by Marieke van Eijk, University of Washington
In her TED talk, Chimamanda Ngozi Adichie warns of the Dangers of a Single Story (https://www.ted.com/talks/chimamanda_adichie_the_danger_of_a_single_story/transcript). She talks about her childhood growing up in Nigeria and of Fide, her family’s house boy. Her mother had told her that Fide’s family was poor. When Adichie visited Fide’s village she admired the baskets that Fide’s brother had made. “All I had heard about [Fide’s family],” Adichie says, “was how poor they were, so that it had become impossible for me to see them as anything else but poor. Their poverty was my single story of them.” Adichie’s example demonstrates the dangers of Single Stories: they create stereotypes; make the singular stand in for the multiple; and maintain unequal power relations. Single stories hide other stories that can be told.
Adichie’s warning of single stores also relates to “boring” ICD codes. ICD codes are part of the International Statistical Classification of Diseases and Related Health Problems (ICD). The ICD is not a diagnostic or etiological tool; it is to aid the systematic collection, recording, interpretation, and comparison of death and disease rates across the globe (Bowker and Star 1999:72). In the United States, financial staff use ICD codes to prepare medical bills and insurance claims to patients, insurance companies, and third-party payers. These codes are what I call “boring,” namely they are embedded in the larger health care infrastructure where they fade into the background and often go unnoticed (Lampland and Star 2009). Analysis of such infrastructure often reveals the presence of what Lampland and Star (2009:22) call a master narrative, that is “a single voice that does not problematize diversity.” The financial story that ICD codes are to capture obscures other financial stories that matter to patients, doctors, and hospitals.
As Bowker and Starr show in their book Sorting Things Out, the first nomenclatures, developed in the early 1900s, held a maximum of 200 classifications for the recording of cause of death. With each revision, more diseases and symptoms were described in detailed ways. The accumulation of ever more entries created problems of comparability: to compare items in the ICD from one revision to the next and to conduct large-scale research and collect statistics, changes ideally had to be conservative with regards to the preservation or elimination of categories. The story of progress thus required conservatism. The development of the nomenclature is also part of nation states’ efforts to legitimately govern more individuals by collecting ever more data on their lives, bodies, diseases, and deaths (Bowker and Star 1999). In the ICD, stories about pragmatism and conservatism emerge from behind master narratives of scientific progress and nation-state building.
Codes in the current edition, the ICD-10, are grouped into separate blocks that describe diseases, conditions and symptoms, causes of injury, and social conditions that impact health beyond disease and injury. Most codes consist of a letter, four numbers, and are followed by a description. Code C79.51 is part of a long list of “Malignant neoplasms” (C) and indicates the presence of “Secondary malignant neoplasm of bone and bone marrow.” Cancerous cells have emerged in a bone. Other codes describe “Diseases of the circulatory system,” such as “I30.1 Infective pericarditis,” or “problems related to education and literacy” (Z-codes). While diseases and conditions present differently in different people and may change over the course of their lifetime, ICD codes present them as single, spatial, and stable entries (Bowker and Star 1999).
In the United States, medical coders use these codes to capture a person’s diagnoses and medical procedures in terms that billing departments and insurance providers understand. I interviewed medical coders in the state of Washington as part of an ongoing research project about hidden and precarious labor conditions brought about by, or intensified under, U.S. health care reform. Medical coders are part of a large group of “in/visible” non-medical workers in health care who perform critical tasks behind the scenes. Workers in this group help people enroll in health insurance policies, retrieve patient information, or prepare and process medical bills. Medical coders convert medical information into coding language. After a patient has visited a health care provider or has been hospitalized, a medical coder goes into the patient’s health record. Based on the provider’s description of the clinical encounter, the medical coder identifies and attaches one or more ICD codes to the patient’s diagnoses, conditions, and procedures performed. Coders’ work is repetitive but demanding. They must have a broad and detailed understanding of human physiology and medical procedures and collaborate with physicians who often see coding work as a burden to their doctoring. Coders need to know the details of a plethora of reimbursement and coding rules that change frequently. Like other non-medical workers, coders perform these tasks under pressures of demanding productivity targets, in powerfully hierarchical workplace dynamics (Getrich et al. 2017), and in a multi-payer health care system.
In interviews and coding literature, coding professionals often describe their work as providing a coding story that “accurately reflects” what happened in clinical encounters. To code “accurately,” medical coders need to know how many minutes physicians spent on face-to-face counseling with patients, if their clinical decision-making was “moderately difficulty” or “easy,” and how many milliliters of IV fluids a cancer patient received during chemotherapy. Coding “accurately” is complicated as codes are frequently revised, are open to multiple interpretations, and are accompanied by novel payment models and rules introduced after the implementation of the Affordable Care Act. Coding “inaccurately” or attributing a too high or too low a level of reimbursement can lead to denied claims, missed reimbursement, patients receiving unexpected medical bills, and million-dollar penalties levied against the hospital or provider for “improper” usages of codes under the Federal False Claims Act (FCA). An “accurate” coding narrative is to represent a medical-financial narrative that matches specific payment guidelines, satisfies external third-party auditors, and secures a hospital’s or clinic’s revenue.
Adichie’s warning of the dangers of a single story has an analogy with medical coding. In Adichie’s story, Fide was reduced to being merely poor, which became the definitive story of him. It said nothing, for instance, about his brother’s craftsmanship. The reduction of dynamic patient-doctor encounters into static billable codes matches payment guidelines and coding rules. Yet this single financial story has consequences for patients, providers, and clinics in their struggles to secure payments for health services in the U.S. multi-payer, for-profit health care system. “Accurate” coding impacts patients’ medical bills and can mean the difference between paying for food, housing, and health services or having to file for medical bankruptcy because of thousands of dollars of medical debt; it shapes which patients private practitioners are able or willing to serve; and it impacts hospitals’ continuing ability to provide health services in a highly competitive health care system with constantly changing payment models and financial incentives. Focusing on a “boring” object such as an ICD code can reveal an infrastructure’s master narrative and the material, financial, and individual consequences that the materialization of that story can have in peoples’ and health care institutions’ capacities to provide, access, and pay for health services.
Geoffrey C. Bowker and Susan Leigh Star. 1999. Sorting Things Out: Classification and its Consequences. Cambridge: The MIT Press.
Chimamanda Ngozi Adichie. 2009. Dangers of a Single Story. https://www.ted.com/talks/chimamanda_adichie_the_danger_of_a_single_story/transcript
International Statistical Classification of Diseases and Related Health Problems 10. Version 2016.http://apps.who.int/classifications/icd10/browse/2016/en
Christina Getrich, Jacqueline M. García, Angélica Solares, and Miria Kano. 2017. Buffering the Uneven Impact of the Affordable Care Act: Immigrant-serving Safety-net Providers in New Mexico. Medical Anthropology Quarterly, vol. 00, issue o. pp. 1-
Martha Lampland and Susan Leigh Star. 2009. Standards and Their Stories: How Quantifying, Classifying, and Formalizing Practices Shape Everyday Life. Ithaca: Cornell University Press.