Health Care Utilization in an Academic Integrative Medicine Center,2011

Abstract

Objectives:

As empirical evidence about the efficacy and therapeutic benefits of integrative medicine grows and insurance coverage of services increases, patient demand for integrative medicine is likely to increase. Relatively few studies have looked at electronic health records (EHRs) data to understand utilization of integrative medicine services within “real-world” practice settings. This study’s objective is to describe sociodemographic data and health care utilization for adults (age 18 or older) within a large regional health system from 2011 to 2022.

Methods:

The study design was a longitudinal cohort analysis using EHRs data for patients seen at an integrative medicine center from 2011 to 2022.

Setting/Location:

UCHealth Integrative Medicine Center (“the Center”) within UCHealth, a not-for-profit health care system with hospitals and clinical facilities throughout Colorado, southern Wyoming, and western Nebraska.

Participants:

Adults 18 years or older at the time of care delivery seen at the Center from April 1, 2011, through December 31, 2022.

Results:

The Center provided 95,754 visits to 15,157 unique individuals from April 1, 2011, through December 31, 2022. The average number of individuals seen was 1,833 per year (Range 1,405–2,347). The cohort’s mean age was 43 years; the majority were female (75%) and white (77.2%) with commercial insurance (87.1%). Medicare (29.6%) and Medicaid (19.7%) insurance were also relatively common. The Social Deprivation Index scores were distributed broadly across the cohort. The top three reasons for visits were chronic pain, mental/behavioral health conditions, and obesity. The most frequent visits were for acupuncture, massage, and physician/physician assistant services. A total of 1,586 health care professionals from 52 different specialties, both within and outside UCHealth, referred to the Center.

Conclusion:

This study describes a large cohort of adults seen for integrative medicine services and referral sources within a large regional health care system. Study findings have the potential to shape future integrative health care provision, education, research, and policy.

Introduction

Integrative medicine is an important and often underestimated aspect of health care. Integrative medicine is the coordinated combination of complementary and conventional Western medical practices with emphasis on multimodal care treating the whole person versus a single organ system.^1
–3 The term complementary medicine is commonly used to describe health care approaches alongside conventional medical care or traditional Western medical practices. Common examples of complementary approaches used alongside of conventional care consist of acupuncture, Traditional Chinese Medicine, Ayurveda, naturopathy, homeopathy, massage, chiropractic, functional medicine,⁴ osteopathic, nutrition, herbal/botanical therapies, psychological mind−body approaches, mindfulness, and yoga.⁵ The combined modality approach to addressing complex medical problems has evolved into the concept of whole-person health.

Integrative medicine is found in nearly every country in the world, and demand for its services continues to increase.⁶ According to a 2012 U.S. National Health Interview Survey one-third of adults have used integrative medicine modalities. Another study at the University of Michigan’s Integrative Health Center reported improvements in patient-reported health measures and high overall satisfaction with care.⁷ Another study at the University of California, Los Angeles reported a reduction in the number of hospitalizations and hospitalization days among adults receiving integrative medicine services as part of a complex high utilizer patient care program.⁸ People seeking integrative medicine services often do so because they seek a model of care that aligns with their values, desire more autonomy over their health, and may be dissatisfied with conventional care.⁹

There has been growing literature describing integrative medicine health care utilization among adults with specific disease conditions, including spinal cord injuries,¹⁰ psychiatric disorders,¹¹ and multiple sclerosis, as part of a complex care management program.⁸ While clinical research has increased in integrative medicine, health services research remains relatively underdeveloped.^12,13 To our knowledge, very few studies have looked at electronic health records (EHRs) data to understand utilization of integrative medicine services within “real-world” practice settings. As the body of reliable evidence about integrative medicine grows and insurance coverage of integrative medicine services expands, patient demand for complementary and integrative medicine is expected to rise.¹⁴ A recent example is the increasing use of integrative medicine approaches to treat long COVID.¹⁵ Therefore, knowledge about health care utilization is essential to inform health care systems on how to implement integrative medicine services based on real world usage that highlights referral sources and specific conditions treated.

The purpose of this paper is to describe sociodemographic data and health care utilization for adults (age 18 or older) seen at UCHealth Integrative Medicine Center from 2011 to 2022. Secondary objectives were to (1) describe characteristics of people who had one visit versus more than one integrative medicine visit; and (2) contextualize the cohort to the larger population in the region. The use of longitudinal data is an important innovation for research in integrative medicine, which has historically used predominantly cross-sectional data.

Materials and Methods

Study design

The study design was a longitudinal descriptive cohort analysis using EHRs data for patients seen at UCHealth Integrative Medicine Center from 2011 to 2022.

Study setting

This study was conducted at UCHealth Integrative Medicine Center within UCHealth, a not-for-profit health care system with hospitals and clinical facilities throughout Colorado, southern Wyoming, and western Nebraska. As an academic medical center, UCHealth is closely affiliated with the University of Colorado School of Medicine and Skaggs School of Pharmacy and Pharmaceutical Sciences.

UCHealth’s Integrative Medicine Center was founded in 2001. A group of 24 full- or part-time physicians, a physician assistant, psychologists, acupuncturists, massage therapists, a yoga therapist, a pharmacist/herbalist/aromatherapist, a chiropractor, nurses, and a registered dietician provided services at the Center, making it an ideal site to understand integrative medicine health services utilization.

Participants/cohort definition

Participants in this analysis were any adults (18 years or older at the time of care delivery) seen at UCHealth Integrative Medicine Center from April 1, 2011, through December 31, 2022. The earliest data available from Epic health records software at this facility was April 2011. Therefore, the cohort for this study is defined as the total number of unique adults with at least one integrative medicine visit within this timeframe. For the analysis, the cohort was divided into two subgroups: (1) individuals with only one visit to the Center; and (2) individuals with more than one visit. To better examine trends in chronic conditions and medication frequencies among the cohort over time, we analyzed these data at more specific visit frequencies: 1, 2–5, 6–10, 11–15, 15–20, and 21 or more visits during the observation period.

To address potential sources of bias, we included all individuals seen at the Center during the observation period, and used all available clinical data for the cohort, and applied the same criteria to determine visits for all provider types. We compared the number of unique individuals and visits obtained through our Caboodle data extraction process with data from Epic’s Slicer Dicer, a reporting tool within the EHR that is commonly used for institutional quality improvement purposes. We also identified sources of likely missing or incomplete data (i.e., the psychologist visit counts) in our results, and as a limitation.

Data elements extracted from EHR

Box 1 shows the sociodemographic, diagnostic, and utilization data elements that were extracted from the EHR.

Data extraction occurred in January 2023 from the University of Colorado research data repository, Health COMPASS, which utilizes the OMOP v5.4 Common Data Model. The cohort was developed by selecting patients who had a visit with at least one of the integrative medicine providers during the observation period. To determine the integrative medicine providers, a list of 53 current and previous physicians and other providers and staff working at UCHealth Integrative Medicine Center was developed using data from the EHR system. This list was verified by the current UCHealth Integrative Medicine Center research team. We compared data extraction of the EHR data to Epic’s SlicerDicer tool, which is a self-service reporting tool that provides access to some clinical data for data exploration purposes.

Sociodemographic

Age, gender, race, ethnicity, insurance type, and housing zip code were obtained from patient charts. Age was determined for the year of initial visit. Insurance type was determined using data from the last year of the observation period in which the patient received medical care.

Box 1. Data Elements Extracted from EHR

Sociodemographic -

Age

Gender

Race

Ethnicity

Insurance type

Zip code

Diagnostic -

All conditions

Prescription and over-the-counter medications

Utilization -

Visit specialty

Visit date

Visit type

Visit diagnoses

Referral specialty

Diagnostic

Data for all medical conditions and comorbidities were obtained via diagnosis codes in the patient’s chart (ICD-9, ICD-10). Conditions were categorized into groups with similar codes (i.e., diabetes type 1 and diabetes type 2) or similar conditions.^16,17 Data for medication records contained all medications prescribed to the cohort during the observation period. Medications were categorized into groups according to the condition they are used for (e.g., antihypertensives, anticoagulants), or their main ingredient (e.g., opioids, steroids). These groups were developed by two physicians and reviewed by the research team.

Utilization

Integrative medicine visits were defined as any procedure, service, or visit that was provided by an integrative medicine clinician at UCHealth Integrative Medicine Center. All referrals were included regardless of source; that is both clinician and patient self-referrals were included. Visits were grouped according to the provider’s specialty, and the visit date, type, and diagnoses were captured. Data for referrals to integrative medicine was extracted using Caboodle, a data warehouse system within Epic that supports Epic’s clinical information system. Referrals data for Caboodle to integrative medicine was extracted from 2011 to 2022. Referral providers’ specialties were grouped and reviewed by two physicians and verified by a third physician. For unclear referring providers’ specialties, a manual search was done using the clinician’s name to determine the referral specialty.

Analysis

The integrative medicine cohort’s demographics and clinical variables were summarized and compared among the following groups within the cohort: (1) individuals seen with only one visit to integrative medicine; and (2) individuals with multiple visits to integrative medicine. In order to examine changes over time according to more specific visit frequencies, we analyzed chronic conditions and medication frequencies according to whether the cohort had one visit, 2–5 visits, 6–10 visits, 11–15 visits, 16–20 visits or more than 21 visits during the observation period.

A descriptive analysis was conducted using data elements shown in Box 1. Sociodemographic and health characteristics associated with integrative medicine services were calculated for individuals with one visit to integrative medicine, and individuals with more than one integrative medicine visit. Trends in integrative medicine visits, diagnostic information, and reasons for referral were examined. The mean, median, and range for integrative medicine visits and provider types seen were calculated.

Continuous variables were summarized as mean (standard deviation[SD]) and compared using a t test if the distribution was approximately normal, or as a median (interquartile range[IQR]) and compared using a Wilcoxon rank sum test if otherwise. Categorical variables were summed as frequency and percentage and compared using chi-squared tests.

To characterize the social risk of each participant in the cohort, we calculated the Social Deprivation Index (SDI). The SDI is a composite measure of area deprivation level based on seven demographic characteristics (percent living in poverty, percent with less than 12 years of education, percent single-parent households, the percentage living in rented housing units, the percentage living in overcrowded housing units, percent of households without a car, and percentage of nonemployed adults under 65 years of age) collected in the American Community Survey¹⁸ and used to quantify the socioeconomic variation in health outcomes.¹⁹ Patient zip codes were used to calculate the SDI to quantify the levels of deprivation and indicate the extent to which a community is socially disadvantaged. The relationship between the SDI score and the severity of deprivation is direct, positive, and linear; as the SDI score increases, the severity of deprivation also increases.²⁰

This project was reviewed by the Colorado Multiple Institution Review Board and was determined to meet criteria as a Quality Improvement study. The data analysis was completed in August 2023.

Results

Overall, Figure 1 shows the development of the integrative medicine cohort from the EHR data initially extracted. The UCHealth Integrative Medicine Center provided 95,754 visits to 15,157 unique individuals from April 1, 2011, through December 31, 2022. The average number of unique individuals seen was 1,833 per year (Range 1,405–2,347). A total of 5,245 individuals (34.6%) had one visit and 7,278 (48%) had 2–10 visits during the observation period. The average number of visits per patient was 13 (for the patients in the two or more-visit group). Overall the average number of visits per patient is 9 (min = 1, max = 487).

FIG. 1.

Visits to UCHealth Integrative Medicine Center between April 1, 2011 and December 31, 2022.

Sociodemographic characteristics of the cohort

Table 1 shows the sociodemographic characteristics of the cohort for integrative medicine. The cohort’s mean age at the start of the observation period was 43 years. The majority of the cohort (75%) were female and white (77.2%). The majority of patients had commercial insurance (87.1%), with Medicare (29.6%) and Medicaid (19.7%) insurance also relatively common. (Numbers add to greater than 100% due to some individuals having more than one type of insurance).

Table 1.

Demographic Characteristics of Patients Aged 18 and Older Visiting UCHealth Integrative Medicine Center, 2011–2022 (n = 15,157)

Characteristic	Totaln = 15,157n (%)	Patients with one visit n = 5,245n (%)	Patients with more than one visitn = 9,912n (%)	p-value
Age at start of observation period, median years (IQR)	42.0 (30–56)	39.0 (27–54)	44.0 (31–57)	<0.0001
Gender (n = 15,157)				<0.0001
Female	11,361 (75.0)	3,818 (72.8)	7,543 (76.1)
Male	3,796 (25.0)	1,427 (27.2)	2,369 (23.9)
Race				0.0002
White	11,703 (77.2)	3,938 (75.1)	7,765 (78.3)
Black	1,158 (7.6)	435 (8.3)	723 (7.3)
Asian	22 (0.2)	5 (0.1)	17 (0.2)
American Indian or Alaska Native	53 (0.4)	21 (0.4)	32 (0.3)
Native Hawaiian or Pacific Islander	12 (0.1)	11 (0.2)	9 (0.1)
Multiple Race	433 (2.9)	170 (3.2)	263 (2.7)
Other/Unknown	1,768 (11.7)	665 (12.7)	1,103 (11.1)
Ethnicity				<0.0001
Hispanic	1,349 (8.9)	529 (10.1)	820 (8.3)
Non-Hispanic	13,309 (87.8)	4,491 (85.6)	8,818 (89.0)
Unknown	499 (3.3)	225 (4.3)	274 (2.8)
Insurance Type Frequency^a
Self-pay	673 (4.4)	281 (5.4)	392 (4.0)
Commercial payer	13,200 (87.1)	4,404 (84.3)	8,796 (89.5)
Medicare	4,493 (29.6)	1,337 (25.6)	3,156 (31.8)
Medicaid^b	2,985 (19.7)	1,148 (22.0)	1,837 (18.5)
Veteran Care	1,608 (10.9)	513 (10.3)	1,095 (11.2)
Other	1,653 (10.6)	539 (9.8)	1,114 (11.0)
SDI (median, IQR)	31 (10–57)	33 (10–59)	31 (10–57)	0.4
Social Deprivation Index categories^c				0.66
1–25	5,678 (37.9)	1963 (37.9)	3,715 (37.9)
25.1–50	4,919 (32.8)	1,671 (32.2)	3,248 (33.1)
50.1–75	2,712 (18.1)	953 (18.4)	1,759 (17.9)
75.1–100	1,689 (11.3)	596 (11.5)	1,093 (11.1)

Insurance Type was determined using data for the last year of the observation period in which the patient received medical care. Patients may have had more than one type of insurance. The self-pay category includes those whose insurance did not cover services received, or who opted to pay out-of-pocket.

Medicaid insurance was only accepted at the Center beginning in 2018.

SDI was calculated using zip code for each person. Of the total cohort (n = 15,157), 14,998 available zip codes were obtained from patient records, representing 99% of the cohort.

IQR, interquartile range; SDI, Social Deprivation Index.

Compared with the Denver metropolitan area population, this cohort tended to be older (median age of 43 years vs. Denver median age of 37 years²¹), have more females (75.0% vs. 49.7% in Denver metropolitan area²²) and have more people identifying as white (77.2% vs. 68.8% for Denver metropolitan area²²). As with other integrative medicine centers in the United States, the patient population was primarily adults, due to the majority of providers being trained in adult care only.²³ The presence of multiple conditions (five, on average) for which this cohort received both integrative and conventional care was substantial.

The Social Deprivation Index (SDI) scores for this population show that people receiving integrative medicine services lived in areas that represent the full distribution of social risks-i.e., this cohort represents the full spectrum of individuals living in high socioeconomically advantaged areas to high socioeconomically disadvantaged areas. More than a third (37.9%) reside in areas that are considered the most advantaged areas and 11.3% live in areas that are the most disadvantaged in this population, with the remaining population falling in between.

Table 2 shows patient characteristics and utilization data for patients seen at UCHealth Integrative Medicine Center. The average number of years a person visited the Integrative Medicine Center was 1.8 years (min = 1, max = 12). Table 2 shows that the most common conditions were chronic pain, mental and behavioral health issues, and obesity. There was a very wide range in visit frequency.

Table 2.

Diagnostic Characteristics and Utilization Data of Patients Aged 18 and Older Visiting UCHealth Integrative Medicine Center, 2011–2022 (n = 15,157)

Characteristic	Totaln = 15,157n (%)	Patients with one visit n = 5,245n (%)	Patients with more than one visitn = 9,912 (%)
Number of conditions grouped mean per year (SD)	4.7 (3.6)	4.5 (3.5)	4.8 (3.6)
Top 10 conditions
Chronic pain	12,420 (81.9)	3,905 (74.5)	8,547 (86.2)
Mental/behavioral health	10,767 (71.0)	3,448 (65.7)	7,347 (74.1)
Obesity	10,361 (68.4)	3,356 (64.0)	7,041 (71.0)
Other metabolic conditions	7,628 (50.3)	2,313 (44.1)	5,338 (53.9)
Respiratory conditions	7,392 (48.8)	2,317 (44.2)	5,075 (51.2)
Sleep disorders	7,159 (47.2)	2,335 (44.5)	5,078 (51.2)
Infectious disease	6,198 (40.9)	1,958 (37.3)	4,261 (43.0)
GI conditions	5,877 (38.8)	1,796 (34.2)	4,096 (41.3)
Arthritis	5,682 (37.5)	1,593 (30.4)	4,115 (41.5)
Hypertension	5,320 (35.1)	1,716 (32.7)	3,620 (36.5)
Number of medications grouped mean per year (SD)	5.2 (3.7)	5.0 (3.7)	5.3 (3.7)
Most common medication groups (top 10)
Antimicrobial	11,006 (72.6)	3,502 (66.8)	7,504 (75.7)
Antiinflammatory	9,319 (61.5)	2,953 (56.3)	6,366 (64.2)
Opioids	8,884 (58.6)	2,779 (53)	6,105 (61.6)
Antidepressant	8,707 (57.4)	2,786 (53.1)	5,921 (59.7)
Other mental health medications	8,008 (52.8)	2,444 (46.6)	5,564 (56.1)
Anticonvulsant	7,314 (48.3)	2,228 (42.5)	5,086 (51.3)
Antihypertensive	7,292 (48.1)	2,332 (44.5)	4,960 (50.0)
Antihistamines, decongestants	6,618 (43.7)	2,078 (39.6)	4,540 (45.8)
Steroids	6,562 (43.3)	1,998 (38.1)	4,564 (46.0)
Bronchodilators, inhaled corticosteroids	6,294 (41.5)	1,967 (37.5)	4,327 (43.7)
Number of integrative medicine services, mean per patient per year (SD)	1.2 (0.5)	1.0 (0.1)	2.6 (3.0)
Most frequent integrative medicine services (unique patients)
Acupuncture	4,511 (29.8)	549 (10.5)	3,962 (40.0)
Massage	4,028 (26.6)	875 (16.7)	3,153 (31.8)
Physician or PA	3,835 (25.3)	792 (15.1)	3,043 (30.7)
Nutrition	1,867 (12.3)	698 (13.3)	1,169 (11.8)
Chiropractic	1,106 (7.3)	111 (2.1)	995 (10.0)
Psychology^a	1,016 (6.7)	266 (5.1)	750 (7.6)
Physical therapy	353 (2.3)	2 (0)	351 (3.5)
Herbalist	242 (1.6)	28 (0.5)	214 (2.2)
Yoga	192 (1.3)	11 (0.2)	181 (1.8)
Most frequent integrative medicine services (number of visits)
Total number of visits	78,542	4,937	73,605
Acupuncture	28,720	556	28,164
Massage	20,041	881	19,160
Physician or PA	9,785	958	8,827
Chiropractic	5,337	108	5,229
Physical therapy	3,888	2	3,886
Nutrition	3,112	690	2,422
Psychology	2,787	290	2,497
Yoga	751	10	741
Herbalist	387	28	359

SD, standard deviation; GI, gastrointestinal.

Referrals to Integrative Medicine, 2011–2022 (Table 3)

Referrals were made from numerous specialties within the health care system as well as community clinicians in the region From the referral Caboodle data in Epic, a total of 11,304 unique people were referred to integrative medicine from 2011 to 2022. Of the 11,304 referred, a total of 9,467 (83.7%) had at least one visit with an integrative medicine provider. Patients were referred by a total of 1,586 health care professionals from 52 different specialties both within and outside UCHealth. The top three referral sources were internal medicine, family medicine, and clinicians practicing within the Integrative Medicine Center referring to other practitioners within the group.

Table 3.

Integrative Medicine Population Referral Data (Patients with a Referral to UCHealth Integrative Medicine Center)

Department specialty	Total (n = 11,304)n (%)	People with referral and visit to IM(n = 9,467)n (%)
Source of referral
Internal medicine	3,293 (29.1)	2,854 (30.1)
Family medicine	2,148 (19.0)	1,764 (18.6)
Integrative medicine (internal)	1,317 (11.7)	1,246 (13.2)
Surgery	725 (6.4)	405 (4.3)
Oncology	674 (6.0)	626 (6.6)
Neurology	632 (5.6)	485 (5.1)
Obstetrics and gynecology	553 (4.9)	460 (4.9)
Emergency medicine	257 (2.3)	254 (2.7)
Unspecified	213 (1.9)	188 (2)
Physical medicine and rehabilitation	209 (1.8)	188 (2)

IM, Integrative Medicine.

Discussion

This study was designed to describe sociodemographic and health care utilization data for patients seeking integrative medicine services within a large regional health system in Colorado and surrounding states. Although other studies have assessed health services utilization for integrative medicine for selected disease conditions, to our knowledge, this is the first study to describe health care utilization for a cohort of this size using real-world EHRs data focused on a population with multiple disease conditions.

The SDI has been shown to be correlated with several conditions that are commonly seen in integrative medicine. For example, higher SDI scores are associated with higher risk of sleep deprivation, poor mental health, and poor diabetes outcomes.^24,25 The median SDI score is lower than two other reports, one from a federally qualified health center setting²⁴ and one from the Veterans Administration hospital system.²⁶ Improving equitable access to care is a core value of many health systems. Additionally, the field of integrative medicine has been critiqued for not being accessible to, or representative of, the full spectrum of diversity of the populations and communities it serves. Therefore, we sought to address these issues by contextualizing the social risk of the population. Knowledge of SDI scores offers an opportunity to understand and provide targeted outreach for service provision to populations at highest risk. In this study, for example, individuals with higher SDI scores and risky health conditions could be targeted for integrative medicine services, both because they might benefit from such services, and are under-represented in the population seen at the center.

In 2018–2019, the Integrative Medicine Center began to enhance its efforts to provide services to people with Medicaid insurance to improve access to the integrative medicine center for people with lower incomes. Nearly 20% of the cohort overall had Medicaid insurance, suggesting that demand for integrative medicine services among this population is significant. Prior to 2018, a range of 400–800 people with Medicaid insurance were seen each year at the Center; from 2019 to 2023, this group increased from 1,000 to 1,200 people. Improving access to integrative medicine services for people with lower incomes has also been a priority reported for other centers.²⁷

Measures of community-level social risk (such as the SDI) are not always accurate in identifying individual-level social risks (such as an individual’s self-assessment of food insecurity, housing insecurity, or financial strain).²⁸ Relying solely on community-level data to understand the social risks of an individual risks ecological fallacy.²⁸ However, when individual level social risk screening is not available or unknown, community-level social risk assessment is an alternative means to try to understand and quantify levels of social disadvantage within a population. As others have reported, community-level social determinants of health or “community vital signs”—such as the availability of green space for walking, financial resources, and housing conditions within a community provide important contextual information about a person’s environment that is highly relevant to recommendations are often made in integrative medicine facilities regarding lifestyle change.

The large number of referrals representing nearly all of the major specialty groups and provider types within and beyond the health system speak to the broad acceptance and support of integrative medicine in the health care community. The top three referral sources were from internal and family medicine and internal referrals, the latter of which speaks to the value of collaborative care within an integrative medicine setting and the ease with which patients can learn about and receive multiple services.

This finding is consistent with others’ work showing that health professionals generally have a positive view about complementary and integrative medicine. However, they may have knowledge gaps or safety concerns about the appropriate use of integrative medicine and may view referrals to an integrative medicine practice within an academic health system as a means to address such concerns.^14,29,30 The most frequent conditions associated with integrative medicine referrals reflect common, difficult-to-treat conditions across the U.S. health care system such as chronic pain, mental health disorders, and obesity. Health care professionals view integrative medicine as having a diverse set of tools and treatment options unlike standard medical care, including an expanded team-based approach to help complex patients with multiple chronic conditions that are often difficult to manage.²⁷ Previous research has shown that health professionals acknowledge that conventional health care may fail to meet the needs of some patients, especially those with chronic conditions.²⁷ Indeed, evidence suggests that people with chronic conditions (e.g., cancer, musculoskeletal, and cardiovascular disease) use integrative medicine approaches to improve wellbeing and reduce side effects from treatment.²⁷

The most common chronic conditions seen in the Center—such as chronic pain, mental health disorders, and a variety of conditions associated with metabolic dysfunction and/or chronic inflammation—represent conditions for which there is evidence that integrative medicine approaches may be beneficial. The specific services provided at this integrative medicine center are similar to services that national surveys of the U.S. population have reported,^31,32 and are also consistent with previous studies of health care professionals’ self-report of the integrative medicine services they provide.³³ The center provides consultative services, and although care models vary with some centers also providing primary care services, UCHealth Integrative Medicine Center was established to provide consultative services, consistent with the majority of integrative medicine centers at academic health systems in the United States.^23,34 Indeed, health systems such as the Veterans Health Administration have begun to implement complementary and integrative health care alongside primary and specialty conventional care as part of their transformation to a Whole Health system of care as means to meet the growing demand for these services and to engage and empower individuals to take control of their health.³⁵

We were interested in examining the distribution of single versus multiple appointments for the cohort to see if there were any trends in numbers of visits for chronic conditions for which integrative medicine services might be beneficial. For example, individuals with chronic pain or mental health issues, two conditions for which integrative medicine services can be beneficial but require regular follow-up, might be expected to have greater numbers of visits. However, we did not observe greater numbers of visits among the cohort with these chronic conditions. Individuals with only one visit could be due to lack of interest in the integrative medicine care model or fit with the service type. Also, clinician availability was an issue as it was common for clinician schedules to be full and wait times to be fairly long, even for follow-up visits. It is also possible that financial or other barriers to access were an issue, and/or that these individuals also were seeing other specialists for their conditions. A future study incorporating surveys or qualitative methods could help shed light on these issues.

Limitations

This study’s findings should be interpreted in light of its limitations and strengths. Our results were derived from a single academic medical center and cannot necessarily be generalized to other sites. As the Integrative Medicine Center is a unique center at our institution, it is possible that some of the EHRs data were more difficult to capture using the institution’s data abstraction processes tailored toward conventional medical services. Due to institutional restrictions on release of psychologist visit data, the number of psychologist visits is likely to be a significant underestimate of the actual psychologist visits to the Center for this time period. Due to constraints on data availability, we were unable to report SDI scores for the rest of the academic medical center, which would have provided a more robust characterization of our cohort relative to all people seen within the health care system. Strengths include the relatively large cohort size for a study of this nature in integrative medicine, access to a relatively broad set of real-world EHRs data, our ability to examine trends longitudinally, and the ability to capture and report on data over an 11-year period.

Conclusions

In this longitudinal cohort analysis using EHRs data for patients seen at UCHealth Integrative Medicine Center over an 11-year period, 15,157 individuals were seen for a variety of chronic conditions, especially chronic pain, mental health disorders, and obesity. The population was relatively broad across the spectrum of social advantage to disadvantage. The center received referrals from 1,586 referring providers from nearly all subspecialties at the institution, an indicator of broad acceptance for the integrative medicine model and effective referral relationships, and patient follow through with referrals at this institution. Age, gender, race, and ethnicity, but not insurance or SDI, were associated with having one visit versus multiple visits to the Center.

EHRs data have potential to increase our knowledge about integrative medicine health service utilization; however, there are important limitations and challenges to data access that need to be addressed in future studies. The results of this descriptive, exploratory study have potential to shape future clinical, educational, and research in integrative medicine.

Footnotes

Authors’ Contributions

J.K.C.: Conceptualization, investigation, data curation, methodology, project administration, funding acquisition, supervision, visualization, writing—original draft, and writing—reviewing and editing. T.J.W.: Writing—reviewing and editing. M.N.: Writing—reviewing and editing. M.S.: Writing—reviewing and editing. T.T.N.: Writing—reviewing and editing. C.P.: Writing—reviewing and editing. J.W.: Writing—reviewing and editing. L.G.: Writing—reviewing and editing, funding acquisition/resources. F.R.G.: Writing—reviewing and editing

Author Disclosure Statement

No competing financial interests exist.

Funding Information

This work was supported by institutional funding from the University of Colorado Anschutz Medical Campus Department of Internal Medicine.

References

Manheimer

. Summary of findings tables: Presenting the main findings of Cochrane complementary and alternative medicine-related reviews in a transparent and simple tabular format. Glob Adv Health Med, 2012; 1(1):90–91.

Murphy

, Botticello

, Bryce

, et al. Who moves? A demographic profile of post-injury residential movers in a sample of people with spinal cord injury. Archives Phys Med Rehabil, 2021; 102(10):e30.

Health NCfCaI. Complementary, Alternative, or integrative health: What’s in a name? 2021. Available from: https://www.nccih.nih.gov/health/complementary-alternative-or-integrative-health-whats-in-a-name

Bland

. Defining function in the functional medicine model. Integr Med (Encinitas), 2017; 16(1):22–25.

Chen

, Michalsen

. Management of chronic pain using complementary and integrative medicine. BMJ, 2017; 357:j1284.

World Health Organization. WHO Traditional Medicine Strategy: 2014–2023. World Health Organization: Geneva; 2013.

Myklebust

, Pradhan

, Gorenflo

. An integrative medicine patient care model and evaluation of its outcomes: The University of Michigan experience. J Altern Complement Med, 2008; 14(7):821–826.

Zhang

, Chu

, Yoo

, et al. Effects of intensive outpatient integrative medicine on health care utilization on high utilizer patients at a major academic health system. J Alternative Complement Med, 2021; 27(9):803–806; doi: 10.1089/acm.2021.0087

Astin

. Why patients use alternative medicine: Results of a national study. JAMA, 1998; 279(19):1548–1553; doi: 10.1001/jama.279.19.1548

10.

Coker

, Berliner

, Botticello

, et al. Utilization of complementary and integrative health care by people with spinal cord injury in the Spinal Cord Injury Model Systems: A descriptive study. Arch Phys Med Rehabil, 2022; 103(4):755–763.

11.

Marchand

, Zhang

, Hamilton

, et al. Utilization and outcomes of a Whole Health model of care by Veterans with psychiatric illness. Complement Ther Med, 2022; 71:102884.

12.

Adams

, Sommers

, Robinson

. Public health and health services research in integrative medicine: An emerging, essential focus. European Journal of Integrative Medicine, 2013; 5(1):1–3; doi: 10.1016/j.eujim.2012.11.004

13.

Koster

, Baars

, Delnoij

. Patient-reported quality of care in anthroposophic and integrative medicine: A scoping review. Patient Educ Couns, 2020; 103(2):276–285.

14.

Bauer

, Townsend

, Cutshall

, et al. Advanced practice providers’ knowledge, attitudes, and utilization of complementary and integrative medicine at an Academic Medical Center. Altern Ther Health Med, 2020; 26(5):8–16.

15.

Roth

, Chan

, Jonas

. Addressing the long COVID crisis: Integrative health and long COVID. Glob Adv Health Med, 2021; 10(21649561211056597); doi: 10.1177/21649561211056597

16.

Informatics OHDSa. Concept Sets (LEGACY). 2019. Available from: https://www.ohdsi.org/web/wiki/doku.php?id=documentation:software:atlas:concept_sets [Last accessed: August 10, 2023 ].

17.

Sena

. Concept Sets. 2019. Available from: https://github.com/OHDSI/Atlas/wiki/Concept-Sets [Last accessed: August 10, 2023 ].

18.

Bureau USC. American Community Survey. United States Census Bureau: 2022.

19.

Center RG. Social Deprivation Index (SDI). Available from: https://www.graham-center.org/maps-data-tools/social-deprivation-index.html

20.

Butler

, Petterson

, Phillips

, Bazemore

. Measures of social deprivation that predict health care access and need within a rational area of primary care service delivery. Health Serv Res., 2013; 48(2 Pt 1):539–559; doi: 10.1111/j.1475-6773.2012.01449.x

21.

Corporation MDED. Population By Age. 2020. Available from: https://www.metrodenver.org/regional-data/demographics/age [Last accessed: September 15, 2023 ].

22.

Bureau USC. QuickFacts: Denver city, Colorado; Denver County, Colorado. 2022. Available from: https://www.census.gov/quickfacts/fact/table/denvercitycolorado,denvercountycolorado/PST045222 [Last accessed: September 15, 2023 ].

23.

Horrigan

, Lewis

, Abrams

, et al. Integrative medicine in America—How integrative medicine is being practiced in clinical centers across the United States. Glob Adv Health Med, 2012; 1(3):18–52.

24.

Cottrell

, O’Malley

, Dambrun

, et al. The impact of social and clinical complexity on diabetes control measures. J Am Board Fam Med, 2020; 33(4):600–610.

25.

Griggs

, Horvat Davey

, Howard

, et al. Socioeconomic deprivation, sleep duration, and mental health during the first year of the COVID-19 pandemic. Int J Environ Res Public Health, 2022; 19(21):14367.

26.

Patel

, Krasnow

, Long

, et al. Excess 30-day heart failure readmissions and mortality in black patients increases with neighborhood deprivation. Circ Heart Fail, 2020; 13(12):e007947.

27.

, Templeman

, Grant

, et al. Informing the model of care for an academic integrative health care center: A qualitative study of primary care stakeholder views. J Altern Complement Med, 2020; 26(4):300–315.

28.

Cottrell

, Hendricks

, Dambrun

, et al. Comparison of community-level and patient-level social risk data in a network of community health centers. JAMA Netw Open, 2020; 3(10):e2016852-e2016852.

29.

Sewitch

, Cepoiu

, Rigillo

, et al. A literature review of health care professional attitudes toward complementary and alternative medicine. Complementary Health Practice Rev, 2008; 13(3):139–154.

30.

Ventola

. Current Issues Regarding Complementary and Alternative Medicine (CAM) in the United States: Part 1: The widespread use of CAM and the need for better-informed health care professionals to provide patient counseling. P T, 2010; 35(8):461–468.

31.

Barnes

, Bloom

, Nahin

. Complementary and alternative medicine use among adults and children: United States, 2007. Natl Health Stat Report, 2008; 12(12):1–23.

32.

Barnes

, Bloom

, Nahin

, et al. Costs of complementary and alternative medicine (CAM) and frequency of visits to CAM practitioners, United States, 2007. Natl Health Stat Report, 2009; 30(18):1–14.

33.

Ehrlich

, Callender

, Gaster

. Integrative medicine at academic health centers: A survey of clinicians’ educational backgrounds and practices. Family Medicine, 2013; 45(5).

34.

Eisenberg

, Kaptchuk

, Post

, et al. Establishing an integrative medicine program within an academic health center: Essential considerations. Acad Med J Assoc Am Med Colleges, 2016; 91(9):1223–1230.

35.

Whitehead

, Kligler

. Innovations in care: Complementary and integrative health in the Veterans health administration whole health system. Med Care, 2020; 58(9S Suppl 2):S78–S79.

Health Care Utilization in an Academic Integrative Medicine Center,2011–2022

Abstract

Objectives:

Methods:

Setting/Location:

Participants:

Results:

Conclusion:

Introduction

Materials and Methods

Study design

Study setting

Participants/cohort definition

Data elements extracted from EHR

Sociodemographic

Diagnostic

Utilization

Analysis

Results

Sociodemographic characteristics of the cohort

Referrals to Integrative Medicine, 2011–2022 (Table 3)

Discussion

Limitations

Conclusions

Footnotes

Authors’ Contributions

Author Disclosure Statement

Funding Information

References