A Patient-Centered Framework for Evaluating Digital Maturity of Health Services: A Systematic Review

© Kelsey Flott, Ryan Callahan, Ara Darzi, Erik Mayer.Background: Digital maturity is the extent to which digital technologies are used as enablers to deliver a high-quality health service. Extensive literature exists about how to assess the components of digital maturity, but it has not been used to design a comprehensive framework for evaluation. Consequently, the measurement systems that do exist are limited to evaluating digital programs within one service or care setting, meaning that digital maturity evaluation is not accounting for the needs of patients across their care pathways. Objective: The objective of our study was to identify the best methods and metrics for evaluating digital maturity and to create a novel, evidence-based tool for evaluating digital maturity across patient care pathways. Methods: We systematically reviewed the literature to find the best methods and metrics for evaluating digital maturity. We searched the PubMed database for all papers relevant to digital maturity evaluation. Papers were selected if they provided insight into how to appraise digital systems within the health service and if they indicated the factors that constitute or facilitate digital maturity. Papers were analyzed to identify methodology for evaluating digital maturity and indicators of digitally mature systems. We then used the resulting information about methodology to design an evaluation framework. Following that, the indicators of digital maturity were extracted and grouped into increasing levels of maturity and operationalized as metrics within the evaluation framework. Results: We identified 28 papers as relevant to evaluating digital maturity, from which we derived 5 themes. The first theme concerned general evaluation methodology for constructing the framework (7 papers). The following 4 themes were the increasing levels of digital maturity: resources and ability (6 papers), usage (7 papers), interoperability (3 papers), and impact (5 papers). The framework includes metrics for each of these levels at each stage of the typical patient care pathway. Conclusions: The framework uses a patient-centric model that departs from traditional service-specific measurements and allows for novel insights into how digital programs benefit patients across the health system

Future broadband access network challenges

Copyright @ 2010 IEEEThe optical and wireless communication systems convergence will activate the potential capacity of photonic technology for providing the expected growth in interactive video, voice communication and data traffic services that are cost effective and a green communication service. The last decade growth of the broadband internet projects the number of active users will grow to over 2 billion globally by the end of 2014. Enabling the abandoned capacity of photonic signal processing is the promising solution for seamless transportation of the future consumer traffic demand. In this paper, the future traffic growth of the internet, wireless worldwide subscribers, and the end-users during the last and next decades is investigated. The challenges of the traditional access networks and Radio over Fiber solution are presented

Community detection and role identification in directed networks: understanding the Twitter network of the care.data debate

With the rise of social media as an important channel for the debate and discussion of public affairs, online social networks such as Twitter have become important platforms for public information and engagement by policy makers. To communicate effectively through Twitter, policy makers need to understand how influence and interest propagate within its network of users. In this chapter we use graph-theoretic methods to analyse the Twitter debate surrounding NHS Englands controversial care.data scheme. Directionality is a crucial feature of the Twitter social graph - information flows from the followed to the followers - but is often ignored in social network analyses; our methods are based on the behaviour of dynamic processes on the network and can be applied naturally to directed networks. We uncover robust communities of users and show that these communities reflect how information flows through the Twitter network. We are also able to classify users by their differing roles in directing the flow of information through the network. Our methods and results will be useful to policy makers who would like to use Twitter effectively as a communication medium

The shifted Jacobi polynomial integral operational matrix for solving Riccati differential equation of fractional order

In this article, we have applied Jacobi polynomial to solve Riccati differential equation of fractional order. To do so, we have presented a general formula for the Jacobi operational matrix of fractional integral operator. Using the Tau method, the solution of this problem reduces to the solution of a system of algebraic equations. The numerical results for the examples presented in this paper demonstrate the efficiency of the present method

Common sequences of emergency readmissions among high-impact users following AAA repair

Introduction The aim of the study was to examine common sequences of causes of readmissions among those patients with multiple hospital admissions, high-impact users, after abdominal aortic aneurysm (AAA) repair and to focus on strategies to reduce long-term readmission rate. Methods The patient cohort (2006-2009) included patients from Hospital Episodes Statistics, the national administrative data of all NHS English hospitals, and followed up for 5 years. Group-based trajectory modelling and sequence analysis were performed on the data. Results From a total of 16,973 elective AAA repair patients, 18% (n=3055) were high-impact users. The high-impact users among rAAA repair constituted 17.3% of the patient population (n=4144). There were 2 subtypes of high-impact users, short-term (7.2%) with initial high readmission rate following by rapid decline and chronic high-impact (10.1%) with persistently high readmission rate. Common causes of readmissions following elective AAA repair were respiratory tract infection (7.3%), aortic graft complications (6.0%), unspecified chest pain (5.8%), and gastro-intestinal haemorrhage (4.8%). However, high-impact users included significantly increased number of patients with multiple readmissions and distinct sequences of readmissions mainly consisting of COPD (4.7%), respiratory tract infection (4.7%) and ischaemic heart disease (3.3%). Conclusion A significant number of patients were high-impact users after AAA repair. They had a common and distinct sequence of causes of readmissions following AAA repair, mainly consisting of cardiopulmonary conditions and aortic graft complications. The common causes of long-term mortality were not related to AAA repair. The quality of care can be improved by identifying these patients early and focusing on prevention of cardiopulmonary diseases in the community

Regional variation in trajectories of long-term readmission rates among patients in England with heart failure

Background We aimed to compare the characteristics and types of heart failure (HF) patients termed “high-impact users”, with high long-term readmission rates, in different regions in England. This will allow clinical factors to be identified in areas with potentially poor quality of care. Methods Patients with a primary diagnosis of heart failure (HF) in the period 2008–2009 were identified using nationally representative primary care data linked to national hospital data and followed up for 5 years. Group-based trajectory models and sequence analysis were applied to their readmissions. Results In each of the 8 NHS England regions, multiple discrete groups were identified. All the regions had high-impact users. The group with an initially high readmission rate followed by a rapid decline in the rate ranged from 2.5 to 11.3% across the regions. The group with constantly high readmission rate compared with other groups ranged from 1.9 to 12.1%. Covariates that were commonly found to have an association with high-impact users among most of the regions were chronic respiratory disease, chronic renal disease, stroke, anaemia, mood disorder, and cardiac arrhythmia. Respiratory tract infection, urinary infection, cardiopulmonary signs and symptoms and exacerbation of heart failure were common causes in the sequences of readmissions among high-impact users in all regions. Conclusion There is regional variation in England in readmission and mortality rates and in the proportions of HF patients who are high-impact users

Prefrontal transcranial direct-current stimulation improves early technical skills in surgery

Background Studies applying transcranial direct-current stimulation (tDCS) to motor regions to enhance surgical skills have observed modest benefits in performance. Early surgical skills acquisition is known to be dependent on the prefrontal cortex (PFC) which could be a suitable target for performance enhancement in fields with high cognitive demand. Objective To assess whether prefrontal tDCS could improve early phases of surgical skill development. Methods In a randomized sham-controlled double-blind parallel design, 40 surgical novices performed an open knot-tying task repeated in three blocks; pre-, online- and post-tDCS. During online stimulation, participants were randomized to either active tDCS (2 mA for 15 min) to the prefrontal cortex (anode over F3, cathode over F4) or sham tDCS. Performance score (PS) was computed using a validated algorithm and introspective workload domains were assessed using a SURG-TLX questionnaire. Results There was no difference in demographics or PS between groups prior to receiving tDCS. PS significantly improved from pre-to online- (p < 0.001) and from pre-to post-tDCS (p < 0.001) in the active group only. Following active tDCS, PS was closer to the defined proficiency benchmark and significantly greater compared to sham (p = 0.002). Only the active group reported significantly improved temporal demand scores from pre-to online- (p = 0.004) to post-tDCS (p = 0.002). Conclusions This study demonstrates significantly improved early phase surgical-skill acquisition following prefrontal tDCS. Further work is required to determine the underlying neurophysiological mechanisms and whether the benefits observed are retained long-term