Research Original Investigation
Patient-Centered Medical Home Implementation
18. Helfrich CD, Dolan ED, Simonetti J, et al. Elements of team-based care in a patient-centered medical home are associated with lower burnout among VA primary care employees. J Gen Intern Med. 2014. doi:10.1007/s11606-013-2702-z.
26. Goulet JL, Erdos J, Kancir S, et al. Measuring performance directly using the Veterans Health Administration electronic medical record: a comparison with external peer review. Med Care. 2007;45(1):73-79.
35. Friedberg MW, Safran DG, Coltin KL, Dresser M, Schneider EC. Readiness for the patient-centered medical home: structural capabilities of Massachusetts primary care practices. J Gen Intern Med. 2009;24(2):162-169.
19. Shen Y, Hendricks A, Zhang S, Kazis LE. VHA enrollees’ health care coverage and use of care. Med Care Res Rev. 2003;60(2):253-267.
27. Agency for Healthcare Research and Quality. Prevention quality indicators. http://www .qualityindicators.ahrq.gov/modules/pqi_resources .aspx. Accessed February 28, 2014.
36. Martsolf GR, Alexander JA, Shi Y, et al. The patient-centered medical home and patient experience. Health Serv Res. 2012;47(6):2273-2295.
20. Perlin JB, Kolodner RM, Roswell RH. The Veterans Health Administration: quality, value, accountability, and information as transforming strategies for patient-centered care. Am J Manag Care. 2004;10(11, pt 2):828-836. 21. Schaufeli WB, Enzmann D, Girault N. Measurement of burnout: a review. In: Schaufeli WB, ed. Professional Burnout: Recent Developments in Theory and Research. Philadelphia, PA: Taylor & Francis; 1993:199-215. 22. Wheeler DL, Vassar M, Worley JA, Barnes LL. A reliability generalization meta-analysis of coefficient alpha for the Maslach Burnout Inventory. Educ Psychol Meas. 2011;71(1):231-244. doi:10.1177/0013164410391579. 23. Maslach C, Jackson SE. The measurement of experienced burnout. J Organiz Behav. 1981;2(2) 99-113. doi:10.1002/job.4030020205. 24. Rohland BM, Kruse GR, Rohrer JE. Validation of a single-item measure of burnout against the Maslach Burnout Inventory among physicians. Stress Health. 2004;20(2):75-79. doi:10.1002/smi.1002. 25. Leiter MP, Shaughnessy K. The areas of worklife model of burnout: tests of mediation relationships. Ergonomia. 2006;28:327-341.
28. Elixhauser A, Steiner C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care. 1998;36(1):8-27. 29. Cuzick J. A Wilcoxon-type test for trend. Stat Med. 1985;4(1):87-90. 30. Benjamini Y, Yekutieli D. The control of the false discovery rate in multiple testing under dependency. Ann Stat. 2001;29:1165-1188. 31. Hebert PLLC, Wong ES, Hernandez SE, et al. The economic effects and return on investment of the Veterans Health Administration’s Patient Centered Home Initiative, 2010 through 2012. Health Aff. In press. 32. Liu CF, Chapko M, Bryson CL, et al. Use of outpatient care in Veterans Health Administration and Medicare among veterans receiving primary care in community-based and hospital outpatient clinics. Health Serv Res. 2010;45(5, pt 1):1268-1286. 33. Yoon J, Rose DE, Canelo I, et al. Medical home features of VHA primary care clinics and avoidable hospitalizations. J Gen Intern Med. 2013;28(9):11881194. 34. Holmboe ES, Arnold GK, Weng W, Lipner R. Current yardsticks may be inadequate for measuring quality improvements from the medical home. Health Aff (Millwood). 2010;29(5):859-866.
37. Gray BM, Weng W, Holmboe ES. An assessment of patient-based and practice infrastructure-based measures of the patient-centered medical home: do we need to ask the patient? Health Serv Res. 2012;47(1, pt 1):4-21. 38. Kerr EA, Gerzoff RB, Krein SL, et al. Diabetes care quality in the Veterans Affairs Health Care System and commercial managed care: the TRIAD study. Ann Intern Med. 2004;141(4):272-281. 39. Birnberg JM, Drum ML, Huang ES, et al. Development of a safety net medical home scale for clinics. J Gen Intern Med. 2011;26(12):1418-1425. 40. Shanafelt TD, Boone S, Tan L, et al. Burnout and satisfaction with work-life balance among US physicians relative to the general US population. Arch Intern Med. 2012;172(18):1377-1385. 41. Lewis SE, Nocon RS, Tang H, et al. Patient-centered medical home characteristics and staff morale in safety net clinics. Arch Intern Med. 2012;172(1):23-31. 42. Wang L, Porter B, Maynard C, et al. Predicting risk of hospitalization or death among patients receiving primary care in the Veterans Health Administration. Med Care. 2013;51(4):368-373.
Invited Commentary
Not All (Medical) Homes Are Built Alike Some Work Better Than Others Richard J. Baron, MD
In this issue of JAMA Internal Medicine, Nelson et al1 provide an informative study of a large-scale implementation of the patient-centered medical home (PCMH) model within the Veteran’s Health Administration (VHA), looking at Related article page 1350 important outcomes of hospitalization and emergency department use, patient satisfaction, and staff burnout. The scale of the study is impressive, involving administrative and clinical data on 5.6 million veterans receiving care at all 913 VHA clinics. The findings that both utilization rates and staff burnout declined while patient satisfaction improved have face validity and will encourage continued development of this model. Perhaps even more important, the authors confront head on some of the methodologic challenges in studying PCMH implementation, including the variable definitions of the PCMH model itself, the need to risk-adjust for the varying populations that might be served, and factors other than the implementation of the PCMH 1358
that could be contributing to any observed variation. Even though the study was done within the VHA—which might lead some readers to question the relevance of the findings to outside systems—the design of the study allows us to glean some highly relevant national lessons. The VHA decided to implement a PCMH-type model in 2010 across its entire system, the Patient Aligned Care Team (PACT), which did not rely on any existing definitions of the PCMH. Instead, the VHA chose to reorganize existing resources (resources that would not be available to typical community practices or even to many primary care practices in other delivery systems), focusing on team-based care, improved access, and care management. The VHA chose to “get the idea” of a PCMH and express it in the VHA’s own context. Nelson et al1 realized that there would be variable success in the actual implementation of the PACT model in the VHA system. This led them to develop their own index, the PACT Implementation Progress Index (Pi2), which would allow them to measure different components of the PACT imple-
JAMA Internal Medicine August 2014 Volume 174, Number 8
Copyright 2014 American Medical Association. All rights reserved.
Downloaded From: http://archinte.jamanetwork.com/ by a New York University User on 06/02/2015
jamainternalmedicine.com
Patient-Centered Medical Home Implementation
Original Investigation Research
mentation at each of the 913 VHA clinics and then allow them to correlate success in implementation with the outcomes achieved in rates of hospitalization and emergency department visits, patient satisfaction, and staff burnout. This was a wise decision: many attributes of a PCMH in commonly used credentialing activities (eg, National Committee for Quality Assurance PCMH tool2) give “credit” for the presence of various structural aspects of care delivery, many of which are part of how the VHA as an integrated delivery system already delivers care. The authors realized that using any existing PCMH tool to measure “PCMH-ness” would not allow them to differentiate the VHA clinics in a meaningful way. The authors broke down PACT implementation into 8 domains (eg, access and team-based care), which they were able to score using multiple elements from 3 data sources (patient surveys, provider surveys, and a corporate data warehouse maintained by the VHA), calculating a single score based on these multiple data elements (Table 1). They then stratified all 913 practices by Pi2 score into deciles and compared them for the outcomes of interest, including patient experience and staff burnout (Table 3), emergency department visits and hospitalizations (Table 4), and quarterly hospitalization rates, both total and for ambulatory care–sensitive conditions (Table 5). The results are striking. The more effective a clinic site was at PACT implementation as measured by the Pi2 score, the higher the level of patient satisfaction (P < .001) and the lower the level of staff burnout (P < .05). For emergency department visits, the correlations were equally impressive (P < .001). The observed change for total hospital admissions was not large (4.8% reduction), but it was statistically significant (P < .001); when admissions were separated into those for ambulatory care–sensitive conditions, the effect was larger (13.4% reduction), and the correlations were again significant (P < .001). Of 48 measures of clinical quality, 41 were higher in the top decile of practices than in the bottom decile, with 19 of the differences statistically significant (P < .05). Why does all of this matter? First, many of the efforts to reorganize health care to achieve higher quality at lower cost are focused on strengthening primary care, commonly using the PCMH model as a template. Such efforts require additional new resources for primary care, and we need to know whether there is a return on that investment. Study findings have been conflicting. A recent study involving community practices in Pennsylvania (full disclosure: the practice where ARTICLE INFORMATION Author Affiliation: American Board of Internal Medicine, Philadelphia, Pennsylvania. Corresponding Author: Richard J. Baron, MD, American Board of Internal Medicine, 510 Walnut St, Philadelphia, PA 19106 ([email protected]). Published Online: June 23, 2014. doi:10.1001/jamainternmed.2014.2497. Conflict of Interest Disclosures: None reported. REFERENCES 1. Nelson KM, Helfrich C, Sun H, et al. Implementation of the patient-centered medical
I used to work was one of them) showed little effect on total quality and none on total cost,3 whereas a compendium of studies catalogued by the Patient-Centered Primary Care Collaborative suggests substantial positive effects on both quality and cost.4 It seems clear that we need to know more about the PCMH, including which key elements need to be in place and which patients are most likely to benefit. There will, of course, be variability in how PCMH models are implemented around the country in non-VHA settings. The study by Nelson et al1 helps inform our understanding of the core structural elements requisite to success in a PCMH model, the 8 elements of the Pi2: access, continuity of care, care coordination, comprehensiveness, self-management support, patient-centered care and communication, shared decision making, and team-based care (including delegation, staffing, and team functioning) (Table 1). Just as the VHA had to adapt the PCMH concept to its own context in developing and implementing the PACT model, practices that aspire to be a successful PCMH could assess their own performance for the constructs that underlie the Pi2 (asking, for example, “Are we providing access? Do we have continuity? Do we offer shared decision making?”) and use that assessment as a less bureaucratic and more authentic measure of how likely the practice is to improve the patient experience, decrease staff burnout, and decrease total costs of care. Practices need not measure as precisely as the VHA investigators did, and they probably cannot without the same rich data environment. But the current findings outline, in accessible terms, where a primary care practice needs to go, and they could support the development of other assessment tools for PCMH-ness. Nelson et al1 did not address the question of which patients are likely to benefit, but it is becoming increasingly clear that a PCMH needs to target high-cost, complex patients.5 Healthy persons, fortunately, do not consume enough health services for us to expect that improving care delivery to them alone will save money and justify increased investment. Antihypertensive medications do a terrific job of reducing the risk of myocardial infarction and stroke, but only in those with high blood pressure; similarly, the PCMH model will not improve results among patients for whom results are already pretty good. However, as we design and implement new primary care models to achieve the triple aim of higher quality, lower cost, and better patient experience, the VHA findings will help point the way to success.
home in the Veterans Health Administration: associations with patient satisfaction, quality of care, staff burnout, and hospital and emergency department use [published online June 23, 2014]. JAMA Intern Med. doi:10.1001/jamainternmed.2014 .2488. 2. National Committee for Quality Assurance. Patient-centered medical home survey tool. www.ncqa.org/PublicationsProducts /RecognitionProducts/PCMHPublications.aspx. Accessed May 9, 2014. 3. Friedberg MW, Schneider EC, Rosenthal MB, Volpp KG, Werner RM. Association between participation in a multipayer medical home
jamainternalmedicine.com
intervention and changes in quality, utilization, and costs of care. JAMA. 2014;311(8):815-825. doi:10.1001/jama.2014.353. 4. Nielsen M, Olayiwola JN, Grundy P, Grumbach K. The patient-centered medical home's impact on cost & quality: an annual update of the evidence, 2012-2013. Patient-Centered Primary Care Collaborative. Published January 2014. www.pcpcc .org/resource/medical-homes-impact -cost-quality. Accessed May 9, 2014. 5. Schwenk TL. The patient-centered medical home: one size does not fit all. JAMA. 2014;311(8): 802-803. doi:10.1001/jama.2014.352.
JAMA Internal Medicine August 2014 Volume 174, Number 8
Copyright 2014 American Medical Association. All rights reserved.
Downloaded From: http://archinte.jamanetwork.com/ by a New York University User on 06/02/2015
1359
Patient-Centered Medical Home Implementation
18. Helfrich CD, Dolan ED, Simonetti J, et al. Elements of team-based care in a patient-centered medical home are associated with lower burnout among VA primary care employees. J Gen Intern Med. 2014. doi:10.1007/s11606-013-2702-z.
26. Goulet JL, Erdos J, Kancir S, et al. Measuring performance directly using the Veterans Health Administration electronic medical record: a comparison with external peer review. Med Care. 2007;45(1):73-79.
35. Friedberg MW, Safran DG, Coltin KL, Dresser M, Schneider EC. Readiness for the patient-centered medical home: structural capabilities of Massachusetts primary care practices. J Gen Intern Med. 2009;24(2):162-169.
19. Shen Y, Hendricks A, Zhang S, Kazis LE. VHA enrollees’ health care coverage and use of care. Med Care Res Rev. 2003;60(2):253-267.
27. Agency for Healthcare Research and Quality. Prevention quality indicators. http://www .qualityindicators.ahrq.gov/modules/pqi_resources .aspx. Accessed February 28, 2014.
36. Martsolf GR, Alexander JA, Shi Y, et al. The patient-centered medical home and patient experience. Health Serv Res. 2012;47(6):2273-2295.
20. Perlin JB, Kolodner RM, Roswell RH. The Veterans Health Administration: quality, value, accountability, and information as transforming strategies for patient-centered care. Am J Manag Care. 2004;10(11, pt 2):828-836. 21. Schaufeli WB, Enzmann D, Girault N. Measurement of burnout: a review. In: Schaufeli WB, ed. Professional Burnout: Recent Developments in Theory and Research. Philadelphia, PA: Taylor & Francis; 1993:199-215. 22. Wheeler DL, Vassar M, Worley JA, Barnes LL. A reliability generalization meta-analysis of coefficient alpha for the Maslach Burnout Inventory. Educ Psychol Meas. 2011;71(1):231-244. doi:10.1177/0013164410391579. 23. Maslach C, Jackson SE. The measurement of experienced burnout. J Organiz Behav. 1981;2(2) 99-113. doi:10.1002/job.4030020205. 24. Rohland BM, Kruse GR, Rohrer JE. Validation of a single-item measure of burnout against the Maslach Burnout Inventory among physicians. Stress Health. 2004;20(2):75-79. doi:10.1002/smi.1002. 25. Leiter MP, Shaughnessy K. The areas of worklife model of burnout: tests of mediation relationships. Ergonomia. 2006;28:327-341.
28. Elixhauser A, Steiner C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care. 1998;36(1):8-27. 29. Cuzick J. A Wilcoxon-type test for trend. Stat Med. 1985;4(1):87-90. 30. Benjamini Y, Yekutieli D. The control of the false discovery rate in multiple testing under dependency. Ann Stat. 2001;29:1165-1188. 31. Hebert PLLC, Wong ES, Hernandez SE, et al. The economic effects and return on investment of the Veterans Health Administration’s Patient Centered Home Initiative, 2010 through 2012. Health Aff. In press. 32. Liu CF, Chapko M, Bryson CL, et al. Use of outpatient care in Veterans Health Administration and Medicare among veterans receiving primary care in community-based and hospital outpatient clinics. Health Serv Res. 2010;45(5, pt 1):1268-1286. 33. Yoon J, Rose DE, Canelo I, et al. Medical home features of VHA primary care clinics and avoidable hospitalizations. J Gen Intern Med. 2013;28(9):11881194. 34. Holmboe ES, Arnold GK, Weng W, Lipner R. Current yardsticks may be inadequate for measuring quality improvements from the medical home. Health Aff (Millwood). 2010;29(5):859-866.
37. Gray BM, Weng W, Holmboe ES. An assessment of patient-based and practice infrastructure-based measures of the patient-centered medical home: do we need to ask the patient? Health Serv Res. 2012;47(1, pt 1):4-21. 38. Kerr EA, Gerzoff RB, Krein SL, et al. Diabetes care quality in the Veterans Affairs Health Care System and commercial managed care: the TRIAD study. Ann Intern Med. 2004;141(4):272-281. 39. Birnberg JM, Drum ML, Huang ES, et al. Development of a safety net medical home scale for clinics. J Gen Intern Med. 2011;26(12):1418-1425. 40. Shanafelt TD, Boone S, Tan L, et al. Burnout and satisfaction with work-life balance among US physicians relative to the general US population. Arch Intern Med. 2012;172(18):1377-1385. 41. Lewis SE, Nocon RS, Tang H, et al. Patient-centered medical home characteristics and staff morale in safety net clinics. Arch Intern Med. 2012;172(1):23-31. 42. Wang L, Porter B, Maynard C, et al. Predicting risk of hospitalization or death among patients receiving primary care in the Veterans Health Administration. Med Care. 2013;51(4):368-373.
Invited Commentary
Not All (Medical) Homes Are Built Alike Some Work Better Than Others Richard J. Baron, MD
In this issue of JAMA Internal Medicine, Nelson et al1 provide an informative study of a large-scale implementation of the patient-centered medical home (PCMH) model within the Veteran’s Health Administration (VHA), looking at Related article page 1350 important outcomes of hospitalization and emergency department use, patient satisfaction, and staff burnout. The scale of the study is impressive, involving administrative and clinical data on 5.6 million veterans receiving care at all 913 VHA clinics. The findings that both utilization rates and staff burnout declined while patient satisfaction improved have face validity and will encourage continued development of this model. Perhaps even more important, the authors confront head on some of the methodologic challenges in studying PCMH implementation, including the variable definitions of the PCMH model itself, the need to risk-adjust for the varying populations that might be served, and factors other than the implementation of the PCMH 1358
that could be contributing to any observed variation. Even though the study was done within the VHA—which might lead some readers to question the relevance of the findings to outside systems—the design of the study allows us to glean some highly relevant national lessons. The VHA decided to implement a PCMH-type model in 2010 across its entire system, the Patient Aligned Care Team (PACT), which did not rely on any existing definitions of the PCMH. Instead, the VHA chose to reorganize existing resources (resources that would not be available to typical community practices or even to many primary care practices in other delivery systems), focusing on team-based care, improved access, and care management. The VHA chose to “get the idea” of a PCMH and express it in the VHA’s own context. Nelson et al1 realized that there would be variable success in the actual implementation of the PACT model in the VHA system. This led them to develop their own index, the PACT Implementation Progress Index (Pi2), which would allow them to measure different components of the PACT imple-
JAMA Internal Medicine August 2014 Volume 174, Number 8
Copyright 2014 American Medical Association. All rights reserved.
Downloaded From: http://archinte.jamanetwork.com/ by a New York University User on 06/02/2015
jamainternalmedicine.com
Patient-Centered Medical Home Implementation
Original Investigation Research
mentation at each of the 913 VHA clinics and then allow them to correlate success in implementation with the outcomes achieved in rates of hospitalization and emergency department visits, patient satisfaction, and staff burnout. This was a wise decision: many attributes of a PCMH in commonly used credentialing activities (eg, National Committee for Quality Assurance PCMH tool2) give “credit” for the presence of various structural aspects of care delivery, many of which are part of how the VHA as an integrated delivery system already delivers care. The authors realized that using any existing PCMH tool to measure “PCMH-ness” would not allow them to differentiate the VHA clinics in a meaningful way. The authors broke down PACT implementation into 8 domains (eg, access and team-based care), which they were able to score using multiple elements from 3 data sources (patient surveys, provider surveys, and a corporate data warehouse maintained by the VHA), calculating a single score based on these multiple data elements (Table 1). They then stratified all 913 practices by Pi2 score into deciles and compared them for the outcomes of interest, including patient experience and staff burnout (Table 3), emergency department visits and hospitalizations (Table 4), and quarterly hospitalization rates, both total and for ambulatory care–sensitive conditions (Table 5). The results are striking. The more effective a clinic site was at PACT implementation as measured by the Pi2 score, the higher the level of patient satisfaction (P < .001) and the lower the level of staff burnout (P < .05). For emergency department visits, the correlations were equally impressive (P < .001). The observed change for total hospital admissions was not large (4.8% reduction), but it was statistically significant (P < .001); when admissions were separated into those for ambulatory care–sensitive conditions, the effect was larger (13.4% reduction), and the correlations were again significant (P < .001). Of 48 measures of clinical quality, 41 were higher in the top decile of practices than in the bottom decile, with 19 of the differences statistically significant (P < .05). Why does all of this matter? First, many of the efforts to reorganize health care to achieve higher quality at lower cost are focused on strengthening primary care, commonly using the PCMH model as a template. Such efforts require additional new resources for primary care, and we need to know whether there is a return on that investment. Study findings have been conflicting. A recent study involving community practices in Pennsylvania (full disclosure: the practice where ARTICLE INFORMATION Author Affiliation: American Board of Internal Medicine, Philadelphia, Pennsylvania. Corresponding Author: Richard J. Baron, MD, American Board of Internal Medicine, 510 Walnut St, Philadelphia, PA 19106 ([email protected]). Published Online: June 23, 2014. doi:10.1001/jamainternmed.2014.2497. Conflict of Interest Disclosures: None reported. REFERENCES 1. Nelson KM, Helfrich C, Sun H, et al. Implementation of the patient-centered medical
I used to work was one of them) showed little effect on total quality and none on total cost,3 whereas a compendium of studies catalogued by the Patient-Centered Primary Care Collaborative suggests substantial positive effects on both quality and cost.4 It seems clear that we need to know more about the PCMH, including which key elements need to be in place and which patients are most likely to benefit. There will, of course, be variability in how PCMH models are implemented around the country in non-VHA settings. The study by Nelson et al1 helps inform our understanding of the core structural elements requisite to success in a PCMH model, the 8 elements of the Pi2: access, continuity of care, care coordination, comprehensiveness, self-management support, patient-centered care and communication, shared decision making, and team-based care (including delegation, staffing, and team functioning) (Table 1). Just as the VHA had to adapt the PCMH concept to its own context in developing and implementing the PACT model, practices that aspire to be a successful PCMH could assess their own performance for the constructs that underlie the Pi2 (asking, for example, “Are we providing access? Do we have continuity? Do we offer shared decision making?”) and use that assessment as a less bureaucratic and more authentic measure of how likely the practice is to improve the patient experience, decrease staff burnout, and decrease total costs of care. Practices need not measure as precisely as the VHA investigators did, and they probably cannot without the same rich data environment. But the current findings outline, in accessible terms, where a primary care practice needs to go, and they could support the development of other assessment tools for PCMH-ness. Nelson et al1 did not address the question of which patients are likely to benefit, but it is becoming increasingly clear that a PCMH needs to target high-cost, complex patients.5 Healthy persons, fortunately, do not consume enough health services for us to expect that improving care delivery to them alone will save money and justify increased investment. Antihypertensive medications do a terrific job of reducing the risk of myocardial infarction and stroke, but only in those with high blood pressure; similarly, the PCMH model will not improve results among patients for whom results are already pretty good. However, as we design and implement new primary care models to achieve the triple aim of higher quality, lower cost, and better patient experience, the VHA findings will help point the way to success.
home in the Veterans Health Administration: associations with patient satisfaction, quality of care, staff burnout, and hospital and emergency department use [published online June 23, 2014]. JAMA Intern Med. doi:10.1001/jamainternmed.2014 .2488. 2. National Committee for Quality Assurance. Patient-centered medical home survey tool. www.ncqa.org/PublicationsProducts /RecognitionProducts/PCMHPublications.aspx. Accessed May 9, 2014. 3. Friedberg MW, Schneider EC, Rosenthal MB, Volpp KG, Werner RM. Association between participation in a multipayer medical home
jamainternalmedicine.com
intervention and changes in quality, utilization, and costs of care. JAMA. 2014;311(8):815-825. doi:10.1001/jama.2014.353. 4. Nielsen M, Olayiwola JN, Grundy P, Grumbach K. The patient-centered medical home's impact on cost & quality: an annual update of the evidence, 2012-2013. Patient-Centered Primary Care Collaborative. Published January 2014. www.pcpcc .org/resource/medical-homes-impact -cost-quality. Accessed May 9, 2014. 5. Schwenk TL. The patient-centered medical home: one size does not fit all. JAMA. 2014;311(8): 802-803. doi:10.1001/jama.2014.352.
JAMA Internal Medicine August 2014 Volume 174, Number 8
Copyright 2014 American Medical Association. All rights reserved.
Downloaded From: http://archinte.jamanetwork.com/ by a New York University User on 06/02/2015
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