A novel concept for integrating and delivering health information using a comprehensive digital dashboard: An analysis of healthcare professionals’ intention to adopt a new system and the trend of its real usage

Lee, Kee Hyuck; Jung, Sung Il; Hwang, Hee; Yoo, Sooyoung; Baek, Hyun Young; Baek, Rong Min; Kim, Seok

doi:10.1016/j.ijmedinf.2016.10.001

Cited by 39 publications

(70 citation statements)

References 19 publications

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“…The average number of patients to whom doctors have replied could be used as a critical indicator of service empathy. Thus, the service empathy [ 48 ] of doctors to patient i (ie, SQ 3 i ) could be evaluated by the average number of patients to whom doctors have replied (equation 13, Figure 2 ), where count k ( drp ij ) is the total number of patients to whom the k th doctor replied, in which the k th doctor is the one who replied to j th post p ij by patient i , num ( drp ij ) is the total number of doctors who replied to the j th post p ij by patient i , and n is the total number of posts by patient i during a certain time interval i .…”

Section: Methodsmentioning

confidence: 99%

Patient Continued Use of Online Health Care Communities: Web Mining of Patient-Doctor Communication

Wu¹

2018

J Med Internet Res

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BackgroundIn practice, online health communities have passed the adoption stage and reached the diffusion phase of development. In this phase, patients equipped with knowledge regarding the issues involved in health care are capable of switching between different communities to maximize their online health community activities. Online health communities employ doctors to answer patient questions, and high quality online health communities are more likely to be acknowledged by patients. Therefore, the factors that motivate patients to maintain ongoing relationships with online health communities must be addressed. However, this has received limited scholarly attention.ObjectiveThe purpose of this study was to identify the factors that drive patients to continue their use of online health communities where doctor-patient communication occurs. This was achieved by integrating the information system success model with online health community features.MethodsA Web spider was used to download and extract data from one of the most authoritative Chinese online health communities in which communication occurs between doctors and patients. The time span analyzed in this study was from January 2017 to March 2017. A sample of 469 valid anonymous patients with 9667 posts was obtained (the equivalent of 469 respondents in survey research). A combination of Web mining and structural equation modeling was then conducted to test the research hypotheses.ResultsThe results show that the research framework for integrating the information system success model and online health community features contributes to our understanding of the factors that drive patients' relationships with online health communities. The primary findings are as follows: (1) perceived usefulness is found to be significantly determined by three exogenous variables (ie, social support, information quality, and service quality; R2=0.88). These variables explain 87.6% of the variance in perceived usefulness of online health communities; (2) similarly, patient satisfaction was found to be significantly determined by the three variables listed above (R2=0.69). These variables explain 69.3% of the variance seen in patient satisfaction; (3) continuance use (dependent variable) is significantly influenced by perceived usefulness and patient satisfaction (R2=0.93). That is, the combined effects of perceived usefulness and patient satisfaction explain 93.4% of the variance seen in continuance use; and (4) unexpectedly, individual literacy had no influence on perceived usefulness and satisfaction of patients using online health communities.ConclusionsFirst, this study contributes to the existing literature on the continuance use of online health communities using an empirical approach. Second, an appropriate metric was developed to assess constructs related to the proposed research model. Additionally, a Web spider enabled us to acquire objective data relatively easily and frequently, thereby overcoming a major limitation of survey techniques.

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Section: Methodsmentioning

confidence: 99%

Patient Continued Use of Online Health Care Communities: Web Mining of Patient-Doctor Communication

Wu¹

2018

J Med Internet Res

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“…Prior studies have shown that clinicians have high satisfaction with the use of dashboards in clinical workflows [17,18]. Clinical dashboards utilize visual displays to present a large amount of information, thereby enabling clinicians to tackle information overload by synthesizing a large amount of information in order to quickly aid in decision making.…”

Section: Discussionmentioning

confidence: 99%

A Dashboard Prototype for Tracking the Impact of Diabetes on Hospital Readmissions Using a National Administrative Database

Wong

Brovman

Rao³

et al. 2020

J Clin Med Res

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Background: Over the past several decades, diabetes mellitus has contributed to a significant disease burden in the general population. Evidence suggests that patients with a coexisting diabetes diagnosis consume more hospital resources, and have higher readmission rates compared to those who do not. Against the backdrop of bundled-payment programs, healthcare systems cannot underestimate the importance of monitoring patient health information at the population level. Methods: Using the data from the Centers for Medicare and Medicaid Services (CMS) administrative claims database, we created a dashboard prototype to enable hospitals to examine the impact of diabetes on their all-cause readmission rates and financial implications if diabetes was present at the index hospitalization. The technical design involved loading the relevant 10th revision of International Classification of Diseases (ICD-10) codes provided by the medical team and flagging diabetes patients at the claim. These patients were then tagged for readmissions within the same database. The odds ratios were determined based on data from two groups: those with diabetes at index hospitalization which include type 1 only, type 2 only, and type 1 and type 2 diabetes, plus those without diabetes at index hospitalization. Results: The dashboard presents summary data of diabetes readmissions quality metrics at a national level. Users can visualize summary data of each state and compare odds ratios for readmissions as well as raw hospitalization data at their facility. Dashboard users can also view data classified by a diagnosis-related group (DRG) system. In addition to a "national" data view, for users who inquire about data specific to demographic regions, the DRG view can be further stratified at the state level or county level. At the DRG level, users can view data about the cost per readmissions for all index hospitalization with and without diabetes. Conclusions: The dashboard prototype offers users a virtual interface which displays visual data for quick interpretation, monitors changes at a population level, and enables administrators to benchmark facility data against local and national trends. This is an important step in using data analytics to drive population level decision making to ultimately improve medical systems.

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“…At the end of the data collection period, we will ask participants to complete a questionnaire based on the Technology Acceptance Model, using well-validated items that have been used in numerous evaluations of HIT,49 including dashboards 50. This will provide participants’ perceptions of the usefulness of QualDash and data on whether they intend to continue using QualDash after the study period.…”

Section: Methods and Analysismentioning

confidence: 99%

How, in what contexts, and why do quality dashboards lead to improvements in care quality in acute hospitals? Protocol for a realist feasibility evaluation

et al. 2020

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IntroductionNational audits are used to monitor care quality and safety and are anticipated to reduce unexplained variations in quality by stimulating quality improvement (QI). However, variation within and between providers in the extent of engagement with national audits means that the potential for national audit data to inform QI is not being realised. This study will undertake a feasibility evaluation of QualDash, a quality dashboard designed to support clinical teams and managers to explore data from two national audits, the Myocardial Ischaemia National Audit Project (MINAP) and the Paediatric Intensive Care Audit Network (PICANet).Methods and analysisRealist evaluation, which involves building, testing and refining theories of how an intervention works, provides an overall framework for this feasibility study. Realist hypotheses that describe how, in what contexts, and why QualDash is expected to provide benefit will be tested across five hospitals. A controlled interrupted time series analysis, using key MINAP and PICANet measures, will provide preliminary evidence of the impact of QualDash, while ethnographic observations and interviews over 12 months will provide initial insight into contexts and mechanisms that lead to those impacts. Feasibility outcomes include the extent to which MINAP and PICANet data are used, data completeness in the audits, and the extent to which participants perceive QualDash to be useful and express the intention to continue using it after the study period.Ethics and disseminationThe study has been approved by the University of Leeds School of Healthcare Research Ethics Committee. Study results will provide an initial understanding of how, in what contexts, and why quality dashboards lead to improvements in care quality. These will be disseminated to academic audiences, study participants, hospital IT departments and national audits. If the results show a trial is feasible, we will disseminate the QualDash software through a stepped wedge cluster randomised trial.

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A novel concept for integrating and delivering health information using a comprehensive digital dashboard: An analysis of healthcare professionals’ intention to adopt a new system and the trend of its real usage

Cited by 39 publications

References 19 publications

Patient Continued Use of Online Health Care Communities: Web Mining of Patient-Doctor Communication

Patient Continued Use of Online Health Care Communities: Web Mining of Patient-Doctor Communication

A Dashboard Prototype for Tracking the Impact of Diabetes on Hospital Readmissions Using a National Administrative Database

How, in what contexts, and why do quality dashboards lead to improvements in care quality in acute hospitals? Protocol for a realist feasibility evaluation

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