<p>Care of patients with chronic conditions is complicated and
usually includes large number of healthcare providers. Understanding the team
structure and networks of healthcare providers help to make informed decisions
for health policy makers and design of wellness programs by identifying the
influencers in the network. This work presents a novel approach to assess the
collaboration of healthcare providers involved in the care of patients with
chronic conditions and the impact on patient outcomes. </p>
<p>In the first study, we assessed a patient population needs,
preventive service utilization, and impact of an onsite clinic as an
intervention on preventive service utilization patterns over a three-year
period. Classification models were developed to identify groups of patients
with similar characteristics and healthcare utilization. Logistic regression
models identified patient factors that impacted their utilization of preventive
health services in the onsite clinic vs. other providers. Females had higher
utilizations compared to males. Type of insurance coverages, and presence of
diabetes/hypertension were significant factors that impacted utilization. The
first study framework helps to understand the patient population
characteristics and role of specific providers (onsite clinic), however, it
does not provide information about the teams of healthcare providers involved
in the care process. </p>
<p>Considering the high prevalence of diabetes in the patient
cohort of study 1, in the second study, we followed the patient cohort with
diabetes from study 1 and extracted their healthcare providers over a two-year
period. A framework based on the social network analysis was presented to
assess the healthcare providers’ networks and teams involved in the care of
diabetes. The relations between healthcare providers were generated based on
the patient sharing relations identified from the claims data. A multi-scale
community detection algorithm was used to identify groups of healthcare
providers more closely working together. Centrality measures of the social
network identified the influencers in the overall network and each community.
Mail-order and retail pharmacies were identified as central providers in the
overall network and majority of communities. This study presented metrics and
approach for assessment of provider collaboration. To study how these
collaborative relations impact the patients, in the last study, we presented a
framework to assess impacts of healthcare provider collaboration on patient
outcomes. </p>
<p>We focused on patients with diabetes, hypertension, and
hyperlipidemia due to their similar healthcare needs and utilization. Similar
to the second study, social network analysis and a multi-scale community
detection algorithm were used to identify networks and communities of
healthcare providers. We identified providers who were the majority source of
care for patients over a three-year period. Regression models using generalized
estimating equations were developed to assess the impact of majority source of
care provider community-level centrality on patient outcomes. Higher
connectedness (higher degree centrality) and higher access (higher closeness
centrality) of the majority source of care provider were associated with
reduced number of inpatient hospitalization and emergency department visits. </p>
<p>This research proposed a framework based on the social
network analysis that provides metrics for assessment of care team relations
using large-scale health data. These metrics help implementation experts to
identify influencers in the network for better design of care intervention
programs. The framework is also useful for health services researchers to
assess impact of care teams’ relations on patient outcomes. </p>
<br>
<p> </p>
Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/8014985 |
Date | 15 May 2019 |
Creators | Mina Ostovari (6611648) |
Source Sets | Purdue University |
Detected Language | English |
Type | Text, Thesis |
Rights | CC BY 4.0 |
Relation | https://figshare.com/articles/The_Impact_of_Healthcare_Provider_Collaborations_on_Patient_Outcomes_A_Social_Network_Analysis_Approach/8014985 |
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