Stratification and morbidity database (2n part)

31 Mar
Foto Emili Vela
Emili Vela

(This post is the second part of this post)

A key element for completing the stratification of population in risk groups is information system. It’s necessary to have a database that integrates information collected from different health records and therefore, in order to meet this demand, the population morbidity database was created.

The point is that every day there is more and more emphasis on the need to provide patients with a comprehensive and integrated health and social care, but the analysis and evaluation of this care can not be carried out correctly with fragmented information systems, on the contrary: it must be done starting from the integration of the data these contain.

Population morbidity database structure

The population morbidity database is based on a system of related tables that pivot around the users table, which includes the main data of the insured patient (demographics or health status, to name two examples).

Currently, there are three more tables: the diagnostic, the contact with health services and the pharmacy, but this type of structure relatively easily allows incorporating both information from new records (outpatient clinics, dialysis, respiratory therapy, etc.) and new tables with other relevant information, such as results of clinical findings:

Figure 2: Structure and content of the population morbidity database. The clinical determinations table in gray is not yet implemented.

Taula d'assegurats

The population morbidity database integrates information from the following records:

  • Registro Central de Asegurados – (RCA) (Central Registry of Insured Patients) managed by public relations management of CatSalut. This register basically provides all the information of residence, socio-demographics and health status of the insured patient.
  • Registros del conjunto mínimo básico de datos – (CMBD) (Records of basic minimum data set) managed by CatSalut Division of demand and activity analysis. These records feed both into the diagnoses table and in the contacts tables. There are different registers to collect information from the healthcare lines:
  • Hospitalization (CMBD-HA): information provided by general acute care hospitals (hospital admissions, outpatient surgery, home hospitalization, day hospital) from 2005 to 2014
  • Socio – sanitary (CMBD-SS): information of the care provided by the health centres of internment (long and medium stay and UFISS) and outpatient care equipment (PADES) from 2005-2014.
  • Psychiatric hospitalization (CMBD-SMH): information of the care provided by psychiatric hospitals from 2005-2014.
  • Outpatient Mental Health (CMBD-SMP): information of the care provided by outpatient mental health centres for the period 2005-2014.
  • Primary Care (CMBD-AP) information on the care provided by primary care teams from 2010 to 2014.
  • Emergency (CMBD-UR): information of emergency care (hospital and CUAP) from 2013 to 2014.
  • Pharmacy activity Log (RAF) managed by CatSalut’ management of pharmacy and medicine unit. This record provides all the information about outpatient pharmacy dispensing for the period 2011-2014.
  • Record health services turnover (RF) managed by the Division of care services provision. This record provides information on any activity financed by CatSalut, but that does not rely on a specific record: hospital outpatient clinics, dialysis, home oxygen therapy, rehabilitation or non-emergency medical transport. This record provides information mainly on the contacts table for the period 2011-2014.

The possible uses of the population morbidity database are multiple: the population stratification, the specific analysis of certain health problems (broken femur, IC, COPD,…), the development of population indicators of efficiency in the use of resources, etc.

We can conclude that, for the volume of data that integrates, this database has the characteristics of a structured “big data”, with a considerable capacity for growth and adaptation to new requirements and data sources and offers enormous possibilities for analysis.

Post written by Emili Vela, head of Modules for Tracking Quality Indicators (MSIQ). Health Care Area. CatSalut.

Leave a Reply

Your email address will not be published.

This site uses Akismet to reduce spam. Learn how your comment data is processed.