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| Name | Class |
|---|---|
| West Virginia University | OTHER |
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The need for new models of integrated care that can improve the efficiency of healthcare and reduce the costs are key priorities for health systems across the United States. Treatment costs for patients with at least one chronic medical or cardiovascular condition make up over 4-trillion dollars in spending on healthcare, with estimations of a population prevalence of 100-million affected individuals within the next decade. Therefore, the management of chronic conditions requires innovative and new implementation methods that improve outcomes, reduce costs, and increase healthcare efficiencies. Digital health, the use of mobile computing and communication technologies as an integral new models of care is seen as one potential solution. Despite the potential applications, there is limited data to support that new technologies improve healthcare outcomes. To do so requires; 1) robust methods to determine the impact of new technologies on healthcare outcomes and costs; and 2) evaluative mechanisms for how new devices are integrated into patient care. In this regard, the proposed clinical trial aims to advance the investigator's knowledge and to demonstrate the pragmatic utilization of new technologies within a learning healthcare system providing services to high-risk patient populations.
Objective #1: Determine the effectiveness of handheld imaging and digital health devices on long term health and patient-reported outcomes through pragmatic and randomized clinical trial designs.
Objective #2: Assess the impact of digital health devices and remote patient monitoring (RPM) on measures of healthcare efficiency. Measures of healthcare efficiency directly related to digital health technologies and RPM include: identify which interventions can improve care; define the variations in care and; demonstrate within which patient populations digital health technologies are most effective.
Objective #3: Apply integration methods for handheld imaging and digital health devices used for clinical decisions.
Achieving integration and interoperability-the ability of different information technology systems and software applications to communicate and exchange data with each other-requires identification for precisely how new innovations merge into systems of care and are applied to various practice settings.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Technology-Enabled Visitations | Experimental | Technology-enabled visitations with digital health will include the following devices used at the time of a patient-physician encounter. These findings will be available to the treating physician at the time the visitation and to be used for clinical decisions. |
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| Standard-Care Visitations | No Intervention | Standard-care is defined as the range of services available during usual patient care. Handheld Imaging and digital health screening will be performed in the control group after the patient-physician encounter. As such, patients and physicians will be blinded to the diagnostic findings unless an abnormal finding is detected that requires physician review and triage for further care. |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Digital Health Device Diagnostics | Diagnostic Test | Technology-enabled visitations with digital health will include the following devices used at the time of a patient-physician encounter. These findings will be available to the treating physician at the time the visitation and to be used for clinical decisions.
|
| Measure | Description | Time Frame |
|---|---|---|
| Health Economic Outcomes | Economic difference between the total costs of care between randomized arms including; clinic visitations, hospitalizations, emergency room visitations, and diagnostic testing. Collected as cumulative diagnosis-related group (DRG) and current procedural terminology (CPT) amounts in United States Dollars | 180 days |
| Measure | Description | Time Frame |
|---|---|---|
| Mobile Cardiac Telemetry | Number of referrals for mobile cardiac telemetry monitoring between randomized arms | 180 days |
| Health Economic Outcomes | Economic difference between the total costs of care between randomized arms including; clinic visitations, hospitalizations, emergency room visitations, and diagnostic testing. Collected as cumulative diagnosis-related group (DRG) and current procedural terminology (CPT) amounts in United States Dollars |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Partho Sengupta, MD | West Virginia University Heart and Vascular Institute | Principal Investigator |
| Sanjeev Bhavnani, MD | Scripps Clinic | Study Director |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| West Virgina University | Morgantown | West Virginia | 26506 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 23439071 | Background | Singh S, Bansal M, Maheshwari P, Adams D, Sengupta SP, Price R, Dantin L, Smith M, Kasliwal RR, Pellikka PA, Thomas JD, Narula J, Sengupta PP; ASE-REWARD Study Investigators. American Society of Echocardiography: Remote Echocardiography with Web-Based Assessments for Referrals at a Distance (ASE-REWARD) Study. J Am Soc Echocardiogr. 2013 Mar;26(3):221-33. doi: 10.1016/j.echo.2012.12.012. | |
| 28883036 |
| Label | URL |
|---|---|
| Related Info | View source |
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| ID | Term |
|---|---|
| D002318 | Cardiovascular Diseases |
| D006973 | Hypertension |
| D006333 | Heart Failure |
| D001281 | Atrial Fibrillation |
| D024821 | Metabolic Syndrome |
| D030342 | Genetic Diseases, Inborn |
| ID | Term |
|---|---|
| D014652 | Vascular Diseases |
| D006331 | Heart Diseases |
| D001145 | Arrhythmias, Cardiac |
| D010335 | Pathologic Processes |
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Pragmatic, multisite, cluster randomized trial comparing point of care and remote patient monitoring with digital health devices and handheld imaging to standard-care
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Treating physicians and clinical practitioners will not be concealed to the randomized allocation of individual clinics or the patients that are seen in these encounters. Physicians in the interventional group will participate in conducting technology-enabled visitations before and after a patient encounter and therefore are not blinded to the assessment. For the standard care group handheld imaging and remote patient monitoring will not be performed after the patient-physician encounter. Principal investigators, outcome adjudicators, and statisticians are blinded to randomization, device findings, and treatment decisions.
|
| 30 days |
| Patient-Reported Outcome Measures | Veterans Research and Development Corporation-12 Patient Reported Outcomes (mean total score 50 +/- 10) where higher values are associated with greater mental and physical debility | 30 days |
| Patient-Reported Outcome Measures | Veterans Research and Development Corporation-12 Patient Reported Outcomes (mean total score 50 +/- 10) where higher values are associated with greater mental and physical debility | 180 days |
| Patient-Reported Experience Measures | Agency for Healthcare Research and Quality Consumer Assessment of Healthcare Providers and Systems (average scores and difference between randomized arms) where higher scores are associated with greater patient satisfaction and patient experience | 30 days |
| Patient-Reported Experience Measures | Agency for Healthcare Research and Quality Consumer Assessment of Healthcare Providers and Systems (average scores and difference between randomized arms) where higher scores are associated with greater patient satisfaction and patient experience | 180 days |
| Diagnostic Imaging | Number of referrals for diagnostic imaging with transthoracic echocardiography between randomized arms | 180 days |
| Heart Failure | Incidence of heart failure diagnosed between randomized arms | 180 days |
| Atrial Fibrillation | Incidence of atrial fibrillation diagnosed between randomized arms | 180 days |
| Emergency Department Visitations | Percentage of patients presenting to the emergency department for a cardiac condition (example; myocardial infarction, heart failure, atrial fibrillation, and stroke) between randomized arms | 180 days |
| Hospitalization | Percentage of patients hospitalized for a cardiac condition (example; myocardial infarction, heart failure, atrial fibrillation, and stroke) between randomized arms | 180 days |
| Clinic Visitations | Percentage of patients presenting for a clinical visitation for a cardiac condition (example; myocardial infarction, heart failure, atrial fibrillation, and stroke) between randomized arms | 180 days |
| Medical Therapy | Percentage of patients initiating medical therapy for a cardiac condition including: heart failure, coronary artery disease, atrial fibrillation, and/or hypertension between randomized arms | 180 days |
| Background |
| Bansal M, Sengupta PP. How to interpret an echocardiography report (for the non-imager)? Heart. 2017 Nov;103(21):1733-1744. doi: 10.1136/heartjnl-2016-309443. Epub 2017 Sep 7. No abstract available. |
| 26304560 | Background | Bansal M, Sengupta PP. Setting global standards in adult echocardiography: Where are we? Indian Heart J. 2015 Jul-Aug;67(4):298-301. doi: 10.1016/j.ihj.2015.07.020. Epub 2015 Aug 21. No abstract available. |
| 29169478 | Background | Bhavnani SP, Parakh K, Atreja A, Druz R, Graham GN, Hayek SS, Krumholz HM, Maddox TM, Majmudar MD, Rumsfeld JS, Shah BR. 2017 Roadmap for Innovation-ACC Health Policy Statement on Healthcare Transformation in the Era of Digital Health, Big Data, and Precision Health: A Report of the American College of Cardiology Task Force on Health Policy Statements and Systems of Care. J Am Coll Cardiol. 2017 Nov 28;70(21):2696-2718. doi: 10.1016/j.jacc.2017.10.018. No abstract available. |
| 29180495 | Background | Chamsi-Pasha MA, Sengupta PP, Zoghbi WA. Handheld Echocardiography: Current State and Future Perspectives. Circulation. 2017 Nov 28;136(22):2178-2188. doi: 10.1161/CIRCULATIONAHA.117.026622. |
| 27749962 | Background | Levine DM, Linder JA, Landon BE. The Quality of Outpatient Care Delivered to Adults in the United States, 2002 to 2013. JAMA Intern Med. 2016 Dec 1;176(12):1778-1790. doi: 10.1001/jamainternmed.2016.6217. |
| 28254835 | Background | Maddox TM, Albert NM, Borden WB, Curtis LH, Ferguson TB Jr, Kao DP, Marcus GM, Peterson ED, Redberg R, Rumsfeld JS, Shah ND, Tcheng JE; American Heart Association Council on Quality of Care and Outcomes Research; Council on Cardiovascular Disease in the Young; Council on Clinical Cardiology; Council on Functional Genomics and Translational Biology; and Stroke Council. The Learning Healthcare System and Cardiovascular Care: A Scientific Statement From the American Heart Association. Circulation. 2017 Apr 4;135(14):e826-e857. doi: 10.1161/CIR.0000000000000480. Epub 2017 Mar 2. |
| 25956159 | Background | Loudon K, Treweek S, Sullivan F, Donnan P, Thorpe KE, Zwarenstein M. The PRECIS-2 tool: designing trials that are fit for purpose. BMJ. 2015 May 8;350:h2147. doi: 10.1136/bmj.h2147. No abstract available. |
| 24950690 | Background | Henderson C, Knapp M, Fernandez JL, Beecham J, Hirani SP, Beynon M, Cartwright M, Rixon L, Doll H, Bower P, Steventon A, Rogers A, Fitzpatrick R, Barlow J, Bardsley M, Newman SP. Cost-effectiveness of telecare for people with social care needs: the Whole Systems Demonstrator cluster randomised trial. Age Ageing. 2014 Nov;43(6):794-800. doi: 10.1093/ageing/afu067. Epub 2014 Jun 20. |
| 26810587 | Background | Delaney SK, Hultner ML, Jacob HJ, Ledbetter DH, McCarthy JJ, Ball M, Beckman KB, Belmont JW, Bloss CS, Christman MF, Cosgrove A, Damiani SA, Danis T, Delledonne M, Dougherty MJ, Dudley JT, Faucett WA, Friedman JR, Haase DH, Hays TS, Heilsberg S, Huber J, Kaminsky L, Ledbetter N, Lee WH, Levin E, Libiger O, Linderman M, Love RL, Magnus DC, Martland A, McClure SL, Megill SE, Messier H, Nussbaum RL, Palaniappan L, Patay BA, Popovich BW, Quackenbush J, Savant MJ, Su MM, Terry SF, Tucker S, Wong WT, Green RC. Toward clinical genomics in everyday medicine: perspectives and recommendations. Expert Rev Mol Diagn. 2016;16(5):521-32. doi: 10.1586/14737159.2016.1146593. Epub 2016 Feb 24. |
| 28914267 | Background | Orlando LA, Sperber NR, Voils C, Nichols M, Myers RA, Wu RR, Rakhra-Burris T, Levy KD, Levy M, Pollin TI, Guan Y, Horowitz CR, Ramos M, Kimmel SE, McDonough CW, Madden EB, Damschroder LJ. Developing a common framework for evaluating the implementation of genomic medicine interventions in clinical care: the IGNITE Network's Common Measures Working Group. Genet Med. 2018 Jun;20(6):655-663. doi: 10.1038/gim.2017.144. Epub 2017 Sep 14. |
| 24951446 | Background | Via G, Hussain A, Wells M, Reardon R, ElBarbary M, Noble VE, Tsung JW, Neskovic AN, Price S, Oren-Grinberg A, Liteplo A, Cordioli R, Naqvi N, Rola P, Poelaert J, Gulic TG, Sloth E, Labovitz A, Kimura B, Breitkreutz R, Masani N, Bowra J, Talmor D, Guarracino F, Goudie A, Xiaoting W, Chawla R, Galderisi M, Blaivas M, Petrovic T, Storti E, Neri L, Melniker L; International Liaison Committee on Focused Cardiac UltraSound (ILC-FoCUS); International Conference on Focused Cardiac UltraSound (IC-FoCUS). International evidence-based recommendations for focused cardiac ultrasound. J Am Soc Echocardiogr. 2014 Jul;27(7):683.e1-683.e33. doi: 10.1016/j.echo.2014.05.001. |
| 23711341 | Background | Spencer KT, Kimura BJ, Korcarz CE, Pellikka PA, Rahko PS, Siegel RJ. Focused cardiac ultrasound: recommendations from the American Society of Echocardiography. J Am Soc Echocardiogr. 2013 Jun;26(6):567-81. doi: 10.1016/j.echo.2013.04.001. No abstract available. |
| 28917688 | Result | Bhavnani SP, Sola S, Adams D, Venkateshvaran A, Dash PK, Sengupta PP; ASEF-VALUES Investigators. A Randomized Trial of Pocket-Echocardiography Integrated Mobile Health Device Assessments in Modern Structural Heart Disease Clinics. JACC Cardiovasc Imaging. 2018 Apr;11(4):546-557. doi: 10.1016/j.jcmg.2017.06.019. Epub 2017 Oct 5. |
| 26873093 | Result | Bhavnani SP, Narula J, Sengupta PP. Mobile technology and the digitization of healthcare. Eur Heart J. 2016 May 7;37(18):1428-38. doi: 10.1093/eurheartj/ehv770. Epub 2016 Feb 11. |
| 25306222 | Result | Bansal M, Singh S, Maheshwari P, Adams D, McCulloch ML, Dada T, Sengupta SP, Kasliwal RR, Pellikka PA, Sengupta PP; VISION-in-Tele-Echo Study Investigators. Value of interactive scanning for improving the outcome of new-learners in transcontinental tele-echocardiography (VISION-in-Tele-Echo) study. J Am Soc Echocardiogr. 2015 Jan;28(1):75-87. doi: 10.1016/j.echo.2014.09.001. Epub 2014 Oct 8. |
| 24687081 | Result | Lowres N, Neubeck L, Salkeld G, Krass I, McLachlan AJ, Redfern J, Bennett AA, Briffa T, Bauman A, Martinez C, Wallenhorst C, Lau JK, Brieger DB, Sy RW, Freedman SB. Feasibility and cost-effectiveness of stroke prevention through community screening for atrial fibrillation using iPhone ECG in pharmacies. The SEARCH-AF study. Thromb Haemost. 2014 Jun;111(6):1167-76. doi: 10.1160/TH14-03-0231. Epub 2014 Apr 1. |
| 21300712 | Result | Kaczorowski J, Chambers LW, Dolovich L, Paterson JM, Karwalajtys T, Gierman T, Farrell B, McDonough B, Thabane L, Tu K, Zagorski B, Goeree R, Levitt CA, Hogg W, Laryea S, Carter MA, Cross D, Sabaldt RJ. Improving cardiovascular health at population level: 39 community cluster randomised trial of Cardiovascular Health Awareness Program (CHAP). BMJ. 2011 Feb 7;342:d442. doi: 10.1136/bmj.d442. |
| 29634829 | Result | US Burden of Disease Collaborators; Mokdad AH, Ballestros K, Echko M, Glenn S, Olsen HE, Mullany E, Lee A, Khan AR, Ahmadi A, Ferrari AJ, Kasaeian A, Werdecker A, Carter A, Zipkin B, Sartorius B, Serdar B, Sykes BL, Troeger C, Fitzmaurice C, Rehm CD, Santomauro D, Kim D, Colombara D, Schwebel DC, Tsoi D, Kolte D, Nsoesie E, Nichols E, Oren E, Charlson FJ, Patton GC, Roth GA, Hosgood HD, Whiteford HA, Kyu H, Erskine HE, Huang H, Martopullo I, Singh JA, Nachega JB, Sanabria JR, Abbas K, Ong K, Tabb K, Krohn KJ, Cornaby L, Degenhardt L, Moses M, Farvid M, Griswold M, Criqui M, Bell M, Nguyen M, Wallin M, Mirarefin M, Qorbani M, Younis M, Fullman N, Liu P, Briant P, Gona P, Havmoller R, Leung R, Kimokoti R, Bazargan-Hejazi S, Hay SI, Yadgir S, Biryukov S, Vollset SE, Alam T, Frank T, Farid T, Miller T, Vos T, Barnighausen T, Gebrehiwot TT, Yano Y, Al-Aly Z, Mehari A, Handal A, Kandel A, Anderson B, Biroscak B, Mozaffarian D, Dorsey ER, Ding EL, Park EK, Wagner G, Hu G, Chen H, Sunshine JE, Khubchandani J, Leasher J, Leung J, Salomon J, Unutzer J, Cahill L, Cooper L, Horino M, Brauer M, Breitborde N, Hotez P, Topor-Madry R, Soneji S, Stranges S, James S, Amrock S, Jayaraman S, Patel T, Akinyemiju T, Skirbekk V, Kinfu Y, Bhutta Z, Jonas JB, Murray CJL. The State of US Health, 1990-2016: Burden of Diseases, Injuries, and Risk Factors Among US States. JAMA. 2018 Apr 10;319(14):1444-1472. doi: 10.1001/jama.2018.0158. |
| 23443509 | Result | Steventon A, Bardsley M, Billings J, Dixon J, Doll H, Beynon M, Hirani S, Cartwright M, Rixon L, Knapp M, Henderson C, Rogers A, Hendy J, Fitzpatrick R, Newman S. Effect of telecare on use of health and social care services: findings from the Whole Systems Demonstrator cluster randomised trial. Age Ageing. 2013 Jul;42(4):501-8. doi: 10.1093/ageing/aft008. Epub 2013 Feb 25. |
| 22723612 | Result | Steventon A, Bardsley M, Billings J, Dixon J, Doll H, Hirani S, Cartwright M, Rixon L, Knapp M, Henderson C, Rogers A, Fitzpatrick R, Hendy J, Newman S; Whole System Demonstrator Evaluation Team. Effect of telehealth on use of secondary care and mortality: findings from the Whole System Demonstrator cluster randomised trial. BMJ. 2012 Jun 21;344:e3874. doi: 10.1136/bmj.e3874. |
| 27224997 | Result | Hirani SP, Rixon L, Beynon M, Cartwright M, Cleanthous S, Selva A, Sanders C, Newman SP; WSD investigators. Quantifying beliefs regarding telehealth: Development of the Whole Systems Demonstrator Service User Technology Acceptability Questionnaire. J Telemed Telecare. 2017 May;23(4):460-469. doi: 10.1177/1357633X16649531. Epub 2016 May 25. |
| 25986472 | Result | Steventon A, Grieve R, Bardsley M. An Approach to Assess Generalizability in Comparative Effectiveness Research: A Case Study of the Whole Systems Demonstrator Cluster Randomized Trial Comparing Telehealth with Usual Care for Patients with Chronic Health Conditions. Med Decis Making. 2015 Nov;35(8):1023-36. doi: 10.1177/0272989X15585131. Epub 2015 May 18. |
| 24099334 | Result | Bardsley M, Steventon A, Doll H. Impact of telehealth on general practice contacts: findings from the whole systems demonstrator cluster randomised trial. BMC Health Serv Res. 2013 Oct 8;13:395. doi: 10.1186/1472-6963-13-395. |
| 30042363 | Result | Owusu Obeng A, Fei K, Levy KD, Elsey AR, Pollin TI, Ramirez AH, Weitzel KW, Horowitz CR. Physician-Reported Benefits and Barriers to Clinical Implementation of Genomic Medicine: A Multi-Site IGNITE-Network Survey. J Pers Med. 2018 Jul 24;8(3):24. doi: 10.3390/jpm8030024. |
| 26269293 | Result | Kimura BJ, Shaw DJ, Amundson SA, Phan JN, Blanchard DG, DeMaria AN. Cardiac Limited Ultrasound Examination Techniques to Augment the Bedside Cardiac Physical Examination. J Ultrasound Med. 2015 Sep;34(9):1683-90. doi: 10.7863/ultra.15.14.09002. Epub 2015 Aug 12. |
| 28851729 | Result | Halcox JPJ, Wareham K, Cardew A, Gilmore M, Barry JP, Phillips C, Gravenor MB. Assessment of Remote Heart Rhythm Sampling Using the AliveCor Heart Monitor to Screen for Atrial Fibrillation: The REHEARSE-AF Study. Circulation. 2017 Nov 7;136(19):1784-1794. doi: 10.1161/CIRCULATIONAHA.117.030583. Epub 2017 Aug 28. |
| 28923013 | Result | Weinfurt KP, Hernandez AF, Coronado GD, DeBar LL, Dember LM, Green BB, Heagerty PJ, Huang SS, James KT, Jarvik JG, Larson EB, Mor V, Platt R, Rosenthal GE, Septimus EJ, Simon GE, Staman KL, Sugarman J, Vazquez M, Zatzick D, Curtis LH. Pragmatic clinical trials embedded in healthcare systems: generalizable lessons from the NIH Collaboratory. BMC Med Res Methodol. 2017 Sep 18;17(1):144. doi: 10.1186/s12874-017-0420-7. |
| D013568 |
| Pathological Conditions, Signs and Symptoms |
| D007333 | Insulin Resistance |
| D006946 | Hyperinsulinism |
| D044882 | Glucose Metabolism Disorders |
| D008659 | Metabolic Diseases |
| D009750 | Nutritional and Metabolic Diseases |
| D009358 | Congenital, Hereditary, and Neonatal Diseases and Abnormalities |