Emprego do modelo matemático SEIHDR para auxiliar gestores na estimativa de ocupação de leitos de UTI em uma pandemia: simulação para pacientes com COVID-19 no município de Porto Alegre / Use of the SEIHDR mathematical model to assist health managers in estimating ICU bed occupancy in a pandemic: simulation for patients with COVID-19 in the city of Porto Alegre, Brazil

Introdução: A pandemia de COVID-19, no Brasil, constituiu uma ameaça ao sistema de saúde pelo risco de esgotamento dos leitos de Unidade de Terapia Intensiva (UTI). O objetivo do estudo foi projetar a ocupação de leitos de UTI com casos de COVID-19 no pico em Porto Alegre. Para isso, resolvemos utilizar uma ferramenta matemática com parâmetros da pandemia desta cidade.Métodos:Utilizamos o modelo matemático SEIHDR. Analisamos os casos de hospitalização por COVID-19 em Porto Alegre e RS até 3 de agosto de 2020 a fim de extrair os parâmetros locais para construir uma curva epidemiológica do total de casos prevalentes hospitalizados em UTI. Também analisamos as taxas de reprodução básica (R0) e reprodução efetiva (Re).Resultados: O modelo matemático projetou um pico de 344 casos prevalentes, em UTI, para o dia 22 de agosto de 2020. Calculamos 1,56 para o R0 e 1,08 no dia 3 de agosto para o Re.Conclusão: O modelo matemático simulou uma primeira onda de casos ocupando leitos de UTI muito próxima dos dados reais. Também indicou corretamente uma queda no número de casos nos dois meses subsequentes. Apesar das limitações, as estimativas do modelo matemático forneceram informações sobre as dimensões temporal e numérica de uma pandemia que poderiam ser usadas como auxílio aos gestores de saúde na tomada de decisões para a alocação de recursos frente a calamidades de saúde como o surto de COVID-19 no Brasil.

Introduction: The COVID-19 pandemic in Brazil has been a threat to health services due to the risk of bed shortage in the intensive care unit (ICU). This study aimed to estimate the bed occupancy at the ICU with patients with COVID-19 during the peak of the pandemic in Porto Alegre, capital of Rio Grande do Sul (RS), the southernmost state of Brazil. To this end, we used a mathematical model with pandemic parameters from the city.Methods: We used the SEIHDR mathematical model. We analyzed hospitalizations for COVID-19 in Porto Alegre and RS until August 3, 2020, to extract local parameters to create an epidemiological curve of the total number of prevalent cases in the ICU. We also analyzed the basic reproduction rate (R0) and effective reproduction rate (Re). Results: The mathematical model estimated a peak of 344 prevalent cases in the ICU on August 22, 2020. The model calculated an R0 of 1.56 and Re of 1.08 on August 3, 2020.Conclusion: The mathematical model accurately estimated the first peak of cases in the ICU. Also, it correctly indicated a drop in the number of cases in the following two months. Despite the limitations, the mathematical model estimates provided information on the temporal and numerical dimensions of a pandemic that could be used to assist health managers in making decisions on the allocation of resources in a state of public calamity such as the COVID-19 outbreak in Brazil.

Association of Multiple Hospital Affiliations With Clinician Service Use, Breadth of Procedures, and Costs.

Importance: Little is known about whether a clinician having multiple hospital affiliations (ie, 1 clinician working across multiple teams and organizations) is associated with clinician practice style and cost. The measurement of this association requires adjusting for selection into multihospital affiliations based on both observable and unobservable clinician characteristics. Objective: To evaluate the association of multiple hospital affiliations with clinician service use, breadth of procedures used, and costs. Design, Setting, and Participants: This cohort study used Medicare Part B data from 2016 through 2017 in a fixed-effects panel data design to compare service use, procedure breadth, and costs between clinicians with multiple affiliations (treatment group) and clinicians with a single affiliation (control group), with adjustment for volume, patients, and clinician characteristics. The study also controlled for unobserved (time-invariant) clinician characteristics using individual clinician fixed effects. Clinicians with Medicare claims, a reported National Provider Identifier, and affiliation data within Medicare Physician Compare were included for a total sample of 1 073 252 observations (633 552 unique clinicians) for medical services and 358 669 observations (210 260 unique clinicians) for drug prescribing. Statistical analyses were performed from February 1 to October 15, 2021. Main Outcomes and Measures: Service use is the total number of medical (or drug) services that clinicians render to their Medicare beneficiaries within a given year, procedure breadth is the total number of unique Healthcare Common Procedure Coding System codes that are associated with clinicians' medical (or drug) services within a given year, and costs represent the total standardized amount paid by Medicare for the medical (or drug) services. Additional measures were multiple-hospital affiliations, Accountable Care Organization affiliation, and controls across clinician and patient characteristics. Results: The medical service sample consisted of 633 552 clinicians (248 359 women [39.2%]; mean [SD] of 19.6 [12.5] years of experience), and the drug service sample consisted of 210 260 clinicians (74 875 women [35.6%]; mean [SD] of 21.6 [12.3] years of experience). For medical services, clinicians with multiple practice affiliations used a mean 8.2% (95% CI, 7.5%-8.9%; P < .001) more medical services per patient, drew on a mean 5.4% (95% CI, 5.1%-5.7%; P < .001) wider set of procedures within their medical care, and incurred a mean 8.6% (95% CI, 7.9%-9.2%; P < .001) more in medical costs. Pertaining to drug services, clinicians with multiple practice affiliations used a mean 2.9% (95% CI, 1.9%-3.9%; P < .001) more drug services per patient, drew on a mean 1.0% (95% CI, 0.5%-1.4%; P < .001) wider set of procedures within their medical care, and incurred a mean 2.7% (95% CI, 1.6%-3.7%; P < .001) more in drug costs. Significant results were also found across extensive and intensive margins of hospital affiliation, and supplemental analysis further indicated heterogenous treatment associations across clinician specialties. Conclusions and Relevance: This cohort study found that a clinician having multihospital affiliations was associated with greater service use, procedure breadth, and costs across both medical and drug services. These findings suggest that clinician affiliations ought to be considered as part of health care delivery design and potential cost-containment strategies.

Increased time from physiological derangement to critical care admission associates with mortality.

BACKGROUND: Rapid response systems aim to achieve a timely response to the deteriorating patient; however, the existing literature varies on whether timing of escalation directly affects patient outcomes. Prior studies have been limited to using 'decision to admit' to critical care, or arrival in the emergency department as 'time zero', rather than the onset of physiological deterioration. The aim of this study is to establish if duration of abnormal physiology prior to critical care admission ['Score to Door' (STD) time] impacts on patient outcomes. METHODS: A retrospective cross-sectional analysis of data from pooled electronic medical records from a multi-site academic hospital was performed. All unplanned adult admissions to critical care from the ward with persistent physiological derangement [defined as sustained high National Early Warning Score (NEWS) > / = 7 that did not decrease below 5] were eligible for inclusion. The primary outcome was critical care mortality. Secondary outcomes were length of critical care admission and hospital mortality. The impact of STD time was adjusted for patient factors (demographics, sickness severity, frailty, and co-morbidity) and logistic factors (timing of high NEWS, and out of hours status) utilising logistic and linear regression models. RESULTS: Six hundred and thirty-two patients were included over the 4-year study period, 16.3% died in critical care. STD time demonstrated a small but significant association with critical care mortality [adjusted odds ratio of 1.02 (95% CI 1.0-1.04, p = 0.01)]. It was also associated with hospital mortality (adjusted OR 1.02, 95% CI 1.0-1.04, p = 0.026), and critical care length of stay. Each hour from onset of physiological derangement increased critical care length of stay by 1.2%. STD time was influenced by the initial NEWS, but not by logistic factors such as out-of-hours status, or pre-existing patient factors such as co-morbidity or frailty. CONCLUSION: In a strictly defined population of high NEWS patients, the time from onset of sustained physiological derangement to critical care admission was associated with increased critical care and hospital mortality. If corroborated in further studies, this cohort definition could be utilised alongside the 'Score to Door' concept as a clinical indicator within rapid response systems.

The efficiency in the ordinary hospital bed management: A comparative analysis in four European countries before the COVID-19 outbreak.

During COVID-19 emergency the majority of health structures in Europe saturated or nearly saturated their availabilities already in the first weeks of the epidemic period especially in some regions of Italy and Spain. The aim of this study is to analyse the efficiency in the management of hospital beds before the COVID-19 outbreak at regional level in France, Germany, Italy and Spain. This analysis can indicate a reference point for future analysis on resource management in emergency periods and help hospital managers, emergency planners as well as policy makers to put in place a rapid and effective response to an emergency situation. The results of this study clearly underline that France and Germany could rely on the robust structural components of the hospital system, compared to Italy and Spain. Presumably, this might have had an impact on the efficacy in the management of the COVID-19 diffusion. In particular, the high availability of beds in the majority of the France regions paired with the low occupancy rate and high turnover interval led these regions to have a high number of available beds. Consider also that this country generally manages complex cases. A similar structural component is present in the German regions where the number of available beds is significantly higher than in the other countries. The impact of the COVID-19 was completely different in Italy and Spain that had to deal with a relevant large number of patients relying on a reduced number of both hospital beds and professionals. A further critical factor compared to France and Germany concerns the dissimilar distribution of cases across regions. Even if in these countries the hospital beds were efficiently managed, the concentration of hospitalized patients and the scarcity of beds have put pressure on the hospital systems.

Higher clinical acuity and 7-day hospital mortality in non-COVID-19 acute medical admissions: prospective observational study.

OBJECTIVES: To understand the effect of COVID-19 lockdown measures on severity of illness and mortality in non-COVID-19 acute medical admissions. DESIGN: A prospective observational study. SETTING: 3 large acute medical receiving units in NHS Lothian, Scotland. PARTICIPANTS: Non-COVID-19 acute admissions (n=1682) were examined over the first 31 days after the implementation of the COVID-19 lockdown policy in the UK on 23 March 2019. Patients admitted over a matched interval in the previous 5 years were used as a comparator cohort (n=14 954). MAIN OUTCOME MEASURES: Patient demography, biochemical markers of clinical acuity and 7-day hospital inpatient mortality. RESULTS: Non-COVID-19 acute medical admissions reduced by 44.9% across all three sites in comparison with the mean of the preceding 5 years (p<0.001). Patients arriving during this period were more likely to be male, of younger age and to arrive by emergency ambulance transport. Non-COVID-19 admissions during lockdown had a greater incidence of acute kidney injury, lactic acidaemia and an increased risk of hospital death within 7 days (4.2% vs 2.5%), which persisted after adjustment for confounders (OR 1.87, 95% CI 1.43 to 2.41, p<0.001). CONCLUSIONS: These data demonstrate a significant reduction in non-COVID-19 acute medical admissions during the early weeks of lockdown. Patients admitted during this period were of higher clinical acuity with a higher incidence of early inpatient mortality.

The Effect of Medicare Shared Savings Program on Readmissions and Variations by Race/Ethnicity and Payer Status (December 9, 2020).

OBJECTIVE: Accountable care organizations in the Medicare Shared Savings Program (MSSP) in the United States attempt to reduce cost and improve quality for their patients by improving care coordination across care settings. We examined the impact of hospital participation in the MSSP on 30-day readmissions for several groups of Medicare inpatients, and by race/ethnicity and payer status. MAIN DATA SOURCE: A 2010-2016 Medicare Provider Analysis and Review files. RESEARCH DESIGN: With propensity score matched sample of MSSP and non-MSSP-participating hospitals, patient-level linear probability models with difference-in-differences approach were used to compare the changes in readmission rates for Medicare fee-for-service patients initially admitted for ischemic stroke, hip fracture, or total joint arthroplasty in MSSP-participating hospitals with non-MSSP-participating hospitals as well as to compare the changes in disparities in readmission rates over time. PRINCIPAL FINDINGS: Hospital participation in MSSP was associated with further reduced readmission rate by 1.1 percentage points (95% confidence interval: -0.02 to 0.00, P<0.05) and 1.5 percentage points (95% confidence interval: -0.03 to 0.00, P=0.08) for ischemic stroke and hip fracture cohorts, respectively, compared with non-MSSP-participating hospitals, after the third year of hospital participation in the MSSP. There was no evidence that MSSP had an impact on racial/ethnic disparities, but increased disparity by payer status (dual vs. Medicare-only) was observed. These findings together suggest that MSSP accountable care organizations may take at least 3 years to achieve reduced readmissions and may increase disparities by payer status.

Healthcare and education networks interaction as an indicator of social services stability following natural disasters.

Healthcare and education systems have been identified by various national and international organizations as the main pillars of communities' stability. Understanding the correlation between these main social services institutions is critical to determining the tipping point of communities following natural disasters. Despite being defined as social services stability indicators, to date, no studies have been conducted to determine the level of interdependence between schools and hospitals and their collective influence on their recoveries following extreme events. In this study, we devise an agent-based model to investigate the complex interaction between healthcare and education networks and their overall recovery, while considering other physical, social, and economic factors. We employ comprehensive models to simulate the functional processes within each facility and to optimize their recovery trajectories after earthquake occurrence. The results highlight significant interdependencies between hospitals and schools, including direct and indirect relationships, suggesting the need for collective coupling of their recovery to achieve full functionality of either of the two systems following natural disasters. Recognizing this high level of interdependence, we then establish a social services stability index, which can be used by policymakers and community leaders to quantify the impact of healthcare and education services on community resilience and social services stability.

Improving Hospital Oxygen Systems for COVID-19 in Low-Resource Settings: Lessons From the Field.

Oxygen therapy is an essential medicine and core component of effective hospital systems. However, many hospitals in low- and middle-income countries lack reliable oxygen access-a deficiency highlighted and exacerbated by the coronavirus disease (COVID-19) pandemic. Oxygen access can be challenged by equipment that is low quality and poorly maintained, lack of clinical and technical training and protocols, and deficiencies in local infrastructure and policy environment. We share learnings from 2 decades of oxygen systems work with hospitals in Africa and the Asia-Pacific regions, highlighting practical actions that hospitals can take to immediately expand oxygen access. These include strategies to: (1) improve pulse oximetry and oxygen use, (2) support biomedical engineers to optimize existing oxygen supplies, and (3) expand on existing oxygen systems with robust equipment and smart design. We make all our resources freely available for use and local adaptation.

Hospital adoption of electronic health record functions to support age-friendly care: results from a national survey.

OBJECTIVE: To measure US hospitals' adoption of electronic health record (EHR) functions that support care for older adults, focusing on structured documentation of the 4Ms (What Matters, Medication, Mentation, and Mobility) and electronic health information exchange/communication with patients, caregivers, and long-term care providers. MATERIALS AND METHODS: In an online survey of a national, random sample of 797 US acute-care hospitals in 2018-2019, 479 (60.1%) responded. We calculated nationally representative measures of the percentages of hospitals with EHRs that include structured documentation of the 4Ms and exchange/communications functions. RESULTS: Structured EHR documentation of the 4Ms was fully implemented in at least 1 unit in 64.0% of hospitals and across all units in 41.5% of hospitals. Of the 4Ms, structured documentation was the highest for medications (91.3% in at least 1 unit) and the lowest for mentation (70.3% in at least 1 unit). All exchange/communication functions had been implemented in at least 1 unit in 16.2% of facilities and across all units in 7.6% of hospitals. Less than half of the hospitals had an EHR portal for long-term care facilities to access hospital information (45.4% in at least 1 unit), sent information electronically to long-term care facilities (44.6%), and had training for adults/caregivers on the patient portal (32.1%). DISCUSSION: Despite significant national investment in EHRs, hospital EHRs do not yet include key documentation, exchange, and communication functions needed to support evidence-based care for the older adults who comprise the majority of the inpatient population. Additional policy efforts are likely needed to promote the expansion of EHR capabilities into these high-value domains. CONCLUSIONS: US acute-care hospital EHRs are lacking key functions that support care for older adults.

Reconsidering hospital EHR adoption at the dawn of HITECH: implications of the reported 9% adoption of a "basic" EHR.

OBJECTIVE: In 2009, a prominent national report stated that 9% of US hospitals had adopted a "basic" electronic health record (EHR) system. This statistic was widely cited and became a memetic anchor point for EHR adoption at the dawn of HITECH. However, its calculation relies on specific treatment of the data; alternative approaches may have led to a different sense of US hospitals' EHR adoption and different subsequent public policy. MATERIALS AND METHODS: We reanalyzed the 2008 American Heart Association Information Technology supplement and complementary sources to produce a range of estimates of EHR adoption. Estimates included the mean and median number of EHR functionalities adopted, figures derived from an item response theory-based approach, and alternative estimates from the published literature. We then plotted an alternative definition of national progress toward hospital EHR adoption from 2008 to 2018. RESULTS: By 2008, 73% of hospitals had begun the transition to an EHR, and the majority of hospitals had adopted at least 6 of the 10 functionalities of a basic system. In the aggregate, national progress toward basic EHR adoption was 58% complete, and, when accounting for measurement error, we estimate that 30% of hospitals may have adopted a basic EHR. DISCUSSION: The approach used to develop the 9% figure resulted in an estimate at the extreme lower bound of what could be derived from the available data and likely did not reflect hospitals' overall progress in EHR adoption. CONCLUSION: The memetic 9% figure shaped nationwide thinking and policy making about EHR adoption; alternative representations of the data may have led to different policy.

Evaluating health promotion standards at the Farshchian heart center of Hamadan, Iran.

OBJECTIVE: Farshchian Heart Center is the fifth health-promoting hospital and the first center of its type in Western Iran that officially joined the International Network of Health Promoting Hospitals and Health Services (HPH) in 2016. The purpose of the present study is to evaluate the health promotion standards at this center in 2018. METHODS: We conducted this cross-sectional study at Farshchian Heart Center of Hamadan. The main data collection instruments included questionnaires obtained from indicators of five different main standards of health-promoting hospitals developed by the World Health Organization (WHO) which were evaluated from three different perspectives: Management staff, hospital employees, and patients. The data were analyzed by SPSS version 21 software. RESULTS: We evaluated 111 hospital employees, 109 patients, and 6 management staff. Nurses (46.8%) comprised the majority of the hospital staff respondents. Less than half (42.3%) of the hospital staff expressed awareness of hospital health promotion policies; however, only 13.5% had attended various health promotion programs. Only 51.4% of patients knew about the hospital health promotion policies and 17.4% of them participated in relevant programs. The mean score for patient satisfaction with the hospital health promotion programs according to the visual analogue scale (VAS, range: 0-10) was 7.16 ± 2.45, which was significantly higher in outpatients (8.16 ± 1.85) compared to inpatients (6.44 ± 2.59, p = 0.001). Two thirds (66.7%) of the management staff expressed awareness of implementation of these programs. CONCLUSION: The results of this study demonstrated that health promotion policies based on WHO standards were not well-recognized among patients, hospital employees, and management staff in Farshchian Heart Center of Hamadan, Iran.

Accountable care organizations are increasingly led by physician groups rather than hospital systems.

Because hospitals and health systems sponsored the majority of new accountable care organizations (ACOs) from 2010 to 2015, they influenced priorities and strategies of the policies designed to drive ACO adoption. In recent years, however, the majority of new ACOs have been sponsored by physician groups. This shift means that policies need to be developed with the characteristic strengths and weaknesses of physician-led ACOs in mind. Using data from the Leavitt Partners ACO database, we analyzed the types of providers becoming ACOs over time to look at their numbers and market potential. Because the market potential for further growth of physician group-led ACOs is much stronger than for hospital- or health system-led ACOs, policy makers need to create programs and policies that facilitate physician-led ACOs' success by helping them develop the capacity to take on risk, finance investments in high-value healthcare, and partner with other organizations to provide the full spectrum of care.

Associations between Medicaid expansion and nurse staffing ratios and hospital readmissions.

OBJECTIVE: To examine the associations between Medicaid expansion and nurse staffing ratios and hospital-wide readmission rates. DATA SOURCES: Secondary data from the 2011-2016 Healthcare Cost Report Information System, the American Hospital Association Annual Survey, and the Hospital Compare data. STUDY DESIGN: Difference-in-difference models are used to compare outcomes in hospitals located in states that expanded Medicaid with those located in nonexpansion states. The changes in nurse staffing ratios and hospital-wide readmission rates are calculated in each one of the postexpansion years (2014, 2015, and 2016), compared to pre-expansion. PRINCIPAL FINDINGS: Results indicate that nurse staffing ratios increased, whereas hospital-wide readmission rates declined in expansion states relative to nonexpansion states. Nurse staffing ratios increased by 0.33, 0.42, and 0.46 registered nurses hours per adjusted patient days in 2014, 2015, and 2016 in hospitals located in expansion states, compared with hospitals in nonexpansion states after expansion. This increase was statistically significant (P < .001) in 2015 and 2016, but marginally significant (P = .016) in 2014. Hospital-wide readmission rates statistically significantly decreased by 9, 16, and 18 per 10 000 patients (P < .001) in 2014, 2015, and 2016, respectively, in expansion vs nonexpansion states hospitals after expansion. CONCLUSIONS: Medicaid expansion was associated with gradually improved hospitals' nurse staffing ratios and hospital-wide readmission rates from 2014 through 2016. The continued monitoring of quality measures of hospitals can help assess the impact of Medicaid expansion over a longer period of time.

Hospital adoption of multiple health information exchange approaches and information accessibility.

OBJECTIVE: Hospital engagement in electronic health information exchange (HIE) has increased over recent years. We aimed to 1) determine the change in adoption of 3 types of information exchange: secure messaging, provider portals, and use of an HIE; and 2) to assess if growth in each approach corresponded to increased ability to access and integrate patient information from outside providers. METHODS: Panel analysis of all nonfederal, acute care hospitals in the United States using hospital- and year-fixed effects. The sample consisted of 1917 hospitals that responded to the American Hospital Association Information Technology Supplement every year from 2014 to 2016. RESULTS: Adoption of each approach increased by 9-15 percentage points over the study period. The average number of HIE approaches used by each hospital increased from 1.0 to 1.4. Adoption of each approach was associated with increased likelihood that providers routinely had necessary outside information of 4.2-12.7 percentage points and 4.5-13.3 percentage points increase in information integration. Secure messaging was associated with the largest increase in both. Adoption of 1 approach increased the likelihood of having outside information by 10.3 percentage points, while adopting a second approach further increased the likelihood by 9.5 percentage points. Trends in number of approaches and integration were similar. DISCUSSION/CONCLUSION: No single HIE tool provided high levels of usable, integrated health information. Instead, hospitals benefited from adopting multiple tools. Policy initiatives that reduce the complexity of enabling high value HIE could result in broader adoption of HIE and use of information to inform care.

The Distributions of Weekday Discharge Times at Acute Care Hospitals in the State of Florida were Static from 2010 to 2018.

When hospital capacity is near census, either due to limits on the number of physical or staffed beds, delays in patients' discharge can result in domino effects of congestion for the emergency department, the intensive care units, the postanesthesia care unit, and the operating room. Hospital administrators often promote increasing the percentage of patients discharged before noon as mitigation. However, benchmark data from multiple hospitals are lacking. We studied the time of weekday inpatient discharges from all 202 acute care hospitals in the state of Florida between 2010 and 2018 using publicly available data. Statewide, the average length of stay (4.63 days) did not change, but hospital discharges increased 6.1%. There was no change over years in the percentage of patients discharged before 12 noon (13.0% ± 0.28% standard error [SE]) or before 3 PM (42.2% ± 0.25% SE). For every year, the median hour of patient discharge was 3 PM. Only 9 of the 202 hospitals (4.5%) reliably achieved a morning weekday discharge rate ≥ 20.0%. Only 19 hospitals (9.4%) in the state reliably achieved a ≥ 50.0% weekday discharge rate before 3 PM. Hospital administrators seeking to achieve earlier patient discharges can use our provided data as realistic benchmarks to guide efforts. Alternatively, administrators could plan based on a model that beds will not be reliably available for new patients until late in the afternoon and apply other well-developed operational strategies to address bottlenecks affecting the internal transfer of patients within the hospital.

Integrated k-means clustering with data envelopment analysis of public hospital efficiency.

The goal of this study is to integrate k-means clustering with data envelopment analysis to examine technical efficiencies in public hospitals in Turkey. A two-step analysis procedure involving provinces and public hospitals is applied in this study. The first step examines similar provinces in terms of welfare state indicators by using k-means clustering and silhouette (Sil) cluster validity index measures. Then, the efficiencies of public hospitals in different groups of provinces are determined. The data are taken from the Turkish Statistical Institute and the 2017 Public Hospitals Statistical Year Book for eighty-one provinces and 688 public hospitals. Study results show that, relative to similarities of welfare state indicators, there are five province groups (Sil = .58). The number of technically inefficient public hospitals is greater than the number of technically efficient public hospitals in all groups. Study results emphasize that incorporated methodology of k-means clustering with data envelopment analysis is useful to identify efficiencies of public hospitals located in provinces that have similar welfare status.

Global budget versus cost ceiling: a natural experiment in hospital payment reform in the Netherlands.

Global budget (GB) arrangements have become a popular method worldwide to control the rise in healthcare expenditures. By guaranteeing hospital funding, payers hope to eliminate the drive for increased production, and incentivize providers to deliver more efficient care and lower utilization. We evaluated the introduction of GB contracts by certain large insurers in Dutch hospital care in 2012 and compared health care utilization to those insurers who continued with more traditional production-based contracts, i.e., cost ceiling (CC) contracts. We used the share of GB hospital funding per postal code region to study the effect of contract types. Our findings show that having higher share of GB financing was associated with lower growth in treatment intensity, but it was also associated with higher growth in the probability of having at least one hospital visit. While the former finding is in line with our expectation, the latter is not and suggests that hospital visits may take longer to respond to contract incentives. Our study covers the years of 2010-2013 (2 years before and 2 years following the introduction of the new contracts). Therefore, our results capture only short-term effects.

Association between adopting emergency department crowding interventions and emergency departments' core performance measures.

OBJECTIVES: To estimate the association between adopting emergency department (ED) crowding interventions and emergency departments' core performance measures. METHODS: We analyzed the National Hospital Ambulatory Medical Care Survey (NHAMCS) data from 2007 to 2015. The outcome variables are ED length of stay for discharged and admitted patients, boarding time, wait time and percentage of patients who left ED before being seen (LWBS). The independent variables are whether or not a hospital adopted each of the 20 crowding interventions. Controlling for patient-level, hospital level and temporal confounders we analyze and report results using multivariable logit model. RESULTS: Between 2007 and 2015, NHAMCS collected data for 269,721 ED visit encounters, representing a nationwide of about 1.18 billion separate ED visits. Of 20 crowding interventions we tested, using adopting bedside registration (OR = 0.89, 95% CI = 0.75-0.98, P < .05), electronic dashboard (OR = 0.86, 95% CI = 0.76-0.98, P < .05), kiosk check-in technology (OR = 0.56, 95% CI = 0.41-0.83, P < .001), physician based triage (OR = 0.86, 95% CI = 0.73-0.99, P < .05) full capacity protocol (OR = 0.91, 95% CI = 0.79-0.99, P < .05) are associated with decrease in the odds of prolonged wait time. Adopting kiosk check-in (OR = 0.55, 95% CI = 0.35-0.85, P < .05) is associated with a decrease in the odds of prolonged boarding time. Using wireless communication devices (OR = 0.77, 95% CI = 0.57-0.97, P < .05), bedside registration (OR = 0.77, 95% CI = 0.64-0.094, P < .05) and pooled nursing (OR = 0.84, 95% CI = 0.72-0.98, P < .05) are associated with decrease in the odds of a patient LWBS. CONCLUSIONS: Majority of interventions did not significantly associated with ED' core performance measures.

Predictors of online accountability practices in US hospitals: An exploratory investigation.

The purpose of this research paper is to explore variations in online accountability practices in US hospitals and determine the factors that are associated with higher levels of online accountability practices. This project employed a quantitative content analysis of 240 US hospital websites. Additionally, secondary data were obtained from the American Hospital Association and the American Hospital Directory. The results show that the external environment somewhat impacted hospitals' online accountability practices, with hospital volume (measured through the number of annual admissions) as an unquestionable predictor. Another key finding is that some of the governance forms impacted online accountability practices. Particularly, hospitals with private ownership structures tended to disclose less accountability information in an online environment, compared with their public and nonprofit counterparts. The financial situation of hospitals did not have any significant impact on overall online accountability practices but was influencing performance disclosure practices. Online accountability studies have not been conducted in a health care setting. This research theoretically relates online accountability practices to organizational characteristics (such as size, volume, financial performance, system affiliation, ownership, and rurality). Knowledge of the online accountability landscape might benefit future policy decisions on accountability models.