Factors That Influence Patient Satisfaction With the Service Quality of Home-Based Teleconsultation During the COVID-19 Pandemic: Cross-Sectional Survey Study.

BACKGROUND: Ontario stroke prevention clinics primarily held in-person visits before the COVID-19 pandemic and then had to shift to a home-based teleconsultation delivery model using telephone or video to provide services during the pandemic. This change may have affected service quality and patient experiences. OBJECTIVE: This study seeks to understand patient satisfaction with Ontario stroke prevention clinics' rapid shift to a home-based teleconsultation delivery model used during the COVID-19 pandemic. The research question explores explanatory factors affecting patient satisfaction. METHODS: Using a cross-sectional service performance model, we surveyed patients who received telephone or video consultations at 2 Ontario stroke prevention clinics in 2021. This survey included closed- and open-ended questions. We used logistic regression and qualitative content analysis to understand factors affecting patient satisfaction with the quality of home-based teleconsultation services. RESULTS: The overall response rate to the web survey was 37.2% (128/344). The quantitative analysis was based on 110 responses, whereas the qualitative analysis included 97 responses. Logistic regression results revealed that responsiveness (adjusted odds ratio [AOR] 0.034, 95% CI 0.006-0.188; P<.001) and empathy (AOR 0.116, 95% CI 0.017-0.800; P=.03) were significant factors negatively associated with low satisfaction (scores of 1, 2, or 3 out of 5). The only characteristic positively associated with low satisfaction was when survey consent was provided by the substitute decision maker (AOR 6.592, 95% CI 1.452-29.927; P=.02). In the qualitative content analysis, patients with both low and high global satisfaction scores shared the same factors of service dissatisfaction (assurance, reliability, and empathy). The main subcategories associated with dissatisfaction were missing clinical activities, inadequate communication, administrative process issues, and absence of personal connection. Conversely, the high-satisfaction group offered more positive feedback on assurance, reliability, and empathy, as well as on having a competent clinician, appropriate patient selection, and excellent communication and empathy skills. CONCLUSIONS: The insights gained from this study can be considered when designing home-based teleconsultation services to enhance patient experiences in stroke prevention care.

Service process factors affecting patients' and clinicians' experiences on rapid teleconsultation implementation in out-patient neurology services during COVID-19 pandemic: a scoping review.

BACKGROUND: The adoption of teleconsultation for outpatient neurology services was limited until the onset of the COVID-19 pandemic which forced many outpatient neurology services to rapidly switch to virtual models. However, it remains unclear how this change has impacted patients' and clinicians' perceptions of service quality. The purpose of this scoping review is to identify process factors that influence patients' and clinicians' experiences of outpatient teleconsultation services during COVID-19. METHODS: Arksey and O'Malley scoping review framework was used to search PubMed, Scopus, CINAHL, and PsycInfo for original peer-reviewed research studies that examined the experiences of synchronous teleconsultation between a clinician and patient in a home-setting since the World Health Organization announced the COVID-19 global pandemic. The service quality model SERVQUAL was used to conduct a deductive thematic analysis to identify the key factors that impacted the patients' and clinicians' perception of teleconsultation services. RESULTS: A total of nineteen studies published between January 1, 2020, and April 17, 2021, were identified. The most common service process factors affecting the patients' and clinicians' experiences of teleconsultation were technical issues, addressing logistical needs, communication, ability to perform clinical activities, appropriate triage, and administrative support. CONCLUSIONS: Our findings identified six key service process factors affecting the patients' and clinicians' teleconsultation experiences in outpatient neurology services. The need for improvement of triage process and standardizing administrative virtual care pathway are identified as important steps to improve patients and clinicians' teleconsultation experiences compared to pre-COVID era. More research is needed to assess outpatient neurology teleconsultation service quality from patients' and clinicians' perspectives.

Federated Deep Learning Architecture for Personalized Healthcare.

Using deep learning to advance personalized healthcare requires data about patients to be collected and aggregated from disparate sources that often span institutions and geographies. Researchers regularly come face-to-face with legitimate security and privacy policies that constrain access to these data. In this work, we present a vision for privacy-preserving federated neural network architectures that permit data to remain at a custodian's institution while enabling the data to be discovered and used in neural network modeling. Using a diabetes dataset, we demonstrate that accuracy and processing efficiencies using federated deep learning architectures are equivalent to the models built on centralized datasets.

Improving Patient Experience and Primary Care Quality for Patients With Complex Chronic Disease Using the Electronic Patient-Reported Outcomes Tool: Adopting Qualitative Methods Into a User-Centered Design Approach.

BACKGROUND: Many mHealth technologies do not meet the needs of patients with complex chronic disease and disabilities (CCDDs) who are among the highest users of health systems worldwide. Furthermore, many of the development methodologies used in the creation of mHealth and eHealth technologies lack the ability to embrace users with CCDD in the specification process. This paper describes how we adopted and modified development techniques to create the electronic Patient-Reported Outcomes (ePRO) tool, a patient-centered mHealth solution to help improve primary health care for patients experiencing CCDD. OBJECTIVE: This paper describes the design and development approach, specifically the process of incorporating qualitative research methods into user-centered design approaches to create the ePRO tool. Key lessons learned are offered as a guide for other eHealth and mHealth research and technology developers working with complex patient populations and their primary health care providers. METHODS: Guided by user-centered design principles, interpretive descriptive qualitative research methods were adopted to capture user experiences through interviews and working groups. Consistent with interpretive descriptive methods, an iterative analysis technique was used to generate findings, which were then organized in relation to the tool design and function to help systematically inform modifications to the tool. User feedback captured and analyzed through this method was used to challenge the design and inform the iterative development of the tool. RESULTS: Interviews with primary health care providers (n=7) and content experts (n=6), and four focus groups with patients and carers (n=14) along with a PICK analysis-Possible, Implementable, (to be) Challenged, (to be) Killed-guided development of the first prototype. The initial prototype was presented in three design working groups with patients/carers (n=5), providers (n=6), and experts (n=5). Working group findings were broken down into categories of what works and what does not work to inform modifications to the prototype. This latter phase led to a major shift in the purpose and design of the prototype, validating the importance of using iterative codesign processes. CONCLUSIONS: Interpretive descriptive methods allow for an understanding of user experiences of patients with CCDD, their carers, and primary care providers. Qualitative methods help to capture and interpret user needs, and identify contextual barriers and enablers to tool adoption, informing a redesign to better suit the needs of this diverse user group. This study illustrates the value of adopting interpretive descriptive methods into user-centered mHealth tool design and can also serve to inform the design of other eHealth technologies. Our approach is particularly useful in requirements determination when developing for a complex user group and their health care providers.

Contemplating case mix: A primer on case mix classification and management.

Case mix classifications are the frameworks that underlie many healthcare funding schemes, including the so-called activity-based funding. Now more than ever, Canadian healthcare administrators are evaluating case mix-based funding and deciphering how they will influence their organization. Case mix is a topic fraught with technical jargon and largely relegated to government agencies or private industries. This article provides an abridged review of case mix classification as well as its implications for management in healthcare.

Development of mental health quality indicators (MHQIs) for inpatient psychiatry based on the interRAI mental health assessment.

BACKGROUND: Outcome quality indicators are rarely used to evaluate mental health services because most jurisdictions lack clinical data systems to construct indicators in a meaningful way across mental health providers. As a result, important information about the effectiveness of health services remains unknown. This study examined the feasibility of developing mental health quality indicators (MHQIs) using the Resident Assessment Instrument - Mental Health (RAI-MH), a clinical assessment system mandated for use in Ontario, Canada as well as many other jurisdictions internationally. METHODS: Retrospective analyses were performed on two datasets containing RAI-MH assessments for 1,056 patients from 7 facilities and 34,788 patients from 70 facilities in Ontario, Canada. The RAI-MH was completed by clinical staff of each facility at admission and follow-up, typically at discharge. The RAI-MH includes a breadth of information on symptoms, functioning, socio-demographics, and service utilization. Potential MHQIs were derived by examining the empirical patterns of improvement and incidence in depressive symptoms and cognitive performance across facilities in both sets of data. A prevalence indicator was also constructed to compare restraint use. Logistic regression was used to evaluate risk adjustment of MHQIs using patient case-mix index scores derived from the RAI-MH System for Classification of Inpatient Psychiatry. RESULTS: Subscales from the RAI-MH, the Depression Severity Index (DSI) and Cognitive Performance Scale (CPS), were found to have good reliability and strong convergent validity. Unadjusted rates of five MHQIs based on the DSI, CPS, and restraints showed substantial variation among facilities in both sets of data. For instance, there was a 29.3% difference between the first and third quartile facility rates of improvement in cognitive performance. The case-mix index score was significantly related to MHQIs for cognitive performance and restraints but had a relatively small impact on adjusted rates/prevalence. CONCLUSIONS: The RAI-MH is a feasible assessment system for deriving MHQIs. Given the breadth of clinical content on the RAI-MH there is an opportunity to expand the number of MHQIs beyond indicators of depression, cognitive performance, and restraints. Further research is needed to improve risk adjustment of the MHQIs for their use in mental health services report card and benchmarking activities.

"Eye-T": information technology adoption and use in Canada's optometry practices.

BACKGROUND: While information technology (IT) is playing an increasing role in the delivery of optometric services, little specific information is available about how IT is changing the practice of optometry in Canada or whether optometry schools are adequately preparing their students to use this technology when they graduate. METHODS: Quantitative data on how IT is being used, as well as related barriers and potential benefits, were obtained in a survey of Canadian optometrists (N = 474). Three site visits were made to geographically dispersed Canadian optometry practices identified as exemplars of IT adoption. RESULTS: More than 96% of Canadian optometrists use computers in their practices, but fewer have integrated computers into their examination rooms. Optometrists are regularly using computers to manage their practices and medical record keeping. The automated perimeter is the clinical assessment technology most used (88.4%), followed by the autorefractor (83.9%) and the autokeratometer (72.2%). The anterior segment camera is the technology most likely to be acquired within the next 5 years (36.9%), followed by the scanning laser ophthalmoscope (26.8%). Major benefits of IT for optometrists include being better able to provide patients with images and information to explain results and to inspire greater patient confidence that the practice is state of the art. Perceived barriers include the need for frequent updates, lack of resources for training, and cost. There is support for increased exposure to IT as part of training in optometry. CONCLUSIONS: Use of IT in optometry practices is widespread and likely to continue to increase in the years ahead. IT may be a key element in the future success of optometry practices in an increasingly competitive marketplace. Perceptions of high investment and training costs are barriers to further adoption. Optometrists may benefit from increased exposure to IT as part of their training.

Nurse staffing and system integration and change indicators in acute care hospitals: evidence from a balanced scorecard.

This study examined relationships between financial indicators for nurse staffing and organizational system integration and change indicators. These indicators, along with hospital location and type, were examined in relation to the nursing financial indicators. Results showed that different indicators predicted each of the outcome variables. Nursing care hours were predicted by the hospital type, geographic location, and the system. Both nursing and patient care hours were significantly related to dissemination and benchmarking of clinical data.

Validation of Resource Utilization Groups version III for Home Care (RUG-III/HC): evidence from a Canadian home care jurisdiction.

BACKGROUND: The case-mix system Resource Utilization Groups version III for Home Care (RUG-III/HC) was derived using a modest data sample from Michigan, but to date no comprehensive large scale validation has been done. OBJECTIVES: This work examines the performance of the RUG-III/HC classification using a large sample from Ontario, Canada. METHODS: Cost episodes over a 13-week period were aggregated from individual level client billing records and matched to assessment information collected using the Resident Assessment Instrument for Home Care, from which classification rules for RUG-III/HC are drawn. The dependent variable, service cost, was constructed using formal services plus informal care valued at approximately one-half that of a replacement worker. RESULTS: An analytic dataset of 29,921 episodes showed a skewed distribution with over 56% of cases falling into the lowest hierarchical level, reduced physical functions. Case-mix index values for formal and informal cost showed very close similarities to those found in the Michigan derivation. Explained variance for a function of combined formal and informal cost was 37.3% (20.5% for formal cost alone), with personal support services as well as informal care showing the strongest fit to the RUG-III/HC classification. CONCLUSIONS: RUG-III/HC validates well compared with the Michigan derivation work. Potential enhancements to the present classification should consider the large numbers of undifferentiated cases in the reduced physical function group, and the low explained variance for professional disciplines.

Selection of key financial indicators: a literature, panel and survey approach.

Since 1998, most hospitals in Ontario have voluntarily participated in one of the largest and most ambitious publicly available performance-reporting initiatives in the world. This article describes the method used to select key financial indicators for inclusion in the report including the literature review, panel and survey approaches that were used. The results for five years of recent data for Ontario hospitals are also presented.

Financial benchmarks for Ontario hospitals.

Since the inception of the Hospital Reports in 1998, researchers have focused on three separate but related problems--how to measure performance; how to evaluate performance; and how to transfer knowledge about excellent performance to the field. This article describes a method to address the second problem--how to evaluate performance by benchmarking two indicators of financial performance and condition through three years of recent data for Ontario hospitals.

A province-wide study of the association between hospital resource allocation and length of stay.

The relationship between hospital resource allocation and clinical efficiency is poorly understood. Within the single-payer healthcare system in Ontario, Canada, the association between hospital spending patterns and length of stay was studied using data from 1117090 patient discharges in 1997/8 at 162 of 171 acute care hospitals. A weighted regression model was created using an overall hospital length of stay index (actual length of stay divided by predicted length of stay) as the dependent variable. Control variables included: hospital size, teaching activity, occupancy rate, rural location and geographic region. Four independent spending variables were defined as a percentage of total hospital spending: nursing, ambulatory care, administration and support, and diagnostics and therapeutics. The reduced regression model had an r-squared of 0.45. Across all spending variables, hospitals spending relatively too little or too much had significantly longer length of stay. Hospitals' overall pattern of resource allocation was also significantly associated with length of stay. Thus, measurable clinical effects can be seen with resource allocation decisions made by hospital management, supporting the need for rigorous decision-making processes. Future research should focus on exploring the nature of this relationship and the potential interdependencies among hospital services that cause this effect.