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1.
PLoS One ; 16(12): e0260798, 2021.
Article in English | MEDLINE | ID: covidwho-1599553

ABSTRACT

Despite remarkable academic efforts, why Enterprise Resource Planning (ERP) post-implementation success occurs still remains elusive. A reason for this shortage may be the insufficient addressing of an ERP-specific interior boundary condition, i.e., the multi-stakeholder perspective, in explaining this phenomenon. This issue may entail a gap between how ERP success is supposed to occur and how ERP success may actually occur, leading to theoretical inconsistency when investigating its causal roots. Through a case-based, inductive approach, this manuscript presents an ERP success causal network that embeds the overlooked boundary condition and offers a theoretical explanation of why the most relevant observed causal relationships may occur. The results provide a deeper understanding of the ERP success causal mechanisms and informative managerial suggestions to steer ERP initiatives towards long-haul success.


Subject(s)
Delivery of Health Care, Integrated/organization & administration , Efficiency, Organizational/standards , Financial Management, Hospital/methods , Health Care Rationing/standards , Health Resources/organization & administration , Hospital Information Systems/standards , Resource Allocation/methods , Humans , Planning Techniques , Software
2.
Vaccine ; 39(47): 6876-6882, 2021 11 16.
Article in English | MEDLINE | ID: covidwho-1525977

ABSTRACT

OBJECTIVE: Vaccine shortage and supply-chain challenges have caused limited access by many resource-limited countries during the COVID-19 pandemic. One of the primary decisions for a vaccine-ordering decision-maker is how to allocate the limited resources between different types of vaccines effectively. We studied the tradeoff between efficacy and reach of the two vaccine types that become available at different times. METHODS: We extended a Susceptible-Infected-Recovered-Deceased (SIR-D) model with vaccination, ran extensive simulations with different settings, and compared the level of infection attack rate (IAR) under different reach ratios between two vaccine types under different resource allocation decisions. RESULTS: We found that when there were limited resources, allocating resources to a vaccine with high efficacy that became available earlier than a vaccine with lower efficacy did not always lead to a lower IAR, particularly if the former could vaccinate less than 42.5% of the population (with the selected study parameters) who could have received the latter. Sensitivity analyses showed that this result stayed robust under different study parameters. CONCLUSIONS: Our results showed that a vaccine with lower resource requirements (wider reach) can significantly contribute to reducing IAR, even if it becomes available later in the pandemic, compared to a higher efficacy vaccine that becomes available earlier but requires more resources. Limited resource in vaccine distribution is significant challenge in many parts of the world that needs to be addressed to improve the global access to life-saving vaccines. Understanding the tradeoffs between efficacy and reach is critical for resource allocation decisions between different vaccine types for improving health outcomes.


Subject(s)
COVID-19 , Vaccines , COVID-19 Vaccines , Humans , Pandemics , Resource Allocation , SARS-CoV-2 , Vaccination
5.
Crit Care Med ; 49(10): 1739-1748, 2021 10 01.
Article in English | MEDLINE | ID: covidwho-1475872

ABSTRACT

OBJECTIVES: The coronavirus disease 2019 pandemic has overwhelmed healthcare resources even in wealthy nations, necessitating rationing of limited resources without previously established crisis standards of care protocols. In Massachusetts, triage guidelines were designed based on acute illness and chronic life-limiting conditions. In this study, we sought to retrospectively validate this protocol to cohorts of critically ill patients from our hospital. DESIGN: We applied our hospital-adopted guidelines, which defined severe and major chronic conditions as those associated with a greater than 50% likelihood of 1- and 5-year mortality, respectively, to a critically ill patient population. We investigated mortality for the same intervals. SETTING: An urban safety-net hospital ICU. PATIENTS: All adults hospitalized during April of 2015 and April 2019 identified through a clinical database search. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of 365 admitted patients, 15.89% had one or more defined chronic life-limiting conditions. These patients had higher 1-year (46.55% vs 13.68%; p < 0.01) and 5-year (50.00% vs 17.22%; p < 0.01) mortality rates than those without underlying conditions. Irrespective of classification of disease severity, patients with metastatic cancer, congestive heart failure, end-stage renal disease, and neurodegenerative disease had greater than 50% 1-year mortality, whereas patients with chronic lung disease and cirrhosis had less than 50% 1-year mortality. Observed 1- and 5-year mortality for cirrhosis, heart failure, and metastatic cancer were more variable when subdivided into severe and major categories. CONCLUSIONS: Patients with major and severe chronic medical conditions overall had 46.55% and 50.00% mortality at 1 and 5 years, respectively. However, mortality varied between conditions. Our findings appear to support a crisis standards protocol which focuses on acute illness severity and only considers underlying conditions carrying a greater than 50% predicted likelihood of 1-year mortality. Modifications to the chronic lung disease, congestive heart failure, and cirrhosis criteria should be refined if they are to be included in future models.


Subject(s)
COVID-19/therapy , Crisis Intervention/standards , Resource Allocation/methods , Academic Medical Centers/organization & administration , Academic Medical Centers/statistics & numerical data , Adult , COVID-19/epidemiology , Crisis Intervention/methods , Crisis Intervention/statistics & numerical data , Female , Hospitalization/statistics & numerical data , Humans , Male , Massachusetts , Middle Aged , Resource Allocation/statistics & numerical data , Retrospective Studies , Safety-net Providers/organization & administration , Safety-net Providers/statistics & numerical data , Standard of Care/standards , Standard of Care/statistics & numerical data , Urban Population/statistics & numerical data
6.
Anaesthesist ; 70(7): 582-597, 2021 07.
Article in German | MEDLINE | ID: covidwho-1453677

ABSTRACT

BACKGROUND AND OBJECTIVE: During the initial phase of the COVID-19 pandemic the government of the state of Bavaria, Germany, declared a state of emergency for its entire territory for the first time in history. Some areas in eastern Bavaria were among the most severely affected communities in Germany, prompting authorities and hospitals to build up capacities for a surge of COVID-19 patients. In some areas, intensive care unit (ICU) capacities were heavily engaged, which occasionally made a redistribution of patients necessary. MATERIAL AND METHODS: For managing COVID-19-related hospital capacities and patient allocation, crisis management squads in Bavaria were expanded by disaster task force medical officers ("Ärztlicher Leiter Führungsgruppe Katastrophenschutz" [MO]) with substantial executive authority. The authors report their experiences as MO concerning the superordinate patient allocation management in the district of Upper Palatinate (Oberpfalz) in eastern Bavaria. RESULTS: By abandoning routine patient care and building up additional ICU resources, surge capacity for the treatment of COVID-19 patients was generated in hospitals. In parts of the Oberpfalz, ICU capacities were almost entirely occupied by patients with corona virus infections, making reallocation to other hospitals within the district and beyond necessary. The MO managed patient pathways in an escalating manner by defining local (within the region of responsibility of a single MO), regional (within the district), and cross-regional (over district borders) reallocation lanes, as needed. When regional or cross-regional reallocation lanes had to be established, an additional management level located at the district government was involved. Within the determined reallocation lanes, emitting and receiving hospitals mutually agreed on any patient transfer without explicitly involving the MO, thereby maintaining the established interhospital routine transfer procedures. The number of patients and available treatment resources at each hospital were monitored with the help of a web-based treatment capacity registry. If indicated, reallocation lanes were dynamically revised according to the present situation. To oppose further virus spreading in nursing homes, the state government prohibited patient allocation to these facilities, which led to considerably longer hospital length of stay of convalescent elderly and/or dependent patients. In parallel to the flattening of the COVID-19 incidence curve, routine hospital patient care could be re-established in a stepwise manner. CONCLUSION: Patient allocation during the state of emergency by the MO sought to keep up routine interhospital reallocation procedures as much as possible, thereby reducing management time and effort. Occasionally, difficulties were observed during patient allocations crossing district borders, if other MO followed different management principles. The nursing home blockade and conflicting financial interests of hospitals posed challenges to the work of the disaster task force medical officers.


Subject(s)
COVID-19 , Decision Making, Organizational , Pandemics , Surge Capacity/organization & administration , Critical Care , Disease Management , Emergency Service, Hospital , Germany , Humans , Intensive Care Units , Length of Stay , Nursing Homes , Patient Transfer , Research Report , Resource Allocation
8.
Healthc Manage Forum ; 34(6): 353-356, 2021 Nov.
Article in English | MEDLINE | ID: covidwho-1440872

ABSTRACT

Resource allocation under non-emergency conditions is often challenging. Within the context of a Public Health Emergency (PHE), allocation decisions become significantly more difficult as decisions are often necessary on very short timelines, where relevant information (either evidence or information "on the ground") is changing or incomplete, there is significant potential for harm, and resources are scarce, in unpredictable supply, and likely in high demand. An intentional value-based decision-making approach in such circumstances can clarify the values that ought to guide decisions, offering transparency and consistency, among other benefits. We use the example of vaccine allocation during the COVID-19 pandemic to explore value-based decision-making within a PHE context. We describe several core values that are relevant to PHE decision-making and outline their implications for approaches to vaccine allocation. While we focus on vaccine allocation, the values discussed are relevant to other system-level decisions in both emergency and non-emergency situations. Tips for leaders wishing to adopt a value-based approach to decision-making are offered.


Subject(s)
COVID-19 , Public Health , Humans , Pandemics , Resource Allocation , SARS-CoV-2
9.
Proc Natl Acad Sci U S A ; 118(40)2021 10 05.
Article in English | MEDLINE | ID: covidwho-1440509

ABSTRACT

Global cooperation rests on popular endorsement of cosmopolitan values-putting all humanity equal to or ahead of conationals. Despite being comparative judgments that may trade off, even sacrifice, the in-group's interests for the rest of the world, moral cosmopolitanism finds support in large, nationally representative surveys from Spain, the United Kingdom, Germany, China, Japan, the United States, Colombia, and Guatemala. A series of studies probe this trading off of the in-group's interests against the world's interests. Respondents everywhere distinguish preventing harm to foreign citizens, which almost all support, from redistributing resources, which only about half support. These two dimensions of moral cosmopolitanism, equitable security (preventing harm) and equitable benefits (redistributing resources), predict attitudes toward contested international policies, actual charitable donations, and preferences for mask and vaccine allocations in the COVID-19 response. The dimensions do not reflect several demographic variables and only weakly reflect political ideology. Moral cosmopolitanism also differs from related psychological constructs such as group identity. Finally, to understand the underlying thought structures, natural language processing reveals cognitive associations underlying moral cosmopolitanism (e.g., world, both) versus the alternative, parochial moral mindset (e.g., USA, first). Making these global or local terms accessible introduces an effective intervention that at least temporarily leads more people to behave like moral cosmopolitans.


Subject(s)
Internationality , Morals , Humans , Judgment , Linguistics , Psychological Theory , Public Policy , Resource Allocation , Safety , Surveys and Questionnaires
14.
15.
J Am Med Dir Assoc ; 22(9): 1831-1839.e1, 2021 09.
Article in English | MEDLINE | ID: covidwho-1376015

ABSTRACT

A coordinated emergency management response to disaster management in nursing homes is desperately needed globally. During the most recent COVID-19 pandemic, aside from a few exemplary countries, most countries have struggled to protect their nursing home populations. Timely and appropriate allocation of resources to nursing homes during disaster response is a challenging yet crucial task to prevent morbidity and mortality of residents. The responsibility for the management of nursing homes during the pandemic was multifaceted, and responsibilities lay at the national, jurisdictional, and regional levels. Success in managing COVID-19 in nursing homes required all these levels to be aligned and supportive, ideally through management by an emergency response leadership team. However, globally there is a paucity of effective management strategies. This article uses the example of the COVID-19 pandemic to propose a risk stratification system to ensure timely and appropriate allocation of resources to nursing homes during disaster preparation and management. Nursing homes should be risk-stratified according to 4 domains: risk of intrusion, capability for outbreak containment, failure in organizational capability, and failure in the availability of community and health care supports. Risk stratification should also consider factors such as current levels of community transmission, if applicable, and geographic location of nursing homes and services. Early identification of nursing homes at risk for infectious disease, or disasters, and targeted allocation of resources might help reduce the number of outbreaks, lower the mortality, and preserve community supports such as acute hospital services. The next step is to debate this concept to validate the selected variables and then develop and pilot test a risk stratification tool for use.


Subject(s)
COVID-19 , Disasters , Humans , Nursing Homes , Pandemics , Resource Allocation , Risk Assessment , SARS-CoV-2
16.
Br J Hosp Med (Lond) ; 82(8): 1-6, 2021 Aug 02.
Article in English | MEDLINE | ID: covidwho-1372162

ABSTRACT

BACKGROUND/AIMS: The trauma and orthopaedic surgery department needed to modify practices as a result of the COVID-19 pandemic. This study quantitatively assessed the effects of changes in resource allocation on the efficiency of trauma, specifically the number of operations performed per defined trauma session. METHODS: Trauma lists were reviewed pre-COVID, at the peak and at the tail of the first wave of COVID-19 infections at a hospital in the UK. Efficiency was calculated before and after the reallocation of resources and this was defined as the number of cases per trauma session as well as turnaround times for each part of the surgical patient journey. RESULTS: The mean trauma list efficiency was 1.73 cases per session in February 2020 compared to 1.89 in February 2019. It reduced to 1.21 during the COVID peak in April 2020 compared to 1.90 in April 2019 and improved to 1.48 per session in June 2020 vs 1.82 in June 2019. CONCLUSIONS: Measures introduced at the start of the pandemic are likely to continue for the foreseeable future. Increased allocation of resources would be needed to allow urgent trauma surgery to provide a timely and efficient service.


Subject(s)
COVID-19 , Orthopedic Procedures , Orthopedics , Humans , Pandemics , Resource Allocation , SARS-CoV-2
18.
Med Health Care Philos ; 24(4): 487-492, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1358114

ABSTRACT

The Covid-19 pandemic has led to a health crisis of a scale unprecedented in post-war Europe. In response, a large amount of healthcare resources have been redirected to Covid-19 preventive measures, for instance population-wide vaccination campaigns, large-scale SARS-CoV-2 testing, and the large-scale distribution of protective equipment (e.g., N95 respirators) to high-risk groups and hospitals and nursing homes. Despite the importance of these measures in epidemiological and economic terms, health economists and medical ethicists have been relatively silent about the ethical rationales underlying the large-scale allocation of healthcare resources to these measures. The present paper seeks to encourage this debate by demonstrating how the resource allocation to Covid-19 preventive measures can be understood through the paradigm of the Rule of Rescue, without claiming that the Rule of Rescue is the sole rationale of resource allocation in the Covid-19 pandemic.


Subject(s)
COVID-19 , Pandemics , COVID-19 Testing , Humans , Resource Allocation , SARS-CoV-2
19.
J Prev Med Hyg ; 62(2): E261-E269, 2021 Jun.
Article in English | MEDLINE | ID: covidwho-1355278

ABSTRACT

Background: The COVID-19-related deaths are growing rapidly around the world, especially in Europe and the United States. Purpose: In this study we attempt to measure the association of these variables with case fatality rate (CFR) and recovery rate (RR) using up-to-date data from around the world. Methods: Data were collected from eight global databases. According to the raw data of countries, the CFR and RR and their relationship with different predictors was compared for countries with 1,000 or more cases of COVID-19 confirmed cases. Results: There were no significant correlation between the CFR and number of hospital beds per 1,000 people, proportion of population aged 65 and older ages, and the number of computed tomography per one million inhabitants. Furthermore, based on the continents-based subgroup univariate regression analysis, the population (R2 = 0.37, P = 0.047), GPD (R2 = 0.80, P < 0.001), number of ICU Beds per 100,000 people (R2 = 0.93, P = 0.04), and number of CT per one million inhabitants (R2 = 0.78, P = 0.04) were significantly correlated with CFR in America. Moreover, the income-based subgroups analysis showed that the gross domestic product (R2 = 0.30, P = 0.001), number of ICU Beds per 100,000 people (R2 = 0.23, P = 0.008), and the number of ventilator (R2 = 0.46, P = 0.01) had significant correlation with CFR in high-income countries. Conclusions: The level of country's preparedness, testing capacity, and health care system capacities also are among the important predictors of both COVID-19 associated mortality and recovery. Thus, providing up-to-date information on the main predictors of COVID-19 associated mortality and recovery will hopefully improve various countries hospital resource allocation, testing capacities, and level of preparedness.


Subject(s)
COVID-19 Testing/statistics & numerical data , COVID-19/epidemiology , COVID-19/mortality , Delivery of Health Care/standards , Hospital Bed Capacity , Pandemics , Resource Allocation , Age Distribution , Aged , Aged, 80 and over , COVID-19/complications , Comorbidity , Europe/epidemiology , Humans , SARS-CoV-2
20.
Value Health ; 24(11): 1570-1577, 2021 11.
Article in English | MEDLINE | ID: covidwho-1340749

ABSTRACT

OBJECTIVES: To assist with planning hospital resources, including critical care (CC) beds, for managing patients with COVID-19. METHODS: An individual simulation was implemented in Microsoft Excel using a discretely integrated condition event simulation. Expected daily cases presented to the emergency department were modeled in terms of transitions to and from ward and CC and to discharge or death. The duration of stay in each location was selected from trajectory-specific distributions. Daily ward and CC bed occupancy and the number of discharges according to care needs were forecast for the period of interest. Face validity was ascertained by local experts and, for the case study, by comparing forecasts with actual data. RESULTS: To illustrate the use of the model, a case study was developed for Guy's and St Thomas' Trust. They provided inputs for January 2020 to early April 2020, and local observed case numbers were fit to provide estimates of emergency department arrivals. A peak demand of 467 ward and 135 CC beds was forecast, with diminishing numbers through July. The model tended to predict higher occupancy in Level 1 than what was eventually observed, but the timing of peaks was quite close, especially for CC, where the model predicted at least 120 beds would be occupied from April 9, 2020, to April 17, 2020, compared with April 7, 2020, to April 19, 2020, in reality. The care needs on discharge varied greatly from day to day. CONCLUSIONS: The DICE simulation of hospital trajectories of patients with COVID-19 provides forecasts of resources needed with only a few local inputs. This should help planners understand their expected resource needs.


Subject(s)
COVID-19/economics , Computer Simulation/standards , Resource Allocation/methods , Surge Capacity/economics , COVID-19/prevention & control , COVID-19/therapy , Humans , Resource Allocation/standards , Surge Capacity/trends
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