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The global burden of anxiety and depression has created an urgent need for scalable approaches to increase access to evidence-based mental health care. The Screening and Treatment for Anxiety and Depression (STAND) system of care was developed to meet this need through the use of internet-connected devices for assessment and provision of treatment. STAND triages to level of care (monitoring only, digital therapy with coaches, digital therapy assisted by clinicians in training, and clinical care) and then continuously monitors symptoms to adapt level of care. Triaging and adaptation are based on symptom severity and suicide risk scores obtained from computerized adaptive testing administered remotely. This article discusses how the STAND system of care improves upon current clinical paradigms, and presents preliminary data on feasibility, acceptability, and effectiveness of STAND in a sample of US-based university students. US-based university students were recruited and enrolled in an open trial of the STAND system of care. Participants were triaged based on initial symptom severity derived from a computerized adaptive test and monitored over 40 weeks on anxiety, depression, and suicide risk to inform treatment adaptation and evaluate preliminary effectiveness. Nearly 5000 students were screened and 516 received care. Depression and anxiety severity scores improved across all tiers (P<.001 in all cases). Suicide risk severity improved in the highest tier (ie, clinical care; P<.001). Acceptability and feasibility were demonstrated. STAND is a feasible and acceptable model of care that can reach large numbers of individuals. STAND showed preliminary effectiveness on all primary outcome measures. Current directions to improve STAND are described.

The implementation of telemonitoring (TM) has been successful in terms of the overall feasibility and adoption in single disease care models. However, a lack of available research focused on nurse-led implementations of TM that targets patients with multiple and complex chronic conditions (CCC) hinders the scale and spread to these patient populations. In particular, little is known about the clinical perspective on the implementation of TM for patients with CCC in outpatient care. This study aims to better understand the perspective of the clinical team (both frontline clinicians and those in administrative positions) on the implementation and normalization of TM for complex patients in a nurse-led clinic model. A pragmatic, 6-month implementation study was conducted to embed multicondition TM, including heart failure, hypertension, and diabetes, into an integrated nurse-led model of care. Throughout the study, clinical team members were observed, and a chart review was conducted of the care provided during this time. At the end of the study, clinical team members participated in qualitative interviews and completed the adapted Normalization Measure Development questionnaires. The Normalization Process Theory guided the deductive data analysis. Overall, 9 team members participated in the study as part of a larger feasibility study of the TM program, of which 26 patients were enrolled. Team members had a shared understanding of the purpose and value of TM as an intervention embedded within their practice to meet the diverse needs of their patients with CCC. TM aligned well with existing chronic care practices in several ways, yet it changed the process of care delivery (ie, interactional workability subconstruct). Effective TM normalization in nurse-led care requires rethinking of clinical workflows to incorporate TM, relationship development between the clinicians and their patients, communication with the interdisciplinary team, and frequent clinical care oversight. This was captured well through the subconstructs of skill set workability, relational integration, and contextual integration of the Normalization Process Theory. Clinicians successfully adopted TM into their everyday practice such that some providers felt their role would be significantly and negatively affected without TM. This study demonstrated that smartphone-based TM systems complemented the routine and challenging clinical work caring for patients with CCC in an integrated nurse-led care model.

Aims To inform a discussion for the applicability of using the Nursing Role Effectiveness Model (NREM) in the primary health care setting through a synthesis of the literature that has used the model in all health care sectors. Design Scoping Review. Methods Articles were considered for inclusion if they discussed any aspect of the NREM in health care research that presented information related to any nursing regulatory designation, such as nurse practitioner (NP), registered nurse (RN), licensed/registered practical nurse (LPN/RPN) and considered both quantitative and qualitative study designs, including expert opinions and reports. Results A total of 22 articles that cited and/or used the NREM were identified in this review. Only two studies were focused in the primary health care setting. There is precedence for the use of the NREM to guide research in primary health care. The NREM should be modified to incorporate the unique characteristics of the primary health care setting.

Background For more than a century, Māori have experienced poorer health than non-Māori. In 2019 an independent Tribunal found the Government had breached Te Tiriti o Waitangi by “failing to design and administer the current primary health care system to actively address persistent Māori health inequities”. Many Māori (44%) have unmet needs for primary care. Seven models of primary care were identified by the funders and the research team, including Māori-owned practices. We hypothesised patient health outcomes for Māori would differ between models of care. Methods Cross-sectional primary care data were analysed at 30 September 2018. National datasets were linked to general practices at patient level, to measure associations between practice characteristics and patient health outcomes. Primary outcomes: polypharmacy (≥ 55 years), HbA1c testing, child immunisations, ambulatory sensitive hospitalisations (0–14, 45–64 years) and emergency department attendances. Regressions include only Māori patients, across all models of care. Results A total of 660,752 Māori patients were enrolled in 924 practices with 124,854 in 65 Māori-owned practices. Māori practices had: no significant association with HbA1c testing, ambulatory sensitive hospitalisations or ED attendances, and a significant association with lower polypharmacy (3.7% points) and lower childhood immunisations (13.4% points). Māori practices had higher rates of cervical smear and cardiovascular risk assessment, lower rates of HbA1c tests, and more nurse (46%) and doctor (8%) time (FTE) with patients. The average Māori practice had 52% Māori patients compared to 12% across all practices. Māori practices enrolled a higher percentage of children and young people, five times more patients in high deprivation areas, and patients with more multimorbidity. More Māori patients lived rurally (21.5% vs 15%), with a greater distance to the nearest ED. Māori patients were more likely to be dispensed antibiotics or tramadol. Conclusions Māori practices are an expression of autonomy in the face of enduring health system failure. Apart from lower immunisation rates, health outcomes were not different from other models of care, despite patients having higher health risk profiles. Across all models, primary care need was unmet for many Māori, despite increased clinical input. Funding must support under-resourced Māori practices and ensure accountability for the health outcomes of Māori patients in all models of general practice.

To describe the design and initial implementation of an Intensive Care Unit Recovery Center (ICU-RC) in the United States. A prospective, observational feasibility study was undertaken at an academic hospital between July 2012 and December 2015. Clinical criteria were used to develop the ICU-RC, identify patients at high risk for post intensive care syndrome (PICS), and offer them post-ICU care. 218/307 referred patients (71%) survived to hospital discharge; 62 (28% of survivors) were seen in clinic. Median time from discharge to ICU-RC visit was 29days. At initial evaluation, 64% of patients had clinically meaningful cognitive impairment. Anxiety and depression were present in 37% and 27% of patients, respectively. One in three patients was unable to ambulate independently; median 6min walk distance was 56% predicted. Of 47 previously working patients, 7 (15%) had returned to work. Case management and referral services were provided 142 times. The median number of interventions per patient was 4. An ICU-RC identified a high prevalence of cognitive impairment, anxiety, depression, physical debility, lifestyle changes, and medication-related problems warranting intervention. Whether an ICU-RC can improve ICU recovery in the US should be investigated in a systematic way. •An outpatient intervention for recovery after critical illness (ICU Recovery Center) is proposed.•The development, implementation, and characteristic patient population of an ICU-RC in the United States is described.•A pragmatic clinical population of patients recovering from critical illness had a range of impairments after discharge.•Post-ICU recovery programs have not been widely studied or adopted despite the scope of these problems.•An ICU-RC is feasible and has the potential to minimize post intensive care syndrome (PICS) and maximize recovery.

Purpose To critically assess the effectiveness and implementation of different models of post-treatment cancer survivorship care compared to specialist-led models of survivorship care assessed in published systematic reviews. Methods MEDLINE, CINAHL, Embase, and Cochrane CENTRAL databases were searched from January 2005 to May 2021. Systematic reviews that compared at least two models of cancer survivorship care were included. Article selection, data extraction, and critical appraisal were conducted independently by two authors. The models were evaluated according to cancer survivorship care domains, patient and caregiver experience, communication and decision-making, care coordination, quality of life, healthcare utilization, costs, and mortality. Barriers and facilitators to implementation were also synthesized. Results Twelve systematic reviews were included, capturing 53 primary studies. Effectiveness for managing survivors’ physical and psychosocial outcomes was found to be no different across models. Nurse-led and primary care provider-led models may produce cost savings to cancer survivors and healthcare systems. Barriers to the implementation of different models of care included limited resources, communication, and care coordination, while facilitators included survivor engagement, planning, and flexible services. Conclusions Despite evidence regarding the equivalent effectiveness of nurse-led, primary care-led, or shared care models, these models are not widely adopted, and evidence-based recommendations to guide implementation are required. Further research is needed to address effectiveness in understudied domains of care and outcomes and across different population groups. Implications for Cancer Survivors Rather than aiming for an optimal “one-size fits all” model of survivorship care, applying the most appropriate model in distinct contexts can improve outcomes and healthcare efficiency.

Background Systems navigation provided by individuals or teams is emerging as a strategy to reduce barriers to care. Complex clients with health and social support needs in primary care experience fragmentation and gaps in service delivery. There is great diversity in the design of navigation and a lack of consensus on navigation roles and models in primary care. Methods We conducted a scoping literature review following established methods to explore the existing evidence on system navigation in primary care. To be included, studies had to be published in English between 1990 and 2013, and include a navigator or navigation process in a primary care setting that involves the community- based social services beyond the health care system. Results We included 34 papers in our review, most of which were descriptive papers, and the majority originated in the US. Most of the studies involved studies of individual navigators (lay person or nurse) and were developed to meet the needs of specific patient populations. We make an important contribution to the literature by highlighting navigation models that address both health and social service navigation. The emergence and development of system navigation signals an important shift in the recognition that health care and social care are inextricably linked especially to address the social determinants of health. Conclusions There is a high degree of variance in the literature, but descriptive studies can inform further innovation and development of navigation interventions in primary care.

Background Primary care in Aotearoa New Zealand is largely delivered by general practices, heavily subsidised by government. Te Tiriti o Waitangi (1840) guarantees equal health outcomes for Māori and non-Māori, but differences are stark and longstanding. Seven models of primary care have evolved. We hypothesised that patient health outcomes would differ between models of care; and that Māori, Pacific peoples and those living in material deprivation would have poorer outcomes from primary care. Methods We conducted a cross-sectional study of patient-level data from national datasets and practices, at 30 September 2018, using multilevel mixed effects regression analyses (patients clustered within practices). Primary outcomes, considered to be measures of unmet need for primary care, were polypharmacy (≥ 65 years), HbA1c testing in adults with diabetes, childhood immunisations (6 months), ambulatory sensitive hospitalisations (0–14, 45–64 years) and emergency department attendances. Explanatory variables adjusted for patient and practice characteristics. Equity, by model of care, ethnicity and deprivation, was assumed if they showed no significant association with patient outcomes. Patient characteristics included: age, ethnicity, deprivation, multi-morbidity, first specialist assessments and practice continuity. Practice characteristics included: size, funding and doctor continuity. Clinical input (consultations and time with nurses and doctors) was considered a measure of practice response . Results The study included 924 general practices with 4,491,964 enrolled patients. Traditional practices enrolled 73% of the population, but, on average, the proportion of Māori, Pacific and people living with material deprivation was low in any one Traditional practice. Patients with high health needs disproportionately enrolled in Māori, Pacific and Trust/NGO practices. There were multiple associations between models of care and patient health outcomes in fully adjusted regressions. No one model of care out-performed others across all outcomes. Patients with higher health need received more clinical input but this was insufficient to achieve equity in all outcomes. Being a Māori or Pacific patient, or living in material deprivation, across models of care, remained associated with poorer outcomes. Conclusions Model-level associations with poor patient outcomes suggest inequity in measures that might be used to target investment in primary care.

Although they are critical to models of coordinated care, the relationship and communication between primary care providers (PCPs) and cancer specialists throughout the cancer continuum are poorly understood. By using predefined search terms, the authors conducted a systematic review of the literature in 3 databases to examine the relationship and communication between PCPs and cancer specialists. Among 301 articles identified, 35 met all inclusion criteria and were reviewed in-depth. Findings from qualitative, quantitative, and disaggregated mixed-methods studies were integrated using meta-synthesis. Six themes were identified and incorporated into a preliminary conceptual model of the PCP-cancer specialist relationship: 1) poor and delayed communication between PCPs and cancer specialists, 2) cancer specialists' endorsement of a specialist-based model of care, 3) PCPs' belief that they play an important role in the cancer continuum, 4) PCPs' willingness to participate in the cancer continuum, 5) cancer specialists' and PCPs' uncertainty regarding the PCP's oncology knowledge/experience, and 6) discrepancies between PCPs and cancer specialists regarding roles. These data indicate a pervasive need for improved communication, delineation, and coordination of responsibilities between PCPs and cancer specialists. Future interventions aimed at these deficiencies may improve patient and physician satisfaction and cancer care coordination.