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The following reports are under development at one of the four ESP sites. If you would like to provide comments about the topic under development, serve as a peer reviewer for the draft report, or know the timeline for completion, please contact the ESP Coordinating Center.
To review the most up-to-date protocols, please visit the PROSPERO website. Protocol registration numbers for an individual project can be found along with the brief abstract for the project, below.
KQ1: Among males, is there a clinical risk tool (eg, FRAX) that identify patients at highest risk of osteoporosis or major osteoporotic fracture?
KQ2: Among male Veterans, is there a combination of risk factors that identify patients at highest risk of osteoporosis or major osteoporotic fracture?
KQ3: What systems level interventions improve uptake of osteoporosis screening?
Populations:
KQ 1: Adult men, KQ 2: Adult male Veterans, KQ 3: Health care providers, adult patients, health system administrators and/or staff.
In studies that recruit populations with and without facture histories, 80% of recruited study population should have no prior identified low-trauma fracture.
For studies with mixed populations of men and women, we will include them if they conduct a subgroup analysis of men only.
Interventions:
KQ 1: Clinical risk assessment or fracture risk predations tools (eg, FRAX, GARVAN FRC, Q fracture, fracture risk calculator, Osteoporosis Screening tool [OST], male osteoporosis screening tool [MOST], Male Osteoporosis Risk Estimation Score [MORES]); combination of assessment tools and screening tests (eg, dual-energy x-ray absorptiometry-DXA)
KQ 2: Risk factor for osteoporosis (eg, medication use, smoking, body mass index) and clinical risk assessment or fracture risk predations tools.
KQ 3: System-level approaches targeting provider behaviors or systems operations to optimize uptake of osteoporosis screening (eg, clinical reminder systems; bone health clinics; provider education; tailored and/or bi-directional patient education such as IVR assessing individual risk scores; remote consultation; nurse/physician/pharmacist led interventions; clinician incentives, academic detailing; patient self-referral system)
Comparators:
KQ 1 & KQ 2: other risk assessment tools, bone mineral density testing via validated approach (eg, dual-energy x-ray absorptiometry-DXA)
KQ 3: usual care, other system-level approached, patient-focused interventions
Outcomes:
KQ 1 & KQ 2: fracture rates; bone mineral density
KQ 3: fracture rates, screening rates
Setting: Outpatient general medical settings (eg, geriatrics, family medicine, general internal medicine, integrative medicine, urgent care, emergency departments) or inpatient health care settings
We will conduct a primary search from inception to the current date of MEDLINE® (via PubMed®), Embase, and CINAHL. We will use a combination of MeSH keywords and selected free-text terms to search titles and abstracts. To ensure completeness, search strategies will be developed in consultation with an expert librarian. We will also hand search key references for relevant citations that may not be captured by our database search.
KQ1:
a.) Among adults, what are the effects of tele-urgent care for low acuity conditions on key clinical and health systems outcomes (ie, patient satisfaction, health care access, health care utilization, case resolution, cost, patient safety)?
b.) Does the impact of tele-urgent care for low acuity conditions differ by
1.) provider characteristics (ie, specialty, amount of telehealth experience, training) or
2.)mode of delivery (ie, telephone, video, web, short message service [SMS])?
KQ2:
a.) Among adults, what are the adverse effects (ie, inappropriate treatment, misdiagnosis, or delayed diagnosis; provider burnout) of tele-urgent care for low acuity conditions?
b.) Do the adverse effects of low acuity conditions differ by
1.) provider characteristics (ie, specialty, amount of telehealth experience, training) or
2.) mode of delivery (ie, telephone, video, web, short message service [SMS])?
Population(s): KQ1 & KQ2: Adults with low acuity but urgent conditions (≥18 years of age) and their families and caregivers.
KQ2 ONLY: Tele-urgent care providers (if included in harms)
Interventions: Tele-urgent care for low acuity conditions is defined as remotely delivered (eg, telephone, video conferencing) medical services indented to provide on-demand, initial treatment of illnesses or injuries of a less serious nature than those constituting emergencies (ie, urgent care, not routine primary care) and is initiated by a patient with a provider
Comparator: KQ1: Usual care/standard of care, waitlist control, other active comparator (eg, in-person care
KQ 2: No comparator required
Outcome(s): KQ1: Patient, provider, system outcomes (eg, patient satisfaction, health care access, health care utilization, case resolution, cost, and patient safety)
KQ 2: Key adverse effects associated with telehealth (eg, inappropriate treatment, misdiagnosis, delayed diagnosis, increase in resource costs; provider burnout)
We will conduct a primary search from inception to the current date of MEDLINE® (via Ovid®), EMBASE (via Elsevier), CINAHL Complete (via EBSCO). We will use a combination of MeSH keywords and selected free-text terms to search titles and abstracts. To ensure completeness, search strategies will be developed in consultation with an expert librarian. We will hand search previous systematic reviews conducted on this or a related topic for potential inclusion.
KQ1: What are the risk and protective factors for suicidal behaviors (attempts or death by suicide) across socioecological levels of risk?
Population(s): Community-dwelling Veterans or military service members
Interventions: N/A
Comparator: N/A
Outcome(s): Suicide attempts, suicide deaths
We will search MEDLINE, Embase, PsycINFO, and Sociological Abstracts. We will include observational population-based studies, published January 2011 – December 2020, that examine risk factors for suicide deaths and/or suicide attempts. Studies will capture risk factors/variables of interest, prior (precede) to the outcomes of interest (suicide, suicide attempt). We will exclude systematic reviews, narrative reviews, case reports, editorials, commentary, conference abstracts, interventions, and non-English language publications.
PROSPERO registration number: CRD42020215229
KQ1: Among adults hospitalized with COVID-19 and discharged with physical functional impairment, what is the prevalence of short (eg, < 3 months) and long-term (eg, 4+ months) healthcare use?
Population(s): Adults hospitalized with diagnosis COVID-19 (ie, SARs-CoV-2)
Interventions: Diagnosis of COVID-19 (ie, SARs-CoV-2) as defined as laboratory-confirmed cases
Comparator: None
Outcome(s): Prevalence of short term and long term health care services (eg, skilled nursing facility, in-patient rehabilitation, occupational therapy, physical therapy, primary care, ER/urgent care, home health) and durable medical equipment use (eg, walkers) post-acute hospitalization
We conducted the search of our living review in MEDLINE (via Ovid) and Embase (via Elsevier) databases on September 2, 2020. We also reviewed posted evidence syntheses on the multiple online databases for recent and ongoing rapid reviews related to COVID-19. To identify emerging literature, we adapted our search strategy for preprint server collections from medRxiv.org. Searches were not limited by date or language.
KQ1a) Among adults, what is the effect of synchronous virtual care (ie, phone and/or video) compared to in-person care (or phone vs video) for chronic management of congestive heart failure on key disease specific clinical outcomes and healthcare utilization (ie, hospital admission, hospital re-admission, ER visits)?
KQ1b) Does this effect differ by race/ethnicity, gender, age, and rural status?
KQ2a) Among adults, what is the effect of synchronous virtual care (ie, phone and/or video) compared to in-person care (or phone vs video) for chronic management of chronic obstructive pulmonary disorder on key disease specific clinical outcomes and healthcare utilization (ie, hospital admission, hospital re-admission, ER visits)?
KQ2b) Does this effect differ by race/ethnicity, gender, age, and rural status
KQ3a) Among adults, what is the effect of synchronous virtual care (ie, phone and/or video) compared to in-person care (or phone vs video) for chronic management of type 2 diabetes on key disease specific clinical outcomes and healthcare utilization (ie, hospital admission, hospital re-admission, ER visits)?
KQ3b) Does this effect differ by race/ethnicity, gender, age, and rural status
KQ4) Among patients receiving care, clinical team members, and clinics, what are the adverse effects of synchronous virtual care for chronic management of congestive heart failure, COPD, and Type 2 DM (ie, inappropriate treatment, increase in resource costs, provider burnout) as compared to in-person care (or phone vs video)?
Population(s): Adults (18 years and older) with the following chronic conditions:
1) congestive heart failure (CHF),
2) chronic obstructive pulmonary disorder (COPD),
3) type 2 diabetes (at least 75% if a mix of type 1 and type 2)
Clinicians/clinics conducting virtual care for chronic conditions if relevant to harms.
Interventions: Synchronous care delivered over at least two encounters in which some or all in-person care is supplanted by virtual care (ie, phone and/or video) and which is delivered remotely by a clinician with a scope of practice that includes independent prescribing, diagnosis, and/or chronic management (ie, physician, nurse practitioner, physician assistant, clinical pharmacist) of a patient who is not physically present in the same clinic (aka teleconsultation, video-conferencing) and which is administered within the context of longitudinal care provision (even if individual visits are for acute concerns).
Comparator: In-person care without any virtual care delivery or telephone if compared to video
Outcome(s): General clinical outcomes (eg, medication adherence, quality of life, depression)
CHF clinical outcomes (eg, NYHA class/symptoms)
COPD clinical outcomes (eg, exercise tolerance, dyspnea)
Type 2 DM clinical outcomes (eg, hemoglobin A1c)
Clinical utilization (ie, hospitalizations, hospital re-admissions, emergency room visits/urgent care)
Adverse effects (eg, hypoglycemic episodes, inappropriate treatment, provider burnout)
Setting: OECD countries; Any outpatient setting (ie, general medical or specialty care clinic)
We will conduct a primary search from inception to the current date of MEDLINE® (via Ovid®) and Embase. We will use a combination of MeSH keywords and selected free-text terms to search titles and abstracts. To ensure completeness, search strategies will be developed in consultation with an expert medical librarian. We will hand search previous systematic reviews conducted on this or a related topic for potential inclusion.
KQ1: For cognitive behavioral therapy, acceptance and commitment therapy, and mindfulness-based therapy used to treat adults with chronic pain
KQ2: For evidence-based psychotherapies and mindfulness-based interventions used in integrated delivery systems to treat adults with chronic mental health conditions:
Population(s): Community-dwelling adults with chronic pain (KQ1) or chronic mental health conditions (KQ2)
Interventions: or KQ1:
For KQ2:
Comparator: Any (active or inactive)
Outcome(s): KQ1 – Pre-implementation studies: patient, provider, and system-level barriers and facilitators
KQ2 – Pre-implementation studies: Provider and system-level barriers and facilitators
KQ1&2 – Evaluations of implementation strategies:
Timing: Text
Setting: Outpatient (including clinics, home, and telehealth)
Keyword and subject headings for interventions (as specified below); chronic pain; Veterans or VA; integrated delivery systems; and implementation barriers, facilitators and strategies. Databases to be searched: MEDLINE, Embase, CINAHL, PsycINFO, Cochrane database, and AHRQ EPC reports.
KQ1: What is the comparative effectiveness or effectiveness of implementing continuous quality improvement (CQI) frameworks in terms of health care workers’ outcomes (eg, reaction, learning, behavior change, results, and sustainment of change)?
KQ2: What factors (including intervention, inner setting, outer setting, individuals involved, and process by which implementation is accomplished) contribute to the success or failure of these CQI frameworks?
Population(s): Health care workers
Interventions: Continuous Quality Improvement (CQI) frameworks (eg, Lean, Lean Six Sigma, Institute for Healthcare Improvement [IHI] Model for Change, and Clinical MicroSystems)
Comparator: Studies that directly compare one CQI framework to another when possible
Outcome(s): Health care workers’ outcomes (eg, reaction, learning, behavior change, results, and sustainment of change)
Timing: Text
Setting: Any healthcare setting
We will procure literature from these sources: PubMed, CINAHL, DARE, Cochrane
