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Revista Española de Enfermedades Digestivas

versión impresa ISSN 1130-0108

Rev. esp. enferm. dig. vol.110 no.1 Madrid ene. 2018 


RECALAD. Patient care at National Health System Digestive Care Units - A pilot study, 2015

Conrado-M. Fernández-Rodríguez1  8  , Cristina Fernández-Pérez2  8  5  , José-Luis Bernal3  5  8  ; Isabel Vera4  8  , Responsable del Comité de Excelencia Clínica de la Sociedad Española de Patología Digestiva, Javier Elola5  8  , Javier Júdez6  8  ; Fernando Carballo7  8  , Presidente de la Federación de Asociaciones Científico-Médicas Españolas (FACME). Presidente de la Sociedad Española de Patología Digestiva

1Unidad de Aparato Digestivo. Hospital Universitario Fundación Alcorcón. Universidad Rey Juan Carlos. Madrid. España

2Servicio de Medicina Preventiva. Hospital Clínico Universitario San Carlos. Madrid. España

3Unidad de Control de Gestión. Hospital Universitario 12 de Octubre. Madrid. España

4Servicio de Gastroenterología. Hospital Universitario Puerta de Hierro-Majadahonda. Madrid. España

5Fundación Instituto para la Mejora de la Asistencia Sanitaria. Madrid. España

6Gestión del Conocimiento. Sociedad Española de Patología Digestiva. España

7Federación de Asociaciones Científico-Médicas Españolas (FACME). España

8Sociedad Española de Patología Digestiva. España


In most Western countries, a tendency towards self-assessment and professionalism has lately emerged in the health care sector, particularly regarding results and patient safety 1) (2. In relation to digestive system units and services (digestive care units or DCUs) within the National Health System (NHS), there is a dearth of information about their structure, activities, and results. In 2011, the Sociedad Española de Patología Digestiva (SEPD), Asociación Española para el Estudio del Hígado (AEEH) and Asociación Española de Gastroenterología (AEG), amongst other scientific societies, worked jointly with the Spanish Ministry of Health, Social Services and Equality (MSSSI) to develop standards and recommendations for NHS DCUs 3. Some of these recommendations included developing a systematic analysis of DCU indicators, and collecting information on their structure and operation. Recently, the Federación de Asociaciones Científico-Médicas (FACME), with the help of the Instituto para la Mejora de la Asistencia Sanitaria (IMAS), is driving the development of RECAL (resources and quality) projects together with a number of scientific societies. The RECALAD (resources and quality in digestive care) project, developed by the SEPD in collaboration with the IMAS, has the following goals: a) to develop a DCU registry to record the specialty's care resources within the NHS (RECALAD survey); b) to facilitate a comparative assessment (benchmarking) system to facilitate ongoing improvement in DCUs; c) to analyze the relationship between structure data and performance in NHS DCUs with health outcomes (as measured by exploiting the NHS minimum basic data set ENT#091;MBDSENT#093;), as well as their use as a tool for healthcare management and planning; and d) to identify needs according to the evolution of epidemiologic data as provided by the MBDS and RECALAD survey.

The goal of this paper is to present the data collected by the RECALAD 2015 survey, the pilot experience for the implementation of the RECALAD survey, and the initial analyses of the MBDS database as related to digestive diseases.


RECALAD survey

The SEPD set up a task force to adapt the survey on care unit resources and quality used by other scientific societies for online completion in the area of NHS DCUs. A pilot sample was established with a total of 103 items requesting data for 2015. A total of 209 heads of NHS DCUs, including general acute hospitals with over 99 beds, were invited. The goal of this survey, which was designed to be regularly completed, is to understand aspects such as structure, human and technological resources, target population, services portfolio, cooperation with Primary Care, research and education, and good practices implementation.

MBDS database

The MBDS is a registry of all discharge reports from NHS hospitals. It includes sex, age, reason for admission (primary diagnosis), risk factors, comorbidities, complications (secondary diagnoses), and procedures performed. The registry also includes admission date, discharge date, admission status (urgent or scheduled), and discharge status (home, demise, transfer to another facility). The MBDS uses International Classification of Diseases (ICD) codes: ICD-9 up to 2015, then ICD-9-CM, and ICD-10 from 2016 onwards 4.

The MBDS-DS includes all admission events with a coded primary diagnosis of "diseases of digestive system" (DDS) occurred in NHS hospitals 3 (Table 1), as well as discharges from DCUs even in the absence of a primary DDS diagnosis.

Table 1 ICD-9-CM. International classification of "diseases of digestive system" 

Hospital classification (characterization)

The MSSSI cluster classification was used. This classification gathers NHS hospitals into five groups according to size, complexity, case mix or DRGs, and services portfolio 5.

Statistical analysis

Qualitative variables are summarized with frequency distribution, and their associations were assessed using a Chi-squared test. Quantitative variables are expressed as mean and standard deviation (SD). Correlation among quantitative variables was studied using Pearson's coefficient (r) and determination coefficient (r2).

DCU-related mortality and readmissions were risk-adjusted using MBDS-DS data and considering sex, age, admission type, comorbidity load according to the Charlson index, and episode duration in stays as independent variables. Risk adjustment for overall DCU activity was performed with a multilevel logistic regression model using the Charlson index 6) (7 (Table 2). The probability of patient dying or being readmitted is considered to be a composite of individual risk factors (casuistics) and quality of care (performance) 8. In addition to demographic and clinical patient variables, multilevel risk-adjusted models take into consideration a specific hospital effect 9) (10) (11. Hospital mortality and readmission rates were estimated from multilevel models as the ratio of foreseen outcome (which considers the performance of the specific hospital where the patient is cared for) over expected outcome (which considers a standard performance according to the mean value for all hospitals) multiplied by gross mortality rate (GMR) or readmission rate 8) (10. Thus, should a hospital's ratio be higher than its GMR or readmission rate, the site's fatality or readmission odds would be higher than the mean value for the considered hospitals. Risk-adjusted model calibration was analyzed using the Hosmer-Lemeshow test, and discrimination was assessed using the area under the ROC (receiver operating characteristic) curve (AROC).

For all comparisons the null hypothesis was rejected with p < 0.05. Statistical analyses were performed using the STATA 13 software.

Table 2 Multilevel risk adjustment model for DDS-related mortality (RSMR) and readmission (RSRR) rates 

Median OR: 1.19; area under ROC curve: 0.61 (95% IC: 0.61-0.61).


RECALAD survey

Out of 209 hospitals, 55 (26.3%) DCUs completed the survey. Response rate varied considerably among autonomous communities, and was very low among less complex institutions.

According to DCU type, 32 of 55 (58%) responders were services, 24% were sections, and 14.5% were institutes or clinical management areas. There is considerable dispersion regarding the hospital types where responding DCUs were located. Average number of beds was 635 ± 388, with a range of 100 to 1,671. As regards the hospital influence area population, dispersion was found to be similar, with an average 315,000 ± 180,000 inhabitants, range from 70,000 to 1,200,000 population. Thirteen (24%) units were in the "large hospitals" group (cluster 5), 31% were in high structural and activity load sites (cluster 4), 27% were in area hospitals (cluster 3), 11% were in basic general hospitals (cluster 2), and 7% were in cluster 1 facilities.

Most responding DCUs (86%) have a system set up for contacts between Primary Care teams (PCTs) and gastroenterologists, with e-mail and phone contacts being most common (72% and 77%, respectively), and 21% of DCUs regularly meet with PCTs (one meeting monthly on average).

Beds assigned to gastroenterology were present in 91% of responding hospitals, and monitoring beds were present in 18%. On-duty physicians were available in 34.5% (51.9% in DCUs with ≥ 24 beds), and on-call practitioners were available in 78.8% of facilities without on-duty services.

The average number of discharges from the DCUs was 1,139 ± 653/year, 100 ± 66 per year for each dedicated gastroenterologist. DCUs frequentation rate in 2014 (discharges per 100,000 population/year) was, according to the survey, 280/100,000 population/year, with a mean stay (MS) of 7.4 days.

Regarding endoscopy units, there was one room/75,000 ± 25,000 inhabitants. Average use time was 55 ± 19 hours/room. The rate of upper digestive endoscopies was 12 ± 7/1,000 population/year, and that of lower digestive endoscopies was 16 ± 6 per 1,000 population per year. In 35% of lower digestive endoscopies some intervention was carried out, albeit with relevant variations amongst units. The rate of endoscopic retrograde cholangiopancreatography procedures estimated from the survey data was 790 ± 405 per million population on average, whereas the rate of endoscopic ultrasounds was 941 ± 527 per million population.

Digestive endoscopy room performance, determined according to number of rooms and working hours as estimated by the survey, and applying the estimated times provided by the standards document 3, was 33 ± 12%.

A total of 23.6% of DCUs had a structured ultrasound unit, with a reference population similar to that in the hospital's influence area. Ultrasound unit working time was 34 ± 15 hours on average; 9% of specialists were dedicated to ultrasound units. The average rate of ultrasonograms per 1,000 population, as estimated by our survey, was 10 ± 6. However, this estimate has to be taken with caution given the low response rate obtained on this topic.

Of all responding DCUs, 74% were accredited to train residents in gastroenterology, and 96% were involved in undergraduate education; 66% of DCUs had associated professors, and 23% had research professors.

In all, 26% of responding DCUs were part of a RETIC or CIBER, 65% developed research projects (three projects on average), and 89% had papers published in indexed journals (a median of four papers). In four units their staff had got a patent registered.

Forty-nine percent of DCUs responded they had a procedure in place for the most relevant conditions they saw; 4% were part of a regional DCU network (for 600,000 or more population).


The MBDS-DS database includes 3,741,074 DDS-related discharge events during the 2005-2014 period. Of these events, 25% correspond to discharges from a DCU. In all, 46% of DDS-related discharges derived from General Surgery services and 17%, from Internal Medicine units. Table 3 shows the evolution of admissions for DDS, and highlights the ten most common diagnoses on discharge. In 2014 admissions for DDS increased by 17% over 2005; all common primary diagnoses increased except for "chronic liver disease and cirrhosis", which decreased to a considerable extent (24%). The number of admissions for upper digestive bleeding remained stable.

Table 3 Evolution of discharges for DDS by primary diagnosis, 2005-2014 

DDS: Diseases of digestive system.

From 2005 (first year the MBDS reliably records discharge reports) to 2014, HNS DCUs reported 1,175,201 discharge events (Table 4). During this period this number increased gradually (by 37% in 2014 vs 2005), which was associated with a decrease in GMR (3.7% in 2014, -28% vs 2005) and a slight reduction of MS (7.6 days in 2014, -14% vs 2005) (Table 4).

Table 4 Evolution of case numbers, mortality and mean stay in NHS DCUs 2005-2014 

DCU: Digestive Care Unit; GMR: Gross mortality rate; MS: Mean stay.

Mortality (multilevel) adjustment using the Charlson index is good (AROC: 0.81; 95% CI: 0.81-0.81; p < 0.001) and low for readmissions (AROC: 0.61; 95% CI: 0.61-0.61; p < 0.001) (Table 2). Adjustment is deemed excellent when the AROC (test discrimination) is above 0.97, and poor when it is below 0.6. As with other RECAL projects, a finding to be highlighted is the notable dispersion seen in outcome indicators such as mortality and readmission rates (both gross and adjusted), both amongst DCUs (Table 5) and autonomous communities (Table 6), with regard to DDS. Mortality adjusted rates may vary up to 3-fold amongst DCUs, and notable dispersions also exist in DDS-related frequentation and the other indicators amongst autonomous communities, including the proportion of DCU-reported discharge events for DDS.

Table 5 Indicator variations among DCUs 2014 

DCU: Digestive care unit; MS: Mean stay; GMR: Gross mortality rate; RSMR: Risk-standardized mortality rate (multilevel adjustment); RSRR: Risk-standardized readmission rate (multilevel adjustment). DCUs with 100 or more discharges for DDS in 2014.

Table 6 Indicator comparison among autonomous communities. DDS 2014 

Frequentation: Discharges per 100,000 population; DDS: Diseases of digestive system; MS: Mean stay; GMR: Gross mortality rate; RSMR: Risk-standardized mortality rate (multilevel adjustment); Readmission: Within 30 days of discharge (all causes); RSRR: Risk-standardized readmission rate (multilevel adjustment); % DIG/Total: Percentage of discharges by GI units over total.

Survey comparisons - MBDS

DCU frequentation in 2014 (discharges per 100,000 population/year), according to data from the MBDS, was 280/100,000/year, with a MS of 7.6 days. Estimates for these indicators based on the survey results yielded 352/100,000/year and a MS of 7.4 days.

No correlation was seen between risk-standardized mortality rate (RSMR) and frequentation (r2 = 0.08; p = 0.37), or between RSMR and MS (r2 = 0.08; p = 0.3), or in comparison with the risk-standardized readmission rate (RSRR) (r2 = 0.17; p = 0.1). However, a significant inverse correlation was found between RSRR and MS (r = -0.68; p < 0.01).


The results of this first RECALAD survey, a pilot experience with data from 2015, provide relevant information on the structure and operation of NHS DCUs. The MBDS analysis shows a steady decrease in MS and mortality over time for most conditions, which suggests higher hospital care quality regarding digestive diseases. Interestingly, hospital frequentation increased for most conditions except chronic liver disease and cirrhosis, and remained stable for digestive bleeding. These results are similar for some conditions to the admission rates seen in the USA until 2012, inasmuch as admission rates for GI bleeding (the first most common admission cause among digestive conditions ENT#091;12ENT#093;) became stable whereas admissions for acute pancreatitis, intestinal obstruction, and diverticulitis increased. In contrast, admissions for chronic liver disease have increased while those for cholelithiasis decreased by 5% 12. The reason for such an increase in admissions for chronic liver disease, by 21%, may be hepatitis C, with an admission rate that grew by 225% (12). The introduction of direct-acting antivirals (DAAs) in 2014 may well radically change this scenario in upcoming years.

Furthermore, in this same period from 2005 to 2014 there was an increase in readmission rates. The inverse correlation between MS and RSRR defies interpretation, and it may be speculated that early discharge for some complex conditions would be associated with higher readmission rates.

Upper and lower digestive endoscopy rates per 1,000 population/year are similar to those found in other developed countries such as the United Kingdom 13, where also a significant increase in the demand for and performance of such procedures was witnessed in the past decade. Since screening with colonoscopy reduces the incidence of colorectal cancer and its related mortality by almost 90% 14, it is highly likely that screening policies might be increasing colonoscopy rates in all autonomous communities, particularly among the population over 55 years of age. However, screening strategies in our setting should be improved in order to enhance program adherence 15.

The differences found in frequentation and MS between our survey and MBDS-based estimations may be explained by the limited number of respondents we had, by the fact that higher-volume hospitals responded more often, and by the fact that the RECALAD survey collects DCU discharge events whereas the MBDS includes discharges to other hospital departments.

A notable finding is the significant variability of outcome indicators between hospitals and Autonomous Community health services, the latter also exhibiting a strong variability both in DDS-related frequentation and clinical management (percentage of DDS-related discharges from DCUs). Although higher volume is associated with lower mortality for some conditions 16, no correlation was observed between hospital volume and adjusted mortality (RSMR) or readmission rate (RSRR) regarding DDS.

The variability found in risk-adjusted indicators may be hardly accounted for by epidemiological conditions or random variation, hence reaching a relevant number of responding DCUs to the next RECALAD survey would be important to provide consistency for the statistical analyses of associations between DCU structure and operation and health outcomes. Health outcome research as provided by the RECAL projects is collecting relevant information on the policy-enabling workings of the various specialties within the NHS 17) (18, hence DCUs are dared to provide adequate response rates.


The main limitation of this RECALAD pilot experience is the low proportion of responding DCUs (26%), inferior to the minimum 50% required by the MSSSI to gain NHS interest status, which is the goal pursued by the SEPD. Despite this limitation, which does not apply to the results obtained from the MBDS, the information collected from all 55 responding DCUs may be considered to faithfully reflect the organization and functioning of these units, particularly as it is mostly derived from high-volume hospitals. Similar response rates were obtained in similar surveys 19, but RECAL projects aim at reaching a far greater number of responses 18) (19. The low number of responses obtained also conditions the analysis of associations between DCU structure and functioning and health outcomes. Circulating the findings of this pilot, as well as promoting a campaign amongst SEPD members and DDS-related scientific societies on the significance of reliable data on DCU performance, are components of the SEPD strategy devised to increase response rates.


DDS represent a significant cause of hospital-related morbidity and mortality. The number of hospital admissions considerably grew (17%) during the period 2005-2014, in association with decreases in GMR and MS, and increases in readmissions. DCUs are responsible for 25% of DDS-related discharges. The RECALAD survey provides relevant information on the structure and organization of these units. Both the RECALAD survey and MBDS analysis show important variations amongst hospitals, DCUs and Autonomous Community health services. In order to gain a deeper insight into the causes of these variations it is important that higher numbers of RECALAD participating DCUs be recruited for the upcoming editions, among other factors.


The authors are grateful to all RECALAD responders, to the Ministry of Health, Social Services and Equality for the help granted to SEPD regarding the development of RECALAD, and most particularly to the Dirección General de Salud Pública, Calidad e Innovación and Instituto de Información Sanitaria.


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Received: October 24, 2017; Accepted: December 15, 2017

Correspondence: Conrado Fernández Rodríguez. Clinical Management Area. Sociedad Española de Patología Digestiva. Department of Digestive Diseases. Hospital Universitario Fundación Alcorcón. Universidad Rey Juan Carlos. Av. de Budapest, 1. 28221 Alcorcón, Madrid. Spain. e-mail:

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