The relationship between preventive dental care and overall medical expenditures.

OBJECTIVES: To examine the relationship between preventive dental visits (PDVs) and medical expenditures while mitigating bias from unobserved confounding factors. STUDY DESIGN: Retrospective data analysis of Indiana Medicaid enrollment and claims data (2015-2018) and the Area Health Resources Files. METHODS: An instrumental variable (IV) approach was used to estimate the relationship between PDVs and medical and pharmacy expenditures among Medicaid enrollees. The instrument was defined as the number of adult enrollees with at least 1 nonpreventive dental claim per total Medicaid enrollees within a Census tract per year. RESULTS: In naive analyses, enrollees had on average greater medical expenditures if they had a prior-year PDV (ß = $397.21; 95% CI, $184.23-$610.18) and a PDV in the same year as expenditures were measured (ß = $344.81; 95% CI, $193.06-$496.56). No significant differences in pharmacy expenditures were observed in naive analyses. Using the IV approach, point estimates of overall medical expenditures for the marginal enrollee who had a prior-year PDV (ß = $325.17; 95% CI, -$708.03 to $1358.37) or same-year PDV (ß = $170.31; 95% CI, -$598.89 to $939.52) were similar to naive results, although not significant. Our IV approach indicated that PDV was not endogenous in some specifications. CONCLUSIONS: This is the first study to present estimates with causal inference from a quasi-experimental study of the effect of PDVs on overall medical expenditures. We observed that prior- or same-year PDVs were not related to overall medical or pharmacy expenditures.

Does preventive dental care reduce nonpreventive dental visits and expenditures among Medicaid-enrolled adults?

OBJECTIVE: To determine whether preventive dental visits are associated with fewer subsequent nonpreventive dental visits and lower dental expenditures. DATA SOURCES: Indiana Medicaid enrollment and claims data (2015-2018) and the Area Health Resource File. STUDY DESIGN: A repeated measures design with individual and year fixed effects examining the relationship between preventive dental visits (PDVs) and nonpreventive dental visits (NPVs) and dental expenditures. DATA COLLECTION/EXTRACTION METHODS: Not applicable. PRINCIPAL FINDINGS: Of 28,152 adults (108,349 observation-years) meeting inclusion criteria, 36.0% had a dental visit, 27.8% a PDV, and 22.1% a NPV. Compared to no PDV in the prior year, at least one was associated with fewer NPVs (ß = -0.13; 95% CI -0.12, -0.11), lower NPV expenditures (ß = -$29.12.53; 95% CI -28.07, -21.05), and lower total dental expenditures (-$70.12; 95% -74.92, -65.31), as well as fewer PDVs (ß = -0.24; 95% CI -0.26, -0.23). CONCLUSIONS: Our findings suggest that prior year PDVs are associated with fewer subsequent NPVs and lower dental expenditures among Medicaid-enrolled adults. Thus, from a public insurance program standpoint, supporting preventive dental care use may translate into improved population oral health outcomes and lower dental costs among certain low-income adult populations, but barriers to consistent utilization of PDV prohibit definitive findings.

Prevalence of and factors associated with unmet dental need among the US adult population in 2016.

OBJECTIVES: Understanding and addressing contributing factors to unmet dental need is an important public health challenge. This study investigated the prevalence of, and factors associated with, self-reported unmet dental need using a nationally representative sample of US adults. METHODS: This was a cross-sectional study using the Medical Expenditures Panel Survey (MEPS) from 2016. The weighted prevalence of unmet dental need was estimated among individuals aged 18 years or older. Chi-squared and multivariate logit regression with marginal effects (ie absolute risk differences) were used to measure the association of unmet dental need with respondent characteristics. RESULTS: The prevalence of adults reporting unmet dental need was 6% (95% CI: 5.5 to 6.5). Adults with dental insurance were 1.7 percentage points (95% CI: -2.8 to -0.6) less likely to report unmet dental needs than adults without dental insurance. Those with middle income were 2.3 percentage points (95% CI: 1.2 to 3.4), those with low income were 3.3 percentage points (95% CI: 1.7 to 5.0), and those with poor/negative/near-poor income were 4.2 percentage points (95% CI: 2.7 to 5.7) more likely to report an unmet dental need than adults with high income. Both Hispanics (-1.7 percentage points [95% CI: -2.8 to -0.6]) and non-Hispanic Blacks (-1.1 percentage points [95% CI: -2.1 to -0.1]) were less likely to report an unmet dental need than whites. Smoking, education, general health status, chronic disease and marital status were also significantly associated with reporting an unmet dental need. CONCLUSIONS: Future policies should continue to address cost and coverage barriers to adult dental care, as these remain significant barriers to access, particularly for low-income adults. Future research should evaluate the reasons adults report unmet dental need and explore how adults' judgment of dental need compares to providers' clinical judgment. Additionally, research that explores how race and ethnicity affect perceptions of unmet dental need is warranted.

Cost-effectiveness of CYP2C19-guided antiplatelet therapy in patients with acute coronary syndrome and percutaneous coronary intervention informed by real-world data.

Current guidelines recommend dual antiplatelet therapy (DAPT) consisting of aspirin and a P2Y12 inhibitors following percutaneous coronary intervention (PCI). CYP2C19 genotype can guide DAPT selection, prescribing ticagrelor or prasugrel for loss-of-function (LOF) allele carriers (genotype-guided escalation). Cost-effectiveness analyses (CEA) are traditionally grounded in clinical trial data. We conduct a CEA using real-world data using a 1-year decision-analytic model comparing primary strategies: universal empiric clopidogrel (base case), universal ticagrelor, and genotype-guided escalation. We also explore secondary strategies commonly implemented in practice, wherein all patients are prescribed ticagrelor for 30 days post PCI. After 30 days, all patients are switched to clopidogrel irrespective of genotype (nonguided de-escalation) or to clopidogrel only if patients do not harbor an LOF allele (genotype-guided de-escalation). Compared with universal clopidogrel, both universal ticagrelor and genotype-guided escalation were superior with improvement in quality-adjusted life years (QALY's). Only genotype-guided escalation was cost-effective ($42,365/QALY) and demonstrated the highest probability of being cost-effective across conventional willingness-to-pay thresholds. In the secondary analysis, compared with the nonguided de-escalation strategy, although genotype-guided de-escalation and universal ticagrelor were more effective, with ICER of $188,680/QALY and $678,215/QALY, respectively, they were not cost-effective. CYP2C19 genotype-guided antiplatelet prescribing is cost-effective compared with either universal clopidogrel or universal ticagrelor using real-world implementation data. The secondary analysis suggests genotype-guided and nonguided de-escalation may be viable strategies, needing further evaluation.

Effect on Health Care Expenditures During Nationwide Implementation of the Diabetes Prevention Program as a Health Insurance Benefit.

OBJECTIVE: Lifestyle interventions slow development of type 2 diabetes by half, but the impact of health payer reimbursement for delivery of intervention programs is not well known. We evaluated net commercial health payer expenditures when offering reimbursement for access to YMCA's Diabetes Prevention Program (YDPP) in 42 states. RESEARCH DESIGN AND METHODS: We used a nonequivalent comparison group design to evaluate net health care expenditures for adults with prediabetes who attended one or more YDPP visit between 1 July 2009 and 31 May 2013 ("YDPP users"). Rolling, 1:1 nearest neighbor propensity score (PS) matching was used to identify a comparison group of nonusers. Administrative data provided measures of YDPP attendance, body weight at YDPP visits, and health care expenditures. Random effects, difference-in-difference regression was used to estimate quarterly health care expenditures before and after participants' first visit to YDPP. RESULTS: Worksite screening identified 9.7% of the target population; 39.1% of those identified (19,933 participants through June 2015) became YDPP users. Mean weight loss for YDPP users enrolled before June 2013 (n = 1,725) was 7.5 lb (3.4%); 29% achieved ≥5% weight loss. Inclusive of added costs to offer YDPP, there were no statistically significant differences in mean per-person net health care expenditures between YDPP users and PS-matched nonusers over 2 years ($0.2 lower [95% CI $56 lower to $56 higher]). Mean reimbursement to the YMCA was $212 per YDPP user, with 92.8% of all expenditures made for those who attended at a high rate (≥9 completed YDPP visits). CONCLUSIONS: Worksite screening was inefficient for identifying the population with prediabetes, but those identified achieved modest YDPP attendance and clinically meaningful weight loss. Over 2 years, added costs to offer the intervention were modest, with neutral effects on net health care costs.

Graduation and Academic Placement of Underrepresented Racial/Ethnic Minority Doctoral Recipients in Public Health Disciplines, United States, 2003-2015.

OBJECTIVES: Given public health's emphasis on health disparities in underrepresented racial/ethnic minority communities, having a racially and ethnically diverse faculty is important to ensure adequate public health training. We examined trends in the number of underrepresented racial/ethnic minority (ie, non-Hispanic black, Hispanic, American Indian/Alaska Native, Native Hawaiian, and Pacific Islander) doctoral graduates from public health fields and determined the proportion of persons from underrepresented racial/ethnic minority groups who entered academia. METHODS: We analyzed repeated cross-sectional data from restricted files collected by the National Science Foundation on doctoral graduates from US institutions during 2003-2015. Our dependent variables were the number of all underrepresented racial/ethnic minority public health doctoral recipients and underrepresented racial/ethnic minority graduates who had accepted academic positions. Using logistic regression models and adjusted odds ratios (aORs), we examined correlates of these variables over time, controlling for all independent variables (eg, gender, age, relationship status, number of dependents). RESULTS: The percentage of underrepresented racial/ethnic minority doctoral graduates increased from 15.4% (91 of 592) in 2003 to 23.4% (296 of 1264) in 2015, with the largest increase occurring among black graduates (from 6.6% in 2003 to 14.1% in 2015). Black graduates (310 of 1241, 25.0%) were significantly less likely than white graduates (2258 of 5913, 38.2%) and, frequently, less likely than graduates from other underrepresented racial/ethnic minority groups to indicate having accepted an academic position (all P < .001). CONCLUSIONS: Stakeholders should consider targeted programs to increase the number of racial/ethnic minority faculty members in academic public health fields.

Lessons Learned When Introducing Pharmacogenomic Panel Testing into Clinical Practice.

OBJECTIVES: Implementing new programs to support precision medicine in clinical settings is a complex endeavor. We describe challenges and potential solutions based on the Indiana GENomics Implementation: an Opportunity for the Underserved (INGenious) program at Eskenazi Health-one of six sites supported by the Implementing GeNomics In pracTicE network grant of the National Institutes of Health/National Human Genome Research Institute. INGenious is an implementation of a panel of genomic tests. METHODS: We conducted a descriptive case study of the implementation of this pharmacogenomics program, which has a wide scope (14 genes, 27 medications) and a diverse population (patients who often have multiple chronic illnesses, in a large urban safety-net hospital and its outpatient clinics). CHALLENGES: We placed the clinical pharmacogenomics implementation challenges into six categories: patient education and engagement in care decision making; clinician education and changes in standards of care; integration of technology into electronic health record systems; translational and implementation sciences in real-world clinical environments; regulatory and reimbursement considerations, and challenges in measuring outcomes. A cross-cutting theme was the need for careful attention to workflow. Our clinical setting, a safety-net health care system, presented some distinctive challenges. Patients often had multiple chronic illnesses and sometimes were taking more than one pharmacogenomics-relevant medication. Reaching patients for recruitment or follow-up was another challenge. CONCLUSIONS: New, large-scale endeavors in health care are challenging. A description of the challenges that we encountered and the approaches that we adopted to address them may provide insights for those who implement and study innovations in other health care systems.

Designing a natural experiment to evaluate a national health care-community partnership to prevent type 2 diabetes.

To address the growing incidence of type 2 diabetes in the United States, UnitedHealth Group, the YMCA of the USA, and the Centers for Disease Control and Prevention have partnered to bring a group-based adaptation of the Diabetes Prevention Program lifestyle intervention to a national scale. Researchers at Northwestern and Indiana universities are collaborating with these partners to design a robust evaluation of the reach, effectiveness, and costs of this natural experiment. We will employ a quasi-experimental, cluster-randomized study design and combine administrative, clinical, and programmatic data from existing sources to derive reliable, timely, and policy-relevant estimates of the program's impact and potential for sustainability. In this context, evaluation results will provide information about the unique role of a health care-community partnership to prevent type 2 diabetes.

Can lay health workers promote better medical self-management by persons living with HIV? An evaluation of the Positive Choices program.

OBJECTIVE: To evaluate Positive Choices (PC), a program that employed lay health workers to motivate antiretroviral adherence among persons living with HIV with coverage from Indiana's high-risk insurance pool. METHODS: Four hundred and forty nine participants living in the greater Indianapolis area were randomly allocated to treatment (n = 91) or control (n = 358) groups and followed for one year. RESULTS: Compared to control subjects, PC subjects were more likely to adhere to HIV medications (medication possession ratio adherence ≥ 0.95, OR = 1.83, p = 0.046), and to achieve undetectable viral load (<50 copies/mL, OR = 2.01, p = 0.011) in the 12 months following introduction of PC. There were no significant differences observed between groups in any of self-reported health status indicators. CONCLUSION: Estimates suggest that PC clients were 16% more likely to have undetectable viral loads than clients in standard care. The incremental program cost was approximately $10,000 for each additional person who achieved an undetectable viral load. PRACTICE IMPLICATIONS: As persons living with HIV experience greater longevity and healthcare reform expands coverage to these high-risk populations, greater demands will be placed on the HIV-care workforce. Results suggest lay health workers may serve as effective adjuncts to professional care providers.

Case finding with incomplete administrative data: observations on playing with less than a full deck.

Capacity constraints and efficiency considerations require that disease management programs identify patients most likely to benefit from intervention. Predictive modeling with available administrative data has been used as a strategy to match patients with appropriate interventions. Administrative data, however, can be plagued by problems of incompleteness and delays in processing. In this article, we examine the effects of these problems on the effectiveness of using administrative data to identify suitable candidates for disease management, and we evaluate various proposed solutions. We build prospective models using regression analysis and evaluate the resulting stratification algorithms using R² statistics, areas under receiver operator characteristic curves, and cost concentration ratios. We find delays in receipt of data reduce the effectiveness of the stratification algorithm, but the degree of compromise depends on what proportion of the population is targeted for intervention. Surprisingly, we find that supplementing partial data with a longer panel of more outdated data produces algorithms that are inferior to algorithms based on a shorter window of more recent data. Demographic data add little to algorithms that include prior claims data, and are an inadequate substitute when claims data are unavailable. Supplementing demographic data with additional information on self-reported health status improves the stratification performance only slightly and only when disease management is targeted to the highest risk patients. We conclude that the extra costs associated with surveying patients for health status information or retrieving older claims data cannot be justified given the lack of evidence that either improves the effectiveness of the stratification algorithm.

The structure and content of telephonic scripts found useful in a Medicaid Chronic Disease Management Program.

In 2003, the Indiana Office of Medicaid Policy and Planning launched the Indiana Chronic Disease Management Program (ICDMP), a programme intended to improve the health and healthcare utilization of 15,000 Aged, Blind and Disabled Medicaid members living with diabetes and/or congestive heart failure in Indiana. Within ICDMP, programme components derived from the Chronic Care Model and education based on an integrated theoretical framework were utilized to create a telephonic care management intervention that was delivered by trained, non-clinical Care Managers (CMs) working under the supervision of a Registered Nurse. CMs utilized computer-assisted health education scripts to address clinically important topics, including medication adherence, diet, exercise and prevention of disease-specific complications. Employing reflective listening techniques, barriers to optimal self-management were assessed and members were encouraged to engage in health-improving actions. ICDMP evaluation results suggest that this low-intensity telephonic intervention shifted utilization and lowered costs. We discuss this patient-centred method for motivating behaviour change, the theoretical constructs underlying the scripts and the branched-logic format that makes them suitable to use as a computer-based application. Our aim is to share these public-domain materials with other programmes.

The Indiana Chronic Disease Management Program's impact on medicaid claims: a longitudinal, statewide evaluation.

BACKGROUND: : Disease management programs have grown in popularity over the past decade as a strategy to curb escalating healthcare costs for persons with chronic diseases. OBJECTIVES: : To evaluate the effect of the Indiana Chronic Disease Management Program (ICDMP) on the longitudinal changes in Medicaid claims statewide. RESEARCH DESIGN: : Phased implementation of a chronic disease management program in 3 regions of the state. Fourteen repeated cohorts of Medicaid members were drawn over a period of 3.5 years and the trends in claims were evaluated using a repeated measures model. SUBJECTS: : A total of 44,218 Medicaid members with diabetes and/or congestive heart failure in 3 geographic regions in Indiana. RESULTS: : Across all 3 regions and both disease classes, we found a flattening of cost trends between the pre- and post-ICDMP-initiation periods. This change in the slopes was significant for all of the models except for congestive heart failure in southern Indiana. Thus, the average per member claims paid was increasing at a faster rate before ICDMP but slowed once the program was initiated. To distinguish shorter and longer-term effects related to ICDMP, we estimated annual slopes within the pre- and post-ICDMP- time periods. A similar pattern was found in all regions: claims were increasing before ICDMP, flattened in the years around program initiation, and remained flat in the final year of follow-up. CONCLUSIONS: : This analysis shows that the trend in average total claims changed significantly after the implementation of ICDMP, with a decline in the rate of increase in claims paid observed for targeted Medicaid program populations across the state of Indiana.

An evaluation of educational outreach to improve evidence-based prescribing in Medicaid: a cautionary tale.

RATIONALE, AIMS AND OBJECTIVES: Evidence suggests that educational outreach ('academic detailing') improves evidence-based prescribing. We evaluated the impact of an academic detailing programme intended to increase new statin prescriptions. METHODS: In a 2 x 2 factorial design we evaluated the effect of an academic detailing programme with/without telephonic care management for patients. Eligible patients were continuously enrolled Medicaid members at high risk for cardiovascular disease utilization who were not receiving statin medication in the 18 months prior to the intervention. All primary care prescribers assigned to these patients were randomized by clinic to academic detailing. Two trained nurses provided the detailing to prescribers, including specific discussion about the use of statins in this high-risk patient population. Nurses left the prescribers with a summary of clinical practice guidelines, a one-page detailing sheet and a list of patients under the care of the prescriber who were candidates for statins. The primary outcome was the incidence of a new statin prescription claim during the 6-month intervention period and the subsequent 6 months. Logistic regression models were used to estimate main effects of the interventions and to adjust for potential confounding variables in the study. RESULTS: Forty-eight clinics were randomized, effectively randomizing a total of 284 patients and 128 prescribers. Among the 284 patients, 46 (16%) received a new statin claim during the evaluation period. Controlling for significant bivariate associations, the academic detailing intervention had no significant effect on new statin prescriptions compared with the control group (odds ratio = 0.8, 95% confidence interval: 0.4-1.6, P = 0.5). CONCLUSION: Among this Medicaid population at high risk for cardiovascular events, an academic detailing programme to increase statin prescriptions was not effective. To assist others to learn from our failed effort, we identify and discuss critical elements in the design and implementation of the programme that could account for these results.

The net fiscal impact of a chronic disease management program: Indiana Medicaid.

In 2003 the Indiana Office of Medicaid Policy and Planning implemented the Indiana Chronic Disease Management Program (ICDMP). This paper reports on the fiscal impact of the ICDMP from the state's perspective, as estimated from the outcomes of a randomized trial. Medicaid members with congestive heart failure (CHF) or diabetes, or both, were randomly assigned by practice site to chronic disease management services or standard care. The effect of the ICDMP varied by disease group and risk class: while cost savings were achieved in the CHF subgroup, disease management targeted to patients with only diabetes resulted in no significant fiscal impact.

The Indiana Chronic Disease Management Program.

The Indiana Chronic Disease Management Program (ICDMP) is intended to improve the quality and cost-effectiveness of care for Medicaid members with congestive heart failure (chronic heart failure), diabetes, asthma, and other conditions. The ICDMP is being assembled by Indiana Medicaid primarily from state and local resources and has seven components: (1) identification of eligible participants to create regional registries, (2) risk stratification of eligible participants, (3) nurse care management for high-risk participants, (4) telephonic intervention for all participants, (5) an Internet-based information system, (6) quality improvement collaboratives for primary care practices, and (7) program evaluation. The evaluation involves a randomized controlled trial in two inner-city group practices, as well as a statewide observational design. This article describes the ICDMP, highlights challenges, and discusses approaches to its evaluation.

Telephonic case-finding of major depression in a Medicaid chronic disease management program for diabetes and heart failure.

OBJECTIVE: Major depression is common in low-income and chronically ill persons and is a barrier for effective chronic disease care. We evaluated a Medicaid-sponsored strategy for detecting depressive symptoms in adults with diabetes or congestive heart failure. METHODS: Using a two-item screening tool, 890 adults enrolled in the Indiana Chronic Disease Management Program were assessed by telephone for depressive symptoms between December 2003 and March 2004. A subset of 386 participants also completed the eight-item Patient Health Questionnaire (PHQ-8) depression measure. Antidepressant use was examined using pharmacy claims. RESULTS: Depressed mood or anhedonia was reported by 51% of participants. About one in four participants had a PHQ-8 score indicating a high risk for major depression (score >or=10). The two-item screen was 96% sensitive [95% confidence interval (CI), 89-99%] and 60% specific (95% CI, 54-65%) for identifying members at high risk for depression by the full PHQ-8 instrument. Only half of participants with high-risk PHQ-8 scores had a pharmacy claim indicating that an antidepressant medication was filled within 120 days of the depression screening. CONCLUSIONS: A two-stage, telephonic approach involving the PHQ-8 instrument for Medicaid members with either depressed mood or anhedonia could identify two clinically depressed persons for every nine members screened.

Indiana chronic disease management program risk stratification analysis.

OBJECTIVE: The objective of this study was to compare the ability of risk stratification models derived from administrative data to classify groups of patients for enrollment in a tailored chronic disease management program. SUBJECTS: This study included 19,548 Medicaid patients with chronic heart failure or diabetes in the Indiana Medicaid data warehouse during 2001 and 2002. MEASURES: To predict costs (total claims paid) in FY 2002, we considered candidate predictor variables available in FY 2001, including patient characteristics, the number and type of prescription medications, laboratory tests, pharmacy charges, and utilization of primary, specialty, inpatient, emergency department, nursing home, and home health care. METHODS: We built prospective models to identify patients with different levels of expenditure. Model fit was assessed using R statistics, whereas discrimination was assessed using the weighted kappa statistic, predictive ratios, and the area under the receiver operating characteristic curve. RESULTS: We found a simple least-squares regression model in which logged total charges in FY 2002 were regressed on the log of total charges in FY 2001, the number of prescriptions filled in FY 2001, and the FY 2001 eligibility category, performed as well as more complex models. This simple 3-parameter model had an R of 0.30 and, in terms in classification efficiency, had a sensitivity of 0.57, a specificity of 0.90, an area under the receiver operator curve of 0.80, and a weighted kappa statistic of 0.51. CONCLUSION: This simple model based on readily available administrative data stratified Medicaid members according to predicted future utilization as well as more complicated models.

Adjusting for patient characteristics and selection effects in assessment of community mental health centers.

OBJECTIVE: The objective of this study was to determine the effect of patient socioeconomic characteristics and center selection of patients on measured performance of community mental health centers. DATA SOURCE/STUDY SETTING: Data were taken from the administrative records of Indiana's public mental health system for 16,516 adults with severe, persistent mental illness treated in 30 community mental health centers. Center performance was compared using longitudinal information on patient functioning. METHODS: A mixed random-effects model that is suitable for fitting data with a hierarchical structure was used to assess relative performance. PRINCIPAL FINDINGS: Measured performance was found to depend significantly on patient education, income, marital status, race, ethnicity, and baseline health (P<0.05). Results also indicated centers that were more successful at maintaining patients in treatment were unfairly underranked by unadjusted performance scores. CONCLUSIONS: Both the socioeconomic background of patients and patient selection by centers impact apparent performance in community mental health care. If observational data are used to evaluate community-based providers, analysts might need to account for both effects to ensure comparisons of relative performance are accurate.

Performance assessment in community mental health care and at-risk populations.

We examine whether community mental health care centers (CMHCs) differ in their ability to serve at-risk populations, including clients with dual diagnoses for substance abuse, comorbid disabilities, and particularly severe functional impairment. Our analysis uses data from Indiana's public mental health system. Although at-risk clients experience, on average, worse outcomes than other clients, we find that some CMHCs achieve statistically significantly better outcomes than others. Although this information is useful to consumers and providers who wish to identify the most effective providers and treatment models for at-risk clients, it is not generated in standard performance assessments.