Tele-diagnostic and therapeutic guidance in urology

Improving access to urologists through an electronic consultation service

INTRODUCTION

Access to specialist services is limited by wait times and geographic availability. Champlain Building Access to Specialist Advice (BASE) has been implemented in our service region to facilitate access to specialists by primary care providers (PCPs). Through a secure web-based system, PCPs are able to send eConsults instead of requesting a formal in-office consultation.

METHODS

Urology eConsults completed through the Champlain BASE service from March 2013 to January 2015 were analyzed. Each consult was characterized in regard to the type of question asked by the referring physician and the clinical content of the referral. Using the mandatory close-out surveys, we analyzed rates of referral avoidance, physician satisfaction, and overall impact on patient care.

RESULTS

Of 190 eConsultations, 70% were completed in less than 10 minutes. The most common clinical questions related to the interpretation of imaging reports (16%) and tests to choose for investigating a condition (15%). The most common diagnoses were hematuria (13%) and renal mass (8%). In 35% of cases, referral to a urologist had originally been contemplated and was avoided. In 8% of cases, a PCP did not believe a consultation was initially needed, but a referral was ultimately initiated after the eConsultation.

CONCLUSIONS

Our study shows that although certain clinical presentations still require a formal in-person urological consultation, eConsultations can potentially reduce unnecessary clinic visits while identifying patients who may benefit from early urological consultation. Through both these mechanisms, we may improve timely access to urologists.

Data Warehousing and Decision Support in Mobile Wireless Patient Monitoring

The recent advances in wireless communication technologies have made possible the development of wireless systems for monitoring the health and disease status of patients, in both in-patient hospital settings and outside. The volume of patient monitoring data requires Data Warehousing technologies for storage intended for analysis. The analysis is performed by Decision Support Systems (DSS) that provide clinical diagnoses and treatment methodology consistent with the urgency. The clinical DSS is critical in the analysis of a volume of data beyond the capabilities of a healthcare professional, and is effective in reducing workload, saving money, and providing better care for patients. This chapter also analyzes the technical aspects of the process.

Estimating the success of e-health collaborative services: the THEMIS framework

This study proposes a prototype framework (THEMIS) for estimating algebraically the success (S) of the electronic health collaborative services (e-HCS) and examines two hypotheses: first, that the S estimation of an e-HCS, developed by a third-party vendor, demands a 'shrunk formative model' and second that causal relationships between the involved dimensions (FFP, CO, COSTS) do exist, and their parameters affect the S - from weakly to strongly and vice-versa. A formative model was shrunk to generate three causal dimensions ('Collaborators Objections', 'Costs', 'Fitness for Purpose'). Then, the new framework (THEMIS) was enriched with a causal loop diagram, a prototype scoring method, (termed 'polarisation method') and 42 questions. In order to investigate the feasibility of the THEMIS framework, we estimated the S of 15 e-HCSs and the algebraic outcomes (E(S)) were compared - one by one - with usage categories produced by a commercial software. Our findings supported the initial hypotheses. The S was estimated with accuracy; for the e-HCSs with a weak E(S) the commercial software verified that they remained idle several times during the 11-month evaluation period, whereas the e-HCS with a strong E(S) the commercial software verified that they were used frequently. Frameworks, such as the one proposed, which are based on both qualitative and quantitative methods, may provide significant support on the S estimation field.