Incorporating Cost Pathways In Clinical Guidelines | Diabetes | AMA Journal of Ethics | AMA Ed Hub [Skip to Content]
[Skip to Content Landing]

Should Clinical Guidelines Incorporate Cost Pathways for Persons With Financial Hardship?

Learning Objectives
1. Explain a new or unfamiliar viewpoint on a topic of ethical or professional conduct
2. Evaluate the usefulness of this information for his or her practice, teaching, or conduct
3. Decide whether and when to apply the new information to his or her practice, teaching, or conduct
1 Credit CME

The American Diabetes Association 2020 Standards of Care for the treatment of hyperglycemia in type 2 diabetes includes a treatment pathway when “cost is a major issue.” This pathway recommends use of 2 generic drug classes, thereby codifying differential treatment for those with financial hardship. This article explores 4 implications of incorporating the cost pathway into clinical recommendations: (1) the presence of a cost pathway might create the appearance of an evidence-based quality difference through activation of implicit bias; (2) screening for financial hardship to guide therapy has potential harms for patients; (3) concern that financial hardship warrants differing care might impact overall quality of care and patient-clinician relationships; and (4) applying the guidelines when caring for patients with financial hardship might demoralize clinicians.

Recommendations and Pathways

In December 2018, the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD) published recommendations for the treatment of hyperglycemia in type 2 diabetes for persons failing metformin monotherapy.1 These recommendations are incorporated in the ADA 2020 Standards of Care.2 This essay considers 4 ethical concerns about including patients' financial hardship as part of a treatment pathway (algorithm),1 a component of the algorithm I call a social pathway since it relies on assessing medication affordability. The social pathway is distinct from the 4 clinical pathway components of the algorithm, which depend on assessing clinical parameters for persons with type 2 diabetes. Two of these clinical pathways involve assessment of patients for atherosclerotic cardiovascular disease (ASCVD) or for either chronic kidney disease (CKD) or heart failure (HF). When ASCVD, CKD, or HF are not present, there are 2 additional clinical pathways for a “compelling need to minimize hypoglycemia” or a “compelling need to minimize weight gain or promote weight loss.”1 The social pathway, which is indicated when “cost is a major issue,”1 represents a third choice for those without ASCVD, CKD, or HF. The 2 drug classes in common for avoidance of hypoglycemia and weight-related risks in these groups are patented sodium-glucose cotransporter (SGLT2) inhibitors and patented glucagon-like peptide 1 (GLP-1) analogues. Dipeptidyl peptidase 4 inhibitors and thiazolidinediones are also included as medication options to avoid hypoglycemia. The social pathway recommends generic sulfonylureas and thiazolidinediones.1,3

Evidence and Representation

The 2 clinical pathways for persons with ASCVD or either CKD or HF are supported by a number of placebo-controlled trials for individual SGLT2 and GLP-1 medications.46 By contrast, the literature guiding treatment of persons with type 2 diabetes without ASCVD, CKD, or HF is relatively weak. Most studies comparing drug classes to one another are of short duration, rely on surrogate outcomes, and are industry funded. In a 2016 review of comparative effectiveness studies, only 4% of 177 studies had a duration of greater than 2 years and 12% of 162 studies explicitly reported receiving no industry sponsorship.7 Although outcomes such as weight gain and rates of hypoglycemia are well suited to studies of short duration, for persons without cardiovascular or renal disease, we do not have comparative effectiveness studies with microvascular, macrovascular, or mortality outcomes to guide treatment preferences.7,8 The text of the 2020 ADA Standards of Care recognizes the weakness of the data in stating: “For patients without established ASCVD, indicators of high ASCVD risk, HF, or CKD, the choice of a second agent to add to metformin is not yet guided by empiric evidence.”3 The ADA treatment algorithm graphic, however, does not convey the poor-quality evidence and lack of certainty guiding medication choices for persons without ASCVD, HF, or CKD.

Quiz Ref IDThe ADA/EASD treatment algorithm is not aligned with best practices of guideline presentation.9 There are other guidelines commonly used in primary care that more rigorously evaluate and display the evidence. For example, the American Heart Association and American College of Cardiology 2018 Cholesterol Guideline categorizes each evidence statement based on the class (strength) of the recommendation and level (quality) of evidence.10 Their recommendations include value statements when treatments might be supported by high-quality outcomes evidence but do not meet thresholds for cost effectiveness. Unlike the ADA recommendations, the graphic display of the treatment algorithms includes color codes for the strength of the recommendation or value of each branch point.10

Implicit Bias

How will clinicians read the treatment algorithm graphic? Specifically, for persons without ASCVD, CKD, or HF, will the juxtaposition of the 2 clinical pathways and the social pathway encourage the perception that there is an evidence-based quality difference between the choices for the clinical and social pathways? To understand how the algorithm might be communicating a quality difference between the clinical and social pathways, we must consider the nature of implicit bias and how the ADA/EASD treatment algorithm embeds implicit bias.

Research on implicit bias has described the tendency of people to see social groups through the lens of us and them, accentuating differences and thereby distancing the 2 groups. The negative attributes of “them” and their circumstances affirm the positive attributes of “us” and our station. Implicit bias is activated when a socially held bias is anchored to a second set of preferred-less preferred dichotomous elements, such that the bias and second set of value judgments reinforce one another. Although some individuals may not believe in the bias and the differences between “us” and “them,” the strength of the anchoring of the social bias to a second set of value judgments can influence perception.11

Quiz Ref IDThere are long-standing biases against the poor that are reinforced by narratives that the poor are responsible for their status, are prone to dependence, and deserve less.1113 In the ADA/EASD recommendations, the financially able (deserving) are anchored to the clinical pathways (a form of decision making preferred by clinicians) while the people with financial hardship (less deserving) are anchored to decision making that is less clinically grounded (and therefore less preferred by clinicians). The anchoring reinforces the social hierarchy. The anchoring also differentially frames perceptions of medication options: the patented medication options (SGLT2 inhibitors and GLP-1 analogues) in common for the 2 clinical pathways when ASCVD, CKD, or HF is not present are framed as more preferred, higher quality care, and the generic medication options in the social pathway are framed as less preferred, lower quality care, despite the absence of evidence regarding macrovascular and microvascular outcomes and death for this patient population. We come to perceive and value high-quality care for “us” in part by defining and segregating a socially less deserving “other.” The social pathway of the ADA/EASD recommendations functions like a fun house mirror. On one side, it makes the medication options of the clinical pathways look larger and better, because on the other side are poorer people with diminutive care options. The “mirror” can prevent us from seeing gaps and biases in the literature, deviations of the ADA/EASD from best practices in writing guidelines, overreliance on expert opinion, absence of population assessment of costs and benefits of new therapeutics, and our collective failure to provide universal access to care.

More About Ethics and Justice

Here, I discuss 3 additional implications for patient care of incorporating the ADA/EASD social pathway in clinical recommendations.

Potential harms of screening for financial hardship.The social pathway is aligned with efforts to promote cost-of-care discussions. Yet research on cost-of-care discussions is at best formative with respect to screening methods, clinician resistance, interventions, and outcomes.1418 Screening for social determinants of health has shown promise,1922 but potential harms have been acknowledged.23 Some patients might find the screening questions intrusive, disrespectful, stigmatizing, or undermining of trust. However, the purpose of screening for social determinants is to mitigate their impact through structural change,21 a different intent than the ADA/EASD social pathway. Screening for financial hardship to guide diabetes therapy is untested, and absent an evidence base, it raises ethical questions: Should clinicians inform patients that they are asking about ability to afford medications in order to prescribe presumably “lesser” therapy? Will patients feel devalued by being relegated to the social pathway?24 What should clinicians do when they learn that patients' financial hardship goes beyond paying for diabetes medications?

Patient-clinician relationship. Quiz Ref IDOther quality of care factors can be affected by reinforcing tiers of care. Patient-clinician communication and trust may be impaired, eroding the foundations of just relationships. In a seminal study, Lisa Cooper and colleagues demonstrated that measures of clinicians' implicit race bias were associated with potentially harmful communication patterns between clinicians and patients and with poor care ratings among African-American patients.25Quiz Ref IDIn addition, clinicians might make assumptions about who should receive less expensive, lower-quality care based on their “poor” appearance, diction, or behavior. In making such assumptions, they might inadvertently contribute to the burden of discrimination and resultant risk of adverse health effects among those with financial hardship.26

Clinician demoralization. Finally, clinicians are torn between their professional ethics to provide quality care to all patients and real-world financial constraints on practice. A colleague in a safety net practice, reflecting on the type 2 diabetes treatment algorithm, said to me, “The longer I work here, the further I fall behind the rest of primary care practice.” Every prescription for a “bad” generic sulfonylurea (perceived by clinicians as of lesser quality based on their interpretation of the ADA/EASD treatment algorithm) and institutional formulary restrictions for expensive patented medication become demoralizing. Clinicians react negatively to their home institutions as opposed to the expert panel that recommended the generic therapies for people with financial hardship or the health system that structures care as a privilege. Clinicians know their home institutions are imperfect, so it is easy to ascribe blame to them. Given their need for guidance in navigating the complex terrain of medical care, clinicians regard experts as having principled authority. They have difficulty discerning that experts' enthusiasm for progress and the appeal of innovation may perpetuate bias in medical practice. They may not perceive the marginalization and stigmatization of persons with financial hardship and how practice patterns might be promoted, in part, on the backs of the poor.

A Bigger Picture

Quiz Ref IDAlthough I am critical of the function of a cost-of-care pathway in the ADA/EASD recommendation statement, financial hardship is a staggering issue. Prior to the coronavirus pandemic, nearly 41 million Americans lived below the federal poverty line, and nearly 140 million Americans (43%) were either poor or low income under the Supplemental Poverty Measure.27 Nearly 40% of Americans could not afford a $400 emergency,28 and 27.5 million Americans did not have health insurance.29 Among the insured, 43% reported that they “struggled” to meet their deductible, and 40% assumed debt from medical bills.27 Low income is part of the web of social determinants of health that also affects diabetes risk.3033 Survey data indicate that nearly 1 in 4 adults and seniors reported difficulty affording medications.34 Low income, poor health status, and being prescribed 4 or more medications were risk factors for difficulty affording medications34; each factor is associated with type 2 diabetes. Difficulty affording medications leads patients to make unpalatable decisions, such as taking medications less frequently than prescribed, buying less nutritious food to afford medication, or choosing between the needs of family members or their own needs.35

Furthermore, people with low income are subject to structural forces that suppress wages, create dangerous work environments, undermine social services, limit affordable and stable housing, create food deserts, contribute to disproportionate rates of incarceration or control by judicial systems, threaten the social fabric of early childhood, make health care less accessible, expose people to pollutants, undercut the quality of primary and secondary education, and limit access to higher education, thereby maintaining a skewed playing field.9 As described above, the poor are blamed for their poverty.1113 Poverty is often racialized or gendered, strengthening the biases that harm persons of color, women, and the poor.12,3639

The ethical concerns described here are predicated on understanding poverty or financial hardship as an individual characteristic warranting individual intervention. Alternatively, poverty can be understood as being rooted in the socioeconomic system—as being a feature of the economy and the degree of social cohesion.40 That the ADA/EASD recommendations created a pathway for individual patients for whom “cost is a major issue”1 is one more indicator of a broken system in need of repair.41,42 Instead of devoting a pathway in a treatment algorithm to the poor, we should bring urgency to eliminating cost as a barrier to high-value, cost-effective care.

It could be different. Imagine more of our health professional societies demanding universal access to care and single-payer health insurance.43,44 Imagine expert panels applying best practices to writing clinical guidelines in the context of universal access to care, without conflicts of interest with the pharmaceutical industry, and sensitive to patient-centered and population health perspectives. Imagine our medical societies becoming advocates and allies for the elimination of poverty. Engaging issues of poverty and rooting out manifestations of bias within and outside our medical societies, while no doubt challenging, will make our medical societies more relevant and stronger.

Sign in to take quiz and track your certificates

The AMA Journal of Ethics exists to help medical students, physicians and all health care professionals navigate ethical decisions in service to patients and society. The journal publishes cases and expert commentary, medical education articles, policy discussions, peer-reviewed articles for journal-based, video CME, audio CME, visuals, and more. Learn more

Successful completion of this CME activity, which includes participation in the evaluation component, enables the participant to earn up to:

1 Medical Knowledge MOC points in the American Board of Internal Medicine's (ABIM) Maintenance of Certification (MOC) program;

1 Self-Assessment points in the American Board of Otolaryngology – Head and Neck Surgery’s (ABOHNS) Continuing Certification program;

1 MOC points in the American Board of Pediatrics’ (ABP) Maintenance of Certification (MOC) program; and

1 Lifelong Learning points in the American Board of Pathology’s (ABPath) Continuing Certification program;

It is the CME activity provider's responsibility to submit participant completion information to ACCME for the purpose of granting MOC credit.

Article Information

AMA Journal of Ethics

AMA J Ethics. 2021;23(2):E175-182.

AMA CME Accreditation Information

Credit Designation Statement: The American Medical Association designates this journal-based CME activity for a maximum of 1.0 AMA PRA Category 1 Credit™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

CME Disclosure Statement: Unless noted, all individuals in control of content reported no relevant financial relationships.

Acknowledgements: The author would like to acknowledge the thoughtful feedback of Alice O'Connor, PhD, University of California at Santa Barbara.

Conflict of Interest Disclosure: The author(s) had no conflicts of interest to disclose.

The viewpoints expressed in this article are those of the author(s) and do not necessarily reflect the views and policies of the AMA.

Author Information:

  • David Goldberg, MD is a primary care general internist. Over the course of his career in 2 public hospital systems—in Chicago, Illinois and Chinle, Arizona—he has held positions in primary care leadership, clinical preventive medicine, and diabetes and chronic disease care.

Davies  MJ, D'Alessio  DA, Fradkin  J,  et al Management of hyperglycemia in type 2 diabetes, 2018. A consensus report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD).  Diabetes Care. 2018;41(12):2669–2701.Google ScholarCrossref
American Diabetes Association.  Introduction: Standards of Medical Care in Diabetes—2020 Diabetes Care. 2020;43(suppl 1):S1–S2.Google Scholar
American Diabetes Association.  9. Pharmacologic approaches to glycemic treatment :  Standards of Medical Care in Diabetes—2020. Diabetes Care. 2020;43(suppl 1):S98–S110.Google Scholar
Cefalu  WT, Gerstein  HC, Holman  RR,  et al Cardiovascular outcomes trials in type 2 diabetes: where do we go from here? Reflections from a Diabetes Care Editors' Expert Forum.  Diabetes Care. 2018;41(1):14–31.Google ScholarCrossref
Nagahisa  T, Saisho  Y.  Cardiorenal protection: potential of SGLT2 inhibitors and GLP-1 receptor agonists in the treatment of type 2 diabetes.  Diabetes Ther. 2019;10(5):1733–1752.Google ScholarCrossref
McMurray  JJV, Solomon  SD, Inzucchi  SE.  Dapagliflozin in patients with heart failure and reduced ejection fraction.  N Engl J Med. 2019;381(21):1995–2008.Google ScholarCrossref
Bolen  S, Tseng  E, Hutfless  S,  et al Diabetes Medications for Adults With Type 2 Diabetes: An Update. Comparative Effectiveness Review No. 173. Agency for Healthcare Research and Quality; 2016. AHRQ Publication 16-EHC013-EF. Accessed December 9, 2020.
Qaseem  A, Barry  MJ, Humphrey  LL, Forciea  MA; Clinical Guidelines Committee of the American College of Physicians.  Oral pharmacologic treatment of type 2 diabetes mellitus: a clinical practice guideline update from the American College of Physicians.  Ann Intern Med. 2017;166(4):279–290.Google ScholarCrossref
Graham  R, Mancher  M, Miller Wolman  D, Greenfield  S, Steinberg  E, eds; Institute of Medicine.  Clinical Practice Guidelines We Can Trust. National Academies Press; 2011.
Grundy  SM, Stone  NJ, Bailey  AL,  et al 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA guideline on the management of blood cholesterol: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines.  Circulation. 2019;139(25):e1082–e1143.Google Scholar
Banaji  MR, Greenwald  AG.  Blindspot: Hidden Biases of Good People. Delacorte Press; 2013.
Abramsky  S.  The American Way of Poverty: How the Other Half Still Lives. Nation Books; 2013.
Gaffney  A.  To Heal Humankind: The Right to Health in History. Routledge; 2019.
Dine  CJ, Msai  D, Smith  CD.  Tools to help overcome barriers to cost-of-care conversations.  Ann Intern Med. 2019;170(9)(suppl):S36–S38.Google ScholarCrossref
Carroll  JK, Farah  S, Fortuna  RJ,  et al Addressing medication cost during primary care visits: a before-after study of team-based training.  Ann Intern Med. 2019;170(9)(suppl):S46–S53.Google ScholarCrossref
Henrikson  NB, Banegas  MP, Tuzzio  L,  et al Workflow requirements for cost-of-care conversations in outpatient settings providing oncology or primary care: a qualitative, human-centered design study.  Ann Intern Med. 2019;170(9)(suppl):S70–S78.Google ScholarCrossref
Bradham  DD, Garcia  D, Galvan  A, Erb  C.  Cost-of-care conversations during clinical visits in federally qualified health centers: an observational study.  Ann Intern Med. 2019;170(9)(suppl):S87–S92.Google ScholarCrossref
Chino  F, Peppercorn  JM, Rushing  C,  et al Going for broke: a longitudinal study of patient-reported financial sacrifice in cancer care.  J Oncol Pract. 2018;14(9):e533–e546.Google ScholarCrossref
Davidson  KW, McGinn  T.  Screening for social determinants of health: the known and the unknown.  JAMA. 2019;322(11):1037–1038.Google ScholarCrossref
De Marchis  EH, Hessler  D, Fichtenberg  C,  et al Part I: a quantitative study of social risk screening acceptability in patients and caregivers.  Am J Prev Med. 2019;57(6)(suppl 1):S25–S37.Google ScholarCrossref
Byhoff  E, De Marchis  EH, Hessler  D,  et al Part II: a qualitative study of social risk screening acceptability in patients and caregivers.  Am J Prev Med. 2019;57(6)(suppl 1):S38–S46.Google ScholarCrossref
Krist  AH, Davidson  KW, Ngo-Metzger  Q, Mills  J.  Social determinants as a preventive service: US Preventive Services Task Force methods considerations for research.  Am J Prev Med. 2019;57(6)(suppl 1):S6–S12.Google ScholarCrossref
Garg  A, Boynton-Jarrett  R, Dworkin  PH.  Avoiding the unintended consequences of screening for social determinants of health.  JAMA. 2016;316(8):813–814.Google ScholarCrossref
Ewing  E.  Ghosts in the Schoolyard: Racism and School Closings on Chicago's South Side. University of Chicago Press; 2018.
Cooper  LA, Roter  DL, Carson  KA,  et al The associations of clinicians' implicit attitudes about race with medical visit communication and patient ratings of interpersonal care.  Am J Public Health. 2012;102(5):979–987.Google ScholarCrossref
Williams  DR, Lawrence  JA, Davis  BA, Vu  C.  Understanding how discrimination can affect health.  Health Serv Res. 2019;54(suppl 2):1374–1388.Google ScholarCrossref
Anderson  S, Bayard  M, Bennis  P,  et al The Souls of Poor Folk: Auditing America 50 Years After the Poor People's Campaign Challenged Racism, Poverty, the War Economy/Militarism and Our National Morality. Institute for Policy Studies; April 2018. Accessed May 26, 2020.
Board of Governors of the Federal Reserve System.  Report on the economic well-being of US households in 2018.  Updated May 28, 2019. Accessed May 26, 2020.
Berchick  ER, Barnett  JC, Upton  RD.  Health insurance coverage in the United States: 2018.  US Census Bureau; November 2019. Current Population Reports P60-267(RV). Accessed December 9, 2020.
Ross  NA, Gilmour  H, Dasgupta  K.  14-year diabetes incidence: the role of socio-economic status.  Health Rep. 2010;21(3):19–28.Google Scholar
Gaskin  DJ, Thorpe  RJ  Jr, McGinty  EE,  et al Disparities in diabetes: the nexus of race, poverty, and place.  Am J Public Health. 2014;104(11):2147–2155.Google ScholarCrossref
Thornton  PL, Kumanyika  SK, Gregg  EW,  et al New research directions on disparities in obesity and type 2 diabetes.  Ann N Y Acad Sci. 2019;1461(1):5–24.Google ScholarCrossref
Kirzinger  A, Lopes  L, Wu  G. Brodie  M.  KFF health tracking poll—February 2019: prescription drugs.  Kaiser Family Foundation. March 1 , 2019. Accessed May 26, 2020.
Norris  P, Tordoff  J, McIntosh  B, Laxman  K, Chang  SY, Te Karu  L.  Impact of prescription charges on people living in poverty: a qualitative study.  Res Social Adm Pharm. 2016;12(6):893–902.Google ScholarCrossref
Bleich  SN, Findling  MG, Casey  LS,  et al Discrimination in the United States: experiences of black Americans.  Health Serv Res. 2019;54(suppl 2):1399–1408.Google ScholarCrossref
Findling  MG, Bleich  SN, Casey  LS,  et al Discrimination in the United States: experiences of Latinos.  Health Serv Res. 2019;54(suppl 2):1409–1418.Google ScholarCrossref
Findling  MG, Casey  LS, Fryberg  SA,  et al Discrimination in the United States: experiences of Native Americans.  Health Serv Res. 2019;54(suppl 2):1431–1441.Google ScholarCrossref
SteelFisher  GK, Findling  MG, Bleich  SN,  et al Gender discrimination in the United States: experiences of women.  Health Serv Res. 2019;54(suppl 2):1442–1453.Google ScholarCrossref
O'Connor  A.  Poverty Knowledge: Social Science, Social Policy, and the Poor in Twentieth-Century US History. Princeton University Press; 2001.
Woolf  SH, Aron  L, eds; National Research Council; Institute of Medicine.  US Health in International Perspective: Shorter Lives, Poorer Health. Panel on Understanding Cross-National Health Differences Among High-Income Countries. National Academies Press; 2013.
Woolf  SH, Schoomaker  H.  Life expectancy and mortality rates in the United States, 1959-2017.  JAMA. 2019;322(20):1996–2016.Google ScholarCrossref
Woolhandler  S, Himmelstein  DU.  Single-payer reform: the only way to fulfill the president's pledge of more coverage, better benefits, and lower costs.  Ann Intern Med. 2017;166(8):587–588.Google ScholarCrossref
Gaffney  A, Lexchin  J; US/Canadian Pharmaceutical Policy Reform Working Group.  Healing an ailing pharmaceutical system: prescription for reform for United States and Canada.  BMJ. 2018;361:k1039.Google ScholarCrossref
Doherty  R, Cooney  TG, Mire  RD, Engel  LS, Goldman  JM; Health and Public Policy Committee and Medical Practice and Quality Committee of the American College of Physicians.  Envisioning a better US health system for all: a call to action by the American College of Physicians.  Ann Intern Med. 2020;172(2)(suppl):S3–S6.Google ScholarCrossref

Name Your Search

Save Search

Lookup An Activity



My Saved Searches

You currently have no searches saved.