Browsing by Author "Morris, John"

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Open Access
Big Data Analytics and Sensor-Enhanced Activity Management to Improve Effectiveness and Efficiency of Outpatient Medical Rehabilitation.
(International journal of environmental research and public health, 2020-01) Jones, Mike; Collier, George; Reinkensmeyer, David J; DeRuyter, Frank; Dzivak, John; Zondervan, Daniel; Morris, John
Numerous societal trends are compelling a transition from inpatient to outpatient venues of care for medical rehabilitation. While there are advantages to outpatient rehabilitation (e.g., lower cost, more relevant to home and community function), there are also challenges including lack of information about how patient progress observed in the outpatient clinic translates into improved functional performance at home. At present, outpatient providers must rely on patient-reported information about functional progress (or lack thereof) at home and in the community. Information and communication technologies (ICT) offer another option-data collected about the patient's adherence, performance and progress made on home exercises could be used to help guide course corrections between clinic visits, enhancing effectiveness and efficiency of outpatient care. In this article, we describe our efforts to explore use of sensor-enhanced home exercise and big data analytics in medical rehabilitation. The goal of this work is to demonstrate how sensor-enhanced exercise can improve rehabilitation outcomes for patients with significant neurological impairment (e.g., from stroke, traumatic brain injury, and spinal cord injury). We provide an overview of big data analysis and explain how it may be used to optimize outpatient rehabilitation, creating a more efficient model of care. We describe our planned development efforts to build advanced analytic tools to guide home-based rehabilitation and our proposed randomized trial to evaluate effectiveness and implementation of this approach.
Open Access
Establishing a regional, multisite database for quality improvement and service planning in community-based palliative care and hospice.
(J Palliat Med, 2010-08) Bull, Janet; Zafar, S Yousuf; Wheeler, Jane L; Harker, Matthew; Gblokpor, Agbessi; Hanson, Laura; Hulihan, Deirdre; Nugent, Rikki; Morris, John; Abernethy, Amy P
BACKGROUND: Outpatient palliative care, an evolving delivery model, seeks to improve continuity of care across settings and to increase access to services in hospice and palliative medicine (HPM). It can provide a critical bridge between inpatient palliative care and hospice, filling the gap in community-based supportive care for patients with advanced life-limiting illness. Low capacities for data collection and quantitative research in HPM have impeded assessment of the impact of outpatient palliative care. APPROACH: In North Carolina, a regional database for community-based palliative care has been created through a unique partnership between a HPM organization and academic medical center. This database flexibly uses information technology to collect patient data, entered at the point of care (e.g., home, inpatient hospice, assisted living facility, nursing home). HPM physicians and nurse practitioners collect data; data are transferred to an academic site that assists with analyses and data management. Reports to community-based sites, based on data they provide, create a better understanding of local care quality. CURRENT STATUS: The data system was developed and implemented over a 2-year period, starting with one community-based HPM site and expanding to four. Data collection methods were collaboratively created and refined. The database continues to grow. Analyses presented herein examine data from one site and encompass 2572 visits from 970 new patients, characterizing the population, symptom profiles, and change in symptoms after intervention. CONCLUSION: A collaborative regional approach to HPM data can support evaluation and improvement of palliative care quality at the local, aggregated, and statewide levels.
Open Access
The Digital Health Revolution and People with Disabilities: Perspective from the United States.
(International journal of environmental research and public health, 2020-01) Jones, Mike; DeRuyter, Frank; Morris, John
This article serves as the introduction to this special issue on Mobile Health and Mobile Rehabilitation for People with Disabilities. Social, technological and policy trends are reviewed. Needs, opportunities and challenges for the emerging fields of mobile health (mHealth, aka eHealth) and mobile rehabilitation (mRehab) are discussed. Healthcare in the United States (U.S.) is at a critical juncture characterized by: (1) a growing need for healthcare and rehabilitation services; (2) maturing technological capabilities to support more effective and efficient health services; (3) evolving public policies designed, by turns, to contain cost and support new models of care; and (4) a growing need to ensure acceptance and usability of new health technologies by people with disabilities and chronic conditions, clinicians and health delivery systems. Discussion of demographic and population health data, healthcare service delivery and a public policy primarily focuses on the U.S. However, trends identified (aging populations, growing prevalence of chronic conditions and disability, labor shortages in healthcare) apply to most countries with advanced economies and others. Furthermore, technologies that enable mRehab (wearable sensors, in-home environmental monitors, cloud computing, artificial intelligence) transcend national boundaries. Remote and mobile healthcare delivery is needed and inevitable. Proactive engagement is critical to ensure acceptance and effectiveness for all stakeholders.