency as well as customer-vehicle incompatibility constraints.
... The older adults valued being cared for by one single person rather than different actors. As previous research by Russell et al. (2011) showed, personnel continuity in home health care may reduce hospitalisation and increase functioning in daily activities. It also makes the older adult feel calmer and more Content courtesy of Springer Nature, terms of use apply. ...
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The increasing number of older people has a significant impact on the organisation of care in European countries. Formal care services face several limitations, while informal care is decreasing. As a result, older adults search for alternative strategies to meet their care needs. A recent tendency is to hire live-in migrant care workers. This study explores the motivations for and experiences of hiring live-in migrant care workers in Belgium of older people and their families. Using a qualitative study, eight in-depth interviews were conducted with older people or family members who had hired live-in migrant care workers. Additionally, five individual interviews and one focus group (N = 6) with professionals were conducted. Data were thematically analysed, using both deductive and inductive approaches. The main motivations for hiring live-in migrant carers were shortages in the accessibility and availability of formal care service provision and the anticipated benefits offered by live-in carers (i.e. reducing informal carer workloads, guaranteeing person-centred and continuous care, the possibility of ageing in place and delaying entry into residential care). Older people had generally positive experiences of the care provided, both in terms of the task responsibilities and the quality of care. The findings indicate that live-in migrant care workers can meet the demands of person-centred care at home. However, a clear hierarchy between older adults and care providers was identified and questions were raised about the training, insecure employment conditions and legal status of live-in migrant care workers.
... Thus, integrating comprehensive social determinants of health assessments that include patient language preference into home health care records would help enhance the precision of gauging risk for readmission from this point in a health care system. Some research also suggests that continuity of care-the same providers visiting the patient during each home care visit-may also enhance outcomes and reduce readmission risk (Allen et al., 2017;González et al., 2017;McMurray et al., 2007;Murtaugh et al., 2017;Russell et al., 2011). Continuity of care may be especially important for patients who do not speak the same language as their providers because of how it can build trust between them and the provider becoming more familiar with how the patient and family communicate. ...
Background In home health care, language barriers are understudied. Language barriers between patients and providers are known to affect a variety of patient outcomes. How a patient's language preference influences hospital readmission risk from home health care has yet to be determined. Objective To determine if home care patients’ language preference is associated with their risk for hospital readmission from home health care within 30 days of hospital discharge. Design Retrospective cross-sectional study of hospital readmissions from an urban home health care agency's administrative records and the national electronic home health care record for the United States, captured between 2010 and 2015. Setting New York City, New York, USA. Participants The dataset comprised 90,221 post-hospitalization patients and 6.5 million home health care visits. Methods First, a Chi-square test was used to determine if there were significant differences in crude readmission rates based on language group. Inverse probability of treatment weighting was used to adjust for significant differences in known hospital readmission risk factors between to examine all-cause hospital readmission during a home health care stay. The final matched sample included 87,561 patients with a language preference of English, Spanish, Russian, Chinese, or Korean. English-speaking patients were considered the comparison group to the non-English speaking patients. A Marginal Structural Model was applied to estimate the impact of non-English language preference against English language preference on rehospitalization. The results of the marginal structural model were expressed as an odds ratio of likelihood of readmission to the hospital from home health care. Results Home health patients with a non-English language preference had a higher hospital readmission risk than English-speaking patients. Crude readmission rate for the limited English proficiency patients was 20.4% (95% CI, 19.9% - 21.0%) overall compared to 18.5% (95% CI, 18.7% - 19.2%) for English speakers (p < 0.001). Being a non-English-speaking patient was associated with an odds ratio of 1.011 (95% CI, 1.004 – 1.018) in increased hospital readmission rates from home health care (p = 0.001). There were also statistically significant differences in readmission rate by language group (p<0.001), with Korean speakers having the lowest rate and Spanish speakers having the highest, when compared to English speakers. Conclusions People with a non-English language preference have a higher readmission rate from home health care. Hospital and home healthcare agencies may need specialized care coordination services to reduce readmission risk for these patients. Tweetable abstract: A new US-based study finds that home care patients with language barriers are at higher risk for hospital readmission.
This study is inspired by a challenging logistic problem encountered in the cleaning service sector. The company wishes to solve the consistent vehicle routeing problem over a three-month planning horizon. The company has a heterogeneous vehicle fleet to guarantee multiple frequencies of visits to its customers. The objective is to minimise the number of vehicles used and the total distance travelled. This problem is a generalisation of the periodic vehicle routeing problem. We decompose the problem into two sub-problems, namely, the planning and routeing optimisation sub-problems. We construct a mathematical model for the former and a large neighbourhood search for the latter. We evaluate the performance of our approach using the results of the industrial partner and instances from the literature on problems that are closely related to our case study. Our approach is found to be effective and robust. Our results outperform the existing company's plan in terms of solution quality, and staff convenience, and speed. We also discovered new best solutions on some of the instances from the literature.
As demand for home health care (HHC) services surges due to an aging population and public health constraints, HHC companies need to optimize their activities. Increasing costs to deliver care and the need to optimize the capacity of acute care settings such as hospitals, make the planning of HHC services more challenging. To optimally deliver care, the caregivers’ activities must be planned considering conflicting objectives. The proposed multi-objective HHC problem considers three components in the planning process: patients, nurses, and providers. An exact method is presented to efficiently solve a multi-objective HHC routing problem balancing the schedules of the nurses while maximizing quality of service (time windows, continuity, and consistency of care) and provider’s profit. A mixed-integer linear programming (MILP) model is formulated using the ϵ-constraint method and small- and medium-size problems are solved. Computational results on modified benchmark instances from the literature are used to test the method’s efficiency. A Pareto Frontier Analysis is used to evaluate optimality conditions for the provider, and it found that failing to satisfy the preferences of nurses has a larger impact on the provider’s bottom line. Furthermore, it was found that adjusting the patients’ preferences is not as taxing as adjusting the nurses’ preferences.
Home care provides personalized medical care and social support to patients within their own homes. Our work proposes a dynamic scheduling framework to assist in the assignment of health practitioners (HPs) to patients who arrive stochastically over time and are heterogeneous with respect to their health requirements, service duration, and region of residence. We model the decision of which patients to assign to HPs as a discrete‐time, rolling‐horizon, infinite‐stage Markov decision process. Due to the curse of dimensionality and the combinatorial structure associated with an HP's travel, we propose an approximate dynamic programming (ADP) approach based on a one‐step policy improvement heuristic. Four policies are investigated: the first two prioritize HP fairness by balancing service and travel times, respectively, while the other two are based on fluid approximations of the system. We show that the first fluid model is optimal if the number of patient arrivals is sufficiently large while the second performs better experimentally; both approaches leverage pricing and decomposition strategies. We compare our framework to more commonly implemented policies ‐ constrained versions of the classical vehicle routing problem ‐ in a simulation study using data collected from a Canadian home care provider. We show that, in contrast to these approaches, by accounting for future uncertainty, substantial cost savings can be obtained while a fewer number of referrals are rejected. We also find that well‐performing policies assign patients to HPs operating within a small set of adjacent regions while considering the number of periods that a patient requires care for. Otherwise, health practitioner workload may not be appropriately balanced over the long‐term even if travel time is minimized. This article is protected by copyright. All rights reserved
Paid caregivers (e.g., home health aides, home care workers) provide essential care to people with dementia living at home; this study explored family caregiver perspectives on the role and impact of paid caregivers in home-based dementia care. We conducted semi-structured interviews with family caregivers ( n = 15) of people with advanced dementia who received long-term paid care at home in New York between October 2020 and December 2020. We found that given the vulnerability resulting from advanced dementia, family caregivers prioritized finding the “right” paid caregivers and valued continuity in the individual providing care. The stable paid care that resulted improved outcomes for both the person with advanced dementia (e.g., eating better) and their family (e.g., ability to work). Those advocating for high quality, person-centered dementia care should partner with policymakers and home care agencies to promote the stability of well-matched paid caregivers for people with advanced dementia living at home.
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The aging population and the associated rise in the prevalence of chronic conditions suggest that the home health population is increasingly complex and challenging to manage. The purpose of this study was to use national administrative data (Outcome and Assessment Information Set assessments of persons discharged in 2004 and 2005) to examine the clinical complexity of older adults admitted to home healthcare. Our descriptive analyses confirm that multiple chronic conditions and cognitive impairment are common and result in longer lengths of stay. The findings support the need for geriatric home healthcare practices that effectively address multiple morbidities and cognitive function.
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Patients admitted to general medicine inpatient services are increasingly cared for by hospital-based physicians rather than their primary care providers (PCPs). This separation of hospital and ambulatory care may result in important care discontinuities after discharge. We sought to determine whether communication between hospital-based physicians and PCPs influences patient outcomes. We approached consecutive patients admitted to general medicine services at six US academic centers from July 2001 to June 2003. A random sample of the PCPs for consented patients was contacted 2 weeks after patient discharge and surveyed about communication with the hospital medical team. Responses were linked with the 30-day composite patient outcomes of mortality, hospital readmission, and emergency department (ED) visits obtained through follow-up telephone survey and National Death Index search. We used hierarchical multi-variable logistic regression to model whether communication with the patient's PCP was associated with the 30-day composite outcome. A total of 1,772 PCPs for 2,336 patients were surveyed with 908 PCPs responses and complete patient follow-up available for 1,078 patients. The PCPs for 834 patients (77%) were aware that their patient had been admitted to the hospital. Of these, direct communication between PCPs and inpatient physicians took place for 194 patients (23%), and a discharge summary was available within 2 weeks of discharge for 347 patients (42%). Within 30 days of discharge, 233 (22%) patients died, were readmitted to the hospital, or visited an ED. In adjusted analyses, no relationship was seen between the composite outcome and direct physician communication (adjusted odds ratio 0.87, 95% confidence interval 0.56 - 1.34), the presence of a discharge summary (0.84, 95% CI 0.57-1.22), or PCP awareness of the index hospitalization (1.08, 95% CI 0.73-1.59). Analysis of communication between PCPs and inpatient medical teams revealed much room for improvement. Although communication during handoffs of care is important, we were not able to find a relationship between several aspects of communication and associated adverse clinical outcomes in this multi-center patient sample.
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As a step toward developing a standardized measure of continuity of care for mental health services research, the study sought to identify the interpersonal processes of giving and receiving day-to-day services through which individual providers create experiences of continuity for consumers. Ethnographic methods of field observation and open-ended interviewing were used to investigate the meaning of continuity of care. Observations were carried out at two community mental health centers and a psychiatric emergency evaluation unit in Boston. Sixteen recipients and 16 providers of services at these sites were interviewed. Six mechanisms of continuity were identified, labeled, defined, and described through analysis of field notes and interview transcripts: pinch hitting, trouble shooting, smoothing transitions, creating flexibility, speeding the system up, and contextualizing. The mechanisms elaborate dimensions and principles of continuity cited by other observers and also suggest new formulations. The mechanisms identified in this study facilitate operationalization of the concept of continuity of care by specifying its meaning through empirically derived indicators. Ethnography promises to be a valuable methodological tool in constructing valid and reliable measures for use in mental health services research.
In Canada, home care is growing rapidly. Each province takes a somewhat different approach to its delivery. Ontario uses a competitive bidding model to award contracts to community agencies that bid for service delivery rights. Contracts are to be awarded based on quality and price. However, the attributes thought to contribute to high quality, such as continuity of care, are not clearly defined and are not measured. We sought to identify factors that were important to experiencing continuity of care in home care. We interviewed home care clients and their caregivers, workers in the home care system (nursing and homemaking service providers, case managers) and physicians whose patients use home care. During in-depth interviews with these key stakeholders, they described the conditions that led to continuity of care in home care. Service providers and case managers were also asked about the types of clients who need a high level of care continuity. Care that is experienced as running smoothly, that responds to clients’ needs and requires no special effort for clients to maintain, was seen as having continuity. The attributes of care experienced as facilitating continuity could be grouped under two dimensions of care—managing care (care planning, monitoring and review; and care coordination) and direct service provision (uninterrupted service delivery; consistent, appropriate knowledge and skills; ongoing accurate observation; trusting relationship between service provider and client/caregiver; rapport among team members; and consistent timing). Different stakeholders emphasized different attributes of care as most important to continuity. Clients included consistency of timing of service delivery while rarely mentioning care management issues. They emphasized the importance of consistent knowledge and skills in the workers and trusting relationships as important to experiencing care continuity. The description of attributes of continuity of home care that emerged from this study is compared to definitions found in the nursing, mental health and primary care literature.
The period following discharge from the hospital is a vulnerable time for patients. About half of adults experience a medical error after hospital discharge, and 19%–23% suffer an adverse event, most commonly an adverse drug event. This article reviews several important challenges to providing high-quality care as patients leave the hospital. These include the discontinuity between hospitalists and primary care physicians, changes to the medication regimen, new self-care responsibilities that may stress available resources, and complex discharge instructions. We also discuss approaches to promoting more effective transitions of care, including improvements in communication between inpatient and outpatient physicians, effective reconciliation of prescribed medication regimens, adequate education of patients about medication use, closer medical follow-up, engagement with social support systems, and greater clarity in physician–patient communication. By understanding the key challenges and adopting strategies to improve patient care in the transition from hospital to home, hospitalists could significantly reduce medical errors in the postdischarge period. Journal of Hospital Medicine 2007;2:314–323. © 2007 Society of Hospital Medicine.
Continuity of medical care is conceived as the extent to which services are received as part of a coordinated and uninterrupted succession of events consistent with the medical care needs of patients. Two operational measures are proposed, based on the Gini and CON indices of concentration. Examples of their application are provided using the 1970 CHAS-NORC national study of health services utilization. The validity of the proposed measures is assessed in a preliminary fashion, and some commonly held assumptions about the relationship between access, quality, and continuity of care are challenged. Advantages of the proposed measures include their ability to summarize a distribution, the availability of data for construction, the relative ease of computation and interpretation, and their sensitivity to organizational changes in the delivery of health services.
Administrative data result from administering health care delivery, enrolling members into health insurance plans, and reimbursing for services. The primary producers of administrative data are the federal government, state governments, and private health care insurers. Although the clinical content of administrative data includes only the demographic characteristics and diagnoses of patients and codes for procedures, these data are often used to evaluate the quality of health care. Administrative data are readily available, are inexpensive to acquire, are computer readable, and typically encompass large populations. They have identified startling practice variations across small geographic areas and-supported research about outcomes of care. Many hospital report cards (which compare patient mortality rates) and physician profiles (which compare resource consumption) are derived from administrative data. However, gaps in clinical information and the billing context compromise the ability to derive valid quality appraisals from administrative data. With some exceptions, administrative data allow limited insight into the quality of processes of care, errors of omission or commission, and the appropriateness of care. In addition, questions about the accuracy and completeness of administrative data abound. Current administrative data are probably most useful as screening tools that highlight areas in which quality should be investigated in greater depth. The growing availability of electronic clinical information will change the nature of administrative data in the future, enhancing opportunities for quality measurement.
The benefits of continuity of care (COC) have not been firmly established for pediatric patients. To assess whether greater COC is associated with lower emergency department (ED) utilization. Outpatient teaching clinic at Children's Hospital and Regional Medical Center, Seattle, WA. All 785 Medicaid managed care children ages 0 to 19 years followed at Children's Hospital and Regional Medical Center between 1993 to 1997 who had at least four outpatient visits. Retrospective claims-based analysis. COC was quantified based on the number of different care providers in relation to the number of clinic visits. Attending COC was significantly greater than resident COC. In a multiple event survival analysis, compared with those patients in the lowest tertile of attending COC, those in the middle tertile had 30% lower ED utilization (hazard ratio 0.70 [0.53-0.93]) and those in the highest tertile had 35% lower ED use (hazard ratio 0.65 [0.50-0.80]). Resident COC was not significantly associated with ED use. Greater COC with attending physicians in outpatient teaching clinics is associated with lower ED utilization.
Continuity of patient care is a fundamental tenet of professional nursing, yet comprehension of the concept and related issues remains elusive. The purpose of this study was to explore issues associated with definitions, related concepts, and research methods of continuity of care through systematic literature-based study. In Part 1 of this two-part series, definitions and related concepts, factors, and variables associated with continuity of care were explored. Qualitative, integrated literature review of a sample of 38 nursing research articles about continuity of care, 1990-1995. Ganong's (1987) stages of an integrative research review guided this study. A data collection tool was developed and pilot tested, and rules for data analysis and interpretation were established. Research articles were systematically analyzed and reported using descriptive analysis. No consensus was found in the literature about the conceptual definition of continuity of care. Continuity of patient care is a multifactorial concept affected by environmental influences, communication, patient, professional, and system factors.