Pharmaceutical cost management in an ambulatory setting using a risk adjustment tool
Pharmaceutical expenditure is undergoing very high growth, and accounts for 30% of overall healthcare expenditure in Spain. In this paper we present a prediction model for primary health care pharmaceutical expenditure based on Clinical Risk Groups (CRG), a system that classifies individuals into mu...
Gespeichert in:
Veröffentlicht in: | BMC health services research 2014-10, Vol.14 (1), p.462-462, Article 462 |
---|---|
Hauptverfasser: | , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 462 |
---|---|
container_issue | 1 |
container_start_page | 462 |
container_title | BMC health services research |
container_volume | 14 |
creator | Vivas-Consuelo, David Usó-Talamantes, Ruth Guadalajara-Olmeda, Natividad Trillo-Mata, José-Luis Sancho-Mestre, Carla Buigues-Pastor, Laia |
description | Pharmaceutical expenditure is undergoing very high growth, and accounts for 30% of overall healthcare expenditure in Spain. In this paper we present a prediction model for primary health care pharmaceutical expenditure based on Clinical Risk Groups (CRG), a system that classifies individuals into mutually exclusive categories and assigns each person to a severity level if s/he has a chronic health condition. This model may be used to draw up budgets and control health spending.
Descriptive study, cross-sectional. The study used a database of 4,700,000 population, with the following information: age, gender, assigned CRG group, chronic conditions and pharmaceutical expenditure. The predictive model for pharmaceutical expenditure was developed using CRG with 9 core groups and estimated by means of ordinary least squares (OLS). The weights obtained in the regression model were used to establish a case mix system to assign a prospective budget to health districts.
The risk adjustment tool proved to have an acceptable level of prediction (R2 ≥ 0.55) to explain pharmaceutical expenditure. Significant differences were observed between the predictive budget using the model developed and real spending in some health districts. For evaluation of pharmaceutical spending of pediatricians, other models have to be established.
The model is a valid tool to implement rational measures of cost containment in pharmaceutical expenditure, though it requires specific weights to adjust and forecast budgets. |
doi_str_mv | 10.1186/1472-6963-14-462 |
format | Article |
fullrecord | <record><control><sourceid>gale_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4283085</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A539599952</galeid><sourcerecordid>A539599952</sourcerecordid><originalsourceid>FETCH-LOGICAL-b584t-657e940c8ad8df34b0f9e091e15535400428e01877adb8650dee013953b085bc3</originalsourceid><addsrcrecordid>eNqNUkFvFSEQ3hgbW6t3T2YTL162wgILXEyaF60mTeyhPROWnX3luUAFtkn_vWxfffaZmjQQGGa--Zh8M1X1DqMTjEX3CVPeNp3sSINpQ7v2RXW0c718ZB9Wr1PaIIS5aPmr6rBlhGBG8FF1eXGto9MG5myNnmoTUq6d9noNDnyura912a6fJ51DvKsT5Gz9up7Tcuo62vSz1sNmTvk-IYcwvakORj0lePtwH1dXX79crr415z_Ovq9Oz5ueCZqbjnGQFBmhBzGMhPZolIAkBswYYRQh2gpAWHCuh150DA1QnkQy0iPBekOOq89b3pu5dzCY8n_Uk7qJ1ul4p4K2aj_i7bVah1tViEmhKASrLUFvw38I9iMmOLWoqhZVi6WK6IXl40MZMfyaIWXlbDIwTdpDmJPCXculoB2mz4BiUVok2wX64R_oJszRFz0XFJecthL_Ra31BMr6MZQ6zUKqTlmRSkrJlgpPnkCVNYCzJngYbfHvJaBtgokhpQjjThOM1DJ6T6nw_nEzdgl_Zo38BvOe0sI</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1617974291</pqid></control><display><type>article</type><title>Pharmaceutical cost management in an ambulatory setting using a risk adjustment tool</title><source>MEDLINE</source><source>DOAJ Directory of Open Access Journals</source><source>SpringerLink Journals</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>PubMed Central Open Access</source><source>Springer Nature OA Free Journals</source><source>PubMed Central</source><creator>Vivas-Consuelo, David ; Usó-Talamantes, Ruth ; Guadalajara-Olmeda, Natividad ; Trillo-Mata, José-Luis ; Sancho-Mestre, Carla ; Buigues-Pastor, Laia</creator><creatorcontrib>Vivas-Consuelo, David ; Usó-Talamantes, Ruth ; Guadalajara-Olmeda, Natividad ; Trillo-Mata, José-Luis ; Sancho-Mestre, Carla ; Buigues-Pastor, Laia</creatorcontrib><description>Pharmaceutical expenditure is undergoing very high growth, and accounts for 30% of overall healthcare expenditure in Spain. In this paper we present a prediction model for primary health care pharmaceutical expenditure based on Clinical Risk Groups (CRG), a system that classifies individuals into mutually exclusive categories and assigns each person to a severity level if s/he has a chronic health condition. This model may be used to draw up budgets and control health spending.
Descriptive study, cross-sectional. The study used a database of 4,700,000 population, with the following information: age, gender, assigned CRG group, chronic conditions and pharmaceutical expenditure. The predictive model for pharmaceutical expenditure was developed using CRG with 9 core groups and estimated by means of ordinary least squares (OLS). The weights obtained in the regression model were used to establish a case mix system to assign a prospective budget to health districts.
The risk adjustment tool proved to have an acceptable level of prediction (R2 ≥ 0.55) to explain pharmaceutical expenditure. Significant differences were observed between the predictive budget using the model developed and real spending in some health districts. For evaluation of pharmaceutical spending of pediatricians, other models have to be established.
The model is a valid tool to implement rational measures of cost containment in pharmaceutical expenditure, though it requires specific weights to adjust and forecast budgets.</description><identifier>ISSN: 1472-6963</identifier><identifier>EISSN: 1472-6963</identifier><identifier>DOI: 10.1186/1472-6963-14-462</identifier><identifier>PMID: 25331531</identifier><language>eng</language><publisher>England: BioMed Central Ltd</publisher><subject>Age ; Ambulatory Care - economics ; Capitation ; Chronic illnesses ; Classification ; Computerized physician order entry ; Cost Control - economics ; Cross-Sectional Studies ; Disease ; Drug Costs - statistics & numerical data ; Expenditures ; Female ; Health care expenditures ; Health care policy ; Hospitals ; Humans ; Information systems ; Male ; Medicare ; Models, Economic ; Morbidity ; Patients ; Pharmaceuticals ; Pharmacy ; Population ; Prescription drugs ; Primary care ; Risk Adjustment - methods ; Spain</subject><ispartof>BMC health services research, 2014-10, Vol.14 (1), p.462-462, Article 462</ispartof><rights>COPYRIGHT 2014 BioMed Central Ltd.</rights><rights>2014 Vivas-Consuelo et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.</rights><rights>Vivas-Consuelo et al.; licensee BioMed Central Ltd. 2014</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-b584t-657e940c8ad8df34b0f9e091e15535400428e01877adb8650dee013953b085bc3</citedby><cites>FETCH-LOGICAL-b584t-657e940c8ad8df34b0f9e091e15535400428e01877adb8650dee013953b085bc3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4283085/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4283085/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25331531$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Vivas-Consuelo, David</creatorcontrib><creatorcontrib>Usó-Talamantes, Ruth</creatorcontrib><creatorcontrib>Guadalajara-Olmeda, Natividad</creatorcontrib><creatorcontrib>Trillo-Mata, José-Luis</creatorcontrib><creatorcontrib>Sancho-Mestre, Carla</creatorcontrib><creatorcontrib>Buigues-Pastor, Laia</creatorcontrib><title>Pharmaceutical cost management in an ambulatory setting using a risk adjustment tool</title><title>BMC health services research</title><addtitle>BMC Health Serv Res</addtitle><description>Pharmaceutical expenditure is undergoing very high growth, and accounts for 30% of overall healthcare expenditure in Spain. In this paper we present a prediction model for primary health care pharmaceutical expenditure based on Clinical Risk Groups (CRG), a system that classifies individuals into mutually exclusive categories and assigns each person to a severity level if s/he has a chronic health condition. This model may be used to draw up budgets and control health spending.
Descriptive study, cross-sectional. The study used a database of 4,700,000 population, with the following information: age, gender, assigned CRG group, chronic conditions and pharmaceutical expenditure. The predictive model for pharmaceutical expenditure was developed using CRG with 9 core groups and estimated by means of ordinary least squares (OLS). The weights obtained in the regression model were used to establish a case mix system to assign a prospective budget to health districts.
The risk adjustment tool proved to have an acceptable level of prediction (R2 ≥ 0.55) to explain pharmaceutical expenditure. Significant differences were observed between the predictive budget using the model developed and real spending in some health districts. For evaluation of pharmaceutical spending of pediatricians, other models have to be established.
The model is a valid tool to implement rational measures of cost containment in pharmaceutical expenditure, though it requires specific weights to adjust and forecast budgets.</description><subject>Age</subject><subject>Ambulatory Care - economics</subject><subject>Capitation</subject><subject>Chronic illnesses</subject><subject>Classification</subject><subject>Computerized physician order entry</subject><subject>Cost Control - economics</subject><subject>Cross-Sectional Studies</subject><subject>Disease</subject><subject>Drug Costs - statistics & numerical data</subject><subject>Expenditures</subject><subject>Female</subject><subject>Health care expenditures</subject><subject>Health care policy</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Information systems</subject><subject>Male</subject><subject>Medicare</subject><subject>Models, Economic</subject><subject>Morbidity</subject><subject>Patients</subject><subject>Pharmaceuticals</subject><subject>Pharmacy</subject><subject>Population</subject><subject>Prescription drugs</subject><subject>Primary care</subject><subject>Risk Adjustment - methods</subject><subject>Spain</subject><issn>1472-6963</issn><issn>1472-6963</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNqNUkFvFSEQ3hgbW6t3T2YTL162wgILXEyaF60mTeyhPROWnX3luUAFtkn_vWxfffaZmjQQGGa--Zh8M1X1DqMTjEX3CVPeNp3sSINpQ7v2RXW0c718ZB9Wr1PaIIS5aPmr6rBlhGBG8FF1eXGto9MG5myNnmoTUq6d9noNDnyura912a6fJ51DvKsT5Gz9up7Tcuo62vSz1sNmTvk-IYcwvakORj0lePtwH1dXX79crr415z_Ovq9Oz5ueCZqbjnGQFBmhBzGMhPZolIAkBswYYRQh2gpAWHCuh150DA1QnkQy0iPBekOOq89b3pu5dzCY8n_Uk7qJ1ul4p4K2aj_i7bVah1tViEmhKASrLUFvw38I9iMmOLWoqhZVi6WK6IXl40MZMfyaIWXlbDIwTdpDmJPCXculoB2mz4BiUVok2wX64R_oJszRFz0XFJecthL_Ra31BMr6MZQ6zUKqTlmRSkrJlgpPnkCVNYCzJngYbfHvJaBtgokhpQjjThOM1DJ6T6nw_nEzdgl_Zo38BvOe0sI</recordid><startdate>20141021</startdate><enddate>20141021</enddate><creator>Vivas-Consuelo, David</creator><creator>Usó-Talamantes, Ruth</creator><creator>Guadalajara-Olmeda, Natividad</creator><creator>Trillo-Mata, José-Luis</creator><creator>Sancho-Mestre, Carla</creator><creator>Buigues-Pastor, Laia</creator><general>BioMed Central Ltd</general><general>BioMed Central</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7WY</scope><scope>7WZ</scope><scope>7X7</scope><scope>7XB</scope><scope>87Z</scope><scope>88C</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8FL</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>FYUFA</scope><scope>F~G</scope><scope>GHDGH</scope><scope>K60</scope><scope>K6~</scope><scope>K9.</scope><scope>KB0</scope><scope>L.-</scope><scope>M0C</scope><scope>M0S</scope><scope>M0T</scope><scope>M1P</scope><scope>NAPCQ</scope><scope>PIMPY</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope><scope>7U1</scope><scope>7U2</scope><scope>C1K</scope><scope>5PM</scope></search><sort><creationdate>20141021</creationdate><title>Pharmaceutical cost management in an ambulatory setting using a risk adjustment tool</title><author>Vivas-Consuelo, David ; Usó-Talamantes, Ruth ; Guadalajara-Olmeda, Natividad ; Trillo-Mata, José-Luis ; Sancho-Mestre, Carla ; Buigues-Pastor, Laia</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-b584t-657e940c8ad8df34b0f9e091e15535400428e01877adb8650dee013953b085bc3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Age</topic><topic>Ambulatory Care - economics</topic><topic>Capitation</topic><topic>Chronic illnesses</topic><topic>Classification</topic><topic>Computerized physician order entry</topic><topic>Cost Control - economics</topic><topic>Cross-Sectional Studies</topic><topic>Disease</topic><topic>Drug Costs - statistics & numerical data</topic><topic>Expenditures</topic><topic>Female</topic><topic>Health care expenditures</topic><topic>Health care policy</topic><topic>Hospitals</topic><topic>Humans</topic><topic>Information systems</topic><topic>Male</topic><topic>Medicare</topic><topic>Models, Economic</topic><topic>Morbidity</topic><topic>Patients</topic><topic>Pharmaceuticals</topic><topic>Pharmacy</topic><topic>Population</topic><topic>Prescription drugs</topic><topic>Primary care</topic><topic>Risk Adjustment - methods</topic><topic>Spain</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Vivas-Consuelo, David</creatorcontrib><creatorcontrib>Usó-Talamantes, Ruth</creatorcontrib><creatorcontrib>Guadalajara-Olmeda, Natividad</creatorcontrib><creatorcontrib>Trillo-Mata, José-Luis</creatorcontrib><creatorcontrib>Sancho-Mestre, Carla</creatorcontrib><creatorcontrib>Buigues-Pastor, Laia</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing & Allied Health Database</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Healthcare Administration Database (Alumni)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Business Premium Collection (Alumni)</collection><collection>Health Research Premium Collection</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Global</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Healthcare Administration Database</collection><collection>Medical Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>Risk Abstracts</collection><collection>Safety Science and Risk</collection><collection>Environmental Sciences and Pollution Management</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>BMC health services research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Vivas-Consuelo, David</au><au>Usó-Talamantes, Ruth</au><au>Guadalajara-Olmeda, Natividad</au><au>Trillo-Mata, José-Luis</au><au>Sancho-Mestre, Carla</au><au>Buigues-Pastor, Laia</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Pharmaceutical cost management in an ambulatory setting using a risk adjustment tool</atitle><jtitle>BMC health services research</jtitle><addtitle>BMC Health Serv Res</addtitle><date>2014-10-21</date><risdate>2014</risdate><volume>14</volume><issue>1</issue><spage>462</spage><epage>462</epage><pages>462-462</pages><artnum>462</artnum><issn>1472-6963</issn><eissn>1472-6963</eissn><abstract>Pharmaceutical expenditure is undergoing very high growth, and accounts for 30% of overall healthcare expenditure in Spain. In this paper we present a prediction model for primary health care pharmaceutical expenditure based on Clinical Risk Groups (CRG), a system that classifies individuals into mutually exclusive categories and assigns each person to a severity level if s/he has a chronic health condition. This model may be used to draw up budgets and control health spending.
Descriptive study, cross-sectional. The study used a database of 4,700,000 population, with the following information: age, gender, assigned CRG group, chronic conditions and pharmaceutical expenditure. The predictive model for pharmaceutical expenditure was developed using CRG with 9 core groups and estimated by means of ordinary least squares (OLS). The weights obtained in the regression model were used to establish a case mix system to assign a prospective budget to health districts.
The risk adjustment tool proved to have an acceptable level of prediction (R2 ≥ 0.55) to explain pharmaceutical expenditure. Significant differences were observed between the predictive budget using the model developed and real spending in some health districts. For evaluation of pharmaceutical spending of pediatricians, other models have to be established.
The model is a valid tool to implement rational measures of cost containment in pharmaceutical expenditure, though it requires specific weights to adjust and forecast budgets.</abstract><cop>England</cop><pub>BioMed Central Ltd</pub><pmid>25331531</pmid><doi>10.1186/1472-6963-14-462</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1472-6963 |
ispartof | BMC health services research, 2014-10, Vol.14 (1), p.462-462, Article 462 |
issn | 1472-6963 1472-6963 |
language | eng |
recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4283085 |
source | MEDLINE; DOAJ Directory of Open Access Journals; SpringerLink Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central Open Access; Springer Nature OA Free Journals; PubMed Central |
subjects | Age Ambulatory Care - economics Capitation Chronic illnesses Classification Computerized physician order entry Cost Control - economics Cross-Sectional Studies Disease Drug Costs - statistics & numerical data Expenditures Female Health care expenditures Health care policy Hospitals Humans Information systems Male Medicare Models, Economic Morbidity Patients Pharmaceuticals Pharmacy Population Prescription drugs Primary care Risk Adjustment - methods Spain |
title | Pharmaceutical cost management in an ambulatory setting using a risk adjustment tool |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-05T03%3A31%3A41IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Pharmaceutical%20cost%20management%20in%20an%20ambulatory%20setting%20using%20a%20risk%20adjustment%20tool&rft.jtitle=BMC%20health%20services%20research&rft.au=Vivas-Consuelo,%20David&rft.date=2014-10-21&rft.volume=14&rft.issue=1&rft.spage=462&rft.epage=462&rft.pages=462-462&rft.artnum=462&rft.issn=1472-6963&rft.eissn=1472-6963&rft_id=info:doi/10.1186/1472-6963-14-462&rft_dat=%3Cgale_pubme%3EA539599952%3C/gale_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1617974291&rft_id=info:pmid/25331531&rft_galeid=A539599952&rfr_iscdi=true |