Gaps in the Coordination of Care for Older Adults With or at Risk for Cardiovascular Disease

ABSTRACT

Objectives: We sought to determine whether patients with cardiovascular disease (CVD) or CVD risk factors and fragmented care (ie, care spread across multiple providers) perceive any gaps in communication among their providers and whether any gaps are perceived as clinically significant (ie, leading to adverse events).

Study Design: We conducted a cross-sectional telephone survey of community-dwelling Medicare beneficiaries 65 years and older with CVD or at least 1 CVD risk factor and highly fragmented ambulatory care (reversed Bice-Boxerman Index score ≥ 0.85) who had been attributed to an accountable care organization in New York, New York.

Methods: Using a previously tested survey instrument, we asked about perceptions of communication among the respondents’ providers, any adverse events (drug-drug interactions, duplicate tests, emergency department visits, or hospitalizations), and whether those events were preventable with better communication. We used descriptive statistics.

Results: Of 201 eligible individuals, 96 completed surveys (47.8% response rate). Of those, 94 (97.9%) reported having at least 2 ambulatory visits and at least 2 ambulatory providers in the past year and were included in our analytic sample. The mean (SD) age was 76 (6.8) years; approximately two-thirds (69%) were women. Approximately half of respondents (48%) reported a problem with, or “gap” in, communication among their providers. One in 14 respondents (7%) reported experiencing an adverse event that they thought could have been prevented with better communication.

Conclusions: Gaps in communication for patients with CVD or CVD risk factors are common and hazardous. Interventions are needed to leverage patients’ observations to address gaps in communication before they cause harm.

Am J Manag Care. 2025;31(6):268-273. https://doi.org/10.37765/ajmc.2025.89746

Takeaway Points

To determine whether older adults with cardiovascular disease (CVD) or CVD risk factors perceive gaps in communication among their providers and whether they consider those gaps to be consequential, we conducted a cross-sectional survey of Medicare beneficiaries 65 years and older with CVD or CVD risk factors and highly fragmented ambulatory care (reversed Bice-Boxerman Index score ≥ 0.85).

• Approximately half (48%) reported a problem with communication among their providers.
• One in 14 (7%) reported experiencing an adverse event that they thought could have been prevented with better communication.
• Interventions are needed to leverage patients’ observations and address gaps in communication before they cause harm.

Patients with cardiovascular disease (CVD) or CVD risk factors (such as hypertension, hyperlipidemia, and diabetes) frequently have physiologic problems affecting multiple organ systems, which can lead to receiving care from multiple providers in different fields (eg, primary care, cardiology, pulmonology, endocrinology, ophthalmology, nephrology, neurology).¹ Indeed, Medicare beneficiaries with CVD see more different physicians annually than the typical Medicare beneficiary overall.² Although this may be clinically appropriate, it creates challenges because physicians do not consistently communicate with each other, even in the era of electronic health records, often due to system-based constraints (such as lack of time or lack of reimbursement for communication).³ These gaps in communication can lead to harm for patients, including drug-drug interactions,⁴ as well as excess tests,⁵ procedures,⁶ emergency department visits,^7-10 and hospitalizations.^7,11-13

However, it is not clear whether patients with CVD or CVD risk factors are aware of gaps in communication when they occur. One study found that 38% of older adults perceive gaps in communication among their providers,¹⁴ but that study was not restricted to those with CVD or CVD risk factors. That study was also not restricted to those with highly fragmented care (that is, care spread across many ambulatory providers), who may be at particular risk for gaps in communication.

It is important to know how frequently patients with CVD or CVD risk factors perceive gaps in communication in order to inform the development of interventions to mitigate this gap in communication. Patients’ perceptions of communication have traditionally been used as a measure of satisfaction at the population level,¹⁵ but they may also represent opportunities to intervene at the individual level. We sought to determine how frequently people with CVD or CVD risk factors and highly fragmented care perceive gaps in communication among their providers. In addition, we sought to determine whether any gaps were perceived as clinically significant (that is, leading to adverse events that they thought could have been prevented with better communication).

METHODS

Overview

We conducted a cross-sectional survey regarding experiences with health care for people with or at risk for CVD who were randomly assigned to the intervention arm of a pragmatic clinical trial (NCT05820295). The Biomedical Research Alliance of New York institutional review board granted a waiver of informed consent.

Context

This study was embedded in an ongoing pragmatic clinical trial, which is designed to compare the effectiveness of 2 approaches for assigning patients with or at risk for CVD to care coordinators. In the usual care arm, patients are assigned to care coordinators after hospital discharge. In the intervention arm, we proactively reach out to patients (who are not hospitalized), inquire about whether they think their outpatient providers are coordinating with each other, and then offer the assistance of care coordinators to those who report that their outpatient providers are not coordinating with each other. The actual care coordination delivered is similar across the 2 groups; what differs is who is offered that service. This article focuses on the results of our initial outreach to those randomly assigned to the intervention group.

Setting

The setting for this study was NewYork Quality Care (NYQC), an accountable care organization (ACO) that brings together NewYork-Presbyterian Hospital, Weill Cornell Medicine (including the Weill Cornell Physician Organization), and Columbia University (including ColumbiaDoctors).¹⁶ As a Medicare ACO, NYQC takes clinical and financial responsibility for the patients attributed to it by CMS. NYQC provides overarching infrastructure to support population health management, including providing financial support for the care coordinators affiliated with its component organizations. Care coordinators are members of the medical team whose job it is to facilitate communication among all the participants involved in a patient’s care.¹⁷ Care coordinators typically (but are not required to) have backgrounds in nursing or social work. Because all the care coordinators in our study had advanced degrees in nursing or social work, they had the more advanced title of care manager, which we use for the remainder of the article.

Study Population

To be included in the trial overall, individuals had to meet all of the following inclusion criteria, which were captured through claims: (1) be a Medicare fee-for-service beneficiary 65 years or older; (2) have been attributed to the NYQC ACO by CMS for the 12-month period ending December 31, 2022; (3) have CVD or at least 1 CVD risk factor (defined as having 1 or more of the following conditions, using definitions from the CMS Chronic Conditions Data Warehouse¹⁸: acute myocardial infarction, atrial fibrillation, diabetes, heart failure, hyperlipidemia, hypertension, ischemic heart disease, and stroke or transient ischemic attack); (4) live in the community (not a facility); (5) have had at least 4 ambulatory visits in the previous 12 months (because measuring fragmentation with fewer than 4 visits is not reliable)¹⁹; (6) have had highly fragmented care in those 12 months, defined as a reversed Bice-Boxerman Index score of at least 0.85 (a cut point previously found to be independently associated with excess hospitalizations)¹¹; and (7) be in the catchment area of the 3 flagship care management teams for NYQC (NewYork-Presbyterian Hospital, Weill Cornell, and Columbia). We excluded those who were enrolled in hospice, as they would have limited ambulatory care patterns. We also excluded people living with dementia because those individuals are the focus of a separate study. We did not exclude anyone on the basis of language spoken, as the care managers had access to telephone-based translators if needed. Individuals meeting inclusion criteria for the trial were then stratified by care management team and randomly assigned within each team into 2 groups (intervention and control). This article focuses on the intervention group at baseline.

Data Collection

Outreach to the intervention group took place from May 17, 2023, to November 30, 2023. Each care manager received a list of patients and attempted to reach patients by phone, conducting up to 5 calls per patient. Care managers used a written script to describe the survey and invite participation. Participants were not given financial incentives to participate, but they were informed that if they qualified for care management (based on the survey responses), care management would be offered and provided at no cost to them.

Care managers administered a previously tested and published survey instrument about experiences with health care to those individuals who agreed to participate.¹⁴ The survey instrument consists of 22 questions: 8 questions about perceptions of care coordination, 8 questions about preventable adverse events, and 6 questions about ambulatory care utilization. The care managers read the survey aloud, answered any clarifying questions from the respondent, and entered responses into REDCap, a Health Insurance Portability and Accountability Act–compliant data collection platform.²⁰ The surveys took a median (IQR) of 13.50 (8.75-20.00) minutes to complete.

In addition to the data collected by the care managers, we collected from claims data information on patients’ age, sex, race, and comorbidities (using definitions from the CMS Chronic Conditions Data Warehouse¹⁸).

Data Analysis

We used descriptive statistics to characterize the sample and the survey results. We combined responses to 2 similar survey questions regarding how often and how quickly a respondent receives test results, yielding 7 unique questions about perceptions of care coordination.¹⁴ We dichotomized Likert response scales for the perceptions of care coordination questions to determine whether a problem (or “gap”) in care coordination was reported (eAppendix 1 [eAppendices available at ajmc.com]).¹⁴ We then tallied how many respondents reported at least 1 gap in care coordination. We conducted exploratory descriptive analyses showing the frequency of any gap in care coordination, stratified by age, sex, and race.

We also tallied the frequency of 4 self-reported adverse events that the respondents attributed to poor coordination (a test that was repeated because the provider did not have the results of the first test, a drug-drug interaction in the context of multiple prescribers, an emergency department visit that could have been prevented with better communication, and a hospitalization that could have been prevented with better communication).

Analyses were conducted using Stata 17 (StataCorp LP). P values less than .05 were considered significant.

RESULTS

Study Sample

Of the 202 patients in the trial who were randomly assigned to the intervention group, 1 died prior to the start of the trial (Figure). Of the remaining 201 patients, 49 (24.3%) were unable to be reached, 52 (25.9%) were reached but declined to participate, 4 (2.0%) were deemed not appropriate for the study based on the clinical judgment of the care managers, and 96 (47.8%) were willing to participate and completed the survey. Of the 96 respondents, 2 reported having only 1 ambulatory visit or 1 ambulatory provider in the past 12 months and were thus not at risk for gaps in care coordination. The remaining 94 respondents (97.9%) made up our analytic sample, and they were similar to the rest of the participants who were randomly assigned to the intervention group (eAppendix 2).

Sample Characteristics

The mean (SD) age of the respondents was 76 (6.8) years. More than two-thirds (69%) were women. The racial and ethnic distribution was 74% non-Hispanic White, 12% Black, 4% Hispanic, 5% Asian, 2% other, and 2% unknown. The 5 most common chronic conditions were hyperlipidemia (87%), hypertension (71%), ischemic heart disease (41%), diabetes (28%), and chronic kidney disease (20%). The frequency of additional chronic conditions is shown in Table 1. Eighty-nine percent had at least 2 chronic conditions.

Ambulatory Utilization

Nearly all (97%) of respondents reported that they have a usual ambulatory provider they could see for a checkup. Most (84%) had seen this provider in the past 6 months. Respondents reported having had a median (IQR) of 10 (5-15) ambulatory visits to 5 (4-6) different providers over the previous 12 months. Most (89%) reported that the number of visits they had was appropriate. Approximately half (57%) said that the number of visits they had was a result of joint decision-making with providers, whereas 18% said that they determined the number of visits and 25% said that the providers determined the number of visits.

Gaps in Care Coordination

Overall, approximately half (48%) of respondents reported any gap in care coordination. In terms of specific expressions of failures of care coordination, one-fourth of respondents (24%) reported that they only somewhat or never received the help they needed from their usual provider’s practice for coordinating care with other providers and services. Nearly one-fifth of respondents (18%) thought that, in general, the doctors they see do not communicate with each other about their care. Approximately 1 in 7 respondents (15%) rated the coordination of care among all the health professionals that they see, in general, as fair or poor. Nearly 1 in 10 respondents (9%) reported that their usual doctor only sometimes or never talked about all the prescription medicines they were taking. Frequencies of additional gaps in care coordination are shown in Table 2. Exploratory analyses stratifying the frequency of any self-reported gap in care coordination by age, sex, and race are shown in eAppendix 3.

Adverse Events

Overall, 7% of respondents said that they had experienced an adverse event in the past year that they attributed to poor care coordination (Table 3). Two respondents (2%) reported having tests repeated because the provider did not have the results of the first test, 4 respondents (4%) reported experiencing a drug-drug interaction in the context of multiple prescribers, and 1 respondent (1%) reported a hospital admission that could have been prevented with better communication.

DISCUSSION

In this study of 94 older adults with CVD or CVD risk factors, approximately half (48%) reported any problem with the way their providers were coordinating their care. Of note, 18% of respondents reported that they did not think their doctors communicate with each other about their care, and 15% of respondents rated coordination of care among their doctors as fair or poor. Moreover, approximately 1 in 14 respondents (7%) said that they had experienced an adverse event in the past year that they thought could have been prevented with better communication.

Our finding that half of respondents reported a problem with the coordination of their care is higher than the 38% figure found in a previous study of adults 65 years and older.¹⁴ This difference is likely due to our focus on the subset of those 65 years and older with CVD or CVD risk factors and highly fragmented care. Our results are consistent with a Harris Poll conducted online among more than 2500 adults nationally, which found that 49% of respondents felt that health care was not coordinated among their various providers.²¹ However, that result was not among those with CVD or CVD risk factors and may have used a convenience sample, as the poll’s sampling frame and response rate are not clear.

The fact that 7% of respondents had experienced an adverse event that they attributed to poor coordination is important because it illustrates that people do not think of gaps in care coordination as mere inconveniences but rather as potentially harmful. We previously found that ambulatory care fragmentation is independently associated with incident coronary heart disease events among those with very good or good self-rated health.²² We also previously found that ambulatory care fragmentation is independently associated with incident strokes among Black older adults with fair or poor health.²³ This study contributes the perspective of patients with highly fragmented care, indicating that gaps in care coordination are recognized by and important to them.

It is both not surprising and quite shocking that half the respondents reported problems with the coordination of their care. It is not surprising because this issue is well known anecdotally, with experts including “failures of care coordination” among the major sources of waste in health care today.²⁴ It is shocking because it often seems to be accepted as what happens in US health care today, even though this reflects a level of poor quality that should probably not be tolerated.²⁵ Because fragmentation is about care delivery (not biology), it is inherently modifiable. The results of this study support a recent call to have more national discussions about potential interventions that could be deployed to address fragmentation at the levels of the patient, provider, practice, payer, purchaser (employer), and population (community).²⁶

Limitations

This study has several limitations. First, it is cross-sectional and cannot prove causality. Second, it is based on self-report and may be affected by recall bias. However, numerous studies have documented that patients’ reports of errors in medical care are often accurate.^27-32 Moreover, even if patients are not always accurate, their perceptions are valid and should be addressed. Third, although we had a good response rate of 47.8%, we cannot rule out the possibility of selection bias. Fourth, this study took place in the context of 1 Medicare ACO in New York, which may not be generalizable. However, fragmented care takes place throughout the country, even in less urban areas, such as the state of Indiana³³ and western Massachusetts.³⁴ Fifth, the sample size is relatively small, although the estimate for the frequency of gaps in communication was very large.

CONCLUSIONS

Approximately half of patients 65 years and older with CVD or CVD risk factors believe that their providers are not coordinating their care well. Approximately 1 in 14 patients with CVD or CVD risk factors reported having had an adverse event that they thought could have been prevented by better communication. Interventions are needed to leverage patients’ observations and address gaps in communication before they cause harm.

Acknowledgments

The authors would like to thank additional care manager supervisors and care managers who participated in this study: Caryn Donocoff, MS, FNP-C; Kimberly Rosado, DNP, RN-BC; Shirley Jean-Baptiste, RN; Nancy Conroy, RN; Glenda Hall, LMSW; Kathrina Enad, RN; Patricia Rojas-Guerrero, RN; Justine Llop, RN; Lina Forero, RN; and Melissa Feliciano, MSN, RN-BC. The authors would like to thank the NewYork Quality Care administrative and data analytic team: Jessica Han, MSc, MPH; Kelly Wu, MPH; and Jamie Bialor, MPH. In addition, the authors would like to thank Lloyd Dalzell (patient representative) and, separately, the patients who participated in the study.

Author Affiliations: Weill Cornell Medicine (LMK, JEA, SB, JBR, SF, HM, MRS, MMS, PNC), New York, NY; Clinical Directors Network (JNT), New York, NY; The Rockefeller University Center for Clinical and Translational Science (JNT), New York, NY; Case Western Reserve University (KCS), Cleveland, OH; NewYork Quality Care (PNC), New York, NY.

Source of Funding: This study was supported by the Agency for Healthcare Research and Quality (grant K18HS029255). Access to the REDCap tool was provided by the Weill Cornell Clinical & Translational Science Center, which is funded by the National Institutes of Health (UL1TR002384). The funding agencies played no role in the design or conduct of the study, and no role in data management, data analysis, interpretation of data, or preparation of the manuscript.

Author Disclosures: Dr Kern was a consultant to Mathematica, Inc. Dr Tobin has been a consultant to Amgen, AstraZeneca, Washington University at St Louis, and Weill Cornell Medicine; has grants pending from the Patient-Centered Outcomes Research Institute; has received grants from the Administration for Community Living; Agency for Healthcare Research and Quality; Bristol Myers Squibb; The Campbell Foundation; CDC; Johnson & Johnson/Janssen; Leukemia & Lymphoma Society; National Cancer Institute; National Center for Advancing Translational Sciences; National Heart, Lung, and Blood Institute; National Institute of Diabetes and Digestive and Kidney Diseases; National Institute of Mental Health; National Institute on Minority Health and Health Disparities; National Institute of Nursing Research; Patient-Centered Outcomes Research Institute; RCHN Community Health Foundation; Sackler Foundation; and Syneos Health; and has received honoraria from the National Cancer Institute and Weill Cornell Medicine. The remaining authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (LMK, JNT, HM, MRS, KCS, MMS); acquisition of data (JEA, HM); analysis and interpretation of data (LMK, JEA, SB, JBR, JNT, HM, MRS, MMS, PNC); drafting of the manuscript (LMK, SB, JBR, JNT, PNC); critical revision of the manuscript for important intellectual content (LMK, JEA, JNT, SF, MRS, KCS, MMS, PNC); statistical analysis (SB, JBR); provision of patients or study materials (LMK, SF); obtaining funding (LMK); administrative, technical, or logistic support (LMK, SF); patient outreach (HM); preliminary planning (KCS); and supervision (LMK, JNT, SF).

Address Correspondence to: Lisa M. Kern, MD, MPH, Weill Cornell Medicine, 420 E 70th St, Box 331, New York, NY 10021. Email: lmk2003@med.cornell.edu.

REFERENCES

1. Kern LM, Safford MM, Slavin MJ, et al. Patients’ and providers’ views on the causes and consequences of healthcare fragmentation in the ambulatory setting: a qualitative study. J Gen Intern Med. 2019;34(6):899-907. doi:10.1007/s11606-019-04859-1

2. Pham HH, Schrag D, O’Malley AS, Wu B, Bach PB. Care patterns in Medicare and their implications for pay for performance. N Engl J Med. 2007;356(11):1130-1139. doi:10.1056/NEJMsa063979

3. Timmins L, Kern LM, O’Malley AS, Urato C, Ghosh A, Rich E. Communication gaps persist between primary care and specialist physicians. Ann Fam Med. 2022;20(4):343-347. doi:10.1370/afm.2781

4. Guo JY, Chou YJ, Pu C. Effect of continuity of care on drug-drug interactions. Med Care. 2017;55(8):744-751. doi:10.1097/MLR.0000000000000758

5. Kern LM, Seirup JK, Casalino LP, Safford MM. Healthcare fragmentation and the frequency of radiology and other diagnostic tests: a cross-sectional study. J Gen Intern Med. 2017;32(2):175-181. doi:10.1007/s11606-016-3883-z

6. Romano MJ, Segal JB, Pollack CE. The association between continuity of care and the overuse of medical procedures. JAMA Intern Med. 2015;175(7):1148-1154. doi:10.1001/jamainternmed.2015.1340

7. Hussey PS, Schneider EC, Rudin RS, Fox DS, Lai J, Pollack CE. Continuity and the costs of care for chronic disease. JAMA Intern Med. 2014;174(5):742-748. doi:10.1001/jamainternmed.2014.245

8. Katz DA, McCoy KD, Vaughan-Sarrazin MS. Does greater continuity of Veterans Administration primary care reduce emergency department visits and hospitalization in older veterans? J Am Geriatr Soc. 2015;63(12):2510-2518. doi:10.1111/jgs.13841

9. Kern LM, Ringel JB, Rajan M, et al. Ambulatory care fragmentation, emergency department visits, and race: a nationwide cohort study in the U.S. J Gen Intern Med. 2023;38(4):873-880. doi:10.1007/s11606-022-07888-5

10. Liu CW, Einstadter D, Cebul RD. Care fragmentation and emergency department use among complex patients with diabetes. Am J Manag Care. 2010;16(6):413-420.

11. Kern LM, Ringel JB, Rajan M, et al. Ambulatory care fragmentation and subsequent hospitalization: evidence from the REGARDS study. Med Care. 2021;59(4):334-340. doi:10.1097/MLR.0000000000001470

12. Nyweide DJ, Anthony DL, Bynum JPW, et al. Continuity of care and the risk of preventable hospitalization in older adults. JAMA Intern Med. 2013;173(20):1879-1885. doi:10.1001/jamainternmed.2013.10059

13. Rajan M, Helmer D, Rowneki M, Fried D, Kern LM. Ambulatory care fragmentation and hospitalization among veterans with diabetes. Am J Manag Care. 2021;27(4):155-160. doi:10.37765/ajmc.2021.88509

14. Kern LM, Reshetnyak E, Colantonio LD, et al. Association between patients’ self-reported gaps in care coordination and preventable adverse outcomes: a cross-sectional survey. J Gen Intern Med. 2020;35(12):3517-3524. doi:10.1007/s11606-020-06047-y

15. Ducharme J. Exclusive: more than 70% of Americans feel failed by the health care system. Time. May 16, 2023. Accessed May 8, 2024. https://time.com/6279937/us-health-care-system-attitudes/

16. Casale PN, Gordon J, Stewart MG, Cioffi GA, Alge D, Deland EL. Success in a hospital-integrated accountable care organization. NEJM Catalyst. July 10, 2019. Accessed May 8, 2024. https://catalyst.nejm.org/doi/full/10.1056/CAT.19.0642

17. Evans M. Demand grows for care coordinators. Modern Healthcare. March 28, 2015. Accessed May 8, 2024. https://www.modernhealthcare.com/article/20150328/MAGAZINE/303289980/demand-grows-for-care-coordinators

18. Chronic Conditions Data Warehouse. CMS. Accessed May 8, 2024. https://www2.ccwdata.org/web/guest/home

19. Nyweide DJ, Bynum JPW. Relationship between continuity of ambulatory care and risk of emergency department episodes among older adults. Ann Emerg Med. 2017;69(4):407-415.e3. doi:10.1016/j.annemergmed.2016.06.027

20. Research Electronic Data Capture (REDCap). Vanderbilt University. Accessed May 8, 2024. https://projectredcap.org/

21. American Academy of Physician Associates; The Harris Poll. The Patient Experience: Perspectives on Today’s Healthcare. American Academy of Physician Associates. Accessed May 8, 2024. https://www.aapa.org/download/113513/?tmstv=1684243672

22. Kern LM, Rajan M, Ringel JB, et al. Healthcare fragmentation and incident acute coronary heart disease events: a cohort study. J Gen Intern Med. 2021;36(2):422-429. doi:10.1007/s11606-020-06305-z

23. Kern LM, Ringel JB, Rajan M, et al. Ambulatory care fragmentation and incident stroke. J Am Heart Assoc. 2021;10(9):e019036. doi:10.1161/JAHA.120.019036

24. Berwick DM, Hackbarth AD. Eliminating waste in US health care. JAMA. 2012;307(14):1513-1516. doi:10.1001/jama.2012.362

25. Yurkiewicz I. Fragmented: A Doctor’s Quest to Piece Together American Health Care. W. W. Norton & Company Ltd; 2023.

26. Kern LM, Bynum JPW, Pincus HA. Care fragmentation, care continuity, and care coordination—how they differ and why it matters. JAMA Intern Med. 2024;184(3):236-237. doi:10.1001/jamainternmed.2023.7628

27. Bell SK, Gerard M, Fossa A, et al. A patient feedback reporting tool for OpenNotes: implications for patient-clinician safety and quality partnerships. BMJ Qual Saf. 2017;26(4):312-322. doi:10.1136/bmjqs-2016-006020

28. Gillespie A, Reader TW. Patient-centered insights: using health care complaints to reveal hot spots and blind spots in quality and safety. Milbank Q. 2018;96(3):530-567. doi:10.1111/1468-0009.12338

29. Khan A, Furtak SL, Melvin P, Rogers JE, Schuster MA, Landrigan CP. Parent-reported errors and adverse events in hospitalized children. JAMA Pediatr. 2016;170(4):e154608. doi:10.1001/jamapediatrics.2015.4608

30. Mercer AN, Mauskar S, Baird J, et al. Family safety reporting in hospitalized children with medical complexity. Pediatrics. 2022;150(2):e2021055098. doi:10.1542/peds.2021-055098

31. Weingart SN, Pagovich O, Sands DZ, et al. What can hospitalized patients tell us about adverse events? learning from patient-reported incidents. J Gen Intern Med. 2005;20(9):830-836. doi:10.1111/j.1525-1497.2005.0180.x

32. Weissman JS, Schneider EC, Weingart SN, et al. Comparing patient-reported hospital adverse events with medical record review: do patients know something that hospitals do not? Ann Intern Med. 2008;149(2):100-108. doi:10.7326/0003-4819-149-2-200807150-00006

33. Finnell JT, Overhage JM, Grannis S. All health care is not local: an evaluation of the distribution of emergency department care delivered in Indiana. AMIA Annu Symp Proc. 2011;2011:409-416.

34. Bourgeois FC, Olson KL, Mandl KD. Patients treated at multiple acute health care facilities: quantifying information fragmentation. Arch Intern Med. 2010;170(22):1989-1995. doi:10.1001/archinternmed.2010.439