Validity of the Johns Hopkins Adjusted Clinical Groups system on the utilisation of healthcare services in Norway: a retrospective cross-sectional study.

BACKGROUND: The Adjusted Clinical Groups (ACG) System is a validated electronic risk stratification system. However, there is a lack of studies on the association between different ACG risk scores and the utilisation of different healthcare services using different sources of input data. The aim of this study was therefore to assess the validity of the association between five different ACG risk scores and the utilisation of a range of different healthcare services using input data from either general practitioners (GPs) or hospitals. METHODS: Registry-based study of all adult inhabitants in four Norwegian municipalities that received somatic healthcare in one year (N = 168 285). The ACG risk scores resource utilisation band, unscaled ACG concurrent risk, unscaled concurrent risk, frailty flag and chronic condition count were calculated using age, sex and diagnosis codes from GPs and a hospital, respectively. Healthcare utilisation covered GP, municipal and hospital services. Areas under the receiver operating curve (AUC) were calculated and compared to the AUC of a model using only age and sex. RESULTS: Utilisation of all healthcare services increased with increasing scores in the "resource utilisation band" (RUB) and all other investigated ACG risk scores. The risk scores overall distinguished well between levels of utilisation of GP visits (AUC up to 0.84), hospitalisation (AUC up to 0.8) and specialist outpatient visits (AUC up to 0.72), but not out-of-hours GP visits (AUC up to 0.62). The score "unscaled ACG concurrent risk" overall performed best. Risk scores based on data from either GPs or hospitals performed better for the classification of healthcare services in their respective domains. The model based on age and sex performed better for distinguishing between levels of utilisation of municipal services (AUC 0.83-0.90 compared to 0.46-0.79). CONCLUSIONS: Risk scores from the ACG system is valid for classifying GP visits, hospitalisation and specialist outpatient visits. It does not outperform simpler models in the classification of utilisation of municipal services such as nursing homes and home services and outpatient emergency care in primary healthcare. The ACG system can be applied in Norway using administrative data from either GPs or hospitals.

Impact of early death recording on international comparison of acute myocardial infarction mortality - administrative hospital data study using the example of Germany and the United States.

BACKGROUND: In-hospital mortality from acute myocardial infarction (AMI) is widely used in international comparisons as an indicator of health system performance. Because of the high risk of early death after AMI, international comparisons may be biased by differences in the recording of early death cases in hospital inpatient data. This study examined whether differences in the recording of early deaths affect international comparisons of AMI in-hospital mortality by using the example of Germany and the United States, and explored approaches to address this issue. METHODS: The German Diagnosis-Related Groups Statistics (DRG Statistics), the U.S. National Inpatient Sample (NIS) and the U.S. Nationwide Emergency Department Sample (NEDS) were analysed from 2014 to 2019. Cases with treatment for AMI were identified in German and U.S. inpatient data. AMI deaths occurring in the emergency department (ED) without inpatient admission were extracted from NEDS data. 30-day in-hospital mortality figures were calculated according to the OECD indicator definition (unlinked data) and modified by including ED deaths, or excluding all same-day cases. RESULTS: German age-and-sex standardized 30-day in-hospital mortality was substantially higher compared to the U.S. (in 2019, 7.3% vs. 4.6%). The ratio of German vs. U.S. mortality was 1.6. After inclusion of ED deaths in U.S. data this ratio declined to 1.4. Exclusion of same-day cases in German and U.S. data led to a similar ratio. CONCLUSIONS: While short-duration treatments due to early death are generally recorded in German inpatient data, in U.S. inpatient data those cases are partially missing. Excluding cases with short-duration treatment from the calculation of mortality indicators could be a feasible approach to account for differences in the recording of early deaths, that might be existent in other countries as well.

Lower comorbidity scores and severity levels in Veterans Health Administration hospitals: a cross-sectional study.

BACKGROUND: Previous studies found that documentation of comorbidities differed when Veterans received care within versus outside Veterans Health Administration (VHA). Changes to medical center funding, increased attention to performance reporting, and expansion of Clinical Documentation Improvement programs, however, may have caused coding in VHA to change. METHODS: Using repeated cross-sectional data, we compared Elixhauser-van Walraven scores and Medicare Severity Diagnosis Related Group (DRG) severity levels for Veterans' admissions across settings and payers over time, utilizing a linkage of VHA and all-payer discharge data for 2012-2017 in seven US states. To minimize selection bias, we analyzed records for Veterans admitted to both VHA and non-VHA hospitals in the same year. Using generalized linear models, we adjusted for patient and hospital characteristics. RESULTS: Following adjustment, VHA admissions consistently had the lowest predicted mean comorbidity scores (4.44 (95% CI 4.34-4.55)) and lowest probability of using the most severe DRG (22.1% (95% CI 21.4%-22.8%)). In contrast, Medicare-covered admissions had the highest predicted mean comorbidity score (5.71 (95% CI 5.56-5.85)) and highest probability of using the top DRG (35.3% (95% CI 34.2%-36.4%)). CONCLUSIONS: More effective strategies may be needed to improve VHA documentation, and current risk-adjusted comparisons should account for differences in coding intensity.

Health Equity Adjustment and Hospital Performance in the Medicare Value-Based Purchasing Program.

Importance: Medicare's Hospital Value-Based Purchasing (HVBP) program will provide a health equity adjustment (HEA) to hospitals that have greater proportions of patients dually eligible for Medicare and Medicaid and that offer high-quality care beginning in fiscal year 2026. However, which hospitals will benefit most from this policy change and to what extent are unknown. Objective: To estimate potential changes in hospital performance after HEA and examine hospital patient mix, structural, and geographic characteristics associated with receipt of increased payments. Design, Setting, and Participants: This cross-sectional study analyzed all 2676 hospitals participating in the HVBP program in fiscal year 2021. Publicly available data on program performance and hospital characteristics were linked to Medicare claims data on all inpatient stays for dual-eligible beneficiaries at each hospital to calculate HEA points and HVBP payment adjustments. Exposures: Hospital Value-Based Purchasing program HEA. Main Outcomes and Measures: Reclassification of HVBP bonus or penalty status and changes in payment adjustments across hospital characteristics. Results: Of 2676 hospitals participating in the HVBP program in fiscal year 2021, 1470 (54.9%) received bonuses and 1206 (45.1%) received penalties. After HEA, 102 hospitals (6.9%) were reclassified from bonus to penalty status, whereas 119 (9.9%) were reclassified from penalty to bonus status. At the hospital level, mean (SD) HVBP payment adjustments decreased by $4534 ($90 033) after HEA, ranging from a maximum reduction of $1 014 276 to a maximum increase of $1 523 765. At the aggregate level, net-positive changes in payment adjustments were largest among safety net hospitals ($28 971 708) and those caring for a higher proportion of Black patients ($15 468 445). The likelihood of experiencing increases in payment adjustments was significantly higher among safety net compared with non-safety net hospitals (574 of 683 [84.0%] vs 709 of 1993 [35.6%]; adjusted rate ratio [ARR], 2.04 [95% CI, 1.89-2.20]) and high-proportion Black hospitals compared with non-high-proportion Black hospitals (396 of 523 [75.7%] vs 887 of 2153 [41.2%]; ARR, 1.40 [95% CI, 1.29-1.51]). Rural hospitals (374 of 612 [61.1%] vs 909 of 2064 [44.0%]; ARR, 1.44 [95% CI, 1.30-1.58]), as well as those located in the South (598 of 1040 [57.5%] vs 192 of 439 [43.7%]; ARR, 1.25 [95% CI, 1.10-1.42]) and in Medicaid expansion states (801 of 1651 [48.5%] vs 482 of 1025 [47.0%]; ARR, 1.16 [95% CI, 1.06-1.28]), were also more likely to experience increased payment adjustments after HEA compared with their urban, Northeastern, and Medicaid nonexpansion state counterparts, respectively. Conclusions and Relevance: Medicare's implementation of HEA in the HVBP program will significantly reclassify hospital performance and redistribute program payments, with safety net and high-proportion Black hospitals benefiting most from this policy change. These findings suggest that HEA is an important strategy to ensure that value-based payment programs are more equitable.

Lessons learned from value-based pediatric appendectomy care: A shared savings pilot model.

PURPOSE: We aim to assess the healthcare value achieved from a shared savings program for pediatric appendectomy. METHODS: All appendectomy patients covered by our health plan were included. Quality targets were 15% reduction in time to surgery, length of stay, readmission rate, and patient satisfaction. Quality targets and costs for an appendectomy episode in two 6-month performance periods (PP1, PP2) were compared to baseline. RESULTS: 640 patients were included (baseline:317, PP1:167, PP2:156). No quality targets were met in PP1. Two quality targets were met during PP2: readmission rate (-57%) and patient satisfaction. No savings were realized because the cost reduction threshold (-9%) was not met during PP1 (+1.7%) or PP2 (-0.4%). CONCLUSIONS: Payer-provider partnerships can be a platform for testing value-based reimbursement models. Setting achievable targets, identifying affectable quality metrics, considering case mix index, and allowing sufficient time for interventions to generate cost savings should be considered in future programs.

Association of the All-Patient Refined Diagnosis-Related Groups Severity of Illness and Risk of Mortality Classification with Outcomes.

OBJECTIVES: Diagnosis-related groups (DRGs) is a patient classification system used to characterize the types of patients that the hospital manages and to compare the resources needed during hospitalization. The DRG classification is based on International Classification of Diseases diagnoses, procedures, demographics, discharge status, and complications or comorbidities and compares hospital resources and outcomes used to determine how much Medicare pays the hospital for each "product/medical condition." The All-Patient Refined DRG (APR-DRG) incorporated severity of illness (SOI) and risk of mortality (ROM) into the DRG system to adjust for patient complexity to compare resource utilization, complication rates, and lengths of stay. METHODS: This study included 18,478 adult patients admitted to a tertiary care center in Lubbock, Texas during a 1-year period. We recorded the APR-DRG SOI and ROM and some clinical information on these patients, including age, sex, admission shock index, admission glucose and lactate levels, diagnoses based on International Classification of Diseases, Tenth Revision discharge coding, length of stay, and mortality. We compared the levels of SOI and ROM across this clinical information. RESULTS: As the levels of SOI and ROM increase (which indicates increased disease severity and risk of mortality), age, glucose levels, lactate levels, shock index, length of stay, and mortality increased significantly (P < 0.001). Multiple logistic regression analysis demonstrated that each unit increase in ROM and SOI level was significantly associated with an 11.45 and a 10.37 times increase in the odds of in-hospital mortality, respectively. The C-statistics for the corresponding models are 0.947 and 0.929, respectively. When both ROM and SOI were included in the model, the magnitudes of increase in odds of in-hospital mortality were 5.61 and 1.17 times for ROM and SOI, respectively. The C-statistic is 0.949. CONCLUSIONS: This study indicates that the APR-DRG SOI and ROM scores provide a classification system that is associated with mortality and correlates with other clinical variables, such as the shock index and lactate levels, which are available on admission.

Quality of Care Before and After Mergers and Acquisitions of Rural Hospitals.

Importance: Rural hospitals are increasingly merging with other hospitals. The associations of hospital mergers with quality of care need further investigation. Objectives: To examine changes in quality of care for patients at rural hospitals that merged compared with those that remained independent. Design, Setting, and Participants: In this case-control study, mergers at community nonrehabilitation hospitals in Federal Office of Rural Health Policy-eligible zip codes during 2009 to 2016 in 32 states were identified from Irving Levin Associates and the American Hospital Association Annual Survey. Outcomes for inpatient stays for select conditions and elective procedures were derived from the Healthcare Cost and Utilization Project State Inpatient Databases. Difference-in-differences linear probability models were used to assess premerger to postmerger changes in outcomes for patients discharged from merged vs comparison hospitals that remained independent. Data were analyzed from February to December 2020. Exposures: Hospital mergers. Main Outcomes and Measures: The main outcome was in-hospital mortality among patients admitted for acute myocardial infarction (AMI), heart failure, stroke, gastrointestinal hemorrhage, hip fracture, or pneumonia, as well as complications during stays for elective surgeries. Results: A total of 172 merged hospitals and 266 comparison hospitals were analyzed. After matching, baseline patient characteristics were similar for 303 747 medical stays and 175 970 surgical stays at merged hospitals and 461 092 medical stays and 278 070 surgical stays at comparison hospitals. In-hospital mortality among AMI stays decreased from premerger to postmerger at merged hospitals (9.4% to 5.0%) and comparison hospitals (7.9% to 6.3%). Adjusting for patient, hospital, and community characteristics, the decrease in in-hospital mortality among AMI stays 1 year postmerger was 1.755 (95% CI, -2.825 to -0.685) percentage points greater at merged hospitals than at comparison hospitals (P < .001). This finding held up to 4 years postmerger (DID, -2.039 [95% CI, -3.388 to -0.691] percentage points; P = .003). Greater premerger to postmerger decreases in mortality at merged vs comparison hospitals were also observed at 5 years postmerger among stays for heart failure (DID, -0.756 [95% CI, -1.448 to -0.064] percentage points; P = .03), stroke (DID, -1.667 [95% CI, -3.050 to -0.283] percentage points; P = .02), and pneumonia (DID, -0.862 [95% CI, -1.681 to -0.042] percentage points; P = .04). Conclusions and Relevance: These findings suggest that rural hospital mergers were associated with better mortality outcomes for AMI and several other conditions. This finding is important to enhancing rural health care and reducing urban-rural disparities in quality of care.

A Simple Approach to Adjust for Case-Mix When Comparing Institutional Cesarean Birth Rates.

OBJECTIVE: This study aimed to develop a validated model to predict intrapartum cesarean in nulliparous women and to use it to adjust for case-mix when comparing institutional laboring cesarean birth (CB) rates. STUDY DESIGN: This multicenter retrospective study used chart-abstracted data on nulliparous, singleton, term births over a 7-year period. Prelabor cesareans were excluded. Logistic regression was used to predict the probability of CB for individual pregnancies. Thirty-five potential predictive variables were evaluated including maternal demographics, prepregnancy health, pregnancy characteristics, and newborn weight and gender. Models were trained on 21,017 births during 2011 to 2015 (training cohort), and accuracy assessed by prediction on 15,045 births during 2016 to 2017 (test cohort). RESULTS: Six variables delivered predictive success equivalent to the full set of 35 variables: maternal weight, height, and age, gestation at birth, medically-indicated induction, and birth weight. Internal validation within the training cohort gave a receiver operator curve with area under the curve (ROC-AUC) of 0.722. External validation using the test cohort gave ROC-AUC of 0.722 (0.713-0.731 confidence interval). When comparing observed and predicted CB rates at 16 institutions in the test cohort, five had significantly lower than predicted rates and three had significantly higher than predicted rates. CONCLUSION: Six routine clinical variables used to adjust for case-mix can identify outliers when comparing institutional CB rates.

Tracheotomy Timing and Outcomes in the Critically Ill: Complexity and Opportunities for Progress.

OBJECTIVES/HYPOTHESIS: To characterize the effects of tracheotomy timing at our institution on intensive care unit (ICU) length of stay (LOS) and overall hospital LOS. STUDY DESIGN: Retrospective cohort study. METHODS: A retrospective study was performed at a tertiary care medical center for patients undergoing tracheotomy over 2.5 years from January 1, 2016 through June 30, 2018. Demographics, survival, duration of endotracheal intubation, timing of tracheotomy, and ICU and overall hospital LOS were assessed. Tracheotomy was considered early (ET) if it was performed by day 7 of mechanical ventilation and late (LT) thereafter. Readmission, mortality, and costs were also tabulated for each aggregate group. Nonparametric statistics were used to compare results. RESULTS: Of the 536 patients included in the analysis, 160 received tracheotomy early and 376 late. Differences between age and sex were not statistically significant. Duration of total ICU stay was shortened by 65% (12.84 ± 17.69 days vs. 38.49 ± 26.61 days; P < .0001), and length of overall hospital course was reduced by 54% (22.71 ± 26.65 days vs. 50.37 ± 34.20 days; P < .0001) in the early tracheotomy group. Observed/expected (O/E) values standardized results to case mix index and revealed LOS of 1.5 for ET and 2.5 for LT, and mortality of 0.76 for ET and 1.25 for LT, and comparable readmissions of both groups. CONCLUSIONS: Early tracheotomy in ICU patients is associated with earlier ICU discharge, decreased length of overall hospital stay, and lower mortality when controlling for case mix index. Opportunities exist to optimize patient outcomes and O/E performance. LEVEL OF EVIDENCE: 4 Laryngoscope, 131:282-287, 2021.

Predictive value of indicators for identifying child maltreatment and intimate partner violence in coded electronic health records: a systematic review and meta-analysis.

OBJECTIVE: Electronic health records (EHRs) are routinely used to identify family violence, yet reliable evidence of their validity remains limited. We conducted a systematic review and meta-analysis to evaluate the positive predictive values (PPVs) of coded indicators in EHRs for identifying intimate partner violence (IPV) and child maltreatment (CM), including prenatal neglect. METHODS: We searched 18 electronic databases between January 1980 and May 2020 for studies comparing any coded indicator of IPV or CM including prenatal neglect defined as neonatal abstinence syndrome (NAS) or fetal alcohol syndrome (FAS), against an independent reference standard. We pooled PPVs for each indicator using random effects meta-analyses. RESULTS: We included 88 studies (3 875 183 individuals) involving 15 indicators for identifying CM in the prenatal period and childhood (0-18 years) and five indicators for IPV among women of reproductive age (12-50 years). Based on the International Classification of Disease system, the pooled PPV was over 80% for NAS (16 studies) but lower for FAS (<40%; seven studies). For young children, primary diagnoses of CM, specific injury presentations (eg, rib fractures and retinal haemorrhages) and assaults showed a high PPV for CM (pooled PPVs: 55.9%-87.8%). Indicators of IPV in women had a high PPV, with primary diagnoses correctly identifying IPV in >85% of cases. CONCLUSIONS: Coded indicators in EHRs have a high likelihood of correctly classifying types of CM and IPV across the life course, providing a useful tool for assessment, support and monitoring of high-risk groups in health services and research.

Decreased hospital admissions through emergency departments during the COVID-19 pandemic.

STUDY OBJECTIVE: Emergency Department (ED) visits decreased significantly in the United States during the COVID-19 pandemic. A troubling proportion of this decrease was among patients who typically would have been admitted to the hospital, suggesting substantial deferment of care. We sought to describe and characterize the impact of COVID-19 on hospital admissions through EDs, with a specific focus on diagnosis group, age, gender, and insurance coverage. METHODS: We conducted a retrospective, observational study of aggregated third-party, anonymized ED patient data. This data included 501,369 patient visits from twelve EDs in Massachusetts from 1/1/2019-9/9/2019, and 1/1/2020-9/8/2020. We analyzed the total arrivals and hospital admissions and calculated confidence intervals for the change in admissions for each characteristic. We then developed a Poisson regression model to estimate the relative contribution of each characteristic to the decrease in admissions after the statewide lockdown, corresponding to weeks 11 through 36 (3/11/2020-9/8/2020). RESULTS: We observed a 32% decrease in admissions during weeks 11 to 36 in 2020, with significant decreases in admissions for chronic respiratory conditions and non-orthopedic needs. Decreases were particularly acute among women and children, as well as patients with Medicare or without insurance. The most common diagnosis during this time was SARS-CoV-2. CONCLUSION: Our findings demonstrate decreased hospital admissions through EDs during the pandemic and suggest that several patient populations may have deferred necessary care. Further research is needed to determine the clinical and operational consequences of this delay.

DRG-Oriented Mathematical Calculation Model and Method of Integrated Medical Service Cost.

In the context of the new round of medical and health reform, in order to alleviate the problem of "difficult to see a doctor and expensive to see a doctor," the state focuses on reducing the cost of medical services, so it puts forward the calculation and method research of medical costs. The purpose of this study is to calculate and predict the cost of medical services in a DRG-oriented integrated environment. In this study, activity-based costing and weighted moving average methods are used. First, basic data of medical services are collected, then all medical activities are confirmed and all service costs are collected, then a cost database is established, and a calculation model of medical costs is designed. Finally, calculation suggestions and optimization methods are put forward by analyzing the calculated data. The experimental results show that the actual demand of drugs predicted by the general moving average method is relatively insufficient, with the maximum error of 41%, the minimum of 5%, and the average error of 19.8%; the maximum error of drug demand predicted by the weighted moving average method is 24%, the minimum is 2%, and the average is 15.4%. It can be concluded that the prediction effect of the weighted moving average method is better than that of the ordinary moving average method, which plays a good and effective role in the prediction of medical cost. The activity-based costing method is more detailed and organized for the cost calculation and classification of medical services. It provides a certain value for the effective management and control of medical service cost.

[Influence of a spontaneous bacterial peritonitis, nosocomial infections and acute-on-chronic liver failure on treatment revenues in patients with decompensated cirrhosis in Germany]. / Einfluss einer spontan bakteriellen Peritonitis, nosokomialer Infektionen und eines akut auf chronischen Leberversagens auf die Behandlungserlöse bei Patienten mit dekompensierter Leberzirrhose in Deutschland.

BACKGROUND: The economic effects of spontaneous bacterial peritonitis (SBP), nosocomial infections (nosInf) and acute-on-chronic liver failure (ACLF) have so far been poorly studied. We analyzed the impact of these complications on treatment revenues in hospitalized patients with decompensated cirrhosis. METHODS: 371 consecutive patients with decompensated liver cirrhosis, who received a paracentesis between 2012 and 2016, were included retrospectively. DRG (diagnosis-related group), "ZE/NUB" (additional charges/new examination/treatment methods), medication costs, length of hospital stay as well as different kinds of specific treatments (e. g., dialysis) were considered. Exclusion criteria included any kind of malignancy, a history of organ transplantation and/or missing accounting data. RESULTS: Total treatment costs (DRG + ZE/NUB) were higher in those with nosInf (€â€Š10,653 vs. €â€Š5,611, p < 0.0001) driven by a longer hospital stay (23 d vs. 12 d, p < 0.0001). Of note, revenues per day were not different (€â€Š473 vs. €â€Š488, p = 0.98) despite a far more complicated treatment with a more frequent need for dialysis (p < 0.0001) and high-complex care (p = 0.0002). Similarly, SBP was associated with higher total revenues (€â€Š10,307 vs. €â€Š6,659, p < 0.0001). However, the far higher effort for the care of SBP patients resulted in lower daily revenues compared to patients without SBP (€â€Š443 vs. €â€Š499, p = 0.18). ACLF increased treatment revenues to €â€Š10,593 vs. €6,369 without ACLF (p < 0.0001). While treatment of ACLF was more complicated, revenue per day was not different to no-ACLF patients (€â€Š483 vs. €â€Š480, p = 0.29). CONCLUSION: SBP, nosInf and/or ACLF lead to a significant increase in the effort, revenue and duration in the treatment of patients with cirrhosis. The lower daily revenue, despite a much more complex therapy, might indicate that these complications are not yet sufficiently considered in the German DRG system.

Self-reported symptoms among participants in a population-based screening program.

BACKGROUND: A limited number of studies have explored the association between self-reported symptoms and the risk of breast cancer among participants of population based screening programs. METHODS: We performed descriptive statistics on recall, screen-detected and interval cancer, positive predictive value and histopathological tumour characteristics by symptom group (asymptomatic, lump, and skin or nipple changes) as reported from 785,642 women aged 50-69 when they attended BreastScreen Norway 1996-2016. Uni- and multivariable mixed effects logistic regression models were used to analyze the association between symptom group and screen-detected or interval cancer. Results were presented as odds ratios and 95% confidence intervals (CI). RESULTS: A lump or skin/nipple change was reported in 6.2% of the 3,307,697 examinations. The rate of screen-detected cancers per 1000 examinations was 45.2 among women with a self-reported lump and 5.1 among asymptomatic women. Adjusted odds ratio of screen-detected cancer was 10.1 (95% CI: 9.3-11.1) and 2.0 (95% CI: 1.6-2.5) for interval cancer among women with a self-reported lump versus asymptomatic women. Tumour diameter, histologic grade and lymph node involvement of screen-detected and interval cancer were less prognostically favourable for women with a self-reported lump versus asymptomatic women. CONCLUSION: Despite targeting asymptomatic women, 6.2% of the screening examinations in BreastScreen Norway was performed among women who reported a lump or skin/nipple change when they attended screening. The odds ratio of screen-detected cancer was higher for women with versus without symptoms. Standardized follow-up guidelines might be beneficial for screening programs in order to take care of women reporting signs or symptoms of breast cancer when they attend screening.

What presents to a rural district emergency department: A case mix.

BACKGROUND: There is little information available on the range of conditions presenting to generalist run rural district hospital emergency departments (EDs) which are the first point of acute care for many South Africans. AIM: This study aims to assess the range of acute presentations as well as the types of procedures required by patients in a rural district hospital context. SETTING: Zithulele is a 147-bed district hospital in rural Eastern Cape. METHODS: This is a cross-sectional study assessing all patients presenting to the Zithulele hospital emergency department from 01 October 2015 to 31 December 2015. Data collected included the triage acuity using the South African Triage Scale system, patient demographics, diagnosis, outcome and procedures performed. Diagnoses were coded retrospectively according to the international statistical classification of diseases and related health problems version 10 (ICD 10). RESULTS: Of the 4 002 patients presenting to the ED during the study period, 2% were triaged as emergencies and 45% as non-urgent. The most common diagnostic categories were injuries, infections and respiratory illnesses respectively. Diagnoses from all broad categories of the ICD-10 were represented. 67% of patients required no procedure. Diagnostic procedures (n = 877) were more prevalent than therapeutic procedures (n = 377). Only 2.4% of patients were transferred to a referral centre acutely. CONCLUSION: Patients with conditions from all categories of the ICD-10 present for management at rural district hospitals. Healthcare professionals working in this setting need to independently diagnose and manage a wide range of ED presentations and execute an assortment of procedures.

Comparison of individual and neighbourhood socioeconomic status in case mix adjustment of hospital performance in primary total hip replacement in Sweden: a register-based study.

BACKGROUND: Case mix adjustment is a pre-requisite for valid measurement of healthcare performance and socioeconomic status (SES) is important to account for. Lack of information on individual-level SES has led to investigations into using a proxy for SES based on patient area of residence. The objective of this study was to use neighbourhood SES for case mix adjustment of performance indicators in total hip replacement (THR) in Sweden, and to compare with use of individual SES. METHODS: Data from patient administrative systems and the Swedish Hip Arthroplasty Register were extracted for all patients undergoing THR in four Swedish regions. For each subject, individual data and neighbourhood data on country of birth, educational level, and income were provided by Statistics Sweden. Three variables were selected for analysis of performance; EQ-5D, hip pain and length of stay (LoS). In addition to socioeconomic information, several important clinical characteristics were used as case mix factors. Regression analysis was used to study each variable's impact on the three outcome variables and model fit was evaluated using mean squared error. RESULTS: A total of 27,121 patients operated between 2010 and 2016 were included in the study. Both educational level and income were higher when based on neighbourhood information than individual information, while proportion born in Sweden was similar. Higher SES was generally found to be associated with better outcomes and lower LoS, albeit with certain differences between the different measures of SES. The predictive ability of the models was increased when adding information on SES to the clinical characteristics. The increase in predictive ability was higher for individual SES compared to neighbourhood SES. When analysing performance for the two providers with most diverging case mix in terms of SES, the inclusion of SES altered the relative performance using individual as well as neighbourhood SES. CONCLUSIONS: Incorporating SES improves case mix adjustment marginally compared to using only clinical information. In this patient group, geographically derived SES was found to improve case mix adjustment compared to only clinical information but not to the same extent as actual individual-level SES.

Association of Do-Not-Resuscitate Patient Case Mix With Publicly Reported Risk-Standardized Hospital Mortality and Readmission Rates.

Importance: The Centers for Medicare and Medicaid Services's (CMS's) 30-day risk-standardized mortality rate (RSMR) and risk-standardized readmission rate (RSRR) models do not adjust for do-not-resuscitate (DNR) status of hospitalized patients and may bias Hospital Readmissions Reduction Program (HRRP) financial penalties and Overall Hospital Quality Star Ratings. Objective: To identify the association between hospital-level DNR prevalence and condition-specific 30-day RSMR and RSRR and the implications of this association for HRRP financial penalty. Design, Setting, and Participants: This cross-sectional study obtained patient-level data from the Medicare Limited Data Set Inpatient Standard Analytical File and hospital-level data from the CMS Hospital Compare website for all consecutive Medicare inpatient encounters from July 1, 2015, to June 30, 2018, in 4484 US hospitals. Hospitalized patients had a principal diagnosis of acute myocardial infarction (AMI), heart failure (HF), stroke, pneumonia, or chronic obstructive pulmonary disease (COPD). Incoming acute care transfers, discharges against medical advice, and patients coming from or discharged to hospice were among those excluded from the analysis. Exposures: Present-on-admission (POA) DNR status was defined as an International Classification of Diseases, Ninth Revision diagnosis code of V49.86 (before October 1, 2015) or as an International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnosis code of Z66 (beginning October 1, 2015). Hospital-level prevalence of POA DNR status was calculated for each of the 5 conditions. Main Outcomes and Measures: Hospital-level 30-day RSMRs and RSRRs for 5 condition-specific cohorts (mortality cohorts: AMI, HF, stroke, pneumonia, and COPD; readmission cohorts: AMI, HF, pneumonia, and COPD) and HRRP financial penalty status (yes or no). Results: Included in the study were 4 884 237 inpatient encounters across condition-specific 30-day mortality cohorts (patient mean [SD] age, 78.8 [8.5] years; 2 608 182 women [53.4%]) and 4 450 378 inpatient encounters across condition-specific 30-day readmission cohorts (patient mean [SD] age, 78.6 [8.5] years; 2 349 799 women [52.8%]). Hospital-level median (interquartile range [IQR]) prevalence of POA DNR status in the mortality cohorts varied: 11% (7%-16%) for AMI, 13% (7%-23%) for HF, 14% (9%-22%) for stroke, 17% (9%-26%) for pneumonia, and 10% (5%-18%) for COPD. For the readmission cohorts, the hospital-level median (IQR) POA DNR prevalence was 9% (6%-15%) for AMI, 12% (6%-22%) for HF, 16% (8%-24%) for pneumonia, and 9% (4%-17%) for COPD. The 30-day RSMRs were significantly higher for hospitals in the highest quintiles vs the lowest quintiles of DNR prevalence (eg, AMI: 12.9 [95% CI, 12.8-13.1] vs 12.5 [95% CI, 12.4-12.7]; P < .001). The inverse was true among the readmission cohorts, with the highest quintiles of DNR prevalence exhibiting the lowest RSRRs (eg, AMI: 15.3 [95% CI, 15.1-15.5] vs 15.9 [95% CI, 15.7-16.0]; P < .001). A 1% absolute increase in risk-adjusted hospital-level DNR prevalence was associated with greater odds of avoiding HRRP financial penalty (odds ratio, 1.06; 95% CI, 1.04-1.08; P < .001). Conclusions and Relevance: This cross-sectional study found that the lack of adjustment in CMS 30-day RSMR and RSRR models for POA DNR status of hospitalized patients may be associated with biased readmission penalization and hospital-level performance.

Assessing the Impacts of Misclassified Case-Mix Factors on Health Care Provider Profiling: Performance of Dialysis Facilities.

Quantitative metrics are used to develop profiles of health care institutions, including hospitals, nursing homes, and dialysis clinics. These profiles serve as measures of quality of care, which are used to compare institutions and determine reimbursement, as a part of a national effort led by the Center for Medicare and Medicaid Services in the United States. However, there is some concern about how misclassification in case-mix factors, which are typically accounted for in profiling, impacts results. We evaluated the potential effect of misclassification on profiling results, using 20 744 patients from 2740 dialysis facilities in the US Renal Data System. In this case study, we compared 30-day readmission as the profiling outcome measure, using comorbidity data from either the Center for Medicare and Medicaid Services Medical Evidence Report (error-prone) or Medicare claims (more accurate). Although the regression coefficient of the error-prone covariate demonstrated notable bias in simulation, the outcome measure-standardized readmission ratio-and profiling results were quite robust; for example, correlation coefficient of 0.99 in standardized readmission ratio estimates. Thus, we conclude that misclassification on case-mix did not meaningfully impact overall profiling results. We also identified both extreme degree of case-mix factor misclassification and magnitude of between-provider variability as 2 factors that can potentially exert enough influence on profile status to move a clinic from one performance category to another (eg, normal to worse performer).

Economic Implications of Chinese Diagnosis-Related Group-Based Payment Systems for Critically Ill Patients in ICUs.

OBJECTIVES: To evaluate the economic implications of payments based on Chinese diagnosis-related groups for critically ill patients in ICUs in terms of total hospital expenditure, out-of-pocket payments, and length of stay. DESIGN: A pre-post comparison of patient cohorts admitted to ICUs 1 year before and 1 year after Chinese diagnosis-related group reform was undertaken. Demographic characteristics, clinical data, and medical expenditures were collated from a health insurance database. SETTING: Twenty-two public hospitals in Sanming, Southern China. PATIENTS: All patients admitted to ICUs from January 1, 2017, to December 31, 2018. INTERVENTION: The implementation of Chinese diagnosis-related group-based payments on January 1, 2018. MEASUREMENTS AND MAIN RESULTS: Economic variables (total expenditures, out-of-pocket payments, and length of stay) were calculated for each patient from the day of hospital admission to the day of hospital discharge. Adjusted mean out-of-pocket payment estimates were 29.46% (p < 0.001) lower following reform. Adjusted mean out-of-pocket payments fell by 41.32% for patients in neonatal ICU, whereas there were no significant decreases in out-of-pocket payments for patients in PICU and adult ICU. Furthermore, adjusted mean out-of-pocket payments decreased by 55.74% in secondary hospitals, but there was no significant change in tertiary hospitals after Chinese diagnosis-related group reform. No significant changes were found in total expenditures and length of stay. CONCLUSIONS: Chinese diagnosis-related group policy provided an opportunity for critically ill patients in ICUs to achieve at least short-term financial benefits in reducing out-of-pocket payments, without affecting the total expenditures and length of stay. Chinese diagnosis-related group-based payment significantly relieved financial burdens for patients with lower illness severities, such as patients in neonatal ICU. The results of this study can offer significant insights for policymakers in reducing the financial burden on critically ill patients, both in China and in other countries with similar systems.