Impact of High Deductible Health Plans on Diabetes Care Quality and Outcomes: Systematic Review

Abstract

Objective:

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.

Methods:

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 healthcare utilization (eg, emergency department visits, hospitalizations, incident complications).

Results:

Of 303 reviewed articles, eight 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 observed increases in acute healthcare utilization. Additionally, patient out-of-pocket costs for recommended screenings doubled, and total healthcare expenditures increased 49.4%, for HDHP enrollees compared to enrollees in traditional health plans. Reductions in disease monitoring and routine care and increases in acute healthcare 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.

Conclusion:

Although HDHPs reduce some healthcare 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.

INTRODUCTION

High deductible health plans (HDHPs) were introduced and popularized over the past 2 decades as a mechanism of increasing access to health insurance while curbing overall healthcare costs.¹ HDHPs were initially favored by 2 types of enrollees: (1) those who were healthy, and thus did not want to pay high insurance premiums if they did not anticipate having substantial expenditures; and (2) those who were low-income, and thus were drawn to the lower premium rates for HDHPs compared to traditional health plans. More recently, however, HDHPs have become increasingly widespread as employers sought to provide the newly required minimal essential coverage to their workers at lower cost for to the employer, as required by the employer shared responsibility mandate of the Patient Protection and Affordable Care Act, whereby employers with more than 50 employees had to provide minimum essential health coverage.^2,3 Since then, the percentage of individuals enrolled in HDHPs has steadily grown to 30% of all people with employer-sponsored health plans.⁴ However, it remains unclear whether HDHPs have achieved the access and affordability goals policymakers intended and how they impacted the health of individuals covered by these health plans. This is particularly important because nearly half of HDHP enrollees either have a chronic health condition or have a family member with one, and out of those, half have reported substantial economic burdens.⁵ Thus, while HDHPs may lower overall healthcare expenditures for the system, they may do so at the expense of enrollee financial burden and health by discouraging them from seeking preventative and necessary care.

Previous studies of HDHPs’ effects on healthcare consumption have mainly focused on how patterns of utilization may differ between those enrolled in HDHPs and those in traditional plans, such as preferred provider organizations (PPOs) or health maintenance organizations (HMOs). For example, studies have shown that individuals enrolled in HDHPs have decreased completion of preventative services, such as child immunization, mammography,^6,7 and cervical and colorectal cancer screenings.^8,9 Other studies found seemingly favorable trends toward decreased emergency department (ED) utilization,^10-13 though without examining associated long-term health outcomes or the appropriateness of this deferred ED care. Indeed, there is no evidence that HDHP enrollees selectively forgo “unnecessary” care but continue to seek care that is clinically appropriate.¹⁴ Importantly, deferred care may have consequences. For example, HDHP enrollees with cancer experienced delays between diagnostic testing, diagnosis, and chemotherapy initiation.¹⁵ Similarly, enrollees with cardiovascular disease have reported increased nonadherence of critical cardiovascular medications.¹⁶

The increasing prevalence of diabetes in the U.S. has made it one of the costliest chronic health conditions both for the patient and society. In 2018, an estimated 34.1 million U.S. adults (13% of the adult population) were living with diabetes, while another 88 million adults (34.5% of the adult population) were living with prediabetes.^17,18 Poorly controlled diabetes is a strong risk factor for a wide range of complications, including blindness, kidney failure, cardiovascular disease, and lower extremity amputations; diabetes is also among the leading causes of premature death.^17,19 In 2017, diabetes cost the U.S. economy an estimated $327 billion, including $237 billion in direct medical costs incurred by treating diabetes and its complications and $90 billion in lost productivity.²⁰ Reducing the morbidity and costs associated with diabetes is, therefore, a priority for people living with diabetes, health systems, payers, and society.

Diabetes can be effectively managed with proper healthcare and medications, but the ability to access and afford this care depends on the type of health coverage that patients with diabetes have access to, if any. Our objective was to explore the current evidence base on the effects of HDHP enrollment on the quality of care and health outcomes of patients with diabetes. We focus specifically on receipt of preventive diabetes-related care and out-of-pocket costs, medication adherence, diabetes management, and healthcare utilization for potentially preventable diabetes complications.

METHODS

A comprehensive search of several databases from January 1, 2000 to May 7, 2021, in the English language (as the study was focused on health plans available only in the United States), was conducted. The databases included Ovid MEDLINE and Epub Ahead of Print, In-Process & Other Non-Indexed Citations, and Daily, Ovid EMBASE, Ovid Cochrane Central Register of Controlled Trials, and Ovid Cochrane Database of Systematic Reviews. The search strategy was designed and conducted by an experienced librarian with input from the study's principal investigators (D.H.J and R.G.M). Controlled vocabulary supplemented with keywords was used to search for references on high-deductible health care plans and their impact on utilization of care and health outcomes among patients with diabetes mellitus. The actual strategy listing all search terms used and how they are combined is available in Table 1. Only full-length articles were included. The reference lists from primarily studies were searched to obtain additional references that may have been missed by the initial search strategy. 303 articles were identified and screened by 2 reviewers (D.H.J. and R.G.M.). After review of abstracts and full-text studies for eligibility, 8 were confirmed pertinent and included in this review (Table 2).

Table 1: Search Strategies.

Database(s): EBM Reviews - Cochrane Central Register of Controlled Trials April 2021, EBM Reviews - Cochrane Database of Systematic Reviews 2005 to May 5, 2021, Embase 1974 to 2021 May 07 , Ovid MEDLINE® and Epub Ahead of Print, In-Process, In-Data-Review & Other Non-Indexed Citations and Daily 1946 to May 07, 2021 Search Strategy:

#	Searches	Results
1	(“high deductible” or “high-deductible” or “Insurance Deductible*”).tw.	754
2	limit 1 to english language [Limit not valid in CDSR; records were retained]	751
3	limit 2 to yr=“2000 -Current”	723
4	limit 3 to (conference abstract or editorial or erratum or note or addresses or autobiography or bibliography or biography or blogs or comment or dictionary or directory or interactive tutorial or interview or lectures or legal cases or legislation or news or newspaper article or overall or patient education handout or periodical index or portraits or published erratum or video-audio media or webcasts) [Limit not valid in CCTR,CDSR,Embase,Ovid MEDLINE®,Ovid MEDLINE® Daily Update,Ovid MEDLINE® PubMed not MEDLINE,Ovid MEDLINE® In-Process,Ovid MEDLINE® Publisher; records were retained]	157
5	3 not 4	566
6	remove duplicates from 5	303

Table 2:

Studies examining the impact of high deductible health plans on diabetes management and health outcomes

Study	Data		Methods			Results
	Year	Source	Design	Population	Subgroup	Outcome of Interest	Significant Results	Other Results
Wharam, et al. (2020)	2003-2014	“Large national commercial and MA dataset”	Observational before-after study, with matched cohorts	DM; HDHP n=29407 Control n=274986		Cumulative rates of first major cardiovascular events HD vs. Control	No significant difference
Fendrick, et al. (2019) 25	2013-2014	IBM MarketScan	Difference in Differences	DM; age ≥ 18; HDHP n=1490 Control n=1490	Uses at least 1 diabetes medication	Refill rates of branded diabetes medications	No refilla rate: 20.5% (HDHP) vs. 14%	Discontinuation rate of all diabetes medication; No refill & discontinuation rates of generic drugs
Wharam, et al. (2018) 27	2003-2012	Optum Database	Controlled interrupted time-series design; Matching	DM; age 12-64 HDHP n=23493 Control n=192842	Overall	Overall ED Visits	−4% Relative	Overall low-income and high-income emergency department visits; overall high-income hospitalizations
						Hospitalizations	−5.6% Relative
						Direct Hospitalizations	−11.1% Relative
						Total HC Expenditure	−3.8% Relative
				DM; age 12-64 HDHP n=8453 Control n=65468	low incomee neighborhoods	Low Severityb ED Visits	−8.8% Relative
						High Severityc ED Visits	10.5% Relative
						Hospitalizations	−5.7% Relative
						Total HC Expenditure	−2.7% Relative
						High Severity ED visit Expenditure Proxy Adverse Health Outcomesd	23.5% Relative
						Low Severity ED visit Expenditure Proxy Adverse Health Outcomes	−5.5% Relative
						High Severity Hospitalization Days Proxy Adverse Health Outcomes	27.4% Relative
				DM; age 12-64 HDHP n=14841 Control n=124479	high incomef neighborhoods	High severity ED Visits	−3.5% Relative
						Total HC Expenditure	−3.7% Relative
						High severity ED visit expenditure Proxy Adverse Health Outcomes	8% Relative
						High Severity Hospitalization Days Proxy Adverse Health Outcomes	−10.7% Relative
Wharam, et al. (2018) 26	2003-2012	Optum Database	Observation longitudinal comparison of matched groups	DM; age 12-64 HDHP n=33957 Control n=294942	Overall	Time to evaluation for first major symptom, Overall	1.5 month delay	Time to evaluation of CHD, CVD procedure, PAD procedure
						Time to evaluation for first major symptom, CVD	3.4 month delay
						Time to evaluation for first major symptom, PAD	1.8 month delay
						Time to first diagnosis, Overall	1.9 month delay
						Time to first diagnosis, CHD	2.5 month delay
						Time to first diagnosis, CVD	1.7 month delay
						Time to first diagnosis. PAD	3.3 month delay
						Time to first procedure, Overall	3.1 month delay
						Time to first procedure, CHD	3.9 month delay
Wharam, et al. (2017) 22	2003-2012	Optum Database	Controlled, cumulative monthly interrupted time-series design	DM; age 12-64 HDHP n=12084 Control n=12084 Low Morbidity n=7956 High Morbidity n=3640 High Income n=4555 Low Income n=4121 HSA HDHP n=1899	Overall	Total Out-of-Pocket Medical Expenditure	49.4% Relative	Sensitivity not significant; No significance between HDHP and Control in high priority outpatient visits for all subgroups
						Time to first outpatient and ED acute preventable diabetes complication visit	0.94 aHR (6% delay)
						Mean Acute Complication Visits per 1000 members	8% Relative
						Mean Acute Complications Expenditure	5.6% Relative
					Low Morbidityg	Total Out-of-Pocket Medical Expenditure	56.8% Relative
						Mean Acute Complications Expenditure	−4.2% Relative
					High Morbidityh	Total Out-of-Pocket Medical Expenditure	40.9% Relative
						Time to first outpatient and ED acute preventable diabetes complication visit	0.89 aHR (11% delay)
						Mean Acute Complication Visits per 1000 members	−5.2% Relative
						Mean Acute Complications Expenditure	12.1% Relative
					High Incomei	Total Out-of-Pocket Medical Expenditure	48.4% Relative
						Mean Acute Complication Visits per 1000 members	−7.3% Relative
					Low Incomej	Total Out-of-Pocket Medical Expenditure	51.7% Relative
						Time to first outpatient and ED acute preventable diabetes complication visit	0.89 aHR (11% delay)
						Mean Acute Complication Visits per 1000 members	21.7 Relative
						Mean Acute Complications Expenditure	9.5% Relative
					HSA HDHP	Total Out-of-Pocket Medical Expenditure	67.8% Relative
						Mean Acute Complication Visits per 1000 members	15.5% Relative
						Mean Acute Complications Expenditure	29.6% Relative
Rabin, et al. (2017) 23	2011-2013	Medical Expenditure Panel Survey	Bivariate and Regression Analysis	HDHP n=343 LD n=670 ND n=448	DM; age 18-64; low incomek	Utilization of Primary Care LD vs. ND	IRR 0.73	No significant differences between ND, LD, HD, for HbA1C, Feet exam, Eye Exam, Cholesterol Test, Flu Vaccinations, Diet Modifications, for low and high income group; No significant differences between ND, LD, HD for utilizations of ER visits and hospital stays for low income; No significant difference between ND, LD, HD for utilization of checkups and hospital stays, for high income group.
						Utilization of Primary Care HD vs. ND	IRR 0.58
						Utilization of Check Ups LD vs. ND	IRR 0.61
						Utilization of Check Ups HD vs. ND	IRR 0.35
						Utilization of Specialty Visits LD vs. ND	IRR 0.23
						Utilization of Specialty Visits HD vs. ND	IRR 0.14
					DM; age 18-64; high incomel	Utilization of Primary Care HD vs. ND	IRR 1.21
						Utilization of Specialty Visits LD vs. ND	IRR 0.72
						Utilization of ER visits LD vs. ND	OR 0.63
						Utilization of HbA1C (Adjusted) Testing HD vs. ND	IRR 0.79
Segel, et al. (2017)	2011-2013	Medical Expenditure Panel Survey	Multivariate quantile regression; multivariate logistic regression	HDHP n=4120 LD n=7767 ND n=5290	DM; age 18-64	Out-of-pocket spending HD vs. ND	50th percentile: Estimated Marginal Effects=444 90th percentile: Estimate Marginal Effects=1612	No significant association found between ND, LD, and HD for cost-related access barriers
						High Medical Cost Burdenm HD vs. ND	Estimated Marginal Effects=9.3
Reiss, et al. (2011) 24	2001-2008	Harvard Pilgrim Health Care Insurance Data	Interrupted Time-series with comparison group study	HDHP Overall n=3348 HDHP Control n=20534 HDHP DM n=108 Control DM n=640	DM; age 18-63	Utilization of DM meds	Inconsistent results pertaining to the use of DM medication	Trend changes for all prescription drugs, antihypertensive, lipid-lowering agents, and COPD/Asthma controllers.

Abbreviations: aHR, Adjusted Hazard Ratio; CVD, Cerebrovascular Disease; CAD, Coronary Artery Disease; DM, Diabetes Mellitus; ED, Emergency Department; HC, Healthcare; HSA, Health Savings Account; HD, High Deductible; HDHP, High Deductible Health Plans; HbA_1C, Hemoglobin A_1C; IRR, Incidence Risk Ratio; LD, Low Deductible; ND, No Deductible; OR, Odds Ratio; PAD, Peripheral Artery Disease

^a.No Refill: Failure to fill at least 1 script of drug after the index fill; discontinuation: no fills of drug after 60 days.

^b.Low Severity: The probability that the primary diagnosis required emergency department care is < 25%.

^c.High Severity: The probability that the primary diagnosis required emergency department care is ≥ 75%.

^d.Proxy Adverse Health Outcomes: An assessment of intensity of and need for high-acuity diagnostic and therapeutic services, developed by the authors.

^e.Low-income neighborhoods: Living in a neighborhood with below-poverty levels of ≥ 10%.

^f.High-income neighborhoods: Living in a neighborhood with below-poverty levels of < 10%.

^g.Low Morbidity: Johns Hopkins ACG system comorbidity score < 2.0.

^h.High Morbidity: Johns Hopkins ACG system comorbidity score > 3.0.

^i.High-income: Living in a neighborhood with below poverty level < 5%.

^j.Low-income: Living in a neighborhood with below poverty level ≥ 10%.

^k.Low-income: Annual income < 200% of federal poverty level.

^l.High-income: Annual income ≥ 200% of federal poverty level.

^m.High medical cost burden: annual likelihood of spending 10% or more of household income on health care

We organized the resulting papers depending on presented outcomes into 3 categories: (1) disease monitoring (eg, laboratory screening, foot and eye exams) and routine care (eg, ambulatory appointments for diabetes management, diabetes self-management education and support, dietician services); (2) medication management (ie, initiation, adherence, and persistence of pharmacotherapy of antihyperglycemics, lipid-lowering agents, antihypertensives, etc.); and (3) acute or emergent healthcare utilization (eg, ED visits or hospitalizations, incident diabetes complications). For each category, we queried the impact of HDHPs on the rates of and costs (patient out-of-pocket and overall, as available) associated with each of the outcomes.

RESULTS

Disease Monitoring and Routine Care

The impact of HDHPs on disease monitoring and routine care was examined in 3 articles. All found that HDHP enrollees experience a higher likelihood of reporting higher out-of-pocket costs for disease monitoring procedures and delays in obtaining routine care. Segel and Kullgren (2017) used Medical Expenditure Panel Survey data from 2011 to 2013 to estimate out-of-pocket cost-sharing responsibilities for medical care among patients with at least one chronic condition (including diabetes) who have high-, low-, and no-deductible health plans and to correlate high medical cost burden (defined as the annual likelihood of spending 10% or more of household income on health care) and self-reported unmet or delayed care due to cost.²¹ Among patients with diabetes, specifically, HDHP enrollees had significantly higher out-of-pocket spending and medical cost burden. For those in the 50^th percentile of out-of-pocket spending, patients with diabetes on HDHPs spent $444 and $239 more per year than their no-deductible and low-deductible counter parts, respectively. The effect was more pronounced for those in the 90^th percentile of spending, where those with HDHPs spent $1,612 per year more compared to those with no deductibles. The authors also found that the prevalence of high medical cost burden was 9.3 percentage points higher among patients with diabetes on HDHPs than on no deductible plans. Segel and Kullgren did not examine the impact of higher cost-sharing obligations or deferred/delayed care on diabetes-related (or any other) health outcomes.

A 2017 study by Wharam and colleagues used data from Optum (a dataset of commercially insured individuals) to match 12,084 HDHP beneficiaries with diabetes with non-HDHP counterparts to examine utilization patterns and associated out-of-pocket medical expenditures for monitoring, preventative care, and acute healthcare utilization for diabetes complications between 2003 and 2012.²² They found that mean patient out-of-pocket costs for hemoglobin A_1C, low-density lipoprotein cholesterol, urine microalbumin, and retinopathy screening increased substantially for patients with diabetes after transitioning to an HDHP: from $1.20 to $2.90 for hemoglobin A1C, $1.40 to $3.20 for low-density lipoprotein cholesterol, ($1.30 to $2.80 for urine microalbumin, and $24.80 to $39.50 for a retinal eye exam. Routine care for diabetes also became costlier to the patient, with increased out-of-pocket costs for primary care visits ($15.40 to $23.30) and specialty visits ($23.30 to $41.60) upon transition to an HDHP.²² Overall, total out-of-pocket medical expenditures by patients enrolled in HDHPs were 49.4% higher than by those in non-HDHP plans. These excess costs were most pronounced for HDHP enrollees who had health saving accounts (HSAs) and the highest deductible levels (≥$1200 annually, depending on the year, as set by federal regulations), who faced an average of 67% increase in out-of-pocket medical costs with transition to an HDHP. Wharam et al. did not examine the impact of increased cost-sharing on utilization of these monitoring and routine care services or on diabetes-related health outcomes.

Finally, Rabin and colleagues (2016) examined the impact of HDHPs on primary care appointments, checkups (definition for this term was not specified by Rabin et al.), and specialty visits among patients with diabetes insured by HDHPs and traditional health plans using bivariate and regression analyses in Medical Expenditure Panel Survey between 2011 and 2013. Low-income patients with diabetes, defined as those with annual income below 200% of the federal poverty level, who were enrolled in HDHPs had 42% lower (incidence risk ratio [IRR], 0.58; 95% CI, 0.4-0.83) rates of primary care visits, 65% lower (IRR, 0.35; 95% CI, 0.2-0.61) rates of checkups, and 86% (IRR, 0.14; 95% CI, 0.05-0.45) lower rates of specialty visits compared to patients with traditional health plans.²³ Conversely, higher income (>200% of the federal poverty level) HDHP enrollees were more likely to have a primary care visit (IRR, 1.21; SD, 0.11) than patients with traditional health plans, and no statistical difference was detected for check-ups or specialty visits. Rubin et al. did not examine the impact of reduced routine care on diabetes-related health outcomes.

Medication Management

Two articles focused on various aspects of glucose-lowering medication management in the context of HDHPs. Reiss and colleagues (2011) used Harvard Pilgrim Health Care data between 2001 and 2008 for 108 people with diabetes with HDHPs and 640 people with traditional health plans using an interrupted time series group study design and found that adherence to glucose-lowering medications decreased slightly (slope change = −0.007; P < 0.01) for those in the HDHP group.²⁴ However, this study did not differentiate between adherence to costly brand-name mediations and inexpensive generic medications (some of which are also available through low-cost generic drug programs), despite the fact that no generic alternatives to most brand-name second-line glucose lowering drugs exist and patients with more advanced diabetes may need these brand name drugs for optimal management. The impact of HDHP on glycemic control or any diabetes-related health outcomes was not examined.

In a more recent study, Fendrick and colleagues (2019) analyzed the discontinuation rate for branded and generic drugs among patients with diabetes enrolled in HDHPs as compared to traditional health plans using data from MarketScan between 2013 and 2014 with a retrospective matched cohort study design. Although there was no significant difference in overall medication discontinuation rates between HDHP and non-HDHP enrollees,²⁵ the no refill rate, defined as the failure to fill at least one script of a drug after the index fill of brand name glucose-lowering medications (ie, poor medication adherence), was higher among HDHP enrollees (20.5% vs. 14% for traditional plans; P = 0.009). They also did not examine the impact of HDHP on glycemic control or any diabetes-related health outcomes.

Acute Healthcare Utilization

Four studies examined healthcare utilization patterns in patients with HDHPs as compared to traditional health plans. To assess the impact of HDHPs on the timeliness of clinical evaluations, Wharam and colleagues (2018) examined the potential delay in the treatment of coronary heart disease, cerebrovascular disease, and peripheral artery disease among HDHP enrollees, comparing the number of months it took for HDHP and non-HDHP enrollees to seek care, have their first diagnostic test, and have their first procedure-based treatment for these conditions by retrospective comparison of matched groups within the Optum database between 2003 and 2012.²⁶ They found that, on average, HDHP enrollees experienced a 1.5-month delay in seeking treatment, a 1.9-month delay in having the first diagnostic test, and a 3.1-month delay in having their first procedure-based treatment when compared to non-HDHP enrollees. This study did not assess the impact of delayed evaluation on patient health outcomes.

In a subsequent before-after observational study with matched cohorts between 2003 and 2014, using a large national commercial and Medicare Advantage health insurance claim dataset, in which 156 962 individuals with HDHP and 1 467 758 control population, of whom 29 407 (18.7%) and 274 986 (18.7%) had diabetes, respectively, Wharam and colleagues (2020) examined the impact of switching to HDHPs on incident cardiovascular diabetes complications.¹⁷ They found no significant increase in the adjusted cumulative rates of first major adverse cardiovascular events (composite of myocardial infarction and stroke). However, patients were observed for only four years after switching to HDHPs.

Wharam and colleagues (2018) also examined ED visits, hospitalizations, and total healthcare expenditures among low- and higher-income patients with diabetes included in Optum database between 2003 and 2012 using a controlled interrupted time series study. They found that HDHP enrollees had a 4% overall decline in ED visits and a 5.6% overall decline in hospitalizations compared to matched patients in the non-HDHP group.²⁷ However, HDHP enrollees who lived in low-income neighborhoods saw a disproportionate 8% decrease in low-severity ED visits at the expense of a 10.5% increase in high-severity ED visits. The low-income neighborhood HDHP group also saw a 5.5% relative decrease in proxy low-severity ED visit expenditures, but a 23.5% relative increase in proxy high-severity ED visit expenditures and a 27.4% relative increase in proxy high severity hospitalization days. The authors defined these proxy measures as indicators of disease severity comprising of the cost of ED visits and length of hospital stay after a health event. These findings suggest that HDHP enrollees may be delaying necessary care to the point when the progressive deterioration and acuity of the complications forces them to seek ED care.

In the last study, also using a controlled interrupted time series design with Optum^® data between 2003 and 2012, Wharam and colleagues (2017) found that HDHP enrollees had an 8% relative increase in ED visits for acute complications (which they defined as symptoms or conditions that could be associated with delaying recommended or urgent diabetes-related outpatient or ED care for up to 4 months and that require timely care by medical professionals), with a corresponding 5.6% relative increase in expenditures for these acute complications, compared to the overall population.²² Importantly, the increase in ED use among HDHP enrollees was most pronounced among patients with a high morbidity index (12.1% relative increase in mean acute complications expenditure), who are low-income (9.5% relative increase in mean acute complications visits), and those who have health savings accounts (HSAs; 29.6% relative increases in mean expenditures for acute complications).²²

DISCUSSION

There is limited, but consistent and concerning, evidence of negative impacts of HDHPs on the quality of diabetes care and patient health outcomes. HDHPs were envisioned as a mechanism to improve access to health insurance and healthcare while reducing overall healthcare costs.²⁸ However, while HDHPs may be appropriate and adequate for generally healthy individuals who voluntarily choose limited coverage, current evidence suggests that they can lead to cost-related deferral of necessary care among patients with diabetes. Thus, despite HDHP premiums being much lower than those for traditional health insurance plans such as PPOs and HMOs, making them attractive insurance options for lower income patients and employers, the eventual out-of-pocket costs for the enrollee may make care unaffordable and inaccessible. HDHP enrollees faced nearly 50% higher out-of-pocket medical costs than those with traditional health insurance plans.²² Moreover, if deferred and delayed care results in adverse health outcomes and increase acute healthcare utilization, the total downstream costs of HDHPs to the employer may also be higher than for traditional plans.

Cost-related non-adherence to medications and deferred/delayed evidence-based disease monitoring and management can pose substantiative health threats to patients with diabetes. While a central justification for HDHPs is the incentivizing of enrollees to be more economical and cost-conscious in their healthcare decision making (ie, shopping for less costly alternatives, foregoing low-value care), such behavior would be harmful when extended to high-value care. There is no evidence that patients are able to discern “low value” from “high value” care, particularly as the definition and perception of “high value” may have different meaning to patients than healthcare professionals. Unless low-value services are priced higher and/or high value services incur no out-of-pocket costs, patients are incentivized to limit all costly care, especially for currently asymptomatic conditions, and not just services that are clinically low value. This was demonstrated by Wharam et al., who found that while overall ED visits among HDHP enrollees decreased by 4%, high-severity ED visits increased by more than 10% among patients at highest financial risk.²⁷ In 2019, the Internal Revenue Service has attempted to mitigate some of these issues by allowing HDHPs to exempt certain diabetes services from deductibles and still be eligible for linkage to an HSA.²⁹ It will therefore be important to re-examine the impact of HDHPs on diabetes monitoring, routine care, medication adherence, and acute care utilization in contemporary populations.

All studies that contextualized personal healthcare expenditures in the enrollees’ socioeconomic situation found that lower-income or otherwise financially disadvantaged patients were most likely to delay, limit, or forego care when insured by HDHPs. This likely stems from having little dispensable income available to meet the high out-of-pocket expenditures associated with HDHPs, particularly early in the calendar year (though the temporal variation in delaying or foregoing care has not been examined). Importantly, cost-related barriers to care may affect a much larger proportion of the population than that examined in the identified studies. In 2018, nearly four in 10 U.S. adults reported being unable to cover an unexpected $400 expense, which would not be unusual for a HDHP enrollee facing upwards of $1,400 individual annual deductibles and $6900 out-of-pocket maximums.³⁰ If patients limit, forego, or delay care for an often initially asymptomatic chronic disease (such as diabetes) and its low-severity complications (ie, with low overt symptom burden), these conditions are likely to deteriorate over time and progress to high-severity complications. These may ultimately necessitate extensive and costly treatments and result in greater morbidity, disability, and mortality for the patient as well as high costs of care to employers, payers, and society.

Thus, patients, policymakers, and employers need to be more judicious and restrictive in the categories of individuals and families encouraged to sign up for HDHPs. HDHPs may be beneficial for individuals who are at low risk for catastrophic medical events and have no ongoing or anticipated costly health expenditures. Still, acute and chronic health events can develop in previously healthy individuals. Adverse effects of HDHP enrollment may be mitigated if services and medications required for chronic disease management are covered fully, with no deductible or cost-sharing for the patient, akin to preventive services. This would include, for example, guideline-recommended HbA1c, LDL-C, urine microalbumin, and dilated eye examinations, appointments in primary care, endocrinology, and other commonly needed specialties like nephrology and cardiology; diabetes self-management education/support; and at least some glucose-lowering medications required to manage their condition. Increasing the availability, transparency, and accuracy of publicly available price information and extending the reach of HSAs, akin to what the Internal Revenue Service did in 2019, would also be helpful.

Additionally, healthcare professionals may want to be aware of their patients’ health insurance status and financial capacity, address potential for cost-related barriers to health and healthcare with all patients, and work with patients to alleviate barriers to care and address cost-related concerns. Social workers, community health workers, and health insurance navigators can facilitate these efforts as part of team-based primary and diabetes care. Finally, employers and health insurance companies need to be more transparent about the intricacies of their benefit designs, as previous studies have indicated that many patients are not aware of the details within their health plans.³¹

Gaps in knowledge and future studies

Despite the high prevalence of HDHPs, a lot remains unknown about their impact on diabetes management and health outcomes. HDHPs have become increasingly common over the past decade,⁴ yet most literature on HDHPs and diabetes is more than a decade old and predates the broad availability of HDHPs to broad and diverse populations. Contemporary data on HDHPs in diabetes is particularly needed as the financial burden faced by HDHP enrollees likely increased over the past decade in the setting of rapidly rising costs of diabetes medications, particularly insulin.³² The implications of cost-related barriers to using brand-name medications are also more substantial now than a decade ago, as cardiovascular outcomes trials revealed cardiovascular, heart failure, and kidney disease benefits unique to two classes of brand-name drugs (ie, sodium-glucose transport protein-2 inhibitors and glucagon-like peptide-1 receptor agonists). Beyond medication use, it is unclear how HDHP affect receipt of diabetes self-management education, which is vital for optimal diabetes management and health outcomes. Finally, there is urgent need to examine how HDHPs affect glycemic control, treatment burden, morbidity, and mortality in one of the most common serious chronic health conditions in the U.S.

CONCLUSION

HDHPs were created with the intention of making health insurance more affordable, thereby increasing access to healthcare, and to incentivize cost savings by shifting more of the costs to the consumer. However, how HDHPs affect the quality of care and health outcomes in chronic diseases like diabetes remains poorly defined. Our review of the literature reveals that while HDHPs reduce some healthcare utilization and costs, they do so at the expense of limiting necessary high-value care and medication adherence. HDHP impact on delayed or deferred care is disproportionately felt by lower-income individuals, who also have the highest burden of diabetes and its complications.³³ Policymakers, employers, payers, and healthcare providers should be cognizant of the potential detrimental nature of HDHPs when assessing the best course of action for diverse populations.