A Retrospective Cohort Study of Patients with Type 2 Diabetes in China: Associations of Hypoglycemia with Health Care Resource Utilization and Associated Costs

A Retrospective Cohort Study of Patients with Type 2 Diabetes in China: Associations of... Diabetes Ther (2018) 9:1073–1082 https://doi.org/10.1007/s13300-018-0409-1 ORIGINAL RESEARCH A Retrospective Cohort Study of Patients with Type 2 Diabetes in China: Associations of Hypoglycemia with Health Care Resource Utilization and Associated Costs . . . . Yingping Yi Yawei Li Anran Hou Yanqiu Ge . . . . Yuan Xu Gang Xiong Xinlei Yang Stephanie Ann Acevedo Lizheng Shi Hua Xu Received: February 2, 2018 / Published online: April 5, 2018 The Author(s) 2018 Methods: This retrospective cohort study was ABSTRACT conducted with 23,680 T2DM patients [18 years old who visited the Second Affiliated Introduction: This study aimed to examine the Hospital of Nanchang University between 1 associations of hypoglycemia with health care January 2011 and 31 December 2015. Univari- resource utilization (HCRU) and health care ate descriptive statistics were used to relate the costs among patients with type 2 diabetes mel- HCRU and associated costs to patient charac- litus (T2DM) in China. teristics, and regression analysis was used to examine the association between hypoglycemia Enhanced content To view enhanced content for this and HCRU, controlling for other confounding article go to https://doi.org/10.6084/m9.figshare. factors. Results: In the T2DM patients with or without Yingping Yi and Yawei Li contributed equally to the insulin treatment, when compared with non- article as first authors. hypoglycemic patients, hypoglycemia was Y. Xu  G. Xiong Y. Yi  X. Yang Medical Big-Data Center, The Second Affiliated Department of Science and Education, The Second Hospital of Nanchang University, No. 1 Minde Affiliated Hospital of Nanchang University, No. 1 Road, Nanchang 330006, Jiangxi, People’s Republic Minde Road, Nanchang 330006, Jiangxi, People’s of China Republic of China S. A. Acevedo Y. Li  L. Shi (&) Department of Community Health, School of Public Department of Global Health Management and Health and Tropical Medicine, Tulane University, Policy, School of Public Health and Tropical 119A N. Alexander St, New Orleans, LA 70119, USA Medicine, Tulane University, 1440 Canal Street, Suite 1900, New Orleans, LA 70112, USA H. Xu (&) e-mail: lshi1@tulane.edu School of Biomedical Informatics, The University of Texas, Health Science Center at Houston, 7000 A. Hou Fannin, Houston, TX 77030, USA Suzhou Hebta Health Information Technology Co., e-mail: Hua.Xu@uth.tmc.edu Ltd, 10-302 Creative Industrial Park, No. 328, Xinghu Street, Suzhou Industrial Park, Suzhou 215123, People’s Republic of China Y. Ge School of Public Health, Medical School, Nanchang University, No. 1 Minde Road, Nanchang 330006, Jiangxi, People’s Republic of China 1074 Diabetes Ther (2018) 9:1073–1082 associated with more medical visits (all T2DM 12% (114 million) of Chinese adults are diabetic patients 19.48 vs. 10.46, insulin users 23.45 vs. (Dr. Margaret Chan at the 47th Meeting of the 14.12) and higher diabetes-related medical costs National Academy of Medicine, 2016). Adults (all T2DM patients ¥5187.54 vs. ¥3525.00, living with diabetes suffer from a long-term insulin users ¥6948.84 vs. ¥3401.15) and medi- economic burden and are at high risk of blind- cation costs (T2DM patients ¥1349.40 vs. ness, kidney failure, lower limb amputation, ¥641.92, insulin users: ¥1363.87 vs. ¥853.96). and several other long-term consequences that Controlling for age, gender, and Charlson impact significantly on their quality of life [1]. comorbidity index (CCI) score, hypoglycemia Most (80–90%) cases of diabetes mellitus are and insulin intake were associated with greater of type 2 (T2DM), which is a progressive disease health care resource utilization. As compared to that affects glucose regulation [2, 3]. In recent nonhypoglycemic patients, hypoglycemic years, the main goal of T2DM treatment has T2DM patients and those on insulin therapy been to achieve good glycemic control [3] performed more outpatient visits (proportions through a combination of diet, physical activ- of hypoglycemic vs nonhypoglycemic T2DM ity, and—if necessary—medication. Insulin patients performing 3? visits: 72.69% vs. therapy is an effective medication for achieving 65.49%; proportions of hypoglycemic vs non- a common target of T2DM treatment: a glycated hypoglycemic patients on insulin therapy per- hemoglobin (HbA1c) level of below 7% [4, 5]. forming 3? visits: 78.26% vs. 71.73%) and were However, insulin therapy is a risk factor for hospitalized more often (proportions of hypo- iatrogenic hypoglycemia [6–9]. Diabetes-related glycemic vs nonhypoglycemic T2DM patients hypoglycemia can cause complications such as with 3? admissions 75.90% vs. 50.24%; pro- pronounced effects on the cardiovascular (CV) portions of hypoglycemic vs nonhypoglycemic system, atherosclerosis, patient depression, and patients on insulin therapy with 3? admissions: even death [9–14]. Hypoglycemia can also sig- 83.19% vs. 58.51%). nificantly affect the quality of life of elderly Conclusion: Hypoglycemia in diabetes patients patients due to their increased potential for was associated with increased healthcare dysrhythmias, accidents, falls, and neurological resource utilization and health-related expen- symptoms [15, 16]. All of these substantially diture, especially for patients on insulin treat- influence healthcare utilization by and the ment. Insulin treatment regimens should be burden of healthcare costs for diabetic patients more individualized and account for hypo- [15, 17]. glycemia risk. International studies have indicated that even though hypoglycemia prevalence varies markedly from country to country, the preva- Keywords: Diabetes; Healthcare cost; lence of hypoglycemia in each country is gen- Healthcare utilization; Hypoglycemia erally underestimated [17, 18]. In some recent Chinese studies it was found that the level of INTRODUCTION monitoring of glucose control outcomes varies among regions, but that the usage of insulin Diabetes is currently one of the biggest public therapy is commonly high and is continuously increasing [19–22]. health issues worldwide. The World Health Organization states that the prevalence of dia- Given the increasing rate of hypoglycemia, the objective of this study of a subgroup of betes has risen continuously from a total of 108 million (4.7%) globally in 1980 to around four insulin users was to examine health care resource utilization (HCRU) by and health-re- times that number (8.5%) in 2014. China, which has the world’s largest population and is lated costs for Chinese T2DM patients with or without hypoglycemia. undergoing sustained economic growth, is cur- rently facing a serious diabetes epidemic: nearly Diabetes Ther (2018) 9:1073–1082 1075 Statistical Methods METHODS Univariate descriptive statistics were used to Data Sources describe the patient diabetes-specific HCRU and associated costs. Continuous data were reported This retrospective cohort study was conducted as mean values and standard deviations (SD), with 23,680 patients with type 2 diabetes who and categorical data were reported as percent- were selected from 1,477,727 patients who were ages. T2DM patients and patients on insulin over 18 years old and visited the Second Affili- therapy with or without hypoglycemia were ated Hospital of Nanchang University (SAHNU) compared in terms of the number of visits to a between 1 January 2011 and 31 December 2015. physician, the percentage of patients who per- All of the patients in this study were required to formed 3? outpatient visits, the percentage of be alive and to visit the SAHNU at least once a patients who underwent 3? hospitalizations, year during the 4-year period. At visits to the and associated medical costs. SAHNU, patients were required to provide Binary logistic regression analysis was used venous blood after fasting for [8 h overnight. to estimate the likelihood of an outpatient visit Serum was separated from the venous blood and and the likelihood of hospitalization in the stored at - 80 C before inspection. The elec- diabetes patients, and then groups of patients tronic medical records from the Second Affili- were compared based on an independent vari- ated Hospital of Nanchang University database able: either age group (19–64 years old, 65–- were processed using the da Vinci S system 74 years old, or C 75 years old), gender, (provided by HEBTA, Pearland, TX, USA). The Charlson comorbidity index (CCI) score (0–4, records included admission, diagnosis, medica- 5–10, or 11–14), hypoglycemic/nonhypo- tion, testing, surgical, nursing, and cost data as glycemic, and insulin use. well as images, and the database contained all of To further probe the relationship between the clinical data for the hospital. We calculated HCRU and hypoglycemia, two multiple regres- the HCRU associated with diabetes complica- sion analyses controlling for baseline charac- tions in both the hypoglycemic and nonhypo- teristics were conducted: a linear regression glycemic cohorts. analysis of the number of outpatient visits and a Poisson regression analysis of number of hos- Variables pitalizations. All statistical data were analyzed using the SPSS19.0 software package. Type 2 diabetes mellitus was identified in this study based on the ICD-10 codes E11, E11.901, and E11.902. The date of first recorded T2DM COMPLIANCE WITH ETHICS diagnosis was defined as the index date. Pre- GUIDELINES index-date patient information was used to derive baseline data on demographic and illness This article is based on previously conducted characteristics. Hypoglycemia after the index studies of de-identified medical records and date was identified based on the ICD-10 codes does not contain any studies with human par- E16.01, E16.001, E16.101, and E16.201, or a ticipants or animals performed by any of the laboratory-measured glucose level authors. of B 3.9 mmol/L. Post-index-date diabetes- specific HCRU variables included number of medical visits and hospitalization. Post-index- RESULTS date health care costs included medical costs and prescription drug costs. Among 23,680 patients with type 2 diabetes mellitus, 3.29% reported hypoglycemia (54.87% male, mean age 69.02 years old). Among the insulin users (n = 8187), 4.21% suffered from 1076 Diabetes Ther (2018) 9:1073–1082 Table 1 Baseline demographics and illness characteristics of the patients Characteristic Type 2 diabetes mellitus patients Patients on insulin therapy Hypoglycemic Nonhypoglycemic Hypoglycemic Nonhypoglycemic Number of patients (%) 780 (3.29) 22,900 (96.70) 345 (4.21) 7842 (95.78) Age in years, mean (SD) 69.02 (11.55) 64.01 (12.81) 69.11 (11.73) 63.14 (13.16) Gender (male %) 482 (54.87) 12,458 (54.40) 198 (57.39) 4386 (55.92) CCI score, mean (SD) 4.62 (1.86) 3.66 (1.66) 4.77 (1.93) 3.83 (1.81) SD standard deviation, CCI Charlson comorbidity Index hypoglycemia (57.39% male, mean age hospitalization compared to those aged less 69.11 years old) (Table 1). As shown in Table 2, than 65 years [OR 1.80 (1.64–1.98) and 2.73 the CCI scores for T2DM patients and for (2.43–3.06), respectively]. Patients aged 65–74 patients on insulin therapy were higher when years had a lower risk of outpatient visits than the patients were hypoglycemic than when they patients younger than 65 years old [OR 0.90 were not (4.62 vs. 3.66 and 4.77 vs. 3.83). (0.82–0.98)] and patients older than 74 years In T2DM patients, as compared with patients [OR 0.82 (0.74–0.91)]. When the 65–74 year-old who did not report hypoglycemia, the patients group was used as the reference, the risk for with hypoglycemia had a higher number of patients older than 74 was 1.51 times that for medical visits (19.48 vs. 10.46) (Table 2), as well the reference group. Sicker T2DM patients had a as higher diabetes-related medical costs higher hospitalization risk than healthier ones, (¥5187.54 per visit vs. ¥3525.00 per visit) and as the OR for a CCI score of 5–10 vs. 0–4 was prescription drug costs (¥1349.40 per visit vs. 3.03 (2.72–3.37) and the OR for a CCI score of ¥641.92 per visit). As shown in Table 2, among 11–14 vs. 0–4 was 8.31 (2.63–26.28). The risk of the patients who received insulin therapy, the outpatient visits [OR 1.50 (1.36–1.66)] or hos- patients with hypoglycemia had a higher pitalization [OR 6.40 (4.52–9.05)] was higher in number of medical visits (23.45 vs. 14.12). hypoglycemic patients than in nonhypo- Among T2DM patients, the proportion with glycemic patients. Patients on insulin were at a 3? outpatient visits was 72.69% for the hypo- higher risk of walk-in visits than those who were glycemic group vs. 65.49% for the nonhypo- not on insulin [OR 1.11 (1.04–1.18)]. glycemic group, while the corresponding Table 4 presents the results of multivariable proportions with 3? hospitalizations were linear regression analysis for outpatient visits 75.90% and 50.24%, respectively. In a similar and Poisson regression for hospitalization. CCI manner, among the patients taking insulin, the [regression coefficient: 4.37 (3.98–4.76)], hypo- proportion with a mean number of outpatient glycemia [regression coefficient: 19.07 visits of 3? was 78.26% for hypoglycemic (17.60–20.54)], and insulin use [regression patients vs. 71.73% for nonhypoglycemic coefficient: 5.52 (4.63–6.41)] were positively patients, while the corresponding proportions correlated with the number of outpatient visits. The number of hospitalizations was positively with 3? admissions were 83.19% and 58.51%, respectively. associated with gender, CCI, hypoglycemia, and Table 3 shows effects of various patient insulin use [regression coefficients of 0.08 characteristics on the likelihood of outpatient (0.05–0.12), 0.17 (0.15–0.19), 0.75 (0.70–0.79), visits and hospital admissions. Compared with and 0.17 (0.14–0.20), respectively]. Neverthe- males, females had a lower risk of outpatient less, when the 19–64 year-old group was selec- visits [OR 0.79 (0.73–0.84)] but a higher hospi- ted as the reference, the regression coefficient of talization risk [OR 1.15 (1.08–1.22)]. Patients the 65–74 year-old group was - 0.19 [- 0.22 to aged 65–74 years and patients older than 74 - 0.15] and that of the over 74 year-old group years showed an increased frequency of was 0.20 (0.16–0.23), meaning that the Diabetes Ther (2018) 9:1073–1082 1077 Table 2 Dependence of HCRU and associated costs on patient characteristics Characteristic Type 2 diabetes mellitus patients Patients on insulin therapy Hypoglycemic Nonhypoglycemic Hypoglycemic Nonhypoglycemic Number of visits to the 19.48 (33.79) 10.46 (19.15) 23.45 (35.95) 14.12 (24.16) physician, mean (SD) Number of outpatient visits None, N (%) 118 (15.13) 4218 (17.90) 40 (11.59) 1251 (15.95) 1–2, N (%) 95 (12.18) 3897 (16.60) 35 (10.14) 966 (12.32) 3? , N (%) 567 (72.69) 15,565 (65.49) 270 (78.26) 5625 (71.73) Number of times patient was hospitalized None, N (%) 3 (0.38) 4300 (18.76) 2 (0.58) 1348 (17.19) 1–2, N (%) 185 (23.72) 7284 (31.00) 56 (16.23) 1906 (24.31) 3? , N (%) 592 (75.90) 12,096 (50.24) 287 (83.19) 4588 (58.51) Costs (CNY) Medical cost per visit, 5817.54 (18,156.07) 3525.00 (6832.26) 6948.84 (14,325.21) 3401.15 (6483.15) mean (SD) Prescription drug cost 1349.40 (34,574.53) 641.92 (27,294.43) 1363.87 (37,434.04) 853.96 (34,037.53) per visit, mean (SD) Inpatient cost per 27,437.44 (37,902.24) 10,153.36 (18,671.26) 40,140.41 (42,615.87) 13,529.81 (21,940.84) admission, mean (SD) Outpatient cost per 11,761.44 (32,801.13) 4608.88 (14,584.99) 14,296.82 (33,739.50) 6865.97 (19,358.07) visit, mean (SD) Outpatient 7605.88 (24,349.99) 3086.11 (11,152.56) 9569.48 (25,095.73) 4734.81 (14,353.15) reimbursement per person, mean (SD) HCRU health care resource use Values shown are the number and percentage of hypoglycemic T2DM patients / nonhypoglycemic T2DM patients / hypoglycemic patients on insulin therapy / nonhypoglycemic patients on insulin therapy (depending on the column considered) who performed the specified number of outpatient visits or were hospitalized the specified number of times Exchange rate: USD 1 = CNY 6.40 frequency of hospitalization was lowest in the from a hospital to examine diabetes manage- 65–74 year-old group and highest in patients ment in China. Hypoglycemia is commonly older than 74 years. drug-induced in T2DM patients, while the most common cause of severe hypoglycemia is insufficient food intake [10]. Among the T2DM DISCUSSION patients on insulin in our study, those who reported hypoglycemia performed more visits To the best of our knowledge, our study is one to the physician, were admitted to hospital of the first to use electronic medical records more, and presented a greater economic burden 1078 Diabetes Ther (2018) 9:1073–1082 Table 3 Results of the binary logistic regression analysis of In our study, we found that a confounder, the effects of various patient characteristics on the likeli- age, influenced hospitalization frequency: older hood of outpatient visits and hospital admissions patients were at a higher risk of hospitalization a a than 19–64 year-old patients. Patients older Variable Outpatient Inpatient than 74 years presented a lower frequency of OR 95% CI OR 95% CI hospitalization. However, this effect may relate to the association between age and the inci- Age (count; 19–64 group used as reference) dence of hypoglycemia and related complica- 19–64 (18,285) – – – – tions. Elderly patients are more likely to develop complications of hypoglycemia due to decreas- 65–74 (10,620) 0.90 0.82–0.98 1.80 1.64–1.98 ing physiological function [10]. The elderly are C 75 (8818) 0.82 0.74–0.91 2.73 2.43–3.06 more prone to hypoglycemia than other age Age (count; 65–74 group used as reference) groups, but they also find it more difficult to spot their own symptoms of hypoglycemia 19–64 (18,285) 1.12 1.01–1.23 0.55 0.50–0.61 [29, 30]. To avoid severe complications, the 65–74 (10,620) – – – – target blood glucose level among the elderly could be adjusted to give a moderate regimen C 75 (8818) 0.92 0.82–1.02 1.51 1.33–1.73 with a target HbA1c level that is above 7% [31]. Gender 0.88 0.83–0.93 1.15 1.08–1.22 Self-monitoring and family support are important for T2DM patients, as they make it CCI score more likely that hypoglycemia will be identified 0–4 (26,363) – – – – promptly, and glycemic status could be moni- tored dynamically to ensure that blood glucose 5–10 (12,355) 1.05 0.97–1.15 3.03 2.72–3.37 levels remain optimal [32, 33]. Adherence to the 11–14 (124) 0.94 0.55–1.59 8.31 2.62–26.28 treatment regimen also influences the fre- Hypoglycemia 1.50 1.36–1.66 6.40 4.52–9.05 quency of hypoglycemia, while adherence to diabetes treatment has generally been found to Insulin 1.11 1.04–1.18 1.02 0.96–1.09 be poor [34, 35]. Efforts have been made to The dependent variable is a binary variable: whether the reduce the healthcare costs associated with patient was an outpatient or whether they required hypoglycemia and to increase knowledge of hospitalization hypoglycemia in patients and their families Independent variable: 0 = female/no; 1 = male/yes [36]. In addition to alleviating the hypo- glycemia itself, hypoglycemic patients should be shifted to a more appropriate insulin therapy (especially in terms of diabetes drugs) than option in order to reduce side effects, improve those who did not report hypoglycemia. These the outcome, and to initially mitigate the bur- den on the patient [6, 37–41]. findings are consistent with previous research showing that hypoglycemia significantly influ- There are some limitations of this study. First, the retrospective design of the study ences productivity and health care resource utilization and negatively affects patient quality meant that we could not pinpoint the causality in the relationship of T2DM-related hypo- of life [10, 17]. Studies show that patients who suffer from hypoglycemia tend to interrupt the glycemia to HCRU and costs. Second, there may have been a selection bias, since we only therapy regimen (i.e., perform more medical visits) and are associated with higher diabetes- obtained medical records from one hospital, related costs [15, 23]. Among these costs, those and those records lacked data on discharge sta- associated with treating complications and tus and length of hospital stay, which are two drugs were the highest [24]. Whether or not the important HCRU factors. Third, the hypo- glycemia cases considered in this study were hypoglycemia is severe, the economic burden of a hypoglycemic patient is higher than that of a those of severe hypoglycemia, which requires medical attention. Cases of asymptomatic nonhypoglycemic patient [25–28]. Diabetes Ther (2018) 9:1073–1082 1079 Table 4 Factors associated with HCRU in T2DM patients a b c Factor Outpatient visits Hospitalization Regression coefficient 95% CI Regression coefficient 95% CI Age (years) 19–64 – – – – 65–74 - 0.30 - 0.31 to - 0.29 - 0.19 - 0.22 to - 0.15 C 75 0.31 0.30–0.32 0.20 0.16–0.23 Gender 0.20 - 0.64 to 1.04 0.08 0.05–0.12 CCI 4.37 3.98–4.76 0.17 0.15–0.19 Hypoglycemia 19.07 17.60–20.54 0.75 0.70–0.79 Insulin 5.52 4.63–6.41 0.17 0.14–0.20 CI confidence interval The dependent variable is a continuous variable: the number of outpatient visits or hospitalizations Using linear regression for outpatient visits, 0 = female/no; 1 = male/yes for independent variables Using Poisson regression for hospitalization, 0 = male/yes; 1 = female/no for independent variables hypoglycemia were not included in the hypo- Provincial Science and Technology Department glycemia group, meaning that the prevalence (20171BCD40024) helped to fund this study and therefore social cost of hypoglycemia may and the article processing charges, as did a grant have been underestimated in this study. Lastly, from the General Project of the Jiangxi Provin- this study is a single-institute study, so the cial Science and Technology Department results may not be representative of the Chinese (2017BBH80025). health system nationally; our findings cannot Authorship. All named authors meet the therefore be generalized to primary health International Committee of Medical Journal institutions or other areas in China. Editors (ICMJE) criteria for authorship for this article, take responsibility for the integrity of CONCLUSION the work as a whole, and have given their approval for this version to be published. The Insulin use and hypoglycemia in T2DM patients opinions of all authors are fully represented in are associated with an increased likelihood of the publication. medical visits as well as greater healthcare resource utilization by and health-related Author Contributions. Yingping Yi and expenditure on the patient. To ease the disease Yawei Li contributed equally to this manuscript burden on and the economic burden of the and designed and analyzed the study. Yawei Li patient, the insulin treatment regimen needs to and Anran Hou analyzed and explained features be individualized, taking into account the of the data. Yanqiu Ge, Yuan Xu, Gang Xiong, patient’s status. and Xinlei Yang collected the data and helped to analyze it. Stephanie Ann Acevedo helped with the proofreading and provided important suggestions regarding the layout of the paper. ACKNOWLEDGEMENTS The corresponding authors Hua Xu and Lizheng Shi provided important suggestions about the design of the study and about how to refine the Funding. A grant from the Science and analysis of the data. Technology Innovation Platform of the Jiangxi 1080 Diabetes Ther (2018) 9:1073–1082 5. Wong J, Tabet E. The introduction of insulin in type Disclosures. All of the named authors— 2 diabetes mellitus. Aust Fam Physician. 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A Retrospective Cohort Study of Patients with Type 2 Diabetes in China: Associations of Hypoglycemia with Health Care Resource Utilization and Associated Costs

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Medicine & Public Health; Internal Medicine; Diabetes; Cardiology; Endocrinology
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Abstract

Diabetes Ther (2018) 9:1073–1082 https://doi.org/10.1007/s13300-018-0409-1 ORIGINAL RESEARCH A Retrospective Cohort Study of Patients with Type 2 Diabetes in China: Associations of Hypoglycemia with Health Care Resource Utilization and Associated Costs . . . . Yingping Yi Yawei Li Anran Hou Yanqiu Ge . . . . Yuan Xu Gang Xiong Xinlei Yang Stephanie Ann Acevedo Lizheng Shi Hua Xu Received: February 2, 2018 / Published online: April 5, 2018 The Author(s) 2018 Methods: This retrospective cohort study was ABSTRACT conducted with 23,680 T2DM patients [18 years old who visited the Second Affiliated Introduction: This study aimed to examine the Hospital of Nanchang University between 1 associations of hypoglycemia with health care January 2011 and 31 December 2015. Univari- resource utilization (HCRU) and health care ate descriptive statistics were used to relate the costs among patients with type 2 diabetes mel- HCRU and associated costs to patient charac- litus (T2DM) in China. teristics, and regression analysis was used to examine the association between hypoglycemia Enhanced content To view enhanced content for this and HCRU, controlling for other confounding article go to https://doi.org/10.6084/m9.figshare. factors. Results: In the T2DM patients with or without Yingping Yi and Yawei Li contributed equally to the insulin treatment, when compared with non- article as first authors. hypoglycemic patients, hypoglycemia was Y. Xu  G. Xiong Y. Yi  X. Yang Medical Big-Data Center, The Second Affiliated Department of Science and Education, The Second Hospital of Nanchang University, No. 1 Minde Affiliated Hospital of Nanchang University, No. 1 Road, Nanchang 330006, Jiangxi, People’s Republic Minde Road, Nanchang 330006, Jiangxi, People’s of China Republic of China S. A. Acevedo Y. Li  L. Shi (&) Department of Community Health, School of Public Department of Global Health Management and Health and Tropical Medicine, Tulane University, Policy, School of Public Health and Tropical 119A N. Alexander St, New Orleans, LA 70119, USA Medicine, Tulane University, 1440 Canal Street, Suite 1900, New Orleans, LA 70112, USA H. Xu (&) e-mail: lshi1@tulane.edu School of Biomedical Informatics, The University of Texas, Health Science Center at Houston, 7000 A. Hou Fannin, Houston, TX 77030, USA Suzhou Hebta Health Information Technology Co., e-mail: Hua.Xu@uth.tmc.edu Ltd, 10-302 Creative Industrial Park, No. 328, Xinghu Street, Suzhou Industrial Park, Suzhou 215123, People’s Republic of China Y. Ge School of Public Health, Medical School, Nanchang University, No. 1 Minde Road, Nanchang 330006, Jiangxi, People’s Republic of China 1074 Diabetes Ther (2018) 9:1073–1082 associated with more medical visits (all T2DM 12% (114 million) of Chinese adults are diabetic patients 19.48 vs. 10.46, insulin users 23.45 vs. (Dr. Margaret Chan at the 47th Meeting of the 14.12) and higher diabetes-related medical costs National Academy of Medicine, 2016). Adults (all T2DM patients ¥5187.54 vs. ¥3525.00, living with diabetes suffer from a long-term insulin users ¥6948.84 vs. ¥3401.15) and medi- economic burden and are at high risk of blind- cation costs (T2DM patients ¥1349.40 vs. ness, kidney failure, lower limb amputation, ¥641.92, insulin users: ¥1363.87 vs. ¥853.96). and several other long-term consequences that Controlling for age, gender, and Charlson impact significantly on their quality of life [1]. comorbidity index (CCI) score, hypoglycemia Most (80–90%) cases of diabetes mellitus are and insulin intake were associated with greater of type 2 (T2DM), which is a progressive disease health care resource utilization. As compared to that affects glucose regulation [2, 3]. In recent nonhypoglycemic patients, hypoglycemic years, the main goal of T2DM treatment has T2DM patients and those on insulin therapy been to achieve good glycemic control [3] performed more outpatient visits (proportions through a combination of diet, physical activ- of hypoglycemic vs nonhypoglycemic T2DM ity, and—if necessary—medication. Insulin patients performing 3? visits: 72.69% vs. therapy is an effective medication for achieving 65.49%; proportions of hypoglycemic vs non- a common target of T2DM treatment: a glycated hypoglycemic patients on insulin therapy per- hemoglobin (HbA1c) level of below 7% [4, 5]. forming 3? visits: 78.26% vs. 71.73%) and were However, insulin therapy is a risk factor for hospitalized more often (proportions of hypo- iatrogenic hypoglycemia [6–9]. Diabetes-related glycemic vs nonhypoglycemic T2DM patients hypoglycemia can cause complications such as with 3? admissions 75.90% vs. 50.24%; pro- pronounced effects on the cardiovascular (CV) portions of hypoglycemic vs nonhypoglycemic system, atherosclerosis, patient depression, and patients on insulin therapy with 3? admissions: even death [9–14]. Hypoglycemia can also sig- 83.19% vs. 58.51%). nificantly affect the quality of life of elderly Conclusion: Hypoglycemia in diabetes patients patients due to their increased potential for was associated with increased healthcare dysrhythmias, accidents, falls, and neurological resource utilization and health-related expen- symptoms [15, 16]. All of these substantially diture, especially for patients on insulin treat- influence healthcare utilization by and the ment. Insulin treatment regimens should be burden of healthcare costs for diabetic patients more individualized and account for hypo- [15, 17]. glycemia risk. International studies have indicated that even though hypoglycemia prevalence varies markedly from country to country, the preva- Keywords: Diabetes; Healthcare cost; lence of hypoglycemia in each country is gen- Healthcare utilization; Hypoglycemia erally underestimated [17, 18]. In some recent Chinese studies it was found that the level of INTRODUCTION monitoring of glucose control outcomes varies among regions, but that the usage of insulin Diabetes is currently one of the biggest public therapy is commonly high and is continuously increasing [19–22]. health issues worldwide. The World Health Organization states that the prevalence of dia- Given the increasing rate of hypoglycemia, the objective of this study of a subgroup of betes has risen continuously from a total of 108 million (4.7%) globally in 1980 to around four insulin users was to examine health care resource utilization (HCRU) by and health-re- times that number (8.5%) in 2014. China, which has the world’s largest population and is lated costs for Chinese T2DM patients with or without hypoglycemia. undergoing sustained economic growth, is cur- rently facing a serious diabetes epidemic: nearly Diabetes Ther (2018) 9:1073–1082 1075 Statistical Methods METHODS Univariate descriptive statistics were used to Data Sources describe the patient diabetes-specific HCRU and associated costs. Continuous data were reported This retrospective cohort study was conducted as mean values and standard deviations (SD), with 23,680 patients with type 2 diabetes who and categorical data were reported as percent- were selected from 1,477,727 patients who were ages. T2DM patients and patients on insulin over 18 years old and visited the Second Affili- therapy with or without hypoglycemia were ated Hospital of Nanchang University (SAHNU) compared in terms of the number of visits to a between 1 January 2011 and 31 December 2015. physician, the percentage of patients who per- All of the patients in this study were required to formed 3? outpatient visits, the percentage of be alive and to visit the SAHNU at least once a patients who underwent 3? hospitalizations, year during the 4-year period. At visits to the and associated medical costs. SAHNU, patients were required to provide Binary logistic regression analysis was used venous blood after fasting for [8 h overnight. to estimate the likelihood of an outpatient visit Serum was separated from the venous blood and and the likelihood of hospitalization in the stored at - 80 C before inspection. The elec- diabetes patients, and then groups of patients tronic medical records from the Second Affili- were compared based on an independent vari- ated Hospital of Nanchang University database able: either age group (19–64 years old, 65–- were processed using the da Vinci S system 74 years old, or C 75 years old), gender, (provided by HEBTA, Pearland, TX, USA). The Charlson comorbidity index (CCI) score (0–4, records included admission, diagnosis, medica- 5–10, or 11–14), hypoglycemic/nonhypo- tion, testing, surgical, nursing, and cost data as glycemic, and insulin use. well as images, and the database contained all of To further probe the relationship between the clinical data for the hospital. We calculated HCRU and hypoglycemia, two multiple regres- the HCRU associated with diabetes complica- sion analyses controlling for baseline charac- tions in both the hypoglycemic and nonhypo- teristics were conducted: a linear regression glycemic cohorts. analysis of the number of outpatient visits and a Poisson regression analysis of number of hos- Variables pitalizations. All statistical data were analyzed using the SPSS19.0 software package. Type 2 diabetes mellitus was identified in this study based on the ICD-10 codes E11, E11.901, and E11.902. The date of first recorded T2DM COMPLIANCE WITH ETHICS diagnosis was defined as the index date. Pre- GUIDELINES index-date patient information was used to derive baseline data on demographic and illness This article is based on previously conducted characteristics. Hypoglycemia after the index studies of de-identified medical records and date was identified based on the ICD-10 codes does not contain any studies with human par- E16.01, E16.001, E16.101, and E16.201, or a ticipants or animals performed by any of the laboratory-measured glucose level authors. of B 3.9 mmol/L. Post-index-date diabetes- specific HCRU variables included number of medical visits and hospitalization. Post-index- RESULTS date health care costs included medical costs and prescription drug costs. Among 23,680 patients with type 2 diabetes mellitus, 3.29% reported hypoglycemia (54.87% male, mean age 69.02 years old). Among the insulin users (n = 8187), 4.21% suffered from 1076 Diabetes Ther (2018) 9:1073–1082 Table 1 Baseline demographics and illness characteristics of the patients Characteristic Type 2 diabetes mellitus patients Patients on insulin therapy Hypoglycemic Nonhypoglycemic Hypoglycemic Nonhypoglycemic Number of patients (%) 780 (3.29) 22,900 (96.70) 345 (4.21) 7842 (95.78) Age in years, mean (SD) 69.02 (11.55) 64.01 (12.81) 69.11 (11.73) 63.14 (13.16) Gender (male %) 482 (54.87) 12,458 (54.40) 198 (57.39) 4386 (55.92) CCI score, mean (SD) 4.62 (1.86) 3.66 (1.66) 4.77 (1.93) 3.83 (1.81) SD standard deviation, CCI Charlson comorbidity Index hypoglycemia (57.39% male, mean age hospitalization compared to those aged less 69.11 years old) (Table 1). As shown in Table 2, than 65 years [OR 1.80 (1.64–1.98) and 2.73 the CCI scores for T2DM patients and for (2.43–3.06), respectively]. Patients aged 65–74 patients on insulin therapy were higher when years had a lower risk of outpatient visits than the patients were hypoglycemic than when they patients younger than 65 years old [OR 0.90 were not (4.62 vs. 3.66 and 4.77 vs. 3.83). (0.82–0.98)] and patients older than 74 years In T2DM patients, as compared with patients [OR 0.82 (0.74–0.91)]. When the 65–74 year-old who did not report hypoglycemia, the patients group was used as the reference, the risk for with hypoglycemia had a higher number of patients older than 74 was 1.51 times that for medical visits (19.48 vs. 10.46) (Table 2), as well the reference group. Sicker T2DM patients had a as higher diabetes-related medical costs higher hospitalization risk than healthier ones, (¥5187.54 per visit vs. ¥3525.00 per visit) and as the OR for a CCI score of 5–10 vs. 0–4 was prescription drug costs (¥1349.40 per visit vs. 3.03 (2.72–3.37) and the OR for a CCI score of ¥641.92 per visit). As shown in Table 2, among 11–14 vs. 0–4 was 8.31 (2.63–26.28). The risk of the patients who received insulin therapy, the outpatient visits [OR 1.50 (1.36–1.66)] or hos- patients with hypoglycemia had a higher pitalization [OR 6.40 (4.52–9.05)] was higher in number of medical visits (23.45 vs. 14.12). hypoglycemic patients than in nonhypo- Among T2DM patients, the proportion with glycemic patients. Patients on insulin were at a 3? outpatient visits was 72.69% for the hypo- higher risk of walk-in visits than those who were glycemic group vs. 65.49% for the nonhypo- not on insulin [OR 1.11 (1.04–1.18)]. glycemic group, while the corresponding Table 4 presents the results of multivariable proportions with 3? hospitalizations were linear regression analysis for outpatient visits 75.90% and 50.24%, respectively. In a similar and Poisson regression for hospitalization. CCI manner, among the patients taking insulin, the [regression coefficient: 4.37 (3.98–4.76)], hypo- proportion with a mean number of outpatient glycemia [regression coefficient: 19.07 visits of 3? was 78.26% for hypoglycemic (17.60–20.54)], and insulin use [regression patients vs. 71.73% for nonhypoglycemic coefficient: 5.52 (4.63–6.41)] were positively patients, while the corresponding proportions correlated with the number of outpatient visits. The number of hospitalizations was positively with 3? admissions were 83.19% and 58.51%, respectively. associated with gender, CCI, hypoglycemia, and Table 3 shows effects of various patient insulin use [regression coefficients of 0.08 characteristics on the likelihood of outpatient (0.05–0.12), 0.17 (0.15–0.19), 0.75 (0.70–0.79), visits and hospital admissions. Compared with and 0.17 (0.14–0.20), respectively]. Neverthe- males, females had a lower risk of outpatient less, when the 19–64 year-old group was selec- visits [OR 0.79 (0.73–0.84)] but a higher hospi- ted as the reference, the regression coefficient of talization risk [OR 1.15 (1.08–1.22)]. Patients the 65–74 year-old group was - 0.19 [- 0.22 to aged 65–74 years and patients older than 74 - 0.15] and that of the over 74 year-old group years showed an increased frequency of was 0.20 (0.16–0.23), meaning that the Diabetes Ther (2018) 9:1073–1082 1077 Table 2 Dependence of HCRU and associated costs on patient characteristics Characteristic Type 2 diabetes mellitus patients Patients on insulin therapy Hypoglycemic Nonhypoglycemic Hypoglycemic Nonhypoglycemic Number of visits to the 19.48 (33.79) 10.46 (19.15) 23.45 (35.95) 14.12 (24.16) physician, mean (SD) Number of outpatient visits None, N (%) 118 (15.13) 4218 (17.90) 40 (11.59) 1251 (15.95) 1–2, N (%) 95 (12.18) 3897 (16.60) 35 (10.14) 966 (12.32) 3? , N (%) 567 (72.69) 15,565 (65.49) 270 (78.26) 5625 (71.73) Number of times patient was hospitalized None, N (%) 3 (0.38) 4300 (18.76) 2 (0.58) 1348 (17.19) 1–2, N (%) 185 (23.72) 7284 (31.00) 56 (16.23) 1906 (24.31) 3? , N (%) 592 (75.90) 12,096 (50.24) 287 (83.19) 4588 (58.51) Costs (CNY) Medical cost per visit, 5817.54 (18,156.07) 3525.00 (6832.26) 6948.84 (14,325.21) 3401.15 (6483.15) mean (SD) Prescription drug cost 1349.40 (34,574.53) 641.92 (27,294.43) 1363.87 (37,434.04) 853.96 (34,037.53) per visit, mean (SD) Inpatient cost per 27,437.44 (37,902.24) 10,153.36 (18,671.26) 40,140.41 (42,615.87) 13,529.81 (21,940.84) admission, mean (SD) Outpatient cost per 11,761.44 (32,801.13) 4608.88 (14,584.99) 14,296.82 (33,739.50) 6865.97 (19,358.07) visit, mean (SD) Outpatient 7605.88 (24,349.99) 3086.11 (11,152.56) 9569.48 (25,095.73) 4734.81 (14,353.15) reimbursement per person, mean (SD) HCRU health care resource use Values shown are the number and percentage of hypoglycemic T2DM patients / nonhypoglycemic T2DM patients / hypoglycemic patients on insulin therapy / nonhypoglycemic patients on insulin therapy (depending on the column considered) who performed the specified number of outpatient visits or were hospitalized the specified number of times Exchange rate: USD 1 = CNY 6.40 frequency of hospitalization was lowest in the from a hospital to examine diabetes manage- 65–74 year-old group and highest in patients ment in China. Hypoglycemia is commonly older than 74 years. drug-induced in T2DM patients, while the most common cause of severe hypoglycemia is insufficient food intake [10]. Among the T2DM DISCUSSION patients on insulin in our study, those who reported hypoglycemia performed more visits To the best of our knowledge, our study is one to the physician, were admitted to hospital of the first to use electronic medical records more, and presented a greater economic burden 1078 Diabetes Ther (2018) 9:1073–1082 Table 3 Results of the binary logistic regression analysis of In our study, we found that a confounder, the effects of various patient characteristics on the likeli- age, influenced hospitalization frequency: older hood of outpatient visits and hospital admissions patients were at a higher risk of hospitalization a a than 19–64 year-old patients. Patients older Variable Outpatient Inpatient than 74 years presented a lower frequency of OR 95% CI OR 95% CI hospitalization. However, this effect may relate to the association between age and the inci- Age (count; 19–64 group used as reference) dence of hypoglycemia and related complica- 19–64 (18,285) – – – – tions. Elderly patients are more likely to develop complications of hypoglycemia due to decreas- 65–74 (10,620) 0.90 0.82–0.98 1.80 1.64–1.98 ing physiological function [10]. The elderly are C 75 (8818) 0.82 0.74–0.91 2.73 2.43–3.06 more prone to hypoglycemia than other age Age (count; 65–74 group used as reference) groups, but they also find it more difficult to spot their own symptoms of hypoglycemia 19–64 (18,285) 1.12 1.01–1.23 0.55 0.50–0.61 [29, 30]. To avoid severe complications, the 65–74 (10,620) – – – – target blood glucose level among the elderly could be adjusted to give a moderate regimen C 75 (8818) 0.92 0.82–1.02 1.51 1.33–1.73 with a target HbA1c level that is above 7% [31]. Gender 0.88 0.83–0.93 1.15 1.08–1.22 Self-monitoring and family support are important for T2DM patients, as they make it CCI score more likely that hypoglycemia will be identified 0–4 (26,363) – – – – promptly, and glycemic status could be moni- tored dynamically to ensure that blood glucose 5–10 (12,355) 1.05 0.97–1.15 3.03 2.72–3.37 levels remain optimal [32, 33]. Adherence to the 11–14 (124) 0.94 0.55–1.59 8.31 2.62–26.28 treatment regimen also influences the fre- Hypoglycemia 1.50 1.36–1.66 6.40 4.52–9.05 quency of hypoglycemia, while adherence to diabetes treatment has generally been found to Insulin 1.11 1.04–1.18 1.02 0.96–1.09 be poor [34, 35]. Efforts have been made to The dependent variable is a binary variable: whether the reduce the healthcare costs associated with patient was an outpatient or whether they required hypoglycemia and to increase knowledge of hospitalization hypoglycemia in patients and their families Independent variable: 0 = female/no; 1 = male/yes [36]. In addition to alleviating the hypo- glycemia itself, hypoglycemic patients should be shifted to a more appropriate insulin therapy (especially in terms of diabetes drugs) than option in order to reduce side effects, improve those who did not report hypoglycemia. These the outcome, and to initially mitigate the bur- den on the patient [6, 37–41]. findings are consistent with previous research showing that hypoglycemia significantly influ- There are some limitations of this study. First, the retrospective design of the study ences productivity and health care resource utilization and negatively affects patient quality meant that we could not pinpoint the causality in the relationship of T2DM-related hypo- of life [10, 17]. Studies show that patients who suffer from hypoglycemia tend to interrupt the glycemia to HCRU and costs. Second, there may have been a selection bias, since we only therapy regimen (i.e., perform more medical visits) and are associated with higher diabetes- obtained medical records from one hospital, related costs [15, 23]. Among these costs, those and those records lacked data on discharge sta- associated with treating complications and tus and length of hospital stay, which are two drugs were the highest [24]. Whether or not the important HCRU factors. Third, the hypo- glycemia cases considered in this study were hypoglycemia is severe, the economic burden of a hypoglycemic patient is higher than that of a those of severe hypoglycemia, which requires medical attention. Cases of asymptomatic nonhypoglycemic patient [25–28]. Diabetes Ther (2018) 9:1073–1082 1079 Table 4 Factors associated with HCRU in T2DM patients a b c Factor Outpatient visits Hospitalization Regression coefficient 95% CI Regression coefficient 95% CI Age (years) 19–64 – – – – 65–74 - 0.30 - 0.31 to - 0.29 - 0.19 - 0.22 to - 0.15 C 75 0.31 0.30–0.32 0.20 0.16–0.23 Gender 0.20 - 0.64 to 1.04 0.08 0.05–0.12 CCI 4.37 3.98–4.76 0.17 0.15–0.19 Hypoglycemia 19.07 17.60–20.54 0.75 0.70–0.79 Insulin 5.52 4.63–6.41 0.17 0.14–0.20 CI confidence interval The dependent variable is a continuous variable: the number of outpatient visits or hospitalizations Using linear regression for outpatient visits, 0 = female/no; 1 = male/yes for independent variables Using Poisson regression for hospitalization, 0 = male/yes; 1 = female/no for independent variables hypoglycemia were not included in the hypo- Provincial Science and Technology Department glycemia group, meaning that the prevalence (20171BCD40024) helped to fund this study and therefore social cost of hypoglycemia may and the article processing charges, as did a grant have been underestimated in this study. Lastly, from the General Project of the Jiangxi Provin- this study is a single-institute study, so the cial Science and Technology Department results may not be representative of the Chinese (2017BBH80025). health system nationally; our findings cannot Authorship. All named authors meet the therefore be generalized to primary health International Committee of Medical Journal institutions or other areas in China. Editors (ICMJE) criteria for authorship for this article, take responsibility for the integrity of CONCLUSION the work as a whole, and have given their approval for this version to be published. The Insulin use and hypoglycemia in T2DM patients opinions of all authors are fully represented in are associated with an increased likelihood of the publication. medical visits as well as greater healthcare resource utilization by and health-related Author Contributions. Yingping Yi and expenditure on the patient. To ease the disease Yawei Li contributed equally to this manuscript burden on and the economic burden of the and designed and analyzed the study. Yawei Li patient, the insulin treatment regimen needs to and Anran Hou analyzed and explained features be individualized, taking into account the of the data. Yanqiu Ge, Yuan Xu, Gang Xiong, patient’s status. and Xinlei Yang collected the data and helped to analyze it. Stephanie Ann Acevedo helped with the proofreading and provided important suggestions regarding the layout of the paper. ACKNOWLEDGEMENTS The corresponding authors Hua Xu and Lizheng Shi provided important suggestions about the design of the study and about how to refine the Funding. A grant from the Science and analysis of the data. Technology Innovation Platform of the Jiangxi 1080 Diabetes Ther (2018) 9:1073–1082 5. Wong J, Tabet E. The introduction of insulin in type Disclosures. All of the named authors— 2 diabetes mellitus. Aust Fam Physician. Yingping Yi, Yawei Li, Anran Hou, Yanqiu Ge, 2015;44:278–83. Yuan Xu, Gang Xiong, Xinlei Yang, Stephanie Ann Acevedo, Lizheng Shi, and Hua Xu—certify 6. Wallia A, Molitch ME. Insulin therapy for type 2 diabetes mellitus. JAMA. 2014;311:2315–25. that they have no financial or other conflicting interests regarding this work. 7. Birkner K, Hudzik B, Gasior M. The impact of type 2 diabetes mellitus on prognosis in patients with Compliance with Ethics Guidelines. This non-ST elevation myocardial infarction. Pol J Car- article is based on previously conducted studies dio-Thorac Surg. 2017;14:127–32. and does not contain any studies with human 8. Herman ME, O’Keefe JH, Bell DSH, Schwartz SS. participants or animals performed by any of the Insulin therapy increases cardiovascular risk in type authors. 2 diabetes. Prog Cardiovasc Dis. 2017;60:422–34. Data Availability. The datasets generated 9. Hulkower RD, Pollack RM, Zonszein J. Under- standing hypoglycemia in hospitalized patients. and/or analyzed during the current study are Diabetes Manag. 2014;4:165–76. not publicly available due to the confidentiality provision of SAHNU, but are available from the 10. Kalra S, Mukherjee J, Ramachandran A, Saboo B, corresponding author on reasonable request. Shaikh S, Venkataraman S, Das A, et al. Hypo- glycemia: the neglected complication. Indian J Endocrinol Metab. 2013;17:819. Open Access. This article is distributed under the terms of the Creative Commons 11. Yang S-W, Park K-H, Zhou Y-J. The impact of Attribution-NonCommercial 4.0 International hypoglycemia on the cardiovascular system: phys- iology and pathophysiology. Angiology. License (http://creativecommons.org/licenses/ 2016;67:802–9. by-nc/4.0/), which permits any noncommer- cial use, distribution, and reproduction in any 12. Lee AK, Lee CJ, Huang ES, Sharrett AR, Coresh J, medium, provided you give appropriate credit Selvin E. 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Journal

Diabetes TherapySpringer Journals

Published: Apr 5, 2018

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