Profiles and predictors of healthcare utilization: using a cluster-analytic approach to identify typical users across conventional, allied and complementary medicine, and self-care

Abstract Introduction The identification of typologies of health care users and their specific characteristics can be performed using cluster analysis. This statistical approach aggregates similar users based on their common health-related behavior. This study aims to examine health care utilization patterns using cluster analysis; and the associations of health care user types with sociodemographic, health-related and health-system related factors. Methods Cross-sectional data from the 2012 National Health Interview Survey were used. Health care utilization was measured by consultations with a variety of medical, allied and complementary health practitioners or the use of several interventions (exercise, diet, supplementation etc.) within the past 12 months (used vs. not used). A model-based clustering approach based on finite normal mixture modelling, and several indices of cluster fit were determined. Health care utilization within the cluster was analyzed descriptively, and independent predictors of belonging to the respective clusters were analyzed using logistic regression models including sociodemographic, health- and health insurance-related factors. Results Nine distinct health care user types were identified, ranging from nearly non-use of health care modalities to over-utilization of medical, allied and complementary health care. Several sociodemographic and health-related characteristics were predictive of belonging to the respective health care user types, including age, gender, health status, education, income, ethnicity, and health care coverage. Conclusions Cluster analysis can be used to identify typical health care utilization patterns based on empirical data; and those typologies are related to a variety of sociodemographic and health-related characteristics. These findings on individual differences regarding health care access and utilization can inform future health care research and policy regarding how to improve accessibility of different medical approaches.

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Antidepressant use in the elderly: Association with demographic characteristics, health-related factors, and health care utilization

Journal of Clinical Epidemiology ◽

10.1016/0895-4356(94)00188-v ◽

1995 ◽

Vol 48 (3) ◽

pp. 445-453 ◽

Cited By ~ 37

Author(s):

S Brown

Keyword(s):

Health Care ◽

Health Care Utilization ◽

The Elderly ◽

Demographic Characteristics ◽

Care Utilization ◽

Related Factors ◽

Health Related ◽

Antidepressant Use

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Health Disparities and Converging Epidemics in Jail Populations: Protocol for a Mixed-Methods Study (Preprint)

10.2196/preprints.10337 ◽

2018 ◽

Author(s):

Robert T Trotter II ◽

Ricky Camplain ◽

Emery R Eaves ◽

Viacheslav Y Fofanov ◽

Natalia O Dmitrieva ◽

...

Keyword(s):

Health Care ◽

Health Disparities ◽

Data Analysis ◽

Criminal Justice ◽

Health Care Utilization ◽

Secondary Data ◽

Care Utilization ◽

Cross Sectional ◽

Honest Broker ◽

Utilization Patterns

BACKGROUND Incarcerated populations have increased in the last 20 years and >12 million individuals cycle in and out of jails each year. Previous research has predominately focused on the prison population. However, a substantial gap exists in understanding the health, well-being, and health care utilization patterns in jail populations. OBJECTIVE This pilot study has 5 main objectives: (1) define recidivists of the jail system, individuals characterized by high incarceration rates; (2) describe and compare the demographic and clinical characteristics of incarcerated individuals; (3) identify jail-associated health disparities; (4) estimate associations between incarceration and health; and (5) describe model patterns in health care and jail utilization. METHODS The project has two processes—a secondary data analysis and primary data collection—which includes a cross-sectional health survey and biological sample collection to investigate infectious disease characteristics of the jail population. This protocol contains pilot elements in four areas: (1) instrument validity and reliability; (2) individual item assessment; (3) proof of concept of content and database accessibility; and (4) pilot test of the “honest broker” system. Secondary data analysis includes the analysis of 6 distinct databases, each covered by a formal memorandum of agreement between Northern Arizona University and the designated institution: (1) the Superior Court of Arizona Public Case Finder database; (2) North Country Health Care; (3) Health Choice Integrated Care; (4) Criminal Justice Information Services; (5) Correctional Electronic Medical Records; and (6) iLEADS. We will perform data integration processes using an automated honest broker design. We will administer a cross-sectional health survey, which includes questions about health status, health history, health care utilization, substance use practices, physical activity, adverse childhood events, and behavioral health, among 200 Coconino County Detention Facility inmates. Concurrent with the survey administration, we will collect Methicillin-resistant and Methicillin-sensitive Staphylococcus aureus (samples from the nose) and dental microbiome (Streptococcus sobrinus and Streptococcus mutans samples from the mouth) from consenting participants. RESULTS To date, we have permission to link data across acquired databases. We have initiated data transfer, protection, and initial assessment of the 6 secondary databases. Of 199 inmates consented and enrolled, we have permission from 97.0% (193/199) to access and link electronic medical and incarceration records to their survey responses, and 95.0% (189/199) of interviewed inmates have given nasal and buccal swabs for analysis of S. aureus and the dental microbiome. CONCLUSIONS This study is designed to increase the understanding of health needs and health care utilization patterns among jail populations, with a special emphasis on frequently incarcerated individuals. Our findings will help identify intervention points throughout the criminal justice and health care systems to improve health and reduce health disparities among jail inmates. INTERNATIONAL REGISTERED REPOR RR1-10.2196/10337

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