Management, Organization and Performance Measurement in

International Journal of Management and Administrative Sciences (IJMAS)
(ISSN: 2225-7225)
Vol. 2, No. 1, April, 2013(24-43)
www.ijmas.org
Management, Organization and Performance Measurement in Italian
Healthcare System: The Experience of Sicily Region
Marco Ferretti & Antonello Zangrandi
Department of Economics
University of Parma
J.F. Kennedy St., no.6 – cap 43125 Parma – ITALY
[email protected]
[email protected]
Corresponding author: Marco Ferretti
Phone: +390521032334
Fax: +390521032353
Abstract
Regions as well as public administrations in the Italian health system have the responsibility to
develop policies in the health care. Within an improvement policy of service quality, Sicily
region aimed at promoting an improvement of the emergency wards, with a twofold purpose:
first, to make them more reactive to the demand, and second, to make them able to propose
services characterized by higher level of quality.
In order to develop such a policy, different analysis and design methods have been applied.
Specifically, three main analysis have been developed:
1.
2.
3.
An investigation of the “flows”, and the identification of the “path” of the patient that access the
first aid;
A detailed analysis of the organization of the first aids, according to the international
standards proposed by the Joint Commission International;
An analysis of the production costs.
These analysis have allowed the identification of the main differences among the 20 Sicilian
first aids, thus allowing the final identification of corrective actions to be realized in order to
improve the quality of their services.
Keywords: Emergency Departments, Emergency Rooms, Italian Healthcare System, Efficiency
and effectiveness in Healthcare; Costs analysis
1. Introduction
Emergency Departments (EDs) are a vital component of national healthcare network, open 24 hours a day, 7
days a week, for everybody in need of medical care.
As time goes by, there has been a steady increase in the amount and complexity of cases accessing and being
treated in EDs (Knapp J.F. et al, 2004). First data provided by information system “EMUR” (“EmergenzaUrgenza”) give account, for the year 2011, of 13 million accesses in Emergency Rooms (ERs) in Italy. In the year
2009, there were 550 Emergency Room services of which 343 were EDs: 325 public-financed EDs and 18 private
EDs with public financial contribution. Emergency Room (ER), as first access to the hospital, is the most
important interface between national healthcare system and the citizen’s care needs. In Italy, in the same year,
there were 22.741.500 accesses to ER, 379 every 1000 inhabitants, of which 15,5% gave way to an hospital
admission. The prevalence of white codes and the crowding in ER, as we will explain later, is a problem
worldwide (Kellermann, 2006). In some cases, we notice a paradoxical situation: the citizen prefers to wait for
hours in an ER rather than make use of other local healthcare facilities.
24
Copyright ©Pakistan Society of Business and Management Research
International Journal of Management and Administrative Sciences (IJMAS)
(ISSN: 2225-7225)
Vol. 2, No. 1, April, 2013(24-43)
www.ijmas.org
Emergency Room, of course, is one of the most challenging hospital services, because is the main access point to
departments and because there is great diversity in the pathologies and needs of people accessing. ER
organization must face two problems: 1. There is no possibility to program and pre-organize activities (ERs are
active 24 hours a day, patients access without booking, it is impossible to figure out neither quantity, nor
diagnosis, nor time schedule of patients); 2. diversity of human and technical resources, whose minimal level is
fixed by State and Regional law.
By way of consequence, we can say that emergency care is a twofold activity: waiting time and care time must
both be organized, as both are important and determine the patient’s final evaluation of the service. Italian
healthcare organizations are in continuous search of ideas to improve ER services. In a global effort to improve
public care services, Sicily Region has devoted special attention to ERs, to accomplish the demand of patients and
offer better quality services.
This work aims to map the characteristics of the 20 more important ERs in Sicily; identify and describe specific
actions to improve the patients care path and ensure quick intervention; propose actions to improve workers’
performances; foster a revision of economic measurement parameters. We will also try to explain the reasons for
the marked diversity in performance of different ERs in the region and the conditions for a general organization
improvement.
2. Literature Review
The mission of ER is “to guarantee timely diagnosis and interventions, adequate for the patients accessing in a
non-programmable way for emergency care needs” (Italian Society of Emergency Medicine, SIMEU). More
precisely, we can define it “to guarantee to every citizen in need of care appropriate diagnostic-therapy advice
and, in emergency cases, recovery and restoring of vital functions”. The majority of ERs today can provide, in
addition to the core mission, highly professional therapies and care services, at no cost and without booking
(direct access); but there is still room for improvements. The ERs, and Emergency Departments more in general,
are a critical node in healthcare system; the large international bibliography on the subject is a symptom of this
crucial role. These studies focus on ERs and EDs analyzing problems and flaws and proposing solutions. Most
studies are in the clinical field, but some scholars have studied EDs performances in terms of outcome, analyzing
variables measuring organization, effectiveness, quality, efficiency and costs (Kellermann, 2005; McClellan et al,
2013).
One of the most discussed problems is crowding in EDs and its impact on “mortality”, “time to treatment”,
“patient satisfaction”, “quality of care” (Dickinson, 1989; Gallagher, 1990; Bernstein, 2006; Bernstein, 2008).
Some researches have made possible a revision of reasons, consequences and possible solutions for EDs
crowding. Clearly the utmost cause of ED crowding is the presence of many non-emergency patients, who didn’t
follow the correct praxis or didn’t found assistance elsewhere, especially during seasonal epidemics (e.g. flu),
inadequate human resources and scarcity of beds for admissions (Baer, 2001; Hwang, 2004; Nathan, 2008).
Many authors have endeavored to provide organizational, statistical and mathematical models to understand
causes of crowding and find solutions to manage it. These models aim to help researchers, administrators and
politicians to understand causes and develop possible solutions of crowding in EDs. One of these conceptual
models shows 3 separate components for crowding: input, throughput e output. These components exist within
an acute care system that is characterized by the delivery of unscheduled care. The goal of the conceptual model
is to provide a practical framework on which an organized research, policy, and operations management agenda
can be based to alleviate ED crowding (Richardson, 2002; Asplin, 2003; Murray, 2003).
Other authors have created mathematical models for programming the daily schedule of ED doctors, to optimize
work shifts and improve the operative effectiveness (Beaulieu, 1998; Beaulieu, 2000; Yeh and Lin, 2007).
Organizative models based on nursing workers have also been studied, to improve their autonomy in all phases,
including, of course, triage in EDs (Derlet, 1992; Birnbaum, 1994; Lowe, 1994; Kennedy 1996; Williams, 1996b;
Young, 1997; Khurma, 2008, Scardigli and Zangrandi, 2009).
In order to focus on problems and improve performances in public organizations (including of course public
healthcare organizations) performance measurement systems (PMS) have been implemented in the last years.
PMS in the field of public administrations have received a growing attention by both academics and practitioners
in the last two decades. This fact is demonstrated by the proliferation of papers in the management literature on
this matter. Research on PMS in the public context covers different issues: types of PMS available (Newcomer,
1997a; Newcome, 1997b; Wholey, 1999), their main barriers of implementation (Ammons, 1992; De Lancer
Julnes, 2009; Kravchuk and Schack, 1996; Mann, 1986), the results derived from their utilization in public
25
Copyright ©Pakistan Society of Business and Management Research
International Journal of Management and Administrative Sciences (IJMAS)
(ISSN: 2225-7225)
Vol. 2, No. 1, April, 2013(24-43)
www.ijmas.org
administrations (Marshall, 1996; Newcomer and Wright, 1997). Different Authors agree in stating that PMSs
represent the principal element driving the management process and that the information produced by PMSs
can be used for diverse purposes. As De Lancer Julnes (2009) has recently stressed “the measurement of
performance is comparable to the production of knowledge, therefore the use of performance measures can be
assimilated to a problem of the use of knowledge”. Other Authors have proven that PMSs contribute to the
organizational learning process (Torres and Preskill, 2001; Halachmi, 2002). Furthermore PMSs can be used to
promote and communicate organizational contribution in respect to the objectives and aspirations of the
stakeholders. Nevertheless, as Behn (2003) has underlined, in the public sector managers rarely use information
with regard to accountability activities. The literature on the matter of performance measurement still offers few
approaches specific for the public sector. Gooijer (2000), for example, proposed a knowledge management
performance framework and provides some interesting parallels. For a public organization, the role of
stakeholders is seen as an important issue, thus representing an important issue also in the performance
measurement tools. (Kennerley and Neely, 2002): as Wisniewski and Stewart (2004) stressed, in fact, “the enduser of the performance measurement information generated is of critical importance”. More recently, Sole and
Schiuma (2010) stressed in their paper the main challenges of public administrations in using performance
measures in general.
As a consequence of PMS reforms, academics and international organizations such as the World Health
Organization (WHO) and the Organization for Economic Cooperation and Development (OECD) developed
conceptual frameworks and models in order to help countries in building effective tools (Arah et al., 2006; Kelley
et al., 2006; Murray & Evans, 2003; Smith, 2002; Veillard et al., 2005).
In specific, in the Italian health sector, the development of PMS can be traced back to the 90s reforms that
introduced managerial tools and devolved the organization and assessment of healthcare services to Regions.
This devolution, enforced by the recent federalist reform of 2009, has led Regions to shape their own
organizational structures and relationships among health system actors (Censis, 2008; Formez, 2007). As a
consequence of these reforms, Italy has now 21 Regional Health Systems with significant differences from each
other. Scholars suggest benchmarking (Shari et al, 2006) as another driver of change. Although most Regions
acknowledge that benchmarking processes may help spreading innovation and improvements there are still few
Regions that adopt benchmarking within regional boundaries, sometimes because they are small Regions,
sometimes because they don’t want to enable negative competition (Welch et al, 2011; Vainieri and Nuti, 2011).
PMS is directly connected with Indicators of Quality Improvement and Patient Safety. The Annual Report of The
Joint Commission (TJC) for Quality and Safety (2009) transcribes the results of the analysis of assistance
performances’ quality in more than 3,000 USA hospital TJC-certified. Indicators have been selected in team with
practitioners and workers, and their parameter are the most tested and updated Evidence Based (EB) treatment.
The performance has been measured as a percentage of EB treatments on the total; so there is scientific evidence
that the percentage of EB treatments provided and quality, effectiveness of the treatment, and patient safety are
in direct correlation. The analysis shows clearly that hospitals TCJ-certified have a clear trend towards
performance improvement, outcome efficiency and patient safety. Moreover, the quality improvement implies,
as the President of TJC says, a reduction of extra costs due to casualties, and in the middle run, budget economies
for hospitals and healthcare administration (The Joint Commission, 2009 and 2010).
Also connected to PMS is cost analysis. It must emphasized first that the nature of healthcare system (Public,
Private, based on Public-Private agreements) has a strong impact on cost analysis. Many different researches
have been provided at international level. Some scholars have measured the average cost of a ED examination
(Williams, 1996a; Kellerman, 2005); others have calculated a Cost per patient per hour (including educational
costs) (Carey et al, 2013). Brooke et al. (2007) provided a framework that could be used to standardize the
calculation of Emergency Medical Services (EMS) system costs in a community. Researchers, policymakers, and
EMS providers can use this framework. Standardizing the calculation of EMS cost will allow comparisons of costs
between studies, communities, and interventions.
Other scholars have studied the correlation between ED costs and quantity and quality of interventions. Bamezai
et al (2005) suggest that the marginal cost of an outpatient ED visit is higher than is generally believed. Hospitals
thus need to carefully review how EDs fit within their overall operations and cost structure and may need to pay
special attention to policies and procedures that guide the delivery of nonurgent care through the ED.
26
Copyright ©Pakistan Society of Business and Management Research
International Journal of Management and Administrative Sciences (IJMAS)
(ISSN: 2225-7225)
Vol. 2, No. 1, April, 2013(24-43)
www.ijmas.org
3. Research Methodology
ERs evaluation has been developed on different plans:
1. Assistance routines applied, their formalization, the diffusion of good practices, and more in general a protocol
of behavior standards that aim to evaluate the application of assistance routines;
2. The role chart and procedures, human resources managing and its characteristics and education; this
parameter aims to understand resources’ orientation and level of managing formalization;
3. Quantity and quality of activities and interventions, considering both the complexity of cases examined and the
time needed for the treatment. ERs input and output must be observed, with an eye on the hospital where the ER
resides, not only considering dimensions but also diversity and quality in care offer (services available in the
hospital, consulting possibilities, technology in medical equipment, etc..)
4. Production costs and more in general use and allocation of the resources, to evaluate efficiency in procedures.
On each plan, adequate methodologies have been developed as described:
1. Care standards are those provided by Joint Commission International1. A workgroup of international and
national experts2 has selected, in the frame of International Standards for Hospital certification, the ones
especially relevant with EDs (standards have been validated through a confrontation with Italian Society of
Emergency Medicine (SIMEU). In Table 1, there are the results of the selection.
Table 1: Categories of standards and Item evaluated for EDs
Categories of standards
Items evaluated
1. IInternational Patient Safety Goals (IPSG)
24
2. Access to Care and Continuity of Care (ACC)
39
3. Patient and Family Rights (PFR)
36
4. Assessment of Patients (AOP)
26
5. Care of Patients (COP)
30
6. Anesthesia and Surgical Care (ASC)
9
7. Medication Management and Use (MMU)
26
8. Patient and Family Education (PFE)
1
9. Quality Improvement and Patient Safety (QPS)
2
10. Prevention and Control of Infections (PCI)
1
11. Governance, Leadership, and Direction (GLD)
39
12. Facility Management and Safety (FMS)
39
13. Staff Qualifications and Education (SQE)
5
14. Management of Communication and Information (MCI)
12
The manual “Accreditation Standards for Hospital” (Joint Commission International, 2011) offers an explanation
of statements and scopes, for every category, that JCI evaluates. For a detailed analysis of criteria please refer to
research report3.
The 289 items have been evaluated by JCI surveyors in the biggest 20 EDs. As detailed in the research report,
these 20 EDs respond to the 48% of access demand in all Sicily Region. Evaluation ranges from 0 (no
compliance) to 1 (compliance). Standards refer to assistance-care behaviors and organizative conditions
1
Created in 1994 by The Joint Commission, JCI has a presence in more than 90 countries today. JCI works with health care
organizations, governments, and international advocates to promote rigorous standards of care and provide solutions for achie ving peak
performance. Our experts help organizations help themselves in three ways: accreditation, education, and advisory services.
2
For JCI: Derrick Pasternac, Carlo Ramponi, Filippo Azzali; per Regione Sicilia: Giuseppe Murolo.
3
Research full report is available in Direzione Sanità of Sicily Region “Assessorato alla Sanità”.
27
Copyright ©Pakistan Society of Business and Management Research
International Journal of Management and Administrative Sciences (IJMAS)
(ISSN: 2225-7225)
Vol. 2, No. 1, April, 2013(24-43)
www.ijmas.org
imperative for the fulfillment of the service. According to JCI standards, an internationally certified hospital
should have a near 1 evaluation, to sustain the outcome improvement (Chassin, 2010).
Scoring focuses on strengths and weaknesses of each ED, to make easier implementation of improvement plans.
Standards prescribe some expected behaviors (described by JCI) inspired to good practices in assistance-care
and organization. They can be content-categorized:
- expected behaviors from members of the ED;
- production of data reports and formalized informations;
- presence of standard routines regularly updated.
This content-based categorization allows to trace a clear picture of strengths and weaknesses, and also to
provide real indications on the organization model adopted in every hospital.
First of all, 289 items offer a general picture of routines and organization management; but more in detail, some
items can act as a flag of some organizational and managing critical nodes.
As far as Sicily Region is concerned, in its programming, funding and control role in Italian State healthcare
system, some goals are a priority in the context of EDs:
- triage, the process of determining the priority of patients' treatments on the base of their condition. The use of
triage in ERs is relatively recent and the evaluation of the ERs adaptation to it is an extremely relevant indicator;
- informed consent is another relevant item, not only as compliance to Italian law on the matter, but also in the
frame of a policy that can increase the awareness of patients;
- examination and reexamination of patients, and documentation of their medical history in suitable medical
records;
- presence of fixed routines and protocols reinforcing a solid clinical orientation in an evidence-based medicine
logic, that can guarantee some uniformity in the treatment of similar cases; here two analysis are provided, one
on clinics and the other focused on patients with special needs (older patients, psychiatric or securitychallenging patients, etc.)
- drug administration in EDs is a very complex activity, because of the diversity of cases and the need for a quick
and prompt care, making essential the efficiency of drug provision and safety in drug administration;
- presence of a result evaluation system to draw attention to goals and focus on their realization. On this subject,
directors look at quality and efficiency indicators to evaluate:
- priorities in measurement and in improvement of care management, in the frame of single EDs or
service;
- evaluation of treatments provided, based on patient-satisfaction surveys and complaint analysis;
- the importance of a correct perspective on economic efficiency and effectiveness of treatments.
- As far as clinical competences are concerned, the attention is focused on the attribution of “privileges” (as
acknowledgment of singular competences of a practitioner in ED), in order to make everybody aware of the role
of a professional and give key figures the necessary autonomy and leadership. This “privileges” must be the
result of a long and complex evaluation process: individuation of expected competences, long-time evaluation of
clinical performances, improvement and professional updating in every position. This standard allows to
understand the clinical management of the hospital and its role of guidance in the organization.
2. The role chart and procedures, human resources managing and its characteristics and education, is a
parameter aimed to understand resources’ orientation and level of managing formalization. This section of the
research, through structured interviews, analysis of documents and data and further meetings with the
operators, has given these results:
- Tracing of the organizational and human resources chart of EDs. This has made possible to analyze
activity coordination, centralized or decentralized style and connection with the other departments of
the hospital;
- Analysis of activities, in terms of ER accesses and related activities, to evaluate the actual output of the
ED; the activity level makes possible to understand how the emergency care needs direct themselves to
the hospital. Evaluation keeps account of many items: access numbers, triage results, treatment of
accesses (admissions, short-stay observation, discharge, etc.);
28
Copyright ©Pakistan Society of Business and Management Research
International Journal of Management and Administrative Sciences (IJMAS)
(ISSN: 2225-7225)
Vol. 2, No. 1, April, 2013(24-43)
www.ijmas.org
- Analysis of personnel assigned to ER, studying both the human resources plan and the work shifts on a
week, month and year basis. So it is possible to evaluate efficiency level and adequacy of human
resources;
- Performance evaluation on waiting time, a critical parameter in EDs, both on triage and on the
beginning of medical diagnosis;
- Analysis of connection between the ED and other services in the hospital, to evaluate integration,
effectiveness of services and ability to respond to casualties.
The analysis makes possible to evaluate the management and organizational models and make significant
confrontations between the performance and treatments of different centers. Confrontation between various
centers of the same Region is particularly useful.
3. Quantity and quality of activities and interventions, considering both the complexity of cases examined and
the time needed for the treatment, to observe ERs input and output. Three items are particularly relevant:
- The huge quantity of admissions from the ED and the ability of the hospital to manage emergencies. A
simple indicator compares patient afflux from ED with the normal programmed activity. Bigger is the
number of emergency accesses, lesser is the programmed activity, impairing the hospital mission on the
surrounding region. This analysis, conducted also on the main specialty departments, makes easier to
understand if the hospital has a prevailing emergency or ordinary care orientation;
- The complexity of cases is a further parameter. We must compare the complexity of emergency
inpatients with the ordinary cases, to understand if there are real differences. For example, cancer
admission are mostly programmed, where e.g. in the cardiology department a majority of emergency
accesses are expected. The analysis of cases complexity makes possible to evaluate the hospital mission
and its strategic orientation;
- Another parameter is the average length of hospitalization. This is a very interesting indicator to
evaluate the assistance-care procedure length. Diversity in hospitalization length is very relevant to
understand how emergency affects on assistance-care procedures.
These parameters must be unified. We can briefly define these alternatives:
- ED affects strongly on hospital routines; there are many admissions from the ED, their complexity is
high, as the one of ordinary admissions, and average hospitalization length is similar or longer;
- ED affects lightly on hospital routines; there are few admissions from the ED and a prevalence of
ordinary activity, complexity is similar to the one of ordinary admissions, and average hospitalization
length is similar or shorter;
- an intermediate situation in which there isn’t a defined strategy and organization plan.
4. Production costs and more in general, use and allocation of the resources, to evaluate efficiency in procedures.
A systematic cost recognition, to measure a pro-access cost, can be crucial to determine EDs efficiency, of course
relating costs to service level expected and provided. The costs structure can be an useful analysis to understand
the use of resources (external/internal, services, consulting, drugs, etc.) and the cost control from management.
It can be useful to evaluate from two different perspectives:
- Analysis of production costs and their indicators, to evaluate relative efficiency through the pro-access
cost (dividing ED actual costs for the number of accesses).
- Structure of the cost evaluation and analysis system, to understand the level of attention on
management control. Here both the quality of measurement system and the quality and diffusion of
reporting system must be evaluated.
4. ERs in Italy
The concept of Emergency Room has been described for the first time in Italy in a law rule about healthcare
services and personnel (Royal Decree n.1631 of 1938, Norme generali per l’ordinamento dei servizi sanitari e del
personale sanitario degli ospedali). Italy faces for the first time the challenge to create a place for emergency care,
separated from the rest of the hospital and with dedicated human resources able to handle emergency situations.
29
Copyright ©Pakistan Society of Business and Management Research
International Journal of Management and Administrative Sciences (IJMAS)
(ISSN: 2225-7225)
Vol. 2, No. 1, April, 2013(24-43)
www.ijmas.org
In 1969, with Decree of the President of the Republic (DPR) no. 128 on Hospital Reform, there is a new law rule
about ERs. Article 13 states that “in every hospital a permanent ER service must be ensured, connected on a
regional plan with other local healthcare facilities. ER services must dispose, in every hospital, of special vehicles
and machines for diagnosis and therapy of emergencies [...]”.
During the Eighties emergency care in Italy faces its first evolution lap, with the creation of first EDs in some
Italian Regions. These EDs presented nevertheless relevant and arbitrary differences between the Regions.
Moreover, they were often isolated standpoints, without connections with suitable emergency transport and
doctors on duty. The first two region to promote full integration were Friuli and Emilia-Romagna in mid-Eighties.
The reform of emergency care system will reach its peak at the beginning of the Nineties. The DPR march 27th,
1992 (Atto di indirizzo e coordinamento alle Regioni per la determinazione dei livelli di assistenza sanitaria di
emergenza) defines a national plan to coordinate emergency care services. In 1992 Italy creates a system of
emergency care management still in use today, with Departments for Emergency care structures and services.
For the first time in Italian history, it was imperative to create emergency care system more complex and
articulated than a normal ER, to cover a broader span of care interventions and therapies.
5. The Sicily Region model
Sicily Region, with the Decreto dell’Assessore alla Sanit{ n. 34276 del 27/03/2001, has provided the “Linee guida
generali sul funzionamento del Servizio di Urgenza-Emergenza Sanitaria (S.U.E.S) 118”. S.U.E.S. 118 is a
coordinated system, composed of:
- health alarm with a unique telephone number, managed by an Operative Central that must evaluate,
filter requests and active the care system;
- a network of suitable special transport equipped, able to guarantee the intervention of rescue,
preservation and stabilization of vital functions compromised, and transport the patient as fast as
possible in the adequate point of the Region hospital network, that can afford and possibly resolve the
emergency situation;
- a network of hospital and services in the area, with ERs, triage centers and therapy centers for
emergency care needs.
The emergency organization in the regional network is structured in three levels of crescent complexity, as
stated by Legge Regionale n. 30/1993, Article 36:
- first level emergency services: they must cover the functions of ER, anesthesia and resuscitation,
general medicine, surgery, obstetrics and gynecology;
- second level emergency departments: they must cover the functions of ER and triage, short-stay
observation, resuscitation and ensure diagnostics an therapies in the field of general medicine, surgery,
orthopedy and traumatology, cardiology with UTC (Intensive Heart Care Unit). The center also provides
clinical analysis, radiology and blood transfusions;
- third level emergency departments: they ensure the same performances of a second level (Emergency
and Triage Department), with additional diagnostic possibilities and high-specialized divisions in the
same hospital or near hospitals (neurology, dialysis, hyperbaric rooms, neurosurgery, cardio surgery).
6. Results from a case study: 20 Sicilian Emergency Rooms
There are 654 ERs in Sicily. The sample survey is of 20 ERs, 31.3% of total population. As far as complexity is
concerned, 3 ERs are of first level (15%), 11 ERs are of second level (55%) and 6 ERs are of third level (30%). 8
ERs have beds for short-stay observation (OB, “Osservazione Breve”). OB aims to help filtering admissions,
reducing superfluous admissions and early discharges. 9 ERs have OB beds and beds for ordinary admissions. 3
ERs have no beds at all.
Accesses in year 2010 give and idea of the sample effectiveness. Total accesses to 654 Sicilian ERs are 1.970.000,
and accesses to 20 ERs are 944.611, the 48% of total accesses.
Ordinary admissions in the 20 ERs of the sample are the 46% of Sicily Region (572.117).
If we consider only admissions with emergency characteristics, ordered by ERs, the sample is of 168.210
admissions, the 51,6% of all admissions of this sort in the Region.
30
Copyright ©Pakistan Society of Business and Management Research
International Journal of Management and Administrative Sciences (IJMAS)
(ISSN: 2225-7225)
Vol. 2, No. 1, April, 2013(24-43)
www.ijmas.org
Hospital days for all ordinary admissions in the sample correspond, in 2010, to 45,4% of total hospital days in
the Region (3.937,911). If we consider only admissions with emergency characteristics, ordered by ERs, the
sample represents the 53,4% of all hospital days in Sicily (2.124.996).
Sicily Region, by 1° September 2009, is divided in 9 ASP (Aziende Sanitarie Provinciali, Provincial Healthcare
Organization). Every ASP pays all healthcare interventions, provides public, hospital and decentralized
assistance, and allocates its resources for integrating healthcare services and social services, also by the
“compulsory transfer” of the healthcare provisions from hospital to decentralized services.
Figure 1 represents the geographical distribution of 20 ERs of the sample and their reference ASPs. The complex
sample represents all ASPs; where population density and ASP dimensions are bigger, a higher number of ERs
have been selected (Palermo, Catania and Messina).
Figure 1: Geographic distribution of the sample and its reference ASPs
ASP
ASP 1 - Agrigento
ASP 2 - Caltanissetta
ASP 3 - Catania
ASP 4 - Enna
ASP 5 - Messina
ASP 6 - Palermo
ASP 7 - Ragusa
ASP 8 - Siracusa
ASP 9 - Trapani
6.1 The first area of analysis: JCI for ER
The analysis through JCI indicators observes integrated nurses and doctor processes, their formalization, the
spreading of good practices, and more in general a series of behavioral standards aimed to evaluate the
assistance-care procedures.
Items used for evaluation by professional surveyors express the results with a score from 0 (no compliance at
all) to 1 (total compliance), that allow to easily understand the general organization level. The results are shown
in Annex A.
Four elements are particularly relevant:
1. The average evaluation of the sample is 0.64, not entirely satisfactory, and as expected diversity in scores is
noteworthy.
2. 55% of the evaluations is considered compliant, while 27% is not compliant at all. This means sample EDs
have room for improvement.
3. Situation in single EDs is very diverse and this not only reading the average single score, but also looking at the
contribution of the various factors. In general there is great diversity. 6 EDs are under average, but only 2 have
more than 0.8. Anyway, 8 EDs have more of 60% of compliant behaviors and only 3 EDs have less than 40% of
compliant behaviors.
4. Some weaknesses show some recurrences. Patient safety programs are often absent or largely unsatisfactory.
Regarding infection controls, there is a large gap between EDs that have specific protocols an EDs lacking
adequate measures.
Some factors are meaningful for analysis relevance.
31
Copyright ©Pakistan Society of Business and Management Research
International Journal of Management and Administrative Sciences (IJMAS)
(ISSN: 2225-7225)
Vol. 2, No. 1, April, 2013(24-43)
www.ijmas.org
Regarding triage, 12 EDs have a satisfactory procedure, and this shows a correct direction in regional policies,
emphasizing the necessity to sustain these good behaviors.
Regarding informed consent and in general patients’ awareness, the situation is not entirely satisfactory. The
average of the sample is near to 0,5 and few EDs have correct decision procedures. This emphasizes the necessity
of accurate communication policies.
Regarding examination and re-examination of the patient, the situation is generally positive, even if there is
room for improvement; good practices are being implemented. The average for all hospitals is 0.71, a satisfactory
performance.
Regarding protocols and guidelines the situation is critical, in particular regarding protocols for special needs
patients. The average evaluation is 0.36 (the majority of EDs has no guidelines), but in some case the absence of
protocols becomes dramatic in the treatment of older patients, or psychiatric or security-challenging patients. In
this area improvements is especially required.
Concerning drugs, the average is 0.59, a not entirely satisfactory score, because only in few hospitals observed
behaviors are in compliance with the standards. A noteworthy weakness regards protocols for conservation,
control and theft/loss protection for emergency care drugs.
Quality monitoring by EDs directors looks scarce. In the majority of EDs monitoring system look inadequate or
only partially and poorly implemented. This is a very interested parameter for an overall improvement program.
6.2 The second area of analysis: ER organization model
The analysis of organization model is especially interesting to find hypothesis of efficiency and effectiveness in
sample ERs. This area is, anyway, very complex and it has been subdivided in five items.
The first item concerns the placing of ERs in the local assistance-care system and the presence or not of an ED.
The second concerns the number of accesses pro year and pro die in every ER, and the type of accesses and
needs. The third item observes the efficiency level of dedicated human resources. Work shifts on a weekly,
monthly and yearly basis have been observed, to understand efficiency level and adequacy of human resources.
Fourth item focuses on waiting times, a critical parameter in ERs both on triage and on the beginning of medical
diagnosis. The fifth and last variant observes connection between ERs and other services in the same hospital.
This connections aims to evaluate the ER integration in the whole structure, the effectiveness in performance
and, most of all, the integration of different specialties in handling emergency.
6.2.1 The organizational placing
Concerning organizational placing, 3 ERs are Simple Operative Unit, the other 17 ERs are Complex Operative
Units. As said before, 3 ERs are of first level, 11 ERs are of second level and 6 ERs are of third level. Analyzing
human resources management we can divide the sample in two groups:
A. ERs with own personnel: 11 ERs have a personnel chart, 8 have personnel dedicated exclusively to ER, the
other 3 have the same equipe for ER and ordinary admissions;
B. ERs with integration of human resources: 9 ERs need integration of human resources; 3 with private-contract
doctors, 2 with doctors from other Operative Units, 4 with doctors from other Operative Units that have the same
equipe for ER and ordinary admissions.
6.2.2 ERs access volume
The 20 ERs of the sample have an average of 47,231 accesses pro year (2010). Average day accesses so are 129.
ERs have nevertheless a great diversity in access volume, due to geographical position, dimensions and
managing features. 6 ERs have less than 100 accesses/die, 7 have more than 150 accesses/die: one of them have
198 accesses/die. The ERs with the bigger access volume are in the ASP of Palermo and Catania, as these
provinces have the 48% of all Sicily residents (about 5 millions inhabitants).
To understand access volume an analysis of their types is very interesting, e.g. the percentages of access on the
base of triage color code, the percentage of hospital admissions, transfers to other hospital or leaving of the
patient after triage.
We must here make a necessary premise to triage coding in Italy. There are various methodology, but the most
frequent is based on a four category system, that is not too complex and is apt to categorize the large number of
patients intermediate between ordinary care needs and real emergency. Sicily Region has adopted, as the
majority of Italian Regions, the “color codes”, very easily understood by patients.
The white code is assigned to the less severe cases. Generally these are situations that should be resolved by the
General Practitioner. Patients are cared anyway, but only after the staff has solved the most urgent cases. In
32
Copyright ©Pakistan Society of Business and Management Research
International Journal of Management and Administrative Sciences (IJMAS)
(ISSN: 2225-7225)
Vol. 2, No. 1, April, 2013(24-43)
www.ijmas.org
many regions of Italy today, benefits in white code shall be subject to payment of a fee (ticket), this also to try to
put barriers to entry and avoid the problems of overcrowding of the ERs mentioned widely in the analysis
literature.
The green codes are interventions that can wait. The patient is not life-threatened and is assisted after the most
urgent cases. The patient is re-examined every 30-60minutes.
The yellow code is assigned to patients with serious problems, for which there may be the alteration of one of the
three major vital functions (respiratory, circulatory, nervous). The staff of ER strives to minimize waiting times.
For these patients access to examination rooms should be immediate, consistent with other emergencies in
place. The average waiting time should not exceed 10 minutes. A re-examination of the patient after 5-15mins
from triage is necessary.
The red code is assigned to patients in imminent danger of death, that is, for patients in whom there is in place a
failure of one of the three vital signs (blood, breath, state of consciousness). For these patients access to
examination rooms is immediate and there are no waiting times.
Referring to the 20 ERs of the sample, the percentage distribution of triage codes in accesses is this: 8% white
codes, 74% green codes, 18% yellow+red codes (of which 1% of red codes). This distribution, as shown in Table
2, is in the average of other Italian regions.
Table 2: Percentage of accesses on the basis of triage code
Triage color code
Sicily 20 Ers
Emilia Romagna
Lombardia
Lazio
Red
1%
3%
1%
2%
Yellow
17%
23%
10%
19%
Green
74%
69%
70%
70%
White
8%
6%
19%
9%
We consider only the average of 20 ERs of the sample, as strong asymmetries in the assignation of codes has
been noticed in interviews and elaborating data. This phenomenon has been noticed by the Sicily Region itself
who is working to homogenize triage in ERs.
Concerning the end of the process, 79.5% of accesses in the sample is discharged after visit without other
interventions. 5,4% leaves the ER in the time span between triage and medical examination. 0,1% dies. 1,2% is
transferred in another hospital, 13,8% (141.198 patients) is admitted in the same hospital. The sum of transfers
in other hospitals and admissions in the same hospital give a 15% of admissions, in the exact average of National
Healthcare System (source: Italian Ministry of Health).
6.2.3 Human resources efficiency level
To understand human resources adequacy - on the basis of work shifts and ERs accessions - and its efficiency
level through on-site visit, a questionnaire has been predisposed. Its purpose was to gather the following
informations: human resources in ER and its role chart on the basis of work shifts (morning, afternoon, night,
Sundays and holidays). The average of minutes devoted by doctors and nurses for every access to ER has been
calculated.
The indicator “doctor minutes pro access” expresses the average of minutes devoted by a doctor to every access
in ER. The indicator “nurse minutes pro access” expresses the average of minutes devoted by a nurse to every
access in ER. Both indicators have been calculated dividing the number of minutes worked every day in ER by
doctors and nurses for the average number of accesses.
The average doctor minutes pro access are 33, and the average nurse minutes pro access are 55. There are no
significant correlations between human resources and accesses. There are ERs with a low access volume and a
high rate of doctor and nurse minutes pro access (and this seems logical, as doctors and nurses, working on few
accesses, could have more time for every patient accessing). But there are also ERs with a high access volume
and a high rate of doctor and nurse minutes pro access. For a better analysis of the phenomenon waiting times
have been measured (see next paragraph).
33
Copyright ©Pakistan Society of Business and Management Research
International Journal of Management and Administrative Sciences (IJMAS)
(ISSN: 2225-7225)
Vol. 2, No. 1, April, 2013(24-43)
www.ijmas.org
6.2.4 Waiting times
For every ER the attention was focused on triage methodology (“counter” triage, “global” triage with or without
parameters, with or without ECG, etc.), and on type, quantity (number of nurses/others) and placing (of ER
and/or in support to ER) of personnel (h12/h24) on triage.
Main triage methodologies are: the so-called “counter” triage, where there is no space for a complete patient
examination and measurement of vital parameters. These operations are replaced by inspection.
In “global” triage, on the contrary, an expert nurse with apt training, long-time operator in ER following the
protocols, receives the patients and evaluates the emergency and access priorities.
In the 20 ERs of the sample, 15% performs “counter triage”, 5% “counter triage” with some examinations, 80%
performs “global triage”. 85% has triage h24, 15% has triage h12. Once performed the triage, it is interesting to
measure the average time between the triage itself (with the assignment of a color code) and examination by a
doctor. Of course red code is not in question, as it has no waiting times.
Concerning waiting times, it is noteworthy to mention that 6 ERs have no data available. Between a white code
and a visit, in 5 ERs you have to wait an average of 60 min, in one of them 4 hours and in another 6 hours.
Green code waiting times span from 16 to 127 minutes. Laws prescribe a re-evaluation of color code every 30-60
minutes, so the average of the sample is 48 minutes, and 8 ERs are over the 30 minutes of waiting time.
Yellow code waiting times span from 6 to 43 minutes. Laws prescribe 10 minutes from the code assignment to
the examination, so the average of the sample is 25 minutes, and 11 ERs are over the 10 minutes of waiting time.
Regarding only white codes, we observe that 4 ERs have more than 13% white codes, and 2 of these ERs have a
percentage of 35% and 44%. We could think that this data reflects itself on waiting times between the code
assignment and medical examination, because of a wrong recourse to ER; but analysis shows that ERs with
longer waiting times for white codes are not the ones with a larger number of white codes. There seems to be a
correlation between the number of yellow and red codes and the waiting time for white codes.
6.2.5 Connection with other healthcare and hospital services
For the analysis of ER connections with other healthcare and hospital services the indicator “specialty services in
support of ER”. This indicator is calculated on the basis of number of medical specialists in ER and their
continuity on duty, with the aid of the table below (Table 3). This indicator summarizes the number of specialty
services available in support of ER.
Table 3: Incidences to measure the services provided
Type
Incidence
h24
4
h12 + night availability
2
h12 + night availability in working days + other
1
other
0.5
Specialty services analyzed are the essential ones for ER support, according to guidelines provided by Italian
Ministry of Health. These are about 30 specialties as Anesthesia and Resuscitation, Cardio surgery, Gynecology,
Toxicology, Neurosurgery, Orthopedy and Pediatrics.
The average of the sample is of 54 specialty services in support of ERs. The availability in the sample has a great
diversity, ranging from 24 to 100 services. In general, many structures have a number of services in support of
ER, but some of them are not available h24 or with night and holiday availability.
6.3 The third area of analysis: activity volumes, cases’ complexity in the Hospitals as a whole
The activities of hospitals are particularly interesting to the aim to identify a reference model. Special attention
has been devoted to activity volumes, defined as number of beds for emergency admissions. The distribution of
beds between emergency care and ordinary admissions has been evaluated. Other parameters useful to
understand the connection between ER and the hospital as a whole are the complexity of cases accessing and the
number of hospitalization days necessary to heal them.
In this area of analysis, we expose the results about three indicators: volumes of activity in hospitals stemming
from ERs, complexity of cases accessing and performances indicator.
6.3.1 Beds use
34
Copyright ©Pakistan Society of Business and Management Research
International Journal of Management and Administrative Sciences (IJMAS)
(ISSN: 2225-7225)
Vol. 2, No. 1, April, 2013(24-43)
www.ijmas.org
First indicator is the “beds use” that shows the percentage of beds for emergency admissions on the whole of
beds for admissions. The average of the sample is 63.4%. Figure 2 reports the sample distribution around the
average: 9 hospitals casts themselves in a neighborhood of +/- 15% around average, 3 hospitals are under
average of over the 15% and 9 hospitals are above average of over the 15%. It is noteworthy to say that hospitals
with a lower percentage of beds for emergency admissions are Teaching Hospitals. This could be linked to
various factors, one about production stricto sensu and one about organization procedures: 1. Teaching Hospitals
must not only perform assistance and care, but also a research and teaching role; 2. A better compiling of HDFs
(Hospital Discharge Form) in comparison to other hospitals.
Figure 2: Percentage of beds for emergency admissions on the whole of beds (2010)
6.3.2 Complexity of cases and average days of hospitalization
The second indicator is the Case Mix Index (CMI). This indicator, for every hospital y, is the ratio between the
average incidence (Medicare Weight) of the hospital y and a reference value, that is the whole sample incidence.
In other words, the measurement of the cases complexity accessing each hospital is performed by a ratio
between the composition of cases treated in each hospital, weighted with incidence system DRG (Diagnosis
Related Group), and the weighted composition of cases of the sample. If the indicator is > 1 the Hospital has a
complex production, if < 1 cases have a low complexity if compared to the sample.
The third indicator is linked to average hospitalization, useful to evaluate assistance-care procedures. The
Comparative Performance Index (CPI) allows to evaluate the effectiveness of admissions in terms of average
hospitalization, standardized for case-mix, in comparison with specific reference values, obtained studying the
cases of the whole sample. The numerator in CPI formula represents the hospitalization days you would observe
if every hospital was identical to the average of the whole sample (the reference value); is an average expected
hospitalization, calculated on the basis of each hospital DRGs. If the indicator is > 1 the hospital has a bad
performance, if <1 cases are treated with a shorter average hospitalization in comparison to the sample.
The figure 3 shows the result of the analysis correlating these two indicators (CMI and CPI) referring to
emergency inpatients. You see a correlation between Medicare Weight incidence of cases and average days of
hospitalization. Complexity increasing, the average hospitalization length increases. Here we have four
quadrants. Quadrants 2 and 3 represent hospitals with a particular correlation (standard deviation 0.8) between
complexity of cases and number of days for their resolution. In quadrant 2 there are 7 hospitals. These hospitals
afford emergency cases of high complexity, resolved with a longer hospitalization in comparison with the
sample. In quadrant 4 there are 3 hospitals. They afford emergency cases of low complexity (CMI <0.9), resolved
with a much longer hospitalization in comparison with the sample (CPI > 1.12). Only 1 hospital is in quadrant 1
with CMI=1.04 and a CPI=0.85.
35
Copyright ©Pakistan Society of Business and Management Research
International Journal of Management and Administrative Sciences (IJMAS)
(ISSN: 2225-7225)
Vol. 2, No. 1, April, 2013(24-43)
www.ijmas.org
Figure 3: Case Mix Index & Case Performance Index – emergency admissions
It is interesting to notice, as observed before for Image 2, that Teaching Hospitals are in quadrant 2. Moreover,
almost all the hospitals who have a bed use for emergency higher than 72% is in quadrant 3. This could be an
indicator of an improper use of emergency admission and its beds.
6.4 The fourth area of analysis: production costs
Production costs and, in general, the allocation of resources in production processes, are essential to the
evaluation of effectiveness of the processes themselves. Cost measurement analyses parameters, production
costs and operates a comparison between ERs on these basis. The cost data measurement has been conducted
with a questionnaire prepared for the research and with interviews with the individual managers (20 controllers
of the Hospitals).
Concerning this particular area, 5 hospitals couldn’t provide cost data for their ERs, as their analytical accounting
didn’t consider ER as Cost Center. Considering only the hospitals providing cost data (75% of the sample), 2 of
them have provided medium quality data (analytical accounting of costs, some data are missing). Only 2 of 16
hospitals have provided high quality analytical accounting data, providing for ER accurate cost data.
Cost analysis is of course a critical issue with so scarce a data quality. In Table 4 there are cost data pro-access.
Table 4: Pro-access cost (direct and indirect costs)
Hospitals
Pro-access Total Cost
Pro-access Direct Cost
Pro-access Indirect Cost
7
n.d.
n.d.
n.d.
8
n.d.
n.d.
n.d.
10
n.d.
n.d.
n.d.
12
n.d.
n.d.
n.d.
17
n.d.
n.d.
n.d.
21
n.d.
n.d.
n.d.
16
232.29
85.12
147.17
19
217.06
85.85
131.21
18
214.33
155.50
58.83
36
Copyright ©Pakistan Society of Business and Management Research
International Journal of Management and Administrative Sciences (IJMAS)
(ISSN: 2225-7225)
Vol. 2, No. 1, April, 2013(24-43)
www.ijmas.org
15
191.23
93.10
98.13
3
185.38
96.94
88.44
14
144.27
76.13
68.15
1
144.24
46.90
97.34
6
130.67
90.60
40.07
20
127.89
75.68
52.21
9
121.58
93.30
28.28
13
116.66
85.68
30.98
11
99.19
61.63
37.56
2
91.30
45.81
45.50
4
67.56
49.50
18.06
5
54.00
54.00
0.00
Costs in Euro
Table 4 shows how, in the sample, average cost for every single access to ER is 142.52 € (of which 72€ indirect
cost and 62.79€ direct cost). As far as direct cost is concerned, it should be easier to measure by the hospitals
and by way of consequence more accurate; so we can start from it to describe cost structure.
82.0% of direct costs is employees’ labor cost, 6.1% is consumables cost (sanitary and general service
consumables, etc.), 5.1% is related to sanitary and general services, 6.7% is other direct cost (maintenance
works, compensations, contract workers’ labor).
Regarding indirect costs, 70.0% is diagnosis and therapy cost, 15.0% is general hospital cost and 15.0% can be
labeled as “other” The major costs item related to diagnosis and therapy are Radiology (47.0%) and Laboratory
(31.0%).
Interviews have shown great problems, in almost all hospitals, in measuring ER cost in order to understand proaccess costs. Some more care to measurement and reporting through performance measurement systems could
help to make service more cost-effective, with a good use of the few resources and improve effectiveness and
quality. In this area also, with interviews and report, Sicily region has asked to hospitals to implement a most
accurate cost measurement system, most of all in Emergency context.
7. Discussion
Remarkable differences emerge from an accurate analysis of the 20 EDs. First of all, the dimensional topic. In
general, it doesn’t seem to be very influential. The division in classes does not show particular differences, if not
specific strengths and weaknesses. Hence, one can imagine that, regardless of the size (significant for every ED),
assistance-care processes are not significantly affected by their role. Or, better to say, solutions are generated in
each ED that in turn generate specific problems and solutions.
The topic of human resources effectiveness is quite interesting. While a strong diversity in minutes t pro-patient
(which expresses the average availability of time for each access) has been emphasized, it is confirmed that more
the resources, better the results in terms of quality of ED. A lower availability of time reduces quality. This
phenomenon is very interesting from a general point of view, but also bears an important meaning in terms of
policy to be pursued: creating more equitable systems that could provide a higher care quality. Data show that
those who are below the 50° percentile have an average of qualitative performance of 0.59, while those who are
above that percentile do have an average of 0.71.
The first conclusion is quite clear: to generate a quality improvement, differences in terms of personnel assigned
to ER have to be rebalanced.
Another important consideration relates to the organizational forms. The ED endowed themselves of different
organizational forms, which appear related to organizational processes layered over time. Not all ED have
organizational structures appropriate to the complexity of the levels of service provided. Short-Time
Observations are not always present, and the connection with hospital services has not a reference value. It
looks clear that the organizational models are diverse, due to specific historical data and not always to a rational
organization planning. Significant correlations with other variables l are lacking: this leads to the conclusion that
37
Copyright ©Pakistan Society of Business and Management Research
International Journal of Management and Administrative Sciences (IJMAS)
(ISSN: 2225-7225)
Vol. 2, No. 1, April, 2013(24-43)
www.ijmas.org
it is necessary that each ED develops a way of its own organizational planning for the improvement of the
service. Hence, it looks necessary that each ED makes its own improvement plan to reach more appropriate
performance levels.
However, the public health service, organized in the region on the basis of publicly owned hospitals, has an
important role for the determination of the planning and control, and for the funding of the hospitals themselves.
There is no doubt that the Sicily Region should play an important role in the definition of a process of improving
the performance of the ED. The research shows that it is necessary to implement targeted and differentiated
actions on each reality, which is characterized by specific strengths and weaknesses.
Finally, another customization is needed: reporting systems are poorly structured and do not have the same
weight in management that literature and practice assign to them. From this point of view, it seems clear that the
managerial role may benefit of an important tool to play a more significant role in the management of the
improvement processes. Thus, for example, the cost measurement system can be a powerful tool for focusing of a
cost cutting strategy, and also give a balance in the use of proper inputs to generate an adequate level of quality
as well.
8. Conclusions
The analysis leads to three concluding remarks:
1. The diversity of human resources in EDs has to be reduced. It would allow not only to provide an higher
quality of interventions, but also a better equality in provisions;
2. A line of proper intervention for each ED must be found, in order to promote the development of strategies
focused on the specific situation. This places the focus on the management and its ability to generate strategies
and to implement them;
3. The Region's role as funding institution and head of programming is obviously relevant. However, the need to
support the improvement is noteworthy. This process has to be pursued not through the imposition of stringent
operational schemes, but through an incentive to achieve crucial goals; for example, in terms of quality or timing
of intervention, focusing not on pre-designed organization modules, but on incentives for managers.
38
Copyright ©Pakistan Society of Business and Management Research
International Journal of Management and Administrative Sciences (IJMAS)
(ISSN: 2225-7225)
Vol. 2, No. 1, April, 2013(24-43)
www.ijmas.org
References
Ammons DN (1992). Productivity Barriers in the Public Sector. In Holzer M (Editor), Public Productivity
Handbook. NY: Marcel Dekker: 117 - 136.
Arah OA, Westert GP, Hurst J, Klazinga NS (2006). A conceptual framework for the OECD Health Care Quality
Indicators Project. International Journal for Quality in Health Care. 26: 5 - 13.
Asplin BR, Magid DJ, Rhodes KV, Solberg LI, Lurie N, Camargo CA (2003). A conceptual model of emergency
department crowding. Annals of Emergency Medicine. 42(2): 173 – 180.
Baer RB, Pasternack JS, Zwemer FL (2001). Recently discharged inpatients as a source of emergency department
overcrowding. Academic Emergency Medicine. 8(11): 1091 – 1094.
Bamezai A, Melnick G, Nawathe A (2005). The Cost of an Emergency Department Visit and Its Relationship to
Emergency Department Volume. Annals of Emergency Medicine. 45(5): 483 – 490.
Beaulieu H, Ferland J, Gendron B, Lefebvre L (1998). A computer system based on optimization for scheduling
physicians in the emergency room. Publication #1127, Département d’informatique et de recherche
opérationnelle, Université de Montréal.
Beaulieu H, Ferland J, Gendron B, Michelon P (2000). A mathematical programming approach for scheduling
physicians in the emergency room. Health Care management Science. 3(3): 193 – 200.
Behn RD (2003). Why measure performance? Different purposes require different measures. Public
Administration Review. 63(5): 586 – 606.
Bernstein SL, Aronsky D, Duseja R, Epstein S, Handel D, Hwang U, McCarthy M, John McConnell K, Pines JM,
Rathlev N, Schafermeyer R, Zwemer F, Schull M, Asplin BR (2008), The Effect of Emergency Department
Crowding on Clinically Oriented Outcomes. Academic Emergency Medicine. 16(1): 1 – 10.
Bernstein SL, Asplin BR (2006). Emergency department crowding: old problem, new solutions. Emergency
medicine clinics of North America. 24(4): 821 – 837.
Birnbaum A, Gallagher J, Utkewicz M, Gennis P, Carter W (1994). Failure to validate a predictive model for refusal
of care to Emergency Department patients. Academic Emergency Medicine. 1(3): 213 – 217.
Brooke L, Graham N, Spaite D, Garrison H, Maio R (2007). A Comprehensive Framework for Determining the Cost
of an Emergency Medical Services System. Annals of Emergency Medicine. 49(3): 304 – 313.
Censis (2008). I modelli decisionali nella sanità locale. Censis, Roma.
Chassin MR, Loeb JM, Schmaltz SP, Wachter RM (2010). Accountability Measures – Using Measurement to
Promote Quality Improvement. New England Journal of Medicine. 363: 683 – 688.
De Lancer JP (2009). Performance–Based Management System: Effective Implementation and Maintenance. CRC
Press, New York, NY.
Derlet R, Kinser D, Ray L, Hamilton B, McKenzie J (1992). Prospective identification and triage of nonemergency
patients out of an Emergency Department. Annals of Emergency Medicine. 25(2): 215 – 223.
Dickinson G (1989). Emergency department overcrowding. CMAJ. 140(3): 270 – 271.
Formez (2007). I sistemi di governance dei servizi sanitari regionali. Formez, 57.
Gallagher EJ, Lynn SG (1990). The etiology of medical gridlock: causes of emergency department overcrowding in
New York City. Journal of Emergency Medicine. 8(6): 785 – 790.
Gooijer J (2000). Designing a knowledge management performance framework. Journal of Knowledge
Management. 4(4): 303 – 310.
Halachmi A (2002). Performance measurement, accountability, and improved performance. Public Performance
and Management Review. 25(4): 370 – 374.
Hwang U, Concato J (2004). Care in the emergency department: how crowded is overcrowded? Academic
Emergency Medicine. 11(10): 1097 – 1101.Joint Commission International (2011). Accreditation
Standards for Hospitals. Joint Commission Resources, One Renaissance Boulevard, Oakbrook Terrace, Illinois
60181 U.S.A.
Kellermann AL (2005). Calculating the cost of Emergency Care. Annals of Emergency Medicine. 45(5): 491 – 492.
Kellermann AL (2006). Crisis in the Emergency Department, The New England Journal of Medicine. 355: 1300 –
1303.
39
Copyright ©Pakistan Society of Business and Management Research
International Journal of Management and Administrative Sciences (IJMAS)
(ISSN: 2225-7225)
Vol. 2, No. 1, April, 2013(24-43)
www.ijmas.org
Kelley E, Hurst J (2006). Health Care Quality Indicators Project: Conceptual Framework. OECD Health Working
Papers. 23 doi:10.1787/440134737301.
Kennedy K, Aghababian RV, Gans L, Lewis CP (1996). Triage: techniques and applications in decisionmaking.
Annals of Emergency Medicine. 28(2): 136 – 144.
Khurma N, Bacioiu GM, Pasek ZJ (2008). Simulation–based verification of lean improvement for emergency room
process. Proceedings of the 2008 Winter Simulation Conference, edited by Mason SJ, Hill RR, Mönch L,
Rose O, Jefferson T, Fowler JW. 1490 – 1499.
Knapp J.F. et al (2004). Overcrowding Crisis in Our Nation’s Emergency Department: Is Our Safety Net
Unraveling?. Pediatrics. 114(3): 878 – 888.
Kravchuk RS, Schack RW (1996). Designing effective performance measurement systems under the Government
Performance and Results Act of 1993. Public Administration Review. 56(4): 348 – 358.
Lowe RA, Bindman AB, Ulrich SK, Norman G, Scaletta TA, Keane D, Washington D, Grumbach K (1994). Refusing
care to Emergency Department of patients: evaluation of published triage guidelines. Annals of
Emergency Medicine. 23(2): 286 – 293.
Mann S (1986). Politics of public productivity. In Halachmi A, Holzer M (Eds), The Best of Public Productivity and
Management Review, Chatelaine Press, Burke, VA.
Marshall M (1996). Development and Use of Outcome Information in Government: Prince William County,
Virginia. ASPAs Center for Accountability and Performance, Washington, DC.
McClellan CM, Cramp F, Powell J, Benger JR (2013). A randomised trial comparing the cost effectiveness of
different emergency department healthcare professionals in soft tissue injury management. BMJ Open.
3(1): doi:10.1136/bmjopen–2012–001116
Murray CLJ, Evans DB (2003). Health Systems Performance Assessment Debates, Methods and Empiricism.
World Health Organization. Geneva.
Murray M, Bodenheimer T, Rittenhouse D, Grumbach K (2009). Improving timely access to primary care: case
studies of the advanced access model. JAMA. 289(8): 1042 – 1046.
Nathan R, Dominik A (2008). Systematic Review of Emergency Department Crowding: Causes, Effects, and
Solutions. Annals of Emergency Medicine. 52(2): 126 – 136.
Newcomer KE (1997a). Editor’s notes. In Newcomer KE (Ed.), Using performance measurement to improve
public and nonprofit programs. New Directions for Evaluation. 75: 1 – 3.
Newcomer KE (1997b). Using performance measurement to improve programs. In Newcomer KE (Ed.), Using
performance measurement to improve public and nonprofit programs. New Directions for Evaluation.
75: 5 – 14.
Newcomer KE, Wright RF (1997). Effective use of performance measurement at the federal level, Public
Administration Times. 20(2): 72 – 86.
Richardson LD, Asplin BR, Lowe RA (2002). Emergency department crowding as a health policy issue: past
development, future directions. Annals of Emergency Medicine. 40(4): 388 – 393.
Scardigli V, Zangrandi A (2009). The hospital nurses in search of autonomy. The results of a survey among Italian
public health care organizations. Mecosan. 18(70): 99 – 123.
Shari W, James A, Camargo CA, Reese C (2006). Emergency Department Performance Measures and
Benchmarking Summit. Academic Emergency Medicine. 13(13): 1074 – 1080.
Smith PC (2002). Measuring Up. Improving Health Systems Performance in OECD Countries. OECD. Ottawa.
Sole F, Schiuma G (2010). Using performance measures in public organisations: challenges of Italian public
administrations. Measuring Business Excellence. 14(3): 70 – 84.
The Join Commission (2009). Improving America’s Hospitals: The Joint Commission’s Annual Report on Quality
and Safety 2009, The Joint Commission, Chicago.
The Join Commission (2010). Improving America’s Hospitals: The Joint Commission’s Annual Report on Quality
and Safety 2010, The Joint Commission, Chicago.
Torres R, Preskill H (2001). Performance measurement in budgeting: a study of county governments. Public
Budgeting and Finance. 20(3): 102 – 118.
40
Copyright ©Pakistan Society of Business and Management Research
International Journal of Management and Administrative Sciences (IJMAS)
(ISSN: 2225-7225)
Vol. 2, No. 1, April, 2013(24-43)
www.ijmas.org
Vainieri M, Nuti S (2011). Performance Measurement Features of the Italian Regional Healthcare Systems:
Differences and Similarities. In Health Management – Different Approaches and Solutions, edited by Dr.
Krzysztof Smigorski.
Veillard J, Champagne F, Klazinga N, Kazandjian V, Arah OA, Guisset AL (2005). A performance assessment
framework for hospitals: the WHO regional office for Europe PATH project. International Journal for
Quality in Health Care. 17(6): 487 – 496.
Welch S, Stone–Griffith S, Asplin B, Davidson SJ, Augustine J, Schuur JD (2011). Emergency Department
Operations Dictionary: Results of the Second Performance Measures and Benchmarking Summit.
Academic Emergency Medicine. 18(5): 539 – 544.
Wholey JS (1999). Performance–Based Management: Responding to the Challenges, Public Productivity and
Management Review. 22(3): 288 – 307.
Williams RM (1996a), The costs of visits to emergency departments. The New England Journal of Medicine. 334:
642 – 646.
Williams RM (1996b). Triage and Emergency Department Services. Annals of Emergency Medicine. 27(4): 506 –
508.
Wisniewski M, Stewart D (2004). Performance measurement for stakeholders: the case of Scottish local
authorities. The International Journal of Public Sector Management. 17(3): 222 – 233.
Yeh J, Lin W (2007). Using simulation technique and genetic algorithm to improve the quality care of a hospital
emergency department. Expert Systems with Applications. 32(4): 1073 – 1083.
Young GP, Lowe RA (1997). Adverse outcomes of managed care gatekeeping. Academic Emergency Medicine.
4(12): 1129 – 1136.
41
Copyright ©Pakistan Society of Business and Management Research
International Journal of Management and Administrative Sciences (IJMAS)
(ISSN: 2225-7225)
Vol. 2, No. 1, April, 2013(24-43)
www.ijmas.org
Annex A
42
Copyright ©Pakistan Society of Business and Management Research
International Journal of Management and Administrative Sciences (IJMAS)
(ISSN: 2225-7225)
Vol. 2, No. 1, April, 2013(24-43)
www.ijmas.org
Legend
1st Area:
n.e.: not evaluable; values 0: no compliance; value 1: total compliance
2nd Area:
un.: unavailable
2.1
2: ER with beds for inpatients; 3: ER in Complex Operative Unit with Short-Stay
Observation; 4: ER in Simple Operative Unit
2.2; 2.3; 2.4 and 2.5
1: Hospitals are under average of over the 15%; 2: a neighborhood of - 15% around
average; 3: a neighborhood of + 15% around average; 4: Hospitals are above average
of over the 15%.
3rd Area:
3.1; 3.2; and 3.3
1: Hospitals are under average of over the 15%; 2: a neighborhood of - 15% around
average; 3: a neighborhood of + 15% around average; 4: Hospitals are above average
of over the 15%.
4th Area:
un. = unavailable
4.1
1: Hospitals are under average of over the 15%; 2: a neighborhood of - 15% around
average; 3: a neighborhood of + 15% around average; 4: Hospitals are above
average of over the 15%.
4.2
1: null; 2: low; 3: medium; 4: hight
42
Copyright ©Pakistan Society of Business and Management Research