The organizational dynamics enabling patient portal impacts upon organizational performance and patient health: a qualitative study of Kaiser Permanente.

BackgroundPatient portals may lead to enhanced disease management, health plan retention, changes in channel utilization, and lower environmental waste. However, despite growing research on patient portals and their effects, our understanding of the organizational dynamics that explain how effects come about is limited.MethodsThis paper uses qualitative methods to advance our understanding of the organizational dynamics that influence the impact of a patient portal on organizational performance and patient health. The study setting is Kaiser Permanente, the world's largest not-for-profit integrated delivery system, which has been using a portal for over ten years. We interviewed eighteen physician leaders and executives particularly knowledgeable about the portal to learn about how they believe the patient portal works and what organizational factors affect its workings. Our analytical framework centered on two research questions. (1) How does the patient portal impact care delivery to produce the documented effects?; and (2) What are the important organizational factors that influence the patient portal's development?ResultsWe identify five ways in which the patient portal may impact care delivery to produce reported effects. First, the portal's ability to ease access to services improves some patients' satisfaction as well as changes the way patients seek care. Second, the transparency and activation of information enable some patients to better manage their care. Third, care management may also be improved through augmented patient-physician interaction. This augmented interaction may also increase the 'stickiness' of some patients to their providers. Forth, a similar effect may be triggered by a closer connection between Kaiser Permanente and patients, which may reduce the likelihood that patients will switch health plans. Finally, the portal may induce efficiencies in physician workflow and administrative tasks, stimulating certain operational savings and deeper involvement of patients in medical decisions. Moreover, our analysis illuminated seven organizational factors of particular importance to the portal's development--and thereby ability to impact care delivery: alignment with financial incentives, synergy with existing IT infrastructure and operations, physician-led governance, inclusive decision making and knowledge sharing, regional flexibility to implementation, continuous innovation, and emphasis on patient-centered design.ConclusionsThese findings show how organizational dynamics enable the patient portal to affect care delivery by summoning organization-wide support for and use of a portal that meets patient needs

Geisinger Health System: Achieving the Potential of System Integration Through Innovation, Leadership, Measurement, and Incentives

Presents a case study of a physician-led nonprofit healthcare group exhibiting the attributes of an ideal healthcare delivery system as defined by the Fund. Describes how its ProvenCare model improved clinical outcomes with reduced resource utilization

What\u27s in a Message? The Impact of Patient-Clinician Email Message Content on Patient Health Outcomes and Healthcare Utilization

Introduction In the upcoming chapters, we present our study findings as three papers ready for submission to peer-reviewed journals. The first paper describes the associations between taxa and the characteristics of the patients and clinic staff who exchange those messages. The second paper explores the associations between those taxa and patients’ healthcare utilization. The third paper presents associations between taxa and patient health outcomes for diabetes and hypertension. We conclude with how the three papers are related and highlight the importance of this research. Across the three papers, we reference a theory-based taxonomy we developed specifically for secure messaging. A number of researchers have created taxonomies to classify secure message content. Although these contained common themes, many were used only once or twice in published research and few classified content generated by clinic staff. We built our taxonomy upon commonly used themes from these existing classification systems. In contrast with other researchers, however, we leveraged theoretical constructs to group taxa and identify the concepts within messages that must be present for logical linkages between message content and patient outcomes. To identify why patients might outreach to clinicians during times of uncertainty, we referenced Mishel’s Uncertainty in Illness Theory (Mishel, 1988, 1999). We leveraged the framework developed by Street, Makoul, Arora, and Epstein (2009) to highlight patient task-oriented requests that might manifest in secure messages (e.g., to support self-care, satisfaction), and clinician-generated content that might support improved patient health outcomes. Our three papers present the first reports using this taxonomy and are the first to explore associations between taxa, patient outcomes, and the senders’ and receivers’ characteristics. We sampled patients with diabetes and/or hypertension to demonstrate that our taxonomy could be applied to different health conditions, and to highlight any differences in taxa use based on health condition. We included threads initiated and completed between January 1 and December 31, 2017. Our study included 2111 patients, of whom 49 percent initiated 7346 threads that included 10163 patient-generated messages and 8146 messages generated by 674 unique clinic staff (hereafter referred to as clinician-generated messages). Patient and Clinic Staff Characteristics Associated with Message Content In the first paper, we described the coding process and interrater and intrarater reliability derived from that process, and then presented our findings on the characteristics of the senders and receivers associated with selected taxa. We estimated both unadjusted and adjusted differences in characteristics associated with the use of each taxon. We assessed taxon use as a dichotomous variable that was positive if the patient or clinician sent or received at least one message coded with the selected taxon. For patient-generated taxa, we explored associations with the characteristics of the sender (which types of patients sent these taxa) and receiver (which types of clinic staff received these types of content). Similarly, we explored the associations between clinician-generated taxa and the characteristics of the sender (what types of clinic staff sent these taxa) and receiver (what types of patients were the recipients of this content). We created separate regression models for patient characteristics (demographic, geographic, health condition and status, and thread volume) and staff characteristics (staff type, specialty, and message volume). Our patient-level analyses included only the 1031 patients who initiated message threads using the patient portal. Our analyses found differences in taxa use by patients’ age, sex, race, health condition and status, and distance from clinic. Younger patients and females were less likely to share certain types of information with clinic staff (clinic updates among younger patients OR=0.77; 95% CI: 0.65-0.91; self-reporting biometrics by women OR=0.78; 95% CI: 0.62-0.98). Use of certain types of task-oriented requests varied by age (younger patients’ prescription refills OR=0.77; 95% CI: 0.65-0.90 and scheduling requests OR=1.41; 95% CI: 1.19-1.68) and race (black vs white requests for preventive care appointments OR=2.68; 95% CI: 1.30-5.51, requests for a new or changed prescription OR=0.72; 95% CI: 0.53-0.98, and laboratory or other diagnostic procedures OR=0.66; 95% CI: 0.46-0.95). Younger and uninsured patients were less likely to receive medical guidance from clinic staff (OR=0.84; 95% CI: 0.71-0.99 and OR=0.21; 95% CI: 0.06-0.72, respectively), but patients with public payers were two times more likely to receive medical guidance compared to patients with private payers (95% CI: 1.27-3.24). Females were less likely to receive confirmation that requests were fulfilled (OR=0.81; 95% CI: 0.68-0.97). These findings highlight differences in how patients used secure messaging to communicate with their clinic staff, which could result in differential access to care. Further, the differences in taxa use by clinic staff by patients’ characteristics might further exacerbate existing disparities in care and highlight opportunities for training and education to reduce these discrepancies. Healthcare Services Utilization Associated with Message Content The Street, Makoul, et al. (2009) framework highlights access to care as an intermediate outcome in the pathway between health outcomes and communication functions such as information exchange, enabling self-care, and making decisions. Patients reported that effective communication delivered through secure messaging prevented unnecessary appointments (Alpert, Markham, Bjarnadottir, & Bylund, 2019); however, prior studies that explored links between secure messaging and healthcare utilization only considered message volume, not what was said in those messages. Our second paper is the first to explore whether content is associated with healthcare utilization. We measured utilization in four ways: number of outpatient visits, number of emergency department visits, number of inpatient visits, and medication adherence. We created separate medication adherence dichotomous variables for diabetes and hypertension, based on having an average condition-specific medication possession ratio greater than 0.8 (Clifford, Perez-Nieves, Skalicky, Reaney, & Coyne, 2014; Khunti, Seidu, Kunutsor, & Davies, 2017; Krass, Schieback, & Dhippayom, 2015; Schulz et al., 2016). We measured our independent variables as the taxon prevalence among patient- or clinician-generated taxa, as appropriate. Our covariates included the patient characteristics described in the first paper. To estimate incidence rate ratios for the three visit dependent variables, we conducted Poisson regressions with robust variance estimation (Hilbe, 2014). We estimated the odds of medication adherence associated with each taxon using logistic regression. In unadjusted analyses, we found that patients who initiated message threads had higher numbers of outpatient visits (p\u3c0.0001) and better hypertension medication adherence (p\u3c0.01), compared to patients who did not initiate threads. Among patients who initiated message threads, we identified a positive association between emergency department visits and prevalence of request denials from clinic staff (IRR=1.18; 95% CI: 1.03, 1.35) and patients’ requests for follow-up appointments (IRR=1.15; 95% CI: 1.07-1.23), as well as between clinic non-response and the number of outpatient visits (IRR=1.02; 95% CI: 1.00, 1.03). We identified an inverse association between hypertension medication adherence and patients’ appointment reschedule requests (OR=0.87; 95% CI: 0.79-0.96). These findings highlight opportunities for future research about the use of secure messaging to influence care delivery and access to care. Patient Health Outcomes Associated with Message Content Patients whose uncertainty in their illness is addressed experience less stress, leading to better health outcomes (Mishel, 1988). Through appropriate communication functions with clinicians, patients develop better understanding of their condition and how to manage it and may have improved access to care and self-care skills, which leads to better outcomes (Street, Makoul, et al., 2009). Our third paper describes the first study to assess the types of message content associated with improved health outcomes. We examined changes in patients’ glycemic index (A1C) for patients with diabetes and changes in diastolic (DBP) and systolic blood pressure (SBP) among patients with hypertension, comparing patients who sent or received messages with selected taxa to (1) those who sent other types of messages and (2) those who did not initiate threads in 2017. We measured outcome changes as the difference between baseline (the last measured value in 2016) and endpoint (the first measured value reported in 2018) measures. Similar to the analyses conducted for Paper 2, our independent variables were the prevalence of each taxon by patient, where the denominator was the number of patient- or clinician-generated taxa, as appropriate for the selected taxon. Analyses included only patients with the selected condition: 811 patients with diabetes only, 787 patients with hypertension only, and 513 patients with both conditions. We used linear regression to identify associations between the outcomes and each taxon. In unadjusted analyses, we found that patients who initiated threads had lower endpoint A1Cs (p=0.01) compared to patients who did not initiate threads. We observed improvements in A1C among patients who sent information seeking messages (b=-0.07; 95% CI: -0.13, -0.00). We also observed improved SBP associated with clinic non-response to patients’ threads (b=-0.30; 95% CI: -0.56, -0.04), staff acknowledgement and fulfillment of patients’ requests (b=-0.30; 95% CI: -0.58, -0.02), and patients’ complaints (b=-4.03; 95% CI: -7.94, -0.12). Poorer outcomes were associated with information sharing messages among patients with diabetes (b=0.08; 95% CI: 0.01, 0.15), and deferred information sharing by clinic staff among patients with hypertension (SBP b=1.29; 95% CI: 0.4-2.19). In addition, among patients with either condition, we observed positive associations between outcome and patient- and clinician-generated appreciation and praise messages with effect sizes ranging from 0.4 (A1C) to 5.69 (SBP). These findings demonstrate associations between outcomes and message content and further emphasize the need for training and education of clinic staff on appropriate use of secure messaging to prevent exacerbation of health disparities due to differential communication delivered through this modality. Conclusion We identified patient characteristics associated with patients’ use of taxa; not surprisingly, patients’ use of taxa varied by age, sex, and race. Taxa use varied by clinic staff characteristics consistent with the triage systems employed by most healthcare organizations (Heyworth et al., 2013; Ozkaynak et al., 2014; Wooldridge, Carayon, Hoonakker, Musa, & Bain, 2016). We also identified differences in staff’s taxa use based on the characteristics of the patient to whom they were sending the message. We further identified associations between taxa and healthcare utilization and health outcomes. If certain types of patients use taxa less frequently, and these taxa are associated with better outcomes or more appropriate utilization, then that presents opportunities to target those populations for education to shift their use of secure messaging. Further, if clinician-generated message content is associated with improved outcomes and clinic staff are not equitably sharing that content with all patients, there is an opportunity for education and training. Our research is a set of first-of-its-kind analyses that highlight differences in taxa use by both patients and clinicians and demonstrates the associations between those taxa and patient outcomes. Healthcare administrators and clinic staff should be aware of these associations and consider mitigation strategies to improve equitable secure messaging use by their staff and across their patient populations. The studies shared several limitations discussed in more detail in the papers themselves. These limitations included a need for more specificity in the taxa definitions and more rigorous coding processes, the lack of temporal indicators in the analysis, and limited patient and clinical characteristics. The analyses that incorporated A1C measurements suffered from significant missing data. Sample size for some taxa was limited so that the algorithms did not converge. The analyses were based on single taxa, which represented only one component of the overall thread discussion. Finally, our message sample included only those messages saved to patients’ charts, which likely led to an underrepresentation of taxa and clinic non-response. We highlighted a number of opportunities for future research across the three studies. Consideration should be given to refining taxa definitions and applying more rigorous coding practices, incorporating temporal elements into the analyses to provide context and support assessments of causality, adding relevant covariates such as message reading level or patients’ health literacy levels, and exploring other proximal and intermediate outcomes identified in the Street, Makoul, et al. (2009) framework. We also strongly recommend examining the impact of taxa pairings: analyses that consider the call-and-response nature of the full conversation occurring within the thread

The impact of digital patient portals on health outcomes, system efficiency, and patient attitudes: Updated systematic literature review

Background: Patient portals are becoming increasingly popular worldwide even though their impact on individual health and health system efficiency is still unclear. Objective: The aim of this systematic review was to summarize evidence on the impact of patient portals on health outcomes and health care efficiency, and to examine user characteristics, attitudes, and satisfaction. Methods: We searched the PubMed and Web of Science databases for articles published from January 1, 2013, to October 31, 2019. Eligible studies were primary studies reporting on the impact of patient portal adoption in relation to health outcomes, health care efficiency, and patient attitudes and satisfaction. We excluded studies where portals were not accessible for patients and pilot studies, with the exception of articles evaluating patient attitudes. Results: Overall, 3456 records were screened, and 47 articles were included. Among them, 11 studies addressed health outcomes reporting positive results, such as better monitoring of health status, improved patient-doctor interaction, and improved quality of care. Fifteen studies evaluated the impact of digital patient portals on the utilization of health services with mixed results. Patient characteristics were described in 32 studies, and it was reported that the utilization rate usually increases with age and female gender. Finally, 30 studies described attitudes and defined the main barriers (concerns about privacy and data security, and lack of time) and facilitators (access to clinical data and laboratory results) to the use of a portal. Conclusions: Evidence regarding health outcomes is generally favorable, and patient portals have the potential to enhance the doctor-patient relationship, improve health status awareness, and increase adherence to therapy. It is still unclear whether the use of patient portals improves health service utilization and efficiency

Patient Engagement: The Impact of Electronic Patient Portal Use on Missed Appointments in Patients with Diabetes, a Retrospective Study

Background: This retrospective observational chart review evaluated the use of the MyChart® patient portal as a viable tool for engaging patients. Engagement was measured as fewer missed appointments (no-shows and same-day cancellations). Objectives: To determine who uses the MyChart® patient portal in a chronically ill population of adult patients with diabetes and assess the association of portal use with missed appointments. Methods: The medical records of adult patients (18-80) with a diagnosis of Type 1 and/or Type 2 Diabetes Mellitus (DM) were reviewed (N=7,795). The efficacy of the MyChart® patient portal at reducing missed appointments was assessed by comparing patients who use the portal (evidenced by two or more log-ins during the study period) to those who do not. Results: In this study, 43.7% of adult patients with diabetes used a portal account. Portal users were predominantly female, non-Black, married, non-smokers, and had at least one of the comorbidities often associated with diabetes (hypertension, hyperlipidemia, and/or obesity). Portal users were on average 58.8 years old. Use of the MyChart® patient portal was independently associated with a reduced no-show rate (4.7% for portal users compared to 12.4% for nonusers). However, when patients who activated a portal account during the study period were subjected to a within-subjects analysis, the mean missed appointment percentage was not statistically significantly different when patients had an activated portal account compared to when they did not. Thus, the portal may be a useful tool for engaging chronically ill patients but it is only one component to appointment arrivals. Conclusion: Conclusions from this study are limited given the retrospective design. Nonetheless, the findings suggest that the patient portal is effective at engaging chronically ill patients and thus warrants greater merit. The portal may also be a useful tool for reducing missed appointments in patients with chronic illness who would greatly benefit from appointment adherence. Future research should focus on testing the hypotheses generated in a prospective manner

Data Analytics and Modeling for Appointment No-show in Community Health Centers

Objectives: Using predictive modeling techniques, we developed and compared appointment no-show prediction models to better understand appointment adherence in underserved populations. Methods and Materials: We collected electronic health record (EHR) data and appointment data including patient, provider and clinical visit characteristics over a 3-year period. All patient data came from an urban system of community health centers (CHCs) with 10 facilities. We sought to identify critical variables through logistic regression, artificial neural network, and naïve Bayes classifier models to predict missed appointments. We used 10-fold cross-validation to assess the models’ ability to identify patients missing their appointments. Results: Following data preprocessing and cleaning, the final dataset included 73811 unique appointments with 12,392 missed appointments. Predictors of missed appointments versus attended appointments included lead time (time between scheduling and the appointment), patient prior missed appointments, cell phone ownership, tobacco use and the number of days since last appointment. Models had a relatively high area under the curve for all 3 models (e.g., 0.86 for naïve Bayes classifier). Discussion: Patient appointment adherence varies across clinics within a healthcare system. Data analytics results demonstrate the value of existing clinical and operational data to address important operational and management issues. Conclusion: EHR data including patient and scheduling information predicted the missed appointments of underserved populations in urban CHCs. Our application of predictive modeling techniques helped prioritize the design and implementation of interventions that may improve efficiency in community health centers for more timely access to care. CHCs would benefit from investing in the technical resources needed to make these data readily available as a means to inform important operational and policy questions

Organizing the U.S. Health Care Delivery System for High Performance

Analyzes the fragmentation of the healthcare delivery system and makes policy recommendations -- including payment reform, regulatory changes, and infrastructure -- for creating mechanisms to coordinate care across providers and settings

Improving Vaccination Rates in Pediatric Primary Care

Objectives: In a small, rural pediatric primary care clinic, the effectiveness of electronic patient portal reminders were evaluated at improving vaccination rates for school required immunizations. Methods: A quality improvement project was initiated utilizing The Social Ecological Model. All pediatric patients were sent reminders who were under-immunized. This QI project evaluated the effectiveness of vaccine reminders on the improvement of immunization rates in the clinic Results: Total number of fully-vaccinated patients within the practice improved (2%) and patients under-immunized decreased by 1%. 87 immunizations were given to patients were given to patients who were under-immunized and an average of 10% of recorded un-vaccinated patient prior to intervention received at least one immunization. Conclusions: Implementation of vaccine reminders into a rural primary care pediatric practice improved patient compliance with school-required vaccines. Although immunization rates improved, the practice continues to see higher rates of under-immunized patients compared to state reporting data. Key Words: Vaccines, improvement, pediatric, primary care, portal reminder, vaccination rate

An Enhanced Enrollment Process to Impact Appointment Compliance in the HF-Optimize Clinic

Background The HF-Optimize clinic showed improved utilization of guideline-directed medical therapy (GDMT) along with improved clinical outcomes from 2018 to 2020. Appointment compliance was poor with only 44% of patients completing all HF-Optimize visits. Missed appointments led to worse health outcomes, fragmented care, and provider inefficiencies. Interventions to improve appointment compliance are vital to improving heart failure outcomes. Objective The purpose of this quality improvement project is to evaluate the impact that an enhanced enrollment process has on appointment compliance in a culturally diverse, adult population referred to the HF-Optimize clinic at Nebraska Medicine. Methods This prospective quality improvement project evaluated an enhanced enrollment process for patients scheduled for their first visit to the HF-Optimize clinic between March 1, 2022, and August 31, 2022. The enhanced enrollment process included tracking reasons for missed appointments, deployment of an educational video, and instructing patients to enroll in MyChart. Evaluation of the enhanced enrollment process included a survey assessing if the patient watched the video, if they found the video helpful, and if it contributed to them coming to their first appointment. Demographics and MyChart enrollment were collected. Results A total of 138 patients were referred to the HF-Optimize clinic between March 1, 2022 and August 31, 2022. Patients were a mean age of 60.9 +/- 3.5 years, 42% female, and 33% non white. Of those referred, 98 patients came to their first appointment (71%). There were 59 video surveys completed. There were 50 patients that reported signing up for MyChart (85%). There were 15 patients that reported watching the HF-Optimize video. The majority of patients (59%) rated the video between 8 to 10 for helpfulness. Conclusions Appointment compliance improved during the project period. Patients completing the video survey found it to be helpful in describing the HF-Optimize clinic. Due to the small number of completed surveys, a relationship between video viewing and appointment compliance could not be determined. Future studies should utilize electronic applications that track individual use. Keywords: Heart Failure, Optimize, appointment complianc

Exploring Strategies for Reducing Patient Failure to Keep Scheduled Appointments

High no-show rates in the ambulatory setting lead to underutilized resources, decreased clinic revenue, and lower productivity. The purpose of this single case study was to explore strategies that administrators used to maintain acceptable no-show rates and maintain the sustainability of the healthcare practice. The target population for this study included local chapter members of a professional healthcare organization that provided access to practice managers and administrators in the Las Vegas, Nevada regional area where there are a large number of practices that are not part of a health system; the sustainability of these practices is dependent on allocation of adequate resources. The conceptual framework for this study was Kotter\u27s 8-step change management model that uses 8 steps for successfully managing change within the organization and developing quality improvement initiatives. Data collection included semistructured interviews with 2 practice leaders, observation of the organization\u27s practice management and appointment scheduling systems, and a review of internal reports related to appointment trends and no-show rates. Based on the data analysis using deductive and open coding techniques, 3 distinctive themes emerged from the data: appointment booking strategies, appointment reminder strategies, and provider flexibility. The results of this study might positively affect positive social change by helping administrators improve access to care in an outpatient setting through improved appointment utilization and improve patient care outcomes with more appointment availability