Creation and Execution of a Novel Anesthesia Perioperative Care Service at a Veterans Affairs Hospital:

Rural implementation of the perioperative surgical home: A case-control study

BACKGROUND

Perioperative surgical home (PSH) is a novel patient-centric surgical system developed by American Society of Anesthesiologist to improve outcomes and patient satisfaction. PSH has proven success in large urban health centers by reducing surgery cancellation, operating room time, length of stay (LOS), and readmission rates. Yet, only limited studies have assessed the impact of PSH on surgical outcomes in rural areas.

AIM

To evaluate the newly implemented PSH system at a community hospital by comparing the surgical outcomes using a longitudinal case-control study.

METHODS

The research study was conducted at an 83-bed, licensed level-III trauma rural community hospital. A total of 3096 TJR procedures were collected retrospectively between January 2016 and December 2021 and were categorized as PSH and non-PSH cohorts (n = 2305). To evaluate the importance of PSH in the rural surgical system, a case-control study was performed to compare TJR surgical outcomes (LOS, discharge disposition, and 90-d readmission) of the PSH cohort against two control cohorts [Control-1 PSH (C1-PSH) (n = 1413) and Control-2 PSH (C2-PSH) (n = 892)]. Statistical tests including Chi-square test or Fischer’s exact test were performed for categorical variables and Mann-Whitney test or Student’s t-test were performed for continuous variables. The general linear models (Poisson regression and binomial logistic regression) were performed to fit adjusted models.

RESULTS

The LOS was significantly shorter in PSH cohort compared to two control cohorts (median PSH = 34 h, C1-PSH = 53 h, C2-PSH = 35 h) (P value < 0.05). Similarly, the PSH cohort had lower percentages of discharges to other facilities (PSH = 3.5%, C1-PSH = 15.5%, C2-PSH = 6.7%) (P value < 0.05). There was no statistical difference observed in 90-d readmission between control and PSH cohorts. However, the PSH implementation reduced the 90-d readmission percentage (PSH = 4.7%, C1-PSH = 6.1%, C2-PSH = 3.6%) lower than the national average 30-d readmission percentage which is 5.5%. The PSH system was effectively established at the rural community hospital with the help of team-based coordinated multi-disciplinary clinicians or physician co-management. The elements of PSH including preoperative assessment, patient education and optimization, and longitudinal digital engagement were vital for improving the TJR surgical outcomes at the community hospital.

CONCLUSION

Implementation of the PSH system in a rural community hospital reduced LOS, increased direct-to-home discharge, and reduced 90-d readmission percentages.

Identification of Preanesthetic History Elements by a Natural Language Processing Engine

BACKGROUND

Methods that can automate, support, and streamline the preanesthesia evaluation process may improve resource utilization and efficiency. Natural language processing (NLP) involves the extraction of relevant information from unstructured text data. We describe the utilization of a clinical NLP pipeline intended to identify elements relevant to preoperative medical history by analyzing clinical notes. We hypothesize that the NLP pipeline would identify a significant portion of pertinent history captured by a perioperative provider.

METHODS

For each patient, we collected all pertinent notes from the institution's electronic medical record that were available no later than 1 day before their preoperative anesthesia clinic appointment. Pertinent notes included free-text notes consisting of history and physical, consultation, outpatient, inpatient progress, and previous preanesthetic evaluation notes. The free-text notes were processed by a Named Entity Recognition pipeline, an NLP machine learning model trained to recognize and label spans of text that corresponded to medical concepts. These medical concepts were then mapped to a list of medical conditions that were of interest for a preanesthesia evaluation. For each condition, we calculated the percentage of time across all patients in which (1) the NLP pipeline and the anesthesiologist both captured the condition; (2) the NLP pipeline captured the condition but the anesthesiologist did not; and (3) the NLP pipeline did not capture the condition but the anesthesiologist did.

RESULTS

A total of 93 patients were included in the NLP pipeline input. Free-text notes were extracted from the electronic medical record of these patients for a total of 9765 notes. The NLP pipeline and anesthesiologist agreed in 81.24% of instances on the presence or absence of a specific condition. The NLP pipeline identified information that was not noted by the anesthesiologist in 16.57% of instances and did not identify a condition that was noted by the anesthesiologist's review in 2.19% of instances.

CONCLUSIONS

In this proof-of-concept study, we demonstrated that utilization of NLP produced an output that identified medical conditions relevant to preanesthetic evaluation from unstructured free-text input. Automation of risk stratification tools may provide clinical decision support or recommend additional preoperative testing or evaluation. Future studies are needed to integrate these tools into clinical workflows and validate its efficacy.

Predicting Length of Stay using machine learning for total joint replacements performed at a rural community hospital

Background

Predicting patient’s Length of Stay (LOS) before total joint replacement (TJR) surgery is vital for hospitals to optimally manage costs and resources. Many hospitals including in rural areas use publicly available models such as National Surgical Quality Improvement Program (NSQIP) calculator which, unfortunately, performs suboptimally when predicting LOS for TJR procedures.

Objective

The objective of this research was to develop a Machine Learning (ML) model to predict LOS for TJR procedures performed at a Perioperative Surgical Home implemented rural community hospital for better accuracy and interpretation than the NSQIP calculator.

Methods

A total of 158 TJR patients were collected and analyzed from a rural community hospital located in Montana. A random forest (RF) model was used to predict patient’s LOS. For interpretation, permuted feature importance and partial dependence plot methods were used to identify the important variables and their relationship with the LOS.

Results

The root mean square error for the RF model (0.7) was lower than the NSQIP calculator (1.21). The five most important variables for predicting LOS were BMI, Duke Activity Status-Index, diabetes, patient’s household income, and patient’s age.

Conclusion

This pilot study is the first of its kind to develop an ML model to predict LOS for TJR procedures that were performed at a small-scale rural community hospital. This pilot study contributes an approach for rural hospitals, making them more independent by developing their own predictions instead of relying on public models.

The evidence base for US joint commission hospital accreditation standards: cross sectional study

OBJECTIVE

To evaluate the evidence upon which standards for hospital accreditation by The Joint Commission on Accreditation of Healthcare Organizations (the Joint Commission) are based.

DESIGN

Cross sectional study.

SETTING

United States.

PARTICIPANTS

Four Joint Commission R3 (requirement, rationale, and reference) reports released by July 2018 and intended to become effective between 1 July 2018 and 1 July 2019.

INTERVENTIONS

From each R3 report the associated standard and its specific elements of performance (or actionable standards) were extracted. If an actionable standard enumerated multiple requirements, these were separated into distinct components. Two investigators reviewed full text references, and each actionable standard was classified as either completely supported, partly supported, or not supported; Oxford evidence quality ratings were assigned; and the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) was used to assess the strength of recommendations.

MAIN OUTCOME MEASURE

Strengths of recommendation for actionable standards.

RESULTS

20 actionable standards with 76 distinct components were accompanied by 48 references. Of the 20 actionable standards, six (30%) were completely supported by cited references, six were partly supported (30%), and eight (40%) were not supported. Of the six directly supported actionable standards, one (17%) cited at least one reference of level 1 or 2 evidence, none cited at least one reference of level 3 evidence, and five (83%) cited references of level 4 or 5 evidence. Of the completely supported actionable standards, strength of recommendation in five was deemed GRADE D and in one was GRADE B.

CONCLUSIONS

In general, recent actionable standards issued by The Joint Commission are seldom supported by high quality data referenced within the issuing documents. The Joint Commission might consider being more transparent about the quality of evidence and underlying rationale supporting each of its recommendations, including clarifying when and why in certain instances it determines that lower level evidence is sufficient.

Validation of the Hospital Frailty Risk Score in older surgical patients: A population-based retrospective cohort study

BACKGROUND

There is a need for standardized and cost-effective identification of frailty risk. The objective was to validate the Hospital Frailty Risk Score which utilizes International Classification Diagnoses in a cohort of older surgical patients, assess the score as an independent risk factor for adverse outcomes and compare discrimination properties of the frailty risk score with other risk stratification scores.

METHODS

Data were analysed from all patients ≥65 years undergoing primary surgical procedures from 2006-2018. Patients were categorized based on the frailty risk score. The primary outcomes were 30-day mortality and 180-day risk of readmission.

RESULTS

Of 16 793 patients evaluated, 7480 (45%), 7605 (45%) and 1708 (10%) had a low, intermediate and high risk of frailty. There was a higher incidence of 30-day mortality for individuals with intermediate (2.9%) and high (8.3%) compared with low (1.4%) risk of frailty (P < .001 for both comparisons). Similarly, the hazard of readmission within the first 180 days was higher for intermediate (HR 1.25; 95% CI: 1.16-1.34) and high (HR 1.84; 95% CI: 1.66-2.03) compared with low (HR 1.00, P < .001 for both comparisons) risk of frailty. The hazard of long-term mortality was higher for intermediate (HR 1.70; 95% CI: 1.61-1.80) and high (HR 4.16; 95% CI: 3.84-4.49) compared with low (HR 1.00, P < .001 for both comparisons) risk of frailty. Finally, long length of primary hospitalization occurred for 9.3%, 15.0% and 27.3% of individuals with low, intermediate and high frailty risk (P < .001 for all comparisons). A model including age and ASA classification had the best discrimination for 30-day mortality (AUC 0.862; 95% CI: 0.847-0.877).

CONCLUSION

Our findings suggest that the Hospital Frailty Risk Score might be used to screen older surgical patients for risk of frailty. While only slightly improving prediction of 30-day mortality using the ASA classification, the Hospital Frailty Risk Score can be used to independently classify older patients for the risk of important outcomes using pre-existing readily available electronic data.

Implementing ERAS: how we achieved success within an anesthesia department

Background

The Massachusetts General Hospital is a large, quaternary care institution with 58 operating rooms, 164 anesthesiologists, 76 certified nurse anesthetists (CRNAs), an anesthesiology residency program that admits 25 residents annually, and 35 surgeons who perform laparoscopic, vaginal, and open hysterectomies. In March of 2018, our institution launched an Enhanced Recovery After Surgery (ERAS) pathway for patients undergoing hysterectomy. To implement the anesthesia bundle of this pathway, an intensive 14-month educational endeavor was created and put into effect. There were no subsequent additional educational interventions.

Methods

We retrospectively reviewed records of 2570 patients who underwent hysterectomy between October 2016 and March 2020 to determine adherence to the anesthesia bundle of the ERAS Hysterectomy pathway. RESULTS: Increased adherence to the four elements of the anesthesia bundle (p < 0.001) was achieved during the intervention period. Compliance with the pathway was sustained in the post-intervention period despite no additional actions.

Conclusions

Implementing the anesthesia bundle of an ERAS pathway in a large anesthesia group with diverse providers successfully occurred using implementation science-based approach of intense interventions, and these results were maintained after the intervention ceased.

Effects of an anesthesia perioperative surgical home for total knee and hip arthroplasty at a Veterans Affairs Hospital: a quality improvement before-and-after cohort study

BACKGROUND

A perioperative surgical home, the Anesthesia Perioperative Care Service (APCS), was created to execute enhanced recovery after surgery pathways for total knee and total hip arthroplasty patients at the Tennessee Valley Health System Nashville VA Medical Center. We hypothesized that the APCS would be associated with reduced length of stay, in-hospital and post-discharge opioid exposure, costs, and hospital readmissions.

METHODS

Data were collected for all patients admitted to the Nashville VA Medical Center following their respective surgery, for 400 days after the initiation of the APCS and for a 400-day period prior. This cohort study was based on a quality improvement project set up at the initiation of the service. The adjusted effect on each quantitative outcome was evaluated using proportional odds logistic regression methods. In addition, each regression analysis was performed in segmented regression fashion to identify changes in the outcomes over time.

RESULTS

We included 282 patients in our cohort-96 prior and 186 post-implementation. Median hospital length of stay, intravenous (IV) and per os (PO) inpatient opioid administration, outpatient opioid quantity, and total days of supply were all reduced in the cohort cared for by the APCS. After adjusting for potential cofounders and evaluated outcome over time, the APCS remained independently associated with a reduction of hospital length of stay of one day (95% confidence interval, 0.09 to 1.97; P = 0.05) and with decreased IV and PO inpatient opioid administration, while continuing to show no increase in hospital readmissions.

CONCLUSIONS

This cohort study showed significant improvements in important post-surgical outcomes after total knee and hip arthroplasty that were associated with the implementation of an APCS.

Multicomponent hospital-led interventions to reduce hospital stay for older adults following elective surgery: a systematic review

Background

Elective older adult inpatient admissions are increasingly common. Older adults are at an elevated risk of adverse events in hospital, potentially increasing with lengthier hospital stay. Hospital-led organisational strategies may optimise hospital stay for elective older adult inpatients.

Objectives

To evaluate the effectiveness and cost-effectiveness of hospital-led multicomponent interventions to reduce hospital stay for older adults undergoing elective hospital admissions.

Data sources

Seven bibliographic databases (MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations, EMBASE, Health Management Information Consortium, Cochrane Central Register of Controlled Trials, Cumulative Index to Nursing and Allied Health Literature and Allied and Complementary Medicine Database) were searched from inception to date of search (August 2017), alongside carrying out of web searches, citation searching, inspecting relevant reviews, consulting stakeholders and contacting authors. This search was duplicated, with an additional cost-filter, to identify cost-effectiveness evidence.

Review methods

Comparative studies were sought that evaluated the effectiveness or cost-effectiveness of relevant interventions in elective inpatients with a mean or median age of ≥ 60 years. Study selection, data extraction and quality assessment were completed independently by two reviewers. The main outcome was length of stay, but all outcomes were considered. Studies were sorted by procedure, intervention and outcome categories. Where possible, standardised mean differences or odds ratios were calculated. Meta-analysis was performed when multiple randomised controlled trials had the same intervention, treatment procedure, comparator and outcome. Findings were explored using narrative synthesis.

Findings

A total of 218 articles were included, with 80 articles from 73 effectiveness studies (n = 26,365 patients) prioritised for synthesis, including 34 randomised controlled trials conducted outside the UK and 39 studies from the UK, of which 12 were randomised controlled trials. Fifteen studies included cost-effectiveness data. The evidence was dominated by enhanced recovery protocols and prehabilitation, implemented to improve recovery from either colorectal surgery or lower limb arthroplasty. Six other surgical categories and four other intervention types were identified. Meta-analysis found that enhanced recovery protocols were associated with 1.5 days’ reduction in hospital stay among patients undergoing colorectal surgery (Cohen’sd = –0.51, 95% confidence interval –0.78 to –0.24;p < 0.001) and with 5 days’ reduction among those undergoing upper abdominal surgery (Cohen’sd = –1.04, 95% confidence interval –1.55 to –0.53;p < 0.001). Evidence from the UK was not pooled (owing to mixed study designs), but it echoed findings from the international literature. Length of stay usually was reduced with intervention or was no different. Other clinical outcomes also improved or were no worse with intervention. Patient-reported outcomes were not frequently reported. Cost and cost-effectiveness evidence came from 15 highly heterogeneous studies and was less conclusive.

Limitations

Studies were usually of moderate or weak quality. Some intervention or treatment types were under-reported or absent. The reporting of variance data often precluded secondary analysis.

Conclusions

Enhanced recovery and prehabilitation interventions were associated with reduced hospital stay without detriment to other clinical outcomes, particularly for patients undergoing colorectal surgery, lower limb arthroplasty or upper abdominal surgery. The impacts on patient-reported outcomes, health-care costs or additional service use are not well known.

Future work

Further studies evaluating of the effectiveness of new enhanced recovery pathways are not required in colorectal surgery or lower limb arthroplasty. However, the applicability of these pathways to other procedures is uncertain. Future studies should evaluate the implementation of interventions to reduce service variation, in-hospital patient-reported outcomes, impacts on health and social care service use, and longer-term patient-reported outcomes.

Study registration

This study is registered as PROSPERO CRD42017080637.

Funding

The National Institute for Health Research Health Services and Delivery Research programme.