Big Data and Digital Solutions: Laying the Foundation for Cardiovascular Population ManagementCME
References
-
CDC.gov [Internet]
. Atlanta, GA: Centers for Disease Control and Prevention; c2020. Heart Disease Facts; 2020 Sep 8 [cited 2020 Nov 11]. Available from: https://www.cdc.gov/heartdisease/facts.htm. -
Khera
R, Valero-Elizondo J, Nasir K. Financial Toxicity in Atherosclerotic Cardiovascular Disease in the United States: Current State and Future Directions. J Am Heart Assoc. 2020; 9( 19): e017793. DOI: 10.1161/JAHA.120.017793. -
Joynt
KE. Health policy and cardiovascular medicine: rapid changes, immense opportunities. Circulation. 2015 Mar 24; 131( 12): 1098– 105. doi: 10.1161/CIRCULATIONAHA.114.013606. -
Huang
X Rosenthal MB. Overuse of Cardiovascular Services: Evidence, Causes, and Opportunities for Reform. Circulation. 2015 Jul 21; 132( 3): 205– 14. doi: 10.1161/CIRCULATIONAHA.114.012668. -
Aaron
KJ, Colantonio LD, Deng L, . Cardiovascular Health and Healthcare Utilization and Expenditures Among Medicare Beneficiaries: The Reasons for Geographic And Racial Differences in Stroke (REGARDS) Study. J Am Heart Assoc. 2017 Feb 1; 6( 2): e005106. -
Freeman
AC Sweeney K. Why general practitioners do not implement evidence: qualitative study. BMJ. 2001 Nov 10; 323( 7321): 1100– 2. doi: 10.1136/bmj.323.7321.1100. -
Flores
G, Lee M, Bauchner H, Kastner B. Pediatricians' attitudes, beliefs, and practices regarding clinical practice guidelines: a national survey. Pediatrics. 2000 Mar; 105( 3 Pt 1): 496– 501. DOI: 10.1542/peds.105.3.496. -
Hillman
AL. Managing the physician: rules versus incentives. Health Aff (Mill-wood). 1991; 10( 4): 138– 46. doi: 10.1377/hlthaff.10.4.138. -
Ventola
CL. Challenges in evaluating and standardizing medical devices in health care facilities. P T. 2008 Jun; 33( 6): 348– 359. -
Ghosh
AK. On the challenges of using evidence-based information: the role of clinical uncertainty. J Lab Clin Med. 2004 Aug; 144( 2): 60– 4. doi: 10.1016/j.lab.2004.05.013. -
Budrionis
A Bellika JG. The Learning Healthcare System: Where are we now? A systematic review. J Biomed Inform. 2016 Dec; 64 87– 92. doi: 10.1016/j.jbi.2016.09.018. -
Britto
MT, Fuller SC, Kaplan HC, . Using a network organisational architecture to support the development of Learning Healthcare Systems. BMJ Qual Saf. 2018; 27( 11): 937– 946. doi: 10.1136/bmjqs-2017-007219. -
IBM Big Data Hub [Internet].
Infographics & Animations: The Four V's of Big Data
; 2019 [cited 2020 Nov 11]. Available from: https://www.ibmbigdatahub.com/infographic/four-vs-big-data. -
IBM.com [Internet]
. Armonk, NY: IBM; c2020. Jain A. The 5 V's of big data; 2016 Sep 17 [cited 2020 Nov 11]. Available from: https://www.ibm.com/blogs/watson-health/the-5-vs-of-big-data/. -
McPadden
J, Durant TJS, Bunch DR, . Health Care and Precision Medicine Research: Analysis of a Scalable Data Science Platform. J Med Internet Res. 2019 Apr 9; 21( 4): e13043. DOI: 10.1111/tid.13043. -
Schulz
WL, Durant TJS, Torre CJ, Hsiao AL, Krumholz HM. Agile health care analytics: Enabling real-time disease surveillance with a computational health platform. J Med Internet Res. 2020 May 28; 22( 5): e18707. DOI: 10.2196/18707. -
Dash
S, Shakyawar SK, Sharma M, Kaushik S. Big data in healthcare: management, analysis and future prospects. J Big Data. 2019 Jun; 6( 1): 1– 25. doi: 10.1186/s40537-019-0217-0. -
Pastorino
R, De Vito C, Migliara G, . Benefits and challenges of Big Data in healthcare: an overview of the European initiatives. Eur J Public Health. 2019 Oct 1; 29( Supplement_3): 23– 7. DOI: 10.1093/eurpub/ckz168. -
Hekler
EB, Klasnja P, Chevance G, Golaszewski NM, Lewis D, Sim I. Why we need a small data paradigm. BMC Med. 2019 Jul 17; 17( 1): 133. -
IBM.com [Internet]
. Armonk, NY: IBM; c2020. Data infrastructure for managing Population Health; 2016 Jun [cited 2020 Nov 11]. Available from: https://www.ibm.com/downloads/cas/MOJDOKBW. -
Hulsen
T, Jamuar SS, Moody AR, . From Big Data to Precision Medicine. Front Med (Lausanne). 2019 Mar 1; 6: 34. DOI: 10.3389/fmed.2019.00034. -
Google [Internet]
. Mountain View, CA: Google; c2020. Dean J, Ghemawat S. MapReduce: Simplified Data Processing on Large Clusters; 2004 [cited 2020 Nov 11]. Available from: https://static.googleusercontent.com/media/research.google.com/en//archive/mapreduce-osdi04.pdf -
Wiley [Internet].
Hoboken, NJ: John Wiley & Sons, Inc.; c2020. Fernández A, del Río S, López V, et al. Big Data with Cloud Computing: an insight on the computing environment, MapReduce, and programming frameworks; 2014 Sep 29 [cited 2020 Nov 11]. Available from: https://onlinelibrary.wiley.com/doi/abs/10.1002/widm.1134. DOI: 10.1002/widm.1134. -
Inukollu
VN, Arsi S, Rao Ravuri S. Security Issues Associated with Big Data in Cloud Computing. Int J Netw Secur Its Appl. 2014; 6( 3): 45– 56. DOI: 10.5121/ijnsa.2014.6304 -
Han
A, Isaacson A, Muennig P. The promise of big data for precision population health management in the US. Public Health. 2020 Aug; 185 110– 16. doi: 10.1016/j.puhe.2020.04.040. -
Gamache
R, Kharrazi H, Weiner JP. Public and Population Health Informatics: The Bridging of Big Data to Benefit Communities. Yearb Med Inform. 2018 Aug; 27( 1): 199– 206. doi: 10.1055/s-0038-1667081. -
Wells
TS, Ozminkowski RJ, Hawkins K, Bhattarai GR, Armstrong DG. Leveraging big data in population health management. Big Data Anal. 2016 Jul 1; 1( 1): 1– 14. doi: 10.1186/s41044-016-0001-5. -
Providence Health [Internet].
Renton, WA
: Providence Health & Services; c2020. Population Health Dashboards: Data to drive change at the community level; 2020 Jul [cited 2020 Nov 11]. Available from: https://oregon.providence.org/our-services/c/center-for-outcomes-research-and-education-core/population-health-dashboards/. -
Woolf
SH, Purnell JQ, Simon SM, . Translating Evidence into Population Health Improvement: Strategies and Barriers. Annu Rev Public Health. 2015 Mar 18; 36 463– 82. doi: 10.1146/annurev-publhealth-082214-110901. -
AHRQ.gov [Internet]
. Rockville, MD: Agency for Healthcare Research and Quality; c2020. Cardiovascular Treatment Outcomes Dashboard; 2020 [cited 2020 Nov 11]. Available from: https://www.ahrq.gov/evidencenow/tools/clinic-dashboard.html. -
Minnesota Department of Health [Internet]
. St. Paul, MN: Minnesota Department of Health; c2020. Indicator Dashboard for Monitoring the Picture of Cardiovascular Health in Minnesota; 2018 [cited 2020 Nov 11]. Available from: https://www.health.state.mn.us/diseases/cardiovascular/cardio-dashboard/index.html. -
AHRQ.gov [Internet]
. Rockville, MD: Agency for Healthcare Research and Quality; c2020. Health System Dashboards on Patient & Family Advisor Integration; 2020 [cited 2020 Nov 11]. Available from: https://www.ahrq.gov/evidencenow/tools/pfcc-dashboard.html. -
AHRQ.gov [Internet]
. Rockville, MD: Agency for Healthcare Research and Quality; c2020. Data Visualization Best Practices for Primary Care Quality Improvement (QI) Dashboards; 2017 [cited 2020 Nov 11]. Available from: https://www.ahrq.gov/evidencenow/tools/dashboard-best-practice.html. -
Peterson
PN, Rumsfeld JS, Liang L, . Treatment and risk in heart failure: gaps in evidence or quality? Circ Cardiovasc Qual Outcomes. 2010 May; 3( 3): 309– 15. DOI: 10.1161/CIRCOUTCOMES.109.879478. -
Pavlović
J, Greenland P, Deckers JW, . Assessing gaps in cholesterol treatment guidelines for primary prevention of cardiovascular disease based on available randomised clinical trial evidence: The Rotterdam Study. Eur J Prev Cardiol. 2018 Mar; 25( 4): 420– 31. doi: 10.1177/2047487317743352. -
Maviglia
SM, Teich JM, Fiskio J, Bates DW. Using an electronic medical record to identify opportunities to improve compliance with cholesterol guidelines. J Gen Intern Med. 2001 Aug; 16( 8): 531– 7. doi: 10.1046/j.1525-1497.2001.016008531.x. -
The Community Guide [Internet]
. Atlanta, GA: The Community Guide; c2020. CVD: Clinical Decision-Support Systems; 2013 Apr [cited 2020 Nov 11]. Available from: https://www.thecommunityguide.org/findings/cardiovascular-disease-clinical-decision-support-systems-cdss. -
HopkinsMedicine.org [Internet]
. Baltimore, MD: The Johns Hopkins University; c2020. New Decision Support Tool Places Key Information Front and Center; 2018 Nov 2 [cited 2020 Nov 11]. Available from: https://www.hopkinsmedicine.org/office-of-johns-hopkins-physicians/best-practice-news/new-decision-support-tool-places-key-information-front-and-center. -
Clarke
S, Wilson ML, Terhar M. Using Clinical Decision Support and Dashboard Technology to Improve Heart Team Efficiency and Accuracy in a Trans-catheter Aortic Valve Implantation (TAVI) Program. Stud Health Technol Inform. 2016; 225: 98– 102. PMID: 27332170. -
Groenhof
TKJ, Rittersma ZH, Bots ML, . A computerised decision support system for cardiovascular risk management 'live' in the electronic health record environment: development, validation and implementation-the Utrecht Cardiovascular Cohort Initiative. Neth Heart J. 2019 Sep; 27( 9): 435– 42. DOI: 10.1007/s12471-019-01308-w. -
Leslie
SJ, Hartswood M, Meurig C, . Clinical decision support software for management of chronic heart failure: development and evaluation. Comput Biol Med. 2006 May; 36( 5): 495– 506. doi: 10.1016/j.compbiomed.2005.02.002. -
Khairat
SS, Dukkipati A, Lauria HA, Bice T, Travers D, Carson SS. The Impact of Visualization Dashboards on Quality of Care and Clinician Satisfaction: Integrative Literature Review. JMIR Hum factors. 2018 May 31; 5( 2): e22. DOI: 10.2196/humanfactors.9328. -
HIT Consultant [Internet]
. Atlanta, GA: HIT Consultant Media; c2020. Yale School of Medicine Launches Cloud-Based PHR Platform Hugo; 2016 May 10 [cited 2020 Nov 11]. Available from: https://hitconsultant.net/2016/05/10/yale-school-medicine-launches-cloud-based-phr-platform-hugo/#.X5o6GJpYY2w. -
Vawdrey
DK, Wilcox LG, Collins SA, . A tablet computer application for patients to participate in their hospital care. AMIA Annu Symp Proc. 2011; 2011: 1428– 1435. PMID: 22195206. -
Riso
B, Tupasela A, Vears DF, . Ethical sharing of health data in online platforms - which values should be considered? Life Sci Soc Policy. 2017 Aug 21; 13( 1): 12. DOI: 10.1186/s40504-017-0060-z. -
Huang
W, Li J, Alem L. Towards Preventative Healthcare: A Review of Wearable and Mobile Applications. Stud Health Technol Inform. 2018; 251 11– 14. doi: 10.3233/978-1-61499-880-8-11. -
Pliakos
I, Kefaliakos A, Kalokerinou A, Al-Fantel K, Mechili A, Diomidous M. m-Health: Integration of Mobile Phones and Applications for a Better Healthcare System. Stud Health Technol Inform. 2014 Jul; 202: 315. -
Ricciardi
W, Pita Barros P, Bourek A, . How to govern the digital transformation of health services. Eur J Public Health. 2019 Oct 1; 29( Supplement_3): 7– 12. DOI: 10.1093/eurpub/ckz165. -
McCoy
AB, Thomas EJ, Krousel-Wood M, Sittig DF. Clinical decision support alert appropriateness: A review and proposal for improvement. Ochsner J. Summer 2014; 14( 2): 195– 202. PMID: 24940129. -
Anderson
JL, Heidenreich PA, Barnett PG, . ACC/AHA statement on cost/value methodology in clinical practice guidelines and performance measures: A report of the American college of cardiology/American heart association task force on performance measures and task force on practice guidelines. Circulation. 2014 Jun 3; 129( 22): 2329– 45. doi: 10.1161/CIR.0000000000000042. -
Ghazisaeidi
M, Safdari R, Torabi M, Mirzaee M, Farzi J, Goodini A. Development of Performance Dashboards in Healthcare Sector: Key Practical Issues. Acta Inform Medica. 2015 Oct; 23( 5): 317– 21. doi: 10.5455/aim.2015.23.317-321. -
Ferver
K, Burton B, Jesilow P. The Use of Claims Data in Healthcare Research. Open Public Health J. 2009; 2: 11– 24. -
Lee
CH Yoon HJ. Medical big data: promise and challenges. Kidney Res Clin Pract. 2017 Mar; 36( 1): 3– 11. doi: 10.23876/j.krcp.2017.36.1.3. -
Khairat
S, Marc D, Crosby W, Al Sanousi A. Reasons For Physicians Not Adopting Clinical Decision Support Systems: Critical Analysis. JMIR Med Inform. 2018 Apr 18; 6( c 2): e24. DOI: 10.2196/medinform.8912. -
Ash
JS, Sittig DF, Campbell EM, Guappone KP, Dykstra RH. Some unintended consequences of clinical decision support systems. AMIA Annu Symp Proc. 2007 Oct 11; 2007: 26– 30. PMID: 18693791. -
NursingCenter.com [Internet]
. South Holland, Netherlands: Wolters Kluwer; c2020. Castillo RS, Kelemen A. Considerations for a Successful Clinical Decision Support System; 2020 [cited 2020 Nov 11]. Available from: https://www.nursingcenter.com/lnc/ce_articleprint?an=00024665-201307000-00003. -
Sutton
RT, Pincock D, Baumgart DC, Sadowski DC, Fedorak RN, Kroeker KI. An overview of clinical decision support systems: benefits, risks, and strategies for success. npj Digit Med. 2020 Feb 6; 3: 17. DOI: 10.1038/s41746-020-0221-y. -
Sujansky
W. Heterogeneous database integration in biomedicine. J Biomed Inform. 2001 Aug; 34( 4): 285– 98. doi: 10.1006/jbin.2001.1024.
DOI: https://doi.org/10.14797/mdcj-16-4-272 | Journal eISSN: 1947-6108
Language: English
Page range: 272 - 282
Published on: Oct 1, 2020
Published by: Houston Methodist DeBakey Heart & Vascular Center
In partnership with: Paradigm Publishing Services
Keywords:
© 2020 Khurram Nasir, Zulqarnain Javed, Safi U. Khan, Stephen L. Jones, Julia Andrieni, published by Houston Methodist DeBakey Heart & Vascular Center
This work is licensed under the Creative Commons Attribution-NonCommercial 4.0 License.