scholarly journals Modeling Count Data for Healthcare Utilization: an Empirical Study of Outpatient Visits Among Vietnamese Older People

2020 ◽  
Author(s):  
Dung Duc Le ◽  
Roberto Leon-Gonzalez ◽  
Joseph Upile Matola
Keyword(s):  
Empirical Study ◽  
Older People ◽  
Healthcare Utilization ◽  
Count Data ◽  
Outpatient Visits

Abstract The authors have withdrawn this preprint due to erroneous posting.

scholarly journals Modeling Count Data for Healthcare Utilization: an Empirical Study of Outpatient Visits Among Vietnamese Older People

2020 ◽  
Author(s):  
Dung Duc Le ◽  
Roberto Leon-Gonzalez ◽  
Joseph Upile Matola
Keyword(s):  
Model Selection ◽  
Older People ◽  
Healthcare Utilization ◽  
Count Data ◽  
Aging Process ◽  
Cross Validation ◽  
Outpatient Visits ◽  
Best Fitting ◽  
Fold Cross Validation ◽  
Fitting Model

Abstract Background Vietnam is undergoing an unprecedented pace of aging process and is expected to experience the fastest aging process in region. Association between increasing age and health deterioration has been well-documented across settings. Consequently, demand for healthcare utilization is rising among older people. However, healthcare utilization, here measured as count data, creates challenges for modeling because such data typically has distributions that are skewed with a large mass at zero. This study compares empirical econometric strategies for the modeling of healthcare utilization (measured as the number of outpatient visits in the last 12 months), and identifies the determinants of healthcare utilization among Vietnamese older people based on the best-fitting model identified. Methods Using the Vietnam Household Living Standard Survey in 2006 (N=2426), nine econometric regression models for count data were examined to identify the best-fitting one. We used model selection criteria; statistical tests; and goodness-of-fit for in-sample model selection. In addition, we conducted 10-fold cross-validation checks to examine reliability of in-sample model selection. Finally, we utilized marginal effects to identify the factors associated with number of outpatient visits among Vietnamese older people based on the best-fitting model identified. Results We found strong evidence in favor of hurdle negative binomial model 2 (HNB2) for both in-sample selection and 10-fold cross-validation checks. The marginal effect results of the HNB2 showed that predisposing, enabling, need, and lifestyle factors were significantly associated with number of outpatient visits. The predicted probabilities for each count event showed the distinct trends of healthcare utilization among specific groups: at low count events, women and people in younger age group used more healthcare utilization than did men and their counterparts in older age groups, but a reversed trend was found at higher count events. Conclusions The findings here suggest that the HNB2 model should be considered for use in modeling counts of healthcare use. This study’s findings lay the groundwork for future research on the modeling of healthcare utilization in developing countries and those findings could be used to forecast on healthcare demand and making provisions for healthcare costs.

scholarly journals Modeling Count Data for Healthcare Utilization: an Empirical Study of Outpatient Visits Among Vietnamese Older People

2020 ◽  
Author(s):  
Dung Duc Le ◽  
Roberto Leon-Gonzalez ◽  
Joseph Upile Matola
Keyword(s):  
Model Selection ◽  
Older People ◽  
Healthcare Utilization ◽  
Count Data ◽  
Aging Process ◽  
Cross Validation ◽  
Outpatient Visits ◽  
Best Fitting ◽  
Fold Cross Validation ◽  
Fitting Model

Abstract Background Vietnam is undergoing an unprecedented pace of aging process and is expected to experience the fastest aging process in region. Association between increasing age and health deterioration has been well-documented across settings. Consequently, demand for healthcare utilization is rising among older people. However, healthcare utilization, here measured as count data, creates challenges for modeling because such data typically has distributions that are skewed with a large mass at zero. This study compares empirical econometric strategies for the modeling of healthcare utilization (measured as the number of outpatient visits in the last 12 months), and identifies the determinants of healthcare utilization among Vietnamese older people based on the best-fitting model identified. Methods Using the Vietnam Household Living Standard Survey in 2006 (N = 2426), nine econometric regression models for count data were examined to identify the best-fitting one. We used model selection criteria; statistical tests; and goodness-of-fit for in-sample model selection. In addition, we conducted 10-fold cross-validation checks to examine reliability of in-sample model selection. Finally, we utilized marginal effects to identify the factors associated with number of outpatient visits among Vietnamese older people based on the best-fitting model identified. Results We found strong evidence in favor of hurdle negative binomial model 2 (HNB2) for both in-sample selection and 10-fold cross-validation checks. The marginal effect results of the HNB2 showed that predisposing, enabling, need, and lifestyle factors were significantly associated with number of outpatient visits. The predicted probabilities for each count event showed the distinct trends of healthcare utilization among specific groups: at low count events, women and people in younger age group used more healthcare utilization than did men and their counterparts in older age groups, but a reversed trend was found at higher count events. Conclusions The findings here suggest that the HNB2 model should be considered for use in modeling counts of healthcare use. This study’s findings lay the groundwork for future research on the modeling of healthcare utilization in developing countries and those findings could be used to forecast on healthcare demand and making provisions for healthcare costs.

scholarly journals Modeling count data for health care utilization: an empirical study of outpatient visits among Vietnamese older people

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Duc Dung Le ◽  
Roberto Leon Gonzalez ◽  
Joseph Upile Matola
Keyword(s):  
Model Selection ◽  
Older People ◽  
Healthcare Utilization ◽  
Count Data ◽  
Cross Validation ◽  
Negative Binomial ◽  
Outpatient Visits ◽  
Best Fitting ◽  
Fold Cross Validation ◽  
Fitting Model

Abstract Background Vietnam is undergoing a fast-aging process that poses potential critical issues for older people and central among those is demand for healthcare utilization. However, healthcare utilization, here measured as count data, creates challenges for modeling because such data typically has distributions that are skewed with a large mass at zero. This study compares empirical econometric strategies for the modeling of healthcare utilization (measured as the number of outpatient visits in the last 12 months) and identifies the determinants of healthcare utilization among Vietnamese older people based on the best-fitting model identified. Methods Using the Vietnam Household Living Standard Survey in 2006 (N = 2426), nine econometric regression models for count data were examined to identify the best-fitting one. We used model selection criteria, statistical tests and goodness-of-fit for in-sample model selection. In addition, we conducted 10-fold cross-validation checks to examine reliability of the in-sample model selection. Finally, we utilized marginal effects to identify the factors associated with the number of outpatient visits among Vietnamese older people based on the best-fitting model identified. Results We found strong evidence in favor of hurdle negative binomial model 2 (HNB2) for both in-sample selection and 10-fold cross-validation checks. The marginal effect results of the HNB2 showed that ethnicity, region, household size, health insurance, smoking status, non-communicable diseases, and disability were significantly associated with the number of outpatient visits. The predicted probabilities for each count event revealed the distinct trends of healthcare utilization among specific groups: at low count events, women and people in the younger age group used more healthcare utilization than did men and their counterparts in older age groups, but a reverse trend was found at higher count events. Conclusions The high degree of skewness and dispersion that typically characterizes healthcare utilization data affects the appropriateness of the econometric models that should be used in modeling such data. In the case of Vietnamese older people, our study findings suggest that hurdle negative binomial models should be used in the modeling of healthcare utilization given that the data-generating process reflects two different decision-making processes.

scholarly journals Modeling Count Data for Healthcare Utilization: an Empirical Study of Outpatient Visits Among Vietnamese Older People

2020 ◽  
Author(s):  
Dung Duc Le ◽  
Roberto Leon-Gonzalez ◽  
Joseph Upile Matola
Keyword(s):  
Model Selection ◽  
Older People ◽  
Healthcare Utilization ◽  
Count Data ◽  
Selection Criteria ◽  
Cross Validation ◽  
Outpatient Visits ◽  
Best Fitting ◽  
Fold Cross Validation ◽  
Fitting Model

Abstract Background Vietnam is undergoing a fast aging process that poses potential critical issues for older people and central among those is demand for healthcare utilization. However, healthcare utilization, here measured as count data, creates challenges for modeling because such data typically has distributions that are skewed with a large mass at zero. This study compares empirical econometric strategies for the modeling of healthcare utilization (measured as the number of outpatient visits in the last 12 months), and identifies the determinants of healthcare utilization among Vietnamese older people based on the best-fitting model identified. Methods Using the Vietnam Household Living Standard Survey in 2006 (N=2426), nine econometric regression models for count data were examined to identify the best-fitting one. We used model selection criteria; statistical tests; and goodness-of-fit for in-sample model selection. In addition, we conducted 10-fold cross-validation checks to examine reliability of in-sample model selection. Finally, we utilized marginal effects to identify the factors associated with the number of outpatient visits among Vietnamese older people based on the best-fitting model identified. Results We found strong evidence in favor of hurdle negative binomial model 2 (HNB2) for both in-sample selection and 10-fold cross-validation checks. The marginal effect results of the HNB2 showed that ethnicity, region, household size, health insurance, smoking status, non-communicable diseases, and disability were significantly associated with the number of outpatient visits. The predicted probabilities for each count event showed the distinct trends of healthcare utilization among specific groups: at low count events, women and people in the younger age group used more healthcare utilization than did men and their counterparts in older age groups, but a reversed trend was found at higher count events. Conclusions Data come in all shapes and sizes, this study highlights the importance of model specification checks and model selection criteria to avoid potential biased estimates as a result of model misspecifications. This study’s findings lay the groundwork for future research on the modeling of healthcare utilization in developing countries and those findings could be used to forecast on healthcare demand and making provisions for healthcare costs.

The association between an increased reimbursement cap for chronic disease coverage and healthcare utilization in China: an interrupted time series study

2020 ◽  
Vol 35 (8) ◽  
pp. 1029-1038 ◽  
Author(s):  
Menghan Shen ◽  
Wen He ◽  
Eng-Kiong Yeoh ◽  
Yushan Wu
Keyword(s):  
Time Series ◽  
Chronic Disease ◽  
Healthcare Utilization ◽  
Interrupted Time Series ◽  
Claim Data ◽  
Health Events ◽  
Outpatient Visits ◽  
Insurance Claim Data ◽  
Adverse Health Events ◽  
Series Study

Abstract Hypertension and diabetes are highly prevalent in China and pose significant health and economic burdens, but large gaps in care remain for people with such conditions. In this article, drawing on administrative insurance claim data from China’s Urban Employee Basic Medical Insurance (UEBMI), we use an interrupted time series design to examine whether an increase in the monthly reimbursement cap for outpatient visits using chronic disease coverage affects healthcare utilization. The cap was increased by 50 yuan per chronic disease on 1 January 2016, in one of the largest cities in China. Compared with the year before the increase, patients with only hypertension increased their spending using chronic disease coverage by 17.8 yuan (P < 0.001) or 11.6%, and those with only diabetes increased their spending using chronic disease coverage by 19.5 yuan (P < 0.001) or 10.6%, with the differences almost entirely driven by spending on drugs. In addition, these two groups of patients reduced their spending using standard outpatient coverage by 13.9 yuan (P < 0.001) or 5.7% and 14.9 yuan (P = 0.03) or 5.2%, respectively, and thus had no changes in total outpatient spending. Patients with both hypertension and diabetes, meanwhile, increased their spending using chronic disease coverage by 54.8 yuan (P < 0.001) or 18.1% and decreased their spending using standard outpatient coverage by 16.1 yuan (P = 0.002) or 6.1%, with no changes in their probability of hospitalization. Among patients with both hypertension and diabetes who had fewer-than-average outpatient visits in 2015, the hospitalization rate decreased after the 2016 reimbursement cap increase (adjusted odds ratio = 0.702, P = 0.01). These findings suggest that increasing financial protection for patients with hypertension and diabetes may be an important strategy for reducing adverse health events, such as hospitalization, in China.

The use of ‘my side telling’ during history taking in psychiatric consultations

2021 ◽  
pp. 146144562110016
Author(s):  
Xueli Yao
Keyword(s):  
Empirical Study ◽  
Conversation Analysis ◽  
History Taking ◽  
Patients Rights ◽  
Outpatient Visits ◽  
Psychiatric Outpatient ◽  
Audio Recordings ◽  
Sense Of Reality ◽  
Psychiatric Conditions

Using the method of conversation analysis, this article examines an interactional practice through which psychiatric practitioners exhibit knowledge about their patients’ problems, symptoms, or experiences in psychiatric outpatient consultations. This practice is referred to as ‘my side telling’. The data were from audio recordings of 55 psychiatric outpatient visits to four psychiatrists in China. In the data, the psychiatrists employ ‘my side telling’ within larger sequences of talk where psychiatrists solicit their patients to elaborate on their problems or experiences, treating prior answers of the patients as unsatisfactory. Based on empirical study of the data, it is argued that ‘my side telling’ in psychiatry is not merely used to elicit information. Rather, through facing patients with facts or evidence which the psychiatrists got from other sources, it acquires a confrontative function and may be employed as a tool to test the patients’ sense of reality and willingness to talk about their experiences. Thus, it is shown to work towards assessing patients for possible psychiatric conditions and forming diagnostic hypotheses. I further argue that ‘my side telling’ allows the psychiatrists to achieve a balance between respecting the patients’ rights to report their own experiences and influencing the directions in which the information is reported.

scholarly journals What is life like for our elderly? An empirical study of the quality of life of older people in Colombia

CEPAL Review ◽  
2020 ◽  
Vol 2019 (129) ◽  
pp. 129-148
Author(s):  
Bilver Adrián Astorquiza Bustos ◽  
Óscar Armando Chingal
Keyword(s):  
Quality Of Life ◽  
Empirical Study ◽  
Older People

scholarly journals Impact of Gaps in Care during Adult Care Transfer in Sickle Cell Disease

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 2992-2992
Author(s):  
Kristen E Howell ◽  
Mariam Kayle ◽  
Matthew P Smeltzer ◽  
Vikki Nolan ◽  
James G Gurney ◽  
...  
Keyword(s):  
Health Care ◽  
Young Adults ◽  
Healthcare Utilization ◽  
Sickle Cell ◽  
Healthcare Resource Utilization ◽  
Adult Health ◽  
Adult Care ◽  
Outpatient Visits ◽  
Acute Healthcare ◽  
Transfer Interval

Abstract The transition from pediatric to adult health care is critical to the care of young adults with sickle cell disease (SCD). Young adults with SCD, compared with children with SCD, are at risk for a marked increase in disease severity, frequency of acute complications, healthcare utilization, and mortality. 1-4 Professional societies and healthcare experts recommend that young adults with chronic health conditions should transfer to adult-centered healthcare within 6 months of their last pediatric visit. 5-8 However, the effect of a 6-month transfer interval on healthcare utilization in SCD has not been studied. Given the complex health care needs of young adults with SCD, 9-15 it remains unclear whether the recommended 6-month transfer interval 5 is optimal. We hypothesized that longer gaps between pediatric and adult care would be associated with greater healthcare utilization in the first 2 to 6 years of adult care. This study included patients with SCD who were followed by a pediatric sickle cell program in the mid-southern US, participated in a transition to adult care program, 16 and fulfilled an initial adult visit to a partner adult SCD facility during the years 2011-2017. Participants were retrospectively followed from their first adult visit through December 31, 2017. Transfer gap was defined as the time (in months) between the last pediatric and the first adult sickle cell clinic visit. We estimated the association between varying transfer gaps from pediatric to adult care and the rate of healthcare utilization (inpatient, emergency department, and outpatient visits) in the first 2 to 6 years of adult care using negative binomial regression. Transfer gaps were evaluated at <2, ≥2 to <6, ≥6 to <9, and ≥9 months to evaluate whether adult health care utilization increased as the gap in SCD-specific care increased. Transfer gaps were also dichotomized at 6 months (>6 vs ≤6) to evaluate the current recommendation to complete transfer of patients to adult care within 6 months. 6,7 Healthcare resource utilization was analyzed for the complete follow-up (up to 6 years) and for the first 2 years of adult care to assess the immediate effects of delayed transfer. In total, 172 young adults with SCD (52% male, 63% HbSS/HbSβ 0-thalassemia) transferred to adult care at a median age of 18 years during the years 2011-2017 (Table 1). Approximately 83% of the included participants transferred to adult care within the recommended 6 months. young adults with transfer gaps ≥9 months had 2.86 (95%CI: 1.32, 6.20) times the rate of acute healthcare visits (inpatient and emergency department combined) compared to those with <2 months transfer gap (Table 2). The incidence rate ratio increased (IRR: 4.06; 95%CI: 1.65, 9.94) when evaluating the first 2 years of adult care. When evaluating the recommended transfer gap (6 months) as a dichotomous variable, those with gaps >6 months had 2.27 (95%CI: 1.18, 4.40) times the rate of acute care visits compared to those with ≤6 months transfer gap (Table 3). The incidence rate ratio increased slightly (IRR: 2.37; 95%CI: 1.29, 4.37) when evaluating the first 2 years of adult care only. There were no apparent associations between transfer gap duration and outpatient visits during the first 6 years in adult care; however, when restricted to the first 2 years of adult care, those with gaps >6 months had 1.32 (95%CI: 1.01, 1.72) times the rate of outpatient visits compared to those with gaps ≤6 months. Consistent with current guidelines, transfer gaps between pediatric and adult-centered care of greater than 6 months were found to be associated with increased acute healthcare resource utilization. Therefore, SCD transition programs would be well-served to consider policies for young adults that initiate adult care within 6 months of leaving pediatric care. Future studies should continue to investigate duration of transfer gaps from pediatric to adult care for their long-term clinical effects and explore interventions to reduce the transfer gap in the SCD population. Figure 1 Figure 1. Disclosures Shah: Novartis: Consultancy, Research Funding, Speakers Bureau; GBT: Research Funding, Speakers Bureau; Alexion: Speakers Bureau; Guidepoint Global: Consultancy; GLG: Consultancy; Emmaus: Consultancy. Hankins: Bluebird Bio: Consultancy; UpToDate: Consultancy; Vindico Medical Education: Consultancy; Global Blood Therapeutics: Consultancy.

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