Abstract
Medical knowledge is increasing at an exponential rate. At the same time, unexplained variations in practice and patient outcomes and unacceptable rates of medical errors and inefficiencies in health care delivery have emerged. Our Institute for Health Care Delivery Science (I-HDS) began in 2014 as a novel platform to conduct multidisciplinary healthcare delivery research. We followed ten strategies to develop a successful institute with excellence in methodology and strong understanding of the value of team science. Our work was organized around five hubs: 1) Quality/Process Improvement and Systematic Review, 2) Comparative Effectiveness Research, Pragmatic Clinical Trials, and Predictive Analytics, 3) Health Economics and Decision Modeling, 4) Qualitative, Survey, and Mixed Methods, and 5) Training and Mentoring. In the first 5 years of the I-HDS, we have identified opportunities for change in clinical practice through research using our health system’s electronic health record (EHR) data, and designed programs to educate clinicians in the value of research to improve patient care and recognize efficiencies in processes. Testing the value of several model interventions has guided prioritization of evidence-based quality improvements. Some of the changes in practice have already been embedded in the EHR workflow successfully. Development and sustainability of the I-HDS has been fostered by a mix of internal and external funding, including philanthropic foundations. Challenges remain due to the highly competitive funding environment and changes needed to adapt the EHR to healthcare delivery research. Further stakeholder engagement and culture change working with hospital leadership and I-HDS core and affiliate members continues.
Similar content being viewed by others
References
Anderson JG, Abrahamson K (2017) Your health care may kill you: medical errors. Stud Health Technol Inform 234:13–17. https://doi.org/10.3233/978-1-61499-742-9-13
Kyle M, Williams H (2017) Is American health care uniquely inefficient? Evidence from prescription drugs. Am Econ Rev 107(5):486–490. https://doi.org/10.1257/aer.p20171086
Riley WJ (2012) Health disparities: gaps in access, quality and affordability of medical care. Trans Am Clin Climatol Assoc 123:167–172
Abraham E, Blanco c, Lee CC, Christian JB, Kass N, Larson EB, Mazumdar M et al. (2016) Generating knowledge from best care: advancing the continuously learning health system. NAM Perspectives. Discussion Paper, National Academy of Medicine, (Washington, DC):1-23. https://doi.org/10.31478/201609b
Guise JM, Savitz LA, Friedman CP (2018) Mind the gap: putting evidence into practice in the era of learning health systems. J Gen Intern Med 33(12):2237–2239. https://doi.org/10.1007/s11606-018-4633-1
Doyle J, Abraham S, Feeney L, Reimer S, Finkelstein A (2019) Clinical decision support for high-cost imaging: a randomized clinical trial. PLoS One 14(3):1–13. https://doi.org/10.1371/journal.pone.0213373
Poeran J, Mao LJ, Zubizarreta N, Mazumdar M, Darrow B, Genes N, Kannry J, Francaviglia P, Kennelly PD, Whitehorn J, Kilroy G, Garcia D, Mendelson DS (2019) Effect of clinical decision support on appropriateness of advanced imaging use among physicians-in-training. AJR Am J Roentgenol 212(4):859–866. https://doi.org/10.2214/AJR.18.19931
Mallery C, Ganachari D, Fernandez J, Smeeding L, Robinson S, Moon M, Lavallee D, Siegel J. (2012) Innovative methods in stakeholder engagement: an environmental scan. http://www.effectivehealthcare.ahrq.gov/index.cfm/tools-and-resources/how-to-get-involved-in-the-effective-health-care-program/. Accessed 4/30/2020
Perkins SM, Bacchetti P, Davey CS, Lindsell CJ, Mazumdar M, Oster RA, Peduzzi PN, Rocke DM, Rudser KD, Kim M (2016) Best practices for biostatistical consultation and collaboration in academic health centers. Am Stat 70(2):187–194. https://doi.org/10.1080/00031305.2015.1077727
Mathews KS, Durst MS, Vargas-Torres C, Olson AD, Mazumdar M, Richardson LD (2018) Effect of emergency department and ICU occupancy on admission decisions and outcomes for critically ill patients. Crit Care Med 46(5):720–727. https://doi.org/10.1097/CCM.0000000000002993
Hiensch R, Poeran J, Saunders-Hao P, Adams V, Powell CA, Glasser A, Mazumdar M, Patel G (2017) Impact of an electronic Sepsis initiative on antibiotic use and health care facility-onset clostridium Difficile infection rates. Am J Infect Control 45(10):1091–1100. https://doi.org/10.1016/j.ajic.2017.04.005
Holzer H, Reisman A, Marqueen KE, Thomas AT, Yang A, Dunn AS, Jia R, Poeran J, Cho HJ (2019) "lipase only, please": reducing unnecessary amylase testing. Jt Comm J Qual Patient Saf 45(11):742–749. https://doi.org/10.1016/j.jcjq.2019.08.003
Shinwa M, Bossert A, Chen I, Cushing A, Dunn AS, Poeran J, Weinstein S, Cho HJ (2019) "THINK" before you order: multidisciplinary initiative to reduce unnecessary lab testing. J Healthc Qual 41(3):165–171. https://doi.org/10.1097/JHQ.0000000000000157
Cho HJ, Khalil S, Poeran J, Mazumdar M, Bravo N, Wallach F, Markoff B, Lee N, Dunn AS (2017) "lose the tube": a choosing wisely initiative to reduce catheter-associated urinary tract infections in hospitalist-led inpatient units. Am J Infect Control 45(3):333–335. https://doi.org/10.1016/j.ajic.2016.10.023
Tsega S, O'Connor M, Poeran J, Iberti C, Cho HJ (2018) Bedside assessment of the necessity of daily lab testing for patients nearing discharge. J Hosp Med 13(1):38–40. https://doi.org/10.12788/jhm.2869
Institute for Health Care Delivery Science, Icahn School of Medicine at Mount Sinai, the Mount Sinai Health System. http://icahn.mssm.edu/research/institute-health-care-delivery/. Accessed 4/30/2020
Blachman NL, Leipzig RM, Mazumdar M, Poeran J (2017) High-risk medications in hospitalized elderly adults: are we making it easy to do the wrong thing? J Am Geriatr Soc 65(3):603–607. https://doi.org/10.1111/jgs.14703
Howard DR, Kazemi N, Rubenstein WJ, Hartwell MJ, Poeran J, Chang AL, Podolnick JD, Parsons BO, Galatz LM, Flatow EL (2017) Cost-benefit analysis of routine pathology examination in primary shoulder Arthroplasty. J Shoulder Elb Surg 26(4):674–678. https://doi.org/10.1016/j.jse.2016.09.028
Poeran J, Babby J, Rasul R, Mazumdar M, Memtsoudis SG, Reich DL (2015) Tales from the wild west of US drug pricing: the case of intravenous acetaminophen. Reg Anesth Pain Med 40(3):284–286. https://doi.org/10.1097/AAP.0000000000000231
Duke Clinical Research Institute, Duke University Health System. 2018. Pragmatic Clinical Trials: Taking Novel Approaches to Answer Important Questions More Efficiently. https://dcri.org/insights/pragmatic-clinical-trials/. Accessed 4/30/2020
Brown CA, Lilford RJ (2006) The stepped wedge trial design: a systematic review. BMC Med Res Methodol 6:54. https://doi.org/10.1186/1471-2288-6-54
Galsky MD, Diefenbach M, Mohamed N, Baker C, Pokhriya S, Rogers J, Atreja A, Hu L, Tsao CK, Sfakianos J, Mehrazin R, Waingankar N, Oh WK, Mazumdar M, Ferket BS (2017) Web-based tool to facilitate shared decision making with regard to Neoadjuvant chemotherapy use in muscle-invasive bladder Cancer. JCO Clin Cancer Inform 1:1–12. https://doi.org/10.1200/CCI.17.00116
Timsina P, Kia A, Cheng FY, Parchure P, Otto W, Freeman R, Levin M. Real-time machine learning pipeline: a clinical early warning score (EWS) use-case. Paper presented at the HiMMS19 Champions of Health Unite. Global Conference & Exhibition., Orlando, FL, February 12, 2019
Zhong X, Lin JY, Li L, Barrett AM, Friedman J, Poeran J, Mazumdar M Derivation and validation of a delirium comorbidity index. In Press. Health Serv Res
Mazumdar M, Lin JJ, Zhang W, Li L, Liu M, Dharmarajan K, Sanderson M, Isola L, Hu L (2020) Comparison of statistical and machine learning models for healthcare cost data: a simulation study motivated by oncology care model (OCM) data. BMC Health Serv Res 20(1):350. https://doi.org/10.1186/s12913-020-05148-y
Kia A, Timsina P, Joshi HN, Klang E, Gupta RR, Freeman RM, Reich DL, Tomlinson MS, Dudley JT, Kohli-Seth R, Mazumdar M, Levin MA (2020) MEWS++: enhancing the prediction of clinical deterioration in admitted patients through a machine learning model. J Clin Med 9(2). https://doi.org/10.3390/jcm9020343
Timsina P, Cheng F, Joshi H, Kersch I, Wilson S, Colgan C, Freeman R, Mazumdar M, Levin M, Kia A (2020) MUST-Plus: A machine learning classifier that improves malnutrition screening in acute care facilities. J Am Coll Nutr. https://doi.org/10.1080/07315724.2020.1774821
Parchure P, Joshi H, Dharmarajan K, Freeman R, Reich DL, Mazumdar M, Timsina P, Kia A (2020) Development and validation of a machine learning-based prediction model for near-term in-hospital mortality among patients with COVID-19. BMJ Support Palliat Care. https://doi.org/10.1136/bmjspcare-2020-002602
Phelps, C. E. 2017. Health economics Boston: Addison Wesley
Capan M, Khojandi A, Denton BT, Williams KD, Ayer T, Chhatwal J, Kurt M, Lobo JM, Roberts MS, Zaric G, Zhang S, Schwartz JS (2017) From data to improved decisions: operations research in healthcare delivery. Med Decis Mak 37(8):849–859. https://doi.org/10.1177/0272989x17705636
Ferket BS, Feldman Z, Zhou J, Oei EH, Bierma-Zeinstra SM, Mazumdar M (2017) Impact of Total knee replacement practice: cost effectiveness analysis of data from the osteoarthritis initiative. BMJ 356:j1131. https://doi.org/10.1136/bmj.j1131
Giampaolo G, Ferket BS, D’Alessandro DA, Shi W, Horvath KA, Rosen A, Welsh S, Bagiella E, Neill AE, Williams DL (2016) Diabetes and the Association of Postoperative Hyperglycemia with clinical and economic outcomes in cardiac surgery. J Diabetes care 39(3):408–417. https://doi.org/10.2337/dc15-1817
Ferket BS, van Kempen BJ, Hunink MG, Agarwal I, Kavousi M, Franco OH, Steyerberg EW, Max W, Fleischmann KE (2014) Predictive value of updating Framingham risk scores with novel risk markers in the U.S. general population. PLoS One 9 (2). https://doi.org/10.1371/journal.pone.0088312
Shrime MG, Ferket BS, Scott DJ, Lee J, Barragan-Bradford D, Pollard T, Arabi YM, al-Dorzi HM, Baron RM, Hunink MGM, Celi LA, Lai PS (2016) Time-limited trials of intensive Care for Critically ill Patients with Cancer: how long is long enough? JAMA Oncol 2(1):76–83. https://doi.org/10.1001/jamaoncol.2015.3336
van Kempen BJ, Ferket BS, Steyerberg EW, Max W, Hunink MG, Fleischmann KE (2016) Comparing the cost-effectiveness of four novel risk markers for screening asymptomatic individuals to prevent cardiovascular disease (CVD) in the US population. Int J Cardiol 203:422–431. https://doi.org/10.1016/j.ijcard.2015.10.171
Xia FD, Ferket BS, Huang V, Stern RS, Wu PA (2019) Local radiation and phototherapy are the Most cost-effective treatments for stage IA mycosis Fungoides: a comparative decision analysis model in the United States. J Am Acad Dermatol 80(2):485–492. https://doi.org/10.1016/j.jaad.2018.07.040
Wasserman I, Poeran J, Zubizarreta N, Babby J, Serban S, Goldberg AT, Greenstein AJ, Memtsoudis SG, Mazumdar M, Leibowitz AB (2018) Impact of intravenous acetaminophen on perioperative opioid utilization and outcomes in open colectomies: a claims database analysis. Anesthesiology 129(1):77–88. https://doi.org/10.1097/ALN.0000000000002227
The Center for Qualitative Studies in Health Medicine. Johns Hopkins Bloomberg School of Public Health. 2018. https://jhsph.edu/departments/health-behavior-and-society/research-and-centers/center-for-qualitative-studies-in-health-and-medicine/index.html. Accessed 4/30/2020
Gorbenko KO, Fraze T, Lewis VA (2016) Redesigning care delivery with patient support personnel: learning from accountable care organizations. Int J Care Coord 19(3–4):73–83. https://doi.org/10.1177/2053434516676080
Schwartz RM, Gorbenko K, Kerath SM, Flores R, Ross S, Taylor TN, Taioli E, Henschke C (2018) Thoracic surgeon and patient focus groups on decision-making in early-stage lung Cancer surgery. Future Oncol 14(2):151–163. https://doi.org/10.2217/fon-2017-0254
Patients Like Me. https://www.patentslikeme.com/. Accessed 4/30/2020
Brooks JV, Gorbenko K, Bosk C (2017) Interactional resources for quality improvement: learning from participants through a qualitative study. Qual Manag Health Care 26(2):55–62. https://doi.org/10.1097/QMH.0000000000000128
Mazumdar, M. Supporting reproducibility in a learning health system: surveying clinical data quality-related practices, assessing awareness and perspectives, and gauging training needs. In National Academy of Sciences Arthur M. Sackler Colloquium on Reproducibility of Research: Issues and Proposed Remedies. Washington, D.C.
Khairat S, Whitt S, Craven CK, Pak Y, Shyu CR, Gong Y (2019) Investigating the impact of intensive care unit interruptions on patient safety events and electronic health records use: an observational study. J Patient Saf. https://doi.org/10.1097/PTS.0000000000000603
Gorbenko K, Mendelev E, Keefer L (2019) Can multidisciplinary team meetings reduce burnout? J Eval Clin Pract 26:1–3. https://doi.org/10.1111/jep.13234
Marqueen KE, Waingankar N, Sfakianos JP, Mehrazin R, Niglio SA, Audenet F, Jia R, Mazumdar M, Ferket BS, Galsky MD (2018) Early mortality in patients with muscle-invasive bladder Cancer undergoing cystectomy in the United States. JNCI Cancer Spectr 2(4):1–8. https://doi.org/10.1093/jncics/pky075
Budde J, Agarwal P, Mazumdar M, Yeo J, Braman SS (2018) Can an emergency department observation unit reduce hospital admissions for COPD exacerbation? Lung 196(3):267–270. https://doi.org/10.1007/s00408-018-0102-1
Ferket BS, Ailawadi G, Gelijns AC, Acker M, Hohmann SF, Chang HL, Bouchard D et al (2018) Cost-effectiveness of mitral valve repair versus replacement for severe ischemic mitral regurgitation: a randomized clinical trial from the cardiothoracic surgical trials network. Circ Cardiovasc Qual Outcomes 11(11):1–26. https://doi.org/10.1161/CIRCOUTCOMES.117.004466
Mazumdar M, Messinger S, Finkelstein DM, Goldberg JD, Lindsell CJ, Morton SC, Pollock BH, Rahbar MH, Welty LJ, Parker RA, Biostatistics, Epidemiology, and Research Design (BERD) Key Function Committee of the Clinical and Translational Science Awards (CTSA) Consortium (2015) Evaluating academic scientists collaborating in team-based research: a proposed framework. Acad Med 90(10):1302–1308. https://doi.org/10.1097/ACM.0000000000000759
Gourevitch MN, Thorpe LE (2019) Advancing population health at academic medical centers: a case study and framework for an emerging field. Acad Med 94(6):813–818. https://doi.org/10.1097/acm.0000000000002561
Pronovost PJ, Holzmueller CG, Molello NE, Paine L, Winner L, Marsteller JA, Berenholtz SM, Aboumatar HJ, Demski R, Armstrong CM (2015) The Armstrong institute: an academic Institute for Patient Safety and Quality Improvement, research, training, and practice. Acad Med 90(10):1331–1339. https://doi.org/10.1097/acm.0000000000000760
Costlow MR, Landsittel DP, James AE 3rd, Kahn JM, Morton SC (2015) Model for a patient-centered comparative effectiveness research center. Clin Transl Sci 8(2):155–159. https://doi.org/10.1111/cts.12257
Rask KJ, Brigham KL, Johns MM (2011) Integrating comparative effectiveness research programs into predictive health: a unique role for academic health centers. Acad Med 86(6):718–723. https://doi.org/10.1097/ACM.0b013e318217ea6c
Rosenblum D (2012) Access to Core facilities and other research resources provided by the clinical and translational science awards. Clin Transl Sci 5(1):78–82. https://doi.org/10.1111/j.1752-8062.2011.00385.x
Mazumdar M, Moshier EL, Ozbek U, Parsons R (2018) Ten essential practices for developing or reforming a biostatistics Core for a NCI designated Cancer center. JNCI Cancer Spectr 2(1):1–6. https://doi.org/10.1093/jncics/pky010
Acknowledgements
We acknowledge Jeremy Boal, MD, President of Mount Sinai Downtown and Executive Vice President and Chief Clinical Officer of the Mount Sinai Health System. He was the Associate Director of the Institute for its first three years and was instrumental in its initiation and growth. We also recognize the I-HDS Internal Advisory Board (IAB), which comprises Dean Dennis S. Charney and the Presidents, Chief Medical Officers, and Chief Nursing Officers from the Mount Sinai Health System’s seven hospitals, and the chairs/vice chairs/directors of all collaborating departments and Institutes. We thank our External Advisory Board: Peter R. Orszag, PhD, Vice Chair, Corporate and Investment Banking, Citigroup, Inc.; Patricia Wang, JD, Chief Executive Officer, Healthfirst, Inc.; Isaac Kohane, MD, PhD, Co-Director, Center for Bioinformatics, Henderson Professor of Pediatrics and Health Sciences and Technology, Harvard Medical School; and Gregory L. Burke, MD, MSc, Senior Associate Dean for Research and Chief Scientific Officer, Wake Forest Baptist Health. We acknowledge all members of the I-HDS: Umut Ozbek, PhD, Denise Williams, BS, Jiayi Ji, MS, Lihua Li, MS, PhD, Erin Moshier, MS, Liangyuan Hu, PhD, Rachel Jia, PhD, Jung-Yi (Joyce) Lin, MS, Meng Ru, MS, Xiaoyu Song, PhD, Hsin-Hui (Vivien) Huang, MS, PhD, MD, Himanshu Joshi, MBBS, PhD, and Serene Zhan, MS. Finally, we thank our collaborating clinical departments, centers, and institutes for their support.
This work was supported in part by the National Cancer Institute (P30 CA196521);
The National Heart, Lung, and Blood Institute (U01 HL088942); and the National Institute of Aging (P30 AG028741 and P30 AG028741- 09S1).
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Mazumdar, M., Poeran, J.V., Ferket, B.S. et al. Developing an Institute for Health Care Delivery Science: successes, challenges, and solutions in the first five years. Health Care Manag Sci 24, 234–243 (2021). https://doi.org/10.1007/s10729-020-09521-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10729-020-09521-5