Telehealth for Limiting Readmission Rates of COPD Patients: An Assessment Based on Medicare Data
DOI:
https://doi.org/10.30953/tmt.v6.213Keywords:
Telemedicine, COPD, Medicare, ReadmissionAbstract
Objective: Telemedicine has developed as an innovative way to remotely view and treat patients without necessitating for patients to physically come into a physicians’ office or healthcare facility. This study aims to provide insights into the effectiveness of integrating telemedicine in medical facilities, where patients have high hierarchical condition category (HCC) risk scores.
Design: This study utilized two raw datasets: (1) a Centers for Medicare & Medicaid Services (CMS) dataset created from the 2017 Medicare Physician and Other Supplier National Provider Identity Aggregate Report and (2) a National Center for Education Statistics (NCES) dataset created from the NCES table on the number and percentage of households in each state with computer and internet access. A regression analysis was carried out on the CMS dataset to determine the correlation between HCC risk scores and the reimbursement lost by healthcare facilities, where over 50% of their patients are diagnosed with chronic obstructive pulmonary disease (COPD). A second analysis was conducted with the NCES dataset to show which states had a high proportion of both households with internet access and COPD patients. A final regression analysis was run and translated into an interactive map in order to determine which regions of the United States could most benefit from telemedicine adoption.
Results: This study discovered a number of physicians and healthcare facilities in the eastern region of the United States that could benefit significantly from telemedicine applications. These findings were supported by the locations and data abstracted from facilities with high numbers of COPD patients, which were found to have poor HCC risk scores and thus high reimbursement losses.
Conclusions: This study confirmed the association between HCC risk scores and reimbursement losses. In order to alleviate those losses, this study identified states across the United States that should choose to incorporate telemedicine into how they diagnose and treat patients based on the needs of healthcare facilities and the internet capabilities of households in those states, because telemedicine integration presents the potential to improve patient HCC risk scores and reimbursement amounts by lowering readmission rates while also promoting higher patient and physician satisfaction. Future efforts should develop specific strategies to assist with telemedicine implementation and should track the observed effects of its adoption on reimbursements and quality of care.
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References
1. Yeatts JP, Sangvai DG. HCC coding, risk adjustment, physician income: What you need to know. Fam Pract Manag. 2016[cited];0900:24–7. Available from: https://www.aafp.org/fpm/2016/0900/p24.pdf
2. Mehta HB, Dimoouo F, Adhikari D, et al. Comparison of comorbidity scores in predicting surgical outcomes. Med Care. 2016[cited];54(2):180–7. https://doi.org/10.1097/MLR.0000000000000465
3. NIH. NIH statement on World COPD Day 2018. 2018 [cited 2020 June 29]. Available from: https://www.nih.gov/news-events/news-releases/nih-statement-world-copd-day-2018
4. Omachi TA, Gregorich SE, Eisner MD, et al. Risk adjustment for health care financing in chronic disease: What are we missing by failing to account for disease severity? Med Care. 2013[cited];51(8):740–7. https://doi.org/10.1097/MLR.0b013e318298082f
5. Portillo EC, Wilcox A, Seckel E, et al. Reducing COPD readmission rates: Using a COPD care service during care transitions. Fed Pract. 2018[cited];35(11):30–6. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6366592/
6. Turcotte J, Samford Z, Broda A, Patton C. Centers for Medicare and Medicaid Services Hierarchical Condition Category score as a predictor of readmission and reoperation following elective inpatient spin surgery. J Neurosurg Spine. 2019[cited];31(4):600–6. https://doi.org/10.3171/2019.3.SPINE1999
7. Health Catalyst Editors. Five action items to improve HCC coding accuracy and risk adjustment with analytics. Health Catalyst; 2019 [cited 2020 June 29]. Available from: https://www.healthcatalyst.com/insights/5-ways-improve-hcc-coding-accuracy-risk-adjustment
8. Akinleye DD, McNutt L, Lazariu V, McLaughlin CC. Correlation between hospital finances and quality and safety of patient care. PLoS One. 2019[cited];14(8):e0219124. https://doi.org/10.1371/journal.pone.0219124
9. Bazzoli GJ, Clement JP, Lindrooth RC, et al. Hospital financial condition and operational decisions related to the quality of hospital care. Med Care Res Rev. 2007[cited];64(2):148–68. https://doi.org/10.1177/1077558706298289
10. Encinosa WE, Bernard DM. Hospital finances and patient safety outcomes. Inquiry. 2005[cited];42(1):60–72. https://doi.org/10.5034/inquiryjrnl_42.1.60
11. Dong GN. Performing well in financial management and quality of care: Evidence from hospital process measures for treatment of cardiovascular disease. BMC Health Serv Res. 2015[cited];15:45 https://doi.org/10.1186/s12913-015-0690-x
12. Smith RB, Dynan L, Fairbrother G, Chabi G, Simpson L. Medicaid, hospital financial stress, and the incidence of adverse medical events for children. Health Serv Res. 2012[cited];47(4):1621–41. https://doi.org/10.1111/j.1475-6773.2012.01385.x
13. Prakash B. Patient satisfaction. J Cutan Aesthet Surg. 2010[cited];3(3):151–5. https://doi.org/10.4103/0974-2077.74491
14. Wicklund E. Using telemedicine to boost HEDIS, reduce risk and fight blindness. mHealth Intelligence; 2016 [cited 2020 June 29]. Available from: https://mhealthintelligence.com/news/using-telemedicine-to-boost-hedis-reduce-risk-and-fight-blindness
15. Baggot D, Glick S, Lapsley H, Garg P, Javanmardian M, Macphearson M. Telehealth’s opportunities in new Medicare advantage rule. Oliver Wymman; 2019 [cited 2020 June 29]. Available from: https://health.oliverwyman.com/2019/04/cms-permits-telehealth-coverage-for-rural-medicare-patients.html
16. History of telemedicine. md Portal, September 23, 2015 [cited 2020 June 29]. Available from: http://mdportal.com/education/history-of-telemedicine/
17. O’Connor M, Asdornwised U, Dempsey ML, et al. Using telehealth to reduce all-cause 30-day hospital readmissions among heart failure patients receiving skilled home health services. Appl Clin Inform. 2016[cited];7(2):238–47. https://doi.org/10.4338/ACI-2015-11-SOA-0157
18. Ronda MCM, Dijkhorst-Oei L, Rutten GEHM. Reasons and barriers for using a patient portal: Survey among patients with diabetes mellitus. J Med Internet Res. 2014[cited];16(11):e263. https://doi.org/10.2196/jmir.3457
19. Kruse CS, Karem P, Shifflett K, Vegi L, Ravi K, Brooks M. Evaluating barriers to adopting telemedicine worldwide: A systemic review. J Telemed Telecare. 2018;24(1):4–12. https://doi.org/10.1177/1357633X16674087
20. CMS. Medicare Physician and Other Supplier National Provider Identifier (NPI) Aggregate Report, Calendar Year 2017. data.CMS.gov; 2019 [cited 2020 Mar 10]. Available from: https://data.cms.gov/Medicare-Physician-Supplier/Medicare-Physician-and-Other-Supplier-National-Pro/n5qc-ua94
21. Digest of Education Statistics. National Center for Education Statistics (NCES) Home Page, a part of the U.S. Department of Education; 2017 [cited 2020 Mar 3]. Available from: https://nces.ed.gov/programs/digest/d17/tables/dt17_702.60.asp
22. Holm KE, Plaufcan MR, Ford DW, et al. The impact of age on outcomes in chronic obstructive pulmonary disease differs by relationship status. J Behav Med. 2014[cited];37(4):654–63. https://doi.org/10.1007/s10865-013-9516-7
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