Cost-Effectiveness of Low-Dose Computed Tomography Screenings for Lung Cancer in High-Risk Populations: A Markov Model.

Background: Domestic and foreign studies on lung cancer have been oriented to the medical efficacy of low-dose computed tomography (LDCT), but there is a lack of studies on the costs, value and cost-effectiveness of the treatment. There is a scarcity of conclusive evidence regarding the cost-effectiveness of LDCT within the specific context of Taiwan. This study is designed to address this gap by conducting a comprehensive analysis of the cost-effectiveness of LDCT and chest X-ray (CXR) as screening methods for lung cancer. Methods: Markov decision model simulation was used to estimate the cost-effectiveness of biennial screening with LDCT and CXR based on a health provider perspective. Inputs are based on probabilities, health status utility (quality-adjusted life years (QALYs)), costs of lung cancer screening, diagnosis, and treatment from the literatures, and expert opinion. A total of 1,000 simulations and five cycles of Markov bootstrapping simulations were performed to compare the incremental cost-utility ratio (ICUR) of these two screening strategies. Probability and one-way sensitivity analyses were also performed. Results: The ICUR of early lung cancer screening compared LDCT to CXR is $-24,757.65/QALYs, and 100% of the probability agree to adopt it under a willingness-to-pay (WTP) threshold of the Taiwan gross domestic product (GDP) per capita ($35,513). The one-way sensitivity analysis also showed that ICUR depends heavily on recall rate. Based on the prevalence rate of 39.7 lung cancer cases per 100,000 people in 2020, it could be estimated that LDCT screening for high-risk populations could save $17,154,115. Conclusion: LDCT can detect more early lung cancers, reduce mortality and is cost-saving than CXR in a long-term simulation of Taiwan's healthcare system. This study provides valuable insights for healthcare decision-makers and suggests analyzing cost-effectiveness for additional variables in future research.

Cost-Effectiveness Analysis of Digital Breast Tomosynthesis and Mammography in Breast Cancer Screening: A Markov Modeling Study.

BACKGROUND: Mammography (MG) has demonstrated its effectiveness in diminishing mortality and advanced-stage breast cancer incidences in breast screening initiatives. Notably, research has accentuated the superior diagnostic efficacy and cost-effectiveness of digital breast tomosynthesis (DBT). However, the scope of evidence validating the cost-effectiveness of DBT remains limited, prompting a requisite for more comprehensive investigation. The present study aimed to rigorously evaluate the cost-effectiveness of DBT plus MG (DBT-MG) compared to MG alone within the framework of Taiwan's National Health Insurance program. METHODS: All parameters for the Markov decision tree model, encompassing event probabilities, costs, and utilities (quality-adjusted life years, QALYs), were sourced from reputable literature, expert opinions, and official records. With 10,000 iterations, a 2-year cycle length, a 30-year time horizon, and a 2% annual discount rate, the analysis determined the incremental cost-effectiveness ratio (ICER) to compare the cost-effectiveness of the two screening methods. Probabilistic and one-way sensitivity analyses were also conducted to demonstrate the robustness of findings. RESULTS: The ICER of DBT-MG compared to MG was US$5971.5764/QALYs. At a willingness-to-pay (WTP) threshold of US$33,004 (Gross Domestic Product of Taiwan in 2021) per QALY, more than 98% of the probabilistic simulations favored adopting DBT-MG versus MG. The one-way sensitivity analysis also shows that the ICER depended heavily on recall rates, biopsy rates, and positive predictive value (PPV2). CONCLUSION: DBT-MG shows enhanced diagnostic efficacy, potentially diminishing recall costs. While exhibiting a higher biopsy rate, DBT-MG aids in the detection of early-stage breast cancers, reduces recall rates, and exhibits notably superior cost-effectiveness.

Cost-Utility Analysis of Tenofovir Alafenamide and Entecavir in Chronic Hepatitis B Patients: A Markov Decision Model.

From the perspective of health economics, the evaluation of drug-related cost effectiveness and clinical utility is crucial. We conducted a cost-utility analysis of two first-line drugs, tenofovir alafenamide (TAF) and entecavir (ETV), in the treatment of chronic hepatitis B (CHB) patients. We performed inverse probability of treatment weighting (IPTW) to match the independent variables between the two treatment groups. The incremental cost effectiveness ratio (ICER) of the two treatment groups was simulated using a decision tree with the Markov annual-cycle model. A total of 54 patients treated with TAF and 98 with ETV from January 2016 to December 2020 were enrolled. The total medical cost in the TAF group was NT$76,098 less than that in the ETV group, and TAF demonstrated more effectiveness than ETV by 3.19 quality-adjusted life years (QALYs). When the time horizon was set at 30 years, the ICER of the TAF group compared with the ETV group was -NT$23,878 per QALY, suggesting more cost savings for TAF. Additionally, with the application of TAF, over NT$366 million (approximately US$12 million) can be saved annually. TAF demonstrates cheaper medical costs and more favorable clinical QALYs than ETV. To balance health insurance benefits and cost effectiveness, TAF is the optimal treatment for CHB.

Relationship between using cancer resource center services and patient outcomes.

PURPOSE: Psychological and social support are crucial in treating cancer. Cancer resource centers provide patients with cancer and their families with services that can help them through cancer treatment, ensure that patients receive adequate treatment, and reduce cancer-related stress. These centers offer various services, including medical guidance, health education, emotional assistance (e.g., consultations for cancer care), and access to resources such as financial aid and post recovery programs. In this study, we comprehensively analyzed how cancer resource centers assist patients with cancer and improve their clinical outcomes. METHODS: The study participants comprised patients initially diagnosed with head and neck cancer or esophageal cancer. A total of 2442 patients from a medical center in Taiwan were included in the study. Data were analyzed through logistic regression and Cox proportional hazards regression. RESULTS: The results indicate that unemployment, blue-collar work, and a lower education level were associated with higher utilization of cancer resource center services. The patients who were unemployed or engaged in blue-collar work had higher risks of mortality than did their white-collar counterparts. Patient education programs can significantly improve the survival probability of patients with cancer. On the basis of our evaluation of the utilization and benefits of services provided by cancer resource centers, we offer recommendations for improving the functioning of support systems for patients with cancer and provide suggestions for relevant future research. CONCLUSIONS: We conclude that cancer resource centers provide substantial support for patients of low socioeconomic status and improve patients' survival.

Clinical Outcomes and Cost-Effectiveness of Osteoporosis Screening With Dual-Energy X-ray Absorptiometry.

OBJECTIVE: This study aimed to evaluate the clinical outcomes and cost-effectiveness of dual-energy X-ray absorptiometry (DXA) for osteoporosis screening. MATERIALS AND METHODS: Eligible patients who had and had not undergone DXA screening were identified from among those aged 50 years or older at Kaohsiung Veterans General Hospital, Taiwan. Age, sex, screening year (index year), and Charlson comorbidity index of the DXA and non-DXA groups were matched using inverse probability of treatment weighting (IPTW) for propensity score analysis. For cost-effectiveness analysis, a societal perspective, 1-year cycle length, 20-year time horizon, and discount rate of 2% per year for both effectiveness and costs were adopted in the incremental cost-effectiveness (ICER) model. RESULTS: The outcome analysis included 10337 patients (female:male, 63.8%:36.2%) who were screened for osteoporosis in southern Taiwan between January 1, 2012, and December 31, 2021. The DXA group had significantly better outcomes than the non-DXA group in terms of fragility fractures (7.6% vs. 12.5%, P < 0.001) and mortality (0.6% vs. 4.3%, P < 0.001). The DXA screening strategy gained an ICER of US$ -2794 per quality-adjusted life year (QALY) relative to the non-DXA at the willingness-to-pay threshold of US$ 33004 (Taiwan's per capita gross domestic product). The ICER after stratifying by ages of 50-59, 60-69, 70-79, and ≥ 80 years were US$ -17815, US$ -26862, US$ -28981, and US$ -34816 per QALY, respectively. CONCLUSION: Using DXA to screen adults aged 50 years or older for osteoporosis resulted in a reduced incidence of fragility fractures, lower mortality rate, and reduced total costs. Screening for osteoporosis is a cost-saving strategy and its effectiveness increases with age. However, caution is needed when generalizing these cost-effectiveness results to all older populations because the study population consisted mainly of women.

Clinical and cost-effectiveness analysis of mFOLOFX6 with or without a targeted drug among patients with metastatic colorectal cancer: inverse probability of treatment weighting.

This study investigated the cost-effectiveness and quality of life (QoL) within 1 year of receiving mFOLOFX6 with or without a targeted drug (bevacizumab or ramucirumab) as second-line treatment among patients with metastatic colorectal cancer (mCRC) following the failure of FOLFIRI + bevacizumab as first-line treatment. This prospective cohort study included patients who received a diagnosis of mCRC between March 2015 and May 2020. QoL was evaluated before treatment and at 6 months and 1 year posttreatment. All related variables were controlled using the inverse probability of treatment weighting method. Generalized estimating equations with the difference-in-difference method was used to explore changes in QoL. The incremental cost-utility ratio (ICUR) of the two groups was simulated using the annual-cycle Markov decision tree model. Finally, 39 and 76 patients were included in the targeted and nontargeted agent groups, respectively. At 6 months after treatment, QoL of the two groups improved significantly, but the targeted agent group had significantly better QoL than did the nontargeted agent group at 1 year posttreatment (P < 0.05). When the time frame was set to 20 years, the ICUR of the targeted agent group compared with the nontargeted agent group was US$32,052 per quality-adjusted life years. Addition of a targeted drug to the second-line mFOLOFX6 regimen not only improved the patients' QoL but was also more cost effective when the willingness-to-pay threshold was set at US$33,004 (the per capita gross domestic product of Taiwan). These patients should be reimbursed for these targeted agents by the National Health Insurance scheme in Taiwan.

Minimal Clinically Important Difference (MCID) in the Functional Status Measures in Patients with Stroke: Inverse Probability Treatment Weighting.

This study proposed to evaluate the temporal trend, define the minimal clinically important difference (MCID) for five functional status measures, and identify risk factors for reaching deterioration in the MCID. This prospective cohort study analyzed 680 patients with ischemic stroke and 151 patients with hemorrhagic stroke at six hospitals between April 2015 and October 2021. All patients completed the functional status measures before rehabilitation (baseline), and at the 12th week and 2nd year after rehabilitation. Patients in the post-acute care (PAC) group exhibited significantly larger improvements for the functional status measures compared to those in the non-PAC group (p < 0.05). Patients with hemorrhagic stroke also displayed larger improvements in the functional status measures when compared to patients with ischemic stroke. Furthermore, the improvement in MCID ranged from 0.01 to 16.18 points when comparing baseline and the 12th week after rehabilitation, but the deterioration in MCID ranged from 0.38 to 16.12 points. Simultaneously, assessing the baseline and the second year after rehabilitation, the improvement in MCID ranged from 0.01 to 18.43 points, but the deterioration in MCID ranged from 0.68 to 17.26 points. Additionally, the PAC program, age, education level, body mass index, smoking, readmission within 30 days, baseline functional status score, use of Foley catheter and nasogastric tube, as well as a history of previous stroke are significantly associated with achieving deterioration in MCID (p < 0.05). These findings suggest that if the mean change scores of the functional status measures have reached the thresholds, the change scores can be perceived by patients as clinically important.

Quality of life and cost-effectiveness of different breast cancer surgery procedures: a Markov decision tree-based approach in the framework of Predictive, Preventive, and Personalized Medicine.

Purpose: Breast cancer is a complex disease with heterogeneous outcomes that may benefit from the implementation of Predictive, Preventive, and Personalized Medicine (PPPM/3PM) strategies. In this study, we aimed to explore the potential of PPPM approaches by investigating the 10-year trends in quality of life (QOL) and the cost-effectiveness of different types of surgeries for patients with breast cancer. Methods: This prospective cohort study recruited 144 patients undergoing breast conserving surgery (BCS), 199 undergoing modified radical mastectomy (MRM), and 44 undergoing total mastectomy with transverse rectus abdominis myocutaneous flap (TRAMF) from three medical centers in Taiwan between June 2007 and June 2010. Results: All patients exhibited a significant decrease in most QOL dimension scores from before surgery to 6 months postoperatively (p < 0.05); however, from postoperative year 1 to 2, improvement in most QOL dimension scores was significantly better in the TRAMF group than in the BCS and MRM groups (p < 0.05). At 2, 5, and 10 years after surgery, the patients' QOL remained stable. In the Markov decision tree model, the TRAMF group had higher total direct medical costs than the MRM and BCS groups (US$ 32,426, US$ 29,487, and US$ 28,561, respectively) and higher average QALYs gained (7.771, 6.773, and 7.385, respectively), with an incremental cost-utility ratio (ICUR) of US$ 2,944.39 and US$ 10,013.86 per QALY gained. Conclusions: TRAMF appeared cost effective compared with BCS and MRM, and it has been proved with considerable QOL improvements in the framework of PPPM. Future studies should continue to explore the potential of PPPM approaches in breast cancer care. By incorporating predictive models, personalized treatment plans, and preventive strategies into routine clinical practice, we can further optimize patient outcomes and reduce healthcare costs associated with breast cancer treatment. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-023-00326-4.

Medium-term surgical outcomes and health-related quality of life after laparoscopic vs open colorectal cancer resection: SF-36 health survey questionnaire.

BACKGROUND: Previous studies that compared the postoperative health-related quality of life (HRQoL) outcomes after receiving laparoscopic resection (LR) or open resection (OR) in patients with colorectal cancer (CRC) have different conclusions. AIM: To explore the medium-term effect of postoperative HRQoL in such patients. METHODS: This study randomized 567 patients undergoing non-metastatic CRC surgery managed by one surgeon to the LR or OR groups. HRQoL was assessed during the preoperative period and 3, 6, and 12 mo postoperative using a modified version of the 36-Item Short Form (SF-36) Health Survey questionnaire, emphasizing eight specific items. RESULTS: This cohort randomly assigned 541 patients to receive LR (n = 296) or OR (n = 245) surgical procedures. More episodes of postoperative urinary tract infection (P < 0.001), wound infection (P < 0.001), and pneumonia (P = 0.048) were encountered in the OR group. The results demonstrated that the LR group subjectively gained mildly better general health (P = 0.045), moderately better physical activity (P = 0.006), and significantly better social function recovery (P = 0.0001) 3 mo postoperatively. Only the aspect of social function recovery was claimed at 6 mo, with a significant advantage in the LR group (P = 0.001). No clinical difference was found in HRQoL during the 12 mo. CONCLUSION: Our results demonstrated that LR resulted in better outcomes, including intra-operative blood loss, surgery-related complications, course of recovery, and especially some health domains of HRQoL at least within 6 mo postoperatively. Patients should undergo LR if there is no contraindication.

Long-term care insurance purchase decisions of registered nurses: Deep learning versus logistic regression models.

OBJECTIVE: The purpose of this study was to use a deep learning model and a traditional statistical regression model to predict the long-term care insurance decisions of registered nurses. METHODS: We Prospectively surveyed 1,373 registered nurses with a minimum of 2 years of full-time working experience at a large medical center in Taiwan: 615 who already owned long-term care insurance (LTCI), 332 who had no intention to purchase LTCI (group 1), and 426 who intended to purchase LTCI (group 2). RESULTS: After inverse probability of treatment weighting (IPTW), no statistically significant differences were identified in the study characteristics of the two groups. All the performance indices for the deep neural network (DNN) model were significantly higher than those of the multiple logistic regression (MLR) model (P<0.001). The strongest predictor of an individual's long-term care insurance decision was their risk propensity score, followed by their caregiving responsibilities, whether they live with older adult relatives, their experiences of catastrophic illness, and their openness to experience. CONCLUSIONS: The DNN model is useful for predicting long-term care insurance decisions. Its prediction accuracy can be increased through training with temporal data collected from registered nurses. Future research can explore designs for two-level or multilevel models that explain the contextual effects of the risk factors on long-term care insurance decisions.

5-year recurrence prediction after hepatocellular carcinoma resection: deep learning vs. Cox regression models.

Deep learning algorithms have yet to be used for predicting clinical prognosis after cancer surgery. Therefore, this study compared performance indices and permutation importance of potential confounders in three models for predicting 5-year recurrence after hepatocellular carcinoma (HCC) resection: a deep-learning deep neural network (DNN) model, a recurrent neural network (RNN) model, and a Cox proportional hazard (CPH) regression model. Data for 725 patients who had received HCC resection at three medical centers in southern Taiwan between April, 2011, and December, 2015, were randomly divided into three datasets: a training dataset containing data for 507 subjects was used for model development, a testing dataset containing data for 109 subjects was used for internal validation, and a validating dataset containing data for 109 subjects was used for external validation. Feature importance analysis was also performed to identify potential predictors of recurrence after HCC resection. Univariate Cox proportional hazards regression analyses were performed to identify potential significant predictors of 5-year recurrence after HCC resection, which were included in the forecasting models (P < 0.05). All performance indices for the DNN model were significantly higher than those for the RNN model and the conventional CPH model (P < 0.001). The most important potential predictor of 5-year recurrence after HCC resection was surgeon volume followed by, in order of importance, hospital volume, preoperative Beck Depression Scale score, preoperative Beck Anxiety Scale score, co-residence with family, tumor stage, and tumor size. The feature importance analysis performed to investigate interpretability in this study elucidated the potential use of deep learning models for predicting recurrence after HCC resection and for identifying predictors of recurrence. Further experiments using the proposed DNN model would clarify its potential uses for developing, promoting, and improving health policies for treating HCC patients after surgery.

Predicting 30-Day Readmission for Stroke Using Machine Learning Algorithms: A Prospective Cohort Study.

Background: Machine learning algorithms for predicting 30-day stroke readmission are rarely discussed. The aims of this study were to identify significant predictors of 30-day readmission after stroke and to compare prediction accuracy and area under the receiver operating characteristic (AUROC) curve in five models: artificial neural network (ANN), K nearest neighbor (KNN), random forest (RF), support vector machine (SVM), naive Bayes classifier (NBC), and Cox regression (COX) models. Methods: The subjects of this prospective cohort study were 1,476 patients with a history of admission for stroke to one of six hospitals between March, 2014, and September, 2019. A training dataset (n = 1,033) was used for model development, and a testing dataset (n = 443) was used for internal validation. Another 167 patients with stroke recruited from October, to December, 2019, were enrolled in the dataset for external validation. A feature importance analysis was also performed to identify the significance of the selected input variables. Results: For predicting 30-day readmission after stroke, the ANN model had significantly (P < 0.001) higher performance indices compared to the other models. According to the ANN model results, the best predictor of 30-day readmission was PAC followed by nasogastric tube insertion and stroke type (P < 0.05). Using a machine learning ANN model to obtain an accurate estimate of 30-day readmission for stroke and to identify risk factors may improve the precision and efficacy of management for these patients. Conclusion: Using a machine-learning ANN model to obtain an accurate estimate of 30-day readmission for stroke and to identify risk factors may improve the precision and efficacy of management for these patients. For stroke patients who are candidates for PAC rehabilitation, these predictors have practical applications in educating patients in the expected course of recovery and health outcomes.

Cost Utility Analysis of Multidisciplinary Postacute Care for Stroke: A Prospective Six-Hospital Cohort Study.

Background: Few studies have compared the optimal duration and intensity of organized multidisciplinary neurological/rehabilitative care delivered in a regional/district hospital with the standard rehabilitative care delivered in the general neurology/rehabilitation ward of a medical center. This study measured functional outcomes and conducted cost-utility analysis of an organized multidisciplinary postacute care (PAC) project in secondary care compared with standard rehabilitative care delivered in tertiary care. Methods: This prospective cohort study enrolled 1,476 patients who had a stroke between March 2014 and March 2018 and had a modified Rankin scale score of 2-4. After exact matching for age ± 1 year, sex, year of stroke diagnosis, nasogastric tube, and Foley catheter and propensity score matching for the other covariates, we obtained 120 patients receiving PAC (the PAC group) from four regional/district hospitals and 120 patients not receiving PAC (the non-PAC group) from two medical centers. Results: At baseline, the non-PAC group showed significantly better functional outcomes than the PAC group, including EuroQol-5 dimensions (EQ-5D), Mini-Mental State Examination (MMSE) and Barthel index (BI). During weeks 7-12 of rehabilitation, improvements in all functional outcomes were significantly larger in the PAC group (P < 0.001) except for Functional Oral Intake Scale (FOIS). Cost-utility analysis revealed that the PAC group had a significantly lower mean (± standard deviation) of direct medical costs (US$3,480 ± $1,758 vs. US$3,785 ± $3,840, P < 0.001) and a significantly higher average gain of quality-adjusted life years (0.1993 vs. 0.1233, P < 0.001). The PAC project was an economically "dominant" strategy. Conclusions: The PAC project saved costs and significantly improved the functional outcomes of patients with stroke with slight to moderately severe disabilities. Randomized control trials are required to corroborate these results.

Effectiveness and Cost-Utility Analysis of Different Doses of Irinotecan Plus Bevacizumab in Patients With Metastatic Colorectal Cancer: A Long-Term and Prospective Cohort Study.

Objective: Patients with metastatic colorectal cancer (mCRC) had oncological benefits with irinotecan dose escalation of FOLFIRI regimen combined with bevacizumab according to UGT1A1 genotypes in our previous study. In the current study, we performed a quality of life (QOL) outcome evaluation and cost-utility analysis of different irinotecan dose regimens in patients with mCRC. Materials and Methods: With inverse probability-of-treatment weighting (IPTW) matching on all covariates, 75 patients with dose escalation of irinotecan (study group) and 121 patients with the recommended dose of irinotecan (control group) were recruited between October 2015 and December 2019. The QOL outcome measures were Functional Assessment of Cancer Therapy-Colorectal, Beck Anxiety Inventory, Beck Depression Inventory, and SF-36; cost-utility outcome measures were medical direct costs, quality-adjusted life-years (QALYs), and incremental cost-utility ratios (ICURs). Results: All mCRC patients exhibited a significant decrease in both emotional wellbeing and depression from pretherapeutic period to posttherapeutic 6th month (P < 0.05); however, from the posttherapeutic 1st year to the 2nd year, improvement in most QOL measures was significantly better in the study group than in the control group (P < 0.05). Over a 2-year time period, the study group had higher total medical direct costs than the control group (US$ 54,742 ± 14,013 vs. US$ 54,608 ± 9,673) and higher average QALYs gained (1.88 vs. 1.65), with an ICUR of US$ 583 per QALY gained. Conclusion: For patients with mCRC, irinotecan dose escalation appeared cost-effective with considerable QOL improvements during the study period. Further randomized, multi-institutional controlled trials are warranted to corroborate these results.

The Cost-Effectiveness Analysis of Transplant-Ineligible Myeloma Patients with Bortezomib plus Thalidomide plus Dexamethasone (VTD) or Bortezomib plus Melphalan plus Prednisolone (VMP) Treatment in Southern Taiwan.

BACKGROUND: This study aimed to evaluate the cost-effectiveness of treating transplant-ineligible myeloma patients with either a bortezomib plus thalidomide plus dexamethasone (VTD) or a bortezomib plus melphalan plus prednisolone (VMP) treatment in Taiwan. METHODS: Newly diagnosed, transplant-ineligible myeloma patients with VTD or VMP therapy were enrolled from two medical centers in southern Taiwan. Quality-adjusted life years (QALYs) were used as the measurement unit of the effectiveness evaluation, and the incremental cost-effectiveness ratio (ICER) was used for comparison between the two groups. A net monetary benefit approach and cost-effectiveness acceptability curve were also used for the cost-effectiveness assessment. A one-way sensitivity analysis was used to check the impact of different parameters. In total, 77 patients were enrolled in the study with 43 patients in the VTD group and 34 patients in the VMP group. Clinical presentations were similar without significant difference, except the VTD group had a higher survival rate (p = 0.029). Comparisons of the two groups over an eight-month time horizon revealed a significant lower mean of direct medical costs in the VTD group than in the VMP group (p < 0.001), and a significantly higher average QALY was gained (p < 0.001). CONCLUSIONS: The study demonstrated the greater clinical benefit and cost-effectiveness of VTD compared to VMP therapy in transplant-ineligible, newly diagnosed myeloma patients.

Inverse Probability of Treatment Weighting in 5-Year Quality-of-Life Comparison among Three Surgical Procedures for Hepatocellular Carcinoma.

This prospective longitudinal cohort study analyzed long-term changes in individual subscales of quality-of-life (QOL) measures and explored whether these changes were related to effective QOL predictors after hepatocellular carcinoma (HCC) surgery. All 520 HCC patients in this study had completed QOL surveys before surgery and at 6 months, 2 years, and 5 years after surgery. Generalized estimating equation models were used to compare the 5-year QOL among the three HCC surgical procedures. The QOL was significantly (p < 0.05) improved at 6 months after HCC surgery but plateaued at 2−5 years after surgery. In postoperative surveys, the effect size was largest in the nausea and vomiting subscales in patients who had received robotic surgery, and the effect size was smallest in the dyspnea subscale in patients who had received open surgery. It revealed the following explanatory variables for postoperative QOL: surgical procedure type, gender, age, hepatitis C, smoking, tumor stage, postoperative recurrence, and preoperative QOL. The comparisons revealed that, when evaluating QOL after HCC surgery, several factors other than the surgery itself should be considered. The analysis results also implied that postoperative quality of life might depend not only on the success of the surgical procedure, but also on preoperative quality of life.

Cost and Effectiveness of Long-Term Care Following Integrated Discharge Planning: A Prospective Cohort Study.

Little is known about the effects of seamless hospital discharge planning on long-term care (LTC) costs and effectiveness. This study evaluates the cost and effectiveness of the recently implemented policy from hospital to LTC between patients discharged under seamless transition and standard transition. A total of 49 elderly patients in the standard transition cohort and 119 in the seamless transition cohort were recruited from November 2016 to February 2018. Data collected from medical records included the Multimorbidity Frailty Index, Activities of Daily Living Scale, and Malnutrition Universal Screening Tool during hospitalization. Multiple linear regression and Cox regression models were used to explore risk factors for medical resource utilization and medical outcomes. After adjustment for effective predictors, the seamless cohort had lower direct medical costs, a shorter length of stay, a higher survival rate, and a lower unplanned readmission rate compared to the standard cohort. However, only mean total direct medical costs during hospitalization and 6 months after discharge were significantly (p < 0.001) lower in the seamless cohort (USD 6192) compared to the standard cohort (USD 8361). Additionally, the annual per-patient economic burden in the seamless cohort approximated USD 2.9-3.3 billion. Analysis of the economic burden of disability in the elderly population in Taiwan indicates that seamless transition planning can save approximately USD 3 billion in annual healthcare costs. Implementing this policy would achieve continuous improvement in LTC quality and reduce the financial burden of healthcare on the Taiwanese government.

Determinants of Successful Nursing Home Accreditation.

OBJECTIVES: This study examined the factors associated with better accreditation outcomes among nursing homes. METHOD: A total of 538 nursing homes in Taiwan were included in this study. Measures included accreditation scores, external factors (household income, Herfindahl-Hirschman Index, old-age dependency ratio, population density, and number of older adult households), organizational factors (hospital-based status, chain-affiliated status, occupancy rate, the number of registered nurses or nurse aides per bed, and bed size), and internal factors (accountability, deficiencies, person-centered care, nursing skills, quality control, and integrated care). RESULTS: Bed size, hospital-based status, accountability, deficiencies, person-centered care, nursing skills, quality control, and integrated care were found to predict accreditation. CONCLUSION: Among all variables in this study, the quality indicators contributed to the most variation, followed by organizational factors. External environmental factors played a minor role in predicting accreditation. A focus on quality of care would benefit not only the residents of a nursing home but also facilitate its accreditation.

Multidisciplinary Care after Acute Care for Stroke: A Prospective Comparison between a Multidisciplinary Post-Acute Care Group and a Standard Group Matched by Propensity Score.

In this large-scale prospective cohort study, a propensity score matching method was applied in a natural experimental design to investigate how post-acute care (PAC) after stroke affects functional status and to identify predictors of functional status. The main objective of this study was to examine longitudinal changes in various measures of functional status in stroke patients and predictors of scores for these measures before and after PAC. A group of patients who had received PAC for stroke at one of two medical centers (PAC group, n = 273) was compared with a group who had received standard care for stroke at one of four hospitals (three regional hospital and one district hospital; non-PAC group, n = 273) in Taiwan from March, 2014, to October, 2018. The patients completed the functional status measures before rehabilitation, the 12th week and the 1st year after rehabilitation. Generalized estimating equations were used to estimate differences-in-differences models for examining the effects of PAC. The average age was 68.0 (SD = 8.1) years, and males accounted for 57.9%. During the follow-up period, significant risk factors for poor functional outcomes were advanced age, hemorrhagic stroke, and poor function scores before rehabilitation (p < 0.05). Between-group comparisons at subsequent time points revealed significantly higher functional status scores in the PAC group versus the non-PAC group (p < 0.001). Notably, for all functional status measures, between-group differences in total scores significantly increased over time from baseline to 1 year post-rehabilitation (p < 0.001). The contribution of this study is its further elucidation of the clinical implications and health policy implications of rehabilitative care after stroke. Specifically, it improves understanding of the effects of PAC in stroke patients at different follow-up times. Therefore, a policy implication of this study is that standard care for stroke should include intensive rehabilitative PAC to maximize recovery of overall function.