Changes In Medical Utilization Research Articles

The impact of a payer-provider joint venture on healthcare value.

To examine how a novel payer-provider joint venture (JV) between one payer and multiple competitive delivery systems in New Hampshire (NH), which included value-based payment, care management, and non-financial supports, impacted healthcare value and payer and provider group experiences. We conducted a mixed-methods study. We used a quasi-experimental longitudinal difference-in-differences design to examine the impact of the JV (which started in January 2016 and ended in December 2020) on healthcare utilization, quality, and spending, using members in Maine (ME) as a control group. We also analyzed patient uptake of the JV's care management program using routinely collected administrative data and assessed payer and provider group leaders' perspectives about the JV via semi-structured interviews. We used administrative and claims data from 2013 to 2019 in a commercially insured population under 65 years in NH and ME. We also used administrative data on care management eligibility and uptake and conducted semi-structured interviews with payer and provider group leaders affiliated with the JV. The JV was associated with no sustained change in medical utilization, quality, and spending throughout the study period. In the first year of the JV, there was a $142 (95% confidence interval: $41, $243) increase in pharmaceutical spending per member and a 13% (4.4%, 25%) relative increase in days covered for diabetes medications. Only 15% of eligible members engaged in care management, which was a key component of the JV's multi-pronged approach. In a disconnect from the empirical findings, payer and provider group leaders believed that the JV reduced healthcare costs and improved quality. Our findings provide evidence for future payer-provider JVs and demonstrate the importance of having a valid control group when evaluating JVs and value-based payment arrangements.

Increased medical utilization and psychiatric comorbidity following a new diagnosis of methamphetamine use disorder

ABSTRACT Background: Evidence of patterns of medical utilization and distribution of comorbidities among individuals using methamphetamine remains limited Objective: This study aims to investigate changes in medical utilization and comorbidities before and after a diagnosis of methamphetamine use disorder. Methods: A total of 3321 cases (79% were male) of methamphetamine use disorder between January 1, 1996, and December 31, 2012, were identified from Psychiatric Inpatient Medical Claims database in Taiwan. Information was collected on demographics, diagnoses, and medical utilizations. The date of newly diagnosed with methamphetamine use disorder was defined as the baseline. Mirror-image study design was used to compare changes in medical utilization and comorbidities between the pre-baseline period (within 1 year before diagnosis) and the post-baseline period (within 1 year after diagnosis). Conditional logistic regression was used to estimate changes in medical utilization and comorbidities. Results: Most cases (77%) were first identified in a psychiatric department. There is a significant increase (P < .001) in psychiatric admission (odds ratio[OR] = 2.19), psychiatric emergency visits (OR = 1.31), and psychiatric outpatient visits (OR = 1.15) after diagnosis. Multivariable analysis revealed significantly increased risks (P < .001) of non-methamphetamine drug induced mental disorders (adjusted OR[aOR] = 29.47), schizophrenia (aOR = 2.62), bipolar disorder (aOR = 2.14), organic mental disorder (aOR = 1.82), and upper respiratory tract infection (aOR = 2.03) after diagnosis. Conclusions: We found significant increases of medical utilization and psychiatric comorbidities after diagnosed with methamphetamine use disorder. These findings may reflect the problem of delayed diagnosis and treatment. Enhancement of early identification of methamphetamine use disorder in general practice is required for early intervention and decreased subsequent morbidities.

Nationwide Analysis of Changes in Medical Utilization Before and After a New Panic Disorder Diagnosis.

Panic disorder (PD) is associated with somatization and high medical utilization in primary care settings. Treatment of PD could reduce the frequency of panic attacks and visits to emergency departments, but the associated change in medical utilization is unknown. This study investigated the change in medical utilization before and after a PD diagnosis. This study identified 8722 patients with PD enrolled in the National Health Insurance Research Database in Taiwan between January 1, 2000, and December 31, 2012. We used a case-crossover study design to compare medical utilizations with a 1-year time window before and after new PD diagnoses, including medical examinations, specialty visits, and medication used. A conditional logistic regression model was used to estimate changes in comorbidity before and after new PD diagnoses. The utilization of examinations-including electrocardiography, radiography, and sonography-decreased within 1 year after PD diagnosis compared with 1 year before PD diagnosis. Outpatient and emergency department visits to nonpsychiatric departments decreased (risk ratio [RR] = 0.989 [95% confidence interval {CI} = 0.985-0.993] and RR = 0.924 [95% CI = 0.894-0.956], respectively), whereas outpatient visits to psychiatric departments increased (RR = 1.193, 95% CI = 1.171-1.215). PD diagnosis is associated with increased use of antidepressants (RR = 12.65) and benzodiazepines (RR = 11.63), an increased ratio of comorbid depressive disorder (RR = 3.06) and bipolar disorder (RR = 1.77), and a decreased ratio of nonpanic anxiety disorder (RR = 0.69). New PD diagnoses are associated with decreased laboratory examination and nonpsychiatric service utilization, along with increased psychiatric service utilization. We suggest that PD should be detected earlier for mitigating potentially unnecessary use of nonpsychiatric examinations and services.

An increased disease burden of autoimmune inflammatory rheumatic diseases in Korea

ObjectivesTo estimate the prevalence, medical utilization, and recent changes in the economic burden of autoimmune rheumatic diseases (AIRDs) in Korea. MethodsUsing a nationwide claims database that includes all medical claims made by approximately 50 million Korean residents, the prevalences of seropositive rheumatoid arthritis (RA), ankylosing spondylitis (AS), systemic lupus erythematosus (SLE), and others between 2012 and 2016 were calculated. Changes in medical utilization and the direct medical costs of each AIRD from 2012 to 2016 were also evaluated. ResultsBased on the data for 2016, seropositive RA was the most common AIRD in Korea with 96,330 cases (188.5/100,000 population), followed by AS (30,006, 58.7/100,000 population), SLE (19,441, 38.0/100,000 population), Behçet's disease (BD, 14,943, 29.2/100,000 population), primary Sjögren syndrome (pSS, 12,018, 23.5/100,000 population), and systemic sclerosis (SSc, 3606, 7.1/100,000 population). In terms of medical utilization, patients with eosinophilic granulomatosis with polyangiitis visited outpatient clinics the most frequently (9.8 times/year/patient), while hospitalization was most frequent in microscopic polyangiitis patients (1.0 time/year/patient). Total medical costs for all AIRDs increased from $154,348,011 in 2012 to $262,481,974 in 2016. The annual medical cost per patient in 2016 was the highest in microscopic polyangiitis ($6223/year), followed by psoriatic arthritis ($3,362/year), and granulomatosis with polyangiitis ($2823/year). ConclusionsIn Korea, the most prevalent AIRD is seropositive RA, followed by AS, SLE, BD, pSS, and SSc. The economic burden of AIRDs has risen substantially in the last 5 years due not only to an increase in their prevalence but also to an increase in medical costs per patient.

Nationwide analysis of medical utilization in people with severe mental illness receiving home care case management

AimThis nationwide study investigated the change in medical utilization of psychiatric home care case management (CM). MethodsThis nationwide study enrolled patients receiving CM (N = 10,274) from January 1, 1999 to December 31, 2010, from Taiwan's National Health Insurance Research Database. Through a 2-year mirror-image comparison weighted by the contributed person-time for each subject, we evaluated changes in medical utilization. Furthermore, a case-crossover analysis was used to verify the independent effect of CM in changing medical utilization by adjusting the time-variant variables between the pre-2-year (within 2 years before receiving CM) and post-2-year (within years after receiving CM) periods. The same methodology was applied for the subsequent 2-year comparison to assess the maintenance effect. ResultsOf the 10,274 patients receiving CM, 69.7% had schizophrenia. The results showed a chronological trend for the intervention of CM. The adjusted mirror-image analysis revealed a significant decrement of psychiatric and involuntary admissions after the intervention, and the utilization shifted toward psychiatric outpatient service. The case-crossover analysis with the adjustment of time-variant covariates confirmed the independent effect of CM on the changes of medical utilization. The comparable effect persisted after the next 2 years of intervention. However, CM showed no impact on lowering the admission rate for comorbid physical illnesses after the intervention. ConclusionsThe CM model can effectively reduce psychiatric hospitalization and involuntary admission frequency but has no effect on comorbid physical illnesses. Care models aimed at ameliorating physical problems in such patients are needed.

Comparative Analysis of the Trends in Medical Utilization of Cancer Inpatients in Korea.

ObjectivesCancer has attracted worldwide attention. The incidence and prevalence are increasing, and it is the main cause of death. The purpose of this study was to identify the characteristics of hospitalized cancer patients.MethodsThis study is a secondary data study using the Korean National Hospital Discharge In-depth Injury Survey Data conducted annually by the Korea Centers for Disease Control and Prevention. Using these data, we extracted inpatients who principal diagnosis is cancer for nine years from 2005 to 2013.ResultsAccording to the analysis, the annual trend of cancer inpatients is steadily increasing. In 2025, it is expected to increase to about 670,000 inpatients. A cancer diagnosis created a change in medical utilization depending on the characteristics of patients and hospital. Men are more at risk of cancer than women. The number of hospital beds and hospital days were inversely proportional to cancer inpatients. There was also a difference in the equity of medical utilization by region. Other cancer management policies should be based on sex.ConclusionPopulations between the ages of 45 and 64 years should be a priority in cancer policy. Because of the long-term hospitalization of patients with death as the outcome, a terminal cancer patient care facility is needed. These conclusions can provide a basis for various health policies.

Abstract A77: Patterns of medical utilization, finances, health behaviors and comorbidities in older adults reporting negative versus positive net worth after a cancer diagnosis

Abstract Purpose: Financial insolvency following cancer has been linked to increased mortality; however, the individual financial factors, insurance, medical utilization, health behaviors, and comorbidities in cancer patients with a negative net worth (NNW) have not been characterized. Using the Health and Retirement Study, a national longitudinal survey of U.S. households from 1992 to 2012, we examined the effect of a cancer diagnosis on medical spending and personal finances in adults age-eligible for Medicare insurance. Demographic variables, insurance status, and measures of medical utilization, finances, and health in cancer patients reporting negative and positive net worth were assessed. Methods: Analyses were restricted to individuals age 65 years or older to reduce heterogeneity in employment and insurance status. Individual-level fixed effect panel analyses were performed to assess the effect of a cancer diagnosis on log out-of-pocket medical spending, hospitalizations, log household debt, Medicaid enrollment, and NNW. Subset analyses were performed by gender and time period (pre- and post-2002). Summary measures of cancer patients, partitioned by presence or absence of NNW, were performed on financial indices, medical utilization, health measures, and insurance. Results: A new cancer diagnosis significantly increased out-of-pocket medical spending, hospitalizations, Medicaid enrollment, and risk of NNW in all respondents, as well as household debt in males. Following a cancer diagnosis, there was a large change in medical utilization, with a 36.7% increase in log out-of-pocket medical spending and a 71.4% increase in hospitalizations (p&amp;lt;0.01). Log household debt increased by 22.1% in male cancer patients (p&amp;lt;0.05); there was no significant change to household debt for female cancer patients. There was a small but statistically significant increase in risk of financial insolvency and Medicaid enrollment following a cancer diagnosis (1.3% and 1.2%, respectively; p&amp;lt;0.05); on subset analysis, risk of developing a NNW after cancer appeared to be highest in women and in the post-2002 era. Out of 2682 cancer patients, 183 (6.8%) reported NNW. Compared to cancer patients with positive net worth, the NNW group had less education, higher likelihood of being widowed, divorced, or unmarried, higher percentage non-white race and Hispanic ethnicity, higher rates of disability, higher Medicaid enrollment, and less private insurance. While median out-of-pocket medical spending was lower in financially insolvent cancer patients, this group had increased hospitalizations and cumulative length of hospital stays. Smoking rates and body mass index were similar between the two groups, but patients with NNW had worse clinical depression and self-reported health scores, as well as increased rates of hypertension, cerebrovascular disease, diabetes, pulmonary disease, arthritis, and mental illness. Conclusion: A diagnosis of cancer increases out-of-pocket medical spending, hospitalizations, and financial insolvency among individuals age-eligible for Medicare insurance protection. Newly diagnosed cancer patients reporting negative net worth have multiple differences in socioeconomic status, medical utilization, and comorbidities as compared to patients with positive net worth, which may contribute to disparities in survival outcomes. Citation Format: Emily Castellanos, Michael Richards. Patterns of medical utilization, finances, health behaviors and comorbidities in older adults reporting negative versus positive net worth after a cancer diagnosis. [abstract]. In: Proceedings of the Ninth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2016 Sep 25-28; Fort Lauderdale, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(2 Suppl):Abstract nr A77.

GEE estimation of a misspecified time‐varying covariate: an example with the effect of alcoholism treatment on medical utilization

The generalized estimation equation (GEE) method is widely used in longitudinal data analysis, particularly when the outcome variable is non-Gaussian distributed. Under mild regulatory conditions, the parameter estimates are consistent and their asymptotic variances are efficient. In an observational study focusing on alcoholism patients, we applied the GEE method to longitudinal count data from medical utilization records from a large national managed care organization. The health services research question was whether there was a change in medical utilization for patients after engaging in alcoholism treatment as compared to before treatment. Thus, the main effect of interest was a time-varying covariate indicating whether the patient had undergone treatment yet or not. GEE under five different working correlations was employed and mixed results regarding the significance of the treatment effect were found. Because of the large sample size, i.e. 8485 patients with an average of 46 repeated measurements per patient, differences across the estimates produced by the different working correlation structures was suspicious. It is shown that these differences are maybe caused by the fact that the time-varying covariate in the marginal mean model is misspecified. A simulation study is performed to demonstrate that misspecification of the time-varying covariate in the marginal mean structure can cause differences in GEE results across various choices of working correlation structure.

Isolating the effect of alcoholism treatment on medical care use.

This study seeks to refine the analysis of the effects of alcoholism treatment on subsequent use of medical care by examining components of the latter. Claims and encounter data of 29,122 adults (mean age 40, 35% female) receiving benefits from both a mental health managed care program and its parent medical care insurance company who had a diagnosis of alcoholism were analyzed using a longitudinal Poisson regression model fit by the generalized estimating equation method to compare differences between the groups in medical utilization before and after alcoholism treatment. The diagnoses associated with medical care were assigned to one of four groups: alcohol specific, alcohol acute, alcohol chronic and nonalcohol related. All persons applying for alcoholism treatment benefits were included; those who had fewer than four visits for alcoholism treatment served as controls. The largest effect of alcoholism treatment is seen for medical encounters associated with diagnoses that reflect the acute effects of intoxication. The frequency of encounters related to conditions associated with chronic alcohol misuse were the only type that did not significantly decline 1 year past treatment in the outpatient treatment group. This study provides support for the belief that treatment for alcoholism is directly associated with a change in medical care use. However, the findings suggest that the impact on utilization varies with the type of medical care. The most pronounced effects appear to be for acute problems that may be most directly attributed to the effects of active drinking. Changes in medical utilization in this area, therefore, may be responsible for the cost-offset of alcoholism treatment that has been observed in prior research.