Big Data Health Care Innovations: Performance Dashboarding as a Process of Collective Sensemaking

Identifying quality indicators to measure workplace violence in healthcare settings: a rapid review

BACKGROUND

Workplace violence (WPV) in healthcare is a growing challenge posing significant risks to patient care and employee well-being. Existing metrics to measure WPV in healthcare settings often fail to provide decision-makers with an adequate reflection of WPV due to the complexity of the issue. This increases the difficulty for decision-makers to evaluate WPV in healthcare settings and implement interventions that can produce sustained improvements.

OBJECTIVE

This study aims to identify and compile a list of quality indicators that have previously been utilized to measure WPV in healthcare settings. The identified quality indicators serve as tools, providing leadership with the necessary information on the state of WPV within their organization or the impact of WPV prevention interventions. This information provides leadership with a foundation for planning and decision making related to addressing WPV.

METHODS

Ovid databases were used to identify articles relevant to violence in healthcare settings, from which 43 publications were included for data extraction. Data extraction produced a total of 229 quality indicators that were sorted into three indicator categories using the Donabedian model: structure, process, and outcome.

RESULTS

A majority of the articles (93%) contained at least 1 quality indicator that possessed the potential to be operationalized at an organizational level. In addition, several articles (40%) contained valuable questionnaires or survey instruments for measuring WPV. In total, the rapid review process identified 84 structural quality indicators, 121 process quality indicators, 24 outcome quality indicators, 57 survey-type questions and 17 survey instruments.

CONCLUSIONS

This study provides a foundation for healthcare organizations to address WPV through systematic approaches informed by quality indicators. The utilization of indicators showed promise for characterizing WPV and measuring the efficacy of interventions. Caution must be exercised to ensure indicators are not discriminatory and are suited to specific organizational needs. While the findings of this review are promising, further investigation is needed to rigorously evaluate existing literature to expand the list of quality indicators for WPV.

Assessing a Digital Scorecard on Global Immunization Progress: Stakeholder Views and Implications for Enhancing Performance and Accountability

Global health agencies and regional and national stakeholders collaborated to develop the Immunization Agenda 2030 Scorecard, a digital data visualization platform displaying global, regional, and country-level immunization progress. The scorecard serves to focus attention and enable strategic actions around the measures visualized. To assess the scorecard's usability, appropriateness, and context for use, we interviewed 15 immunization officers working across five global regions. To further understand the implementation context, we also reviewed the characteristics of 15 public platforms visualizing population health data. We integrated thematic findings across both methods. Many platforms highlight service gaps and enable comparisons between geographies to foster political pressure for service improvements. We observed heterogeneity regarding the platforms' focus areas and participants' leading concerns, which were management capacity and resourcing. Furthermore, one-third of platforms were out of date. Results yielded recommendations for the scorecard, which participants felt was well suited to focus the attention of decision makers on key immunization data. A simpler design coupled with implementation strategies that more actively engage policymakers would better align the scorecard with other public platforms engaging intended users. For population health platforms to serve as effective accountability mechanisms, studying implementation determinants, including usability testing, is vital to meet stakeholder needs.

A mixed methods evaluation assessing the feasibility of implementing a PrEP data dashboard in the Southeastern United States

BACKGROUND

Alabama is one of seven priority states for the National Ending the HIV Epidemic Initiative due to a disproportionate burden of rural infections. To reverse growing infection rates, the state must increase its focus on prevention efforts, including novel strategies. One such approach is to utilize dashboards that visualize real-time data on the pre-exposure prophylaxis (PrEP) care continuum to assist in prioritizing evidence-based preventative care for those most vulnerable for HIV infection.

METHODS

We conducted a mixed methods evaluation to ascertain stakeholders' perceptions on the acceptability, feasibility, appropriateness, and usability of a PrEP care continuum dashboard, as well as gain insight on ways to improve the activities necessary to sustain it. Clinicians, administrators, and data personnel from participating sites in Alabama completed surveys (n = 9) and participated in key informant interviews (n = 10) to better understand their experiences with the prototype data dashboard and to share feedback on how it can be modified to best fit their needs.

RESULTS

Surveys and interviews revealed that all participants find the pilot data dashboard to be an acceptable, feasible, and appropriate intervention for clinic use. Overall, stakeholders find the pilot dashboard to be usable and helpful in administrative efforts, such as report and grant writing; however, additional refining is needed in order to reduce burden and optimize usefulness. Participants voiced concerns about their site's abilities to sustain the dashboard, including the lack of systematized PrEP protocols and limited funds and staff time dedicated to PrEP data collection, cleaning, and upload.

CONCLUSION

Study participants from clinics providing HIV prevention services, including PrEP, in Alabama voiced interest in sustaining and refining a data dashboard that tracks clients across the PrEP care continuum. Despite viewing the platform itself as an acceptable, feasible, and appropriate intervention, participants agreed that efforts need to be focused on standardizing PrEP data collection protocols in order to ensure consistent, accurate data capture and that limited funds and staff time are barriers to the sustained implementation of the dashboard in practice.

Mechanism of Impact of Big Data Resources on Medical Collaborative Networks From the Perspective of Transaction Efficiency of Medical Services: Survey Study

Background

The application of big data resources and the development of medical collaborative networks (MCNs) boost each other. However, MCNs are often assumed to be exogenous. How big data resources affect the emergence, development, and evolution of endogenous MCNs has not been well explained.

Objective

This study aimed to explore and understand the influence of the mechanism of a wide range of shared and private big data resources on the transaction efficiency of medical services to reveal the impact of big data resources on the emergence and development of endogenous MCNs.

Methods

This study was conducted by administering a survey questionnaire to information technology staff and medical staff from 132 medical institutions in China. Data from information technology staff and medical staff were integrated. Structural equation modeling was used to test the direct impact of big data resources on transaction efficiency of medical services. For those big data resources that had no direct impact, we analyzed their indirect impact.

Results

Sharing of diagnosis and treatment data (β=.222; P=.03) and sharing of medical research data (β=.289; P=.04) at the network level (as big data itself) positively directly affected the transaction efficiency of medical services. Network protection of the external link systems (β=.271; P=.008) at the level of medical institutions (as big data technology) positively directly affected the transaction efficiency of medical services. Encryption security of web-based data (as big data technology) at the level of medical institutions, medical service capacity available for external use, real-time data of diagnosis and treatment services (as big data itself) at the level of medical institutions, and policies and regulations at the network level indirectly affected the transaction efficiency through network protection of the external link systems at the level of medical institutions.

Conclusions

This study found that big data technology, big data itself, and policy at the network and organizational levels interact with, and influence, each other to form the transaction efficiency of medical services. On the basis of the theory of neoclassical economics, the study highlighted the implications of big data resources for the emergence and development of endogenous MCNs.