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JMIR Aging (JA, Founding Editor-in-chief: Jing Wang, Cizik School of Nursing, Houston TX, USA) is a new sister journal of JMIR (the leading open-access journal in health informatics (Impact Factor 2016: 5.175), focusing on technologies, medical devices, apps, engineering, informatics applications and patient education for medicine and nursing, education, preventative interventions and clinical care / home care for elderly populations. In addition, aging-focused big data analytics using data from electronic health record systems, health insurance databases, federal reimbursement databases (e.g. U.S. Medicare and Medicaid), and other large databases are also welcome.
As open access journal we are read by clinicians, nurses/allied health professionals, informal caregivers and patients alike and have (as all JMIR journals) a focus on readable and applied science reporting the design and evaluation of health innovations and emerging technologies. We publish original research, viewpoints, and reviews (both literature reviews and medical device/technology/app reviews).
During a limited period of time, there are no fees to publish in this journal. Articles are carfully copyedited and XML-tagged, ready for submission in PubMed Central.
Be a founding author of this new journal and submit your paper today!
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Background: Half of Medicare reimbursement goes towards caring for the top 5% of the most expensive patients. However, little is known about these patients prior to reaching the top or how their cost...
Background: Half of Medicare reimbursement goes towards caring for the top 5% of the most expensive patients. However, little is known about these patients prior to reaching the top or how their cost changes annually. To address these gaps we analyzed patient flow and associated healthcare cost trends over 5 years period. Objective: To evaluate the cost of healthcare utilization of older patients by analyzing changes in their expenditure long term. Methods: This is a retrospective, longitudinal, multicenter study to evaluate healthcare cost of 2,643 older patients over the period 2011-2015. All patients had at least one episode of home healthcare during the study period and used a Personal Emergency Response Service (PERS) at home for any length of time during the observation period. We segmented all patients into Top-(5%), Middle-(6-50%) and Bottom-(51-100%) segments by their annual expenditures and built cost pyramids based thereon. The longitudinal healthcare expenditure trends of the complete study population as well as each segment were assessed by linear regression models. Patient flows throughout the segments of the cost acuity pyramids from year to year were modeled by Markov chains. Results: Total healthcare cost of the study population nearly doubled from $17.7M in 2011 to $33.0M in 2015 with an expected yearly cost increase of $3.6M (p=0.003). This grow was driven by significantly higher cost increase in the Middle–segment ($2.3M, p=0.002). The expected yearly costs increase of the Top- and Bottom-segments was $1.2M (p=0.008) and $0.1M (p=0.003), respectively. The patients and cost flow analyses showed that 18% of patients moved up the cost acuity pyramid yearly and their cost increased by 672% in contrast to 22% of patients that moved down with a cost decreased by 86%. The remaining 60% of patients stayed at the same segment from year to year but their cost increased by 18%. Conclusions: While many healthcare organizations target costly intensive interventions at their most expensive patients (Top-segment), this analysis unveiled potential cost savings opportunities by managing the patients in the lower cost segments that are at risk of moving up the cost acuity pyramid. To achieve this, data analytics that integrate longitudinal data from the EHRs and home monitoring devices like PERS may help healthcare organizations to optimize resources by enabling clinicians to proactively manage patients in their home or community environments, beyond institutional settings and 30-60 day telehealth services.