Awareness in Practice: Tensions in Access to Sensitive Attribute Data for Antidiscrimination

Organizations cannot address demographic disparities that they cannot see. Recent research on machine learning and fairness has emphasized that awareness of sensitive attributes, such as race and sex, is critical to the development of interventions. However, on the ground, the existence of these data cannot be taken for granted. This paper uses the domains of employment, credit, and healthcare in the United States to surface conditions that have shaped the availability of sensitive attribute data. For each domain, we describe how and when private companies collect or infer sensitive attribute data for antidiscrimination purposes. An inconsistent story emerges: Some companies are required by law to collect sensitive attribute data, while others are prohibited from doing so. Still others, in the absence of legal mandates, have determined that collection and imputation of these data are appropriate to address disparities. This story has important implications for fairness research and its future applications. If companies that mediate access to life opportunities are unable or hesitant to collect or infer sensitive attribute data, then proposed techniques to detect and mitigate bias in machine learning models might never be implemented outside the lab. We conclude that today's legal requirements and corporate practices, while highly inconsistent across domains, offer lessons for how to approach the collection and inference of sensitive data in appropriate circumstances. We urge stakeholders, including machine learning practitioners, to actively help chart a path forward that takes both policy goals and technical needs into account

Responses of Massachusetts hospitals to a state mandate to collect race, ethnicity and language data from patients: a qualitative study

<p>Abstract</p> <p>Background</p> <p>A Massachusetts regulation implemented in 2007 has required all acute care hospitals to report patients' race, ethnicity and preferred language using standardized methodology based on self-reported information from patients. This study assessed implementation of the regulation and its impact on the use of race and ethnicity data in performance monitoring and quality improvement within hospitals.</p> <p>Methods</p> <p>Thematic analysis of semi-structured interviews with executives from a representative sample of 28 Massachusetts hospitals in 2009.</p> <p>Results</p> <p>The number of hospitals using race, ethnicity and language data internally beyond refining interpreter services increased substantially from 11 to 21 after the regulation. Thirteen of these hospitals were utilizing patient race and ethnicity data to identify disparities in quality performance measures for a variety of clinical processes and outcomes, while 16 had developed patient services and community outreach programs based on findings from these data. Commonly reported barriers to data utilization include small numbers within categories, insufficient resources, information system requirements, and lack of direction from the state.</p> <p>Conclusions</p> <p>The responses of Massachusetts hospitals to this new state regulation indicate that requiring the collection of race, ethnicity and language data can be an effective method to promote performance monitoring and quality improvement, thereby setting the stage for federal standards and incentive programs to eliminate racial and ethnic disparities in the quality of health care.</p

Pediatric appendicitis rupture rate: a national indicator of disparities in healthcare access

BACKGROUND: The U.S. National Healthcare Disparities Report is a recent effort to measure and monitor racial and ethnic disparities in health and healthcare. The Report is a work in progress and includes few indicators specific to children. An indicator worthy of consideration is racial/ethnic differences in the rate of bad outcomes for pediatric acute appendicitis. Bad outcomes for this condition are indicative of poor access to healthcare, which is amenable to social and healthcare policy changes. METHODS: We analyzed the KID Inpatient Database, a nationally representative sample of pediatric hospitalization, to compare rates of appendicitis rupture between white, African American, Hispanic and Asian children. We ran weighted logistic regression models to obtain national estimates of relative odds of rupture rate for the four groups, adjusted for developmental, biological, socioeconomic, health services and hospital factors that might influence disease outcome. RESULTS: Rupture was a much more burdensome outcome than timely surgery and rupture avoidance. Rupture cases had 97% higher hospital charges and 175% longer hospital stays than non-rupture cases on average. These burdens disproportionately affected minority children, who had 24% – 38% higher odds of appendicitis rupture than white children, adjusting for age and gender. These differences were reduced, but remained significant after adjusting for other factors. CONCLUSION: The racial/ethnic disparities in pediatric appendicitis outcome are large and are preventable with timely diagnosis and surgery for all children. Furthermore, estimating this disparity using the KID survey is a relatively straightforward process. Therefore pediatric appendicitis rupture rate is a good candidate for inclusion in the National Healthcare Disparities Report. As with most other health and healthcare disparities, efforts to reduce disparities in income, wealth and access to care will most likely improve the odds of favorable outcome for this condition as well

Quasi-experimental trial of diabetes Self-Management Automated and Real-Time Telephonic Support (SMARTSteps) in a Medicaid managed care plan: study protocol

<p>Abstract</p> <p>Background</p> <p>Health information technology can enhance self-management and quality of life for patients with chronic disease and overcome healthcare barriers for patients with limited English proficiency. After a randomized controlled trial of a multilingual automated telephone self-management support program (ATSM) improved patient-centered dimensions of diabetes care in safety net clinics, we collaborated with a nonprofit Medicaid managed care plan to translate research into practice, offering ATSM as a covered benefit and augmenting ATSM to promote medication activation. This paper describes the protocol of the Self-Management Automated and Real-Time Telephonic Support Project (SMARTSteps).</p> <p>Methods/Design</p> <p>This controlled quasi-experimental trial used a wait-list variant of a stepped wedge design to enroll 362 adult health plan members with diabetes who speak English, Cantonese, or Spanish and receive care at 4 publicly-funded clinics. Through language-stratified randomization, participants were assigned to four intervention statuses: SMARTSteps-ONLY, SMARTSteps-PLUS, or wait-list for either intervention. In addition to usual primary care, intervention participants received 27 weekly calls in their preferred language with rotating queries and response-triggered education about self-care, medication adherence, safety concerns, psychological issues, and preventive services. Health coaches from the health plan called patients with out-of-range responses for collaborative goal setting and action planning. SMARTSteps-PLUS also included health coach calls to promote medication activation, adherence and intensification, if triggered by ATSM-reported non-adherence, refill non-adherence from pharmacy claims, or suboptimal cardiometabolic indicators. Wait-list patients crossed-over to SMARTSteps-ONLY or -PLUS at 6 months. For participants who agreed to structured telephone interviews at baseline and 6 months (n = 252), primary outcomes will be changes in quality of life and functional status with secondary outcomes of 6-month changes in self-management behaviors/efficacy and patient-centered processes of care. We will also evaluate 6-month changes in cardiometabolic (HbA1c, blood pressure, and LDL) and utilization indicators for all participants.</p> <p>Discussion</p> <p>Outcomes will provide evidence regarding real-world implementation of ATSM within a Medicaid managed care plan serving safety net settings. The evaluation trial will provide insight into translating and scaling up health information technology interventions for linguistically and culturally diverse vulnerable populations with chronic disease.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov: <a href="http://www.clinicaltrials.gov/ct2/show/NCT00683020">NCT00683020</a></p

The U.S. Preventive Services Task Force: An evidence-based prevention resource for nurse practitioners

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74060/1/j.1745-7599.2009.00410.x.pd