Alcuni abstract di articoli che trattano argomenti relativi all'eHealth

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HealtheLife: Using a Patient Portal App to Reduce Type 2 Diabetes in East Los Angeles

The following proposal explores a potentially cost effective and cost efficient solution to alleviate the burden of type 2 diabetes among White Memorial Medical Center (WMMC) patients and their primary service area within Los Angeles County Service Planning Area 4 (SPA-4). SPA-4 is a medically underserved area with numerous key health indicators that indicate the need for increased self-management efforts among its Hispanic population. In response, WMMC has made a commitment to the SPA-4 community and made diabetes atop its community priority. An organization-wide Glycemic Control Project was created by WMMC administrators to provide more effective services by using Health Information Technology (HIT) within its operations. In support of this project, the WMMC Clinical Informatics Systems (CIS) department has proposed the use of Healthelife mobile application to improve diabetes self-management in WMMC transitional care. A literature review was conducted but, found very limited efficacy studies on mobile patient portal apps and patient portals mhealth interventions among Hispanic diabetics. However, several studies have implied that there are great research opportunities in tailoring the use of a patient portal mobile application for Hispanics, expanding its use within DMSE sessions through Community Health Workers, utilizing the trending mhealth functionality of patient portals, as well as proposing eHealth interventions that reduce health disparities. As a newly available resource to WMMC, the Healthelife mobile application is Cerner’s multilingual patient portal mobile application that is already live and fully integrated with WMMC’s “My Adventist Health” patient portal”. Accordingly, WMMC CIS has proposed a HealtheLife pilot program among its Hispanic patients to determine if its use will improve self-management efficacy and glycemic control among WMMC Type 2 diabetics (18+ years old). Technological Acceptance Model (TAM), Social Support, and Social Cognitive Theory will be applied throughout the pilot to gradually condition Healthelife usage among WMMC patients/caregivers for tailored educational experiences that strengthen WMMC Diabetes Self-Management (DSME) sessions. Essentially, diabetes educators will conduct the pilot program on adult Hispanics (18+) who are inpatient diabetics transitioning to Adventist Health Physician Network (AHPN) Physicians and DSME outpatient services. Primarily, the pilot will aim to improve A1Cs, Self-efficacy, and DSME attendance. Secondary outcomes of the intervention will be asses by qualitative assessment of Healthelife functionality, observed ED use, and ED readmission. All outcomes will be assessed through an internal quasi-experimental study examining an intervention group using Healthelife against a retrospective control groups from 2016. In sum, goal of the pilot program will set forth a care path that improve patients’ continuity of care and diabetes prevention beyond the walls of WMMC operations. By adopting the use of Healthelife as a population health tool, WMMC has the potential to intensify current DSME curriculum, to preventative unnecessary ED use, and to improve type 2 diabetes prevention efforts within SPA-4. More importantly, the suggestion to pilot Healthelife progressively introduces the benefits of HIT to Hispanic populations who are underserved and with limited resources

Implementing Exercise = Medicine in routine clinical care; needs for an online tool and key decisions for implementation of Exercise = Medicine within two Dutch academic hospitals

Background There is much evidence to implement physical activity interventions for medical reasons in healthcare settings. However, the prescription of physical activity as a treatment, referring to as 'Exercise is Medicine' (E = M) is currently mostly absent in routine hospital care in The Netherlands. To support E = M prescription by clinicians in hospitals, this study aimed: (1) to develop an E = M-tool for physical activity advice and referrals to facilitate the E = M prescription in hospital settings; and (2) to provide an E = M decision guide on key decisions for implementation to prepare for E = M prescription in hospital care. Methods A mixed method design was used employing a questionnaire and face-to-face interviews with clinicians, lifestyle coaches and hospital managers, a patient panel and stakeholders to assess the needs regarding an E = M-tool and key decisions for implementation of E = M. Based on the needs assessment, a digital E = M-tool was developed. The key decisions informed the development of an E = M decision guide. Results An online supportive tool for E = M was developed for two academic hospitals. Based on the needs assessment, linked to the different patients' electronic medical records and tailored to the two local settings (University Medical Center Groningen, Amsterdam University Medical Centers). The E = M-tool existed of a tool algorithm, including patient characteristics assessed with a digital questionnaire (age, gender, PA, BMI, medical diagnosis, motivation to change physical activity and preference to discuss physical activity with their doctor) set against norm values. The digital E = M-tool provided an individual E = M-prescription for patients and referral options to local PA interventions in- and outside the hospital. An E = M decision guide was developed to support the implementation of E = M prescription in hospital care. Conclusions This study provided insight into E = M-tool development and the E = M decision-making to support E = M prescription and facilitate tailoring towards local E = M treatment options, using strong stakeholder participation. Outcomes may serve as an example for other decision support guides and interventions aimed at E = M implementation.</p

Implementing Exercise = Medicine in routine clinical care; needs for an online tool and key decisions for implementation of Exercise = Medicine within two Dutch academic hospitals

BACKGROUND: There is much evidence to implement physical activity interventions for medical reasons in healthcare settings. However, the prescription of physical activity as a treatment, referring to as 'Exercise is Medicine' (E = M) is currently mostly absent in routine hospital care in The Netherlands. To support E = M prescription by clinicians in hospitals, this study aimed: (1) to develop an E = M-tool for physical activity advice and referrals to facilitate the E = M prescription in hospital settings; and (2) to provide an E = M decision guide on key decisions for implementation to prepare for E = M prescription in hospital care. METHODS: A mixed method design was used employing a questionnaire and face-to-face interviews with clinicians, lifestyle coaches and hospital managers, a patient panel and stakeholders to assess the needs regarding an E = M-tool and key decisions for implementation of E = M. Based on the needs assessment, a digital E = M-tool was developed. The key decisions informed the development of an E = M decision guide. RESULTS: An online supportive tool for E = M was developed for two academic hospitals. Based on the needs assessment, linked to the different patients' electronic medical records and tailored to the two local settings (University Medical Center Groningen, Amsterdam University Medical Centers). The E = M-tool existed of a tool algorithm, including patient characteristics assessed with a digital questionnaire (age, gender, PA, BMI, medical diagnosis, motivation to change physical activity and preference to discuss physical activity with their doctor) set against norm values. The digital E = M-tool provided an individual E = M-prescription for patients and referral options to local PA interventions in- and outside the hospital. An E = M decision guide was developed to support the implementation of E = M prescription in hospital care. CONCLUSIONS: This study provided insight into E = M-tool development and the E = M decision-making to support E = M prescription and facilitate tailoring towards local E = M treatment options, using strong stakeholder participation. Outcomes may serve as an example for other decision support guides and interventions aimed at E = M implementation

The GUIDES checklist: development of a tool to improve the successful use of guideline-based computerised clinical decision support

Background: Computerised decision support (CDS) based on trustworthy clinical guidelines is a key component of a learning healthcare system. Research shows that the effectiveness of CDS is mixed. Multifaceted context, system, recommendation and implementation factors may potentially affect the success of CDS interventions. This paper describes the development of a checklist that is intended to support professionals to implement CDS successfully. Methods: We developed the checklist through an iterative process that involved a systematic review of evidence and frameworks, a synthesis of the success factors identified in the review, feedback from an international expert panel that evaluated the checklist in relation to a list of desirable framework attributes, consultations with patients and healthcare consumers and pilot testing of the checklist. Results: We screened 5347 papers and selected 71 papers with relevant information on success factors for guideline-based CDS. From the selected papers, we developed a 16-factor checklist that is divided in four domains, i.e. the CDS context, content, system and implementation domains. The panel of experts evaluated the checklist positively as an instrument that could support people implementing guideline-based CDS across a wide range of settings globally. Patients and healthcare consumers identified guideline-based CDS as an important quality improvement intervention and perceived the GUIDES checklist as a suitable and useful strategy. Conclusions: The GUIDES checklist can support professionals in considering the factors that affect the success of CDS interventions. It may facilitate a deeper and more accurate understanding of the factors shaping CDS effectiveness. Relying on a structured approach may prevent that important factors are missed

Email for communicating results of diagnostic medical investigations to patients

&lt;p&gt;Background: As medical care becomes more complex and the ability to test for conditions grows, pressure on healthcare providers to convey increasing volumes of test results to patients is driving investigation of alternative technological solutions for their delivery. This review addresses the use of email for communicating results of diagnostic medical investigations to patients.&lt;/p&gt; &lt;p&gt;Objectives: To assess the effects of using email for communicating results of diagnostic medical investigations to patients, compared to SMS/ text messaging, telephone communication or usual care, on outcomes, including harms, for health professionals, patients and caregivers, and health services.&lt;/p&gt; &lt;p&gt;Search methods: We searched: the Cochrane Consumers and Communication Review Group Specialised Register, Cochrane Central Register of Controlled Trials (CENTRAL, The Cochrane Library, Issue 1 2010), MEDLINE (OvidSP) (1950 to January 2010), EMBASE (OvidSP) (1980 to January 2010), PsycINFO (OvidSP) (1967 to January 2010), CINAHL (EbscoHOST) (1982 to February 2010), and ERIC (CSA) (1965 to January 2010). We searched grey literature: theses/dissertation repositories, trials registers and Google Scholar (searched July 2010). We used additional search methods: examining reference lists and contacting authors.&lt;/p&gt; &lt;p&gt;Selection criteria: Randomised controlled trials, quasi-randomised trials, controlled before and after studies and interrupted time series studies of interventions using email for communicating results of any diagnostic medical investigations to patients, and taking the form of 1) unsecured email 2) secure email or 3) web messaging. All healthcare professionals, patients and caregivers in all settings were considered.&lt;/p&gt; &lt;p&gt;Data collection and analysis: Two review authors independently assessed the titles and abstracts of retrieved citations. No studies were identified for inclusion. Consequently, no data collection or analysis was possible.&lt;/p&gt; &lt;p&gt;Main results: No studies met the inclusion criteria, therefore there are no results to report on the use of email for communicating results of diagnostic medical investigations to patients.&lt;/p&gt; &lt;p&gt;Authors' conclusions: In the absence of included studies, we can draw no conclusions on the effects of using email for communicating results of diagnostic medical investigations to patients, and thus no recommendations for practice can be stipulated. Further well-designed research should be conducted to inform practice and policy for communicating patient results via email, as this is a developing area.&lt;/p&gt

Marshfield Clinic: Health Information Technology Paves the Way for Population Health Management

Highlights Fund-defined attributes of an ideal care delivery system and best practices, including an internal electronic health record, primary care teams, physician quality metrics and mentors, and standardized care processes for chronic care management