According to the Canadian Cancer Society, half of Ontario’s population will be diagnosed with cancer in their lifetime. Many patients being assessed for cancer however become overwhelmed when having to manage information overload, many appointments with different instructions and locations, and recommendations on how to improve their lifestyle. This causes much anxiety and uncertainty among patients. Some cancer assessment clinics offer some guidance in the form of paper-based patient navigators, which provide much reliable information to patients but are limited in terms of dynamic updates to appointments, opportunities for sharing knowledge between healthcare providers and patients, and of patients supporting each other. This thesis proposes a new web-based, mobile, and user-friendly virtual patient navigator application framework named Care Ami, which incorporates the information found in an existing paper-based navigator along with the new features such as remote updates to personal care paths and calendars, personalized navigation guidance, sharing of symptoms/medications information, and peer group support. Unlike existing solutions, Care Ami is configurable to support multiple types of diseases (e.g., lung cancer and breast cancer). This application is evaluated through testing and the usage of heuristic evaluation guidelines related to usability, and a comparison with related work highlights its many benefits.

Despite the advances in antiretroviral therapy (ART) a disproportionate number of people living with HIV (PLWH) remain limited in their access and use of health care and treatment, including racial/ethnic minorities, persons with mental health and substance use disorders and persons experiencing homelessness or unstable housing. Patient navigation programs have emerged as a potential effective and efficient use of resources to reach and engage these vulnerable populations as part of the HIV service delivery system. This dissertation contains three chapters that aim to identify and assess the performance and mechanisms for navigation programs working with PLWH who experience homelessness and co-occurring substance use and mental health disorders. Study 1, Developing a Reliable and Valid Composite Measure of Effectiveness for HIV Navigation Programs for PLWH who are homeless/unstably housed, describes the development of a multidimensional outcome measure to assess the performance of navigation programs for this population. The composite measure was comprised of seven indicator variables: linkage to care, retention in care and adherence to treatment, patient experience of care, physical and mental health related quality of life and housing stability. Using multivariate analyses, a 3 item measure of retention, adherence, and housing stability was found to have high goodness of fit and strong predictive association with viral suppression. Study 2, Classifying Components of HIV Navigation Programs for PLWH who are homeless/unstably housed, used a latent-class analysis to identify common patterns of activities, modalities of communication, location of work, and staff composition among highest utilizers of services. Results showed that types of activities, work setting and modality of contact were significantly associated with increased retention in care. No difference in activity, staffing patterns, work setting or modality of communication of navigation programs were found on viral suppression rates. Study 3, An Economic Evaluation of HIV Navigation Programs Working with PLWH who are Homeless/Unstably housed assessed costs and net benefits of these navigation programs overall and in subpopulations. Cost utility and net benefit analyses performed indicated that navigation programs for PLWH who are homeless/unstably housed are a potential efficient investment of resources at various willingness-to-pay thresholds. Navigation programs provide a myriad of services for PLWH who are homeless/unstably housed and must be flexible in their approach to address the multiple medical and psychosocial needs of this population. The results of this dissertation provide information for improving the design, measuring performance and costs and benefits of navigation programs as part of the HIV service delivery system for PLWH who experience homelessness. / 2020-06-30T00:00:00Z

BACKGROUND: There is a need to identify the populations at high risk of nonadherence to outpatient lung cancer appointments in order to reduce the delay from diagnosis to treatment. The patient navigation system, which helps patients with barriers navigate the health care system, was examined to see if the correct high-risk groups were being addressed. METHODS: A case-control study with 195 subjects from the lung cancer clinics at Boston Medical Center (BMC) was conducted examining three nonadherence case groups: no-shows (n=40), cancelations (n=64) and combined (n=20). Nonadherence was defined as any patient who was a no-show for at least one appointment or who canceled more than one appointment over the three month study period. The combined group incorporated both of these factors. The patients were stratified by 10 patient characteristics, including patient navigation. Odds ratios (ORs) and 95% confidence intervals (CIs) were used for the analysis. A second analysis was done on patients in the patient navigation program (n=33) to determine if the high risk groups identified were being addressed. This was done using ORs and 95% CIs. RESULTS: This study has shown that there are certain patient groups in the lung cancer clinics at BMC that are at higher risk of being nonadherent to lung cancer outpatient appointments. Among those are Hispanic/Latino patients, Spanish and Haitian Creole speaking patients, small cell lung cancer (SCLC) patients, and those patients who have Medicaid, and with late stage lung cancer patients at significantly higher risk (no-shows: OR-5.26 (1.85, 14.95), cancelations: OR-2.49 (1.12, 5.54), combined: OR-12.49 (1.48, 105.46)). Patients in the patient navigation system were also found to be at significantly higher risk of nonadherence (no-shows: OR-3.85 (1.72, 8.65), cancelations: OR-4.13 (1.89, 9.00), combined: OR-5.15 (1.93, 13.72)) than those not in the program. Some patients were also found to be at significantly decreased odds of nonadherence, including those who were: 1000-1999 days post diagnosis (no-shows: OR-0.14 (0.03, 0.59), cancelations: OR-0.20 (0.06, 0.65), combined: OR-0.07 (0.01, 0.64)); 2000-2999 days post diagnosis (no-shows: OR-0.09 (0.01, 0.80), cancelations: OR-0.06 (0.01, 0.50)); aged 71-75 (cancelations: OR-0.25 (0.08, 0.79)). The subset analysis with the patient navigation data yielded no statistically significant results. CONCLUSIONS: The study identified high-risk populations within the total lung cancer population at BMC that should be addressed by the patient navigation program. This study demonstrated that while the program does have its flaws, it is decreasing the odds of nonadherence of many of the high-risk populations.

No description available.

BACKGROUND: Over the past 10 years, molecular-based and targeted therapies in oral forms have emerged and continue to change the landscape of cancer care and care delivery. While cancer treatments traditionally have been administered at the hospital, oral anti-cancer medications (OAM) can be taken by patients at the comfort and convenience of their homes. However, this also creates implications for ensuring that patients take their oral chemotherapies correctly, timely, and safely, all of which can impact outcomes and tolerance. Studies have shown concerning gaps in patients’ knowledge of taking and handling their OAM, including lower rates of adherence. Interventions have largely consisted of a combination of nurse- and pharmacist-led approaches along with the use of various educational and reminder tools. However, few studies have examined the potential of an intervention led by a pharmacist and a medication (patient) navigator. OBJECTIVE: This ongoing pilot study aims to assess the feasibility of the intervention, the impact on patients’ understanding and adherence to their oral anti-cancer medications, and the patient perceptions of the helpfulness of the intervention. METHODS: Patients who were initiating oral chemotherapy were enrolled at Tufts Medical Center Cancer Center, which was the study site for this pilot intervention. Study participants met with the Specialty Pharmacist and Medication Navigator for their initial education session and teach-back using the Oral Agent Teaching Tool (MOATT). They were also given Information Sheets and individualized Calendars for their OAM. The Pharmacist and/or Navigator subsequently followed up with the participants for three more check-ins and educational boosters. Participants completed study measures including the self-reported Adherence Measure, MD Anderson Symptom Inventory, and study evaluation. RESULTS: A total of 37 patients have so far been enrolled in the study and completed their initial education session with the Pharmacist and 33 of those patients completed the Navigator-led booster check-in approximately one week later. These patients are receiving ongoing follow-up for their two remaining check-ins in the study. After the first teach-back with the Pharmacist, patients largely showed sufficient understanding of how to take and handle their medication. This level of understanding was sustained a week later at the Navigator booster. Despite high levels of self-reported adherence, patients showed insufficient understanding of refill logistics. Patients were highly satisfied with the intervention and had found both the check-ins and the educational tools provided useful. CONCLUSION: This Pharmacist- and Navigator-led intervention was found to be feasible to deliver, capable in enhancing patient understanding and adherence to their medications, and helpful to the patients throughout taking their OAM.

Introduktion: Regionalt cancercenter (RCC) har i samarbete med Sveriges kommuner och landsting (SKL) beslutat att varje patient med en cancerdiagnos ska bli tilldelad en kontaktsjuksköterska. Syfte: Att undersöka hur väl implementeringen av kontaktsjuksköterskan har fungerat inom den onkologiska vården på Akademiska sjukhuset i Uppsala samt om de kontaktsjuksköterskor som finns arbetar i enlighet med SKL:s definition. Metod: Kvalitativ metod med semi-strukturerade intervjuer av åtta patienter med olika cancerdiagnos. Huvudresultat: Fem av de åtta deltagarna blev tilldelade en kontaktsjuksköterska eller motsvarande när de fick sin diagnos, antingen i direkt samband med diagnosen eller i ett senare skede. Resultaten tyder på att de patienter som ingår i någon slags forskningsstudie upplever sig ha en kontaktsjuksköterska som underlättar för dem och även deras behandling. Patienter som inte ingår i läkemedelsstudier upplever inte att kontaktsjuksköterskan har arbetat enligt SKL:s definition. Slutsats: Forskningssjuksköterskor är den personalkategori som arbetar närmast definitionen av kontaktsjuksköterska. Brister gällande sjukvårdens tillgänglighet, förmåga att ge fullgod information samt att erbjuda anhöriga stöd har uppmärksammats. Ytterligare forskning måste utföras för att resultaten ska kunna bekräftas. / Introduction:  The Regional Cancer Centre in Sweden (RCC), in collaboration with Local Authorities and Regions (SKL) has decided that every patient with a diagnosis of cancer should be assigned a contact nurse/patient navigator. Objective: To examine how well the implementation of this has been within the oncology care at the University Hospital in Uppsala and whether the patient navigators are working according to the definition decided by SKL. Methods: Qualitative methodology with semi-structured interviews of eight patients with different types of cancer. Main results: Five of the eight participants were assigned a patient navigator or equivalent at the time of their diagnoses or at a later stage. The result suggests that patients included in this study perceive that they have been provided with a patient navigator who facilitates their treatment. Patients assigned with a patient navigator but not included in drug trials do not feel that the patient navigators met the requirements asked by SKL. Conclusion: Research Nurses are the personnel who work most closely with SKLs definition of the patient navigator. Shortcomings regarding health care availability, the ability to provide adequate information and to offer family support have been noted. Further research must be carried out for the results to be confirmed.

Background: Ballad Health participates in the Centers for Medicare and Medicaid Services’ (CMS) Accountable Health Communities (AHC) model. The AHC model is evaluating if universal screening, referral, and navigation services for health-related social needs (HRSN) can improve outcomes and reduce unnecessary utilization and costs of health care services. To ensure the evaluation of the model has sufficient statistical power, navigation services are expected to be provided to a minimum number of individuals. The purpose of this study is to analyze the characteristics of Ballad Health’s AHC navigation services that could be modified to improve opt-in rates. Methods: The primary outcome measure was identified as whether a beneficiary contacted via telephone opted-in or –out of the navigation program. Andersen’s Behavioral Model for Health Service Use was used as the conceptual framework for selecting covariates of interest. Enabling factors were of primary interest because alternate interventions may be designed around them. Data was pulled for the time period of November 17, 2018 through February 14, 2019. Where possible, covariates were associated with data from CMS’ AHC Data Template v3.1 to accommodate replication for all AHC bridge organizations, though additional internally-collected data, which may not be available for all bridge organizations, were needed for some variables. Chi-squared tests were performed for each covariate. Results: No statistical differences were found for the primary covariates of interest. Opt-in rates by Navigator were lowest for Navigator 5 and highest for Navigator 4 (67.53% and 88.24%). Opt-in rates by weekday of decision were lowest on Thursdays and highest on Wednesdays (64.91% and 77.42%). Opt-in rates based on time of day were lowest between 8:00am and 9:59am, and highest between 12:00pm and 1:59pm (62.50% and 100%). Opt-in rates were lowest when the decision was made six days after the screening and highest when made the same day (53.57% and 83.33%). Opt-in rates were lowest when there were five weekdays between screening and navigation decision, and highest when there were three weekdays between the screening and decision (60% and 90%). Other non-process covariates of interest that were statistically significant for opt-in rates were the presence of either food, safety, or utility needs. Conclusions: Several groups had higher opt-in rates that were not statistically significant; small sample sizes may have impacted the significance of these differences. For example, opt-in rates were higher when made the same day as the screening than when made one day after (83.33% and 74.79%). However, only 18 beneficiary decisions were made on the same day, while 119 were made one day after. Increasing the number of same-day phone call attempts may be a method to improve opt-in rates. Importantly, date and time data for contact attempts before a beneficiary decides to opt-in or opt-out were unavailable as of the time of the analysis. These data are captured and will be added to the analysis when available, which could provide more insight into whether a beneficiary is more likely to opt-in or opt-out.

Background: Ballad Health participates in the Centers for Medicare and Medicaid Services’ (CMS) Accountable Health Communities (AHC) model. The AHC model is evaluating if universal screening, referral, and navigation services for health-related social needs (HRSN) can improve outcomes and reduce unnecessary utilization and costs of health care services. To ensure the evaluation of the model has sufficient statistical power, navigation services are expected to be provided to a minimum number of individuals. The purpose of this study is to analyze the characteristics of Ballad Health’s AHC navigation services that could be modified to improve opt-in rates. Methods: The primary outcome measure was identified as whether a beneficiary contacted via telephone opted-in or –out of the navigation program. Andersen’s Behavioral Model for Health Service Use was used as the conceptual framework for selecting covariates of interest. Enabling factors were of primary interest because alternate interventions may be designed around them. Data was pulled for the time period of November 17, 2018 through February 14, 2019. Where possible, covariates were associated with data from CMS’ AHC Data Template v3.1 to accommodate replication for all AHC bridge organizations, though additional internally-collected data, which may not be available for all bridge organizations, were needed for some variables. Chi-squared tests were performed for each covariate. Results: No statistical differences were found for the primary covariates of interest. Opt-in rates by Navigator were lowest for Navigator 5 and highest for Navigator 4 (67.53% and 88.24%). Opt-in rates by weekday of decision were lowest on Thursdays and highest on Wednesdays (64.91% and 77.42%). Opt-in rates based on time of day were lowest between 8:00am and 9:59am, and highest between 12:00pm and 1:59pm (62.50% and 100%). Opt-in rates were lowest when the decision was made six days after the screening and highest when made the same day (53.57% and 83.33%). Opt-in rates were lowest when there were five weekdays between screening and navigation decision, and highest when there were three weekdays between the screening and decision (60% and 90%). Other non-process covariates of interest that were statistically significant for opt-in rates were the presence of either food, safety, or utility needs. Conclusions: Several groups had higher opt-in rates that were not statistically significant; small sample sizes may have impacted the significance of these differences. For example, opt-in rates were higher when made the same day as the screening than when made one day after (83.33% and 74.79%). However, only 18 beneficiary decisions were made on the same day, while 119 were made one day after. Increasing the number of same-day phone call attempts may be a method to improve opt-in rates. Importantly, date and time data for contact attempts before a beneficiary decides to opt-in or opt-out were unavailable as of the time of the analysis. These data are captured and will be added to the analysis when available, which could provide more insight into whether a beneficiary is more likely to opt-in or opt-out.