Abstract
Introduction
The objective of this study was to: 1) describe the prevalence of social needs in an integrated health system in Oregon and Southwest Washington and 2) examine whether and how the presence of social needs is associated with dental care utilization.
Methods
In this observational study, we identified 80,273 patients that met the following inclusion criteria: 1) completed a social needs screening between 1/1/2023 and 10/1/2024 (index date), 2) age 18+ as of index date, 3) 12+ months of dental and medical insurance coverage before and after index date and 4) not on research exclusion list. Four social needs were assessed: financial strain, food insecurity, housing instability and transportation needs. Two logistic regression models analyzed the association of social needs with dental care utilization: 1) each social need variable analyzed as a dichotomous measure: yes vs. no (ref. group) and 2) social needs analyzed as a count variable: 1, 2, 3 or more vs. 0 needs (ref. group).
Results
Approximately 17.8% of patients reported ≥1 social need at index date. We found that those with financial strain, food insecurity and transportation needs had lower odds of having any dental visits in the 12 months after social needs assessment. Having 1 or more social needs was associated with lower odds of having any dental visit.
Discussion
Further research is needed to evaluate the effectiveness of interventions to target social needs and whether resolution of these needs is associated with increases in dental utilization.
Keywords: dental utilization, insurance coverage, medical dental integration, social determinants of health, social needs
1. Introduction
The presence of social needs, such as financial strain and housing instability, has been associated with worse health outcomes (1–3). Similarly, social needs have been linked to poor access to medical care (4) and lower overall use of primary care medical visits (5, 6). However, less is known about how social needs impact routine dental utilization. This area of research is important, since regular access to dental area is linked to not only improved oral health outcomes (7) but also improved physical health outcomes (8, 9).
Among social needs, financial strain or difficulty paying for dental care has been studied most extensively. Several studies found difficulty paying for dental care remains a large barrier to accessing dental care (10–12). Research indicates that more people reported financial barriers to receiving dental care, compared to any other type of health care (10); fewer than 30% of adults ≥65 have dental insurance and 8% are unable to afford dental care (13).
Other research has found that food insecurity (14–16), housing instability (15, 17) and transportation needs (15, 18, 19) negatively impact dental utilization. However, few studies have examined the association of social needs with dental utilization in integrated health systems. Examining the associations of social needs with dental care utilization in integrated health systems can: 1) provide learnings from systems with comprehensive data on social needs, demographic characteristics, and health care utilization and 2) identify possible interventions for populations with specific social needs. Thus, the objective of our study is to: 1) describe the prevalence of social needs in Kaiser Permanente Northwest (KPNW), an integrated health system in Oregon and Southwest Washington and 2) examine whether and how the presence of social needs is associated with dental care utilization. KPNW provides a unique opportunity to conduct research with its integrated medical and dental health record as demonstrated by previous research examining the association of medical/dental integration with care gap closure (20, 21).
2. Methods
This retrospective, observational study used data from adult members of KPNW, an integrated health care system in Oregon and Southwest Washington. To be included, KPNW members met the following criteria: 1) completed an Epic-based social needs assessment between 1/1/2023 and 10/1/2024 (index date; KPNW members complete assessments as part of routine healthcare), 2) age 18 or older upon index date, 3) ≥12 months of KPNW medical and dental insurance coverage before and ≥12 months of medical and dental insurance coverage after index date and 4) not on the KPNW research exclusion list. The study was approved by the Kaiser Permanente Northwest Institutional Review Board. The Epic-based social needs screener is based on previously validated questions published in the research literature (22–29).
2.1. Measures
2.1.1. Outcome measure
The outcome measure for the study was any use of dental care (yes vs. no), measured 12 months after the index date. Dental utilization data was obtained from KPNW's electronic health record (EHR).
2.1.2. Independent variables
The presence of social needs, also identified from the KPNW EHR, was measured in two ways. First, four social needs measures (financial strain, food insecurity, housing instability, transportation needs) assessed on the index date were categorized as binary measures (yes vs. no). These measures have been reported in previous publications (30, 31) and are reported in Appendix A. Second, the total count of social needs was analyzed as: none, one social need, two social needs, and three or more social needs.
2.1.3. Covariate measures
Covariate measures were identified from KPNW's EHR. These measures included three demographic measures: age, sex, and race/ethnicity; one socioeconomic measure, the Area Deprivation Index (ADI) (32) and one clinical comorbidity measure, the Charlson Comorbidity Index (CCI) (33, 34). Further, four utilization measures were assessed in the 12 months prior to the social needs assessment date: dental utilization, primary care utilization, emergency department (ED) visits and hospital admissions.
2.1.4. Analysis
First, we conducted descriptive analyses for the study population. Second, we performed collinearity diagnostics to test for collinearity among the four social needs variables and covariate measures. The results of the analysis found no collinearity and all social needs and covariate measures were included in two logistic regression models. In the first model, each social need variable was analyzed as a dichotomous measure: yes vs. no (ref. group); while in the second model, the count of social needs was analyzed: 1, 2, 3 or more vs. 0 needs (ref. group). All statistical analyses were conducted using SAS Version 9.4.
3. Results
3.1. Study characteristics
Nearly 60% of the population was between age 18 and 64, 60.4% were female, and about 80.1% were White (Table 1). Nearly 80% of the population lived in neighborhoods with ADI scores representative of moderate or lower area deprivation, while 37.3% had a CCI score of 1 or higher. Regarding prior health care utilization in the year prior to social needs assessment, 64.9% had 1 or more dental visits, 57.9% had 1 or more primary care visits, 22.4% had 1 or more ED visits and 9.1% had 1 or more hospital admissions.
Table 1.
Population characteristics.
| Characteristic | Total N = 80,273 N (%) |
|---|---|
| Sociodemographic Characteristics | |
| Age, N (%) | |
| 18–44 | 24,453 (30.5%) |
| 45–64 | 22,953 (28.6%) |
| ≥65 | 32,857 (40.9%) |
| Mean +/- SD | 55.9 +/- 18.3 |
| Sex, N (%) | |
| Female (vs. male) | 48,463 (60.4%) |
| Race/Ethnicity, N (%) | |
| Asian/Asian-American | 3,914 (4.9%) |
| Black/African-American | 2,323 (2.9%) |
| Hawaiian/Pacific Islander | 279 (0.4%) |
| Hispanic/Latino | 5,563 (6.9%) |
| Native American/Alaskan Native | 232 (0.3%) |
| White | 64,316 (80.1%) |
| More than one race/Other race | 3,646 (4.5%) |
| Area Deprivation Index (ADI), N (%) | |
| Least deprivation (1–3) | 32,270 (40.2%) |
| Moderate deprivation (4–6) | 30,705 (38.3%) |
| Highest deprivation (7–10) | 17,298 (21.6%) |
| Comorbidities and Prior Health Care Utilization | |
| Charlson Comorbidity Index, N (%) | |
| 0 | 50,306 (62.7%) |
| 1 | 12,199 (15.2%) |
| 2+ | 17,768 (22.1%) |
| Utilization Characteristics (previous 12 months) | |
| +1 dental visits | 52,135 (64.9%) |
| +1 primary care visits | 46,489 (57.9%) |
| +1 ED visits | 17,948 (22.4%) |
| +1 hospital admissions | 7,266 (9.1%) |
3.2. Type and number of social needs
Approximately 18% of patients reported one or more social needs, while 3.9% reported three or more needs (Table 2). The most common social need was financial strain (12.8%), followed by food insecurity (9.6%), housing instability (5.6%) and transportation needs (4.0%).
Table 2.
Description of social needs.
| Individual social needs | N (%) |
|---|---|
| Financial Strain | 10,293 (12.8%) |
| Food Insecurity | 7,701 (9.6%) |
| Housing Instability | 4,504 (5.6%) |
| Transportation Needs | 3,186 (4.0%) |
| Count of Needs | N (%) |
| None | 65,967 (82.2%) |
| One | 6,833 (8.5%) |
| Two | 4,308 (5.4%) |
| Three or more needs | 3,165 (3.9%) |
| Total needs (mean +/- SD) | 0.3 +/- 0.9 |
3.3. Logistic regression results: association of individual social needs with dental care utilization
Financial strain (OR = 0.82, 95% CI = 0.77–0.88), food insecurity (OR = 0.87, 95% CI = 0.81–0.93) and transportation needs (OR = 0.81, 95% CI = 0.74–0.88) were each associated with lower odds of having one or more dental visits in the year following social needs assessment (Table 3).
Table 3.
Logistic regression results: association of individual social needs with dental utilization in 12 months post social needs assessment.
| Individual social need | OR | 95% CI | p-value |
|---|---|---|---|
| Financial strain | 0.82 | 0.77–0.88 | <0.0001 |
| Food insecurity | 0.87 | 0.81–0.93 | 0.0001 |
| Housing instability | 0.94 | 0.87–1.02 | NS* |
| Transportation needs | 0.81 | 0.74–0.88 | <0.0001 |
Logistic regression model adjusted for age, sex, race/ethnicity, ADI, CCI, prior dental utilization, prior primary care utilization, prior ED utilization and prior hospital admissions.
*Not statistically significant at the p < 0.05 level.
Bolded text indicates statistically significant association between social needs and dental utilization.
3.4. Logistic regression results: association of count of individual social needs with dental care utilization in 12 months post social needs assessment
Compared to having no social needs, having one social need (OR = 0.77, 95% CI = 0.73–0.82), two social needs (OR = 0.74, 95% CI = 0.69–0.79) and three or more social needs (OR = 0.63, 95% CI = 0.58–0.69) were all strongly associated with lower odds of having any dental visit (Table 4). Each additional social need lowered the odds of dental utilization in the following year.
Table 4.
Logistic regression results: association of count of individual social needs with dental utilization in 12 months post social needs assessment.
| Count of social needs | OR | 95% CI | p-value |
|---|---|---|---|
| None | 1.00 | NA | NA |
| One | 0.77 | 0.73–0.82 | <0.0001 |
| Two | 0.74 | 0.69–0.79 | <0.0001 |
| Three or more needs | 0.63 | 0.58–0.69 | <0.0001 |
Logistic regression model adjusted for age, sex, race/ethnicity, ADI, CCI, prior dental utilization, prior primary care utilization, prior ED utilization, and prior hospital admissions.
Bolded text indicates statistically significant association between social needs and dental utilization.
4. Discussion
We found that nearly 18% of our study population, age 18+ with dental and medical insurance coverage, reported one or more social needs, with about 10% reporting two or more social needs. The presence of financial strain, food insecurity and transportation needs were associated with lower odds of having any dental visits in the year after social needs assessment.
Our finding that financial strain was associated with lower use of dental care substantiates previous findings that affordability and cost serve as barriers to accessing dental care (10–12). Additionally, our study results support prior research indicating that food insecurity and transportation barriers are associated with lower use of dental care. Specifically, Wiener (2018) (14), Merchant (2024) (16) and Obeidat (2024) (15) found that food insecurity was associated with lower use of dental care services. Similarly, McKernan (2018) (19), Kim (2024) (18) and Obeidat (2024) (15) found that transportation barriers were associated with lower use of dental care. However, unlike previous research by Obeidat (2024) (15) and Yu (2025) (17) that found housing instability was associated with lower use of dental care, our study found no association between housing instability and dental care utilization.
Of critical importance, we also found a “dose-response” relationship between number of social needs and dental utilization, with each subsequent social need lowering the odds of a person having a dental visit. Consequently, multiple unmet social needs may create overlapping social barriers, draining a patient's time and resources, and forcing economic tradeoffs that may make routine or preventive dental care a lower priority.
Our study did have certain limitations. First, because the study is observational, we cannot establish a causal relationship between social needs and dental utilization. Second, results cannot be generalized outside of integrated health care systems. Third, because social needs data were self-reported, they may be subject to social desirability bias. Moreover, because the study population was mostly White, results cannot be generalized to populations that are more racially/ethnically diverse than the study population. Further, less information is known about whether the association of social needs and dental care utilization is similar in non-White patient populations. Last, results may not be applicable to non-insured populations.
These limitations notwithstanding, our study results have implications for policy and clinical practice. Although the associations of social needs with dental utilization are not causal, our results suggest that dental patients with financial strain, food insecurity and transportation needs may benefit from possible interventions to increase use of dental care. Possible interventions could include outreaching patients via a community health navigator to address social health needs such as, for example, financial strain. Community health navigators can help such patients apply for such services as medical financial assistance to reduce financial barriers to access needed dental services. Last, further research is needed to evaluate the effectiveness of interventions to target social needs and evaluate whether resolution of these needs is associated with increases in dental utilization.
Acknowledgments
We thank Jill Pope for reviewing the manuscript and Mary Early for providing administrative assistance in formatting the manuscript for publication.
Appendix A
Appendix A Description of Social Needs.
| Measure | Reponses below indicate “yes” response for social need |
|---|---|
| Financial strain (1 item) |
Ability to pay for basics such as food, housing, medical care, and heating rated as “very hard,” “hard” or “somewhat hard”. |
| Food insecurity (2 items) |
Rated the following as “sometimes true” or “often true”: In the past 12 months, 1) worried food would run out before more could be bought or 2) worried food bought would not last and did not have money to get more. |
| Housing instability (3 items) |
In the past 12 months (including now), any of the following three conditions occurred: 1) unable to pay the mortgage or rent on time, 2) lived in 3 or more places or 3) did not have a steady place to sleep or slept in a shelter. |
| Transportation needs (2 items) |
In the past 12 months, lack of transportation: 1) kept respondent from medical appointments or from getting medications or 2) kept respondent from meetings, work, or from getting things needed for daily living. |
Funding Statement
The author(s) declared that financial support was received for this work and/or its publication. Funding for this project was provided by Kaiser Permanente Northwest, which supports the Kaiser Permanente Center for Health Research Learning Health System team. Kaiser Permanente Northwest provided funding for the Learning Health System team to complete this study and manuscript.
Footnotes
Edited by: Ajesh George, Western Sydney University, Australia
Reviewed by: Yahya Alholimie, Prince Saud Bin Jalawi Hospital, Saudi Arabia
Girish Shelke, Choctaw Nation Ilc, United States
Data availability statement
The data analyzed in this study is subject to the following licenses/restrictions: Data is proprietary and not publicly available. Further queries should be directed to david.m.mosen@kpchr.org.
Ethics statement
The studies involving humans were approved by Kaiser Permanente Northwest Institutional Review Board (IRB). The studies were conducted in accordance with the local legislation and institutional requirements. The ethics committee/institutional review board waived the requirement of written informed consent for participation from the participants or the participants’ legal guardians/next of kin because data-only study that was minimal risk.
Author contributions
DM: Conceptualization, Writing – original draft. MB: Writing – review & editing. AV: Data curation, Formal analysis, Writing – review & editing. DP: Writing – review & editing. BE-B: Writing – review & editing. JD: Writing – review & editing.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declared that generative AI was not used in the creation of this manuscript.
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References
- 1.Taylor KK, Neiman PU, Bonner S, Ranganathan K, Tipirneni R, Scott JW. Unmet social health needs as a driver of inequitable outcomes after surgery: a cross-sectional analysis of the national health interview survey. Ann Surg. (2023) 278(2):193–200. 10.1097/sla.0000000000005689 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.United States Department of Health and Human Services OoDPaHP. Social Determinants of Health - Healthy People 2030 (n.d.). Available online at: https://odphp.health.gov/healthypeople/priority-areas/social-determinants-health (Accessed April 16, 2026).
- 3.Heller CG, Rehm CD, Parsons AH, Chambers EC, Hollingsworth NH, Fiori KP. The association between social needs and chronic conditions in a large, urban primary care population. Prev Med. (2021) 153:106752. 10.1016/j.ypmed.2021.106752 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Vrtikapa K, Hoque Urmy F, Hoque F. Social determinants of health: the impact of this overlooked vital sign. J Brown Hosp Med. (2025) 4(3):138072. 10.56305/001c.138072 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Fiori KP, Heller CG, Rehm CD, Parsons A, Flattau A, Braganza S, et al. Unmet social needs and no-show visits in primary care in a US northeastern urban health system, 2018–2019. Am J Public Health. (2020) 110(S2):S242–50. 10.2105/ajph.2020.305717 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Poleshuck E, Possemato K, Johnson EM, Cohen AJ, Fogarty CT, Funderburk JS. Leveraging integrated primary care to address patients’ and families’ unmet social needs: aligning practice with National Academy of Sciences, Engineering and Medicine recommendations. J Am Board Fam Med. (2022) 35(1):185–9. 10.3122/jabfm.2022.01.210287 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Mohd Khairuddin AN, Bogale B, Kang J, Gallagher JE. Impact of dental visiting patterns on oral health: a systematic review of longitudinal studies. BDJ Open. (2024) 10(1):18. 10.1038/s41405-024-00195-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Fu D, Shu X, Zhou GM, Liao G, Zou L. Connection between oral health and chronic diseases. Med Comm. (2025) 6(1):e70052. 10.1002/mco2.70052 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.D'Aiuto F, Suvan J, Siripaiboonpong N, Gatzoulis MAD, Aiuto F. The root of the matter: linking oral health to chronic diseases prevention. Int J Cardiol Congenit Heart Dis. (2025) 19:100574. 10.1016/j.ijcchd.2025.100574 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Vujicic M, Buchmueller T, Klein R. Dental care presents the highest level of financial barriers, compared to other types of health care services. Health Aff (Millwood). (2016) 35(12):2176–82. 10.1377/hlthaff.2016.0800 [DOI] [PubMed] [Google Scholar]
- 11.Flynn B, Starkel Weninger R, Zaborowski M, Vujicic M. Barriers to Dental Care among Adult Medicaid Beneficiaries Chicago, IL (2024). Available online at: https://www.ada.org/-/media/project/ada-organization/ada/ada-org/files/resources/research/hpi/barriers_Medicaid_participation_utilization.pdf (Accessed April 16, 2026).
- 12.The Commonwealth Fund. Medicare Beneficiaries with Dental Insurance Face Care Barriers (2025). Available online at: https://www.commonwealthfund.org/blog/2025/many-medicare-beneficiaries-dental-insurance-face-financial-barriers-care (Accessed June 29, 2026).
- 13.Velez M, Buto PT, Pederson AM, Weuve J, Murchland AR, Wang J, et al. Associations of unmet dental care needs due to cost with incident cardiovascular disease and dementia: a prospective study in the all of US cohort. J Gerontol A Biol Sci Med Sci. (2026) 81(4):glag023. 10.1093/gerona/glag023 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Wiener RC, Sambamoorthi U, Shen C, Alwhaibi M, Findley P. Food security and unmet dental care needs in adults in the United States. J Dent Hyg. (2018) 92(3):14–22. [PMC free article] [PubMed] [Google Scholar]
- 15.Obeidat R, Heaton LJ, Tranby EPO, Malley J, Timothé P. Social determinants of health linked with oral health in a representative sample of U.S. adults. BMC Oral Health. (2024) 24(1):1518. 10.1186/s12903-024-05257-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Merchant AT, Fallahi A, Huda A, Lohman M. Food insecurity and oral health in older adults. Front Oral Health. (2024) 5:1400591. 10.3389/froh.2024.1400591 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Yu YH. Access to oral health care and its social determinants across the lifespan in the United States. Front Oral Health. (2025) 6:1619983. 10.3389/froh.2025.1619983 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Kim J, Roy I, Martinez-Mier EA, Shukla A, Weir P. Impact of lack of transportation on access to dental care. Heliyon. (2024) 10(23):e40657. 10.1016/j.heliyon.2024.e40657 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.McKernan SC, Reynolds JC, Ingleshwar A, Pooley M, Kuthy RA, Damiano PC. Transportation barriers and use of dental services among Medicaid-insured adults. JDR Clin Trans Res. (2018) 3(1):101–8. 10.1177/2380084417714795 [DOI] [PubMed] [Google Scholar]
- 20.Mosen DM, Banegas MP, Dickerson JF, Fellows JL, Brooks NB, Pihlstrom DJ, et al. Examining the association of medical-dental integration with closure of medical care gaps among the elderly population. J Am Dent Assoc. (2021) 152(4):302–8. 10.1016/j.adaj.2020.12.010 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Mosen DM, Banegas MP, Dickerson JF, Fellows JL, Pihlstrom DJ, Kershah HM, et al. Evaluating the effectiveness of medical-dental integration to close preventive and disease management care gaps. Front Dent Med. (2021) 2:670012. 10.3389/fdmed.2021.670012 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Hahn EA, DeWalt DA, Bode RK, Garcia SF, DeVellis RF, Correia H, et al. New English and Spanish social health measures will facilitate evaluating health determinants. Health Psychol. (2014) 33(5):490–9. 10.1037/hea0000055 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Cella D, Riley W, Stone A, Rothrock N, Reeve B, Yount S, et al. The patient-reported outcomes measurement information system (PROMIS) developed and tested its first wave of adult self-reported health outcome item banks: 2005–2008. J Clin Epidemiol. (2010) 63(11):1179–94. 10.1016/j.jclinepi.2010.04.011 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Posner BM, Jette AM, Smith KW, Miller DR. Nutrition and health risks in the elderly: the nutrition screening initiative. Am J Public Health. (1993) 83(7):972–8. 10.2105/AJPH.83.7.972 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Puterman E, Haritatos J, Adler NE, Sidney S, Schwartz JE, Epel ES. Indirect effect of financial strain on daily cortisol output through daily negative to positive affect Index in the coronary artery risk development in young adults study. Psychoneuroendocrinology. (2013) 38(12):2883–9. 10.1016/j.psyneuen.2013.07.016 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.National Association of Community Health Centers. Association of Asian Pacific Community Health Organizations, Oregon Primary Care Association, and Institute for Alternative Futures. The Protocol for Responding to and Assessing Patients’ Assets, Risks, and Experiences (Prapare) (2023). Available online at: https://prapare.org/ (Accessed May 26, 2023).
- 27.Childrens Health Watch. Housing Instability: A New Screen for Adverse Health Issues for Caregivers and Children (2018). Available online at: https://childrenshealthwatch.org/housing-instability-a-new-screen-for-adverse-health-issues-for-caregivers-and-children/ (Accessed May 26, 2023).
- 28.Hall MH, Matthews KA, Kravitz HM, Gold EB, Buysse DJ, Bromberger JT, et al. Race and financial strain are independent correlates of sleep in midlife women: the swan sleep study. Sleep. (2009) 32(1):73–82. [PMC free article] [PubMed] [Google Scholar]
- 29.Hager ER, Quigg AM, Black MM, Coleman SM, Heeren T, Rose-Jacobs R, et al. Development and validity of a 2-item screen to identify families at risk for food insecurity. Pediatrics. (2010) 126(1):e26–32. 10.1542/peds.2009-3146 [DOI] [PubMed] [Google Scholar]
- 30.Mosen DM, Fitzpatrick SL, Keast EM, Dickerson JF, Ertz-Berger BL, Banegas MP. Association of social needs with diabetes outcomes in an older population. J Am Board Fam Med. (2025) 38(1):125–32. 10.3122/jabfm.2024.240139R2 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Mosen DM, Banegas MP, Keast EM, Dickerson JF. Examining the association of social needs with future health care utilization in an older adult population: which needs are most important? Popul Health Manag. (2023) 26(6):413–9. 10.1089/pop.2023.0171 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Tuliani TA, Shenoy M, Parikh M, Jutzy K, Hilliard A. Impact of area deprivation index on coronary stent utilization in a Medicare nationwide cohort. Popul Health Manag. (2017) 20(4):329–34. 10.1089/pop.2016.0086 [DOI] [PubMed] [Google Scholar]
- 33.Kieszak SM, Flanders WD, Kosinski AS, Shipp CC, Karp H. A comparison of the charlson comorbidity index derived from medical record data and administrative billing data. J Clin Epidemiol. (1999) 52(2):137–42. 10.1016/s0895-4356(98)00154-1 [DOI] [PubMed] [Google Scholar]
- 34.Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with icd-9-cm administrative databases. J Clin Epidemiol. (1992) 45(6):613–9. 10.1016/0895-4356(92)90133-8 [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data analyzed in this study is subject to the following licenses/restrictions: Data is proprietary and not publicly available. Further queries should be directed to david.m.mosen@kpchr.org.