Assessment of the Portuguese Pediatric Healthcare Services
Based on Pediatric Quality Indicators
Is it really possible?
Adriana Pinto – mimed07200 med.up.pt
Ana Ferrão – mimed07014 med.up.pt
Ana Rita Dias – mimed07036 med.up.pt
Fátima Ribeiro – mimed07214 med.up.pt
Guadalupe Marinho – mimed07224 med.up.pt
Joana Amorim – mimed07210 med.up.pt
João Neves – mimed07061 med.up.pt
Luís Teles – mimed07083 med.up.pt
Mafalda Gonçalves – mimed07087 med.up.pt
Pedro Pereira – mimed07006 med.up.pt
Sara Miranda – mimed07161 med.up.pt
Sara Roca – mimed07157 med.up.pt
turma1_fmup@hotmail.com
Prof. Alberto Freitas Class 1
Introdução à Medicina II
ABSTRACT
Introduction: Nowadays, patients are increasingly interested in the quality of care provided by
hospitals, particularly about pediatric health care services, since it is sufficiently different from adult
care and therefore specific metrics are required. Little is known about the magnitude of deficits in the
quality of care delivered to children since comprehensive studies have been lacking.
The Agency for Healthcare Research & Quality (AHRQ) in 1994 identified 33 indicators to evaluate
quality in the hospitals. Later on, it was necessary to specify quality indicators for Pediatric Hospital’s
Services, in attention to the different needs of children, which led to the definition of the Pediatric
Quality Indicators (PDI’s). These were divided in two categories: provider-level indicators (potentially
preventable complications) and area-level indicators (patient’s risk of the complication occurred in a
separate hospitalization).
Aim: The main goal of our research is to evaluate the quality of Pediatric Portuguese Public Services
determining the PDI’s identified by AHRQ, comparing results obtained for each hospital according to
1
its location (North, Centre, Lisbon, Alentejo and Algarve), economical groups and their evolution
among several years.
Methods: The present investigation is based on bibliographic review of scientific studies published in
MEDLINE (Pubmed). Pediatric Quality Indicators are calculated according to the technical
specifications provided by the AHRQ, using the SPSS software.
Our study will focus on the Pediatric Portuguese inpatient episodes. Pediatric inpatient must respect
determined characteristics, such as being under 18 years old, excluded of MDC - Major Diagnostic
Category (Pregnancy, Childbirth & the Puerperium) and of adult Diagnostic Related Groups.
This is a longitudinal and retrospective investigation because are analysing clinical data collected
from 2000 to 2005 and provided by ACSS (Administração Central do Sistema de Saúde), and it is
also an observational study since there is not a direct intervention over our study population.
Results: In this stage of our project, we randomly chose five of the eighteen PDIs and three variables
to present the results. We cannot take many conclusions based in the results presented before but
this allowed us to be aware of some limitations we will face in the results analysis and conclusion of
our investigation, such as the vast quantity of data and variables and the disparity of the quality
codification system among hospitals. Having these limitations in mind, will be possible to define the
best strategy to analyse and present the results obtained.
KEY-WORDS
Quality of Health Care [N05.715]; child [M01.060.406]; adolescent [M01.060.057]; Portugal
[Z01.542.727]; Quality Indicators, Health Care [N04.761.789].
INTRODUCTION: BACKGROUND AND JUSTIFICATION
Nowadays we are assisting to a demand on information about the quality of medical cares offered by
hospitals. [1] Therefore, it became necessary to take certain measures in order to evaluate that
quality. In response to this, in 1994, the Health Care Cost and Utilization Project were developed at
the Agency for Health Care Research and Quality. Initially 33 indicators were created, designed to
evaluate quality at the hospital for further analysis. However, it was apparent that Quality Indicators
weren’t specific enough to describe and evaluate children healthcare. Once children form a large
percentage of the hospitalizations in our country, specific sets to measure to evaluate children health
care were created - Pediatric Quality Indicators.
These indicators are a set of measures that focus on children’s health care quality using routinely
collected hospital discharge data as the basis for indicators specification.
The population in study needs to have several characteristics like:
- Age under 18 years
- Not in adult diagnosis related groups
2
- Not in major diagnosis category such as pregnancy, childbirth and the puerperium.
The quality indicators are divided in two categories:
Provider-level indicators – include cases where a secondary diagnosis code flags a potentially
preventable complication, as example:
- Decubitus ulcer
- Transfusion reaction
- Selected infections due to medical care
- Pediatric heart surgery volume
- Foreign body left during procedure
Area-level indicators – cases where a patient’s risk of the complication occurred in a separate
hospitalization, as example:
- Asthma admission rate
- Diabetes short-term complication rate
- Urinary tract infection admission rate. [2]
The present investigation is based on these pediatric quality indicators, created by Agency for
Healthcare Research & Quality (AHRQ) in order to evaluate the quality of some pediatric public
services in Portuguese hospitals. This study can be considered important and innovative since there
are findings suggesting that the movement to measure medical care quality has been accelerating,
spurred on by evidence of poor quality of care and trials of interventions to improve care. [3]
Pediatric care, particularly that provided in pediatric intensive care units, is sufficiently different from
adult care therefore requires specific metrics. [4] Little is known about the magnitude of deficits in the
quality of care delivered to children, since comprehensive studies have been lacking [5] and the
evidence base for pediatric care is more limited than for adult care. [6]
This research can provide information to patients about their possibilities and best options. Although
this study could become essential to Portuguese pediatric patients it is also to hospitals
administration, since appropriate measurement of quality of care is an essential aspect of improving
the quality of care.[3] From our results they will be able to be aware of their errors and consequently
improve them.
The investigation will also focus the attention on differences that may exist between regions since
others researches suggested that there may be differences in quality in rural critical access hospitals
and urban acute care hospitals and support the need for future studies addressing disparities
between urban acute care and rural critical access hospitals. [7]
3
The main goal of our research is to evaluate the quality of Pediatric Portuguese Services determining
the PDI’s identified by AHRQ. In this evaluation, it will be considered several factors as their evolution
among five years (from 2000 to 2005), location (North, Centre, Lisbon, Alentejo and Algarve),
administrative and economical groups.
PARTICIPANTS AND METHODS
Study participants
Our study will focus on the Pediatric Portuguese inpatient episodes. Pediatric inpatient must respect
determined characteristics, such as being under 18 years old, excluded of MDC - Major Diagnostic
Category (Pregnancy, Childbirth & the Puerperium) and of adult Diagnostic Related Groups.
Study design
Our study is considered longitudinal and retrospective because we intend to get information about the
pediatric quality services, analysing clinical data collected from 2000 to 2005.
It is also an observational study, since we aim to observe the evolution of PDI’s on the period
considered and there is not a direct intervention over our study population.
Data collection methods
The clinical and administrative data of all inpatient episodes on Portuguese Hospitals from 2000 to
2005 used to calcule the PDI’s on our investigation were provided by ACSS (Administração Central
do Sistema de Saúde). To calculate some of the PDI’s (Area Level Indicators) we need extra data
about the population distribution in Portugal, which will be given by INE (Instituto Nacional de
Estatística).
The Pediatric Quality Indicators Technical Specifications (version 3.2; February 29, 2008), with
inclusion and exclusion criteria used to calculate the PDI’s, were available on the AHRQ (Agency for
Healthcare
Research
and
Quality)
webpage,
(http://www.qualityindicators.ahrq.gov/pdi_download.htm).
To compare our results with the investigation published by Sábado Magazine, we contacted the
article responsible Dr. Carlos Costa in order to obtain detailed information about the used methods.
Dr. Carlos Costa oriented us to the “Escola Nacional de Saúde Pública” (ENSP) webpage
(http://www.ensp.unl.pt), to get more information.
Variables description
The main variables included in the data base provided by ACSS that are used in order to calculate
the PDI’s were Hospital’s ID, primary diagnosis, secondary diagnosis, diagnosis and surgical
4
procedure (ICD-9-CM code), diagnosis related group (DRG), birth weight, length of stay at the
hospital, age (in years), major diagnosis category, Residence area, kind of hospital, hospitals
(divisions per economic groups), administrative division and hospital localization.
Statistical analysis
The present investigation is based on bibliographic review of scientific studies published in
MEDLINE (Pubmed).This bibliographic review was done in order to obtain more information related
with our project which helped us to calculate and compare the final results. The research was also
useful to clarify the importance of this kind of studies to the population in general.
The Pediatric Quality Indicators (PDI’s) were calculated according to the technical specifications
provided by the AHRQ using the SPSS (Statistical Package for the Social Sciences).
In order to calculate the PDI’s we start by opening SPSS data base, which includes all cases that
have been registered on Portuguese Hospitals from 2000 to 2005.
The first step to calculate the PDI implicates the application of the general inclusion and exclusion
criteria of PDI’s, as being under 18 years old, excluded of MDC - Major Diagnostic Category
(Pregnancy, Childbirth & the Puerperium) and of adult Diagnostic Related Groups.
Secondly, we have to apply the specific inclusion and exclusion criteria of the numerator of the
chosen PDI’s. After that, is necessary to calculate the denominator, by applying both the general and
the specific inclusion and exclusion criteria of the PDI in study.
Finally, we divide the numerator by the denominator to obtain the final result.
To exemplify our method, we will describe how to calculate the PDI1:
Accidental Puncture or Laceration (PDI1):
This Indicator consists on the number of patients with accidental puncture or laceration per 1.000
eligible admissions (population at risk). [8]The Accidental Puncture or Laceration indicator is intended
to flag cases of complications that arise due to technical difficulties in medical care--specifically,
those involving an accidental puncture or laceration.[9]
As stated before, to calculate PDI1 we open the SPSS data base with all inpatient episodes on
Portuguese Hospitals and apply the general inclusion and exclusion criteria.
We proceed calculating the numerator that is the discharges among cases meeting the inclusion and
exclusion rules for the denominator with ICD-9-CM code denoting accidental cut, puncture,
perforation, or hemorrhage during medical care in any secondary diagnosis field.
5
To determinate the denominator, we apply the specific inclusion and exclusion criteria of the
denominator.
The denominator of Decubitus Ulcer has the following criteria:
Included cases:
•
All medical and surgical discharges under age 18 defined by specific DRGs - Diagnostic
Related Groups, using ICD-9-CM codes available in Appendix B (Surgical Discharge DRGs)
and E (Medical Discharge DRGs).
Excluded cases:

with ICD-9-CM code denoting technical difficulty (e.g., accidental cut, puncture, perforation, or
laceration) in the principal diagnosis field;

MDC 14 (pregnancy, childbirth, and puerperium);

normal newborn (DRG 391);

Newborns with birth weight less than 500 grams, available in Appendix G: Low Birth Weight
Categories.
Finally, we terminate the PDI dividing the numerator by the denominator. The final result was
977/784820=1,245 per 1000, then we compared our result with the value provided on AHRQ website
(Kids’ Inpatient Database, 2003), AHRQ value: 0.871 per 1000 [10].
Ranking elaboration
PDI 10, due to its complexity and syntax extension, was not possible to calculate.
The fact that there are hospitals which number of cases in the denominator is much reduced can lead
to fallacious conclusions. The denominator corresponds to the number of people who are in risk of
suffering from the medical negligence described in each PDI.
In general, hospitals which offer worse conditions are the ones which have a smaller denominator,
once they tend to send their patients to better equipped hospitals. Therefore, it wouldn’t be fair to
compare these hospitals with the other ones, with better conditions.
To overcome this difficulty, two strategies were adopted. The first one consisted in making a ranking
in which only Central Hospitals were included. The second strategy was to eliminate, for each PDI,
the hospitals which had a denominator lower than 50. This value (50) was established as a limit
because it is an extremely low number, which would slant the study.
In what concerns to the Ranking of Hospitals per Regions, it was decided to use the variable NUT II.
According to Level II of Nomenclatura das Unidades Territoriais para Fins Estatísticos (NUTS),
published in Diário da República, N.o 255, I SÉRIE-A 7101, 5th November 2002, Alteração ao
6
Decreto-Lei n.o 46/89, de 15 de Fevereiro, Portugal is divided into seven regions. Five are in the
continent – Norte, Centro, Lisboa, Alentejo and Algarve – and also Açores and Madeira.
To make the ranking, we started by ordering the Hospitals PDIs results by increasing order, except
for PDI 7.
Based on the information provided in AHRQ web site, we came to the conclusion that, for the majority
of PDIs, the higher the result, the worse are the hospital’s conditions. The exception was PDI 7, in
which a higher value indicates better hospital conditions, reason why the used scale was made in a
decreasing order.
Secondly, it was attributed punctuation from -10 to +10 to each hospital or region, according to the
ranking in question. The “+10” corresponds to the highest value, the “-10” to the minimal value
(except for PDI 7) and zero (0) is the value of the quotient of the total numerator by the total
denominator of each PDI.
To the values between zero and the extreme values (-10 and +10) it was attributed an intermediate
score, according to the position that each one occupied in the ranking. In order to explain this
attribution of values in a more explicit way, we present as examples PDIs 7 and 18:
NUT II PDI value
Ranking Punctuation
NUT II
PDI value
Ranking Punctuation
4
0
-10
4
107,05
10
5
2
-5
5
162,57
6,67
2
28
3,33
2
163,18
3,33
1
35
6,67
3
184,88
-5
3
53
10
1
190,22
-10
PDI 7
PDI 18
Afterwards, all the punctuations obtained for each PDI were summed, bearing in mind each hospital
or region. In the end, the best hospital or region, according to the ranking in question, had the highest
final punctuation.
Finally, the hospitals or regions were ordered in a decreasing order, according to the obtained
punctuation.
7
RESULTS, TABLES AND GRAPHICS
In the following table we present a brief description of each chosen PDI:
Quality Indicator
PDI 1 - Accidental
Description
Cases of technical difficulty per 1,000 eligible discharges
Puncture or
(population at risk). Accidental cut, puncture, perforation or
Laceration
hemorrhage during medical care. (2)
PDI 2 Decubitus Ulcer
Number of patients with decubitus ulcer (pressure sores). per
1,000 eligible admissions (population at risk).(2)
Number of patients with a foreign body unintentionally left in
PDI 3 - Foreign Body
left during
procedure
during a procedure per 1,000 eligible admissions (population at
risk). This indicator is intended to track injuries occurring during
a procedure, specifically accidental cut, puncture, perforation, or
laceration. These procedures may be prevented through proper
technique during procedures. (2)
Number of patients with an iatrogenic pneumothorax and
PDI 4 - Iatrogenic
pneumothorax (in
neonates at risk)
exclusions per 1,000 eligible admissions.
This indicator is intended to flag cases of pneumothorax caused
by medical care in high risk neonates. Premature neonates are at
higher risk of developing barotrauma due to ventilation.
(2)
Number of patients with an iatrogenic pneumothorax per 1,000
PDI 5 - Iatrogenic
pneumothorax in
non-neonates
eligible admissions.
This indicator is intended to flag cases of pneumothorax caused
by medical care, which is sustained following a procedure or due
to barotrauma. Cases of diaphragm surgery and with pleural
effusion are also included.(2)
Number of patients with postoperative hemorrhage or hematoma
PDI 6- Postoperative
hemorrhage and
hematoma
requiring a procedure per 1000 eligible admissions.
This indicator is intended to flag cases of hemorrhage or
hematoma following a surgical procedure. This indicator limits
hemorrhage and hematoma codes to secondary procedure and
diagnosis codes in order to isolate those hemorrhages that can
truly be linked to a surgical procedure. High quality surgical
8
technique and proper prophylaxis in high risk patients may reduce
the risk of this complication. (2)
Number of patients undergoing surgery for congenital heart
PDI 7 - Pediatric
heart surgery
volume
disease.
Discharges with a procedure codes for surgical intervention for
congenital heart disease or non-specific heart surgery with a
diagnosis code of congenital heart disease in any field.
(2)
Number of patients with sepsis per 1,000 eligible admissions.
This indicator is intended to flag cases of nosocomial
PDI 8 Postoperative
Sepsis
postoperative sepsis. This indicator limits its definition of sepsis to
secondary diagnoses (meaning sepsis was not labeled as the
principal diagnosis). High quality of care may reduce the risk for
this complication. (2)
Number of abdominopelvic surgery patients with disruption of
abdominal wall per 1000 eligible admissions.
PDI 9 - Postoperative
wound dehiscence
The indicator relates to wound dehiscence in patients who have
undergone abdominal and pelvic surgery. The indicator is
restricted to secondary diagnoses, and is intended to capture
cases occurring within the same hospitalization.(2)
PDI 10 - Selected
infection due to
medical care
Number of patients with specific infection codes per 1,000 eligible
admissions.
This indicator is intended to capture infections that are due to
medical care, but are limited to those easily captured using
administrative data. This indicator likely captures mostly line and
other vascular access related infections. (2)
PDI 11 - Transfusion
reaction
Number of patients with transfusion reaction per 1,000 eligible
admissions.
This indicator focus on ABO and Rh incompatibility reactions.
PDI 12- Selected
Number of patients with specific infection codes per 1,000
infection due to
eligible admissions. This indicator is intended to capture
9
medical care
infections that are due to medical care, but are limited to those
easily captured using administrative data. This indicator likely
captures mostly line and other vascular access related
infections. High quality care is likely to reduce the risk for this
complication.(2)
PDI 13 - Diabetes
short-term
Number of patients admitted for diabetes short-term complications
(ketoacidosis, hyperosmolarity, coma), per 100,000 population
complications
This indicator has the aim of identify hospitalizations for diabetic
admission rate
ketoacidosis, coma, and hyperosmolarity.(2)
Number of patients admitted for gastroenteritis, per 100,000
PDI 14 -
Gastroenteritis
admission rate
population.
The aim of this indicator is to identify hospitalizations for
gastroenteritis, where gastroenteritis is identified as the principal
reason for hospitalization. (2)
PDI 15 - Perforated
appendix admission
Number of patients admitted for perforated appendix, per 100
admissions for appendicitis within an area.(2)
rate
Number of patients admitted for gastroenteritis per 100,000
PDI 16 Gastroenteritis
population. This indicator is intended to identify hospitalizations
for gastroenteritis, where gastroenteritis is identified as the
admission
principal reason for hospitalization. Timely and effective care for
rate
gastroenteritis, such as oral rehydration therapy, may reduce the
need for hospitalization. (2)
PDI 17 - Pediatric
heart surgery
Number of in-hospital deaths in patients undergoing surgery for
congenital heart disease per 1000 patients.(2)
mortality rate
10
PDI 18 - Pediatric
heart surgery volume
rate
Number of patients undergoing surgery for congenital heart
disease.
This includes procedure codes for surgical intervention, for
congenital heart disease (in any field) or non-specific heart
surgery (in any field) with a diagnosis code of congenital heart
disease (in any field). (2)
Description of the Hospitals Ranking
Hospitals 2, 77, 88 are considered Pediatric Hospitals. Hospitals 24, 53, 54 are Traditional University
Hospitals and Hospitals 3, 8, 16, 39, 68, 72, 78, 80, 83, 94 are Non-Traditional University Hospitals.
Traditional University Hospitals are the ones in which universities installations are common to those
from the hospitals, while Non-Traditional University Hospitals are those which establish protocols with
universities.
Hospital ID
1
Provider Level PDIs
80.625
Hospital ID
78
Area Level PDIs
34.728
61
70
28
34.593
69
68.75
50
34.158
83
64.58
20
32.202
5
61.875
3
31.516
57
60
33
31.172
6
59.667
26
31.086
53
54.321
61
29.452
26
49.286
23
28.818
16
48.421
34
28.568
77
44.893
74
28.26
39
43.125
68
22.224
71
42.75
94
18.896
44
42.047
57
18.34
94
40
5
17.784
72
37.107
6
16.936
2
37.05
71
16.434
74
33.41
69
14.448
78
31.728
39
11.93
3
27.95
72
8.418
68
26.232
53
5.373
28
20.75
77
2.207
54
18.241
1
2.154
11
23
12.05
44
-10.093
20
11.493
83
-13.2707
50
5.173
16
-13.534
33
3.533
24
-15.29
34
-10
2
-27.928
24
-17.359
88
-29.131
88
-29.171
54
-36.313
Table 1 – Central Hospitals Ranking according to Provider-Level and Area-Level Indicators
Hospital 1 obtained the best final result in Provider Level PDIs, while the best hospital in terms of
Area Level PDIs was Hospital 78. Hospital 88 obtained the worst final result in Provider Level PDIs,
while the worst hospital in terms of Area Level PDIs was Hospital 54.
Hospital ID
Ranking Punctuations
61
69
1
26
5
57
6
78
74
53
3
71
94
28
39
83
68
77
72
20
23
50
16
33
44
34
2
54
24
88
99.452
83.198
82.779
80.372
79.659
78.34
76.603
66.456
61.67
59.694
59.466
59.184
58.896
55.343
55.055
51.309
48.456
47.1
45.525
43.695
40.868
39.331
34.887
34.705
31.954
18.568
9122
-18.072
-32.649
-58.302
Municipality
Code
110500
151200
110500
131200
110600
60300
110600
110600
111000
60300
110600
60300
110500
131200
110600
30300
110600
131200
131200
110600
110600
60300
110600
110600
131700
131200
110600
110600
131200
60300
Municipality
Cascais
Setúbal
Cascais
Porto
Lisboa
Coimbra
Lisboa
Lisboa
Oeiras
Coimbra
Lisboa
Coimbra
Cascais
Porto
Lisboa
Braga
Lisboa
Porto
Porto
Lisboa
Lisboa
Coimbra
Lisboa
Lisboa
V. N. Gaia
Porto
Lisboa
Lisboa
Porto
Coimbra
12
Table 2 – Central Hospitals Ranking
Hospital 61, from Cascais, obtained the highest value in the ranking, which means it is the best
hospital in terms of Pediatric Quality Indicators. It is followed by Hospital 69, from Setúbal, and
Hospital1, also from Cascais.
Hospital 88, from Coimbra, obtained the lowest punctuation of the ranking: -58,302.
1st
2nd
3rd
4th
5th
General Ranking
Alentejo
Algarve
Lisboa
Norte
Centro
Provider-Level PDIs
Alentejo
Norte
Algarve
Centro
Lisboa
Area-Level PDIs
Alentejo
Centro
Algarve
Lisboa
Norte
Table 3 – NUT II Ranking
In general, the region of Alentejo includes the better classified hospitals. It is followed by Algarve,
Lisboa, Norte and, finally, Centro.
DISCUSSION OF RESULTS
NUT II
The surprising good results of the regions of Alentejo and Algarve are probably related to the fact
that, in these regions, there are no Central Hospitals. Therefore, severe cases are not sent to the
hospitals of these areas, which decreases the probability of occurring complications.
When comparing Area Level with Provider Level Indicators, we have to understand that, as the first
ones are the number of cases of a situation divided by the number of the population of that hospital’s
area, and the second ones are the number of cases of a situation divided by the number of cases
that entered in that hospital, Provider Level Indicators are much more reliable. We can easily get to
this conclusion if we remember that Central Hospitals do not only receive the cases of its
geographical area but also severe cases of all country.
In Non-Central Hospitals, there is not a level of specification as deep as in central ones. This fact can lead to
mistakes in the process of codification, what may benefit or even negatively affect the areas with no Central
Hospitals.
13
Central Hospitals
Once we do not have access to the name of each hospital, we first tried to make a connection
between the municipality where the hospital is placed in and its score in the ranking. However, the
positions are very spread - in the first ten places we have three hospitals from Lisboa, two from
Cascais and from Coimbra, one from Porto, Setúbal and Oeiras, what does not allow us to take
conclusions.
When dividing the hospitals in Non-University Hospitals, Traditional University Hospitals and
University Hospitals we realize that the results are extremely spread as well. However, it is observed
that most University Hospitals, traditional or not, occupy middle positions. This might be related to the
high number of new formed doctors, who do not have much experience.
Pediatric Hospitals occupy very low positions. This situation is probably caused by the fact that as
they have a very specific pediatric medical assistance, severe cases are more frequently transferred
for them, creating more high-risk situations.
Limitations
The used value, 50, as a minimal number of cases included in the denominator of each PDI was
chosen after analysing some similar studies done in the United States. However, we can not assure
this is the best value to use, once it may influence the results.
The data was not in the same format of the AHRQ’s software. Therefore, we could not use it to
calculate the PDI’s, which turned this calcule harder as SPSS had to be adopted.
Portuguese codification system may not be as rigid as it was desirable, which can lead to inaccurate
results. Some hospitals do not have the qualified staff to do that codification, so different hospitals
might have different codification results.
Conclusions
Due to the limitations discussed above, our study results may not correspond to the Portuguese
reality. It is necessary to improve and invest in our national codification system and in professionals’
formation.
Once Pediatric Quality Indicators is an evaluation system created by the United.States Department of
Health & Human Services, it may not be adequate to Portuguese Pediatric Services.
14
REFERENCES
[1] Drosler SE, Cools A, Kopfer T, Stausberg J. Are quality indicators derived from routine data
suitable for evaluating hospital performance? First results using the AHRQ patient safety indicators in
Germany. Z Arztl Fortbild Qualitatssich. 2007; 101 (1): 35-42.
[2] AHRQ: Agency for healthcare research and quality [Internet]. USA; Measures of Pediatric Health
Care Quality Based on Hospital Administrative Data, The Pediatric Quality Indicators.2007 [about 1
screen] Available from: http://www.qualityindicators.ahrq.gov/downloads/pdi/
[3] Kuhlthau K, Ferris TG, Iezzoni LI. Risk adjustment for pediatric quality indicators. Pediatrics. 2004
Jan;113(1 Pt 2):210-6
[4] Scanlon MC, Mistry KP, Jeffries HE. Determining pediatric intensive care unit quality
indicators for measuring pediatric intensive care unit safety. Pediatr Crit Care Med. 2007 Mar;
8[suppl]: S3-S10
[5] Mangione-Smith R, DeCristofaro AH, Setodji CM, Keesey J, Klein DJ, Adams JL, Schuster
MA, McGlynn EA. The quality of ambulatory care delivered to children in the United States. The New
England Journal of Medicine. 2007; 357:1515-23.
[6] M. A. Schuster, S. M. Asch, E. A. McGlynn, E. A. Kerr, A. M. Hardy and D. S.
Gifford.Development of a quality of care measurement system for children and adolescents.
Methodological considerations and comparisons with a system for adult women. Arch Pediatr
Adolesc Med 1997. 151: 1085-1092.
[7] Nawal Lutfiyya M, Bhat DK, Gandhi SR, Nguyen C, Weidenbacher-Hoper VL, Lipsky MS. A
comparison of quality of care indicators in urban acute care hospitals and rural critical access
hospitals in the United States. Int J Qual Health Care. 2007 Jun; 19 (3): 141-9.
[8] McDonald, K., Measures of Pediatric Health Care Quality Based on Hospital Administrative Data:
The Pediatric Quality Indicators, 2006 February 20. 32
[9] U.S. department of health and human services; AHRQ Quality Indicators Pediatric Quality
Measures
Clearinghouse
[internet],
USAgovernment;
2007,
March;
Available
from:
http://www.qualitymeasures.ahrq.gov/summary/summary.aspx?doc_id=10696
15
[10] U.S. department of health and human services; AHRQ Quality Indicators Pediatric Quality
Indicators Comparative Data for Provider Indicators [internet], USAgovernment; 2007, March;
Available from:
http://www.qualityindicators.ahrq.gov/downloads/pdi/pdi_provider_comparative_v31.pdf,
[11] Costa C, Lopes S. Avaliação do Desempenho dos Hospitais Públicos em Portugal Continental –
2005. ENSP, 2007 (www.ensp.unl.pt).
[12]. U.S. department of health and human services; AHRQ Quality Indicators Pediatric Quality
Indicators Comparative Data for Area Indicators [internet], USAgovernment; 2007, March; Available
from: http://www.qualityindicators.ahrq.gov/downloads/pdi/pdi_are_comparative_v31.pdf,
[13]. McDonald, K., Measures of Pediatric Health Care Quality Based on Hospital Administrative
Data: The Pediatric Quality Indicators, 2006 February 20. 90
16