Matt Dinerstein v. Google, LLC

73 F.4th 502
CourtCourt of Appeals for the Seventh Circuit
DecidedJuly 11, 2023
Docket20-3134
StatusPublished
Cited by41 cases

This text of 73 F.4th 502 (Matt Dinerstein v. Google, LLC) is published on Counsel Stack Legal Research, covering Court of Appeals for the Seventh Circuit primary law. Counsel Stack provides free access to over 12 million legal documents including statutes, case law, regulations, and constitutions.

Bluebook
Matt Dinerstein v. Google, LLC, 73 F.4th 502 (7th Cir. 2023).

Opinion

In the

United States Court of Appeals for the Seventh Circuit ____________________ No. 20-3134 MATT DINERSTEIN, individually and on behalf of all others similarly situated, Plaintiff-Appellant,

v.

GOOGLE, LLC; UNIVERSITY OF CHICAGO; and UNIVERSITY OF CHICAGO MEDICAL CENTER;

Defendants-Appellees. ____________________

Appeal from the United States District Court for the Northern District of Illinois, Eastern Division. No. 19 C 4311 — Rebecca R. Pallmeyer, Chief Judge. ____________________

ARGUED SEPTEMBER 17, 2021 — DECIDED JULY 11, 2023 ____________________

Before SYKES, Chief Judge, and FLAUM and KIRSCH, Circuit Judges. SYKES, Chief Judge. This class-action lawsuit arises from a research collaboration between Google and the University of Chicago together with its affiliated Medical Center. (We will refer to the latter two as “the University” unless the context 2 No. 20-3134

requires otherwise.) Harnessing the power of artificial intelligence, the research partners aspired to develop soft- ware capable of anticipating patients’ future healthcare needs. If successful, the software promised to reduce medi- cal complications, eliminate unnecessary hospital stays, and, ultimately, improve patients’ healthcare outcomes. As an initial step in the research effort, the University de- livered several years of anonymized patient medical records to Google, thus supplying it with the information needed to “train” the software’s algorithms. A Data Use Agreement governed the transfer. Restricting Google’s use of the rec- ords to a list of specific research-related activities, the agreement expressly prohibited the company from attempt- ing to identify any patient whose records were disclosed. The anonymized electronic records subject to the agree- ment included those of Matt Dinerstein, twice an inpatient at the hospital during the period covered by the records disclo- sure. Dinerstein sued Google and the University on behalf of himself and a class of other patients whose anonymized records were disclosed. He alleged several theories of liabil- ity. He first claimed that the University had breached either an express or an implied contract traceable to a privacy notice he received and an authorization he signed upon each admission to the Medical Center. Alternatively, he asserted a claim for unjust enrichment. Citing the same notice and authorization, he also alleged that the University had re- neged on its promise of patient confidentiality and therefore violated the Illinois Consumer Fraud and Deceptive Busi- ness Practices Act, 815 ILL. COMP. STAT. 505/1 et seq. Against Google, he asserted claims for unjust enrichment and tor- tious interference with his contract with the University. No. 20-3134 3

Finally, he brought a privacy claim against all defendants based on allegations of intrusion upon seclusion. The district judge dismissed the consumer-fraud claim for lack of standing and the rest of the suit for failure to state a claim. We agree with her decision to dismiss the case, but our analysis begins and ends with standing. Dinerstein has not adequately alleged standing to pursue any of his claims. To sue in federal court, a plaintiff must plausibly allege (and later prove) that he has suffered an injury in fact that is concrete and particularized, actual or imminent, and tracea- ble to the defendant’s conduct. The injuries Dinerstein alleges lack plausibility, concreteness, or imminence (or some combination of the three). Because the complaint fails to plausibly allege an injury in fact, we affirm but modify the judgment to reflect a jurisdictional dismissal for lack of standing. I. Background Our factual account is drawn from Dinerstein’s amended complaint. We begin with a description of his inpatient stays at the University Medical Center—and more particularly, the paperwork he received at the start of each admission. Dinerstein alleges that he was first admitted to the Medical Center on June 4, 2015, and was discharged three days later. He was then readmitted on June 25, this time for a two-night stay. Upon each admission Dinerstein received a Notice of Privacy Practices detailing the University’s confidentiality obligations and the circumstances in which it might use or disclose patient medical information. Relevant here, the notice stated that the University would obtain “written permission” for the sale of such information. Patient permis- sion was not required, however, for the University to use or 4 No. 20-3134

share the information in limited research-related circum- stances. In addition to the notice, Dinerstein received and signed an Admission and Outpatient Agreement and Au- thorization. By doing so he affirmed that he understood that his medical information might be shared for approved research purposes and that if so, he would “not be entitled to any compensation.” He further acknowledged that “all efforts” would “be made to protect [his] privacy” and that “any use of [his] medical information” would comply with both the notice and “federal and state laws.” During Dinerstein’s two hospital stays, the University compiled records of his vital readings, medical procedures, prescriptions, test results, and diagnoses. The records also contained demographic information. After each discharge from the hospital, the Medical Center maintained electronic copies of his patient records. Approximately two years after Dinerstein’s hospital vis- its, Google announced that it had partnered with the Univer- sity to research new healthcare technology. With the help of machine learning, the research partners aspired to develop predictive modeling software that would improve the ability of medical providers to forecast their patients’ medical needs and, in turn, to tailor subsequent medical care. As described in promotional statements, the project had the potential to prevent medical complications, reduce hospital visits, and improve overall health and well-being. 1

1 Matt Wood, UChicago Medicine Collaborates with Google to Use Machine Learning for Better Health Care, UCHICAGO MEDICINE (May 17, 2017), https://www.uchicagomedicine.org/forefront/research-and-discoveries- articles/uchicago-medicine-collaborates-with-google-to-use-machine- learning-for-better-health-care. No. 20-3134 5

To reliably predict medical outcomes, the models needed extensive information from which to learn. The University thus agreed to transfer to Google a large set of anonymized patient medical records. A Data Use Agreement executed by the partners in December 2016 governed the transfer. While most of the agreement’s provisions are irrelevant for our purposes, a few deserve mention. First, the agreement contemplated that before disclosure the University would strip the patient records of all direct identifying information except the dates of medical events and services. Second, the agreement delineated the records’ authorized uses. In par- ticular, Google was permitted to use the records only to identify key medical information, to develop predictive models, and to assess the models’ efficacy. It could neither disclose information from within the records nor use the records in contravention of federal law. Most importantly, the agreement strictly prohibited Google from using the records “to identify any individual.” Third, if the parties’ research efforts proved successful, the agreement granted the University a perpetual license to use the predictive models for its own “internal non-commercial research purposes.” The batch of medical records covered by the Data Use Agreement spanned several years. Specifically, the agree- ment directed the University to transfer to Google anony- mized records generated from all inpatient, outpatient, and emergency adult-patient encounters between January 1, 2010, and June 30, 2016.

Free access — add to your briefcase to read the full text and ask questions with AI

Related

Cite This Page — Counsel Stack

Bluebook (online)
73 F.4th 502, Counsel Stack Legal Research, https://law.counselstack.com/opinion/matt-dinerstein-v-google-llc-ca7-2023.