Hospital 4Ms: Documentation and association with patient characteristics.
For the thousands of health systems recognized as Age-Friendly, considerable progress has been made to integrate 4Ms into clinical care. This study evaluated associations between 4Ms documentation and patient characteristics in an inpatient setting.
In this prospective cohort, hospitalizations included were from patients in an Acute Care for Elders (ACE) unit where the 4Ms were adopted and implemented. Each M (What Matters, Medication, Mentation, and Mobility) was stratified into three categories (not documented, partly documented, and fully documented) reflecting "assessment" and "action" clinical care processes. Electronic health records were reviewed for patient and hospitalization characteristics. Descriptive statistics evaluated these characteristics across categories of each M.
There were 620 hospital encounters (573 patients) included in the cohort. Patients had a median age of 80 years [IQR 76, 86] and 85% were White. Of all 4Ms, What Matters had the lowest documentation with 413 (67%) of encounters falling into the not documented group. Medication had the highest documentation with 453 (73%) of encounters in the fully documented group. Significant differences in documentation were associated with age and partly versus fully documented Mobility (80 [76, 86] and 82 [77, 88] (p = 0.019)). Hospital length of stay was differentially associated with documentation of all 4M categories. Initial mobility scores were associated with not versus partly documented Medication (6 [2, 7] and 2 [2, 6] (p = 0.041)).
We developed a structured way to categorize "assessment" and "action" 4Ms care processes reflective of three documentation categories in the hospital (not, partly, and fully) and identified important patient and hospital characteristics associated with each. These results offer opportunities for future improvement efforts and insight to which characteristics may be important to measure with wider 4Ms adoption and uptake.
Welch SA
,Archer KR
,Hymel AM
,Pennings JS
,Schwartz AW
,Kang C
,Qian ET
,Duggan MC
,Roumie CL
... -
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The Age-Friendly Learning Healthcare System: Replicating electronic health record based documentation metrics for 4Ms care.
University of Utah Health (UUH) is an academic medical center that achieved "committed to care excellence" in age-friendly care in 2021 and has a long-standing culture of quality improvement central to a learning health system. University of California San Francisco (UCSF) developed electronic health record (EHR) documentation metrics for inpatient assessment of the 4Ms (What Matters, Medication, Mentation, and Mobility) based on the Institute for Healthcare Improvement's recommended care practice for an Age-Friendly Healthcare System. In partnership with UCSF, we replicated the assessment and action EHR metrics with local adaptations for each of the 4Ms at UUH.
The UCSF team shared 4Ms documentation metrics and Structured Query Language code used to assess 4Ms care at UCSF. At UUH, this code was adapted for a different relational database management system and local clinical context. We assessed 4Ms care, individual M, and composite measures of all 4Ms, for all patients aged 65 and older admitted to UU Hospital between January 1, 2019 and December 31, 2021. We conducted a clinical validation of individual patient cases to confirm accuracy of 4Ms queries.
In the 3-year study period, 16,489 qualifying patients, mean age 74.2, were admitted to UU Hospital in a total of 25,070 admissions with mean length of stay of 6.08 days. We were able to replicate 14 of the 16 EHR metrics of individual 4Ms developed at UCSF and five composite measures. For the composite measure addressing completeness of 4Ms care, 50% of patient encounters had all 4Ms administered during their encounter.
Indicators of the completeness of 4Ms care can be measured using EHR data to validate implementation of the 4Ms at multiple academic medical centers. Key lessons to support future scaled-up assessments include the importance of adapting EHR measures to local activities and involving expert data analysts.
Butler JM
,Farrell TW
,Puckett M
,Nanjo C
,Warner P
,Shields D
,Supiano MA
,Kawamoto K
... -
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The effect of sample site and collection procedure on identification of SARS-CoV-2 infection.
Sample collection is a key driver of accuracy in the diagnosis of SARS-CoV-2 infection. Viral load may vary at different anatomical sampling sites and accuracy may be compromised by difficulties obtaining specimens and the expertise of the person taking the sample. It is important to optimise sampling accuracy within cost, safety and accessibility constraints.
To compare the sensitivity of different sampling collection sites and methods for the detection of current SARS-CoV-2 infection with any molecular or antigen-based test.
Electronic searches of the Cochrane COVID-19 Study Register and the COVID-19 Living Evidence Database from the University of Bern (which includes daily updates from PubMed and Embase and preprints from medRxiv and bioRxiv) were undertaken on 22 February 2022. We included independent evaluations from national reference laboratories, FIND and the Diagnostics Global Health website. We did not apply language restrictions.
We included studies of symptomatic or asymptomatic people with suspected SARS-CoV-2 infection undergoing testing. We included studies of any design that compared results from different sample types (anatomical location, operator, collection device) collected from the same participant within a 24-hour period.
Within a sample pair, we defined a reference sample and an index sample collected from the same participant within the same clinical encounter (within 24 hours). Where the sample comparison was different anatomical sites, the reference standard was defined as a nasopharyngeal or combined naso/oropharyngeal sample collected into the same sample container and the index sample as the alternative anatomical site. Where the sample comparison was concerned with differences in the sample collection method from the same site, we defined the reference sample as that closest to standard practice for that sample type. Where the sample pair comparison was concerned with differences in personnel collecting the sample, the more skilled or experienced operator was considered the reference sample. Two review authors independently assessed the risk of bias and applicability concerns using the QUADAS-2 and QUADAS-C checklists, tailored to this review. We present estimates of the difference in the sensitivity (reference sample (%) minus index sample sensitivity (%)) in a pair and as an average across studies for each index sampling method using forest plots and tables. We examined heterogeneity between studies according to population (age, symptom status) and index sample (time post-symptom onset, operator expertise, use of transport medium) characteristics.
This review includes 106 studies reporting 154 evaluations and 60,523 sample pair comparisons, of which 11,045 had SARS-CoV-2 infection. Ninety evaluations were of saliva samples, 37 nasal, seven oropharyngeal, six gargle, six oral and four combined nasal/oropharyngeal samples. Four evaluations were of the effect of operator expertise on the accuracy of three different sample types. The majority of included evaluations (146) used molecular tests, of which 140 used RT-PCR (reverse transcription polymerase chain reaction). Eight evaluations were of nasal samples used with Ag-RDTs (rapid antigen tests). The majority of studies were conducted in Europe (35/106, 33%) or the USA (27%) and conducted in dedicated COVID-19 testing clinics or in ambulatory hospital settings (53%). Targeted screening or contact tracing accounted for only 4% of evaluations. Where reported, the majority of evaluations were of adults (91/154, 59%), 28 (18%) were in mixed populations with only seven (4%) in children. The median prevalence of confirmed SARS-CoV-2 was 23% (interquartile (IQR) 13%-40%). Risk of bias and applicability assessment were hampered by poor reporting in 77% and 65% of included studies, respectively. Risk of bias was low across all domains in only 3% of evaluations due to inappropriate inclusion or exclusion criteria, unclear recruitment, lack of blinding, nonrandomised sampling order or differences in testing kit within a sample pair. Sixty-eight percent of evaluation cohorts were judged as being at high or unclear applicability concern either due to inflation of the prevalence of SARS-CoV-2 infection in study populations by selectively including individuals with confirmed PCR-positive samples or because there was insufficient detail to allow replication of sample collection. When used with RT-PCR • There was no evidence of a difference in sensitivity between gargle and nasopharyngeal samples (on average -1 percentage points, 95% CI -5 to +2, based on 6 evaluations, 2138 sample pairs, of which 389 had SARS-CoV-2). • There was no evidence of a difference in sensitivity between saliva collection from the deep throat and nasopharyngeal samples (on average +10 percentage points, 95% CI -1 to +21, based on 2192 sample pairs, of which 730 had SARS-CoV-2). • There was evidence that saliva collection using spitting, drooling or salivating was on average -12 percentage points less sensitive (95% CI -16 to -8, based on 27,253 sample pairs, of which 4636 had SARS-CoV-2) compared to nasopharyngeal samples. We did not find any evidence of a difference in the sensitivity of saliva collected using spitting, drooling or salivating (sensitivity difference: range from -13 percentage points (spit) to -21 percentage points (salivate)). • Nasal samples (anterior and mid-turbinate collection combined) were, on average, 12 percentage points less sensitive compared to nasopharyngeal samples (95% CI -17 to -7), based on 9291 sample pairs, of which 1485 had SARS-CoV-2. We did not find any evidence of a difference in sensitivity between nasal samples collected from the mid-turbinates (3942 sample pairs) or from the anterior nares (8272 sample pairs). • There was evidence that oropharyngeal samples were, on average, 17 percentage points less sensitive than nasopharyngeal samples (95% CI -29 to -5), based on seven evaluations, 2522 sample pairs, of which 511 had SARS-CoV-2. A much smaller volume of evidence was available for combined nasal/oropharyngeal samples and oral samples. Age, symptom status and use of transport media do not appear to affect the sensitivity of saliva samples and nasal samples. When used with Ag-RDTs • There was no evidence of a difference in sensitivity between nasal samples compared to nasopharyngeal samples (sensitivity, on average, 0 percentage points -0.2 to +0.2, based on 3688 sample pairs, of which 535 had SARS-CoV-2).
When used with RT-PCR, there is no evidence for a difference in sensitivity of self-collected gargle or deep-throat saliva samples compared to nasopharyngeal samples collected by healthcare workers when used with RT-PCR. Use of these alternative, self-collected sample types has the potential to reduce cost and discomfort and improve the safety of sampling by reducing risk of transmission from aerosol spread which occurs as a result of coughing and gagging during the nasopharyngeal or oropharyngeal sample collection procedure. This may, in turn, improve access to and uptake of testing. Other types of saliva, nasal, oral and oropharyngeal samples are, on average, less sensitive compared to healthcare worker-collected nasopharyngeal samples, and it is unlikely that sensitivities of this magnitude would be acceptable for confirmation of SARS-CoV-2 infection with RT-PCR. When used with Ag-RDTs, there is no evidence of a difference in sensitivity between nasal samples and healthcare worker-collected nasopharyngeal samples for detecting SARS-CoV-2. The implications of this for self-testing are unclear as evaluations did not report whether nasal samples were self-collected or collected by healthcare workers. Further research is needed in asymptomatic individuals, children and in Ag-RDTs, and to investigate the effect of operator expertise on accuracy. Quality assessment of the evidence base underpinning these conclusions was restricted by poor reporting. There is a need for further high-quality studies, adhering to reporting standards for test accuracy studies.
Davenport C
,Arevalo-Rodriguez I
,Mateos-Haro M
,Berhane S
,Dinnes J
,Spijker R
,Buitrago-Garcia D
,Ciapponi A
,Takwoingi Y
,Deeks JJ
,Emperador D
,Leeflang MMG
,Van den Bruel A
,Cochrane COVID-19 Diagnostic Test Accuracy Group
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《Cochrane Database of Systematic Reviews》
Impact of residual disease as a prognostic factor for survival in women with advanced epithelial ovarian cancer after primary surgery.
Ovarian cancer is the seventh most common cancer among women and a leading cause of death from gynaecological malignancies. Epithelial ovarian cancer is the most common type, accounting for around 90% of all ovarian cancers. This specific type of ovarian cancer starts in the surface layer covering the ovary or lining of the fallopian tube. Surgery is performed either before chemotherapy (upfront or primary debulking surgery (PDS)) or in the middle of a course of treatment with chemotherapy (neoadjuvant chemotherapy (NACT) and interval debulking surgery (IDS)), with the aim of removing all visible tumour and achieving no macroscopic residual disease (NMRD). The aim of this review is to investigate the prognostic impact of size of residual disease nodules (RD) in women who received upfront or interval cytoreductive surgery for advanced (stage III and IV) epithelial ovarian cancer (EOC).
To assess the prognostic impact of residual disease after primary surgery on survival outcomes for advanced (stage III and IV) epithelial ovarian cancer. In separate analyses, primary surgery included both upfront primary debulking surgery (PDS) followed by adjuvant chemotherapy and neoadjuvant chemotherapy followed by interval debulking surgery (IDS). Each residual disease threshold is considered as a separate prognostic factor.
We searched CENTRAL (2021, Issue 8), MEDLINE via Ovid (to 30 August 2021) and Embase via Ovid (to 30 August 2021).
We included survival data from studies of at least 100 women with advanced EOC after primary surgery. Residual disease was assessed as a prognostic factor in multivariate prognostic models. We excluded studies that reported fewer than 100 women, women with concurrent malignancies or studies that only reported unadjusted results. Women were included into two distinct groups: those who received PDS followed by platinum-based chemotherapy and those who received IDS, analysed separately. We included studies that reported all RD thresholds after surgery, but the main thresholds of interest were microscopic RD (labelled NMRD), RD 0.1 cm to 1 cm (small-volume residual disease (SVRD)) and RD > 1 cm (large-volume residual disease (LVRD)).
Two review authors independently abstracted data and assessed risk of bias. Where possible, we synthesised the data in meta-analysis. To assess the adequacy of adjustment factors used in multivariate Cox models, we used the 'adjustment for other prognostic factors' and 'statistical analysis and reporting' domains of the quality in prognosis studies (QUIPS) tool. We also made judgements about the certainty of the evidence for each outcome in the main comparisons, using GRADE. We examined differences between FIGO stages III and IV for different thresholds of RD after primary surgery. We considered factors such as age, grade, length of follow-up, type and experience of surgeon, and type of surgery in the interpretation of any heterogeneity. We also performed sensitivity analyses that distinguished between studies that included NMRD in RD categories of < 1 cm and those that did not. This was applicable to comparisons involving RD < 1 cm with the exception of RD < 1 cm versus NMRD. We evaluated women undergoing PDS and IDS in separate analyses.
We found 46 studies reporting multivariate prognostic analyses, including RD as a prognostic factor, which met our inclusion criteria: 22,376 women who underwent PDS and 3697 who underwent IDS, all with varying levels of RD. While we identified a range of different RD thresholds, we mainly report on comparisons that are the focus of a key area of clinical uncertainty (involving NMRD, SVRD and LVRD). The comparison involving any visible disease (RD > 0 cm) and NMRD was also important. SVRD versus NMRD in a PDS setting In PDS studies, most showed an increased risk of death in all RD groups when those with macroscopic RD (MRD) were compared to NMRD. Women who had SVRD after PDS had more than twice the risk of death compared to women with NMRD (hazard ratio (HR) 2.03, 95% confidence interval (CI) 1.80 to 2.29; I2 = 50%; 17 studies; 9404 participants; moderate-certainty). The analysis of progression-free survival found that women who had SVRD after PDS had nearly twice the risk of death compared to women with NMRD (HR 1.88, 95% CI 1.63 to 2.16; I2 = 63%; 10 studies; 6596 participants; moderate-certainty). LVRD versus SVRD in a PDS setting When we compared LVRD versus SVRD following surgery, the estimates were attenuated compared to NMRD comparisons. All analyses showed an overall survival benefit in women who had RD < 1 cm after surgery (HR 1.22, 95% CI 1.13 to 1.32; I2 = 0%; 5 studies; 6000 participants; moderate-certainty). The results were robust to analyses of progression-free survival. SVRD and LVRD versus NMRD in an IDS setting The one study that defined the categories as NMRD, SVRD and LVRD showed that women who had SVRD and LVRD after IDS had more than twice the risk of death compared to women who had NMRD (HR 2.09, 95% CI 1.20 to 3.66; 310 participants; I2 = 56%, and HR 2.23, 95% CI 1.49 to 3.34; 343 participants; I2 = 35%; very low-certainty, for SVRD versus NMRD and LVRD versus NMRD, respectively). LVRD versus SVRD + NMRD in an IDS setting Meta-analysis found that women who had LVRD had a greater risk of death and disease progression compared to women who had either SVRD or NMRD (HR 1.60, 95% CI 1.21 to 2.11; 6 studies; 1572 participants; I2 = 58% for overall survival and HR 1.76, 95% CI 1.23 to 2.52; 1145 participants; I2 = 60% for progression-free survival; very low-certainty). However, this result is biased as in all but one study it was not possible to distinguish NMRD within the < 1 cm thresholds. Only one study separated NMRD from SVRD; all others included NMRD in the SVRD group, which may create bias when comparing with LVRD, making interpretation challenging. MRD versus NMRD in an IDS setting Women who had any amount of MRD after IDS had more than twice the risk of death compared to women with NMRD (HR 2.11, 95% CI 1.35 to 3.29, I2 = 81%; 906 participants; very low-certainty).
In a PDS setting, there is moderate-certainty evidence that the amount of RD after primary surgery is a prognostic factor for overall and progression-free survival in women with advanced ovarian cancer. We separated our analysis into three distinct categories for the survival outcome including NMRD, SVRD and LVRD. After IDS, there may be only two categories required, although this is based on very low-certainty evidence, as all but one study included NMRD in the SVRD category. The one study that separated NMRD from SVRD showed no improved survival outcome in the SVRD category, compared to LVRD. Further low-certainty evidence also supported restricting to two categories, where women who had any amount of MRD after IDS had a significantly greater risk of death compared to women with NMRD. Therefore, the evidence presented in this review cannot conclude that using three categories applies in an IDS setting (very low-certainty evidence), as was supported for PDS (which has convincing moderate-certainty evidence).
Bryant A
,Hiu S
,Kunonga PT
,Gajjar K
,Craig D
,Vale L
,Winter-Roach BA
,Elattar A
,Naik R
... -
《Cochrane Database of Systematic Reviews》