scholarly journals Technology-Enabled Health Care Collaboration in Pediatric Chronic Illness: Pre-Post Interventional Study for Feasibility, Acceptability, and Clinical Impact of an Electronic Health Record–Linked Platform for Patient-Clinician Partnership

10.2196/11968 ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. e11968
Author(s):  
Lisa Opipari-Arrigan ◽  
Dana M H Dykes ◽  
Shehzad A Saeed ◽  
Sunny Thakkar ◽  
Lisa Burns ◽  
...  
Keyword(s):  
Chronic Illness ◽  
Electronic Health Record ◽  
Real Time ◽  
Data Sharing ◽  
Self Efficacy ◽  
Feedback Loops ◽  
Health Record ◽  
Pediatric Chronic Illness ◽  
Patient Reported ◽  
Electronic Health

Background Mobile health (mHealth) technology has the potential to support the Chronic Care Model’s vision of closed feedback loops and patient-clinician partnerships. Objective This study aims to evaluate the feasibility, acceptability, and short-term impact of an electronic health record–linked mHealth platform (Orchestra) supporting patient and clinician collaboration through real-time, bidirectional data sharing. Methods We conducted a 6-month prospective, pre-post, proof-of-concept study of Orchestra among patients and parents in the Cincinnati Children’s Hospital inflammatory bowel disease (IBD) and cystic fibrosis (CF) clinics. Participants and clinicians used Orchestra during and between visits to complete and view patient-reported outcome (PRO) measures and previsit plans. Surveys completed at baseline and at 3- and 6-month follow-up visits plus data from the platform were used to assess outcomes including PRO completion rates, weekly platform use, disease self-efficacy, and impact on care. Analyses included descriptive statistics; pre-post comparisons; Pearson correlations; and, if applicable, effect sizes. Results We enrolled 92 participants (CF: n=52 and IBD: n=40), and 73% (67/92) completed the study. Average PRO completion was 61%, and average weekly platform use was 80%. Participants reported improvement in self-efficacy from baseline to 6 months (7.90 to 8.44; P=.006). At 6 months, most participants reported that the platform was useful (36/40, 90%) and had a positive impact on their care, including improved visit quality (33/40, 83%), visit collaboration (35/40, 88%), and visit preparation (31/40, 78%). PRO completion was positively associated with multiple indicators of care impact at 3 and 6 months. Conclusions Use of an mHealth tool to support closed feedback loops through real-time data sharing and patient-clinician collaboration is feasible and shows indications of acceptability and promise as a strategy for improving pediatric chronic illness management.

scholarly journals Technology-Enabled Health Care Collaboration in Pediatric Chronic Illness: Pre-Post Interventional Study for Feasibility, Acceptability, and Clinical Impact of an Electronic Health Record–Linked Platform for Patient-Clinician Partnership (Preprint)

2018 ◽  
Author(s):  
Lisa Opipari-Arrigan ◽  
Dana M H Dykes ◽  
Shehzad A Saeed ◽  
Sunny Thakkar ◽  
Lisa Burns ◽  
...  
Keyword(s):  
Chronic Illness ◽  
Electronic Health Record ◽  
Real Time ◽  
Data Sharing ◽  
Self Efficacy ◽  
Feedback Loops ◽  
Health Record ◽  
Pediatric Chronic Illness ◽  
Patient Reported ◽  
Electronic Health

BACKGROUND Mobile health (mHealth) technology has the potential to support the Chronic Care Model’s vision of closed feedback loops and patient-clinician partnerships. OBJECTIVE This study aims to evaluate the feasibility, acceptability, and short-term impact of an electronic health record–linked mHealth platform <i>(Orchestra)</i> supporting patient and clinician collaboration through real-time, bidirectional data sharing. METHODS We conducted a 6-month prospective, pre-post, proof-of-concept study of <i>Orchestra</i> among patients and parents in the Cincinnati Children’s Hospital inflammatory bowel disease (IBD) and cystic fibrosis (CF) clinics. Participants and clinicians used <i>Orchestra</i> during and between visits to complete and view patient-reported outcome (PRO) measures and previsit plans. Surveys completed at baseline and at 3- and 6-month follow-up visits plus data from the platform were used to assess outcomes including PRO completion rates, weekly platform use, disease self-efficacy, and impact on care. Analyses included descriptive statistics; pre-post comparisons; Pearson correlations; and, if applicable, effect sizes. RESULTS We enrolled 92 participants (CF: n=52 and IBD: n=40), and 73% (67/92) completed the study. Average PRO completion was 61%, and average weekly platform use was 80%. Participants reported improvement in self-efficacy from baseline to 6 months (7.90 to 8.44; <i>P</i>=.006). At 6 months, most participants reported that the platform was useful (36/40, 90%) and had a positive impact on their care, including improved visit quality (33/40, 83%), visit collaboration (35/40, 88%), and visit preparation (31/40, 78%). PRO completion was positively associated with multiple indicators of care impact at 3 and 6 months. CONCLUSIONS Use of an mHealth tool to support closed feedback loops through real-time data sharing and patient-clinician collaboration is feasible and shows indications of acceptability and promise as a strategy for improving pediatric chronic illness management.

The APPROACH trial: Assessing pain, patient-reported outcomes, and complementary and integrative health

2020 ◽  
Vol 17 (4) ◽  
pp. 351-359
Author(s):  
Steven B Zeliadt ◽  
Scott Coggeshall ◽  
Eva Thomas ◽  
Hannah Gelman ◽  
Stephanie L Taylor
Keyword(s):  
Electronic Health Record ◽  
Real Time ◽  
Patient Reported Outcomes ◽  
Health Record ◽  
Business Practices ◽  
Electronic Health Record Data ◽  
Integrative Health ◽  
Patient Reported ◽  
Record Data ◽  
Electronic Health

Electronic health record data can be used in multiple ways to facilitate real-world pragmatic studies. Electronic health record data can provide detailed information about utilization of treatment options to help identify appropriate comparison groups, access historical clinical characteristics of participants, and facilitate measuring longitudinal outcomes for the treatments being studied. An additional novel use of electronic health record data is to assess and understand referral pathways and other business practices that encourage or discourage patients from using different types of care. We describe an ongoing study utilizing access to real-time electronic health record data about changing patterns of complementary and integrative health services to demonstrate how electronic health record data can provide the foundation for a pragmatic study when randomization is not feasible. Conducting explanatory trials of the value of emerging therapies within a healthcare system poses ethical and pragmatic challenges, such as withholding access to specific services that are becoming widely available to patients. We describe how prospective examination of real-time electronic health record data can be used to construct and understand business practices as potential surrogates for direct randomization through an instrumental variables analytic approach. In this context, an example of a business practice is the internal hiring of acupuncturists who also provide yoga or Tai Chi classes and can offer these classes without additional cost compared to community acupuncturists. Here, the business practice of hiring internal acupuncturists is likely to encourage much higher rates of combined complementary and integrative health use compared to community referrals. We highlight the tradeoff in efficiency of this pragmatic approach and describe use of simulations to estimate the potential sample sizes needed for a variety of instrument strengths. While real-time monitoring of business practices from electronic health records provides insights into the validity of key independence assumptions associated with the instrumental variable approaches, we note that there may be some residual confounding by indication or selection bias and describe how alternative sources of electronic health record data can be used to assess the robustness of instrumental variable assumptions to address these challenges. Finally, we also highlight that while some clinical outcomes can be obtained directly from the electronic health record, such as longitudinal opioid utilization and pain intensity levels for the study of the value of complementary and integrative health, it is often critical to supplement clinical electronic health record–based measures with patient-reported outcomes. The experience of this example in evaluating complementary and integrative health demonstrates the use of electronic health record data in several novel ways that may be of use for designing future pragmatic trials.

What does social isolation have to do with my arthritis? Patient and provider views of the implementation of an electronic Social Determinants of Health risk assessment tool

2020 ◽  
Vol 64 (1) ◽  
pp. 707-710
Keyword(s):  
Electronic Health Record ◽  
Social Determinants Of Health ◽  
Social Determinants ◽  
Assessment Tool ◽  
Determinants Of Health ◽  
Health Record ◽  
Institute Of Medicine ◽  
Patient Reported ◽  
Item Responses ◽  
Electronic Health

Social Determinants of Health (SDoH) are the conditions in which people are born, live, learn, work, and play that can affect health, functioning, and quality-of-life outcomes. The Institute of Medicine charged healthcare institutions with capturing and measuring patient SDoH risk factors through the electronic health record. Following the implementation of a social determinants of health electronic module across a major health institution, the response to institutional implementation was evaluated. To assess the response, a multidisciplinary team interviewed patients and providers, mapped the workflow, and performed simulated tests to trace the flow of SDoH data from survey item responses to visualization in EHR output for clinicians. Major results of this investigation were: 1) the lack of patient consensus about value of collecting SDOH data, and 2) the disjointed view of patient reported SDoH risks across patients, providers, and the electronic health record due to the way data was collected and visualized.

scholarly journals Real-Time Intraoperative Consultation Reporting in the Electronic Health Record

2020 ◽  
Vol 154 (3) ◽  
pp. 387-393
Author(s):  
Molly E Klein ◽  
Joseph W Rudolf ◽  
Maryna Tarbunova ◽  
Tanya Jorden ◽  
Susanna R Clark ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Real Time ◽  
Laboratory Medicine ◽  
Clinical Impact ◽  
Final Report ◽  
Health Record ◽  
Laboratory Information System ◽  
Surgical Team ◽  
Operative Note ◽  
Electronic Health

Abstract Objectives We sought to make pathologists’ intraoperative consultation (IOC) results immediately available to the surgical team, other clinicians, and laboratory medicine colleagues to improve communication and decrease postanalytic errors. Methods We created an IOC report in our stand-alone laboratory information system that could be signed out prior to, and independent of, the final report, and transfer immediately to the electronic health record (EHR) as a preliminary diagnosis. We evaluated two metrics: preliminary (IOC) result review in the EHR by clinicians and postanalytic errors. Results We assessed 2,886 IOC orders from the first 22 months after implementation. Clinicians reviewed 1,956 (68%) of the IOC results while in preliminary status, including 1,399 (48%) within the first 24 hours. We evaluated 150 cases preimplementation and 300 cases postimplementation for discrepancies between the pathologist’s IOC result and the IOC result recorded by the surgeon in the operative note. Discrepancies dropped from 12 of 150 preimplementation to 6 of 150 and 7 of 150 in postimplementation years 1 and 2. One of the 25 discrepancies had a major clinical impact. Conclusions Real-time reporting of IOC results to the EHR reliably transmits results immediately to clinical teams. This strategy reduces but does not eliminate postanalytic interpretive errors by clinical teams.

scholarly journals Frequency and Types of Patient-Reported Errors in Electronic Health Record Ambulatory Care Notes

2020 ◽  
Vol 3 (6) ◽  
pp. e205867 ◽  
Author(s):  
Sigall K. Bell ◽  
Tom Delbanco ◽  
Joann G. Elmore ◽  
Patricia S. Fitzgerald ◽  
Alan Fossa ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Ambulatory Care ◽  
Health Record ◽  
Patient Reported ◽  
Electronic Health

Integrating patient-reported outcomes data into the electronic health record.

2018 ◽  
Vol 36 (30_suppl) ◽  
pp. 186-186
Author(s):  
Brandon Bosch ◽  
Scott Hartman ◽  
Lauren Caldarello ◽  
Diane Denny, DBA
Keyword(s):  
Electronic Health Record ◽  
Population Analysis ◽  
Treatment Plan ◽  
Symptom Burden ◽  
Symptom Assessment ◽  
Patient Reported Outcome ◽  
Health Record ◽  
National Network ◽  
Patient Reported ◽  
Electronic Health

186 Background: As a national network of hospitals that specialize in the treatment of patients fighting complex or advanced-stage cancer, the network was an early adopter of using patient reported outcome (PRO) data as part of its routine patient assessment and treatment. Since 2012 an externally validated tool has been used to capture patients’ perceived symptom burden for real-time clinical intervention, from the point of first visit throughout the course of treatment, at intervals of 21 days or greater. Research has demonstrated the use of PRO data as a valuable component of a patient’s treatment plan, promoting improved quality and length of life. Methods: The use of this data across the network was expanded such that results once only accessible on paper and via electronically stored images, has now been fully integrated into the electronic health record (EHR). A multidisciplinary project team formulated the specifications for a successful integration of PRO data into the EHR. Results: The project achieved its goal and went beyond data integration to include implementation of a solution to facilitate documentation of intervention against patients’ symptoms. Provider workflow efficiency is greatly enhanced via single system access and visual notification, with critical values flagged, to focus providers’ attention on severe symptoms. Incorporation of a unified EHR flowsheet provides a paperless, one-stop symptom assessment approach and streamlined mechanism for intervention documentation. The documentation module leverages structured data fields and linkage of PRO data with interventions, such as specialist referrals or medication orders, to support enhanced patient care and quality improvement. Conclusions: The ability to easily view an array of patient reported concerns and document interventions against severe or significantly worsening symptoms provides clinicians an enhanced ability to address quality of life related needs. PRO data is now stored electronically in the enterprise warehouse, thus enabling aggregation with data from which to perform population analysis and eventually, pursue opportunities for predictive modeling.

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