Is the permanent pacemaker implant more efficient in level 1 hospital?

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Med Int ensiva. 2011;35(2):68−74
medicina intensiva
www.elsevier.es/ medint ensiva
ORIGINAL
Is the permanent pacemaker implant more eficient in level 1
hospital?
E. Moreno-Millán, a J.M. García-Torrecillas, b J. Villegas-del Ojo, a, * F. Prieto-Valderreya
Servicio de Medicina Int ensiva, Hospit al «Sant a Bárbara», Puert ollano, Spain
Servicio de Cuidados Crít icos y Urgencias, Complej o Hospit alario «Torrecárdenas», Almería, Spain
a
b
Received 12 April 2010; accept ed 6 July 2010
KEYWORDS
Pacemaker;
Management ;
Eficiency
Abstract
Obj ect ive: To det ermine if permanent pacemaker implant s (PPM) int ervent ions and change of
generator are more eficient in small hospitals.
Design: A cost -effect ive analysis and ret rospect ive, cross-sect ional and observat ional st udy of
diagnost ic relat ed groups (DRG).
Set t ing: The dat a was obt ained from t he nat ional Minimum Basic Dat a Set (MBDS) for t he year
2007 provided by the Health Ministry.
Pat i ent s: This includes t he t ot al number of pat ient s who required t reat ment in all nat ional
hospit als for 5 DRG: 115 - bradyarrhyt hmic complicat ion during t he acut e coronary syndrome,
heart failure or shock; 116 - symptomatic isolated conduction defects; 117 - revisions, but
without changing the battery, 118 - application of a new one, 549 - implementation or revision
but wit h serious complicat ions.
Principal variables of int erest : Demographic, clinical (number of secondary diagnoses (NSD) and
procedures (NP), mort alit y) and management (t ot al and preoperat ive lengt h of st ay (LOS),
access, discharge, hospital size), deining ineficient stays as those exceeding 2 days on the
average.
Result s: 23,154 episodes, 5.3% small hospitals. The comparative bivariate study between small
hospitals and the rest, not discriminated by DRG, showed a mean LOS of 7.87±8.78 days vs
11.01±12.95 (p=0.005, 95% CI for mean difference [0.17, 1.65]) and also lower than
preoperatively (3.62±6.14 vs. 4.22±6.68 days [p=0.015]) without greater comorbidity, as
measured by proxy through the NSD (5.23±2.88 vs 5.42±3.28 [p=0.055]) and NP as proxy of
diagnostic and therapeutic effort (3.79±2.50 vs 3.55±2.69 [p=0.002]). A total of 24.1% were
ineficient, there being an association with preoperative stay, NDS, NP and emergency access.
Conclusion: Pacemaker implantation and generator change in small hospitals is more eficient,
wit h int ernal consist ency by subgroups.
© 2010 Elsevier España, S.L. and SEMICYUC. All right s reserved.
*Corresponding aut hor.
E-mail address: [email protected] (J. Villegas-del Ojo).
0210-5691/ $ - see front mat t er © 2010 Elsevier España, S.L. and SEMICYUC. All right s reserved.
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Is the permanent pacemaker implant more eficient in level 1 hospital?
PALABRAS CLAVE
Marcapasos;
Gest ión;
Eiciencia
69
¿Es más eiciente el implante de marcapasos permanentes en hospitales de nivel I?
Resumen
Obj et ivo: Det erminar si el implant e de marcapasos permanent es (MPP) y cambio de generador
resultan más eicientes en hospitales pequeños.
Diseño: Análisis de cost eefect ividad. Est udio ret rospect ivo, t ransversal y observacional de cinco
GDR.
Ámbit o: Los dat os son procedent es del conj unt o mínimo básico de dat os (CMBD) nacional del
año 2007, facilitado por el Ministerio de Sanidad.
Pacient es: Son el t ot al de los pacient es que requirieron asist encia en algún hospit al nacional por
5 GRD: 115, complicación bradiarrít mica durant e la fase aguda de un síndrome coronario, insuiciencia cardíaca o shock; 116, trastorno de conducción sintomático aislado; 117, revisión pero
sin cambio de batería; 118, aplicación de una nueva, y 549, implantación o revisión pero con
complicaciones graves.
Variables de int erés principales: Se analizaron variables demográicas, clínicas (número de diagnósticos secundarios [NDS], de procedimientos [NP], mortalidad) y de gestión (estancia total y
preoperatoria [Epo], forma de acceso y alta, tamaño de hospital), deiniendo ineiciente una
est ancia superior 2 días a la media.
Result ados: 23.154 episodios (5,3% en hospitales < 200 camas). El estudio bivariado comparativo
entre hospitales pequeños y el resto, no discriminado por GDR, mostró estancia media 7,87 ±
11,01 días vs. 8,78 ± 12,95 (p = 0,005, IC 95% [0,17; 1,65]) y Epo 3,62 ± 6,14 vs. 4,22 ± 6,68 días
[p = 0,015]), sin mayor comorbilidad, medida como proxy por NDS (5,23 ± 2,88 vs. 5,42 ± 3,28
[p = 0,055]); y NP como proxy de esfuerzo diagnóstico-terapéutico (3,79 ± 2,50 vs. 3,55 ± 2,69
[p = 0,002]). 24,1% fueron ineicientes, encontrándose asociación con Epo, NDS, NP y acceso
urgent e.
Conclusiones: La implant ación de marcapasos y cambio de generador en hospit ales pequeños es
más eiciente, con consistencia interna por subgrupos.
© 2010 Elsevier España, S.L. y SEMICYUC. Todos los derechos reservados.
Introduction
The Spanish National Catalog of Hospitals, created within
t he set t ing of Law 16/ 2003, relat ing t o Cohesion and Qualit y
of the National Healthcare System (Si st ema Naci onal de
Sal ud, SNS), classif ies t he cent ers of t he Spanish net work
according t o t heir care profile and funct ional and st ruct ural
dependencies, respect ivel y, but al so cont empl at es f our
models in relation to the existing capacity or number of
beds, and specialized resources. 1 Nevert heless, t here is a
generalized t endency t o classify hospit al cent ers according
t o t heir geodemographic set t ing and services prof ile int o
t hree levels (I, II and III) – level I cent ers being ident ified as
dist rict hospit als of f ering basic specialt ies, and habit ually
possessing fewer t han 200 beds.
The greater complexity of the patient series seen in higher
level hospit als t ends t o generat e management problems,
compl i cat i ng t he act i vi t i es cent ered around one same
healthcare process. In this context, one of the tools used in
measuring t he healt hcare product is hospit al st ay – generally
evaluated as a proxy or surrogate variable of its direct cost.
Comparing st ay relat ed t o cert ain healt hcare product s t hus
implies comparison of t he resources used in elaborat ing
t hem. The management plan of an organizat ion is t echnically
ef f i ci ent when based on a seri es of i nput s i t i s abl e t o
generate a maximum output, or output is generated in less
t ime. A product ive act ivit y in t urn proves inefficient when
t he amount used in some input can be reduced wit hout
impairment of t he resul t / out come, or durat ion of t he
process.
Primary permanent pacemaker (PPM) implant at ion and
replacement of t he generat or are t wo common t echniques
in hospit als, administ rat ively classif ied int o 5 diagnosisr el at ed gr oups ( DRG) : 115, due t o br adyar r hyt hmi c
compl i cat i ons dur i ng t he acut e phase of a cor onar y
syndrome, heart f ailure or shock; 116, due t o an isolat ed
symptomatic conduction disorder; 117, due to revision
wit hout bat t ery replacement ; 118, wit h applicat ion of a
new battery; and 549, due to implantation or revision, but
involving serious complicat ions. 2
The Spanish public hospit al net work is prepared t o at t end
pat ient s requiring emergency and t emporary placement of
an endocavitary electrocatheter equipped with an external
generat or, but not al l hospi t al s i mpl ant or revi se PPM.
Alt hough in Spain t here are different dat abases t hat cont rol
t hese int ervent ions (Pacemaker Regist ries of t he Spanish
Societ y of Cardiology (SEC) and of t he Spanish Societ y of
Int ensive and Crit ical Care Medicine and Coronary Unit s
(SEMICYUC), respect ively), t hey ref er dif f erent number of
i mpl ant s and t her ef or e di f f er ent r at es per mi l l i on
inhabit ant s. 3-5 The Spanish Nat ional Pacemaker Dat abase
(BNDM) came int o operat ion in 1990, 6 t hough t he regist ry of
compar at i ve par amet er s began i n 1993, t hanks t o
int roduct ion of t he “ European carrier pat ient card” , of
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70
obligat e implement at ion. 7,8 Following t he recommendat ions
of t he European Societ y of Cardiology, 9 t here are differences
among Spanish hospit als, depending on t heir size and t he
l evel s of ser vi ces of f er ed – wi t h var i abi l i t y i n t hei r
management , according t o t he ment ioned regist ries. 3-6
We have oft en asked ourselves why PPM are not implant ed
and revised in all Spanish hospit als, regardless of t heir level,
consi der i ng of cour se t he avai l abi l i t y of pr of essi onal s
f amiliarized wit h t he t echnique and of t he inf rast ruct ure
needed to offer a safe and quality product. In this context,
we have raised t he quest ion of whet her t ransfer t o anot her
cent er for pacemaker implant at ion implies or does not imply
unnecessary risks and delays for t he pat ient s, inconveniences
for t heir relat ives, and cost increment s based fundament ally
on t he prolongat ion of st ay, bet ween-hospit al t ransport and
expenses derived from travel of the accompanying persons.
There are t wo obj ect ives in t he present st udy: on one
hand, t o at t empt t o answer t he above quest i ons as an
el ement f or r ef l ect i on and t hought among cl i ni ci ans,
administ rat ors and healt hcare policy makers; and on t he
ot her, t o analyze pract ices in primary PPM implant at ion and
revision in relat ion t o t he t ype of hospit al involved, classified
into two groups (H1: <200 beds, and RH: rest of hospitals) seeking possible differences in cert ain management (mean
(Sm) and preoperat ive lengt h of st ay (Spo) (LOS) and need
f or t r ansf er ) and cl i ni cal i ndi cat or s (compl i cat i ons,
comor bi di t y and mor t al i t y) , accor di ng t o pat i ent
demographic fact ors (age and gender).
Methods
The informat ion was obt ained from t he Minimum Basic Dat a
Set (MBDS) of the Spanish Ministry of Health for the year
2007, facilitated by the Healthcare Information Institute,10
and select ing t he cases classif ied as DRG 115 t o 118 and
549, with the exclusion of DRG 849 to 851 (implantation of
defibrillat ors and resynchronizers). The coding of diagnoses
and procedures was carried out based on t he Int ernat ional
Classificat ion of Diseases 9t h Edit ion – Clinical Modificat ions
(ICD-9-CM), while t he grouping of discharges was based on
t he DRG in it s version 21. Using t his informat ion we designed
a ret rospect ive, cross-sect ional observat ional st udy wit h an
inferent ial component .
The study variables were patient age (expressed in years
and recorded at t he t ime of admission), Sm and Spo, gender,
t ype of admission (emergency or programmed), t ype of
discharge (home, t ransf er, deat h), number and t ype of
secondary diagnoses at discharge (NSD), number of procedures
carried out (NP), efficiency of admission and hospit al level. A
stay in excess of two days of the average for the DRG involved
was regarded as inefficient, since on selecting the extreme
cases based on the formula T2=Q3+1.5* (Q3–Q1)(where Q are
t he quart iles and T2 t he st ay cut off value for t hese cases),
the maximum length of stay (LOS) to be considered was 22
days, and t he analysis of t he no out liers sample showed
percent iles 20, 25 and 30 t o comprise st ays of under t wo
days. As a result, those cases in excess of this value were
regarded as inef f icient , f ol l owing consensus among t he
aut hors in relat ion t o t he cut off value.
In a first phase we carried out a descript ive analysis of t he
var i abl es cont ai ned i n t he MBDS, empl oyi ng t he usual
E. Moreno-Millán et al
posit ion and dispersion measures (mean, mode and median),
w i t h t hei r r espect i ve st andar d devi at i ons, f or t he
quant it at ive variables, and f requencies, percent ages and
dist ribut ion t ables in t he case of t he qualit at ive variables.
The Shapiro-Wilks t est was used t o det ermine adhesion of
t he variables t o a normal dist ribut ion. In t he second st udy
phase (bivariat e analysis), t he quant it at ive variables were
compared using t he St udent t -t est f or independent dat a.
Comparisons bet ween nominal variables, dist ribut ed int o
more t han t wo cat egories, were carried out using analysis of
variance (ANOVA) with the Tukey post hoc maximum
signif icant dif f erence t est . In t he case of t he cat egorical
vari abl es, we used t he chi -squared t est , no cont i nui t y
cor r ect i ons bei ng r equi r ed. Last l y, f or eval uat i ng t he
independent associat ion bet ween ef f icient st ay and t he
different st udy covariables, we const ruct ed a binary logist ic
regression model, with the Hosmer-Lemeshow test to check
goodness of fit – t he result s being int erpret ed as odds rat ios
(OR) wit h t heir respect ive conf idence int erval s (CI). As
independent variables in t he model, we int roduced t hose
t hat proved signif icant in t he bivariat e model, along wit h
t hose which according t o t he lit erat ure were considered t o
be possibly associat ed t o t he dependent variable. The SPSS
ver si on 15. 0 st at i st i cal package was used, accept i ng
statistical significance for p<0.05.
Results
A total of 23,154 episodes were studied (1% of the total
2,232,568 individuals over 45 years of age). The distribution
according t o hospit al group is shown in Figure 1, where it is
seen that only 5.3% of all PPM are implanted in H1 centers.
Tabl e 1 shows t he cl inical and administ rat ive indicat ors
anal yzed ( Sm, Spo, NSD, NP, t ype of admi ssi on and
discharge), as well as some of t he demographic variables
(mean age, percentage patients over 70 years of age,
gender), according t o t he designat ed DRG and gl obal l y
corresponding t o PPM implant at ion. Of not e is t he higher
H1 = 5.38%
Rest of hospitals = 94.62%
Figure 1 Di st r i but i on of t he per manent pacemaker
implant at ion episodes according t o hospit al size.
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Is the permanent pacemaker implant more eficient in level 1 hospital?
71
Table 1 Clinical, demographic and administrative indicators of the DRG in reference to pacemaker implantation, Spain 2007
Episodes (N and %)
Age (x ± SD)
> 70 years (%)
Males (%)
Stay (x ± SD)
Preop. stay (x ± SD)
Emergency (%)
H1 (%)
NSD (x ± SD)
NP (x ± SD)
Death (per 1000)
Transfer (per 1000)
Relative impact
Total
115
116
117
118
549
23,154 (100)
75.55 (9.64)
813 (3,5)
72.21 (10.13)
61.8
68.9
9.77 (9.74)
5.25 (7.04)
55.6
3.3
6.39 (3.27)
3.52 (2.70)
15.0
10.0
4.6014
14,432 (62,33)
76.66 (8.14)
79.0
57.6
6.26 (5.81)
3.77 (4.57)
66.8
5.7
4.99 (2.82)
3.49 (1.89)
4.0
9.0
3.6694
1068 (4,61)
75.26 (9.44)
73.2
59.3
5.62 (6.34)
2.65 (4.31)
47.6
8.7
4.70 (3.11)
2.09 (1.73)
18.0
18.0
2.1114
3280 (14,16)
77.31 (9.51)
80.6
55.6
3.26 (3.68)
1.58 (2.28)
19.7
3.9
3.42 (2.50)
1.66 (1.25)
5.0
5.0
2.0597
3561 (15,38)
70.29 (10.42)
55.3
77.5
24.51 (24.53)
7.63 (11.49)
70.8
4.3
8.94 (3.03)
6.03 (4.26)
268.0
42.0
6.9436
60.8
8.74 (12.85)
4.17 (6.64)
59.5
5.3
5.42 (3.28)
3.55 (2.69)
45.0
14.0
H1 = level I hospital; NSD = number of secondary diagnoses; NP = number of procedures; Healthcare Information Institute, Ministry of
Health, 2007.
(x ± SD) = mean and standard deviation.
incidence (62.33%) of DRG 116, related to pure conduction
disorders wit hout complicat ions, seen in older individuals,
wit h a predominance of males and of emergency admissions.
In turn, DRG 549 (15.38% of the total) is found mainly in
males (77.5%), with very long Sm and Spo (24.51 and 7.63,
respect ively) and import ant comorbidit y (8. 95 secondary
diagnoses), diagnost ic-t herapeut ic int ervent ions (6.03) and
mort alit y (268.0 per t housand).
In the comparative bivariate analysis between H1 centers
and the rest of hospitals corresponding to higher levels (RH),
wi t hout di scri mi nat i on accordi ng t o t ype of DRG, PPM
implantation was seen to require 7.87±11.01 days versus
8.78±12.95 days in RH (p=0.005, 95%CI [0.17; 1,65]), and
Spo was also shorter in H1 than in RH: 3.62±6.14 versus
4.22±6.68 days (p=0.015). This shows that on taking both Sm
and Spo as proxy or surrogate variables of efficiency, the H1
cent ers generat ed f ewer st ays, and t hus woul d be more
efficient (Table 2). In assessing whether the complexity of
t he pat ient s was similar (based on t he evaluat ion of NSD and
NP), we f ound t hat t her e was no cl ear l y si gni f i cant
difference (p=0.055) in NSD (5.23±2.88 versus 5.42±3.28) –
in contrast to NP (3.79±2.50 versus 3.55±2.69) (p=0.002).
Therefore, comorbidity among the patients in H1 centers
was no different from that seen in patients admitted to RH,
Table 2 Differences bet ween st ay and preoperat ive st ay,
NSD and NP bet ween level I hospit als and t he rest
Stay
Preop. stay
NSD
NP
H1
RH
p
7.87 ± 11.01
3.61 ± 6.13
5.23 ± 2.88
3.79 ± 2.50
8.78 ± 12.95
4.22 ± 6.68
5.42 ± 3.28
3.55 ± 2.69
0.005
0.015
0.055
0.002
H1: level I, RH: rest, NSD: number of secondary diagnoses, NP:
number of procedures. Source: Healthcare Information Institute,
Ministry of Health, 2007.
t hough t her e was a cl ear t endency t o per f or m mor e
diagnost ic-t herapeut ic int ervent ions (Table 2).
Table 3 shows t he principal indicat ors evaluat ed, according
t o t he t ype of hospi t al cent er and f or each DRG. The
st rat if ied analysis shown in t he t able yielded st at ist ically
significant differences (p<0.001= in all cases and for all
variables, except mortality (nonsignificant [NS]).
Table 4 shows the variables found to be associated to
inef f iciency, according t o t he devel oped binary l ogist ic
regression model; in this context the probability was seen to
increase 1.38-fold for every Spo day elapsed, 1.098-fold for
ever y new di agnosi s, and 1. 069- f ol d f or ever y new
procedure. In addition, inefficiency proved 1.7 times more
likely when access t ook place on an emergency basis and
1.4 times more likely when in the RH. Globally, 24.1% of all
cases met t he crit erion of inefficiency.
Table 5 report s t he indicat ors of t he pat ient s discharged
home (93.4%) and of those who died (4.5%); statistically
significant differences were observed (p=0.001), the values
corresponding t o Sm, Spo, NSD and NP being lower among
t he former.
Discussion
Pat ient cl assif icat ion based on diagnosis-rel at ed groups
(DRG) is carried out t o define clinically comparable groups,
and is very useful for evaluat ing and measuring t he qualit y
of t he r esour ces used i n t he management of a gi ven
healthcare process. In this context, comparisons can be
made of t he effect iveness and efficiency (benchmarking) of
a concret e clinical service or int ervent ion, est ablishing in
which cases resource consumption exceeds the established
ref erence or norm, wit h a view t o int roducing correct ive
measures. 11
DRG are based on t he grouping of processes wit h similar
uses and costs, evaluated through proxy or surrogate
variables (st ay and relat ive impact ) used as predict ors of
consumpt ion, t hough t his model does not document t he
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72
Table 3
E. Moreno-Millán et al
Principal indicators evaluated, according to type of hospital and DRG, Spain 2007
DRG
Indicator
H1
RH
p
115
Stay
Preop. stay
NSD
NP
Mort alit y
9.69 ± 9.76
5.21 ± 6.42
4.93 ± 2.54
3.98 ± 2.31
10.5
12.04 ± 8.86
5.25 ± 7.08
4.99 ± 2.83
3.46 ± 1.86
10.8
0.001
NS
NS
0.01
NS
116
Stay
Preop. stay
NSD
NP
Mortality
5.87 ± 5.62
2.75 ± 3.67
4.93 ± 2.54
3.98 ± 2.31
10.7
6.29 ± 5.82
3.86 ± 4.62
4.98 ± 2.83
3.46 ± 1.86
11.8
0.01
0.001
NS
0.001
0.01
117
Stay
Preop. stay
NSD
NP
Mortality
3.77 ± 3.97
1.49 ± 2.65
4.16 ± 3.22
2.17 ± 1.73
10.3
5.79 ± 6.50
2.82 ± 4.48
4.76 ± 3.11
2.09 ± 1.73
10.7
0.001
0.001
NS
NS
NS
118
Stay
Preop. stay
NSD
NP
Mort alit y
3.19 ± 3.58
1.53 ± 2.14
3.86 ± 2.51
2.73 ± 1.84
10.5
5.09 ± 5.15
3.26 ± 3.44
3.42 ± 2.50
1.63 ± 1.21
10.9
0.001
0.01
0.05
0.001
NS
549
Stay
Preop. stay
NSD
NP
Mort alit y
22.58 ± 22.27
7.51 ± 11.42
8.33 ± 2.65
4.48 ± 3.17
23.6
24.59 ± 24.32
10.17 ± 12.55
8.94 ± 3.03
6.09 ± 4.28
19.5
NS
0.04
0.01
0.001
0.05
Preop. stay: preoperative stay, NSD: number of secondary diagnoses; NP: number of procedures; Mortality (per 1000); Healthcare
Information Institute, Ministry of Health, 2007.
Table 4
Variables associated to pacemaker implantation ineficiency, Spain 2007
Age
Preop. stay
NSD
NP
Emergency adm.
H1
Constant
B
SE
0.000
0.321
0.093
0.066
0.578
0.335
−3.846
0.003
0.008
0.010
0.011
0.067
0.066
0.255
Wald
0.004
1535.046
91.920
34.053
73.970
25.922
228.153
df
Sign.
Exp (B)
1
1
1
1
1
1
1
0.951
0.001
0.001
0.001
0.001
0.001
0.001
1.000
1.378
1.098
1.069
1.782
1.398
0.021
B: estimated parameter (ineficient implantation; Preop. stay: preoperative stay; SE: standard error; Wald: regression method used; df:
degrees of freedom; Emergency adm.: emergency admission, H1: level I hospitals; OR: odds ratio; Sign: statistical signiicance; NSD:
number of secondary diagnoses, NP: number of procedures; Healthcare Information Institute, Ministry of Health, 2007.
Table 5
Survivors
Deceased
p
Differences in age, st ay, preoperat ive st ay, NSD and NP bet ween t he survivors and t hose pat ient s who died
Number
Age
St ay
Preop. st ay
NSD
NP
22,118
1036
—
75.65 ± 9.60
73.30 ± 10.12
0.01
8.40 ± 12.29
15.88 ± 20.36
0.001
4.05 ± 6.38
6.45 ± 10.04
0.001
5.23 ± 3.16
9.21 ± 3.13
0.001
3.41 ± 2.48
6.71 ± 4.30
0.001
Preop. stay: preoperative stay; NSD: number of secondary diagnoses, NP: number of procedures; Healthcare Information Institute,
Ministry of Health, 2007.
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Is the permanent pacemaker implant more eficient in level 1 hospital?
existence of unnecessary days of hospital stay, which should
be ident if ied in order t o opt imize qualit y and ef f iciency.
The st andards of st ay per process do not det ect inadequat e
use in t he episode, wit h cases t hat clearly differ in t erms of
resource ut ilizat ion – reaching different cost s or giving rise
t o longer st ay; as a result , t his variable may be t aken t o
represent a surrogat e of t hese cost s (at least of t he direct
cost s), wit h lengt h of st ay (LOS) being t he MBDS indicat or
that best explains its important internal variability.12,13
In const ruct ing DRG, use is made of t he principal diagnosis,
t he secondary diagnoses and t he procedures employed –
t hereby measuring t he complicat ions (during st ay) and t he
comorbidit ies (from admission) t hat influence t he durat ion
of st ay, sur gi cal out comes, t he pr esent at i on of added
comorbidit y, end funct ional st at e and qualit y of life, hospit al
readmissions and mortality. Complexity is represented by
t he DRG i t sel f , t hr ough r el at i ve i mpact and st ay. The
complications are explained by the NSD and NP, and the
socioeconomic and demographic charact erist ics are assumed
on t he basi s of pat i ent age and gender, w hi l e t he
charact erist ics of t he heal t hcare process are eval uat ed
usi ng speci f i c var i abl es such as t he t ype of admi ssi on
(emergency or programmed) and readmi ssi ons. 12, 13 The
greatest complexity of the patient circumstances would
correspond t o an increase in Sm – hence t he import ance of
its evaluation and measurement in the context of a given
process. Furt hermore, t he case of surgical int ervent ions, it
is import ant t o assess bot h global Sm and Spo (t he lat t er
clearly being relat ed t o t he former). 14
Resour ce assi gnat i on t o a gi ven act i vi t y i mpl i es t he
opport unit y cost of not being able t o use such resources in
ot her act ivit ies. This j ust ifies t he need t o offer services wit h
effect iveness and efficiency, consuming only t he minimum
resources necessary. In t his sense, t he use of indicat ors as a
management t ool proves essent ial (relat ing t o process or
out come), offering great advant ages for bot h administ rat ors
and cl i ni cal super vi sor s. Thus, t he pr ocess i ndi cat or
measures efficiency by comparing it wit h a st andard, while
t he result s or out come indicat or measures t he impact upon
pat ient healt h. 15,16
Technical inefficiency is generally due to excessive input
use, in t hat assignat ion t akes place in incorrect proport ions.
One of t he indicat ors of t he former is t he analysis of rat ios
which, while having import ant limit at ions part icularly at
hospi t al l evel (demogr aphi c f act or s such as agi ng, or
geographical f act ors such as cent er locat ion), remains an
adequat e cont rol mechanism. 15,16
We have seen t hat our resul t s, obt ai ned t hrough t he
BMDS10 are concordant wit h t hose reflect ed by t he BNDM6:
thus, the distribution among primary implantations (74.61%)
and replacements (25.39%), and the mean ages (76.12 years
for the former and 76.96 for the latter) of the mentioned
regist ry are very similar t o our own dist ribut ion: act ivit ies
(77.81% implants, 22.19% replacements) and ages (76.66
and 77.31 years), respectively.
According to the BNDM, 75.54% of the interventions take
place in the 70-89 years age interval, and 5.17% in patients
over 90 years of age. Our resul t s show t he f ormer age
interval to account for 75.40% of all the interventions, while
only 3.58% involve patients over 90 years of age.6 The PPM
rate according to the BNDM is 680.4 per million inhabitants,
versus 526. 6 in our st udy, t hough wit hout evaluat ing t he
73
pacemakers implanted in individuals under 45 years of age.6
In our ser i es t he DRG showi ng t he l ar gest number of
compl icat ions and comorbidit ies – and t heref ore higher
levels of complexity and mortality – were DRG 115 (which is
l ogi cal , si nce t hese ar e subj ect s wi t h acut e cor onar y
syndr ome, hear t f ai l ur e or shock, accompani ed by
conduction disorders) and DRG 549, which concentrates the
complicated PPM with comorbidities. Since DRG 549
compri ses i mpl ant at i ons and revi si ons accompani ed by
major complications, it exhibits more complex indicators
and has a greater relative impact (6.9436) and higher
mortality (268.0 per thousand). Both DRG (115 and 549)
likewise show inefficiency values (30.8% and 32.7%,
respectively) in excess of the average (24.1%). The H1
centers only cover 3.3% (115) and 5.7% (116) of the implants
and 8.7% (117) and 3.9% (118) of the replacements. This
shows t heir scant act ivit y in t his product ion area, and should
cause administ rat ors and healt hcare supervisors t o reflect
upon the situation. Curiously, the H1 centers concentrate
only 5.3% of the PPM implantation activity, but while DRG
117 (control without replacement) reaches 8.7%, these
hospitals only place 3.9% of the new generators.
With the exception of 549, all the DRG analyzed show
significantly shorter Sm and Spo values in the H1 than in the
rest of the hospitals (RH), with practically equal NSD in both
cases. These result s indicat e t hat primary implant at ion in
level I cent ers is more efficient , despit e similar comorbidit y,
and t hat we could avoid t he need f or t ransf er t o anot her
hospit al – wit h t he consequent delay in int ervent ion, which
coul d cause ser i ous compl i cat i ons, di scomf or t f or t he
pat ient s and t heir relat ives and, of course, great er cost s for
one same activity. Generator replacements (DRG 117 and
118) of f er si mi l ar par amet er s, and ar e l i kewi se mor e
efficient in t hese level I cent ers.
Ment ion also should be made of where implant at ions and
revisions are t o be made. According t o t he lit erat ure, t he
differences bet ween t he availabilit y of a surgical st ruct ure
or of hemodynamics and arrhyt hmia unit s dedicat ed t o
t hese act ivit ies on a mult idisciplinary basis are very few. 17-19
Al t hough t he l i t er at ur e ment i ons t he possi bi l i t y of
performing these interventions in the context of ambulatory
maj or sur ger y pr ogr ams, t he f act i s t hat t her e ar e no
di spar i t i es i n t er ms of cl i ni cal r esul t s or mor bi di t ymort alit y. 20-24
There are evident l imit at ions in our st udy. First l y, it s
design as an observat ional st udy makes f ut ure analyt ical
explorations necessary. Likewise, information is lacking in
the MBDS on the infrastructure possibilities of H1 centers:
the existence of an operating room or specific room for
implant at ion, surgical pressure, and adequat e personnel for
addressi ng t he work l oad (consul t at i on, i mpl ant at i on,
post operat ive period). On t he ot her hand, t he use of DRG as
a t ool for t he measurement of act ivit ies implies inefficiency
t ransfer t o all t he implicat ed healt hcare unit s, not only t o
t he unit responsible for pacemaker implant at ion.
Conclusions
According t o our st udy, organizat ional st rat egies should be
impulsed in level I hospit als t o manage PPM implant at ion
and generat or replacement (wit h t he corresponding follow-
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74
up) – perf orming bot h t echniques in all pat ient s who need
t hem, independent ly of t he hospit al model involved, and
f ocusi ng mor e on t he t echni cal qual i f i cat i on and
preparat ion of t he prof essionals in t he cent er. This would
cont ribut e t o avoid delays and t ransfers t hat are absolut ely
unnecessary when t he necessary specialized resources and
st ruct ures for ensuring safet y and qualit y int ervent ion are
available.
These dat a give rise t o a very int erest ing hypot hesis which
never t hel ess cannot be conf i r med by means of an
observational study such as our own: the existence of a
causal relat ionship bet ween t he efficiency variables and t he
f act ors st udied. Nevert heless, our f indings reinf orce t he
existence of greater efficiency in relation to this process in
t he smal l er hospi t al s, wi t h i nt er nal consi st ency by
subgroups. The comparison of PPM implant at ion in pat ient
cohort s of similar comorbidit y bet ween hospit als of different
l evel s remai ns as an obj ect i ve f or f ut ure st udi es of an
analyt ical nat ure.
Funding
The work has not been f inanced by any public or privat e
inst it ut ion.
Conlict of interest
The aut hors declare no conflict of int erest .
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