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Pilot analysis of pres­sure ulcers –  nationwide data from central adverse event report­­ing system


Pilotní analýza počtu dekubitů –  celostátní data v centrálním systému hlášení nežádoucích událostí

Cíl: Analyzovat národní data o prevalenci hlášených dekubitálních lézích z centrálního systému hlášení nežádoucích událostí u poskytovatelů lůžkové péče v ČR za rok 2018.

Soubor a metodika: V rámci centrálního systému hlášení nežádoucích událostí byla analyzována data o počtu dekubitálních lézí za rok 2018 od 408 poskytovatelů lůžkové péče. Statistická analýza dat byla provedena pomocí SPSS (IBM Corp., Armonk, NY, USA) verze 22 na hladině významnosti p ≤ 0,05.

Výsledky: Dekubity jsou v centrálním systému hlášeny jako nejčastější nežádoucí události (celkový počet sledovaných hospitalizovaných pa­cientů za rok 2018 byl 2 693 008). Počty hlášených událostí se liší u jednotlivých typů poskytovatelů zdravotních služeb. Místo vzniku dekubitů sleduje 249 poskytovatelů péče, u nichž bylo nahlášeno celkem 45 994 nežádoucích událostí dekubitus (z nich 36,7 % vzniklých za hospitalizace a 63,3 % před hospitalizací). Ověřeny byly rozdíly v nahlášených počtech nežádoucích událostí dekubitus v závislosti na počtu zdravotnického personálu na počet pa­cientů, počtu pa­cientů na lůžko a podílu zdravotnického personálu na lůžko.

Závěr: Dekubity jsou hlášeny jako nejčastější nežádoucí události v centrálním systému hlášení, který je povin­ný pro všechny poskytovatele lůžkové péče v ČR. Hlášení je realizováno na základě jednotné metodiky.

Klíčová slova:

dekubitus – nežádoucí událost – prevalence – sledování – centrální systém hlášení


Authors: A. Pokorná 1;  M. Pospíšil 1,2;  J. Mužík 2,3;  J. Kučerová 2;  V. Štrombachová 2;  D. Dolanová 1,2;  P. Búřilová 1,2;  L. Cetlová 4
Authors place of work: Department of Nursing and Midwifery, Faculty od Medicine, Masaryk University, Brno 1;  Institute of Health Information and Statistics, Department of quality of care evaluation, Prague 2;  Institute of Biostatistics and Analyses, Facolty of Medicine, Masaryk University, Brno 3;  Department of Healthcare studies, College of Polytechnics, Jihlava 4
Published in the journal: Cesk Slov Neurol N 2019; 82(Supplementum 1): 8-14
Category: Original Paper
doi: https://doi.org/10.14735/amcsnn2019S8

Summary

Aim: The aim is to analyse nationwide data from the Central Adverse Event Report­­ing System (CAERS) with special attention to pres­sure ulcers (PUs) in inpatient healthcare settings for 2018.

Patients and methods: Data col­lected in CAERs about reported PUs for 2018 were analysed in 408 inpatient healthcare settings. Statistical data analysis was performed us­­ing SPSS (IBM Corp., Armonk, NY, USA) version 22.0 at a significance level of P ≤ 0.05.

Results: PUs are reported as the most com­mon adverse events (total number of monitored hospitalized patients in 2018 was 2,693,008). The number of reported PUs varies depend­­ing on the type of hospitals. The place of origin /  formation of PUs was monitored by 249 healthcare facilities who reported a total of 45,994 adverse events –  PU (of which 36.7% were originated dur­­ing hospitalisation period and 63.3% prior to hospitalization). The dif­ferences in prevalence of PUs were verified in relation to the number of health workers per patient, number of patients per bed and staff /  bed ratio.

Conclusion: PUs are reported as the most com­mon adverse events in central adverse event report­­ing system in which report­­ing is obligatory for all inpatient healthcare settings in the Czech Republic. Report­­ing is based on uniform methodology.

Keywords:

prevalence – pressure ulcer – adverse event – monitoring – central reporting system

Introduction

The pos­sibility of monitor­­ing of the occur­rence of pres­sure ulcers (PUs) in patients is an important is­sue, but neither in the Czech Republic nor international­ly exists any uniform methodology for neces­sary data col­lect­­ing that would suf­ficiently help monitor patients with PU [1]. It is well known that prevalence of PUs is an established quality indicator in health care in many countries [2]. It is also general­ly known that monitor­­ing of PUs (prevalence and incidence) and especial­ly its methodology for data col­lections vary at a national and international level. “Non-medical healthcare profes­sionals form the bulk of the clinical healthcare workforce and play a crucial role in all health service delivery systems [1] and they could also influence accuracy of appropriate preventative measures and report­­ing of pos­sible adverse events –  PUs” [1]. The quality of care could be influenced by the level of knowledge of carers as the process of knowledge translation was described as slow as well as translation of research findings into practice [3,4]. We do hope that it is not true any­more also in the field of PUs thanks to international­ly published guidelines which are be­­ing implement­­ing in clinical practice. Remain­­ing chal­lenge is the need for clear and user-friendly monitor­­ing system for PUs monitoring [1,5]. The lack of national guidelines and uniform methodology for mea­surement and data col­lection, makes shar­­ing and compar­­ing incidence, or prevalence of PUs (nationwide or at the EU level) simply not feasible. “In clinical settings without any systematic and validated PU registration system, estimat­­ing the incidence and prevalence of PUs, will mostly prove an academic and time-consum­­ing exercise, and will lead to imprecise estimations” [6]. As PUs are still considered as adverse events (which is not always true) there was prepared uniform methodology for PUs monitor­­ing on national level verified in four years project [7] and final­ly implemented as a part of Central Adverse Event Reporting System (CAERS) [8] for nationwide data col­lection. In our contribution we are present­­ing data col­lected in the first nationwide yearly data col­lection of adverse events from all inpatient healthcare settings in the Czech Republic with special attention to the PUs reporting.

Methods

The data col­lection was car­ried out in inpatient health care settings in the Czech Republic (N = 418) accord­­ing the cur­rent legislation. Data for the year 2018 were submitted through the special system managed and control­led by the Institute of Health Information and Statistics of the Czech Republic (IHIS CR) in May 2019. The col­lected data were aggregated and anonymised. Main categorization was based on the type of the healthcare institution (A –  faculty and large hospitals; B –  other hospitals of acute care; S –  specialised hospitals/ centres; P –  psychiatric /  mental health hospitals; N –  long term care (LTC); L –  spas /  health resorts /  medical centres and K –  infant homes). Cate­gorisation of hospitals was based on Czech DRG (dia­gnoses related groups) methodolo­gy. The data were col­lected in the given year (2018) in this form: prevalence of reported PUs as adverse events, number of patients over 65 years, number of patients at risk of PUs, number of bed side non-medical health workers (mainly nurses), number of beds and some facilities were able to report also place of origin /  formation of PUs. Statistical analysis of data was performed in SPSS (IBM Corp., Armonk, NY, USA) at a significance level of P ≤ 0.05.

Results and discus­sion

In total 408 inpatient facilities were included in the general data analyses. The total number of patients monitored in 2018 in each type of inpatient facility is presented in Tab. 1. Subsequent events were then recalculated for these total patient numbers for rela­tive comparison. For the analyses of PUs reporting, the category K –  infant homes were excluded as there were no PUs reported. PUs were reported as adverse events in all other included inpatient facilities and they were the most often reported events (Fig. 1, 2). The figure one shows the total absolute number of reported adverse events (AEs). Higher incidence numbers are reported by inpatient providers with a higher total number of patients. The figure two shows the relative frequency of AEs –  the incidence of reported AEs per 1,000 patients in the report­­ing period. This figure tel­ls how much of AEs would be recorded if 1,000 patients would be treated with the inpatient facility, al­low­­ing comparison of dif­ferently sized hospitals /  inpatient facilities. We could see while recalculat­­ing the number of reported PUs per thousand patients, the highest report­­ing rate was noticeable in the category N –  long term care. Interest­­ing information was found when we performed detailed analysis and the as­ses­sment of PUs site of formation/ origin (Fig. 3). The proportion of PUs, depend­­ing on whether they were formatted/ originated in a given facility or outside the facility, varies between hospital categories. The largest proportion of PUs reported as occur­r­­ing in a given facility is in the categories S –  specialized hospitals and P –  psychiatric /  mental health hospitals, the smal­lest in the cate­gory L –  spas and health resorts. Only hospitals in which monitor PUs formatted in a given hospital and outside the hospital (N = 249) were included in detailed analysis. The occur­rence of reported PUs is directly related to the proportion of patients at risk of PU. The risk also increases among older patients and those who, for any reason, stay in hospital for a longer period of time [9,10]. The analysed data can be used for further stratification and comparison of the occur­rence of PUs between the inpatient facilities (proper de-anonymized data of particular healthcare providers were pas­sed on to the authorized persons in the given hospital to evaluate proper preventative measures). The highest proportion of patients at risk of PUs was presumably in category N –  long term care (57.8%) (Tab. 2). Though, it is important to highlight there were only 44 hospitals out of 97 in this category which reported place of PU’s origin/ formation.

Tab. 1. Submitted data for 2018 (type of inpatient facilities and number of monitored patients).
Submitted data for 2018 (type of inpatient facilities and number of monitored patients).
*under category B, the original categories of hospitals B – regional, county hospital; C – middle size hospitals and D – small hospitals are combined AE – adverse event; PU – pressure ulcer

Fig. 1. Comparison of occurrence No. of reported AEs by category of inpatient facilities/hospitals for the 2018. AE – adverse event
Obr. 1. Srovnání absolutního počtu hlášení nežádoucích událostí dle kategorií zdravotnických zařízení/nemocnic v roce 2018. AE – nežádoucí událost
Comparison of occurrence No. of reported AEs by category of inpatient facilities/hospitals for the 2018.
AE – adverse event<br>
Obr. 1. Srovnání absolutního počtu hlášení nežádoucích událostí dle kategorií zdravotnických zařízení/nemocnic v roce 2018.
AE – nežádoucí událost

Fig. 2. Comparison of occurrence No. of reported AEs by category of inpatient facilities/hospitals for the 2018 – per 1,000 patients.
AE – adverse event
Obr. 2. Srovnání počtu hlášení nežádoucích událostí dle kategorií zdravotnických zařízení/nemocnic v roce 2018 – přepočet na 1 000 pacientů.
AE – nežádoucí událost
Comparison of occurrence No. of reported AEs by category of inpatient facilities/hospitals for the 2018 – per 1,000 patients.<br>
AE – adverse event<br>
Obr. 2. Srovnání počtu hlášení nežádoucích událostí dle kategorií zdravotnických zařízení/nemocnic v roce 2018 – přepočet
na 1 000 pacientů.<br>
AE – nežádoucí událost

Fig. 3. Detailed monitoring of adverse event pressure ulcer – formation/origin in and out of the hospital.
AE – adverse event; PU – pressure ulcer
Obr. 3. Detailní analýza nežádoucích událostí dekubitus – místo vzniku ve zdravotnickém zařízení a mimo zdravotnické zařízení.
AE – nežádoucí událost; PU – dekubitus
Detailed monitoring of adverse event pressure ulcer – formation/origin in and out of the hospital.<br>
AE – adverse event; PU – pressure ulcer<br>
Obr. 3. Detailní analýza nežádoucích událostí dekubitus – místo vzniku ve zdravotnickém zařízení a mimo zdravotnické zařízení.<br>
AE – nežádoucí událost; PU – dekubitus

Tab. 2. Detailed monitoring of pressure ulcers – risk of pressure ulcers.
Detailed monitoring of pressure ulcers – risk of pressure ulcers.
* under category B, the original categories of hospitals B, C and D are combined
N – number; PUs – pressure ulcers

Tab. 3. Detailed monitoring of pressure ulcers – patients > 65 years.
Detailed monitoring of pressure ulcers – patients > 65 years.
* under category B, the original categories of hospitals B, C and D are combined
N – number; PUs – pressure ulcers

Similar situation was identified in relation to the proportion of patients over 65 years (Tab. 3). The vast majority of elderly patients (75.6%) was reported in category N –  long term care. So, we could conclude that the occur­rence of reported PUs shows a direct proportion to the proportion of patients over 65 years of age. Older adult patients constitute a population at high risk for complications, in particular PUs dur­­ing hospitalization, especial­ly when they are im­mobile or bedbound; however, the age as a predictive factor for PUs was reported in patients over 85 years in study focused on patient after hip fracture [11]. Another study focused on elderly patients and their age as PUs formation predictive factor highlights that age is potential indicator which could help provide safe and targeted care by pre-emptively identify­­ing patients at highest risk of PUs [12]. We have verified that age could be predictive factor as well but only as an indirect evidence as the majority of patients in LTC facilities are not solely elderly patients, but also polymorbid patients in a poor health and/ or social condition. We consider as the most significant the findings related to the human resources and other capaci­ties of the healthcare facilities. Fig. 4 describes distribution of hospitals/ facilities by the number of healthcare staff per bed, the number of patients per bed and the number of patients per healthcare staff which may provide additional stratification for the pos­sibility of a more accurate comparison of AEs among healthcare hospitals/ facilities. Results in category A –  faculty and large acute care hospitals show a higher frequency of PUs originated/ formatted in a given hospital per 1,000 patients. The higher number of reported PUs was in those hospitals, where there is a smal­ler number of healthcare staff per bed, where the number of patients per bed is lower and where the number of patients per healthcare staff is lower (patient /  staff ratio). It means that patients are stay­­ing in the hospital for the longer time or they are hospitalised at intensive care units (ICUs). In previous studies it has been indicated that critical care patients often have several risk factors for pres­sure ulceration [13]. Results in category N –  long term care sum­marises higher frequency of PUs originated/ formatted in a given hospital per 1,000 patients. The higher reported incidence of PUs was in those hospitals, where there is a smal­ler number of healthcare staff per bed, where the number of patients per bed is lower and where the number of patients per healthcare staff is lower (Fig. 5). Despite the fact that PUs are significantly more frequently mentioned in patients at ICUs than in standard wards and units [13,14] a significant proportion of PUs are not always accurately reported. On the other hand we have to emphasize that patients in LTC facilities have often decreased quality of life, increased morbidity and mortality [15,16]. The fact is that facilities with high rates of PUs have higher costs and risks of litigation [16].

Fig. 4. Detailed monitoring of adverse event pressure ulcer related to the capacities: category A and B – hospitals of acute care.
PU – pressure ulcer
Obr. 4. Detailní analýza hlášení nežádoucích událostí (dekubitů) ve vztahu ke kapacitním ukazatelům ve fakultních nemocnicích a nemocnicích akutní péče (kategorie A a B).
PU – dekubitus
Detailed monitoring of adverse event pressure ulcer related to the capacities: category A and B – hospitals of acute care.<br>
PU – pressure ulcer<br>
Obr. 4. Detailní analýza hlášení nežádoucích událostí (dekubitů) ve vztahu ke kapacitním ukazatelům ve fakultních nemocnicích a nemocnicích
akutní péče (kategorie A a B).<br>
PU – dekubitus

Fig. 5. Detailed monitoring of adverse event pressure ulcer related to the capacities: category N – long term care.
PU – pressure ulcer
Obr. 5. Detailní analýza hlášení nežádoucích událostí (dekubitů) ve vztahu ke kapacitním ukazatelům v nemocnicích následné péče (kategorie N).
PU – dekubitus
Detailed monitoring of adverse event pressure ulcer related to the capacities: category N – long term care.<br>
PU – pressure ulcer<br>
Obr. 5. Detailní analýza hlášení nežádoucích událostí (dekubitů) ve vztahu ke kapacitním ukazatelům v nemocnicích následné péče
(kategorie N).<br>
PU – dekubitus

Strengths and Limitations of the study and data col­lection

In our study we did not present real number of PUs rather the number of reported PUs in the local adverse event report­­ing systems of each healthcare provider. The main strength of the study is the use of uniform methodology and cros­s-sectional study results as we col­lect data from almost all inpatient healthcare facilities in the Czech Republic. The responsible people from all report­­ing units /  hospitals were provided with methodological support from IHIS staff therefore it is as­sumed the data were col­lected accurately.

Conclusion

We have analysed nationwide data from CAERS in which all the inpatient healthcare facilities has obligation to report data at central level under the uniform methodology. Based on our analysis we have verified that number of PUs reported in dif­ferent types of healthcare settings varies. The majority of reported PUs is reported in LTC facilities as formatted outside the facility. The number of reported PUs is related to the proportion of patients at risk of PU and patient over 65 years of age. We would like to emphasize the main objective of the CAERS is to support shared learn­­ing and the promotion of appropriate preventative measures on local level. We do hope that CEARS as the quality improvement program­me provid­­ing unified methodology (includ­­ing technical and non-technical interventions, data feedback to staff and clinical leadership) should be as­sociated with a sustained reduction in the incidence of PUs on a local (provider) level. Centralised data col­lection plays an important role in healthcare quality improvement and could become useful for longitudinal studies and monitoring. Strategies used in our CAERS program­me may be translated to all other inpatient settings and can lead to widespread patient benefit.

The authors declare they have no potential conflicts of interest concerning drugs, products, or services used in the study.

The Editorial Board declares that the manu­script met the ICMJE “uniform requirements” for biomedical papers.

Přijato k recenzi: 30. 6. 2019

Přijato do tisku: 22. 7. 2019

prof. PhDr. Andrea Pokorná, Ph.D.

Department of Nursing and Midwifery, Faculty of Medicine Masaryk University

Kamenice 3

625 00 Brno

e-mail: apokorna@med.muni.cz


Zdroje

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2. Gun­ningberg L, Hom­mel A, Bååth C et al. The first national pres­sure ulcer prevalence survey in county council and municipality settings in Sweden. J Eval Clin Pract 2013; 19(5): 862– 867. doi: 10.1111/ j.1365-2753.2012.01865.x.

3. Balas EA, Boren SA. Manag­­ing clinical knowledge for healthcare improvements. In: Bem­mel J, McCray AT (eds). Yearbook of medical informatics 2000: patient-centered systems. Stuttgart: Schattauer Verlagsgesel­lschaft 2000: 65– 70.

4. Rogers E. Dif­fusion of In­novations. 5th ed. New York: Simon and Schuster 2003.

5. Pokorná A, Saibertová S, Vasmanská S et al. Registers of pres­sure ulcers in an international context. Cent Eur J Nurs Midw 2016; 7(2): 444– 452. doi: 10.15452/  CEJNM.2016.07.0013.

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7. Pokorná A, Mužík J, Búřilová P et al. Pres­sure lesion monitoring –  data set validation after second pilot data col­lection. Cesk Slov Neurol N 2018; 81/ 114 (Suppl 1): 6– 12. doi: 10.14735/ amcsn­n2018S6.

8. Pokorná A, Štrombachová V, Mužík J et al. Národní portál Systém hlášení nežádoucích událostí. Praha: Ústav zdravotnických informací ČR 2016. [online]. Available from URL: https: / / shnu.uzis.cz.

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12. Forni C, D‘Ales­sandro F, Genco R et al. Prospective prog­nostic cohort study of pres­sure injuries in older adult patients with hip fractures. Adv Skin Wound Care 2018; 31(5): 218– 224. doi: 10.1097/ 01.ASW.0000530685.39114.98.

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Štítky
Paediatric neurology Neurosurgery Neurology

Článok vyšiel v časopise

Czech and Slovak Neurology and Neurosurgery

Číslo Supplementum 1

2019 Číslo Supplementum 1
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