David Jiang

All Publications

• Enrollment in High-Deductible Health Plans and Incident Diabetes Complications. JAMA network open McCoy, R. G., Swarna, K. S., Jiang, D. H., Van Houten, H. K., Chen, J., Davis, E. M., Herrin, J. 2024; 7 (3): e243394

  Abstract

  Importance: Preventing diabetes complications requires monitoring and control of hyperglycemia and cardiovascular risk factors. Switching to high-deductible health plans (HDHPs) has been shown to hinder aspects of diabetes care; however, the association of HDHP enrollment with microvascular and macrovascular diabetes complications is unknown.Objective: To examine the association between an employer-required switch to an HDHP and incident complications of diabetes.Design, Setting, and Participants: This retrospective cohort study used deidentified administrative claims data for US adults with diabetes enrolled in employer-sponsored health plans between January 1, 2010, and December 31, 2019. Data analysis was performed from May 26, 2022, to January 2, 2024.Exposures: Adults with a baseline year of non-HDHP enrollment who had to switch to an HDHP because their employer offered no non-HDHP alternative in that year were compared with adults who were continuously enrolled in a non-HDHP.Main Outcomes and Measures: Mixed-effects logistic regression models examined the association between switching to an HDHP and, individually, the odds of myocardial infarction, stroke, hospitalization for heart failure, lower-extremity complication, end-stage kidney disease, proliferative retinopathy, treatment for retinopathy, and blindness. Models were adjusted for demographics, comorbidities, and medications, with inverse propensity score weighting used to account for potential selection bias.Results: The study included 42 326 adults who switched to an HDHP (mean [SD] age, 52 [10] years; 19 752 [46.7%] female) and 202 729 adults who did not switch (mean [SD] age, 53 [10] years; 89 828 [44.3%] female). Those who switched to an HDHP had greater odds of experiencing all diabetes complications (odds ratio [OR], 1.11; 95% CI, 1.06-1.16 for myocardial infarction; OR, 1.15; 95% CI, 1.09-1.21 for stroke; OR, 1.35; 95% CI, 1.30-1.41 for hospitalization for heart failure; OR, 2.53; 95% CI, 2.38-2.70 for end-stage kidney disease; OR, 2.23; 95% CI, 2.17-2.29 for lower-extremity complication; OR, 1.17; 95% CI, 1.13-1.21 for proliferative retinopathy; OR, 2.35; 95% CI, 2.18-2.54 for blindness; and OR, 2.28; 95% CI, 2.15-2.41 for retinopathy treatment).Conclusions and Relevance: This study found that an employer-driven switch to an HDHP was associated with increased odds of experiencing all diabetes complications. These findings reinforce the potential harm associated with HDHPs for people with diabetes and the importance of affordable and accessible chronic disease management, which is hindered by high out-of-pocket costs incurred by HDHPs.

  View details for DOI 10.1001/jamanetworkopen.2024.3394

  View details for PubMedID 38517436

• Legal infrastructure for pandemic response: lessons not learnt in the US. BMJ (Clinical research ed.) Mello, M. M., Jiang, D., Platt, E., Moran-McCabe, K., Burris, S. 2024; 384: e076269

  View details for DOI 10.1136/bmj-2023-076269

  View details for PubMedID 38346813

• Evaluation of High-Deductible Health Plans and Acute Glycemic Complications Among Adults With Diabetes JAMA NETWORK OPEN Jiang, D. H., Herrin, J., Van Houten, H. K., McCoy, R. G. 2023; 6 (1): e2250602

  Abstract

  Optimal diabetes care requires regular monitoring and care to maintain glycemic control. How high-deductible health plans (HDHPs), which reduce overall spending but may impede care by increasing out-of-pocket expenses, are associated with risks of severe hypoglycemia and hyperglycemia is unknown.To examine the association between an employer-forced switch to HDHP and severe hypoglycemia and hyperglycemia.This retrospective cohort study used deidentified administrative claims data for privately insured adults with diabetes from a single insurance carrier with multiple plans across the US between January 1, 2010, and December 31, 2018. Analyses were conducted between May 15, 2020, and November 3, 2022.Patients with 1 baseline year of enrollment in a non-HDHP whose employers subsequently forced a switch to an HDHP were compared with patients who did not switch.Mixed-effects logistic regression models were used to examine the association between switching to an HDHP and the odds of severe hypoglycemia and hyperglycemia (ascertained using diagnosis codes in emergency department [ED] visits and hospitalizations), adjusting for patient age, sex, race and ethnicity, region, income, comorbidities, glucose-lowering medications, baseline ED and hospital visits for hypoglycemia and hyperglycemia, and baseline deductible amount, and applying inverse propensity score weighting to account for potential treatment selection bias.The study population was composed of 42 326 patients who switched to an HDHP (mean [SD] age: 52 [10] years, 19 752 [46.7%] women, 7375 [17.4%] Black, 5740 [13.6%] Hispanic, 26 572 [62.8%] non-Hispanic White) and 202 729 patients who did not switch (mean [SD] age, 53 [10] years, 89 828 [44.3%] women, 29 551 [14.6%] Black, 26 689 [13.2%] Hispanic, 130 843 [64.5%] non-Hispanic White). When comparing all study years, switching to an HDHP was not associated with increased odds of experiencing at least 1 hypoglycemia-related ED visit or hospitalization (OR, 1.01 [95% CI, 0.95-1.06]; P = .85), but each year of HDHP enrollment did increase these odds by 2% (OR, 1.02 [95% CI, 1.00-1.04]; P = .04). In contrast, switching to an HDHP did significantly increase the odds of experiencing at least 1 hyperglycemia-related ED visit or hospitalization (OR, 1.25 [95% CI, 1.11-1.42]; P < .001), with each year of HDHP enrollment increasing the odds by 5% (OR, 1.05 [95% CI, 1.01-1.09]; P = .02).In this cohort study, employer-forced switching to an HDHP was associated with increased odds of potentially preventable acute diabetes complications, potentially because of delayed or deferred care. These findings suggest that employers should be more judicious in their health plan offerings, and health plans and policy makers should consider allowing preventive and high-value services to be exempt from deductible requirements.

  View details for DOI 10.1001/jamanetworkopen.2022.50602

  View details for Web of Science ID 001059414400002

  View details for PubMedID 36662531

  View details for PubMedCentralID PMC9860518

• Out-of-Pocket Cost Burden Associated With Contemporary Management of Advanced Prostate Cancer Among Commercially Insured Patients JOURNAL OF UROLOGY Joyce, D. D., Sharma, V., Jiang, D. H., Van Houten, H. K., Sangaralingham, L. R., Borah, B. J., Kwon, E. D., Penson, D. F., Dusetzina, S. B., Tilburt, J. C., Boorjian, S. A. 2022; 208 (5): 988-996

  Abstract

  Out-of-pocket costs represent an important component of financial toxicity and may impact patients' receipt of care. Herein, we evaluated patient-level factors associated with out-of-pocket costs for contemporary advanced prostate cancer treatment options.We identified all commercially insured men receiving treatment for advanced prostate cancer between 2007 and 2019 within the OptumLabs Data Warehouse®. Patients were categorized into 3 treatment groups: androgen deprivation monotherapy, novel hormonal therapy, and nonandrogen systemic therapy. The primary outcome was out-of-pocket costs in the first year of treatment. The associations of treatment and patient variables with out-of-pocket costs were assessed using multivariable regression models. All costs were adjusted to reflect 2019 U.S. dollars using the Consumer Price Index.In a cohort of 13,409 men 81% (n = 10,926) received androgen deprivation monotherapy, 6% (n = 832) novel hormonal therapy, and 12% (n = 1,651) nonandrogen systemic therapy. Mean treatment-related out-of-pocket costs in the first year were $165, $4,236, and $994 for androgen deprivation monotherapy, novel hormonal therapy, and nonandrogen systemic therapy, respectively. The adjusted difference in annual treatment-related out-of-pocket costs for novel hormonal therapy and nonandrogen systemic therapy were $2,581 (95% CI: $1,923-$3,240) and $752 (95% CI: $600-$903) higher than androgen deprivation monotherapy, respectively. Patient characteristics associated (P < .05) with higher treatment-related out-of-pocket costs included older age (65-74 years), Black race, lower comorbidity scores, and lower household income.Patients receiving novel hormonal therapy for advanced prostate cancer had substantially higher treatment-related out-of-pocket costs. In addition to raising awareness among prescribers, these data support the inclusion of treatment associated financial toxicity in shared decision making for advanced prostate cancer and call attention to subgroups of patients particularly vulnerable to financial toxicity.

  View details for DOI 10.1097/JU.0000000000002856

  View details for Web of Science ID 000947762500012

  View details for PubMedID 36094864

• Modernizing Diabetes Care Quality Measures HEALTH AFFAIRS Jiang, D. H., O'Connor, P. J., Huguet, N., Golden, S., McCoy, R. G. 2022; 41 (7): 955-962

  Abstract

  The proliferation of diabetes quality measures in the US since the mid-1990s has increased the burden of measurement without commensurate improvements in the quality of care or health outcomes. Measures in use today do not represent or incentivize achievement of care goals in all domains of quality that are necessary to achieve optimal diabetes health. We recommend reimagining and improving diabetes quality measurement through the following propositions: widespread adoption of new measures and modernization of existing measures across six domains of quality; use of a subset of new and modernized metrics as top-line measures for reporting and reimbursement; and optional use of the remaining new and modernized measures for evaluative purposes at all levels of the care delivery system to identify and address gaps in care quality and outcomes. These propositions would support practices and policies at all levels of the health care system to improve the health of people with diabetes.

  View details for DOI 10.1377/hlthaff.2022.00233

  View details for Web of Science ID 000827308500005

  View details for PubMedID 35759700

  View details for PubMedCentralID PMC9288231

• Association of stay-at-home orders and COVID-19 incidence and mortality in rural and urban United States: a population-based study BMJ OPEN Jiang, D. H., Roy, D. J., Pollock, B. D., Shah, N. D., McCoy, R. G. 2022; 12 (4): e055791

  Abstract

  We examined the association between stay-at-home order implementation and the incidence of COVID-19 infections and deaths in rural versus urban counties of the United States.We used an interrupted time-series analysis using a mixed effects zero-inflated Poisson model with random intercept by county and standardised by population to examine the associations between stay-at-home orders and county-level counts of daily new COVID-19 cases and deaths in rural versus urban counties between 22 January 2020 and 10 June 2020. We secondarily examined the association between stay-at-home orders and mobility in rural versus urban counties using Google Community Mobility Reports.Issuance of stay-at-home orders.Co-primary outcomes were COVID-19 daily incidence of cases (14-day lagged) and mortality (26-day lagged). Secondary outcome was mobility.Stay-at-home orders were implemented later (median 30 March 2020 vs 28 March 2020) and were shorter in duration (median 35 vs 54 days) in rural compared with urban counties. Indoor mobility was, on average, 2.6%-6.9% higher in rural than urban counties both during and after stay-at-home orders. Compared with the baseline (pre-stay-at-home) period, the number of new COVID-19 cases increased under stay-at-home by incidence risk ratio (IRR) 1.60 (95% CI, 1.57 to 1.64) in rural and 1.36 (95% CI, 1.30 to 1.42) in urban counties, while the number of new COVID-19 deaths increased by IRR 14.21 (95% CI, 11.02 to 18.34) in rural and IRR 2.93 in urban counties (95% CI, 1.82 to 4.73). For each day under stay-at-home orders, the number of new cases changed by a factor of 0.982 (95% CI, 0.981 to 0.982) in rural and 0.952 (95% CI, 0.951 to 0.953) in urban counties compared with prior to stay-at-home, while number of new deaths changed by a factor of 0.977 (95% CI, 0.976 to 0.977) in rural counties and 0.935 (95% CI, 0.933 to 0.936) in urban counties. Each day after stay-at-home orders expired, the number of new cases changed by a factor of 0.995 (95% CI, 0.994 to 0.995) in rural and 0.997 (95% CI, 0.995 to 0.999) in urban counties compared with prior to stay-at-home, while number of new deaths changed by a factor of 0.969 (95% CI, 0.968 to 0.970) in rural counties and 0.928 (95% CI, 0.926 to 0.929) in urban counties.Stay-at-home orders decreased mobility, slowed the spread of COVID-19 and mitigated COVID-19 mortality, but did so less effectively in rural than in urban counties. This necessitates a critical re-evaluation of how stay-at-home orders are designed, communicated and implemented in rural areas.

  View details for DOI 10.1136/bmjopen-2021-055791

  View details for Web of Science ID 000780200000018

  View details for PubMedID 35393311

  View details for PubMedCentralID PMC8990263

• Impact of High Deductible Health Plans on Diabetes Care Quality and Outcomes: Systematic Review ENDOCRINE PRACTICE Jiang, D. H., Mundell, B. F., Shah, N. D., McCoy, R. G. 2021; 27 (11): 1156-1164

  Abstract

  To provide a review of the impact of high deductible health plans (HDHPs) on the utilizations of services required for optimal management of diabetes and subsequent health outcomes.Systematic literature review of studies published between January 1, 2000, and May 7, 2021, was conducted that examined the impact of HDHP on diabetes monitoring (eg, recommended laboratory and surveillance testing), routine care (eg, ambulatory appointments), medication management (eg, medication initiation, adherence), and acute health care utilization (eg, emergency department visits, hospitalizations, incident complications).Of the 303 reviewed articles, 8 were relevant. These studies demonstrated that HDHPs lower spending at the expense of reduced high-value diabetes monitoring, routine care, and medication adherence, potentially contributing to the observed increases in acute health care utilization. Additionally, patient out-of-pocket costs for recommended screenings doubled, and total health care expenditures increased by 49.4% for HDHP enrollees compared with enrollees in traditional health plans. Reductions in disease monitoring and routine care and increases in acute health care utilization were greatest in lower-income patients. None of the studies examined the impact of HDHPs on access to diabetes self-management education, technology use, or glycemic control.Although HDHPs reduce some health care utilization and costs, they appear to do so at the expense of limiting high-value care and medication adherence. Policymakers, providers, and payers should be more cognizant of the potential for negative consequences of HDHPs on patients' health.

  View details for DOI 10.1016/j.eprac.2021.07.001

  View details for Web of Science ID 000717323600014

  View details for PubMedID 34245911

  View details for PubMedCentralID PMC8578412

• Postacute Sequelae of Severe Acute Respiratory Syndrome Coronavirus 2 Infection A State-of-the-Art Review JACC-BASIC TO TRANSLATIONAL SCIENCE Jiang, D. H., Roy, D. J., Gu, B. J., Hassett, L. C., McCoy, R. G. 2021; 6 (9-10): 796-811

  Abstract

  The vast majority of patients (>99%) with severe acute respiratory syndrome coronavirus 2 survive immediate infection but remain at risk for persistent and/or delayed multisystem. This review of published reports through May 31, 2021, found that manifestations of postacute sequelae of severe acute respiratory syndrome coronavirus 2 infection (PASC) affect between 33% and 98% of coronavirus disease 2019 survivors and comprise a wide range of symptoms and complications in the pulmonary, cardiovascular, neurologic, psychiatric, gastrointestinal, renal, endocrine, and musculoskeletal systems in both adult and pediatric populations. Additional complications are likely to emerge and be identified over time. Although data on PASC risk factors and vulnerable populations are scarce, evidence points to a disproportionate impact on racial/ethnic minorities, older patients, patients with preexisting conditions, and rural residents. Concerted efforts by researchers, health systems, public health agencies, payers, and governments are urgently needed to better understand and mitigate the long-term effects of PASC on individual and population health.

  View details for DOI 10.1016/j.jacbts.2021.07.002

  View details for Web of Science ID 000711000100010

  View details for PubMedID 34541421

  View details for PubMedCentralID PMC8442719

• Planning for the Post-COVID Syndrome: How Payers Can Mitigate Long-Term Complications of the Pandemic JOURNAL OF GENERAL INTERNAL MEDICINE Jiang, D. H., McCoy, R. G. 2020; 35 (10): 3036-3039

  Abstract

  As the COVID-19 pandemic continues to unfold, payers across the USA have stepped up to alleviate patients' financial burden by waiving cost-sharing for COVID-19 testing and treatment. However, there has been no substantive discussion of potential long-term effects of COVID-19 on patient health or their financial and policy implications. After recovery, patients remain at risk for lung disease, heart disease, frailty, and mental health disorders. There may also be long-term sequelae of adverse events that develop in the course of COVID-19 and its treatment. These complications are likely to place additional medical, psychological, and economic burdens on all patients, with lower-income individuals, the uninsured and underinsured, and individuals experiencing homelessness being most vulnerable. Thus, there needs to be a comprehensive plan for preventing and managing post-COVID-19 complications to quell their clinical, economic, and public health consequences and to support patients experiencing delayed morbidity and disability as a result.

  View details for DOI 10.1007/s11606-020-06042-3

  View details for Web of Science ID 000551354500005

  View details for PubMedID 32700223

  View details for PubMedCentralID PMC7375754