Preventable hospitalization and access to primary health care in an area of Southern Italy

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Preventable hospitalization and access to primary health care in an area of Southern Italy
  BioMed   Central Page 1 of 8 (page number not for citation purposes) BMC Health Services Research Open Access Research article Preventable hospitalization and access to primary health care in an area of Southern Italy PaoloRizza 1 , AidaBianco 1 , MariaPavia* 1  and ItaloFAngelillo 2  Address: 1 Chair of Hygiene, Medical School, University of Catanzaro "Magna Græcia", Catanzaro, Italy and 2 Department of Public, Clinical and Preventive Medicine, Second University of Naples, Naples, Italy Email:;; MariaPavia*; * Corresponding author Abstract Background: Ambulatory care-sensitive conditions (ACSC), such as hypertension, diabetes,chronic heart failure, chronic obstructive pulmonary disease and asthma, are conditions that canbe managed with timely and effective outpatient care reducing the need of hospitalization.Avoidable hospitalizations for ACSC have been used to assess access, quality and performance of the primary care delivery system. The aims of this study were to quantify the proportion of avoidable hospital admissions for ACSCs, to identify the related patient's socio-demographic profileand health conditions, to assess the relationship between the primary care access characteristicsand preventable hospitalizations, and the usefulness of avoidable hospitalizations for ACSCs tomonitor the effectiveness of primary health care. Methods: A random sample of 520 medical records of patients admitted to medical wards(Cardiology, Internal Medicine, Pneumology, Geriatrics) of a non-teaching acute care 717-bedhospital located in Catanzaro (Italy) were reviewed. Results: A total of 31.5% of the hospitalizations in the sample were judged to be preventable. Of these, 40% were for congestive heart failure, 23.2% for chronic obstructive pulmonary disease,13.5% for angina without procedure, 8.4% for hypertension, and 7.1% for bacterial pneumonia.Preventable hospitalizations were significantly associated to age and sex since they were higher inolder patients and in males. The proportion of patients who had a preventable hospitalizationsignificantly increased with regard to the number of hospital admissions in the previous year and tothe number of patients for each primary care physician (PCP), with lower number of PCP accessesand PCP medical visits in the previous year, with less satisfaction about PCP health services, and,finally, with worse self-reported health status and shorter length of hospital stay. Conclusion: The findings from this study add to the evidence and the urgency of developing andimplementing effective interventions to improve delivery of health care at the community level andprovided support to the usefulness of avoidable hospitalizations for ACSCs to monitor thisprocess. Published: 30 August 2007 BMC Health Services Research  2007, 7 :134doi:10.1186/1472-6963-7-134Received: 20 November 2006Accepted: 30 August 2007This article is available from:© 2007 Rizza et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the srcinal work is properly cited.  BMC Health Services Research  2007, 7 :134 2 of 8 (page number not for citation purposes) Background  Ambulatory care-sensitive conditions (ACSC), such ashypertension, diabetes, chronic heart failure, chronic obstructive pulmonary disease and asthma, are condi-tions that can be managed with timely and effective out-patient care reducing the need of hospitalization. Rates of avoidable hospitalizations, also called preventable hospi-talizations, for ACSC have been used to assess access,quality and performance of the primary care delivery sys-tem. This includes primary prevention, early detectionand monitoring of acute episodes and follow-up andmonitoring of chronic conditions. The Agency for Healthcare Research and Quality (AHRQ)developed the Preventive Quality Indicators (PQIs), a set of measures to identify ACSC as rates of admission to thehospital based on the assumption that high hospitaliza-tion rates for ACSC may result from poor access to pri-mary care and can be prevented [1]. ACSC have beenevaluated in many countries most in the US but also in Australia, Canada and European countries [2-5] for deter- mining the socioeconomic and medical conditions asso-ciated with hospitalized ACSC [6-12]; however, little is known about role of access to primary care, measured asnumber of accesses, number of patients per primary carephysician (PCP), health care seeking and physician prac-tice style [13-17]. In Italy, where universal and free access to primary healthcare is provided through the National Health Service,these indicators can serve as a convenient and effectiveevaluation tool to assess effectiveness of and barriers toaccess to primary care. Community health care is pro- vided by health districts, geographical units responsiblefor coordinating and providing primary care, pharmaceu-ticals, home care, specialist and residential and semi-resi-dential care. Primary care is provided by physicians andpediatricians working under government contract, whoare paid a capitation fee based on the number of patients(adults or children) on their list with a maximum number of patients allowed (1500–1800 for general practitionersand 800–1000 for pediatricians). The PCPs act as "gate-keepers" for access to secondary services and this role hasa great impact both on quality of outcomes and cost of healthcare, but for several reasons patients prefer to attendspecialists or hospitals [18]. The aims of this study were to quantify the proportion of avoidable hospital admissions for ACSCs, to identify therelated patient's socio-demographic profile and healthconditions, to assess whether barriers to access to primary care were related to preventable hospitalizations in Italy and to assess the usefulness of avoidable hospitalizationsfor ACSCs to monitor the effectiveness of primary healthcare. Methods Study population  This cross-sectional study was conducted from April toJuly 2005 by reviewing a random sample of 520 medicalrecords of patients aged 18 and over admitted to medical wards (Cardiology, Internal Medicine, Pneumology, Ger-iatrics) of a non-teaching acute care 717-bed hospitallocated in Catanzaro (Italy). Two physicians, who were not involved in care and whohad been previously trained, collected the data by review-ing charts and by interviewing at bedside all the patients who agreed to participate, independently. Actual data col-lection and extraction did not start until the performanceof the reviewers had been judged satisfactory and showedsatisfactory inter-rater reliability. The analysis on medicalrecords was based on data reviewed by both physicians in which discrepancies were solved through discussionamong reviewers. A total of 492 patients agreed to participate and wereenrolled for a response rate of 94.6%, thus minimizing the role of non-respondent bias. Review instrument  The following data were collected for each patient by reviewing charts: socio-demographics (age, gender, mari-tal status, education level), distance of patient's homefrom hospital, Charlson et al. comorbidity index [19], ward and type of admission, and who referred the patient to the hospital. The following data were collected by inter- viewing at bedside all the patients who agreed to partici-pate: socio-demographics (working activity, number of persons in the household), the self-reported health status,self-reported utilization of health services during the pre- vious year (propensity to seek care, number and main rea-sons of visit and for not having been to a PCP medical visit, difficulty to the access to and satisfaction with PCPhealth services, number and main reasons for specialist  visit, emergency access, hospital admission), and thename of their own PCP. The questionnaire focused partic-ularly on frequency of utilization of health services during the previous year with most questions in "yes/no" format.If the answer was "yes" then the participants were askedthe number of accesses. The questions on satisfaction anddifficulty with PCP health services were scored on a four-point Likert scale with options for no, few, rather, andmuch. The questionnaire was pretested on a sample toensure clarity of interpretation to improve the validity of responses. The accuracy of patient self-report of healthservices utilization is of paramount concern, however such data is often used to estimate health care utilizationand have demonstrated to be a reasonably accuratemethod to obtain information on most types of medicalutilization in the general population [20-22].  BMC Health Services Research  2007, 7 :134 3 of 8 (page number not for citation purposes)  We selected 9 out of 16 PQIs from AHRQ, defined by diagnosis and procedure codes of International Classifica-tion of Diseases (ICD-9-CM) [23], to identify the prevent-able hospitalizations for ACS conditions: diabetes short-term and long-term complication, uncontrolled diabetes,chronic obstructive pulmonary disease, hypertension,congestive heart failure, bacterial pneumonia, angina without procedure and adult asthma. We excluded pediat-ric indicators (pediatric asthma, pediatric gastroenteritis,low birth weight) and indicators for adult conditions that  were rarely encountered, in our setting, as discharge diag-nosis, as measured by reviewing discharge records in theprevious two years (perforated appendix, dehydration,urinary tract infection, lower-extremity amputationamong patients with diabetes). Assessment of avoidablehospitalizations was made by using the discharge dataaccording to the Guide to Prevention Quality Indicatorsfrom AHRQ [1]. The Ethics Committee of the "Mater Domini" Hospital of Catanzaro (Italy) approved the protocol of the study (Prot. E.C. n°16/2005). Statistical analysis  A multivariate logistic regression analysis was performedto identify baseline characteristics independently associ-ated with the following outcomes of interest: preventablehospitalization for all investigated conditions, preventa-ble hospitalization for cardiovascular diseases (hyperten-sion, congestive heart failure, angina without procedure),preventable hospitalization for respiratory diseases(chronic obstructive pulmonary disease, bacterial pneu-monia, adult asthma), preventable hospitalization for diabetes (diabetes short-term complication, diabeteslong-term complication, uncontrolled diabetes). Modelbuilding strategy and particularly ways to include inde-pendent variables in the model (continuous, ordinal or categorical) took into account how each of these ways bet-ter fitted the data at the univariate analysis and we chosethat way in the multivariate analysis. Moreover, as regardsto the cut-off points for less or more than 12 accesses or  visits per year, our idea was that in many chronic patients,one access per month is generally useful for monitoring chronic conditions. In all models the explanatory varia-bles included were the following: patient's age (continu-ous), patient's sex (male = 0, female = 1), distance inkilometers between patient's home and hospital (contin-uous), educational level (no formal education = 0, pri-mary school = 1, secondary school or higher = 2), living condition (with family = 1, other = 2), additional personsin the household (none = 0, 1 = 1, > 1 = 2), working activ-ity (retired = 0, other = 1), type of admission (emergency physician = 1, other = 2), length of hospital stay (contin-uous), age-adjusted Charlson et al. comorbidity index (continuous), self-reported health status on a 10 pointsscale ( ≤  4 = 0, ≥  5 = 1), number of PCP accesses in the pre- vious year ( ≤  12 = 1, > 12 = 2), number of PCP medical visits in the previous year ( ≤  12 = 1, > 12 = 2), satisfaction with PCP health services (no/few = 0, rather/much = 1),number of patients for each PCP (< 1000 = 1, 1000–1300= 2, > 1300 = 3), number of specialist visits in community health services (none = 0, ≥  1 = 1), number of emergency accesses in the previous year (none = 0, ≥  1 = 1), andnumber of hospital admissions in the previous year (none= 0, ≥  1 = 1). The significance level for variables entering the logistic regression models was set at 0.2 and for removing from the model at 0.4. Adjusted odds ratio(ORs) and 95% confidence intervals (CIs) were calcu-lated. The data were analyzed using the Stata software pro-gram [24]. Results  The main characteristics of the study population are pre-sented in Table 1. Fifty-two per cent were females, themedian age was 75 years (range 23–95), and three quar-ters lived with their family, more than half were in generalmedical wards (68.3%), the median length of stay was 9days (range 1–83) and the median of Charlson et al.comorbidity index was 4 (range 0–14). Almost all(99.2%) had at least one PCP access in the previous year,more than 40% had at least one hospital admission in theprevious year, and at least one district health servicesaccess. More than 70% were satisfied with PCP healthservices, and the main reasons for dissatisfaction werelong waiting times for access (18.2%), opening hours(11.7%), and trust in hospital physicians (7.4%). Overall,17.2% reported difficulty of access to PCP health services.In the study period, a total of 31.5% of the hospitaliza-tions in the sample were judged to be preventable. Of these, 40% were for congestive heart failure, 23.2% for chronic obstructive pulmonary disease, 13.5% for angina without procedure, 8.4% for hypertension, 7.1% for bac-terial pneumonia, 3.2% for diabetes short-term complica-tion, 2.6% for adult asthma, 1.3% for diabetes long-termcomplication and 0.6% for uncontrolled diabetes.Patients admitted for a preventable hospitalization weremore frequently males (58.1% vs. 43.3%), older (medianage 76 vs. 74), with a higher unsatisfactory self-reportedhealth status (56.1% vs. 36.8%), reported more fre-quently less than 13 PCP medical visits (93.5% vs. 47.9%)and less than 13 PCP accesses (41.6% vs. 19.5%) in theprevious year, attended a PCP with a higher number of patients (65.6% vs. 31.1%), were more frequently unsat-isfied by PCP health services (54% vs. 15.6%), and weremore likely to have had at least one emergency access(52.6% vs. 45.2%) and hospital admission in the previous year (54% vs. 40.1%).Preventable hospitalizations were significantly associated with age and sex since they were higher in older patients  BMC Health Services Research  2007, 7 :134 4 of 8 (page number not for citation purposes) (OR = 1.03, 95% CI = 1.01–1.05, p = 0.027) and in males(OR = 0.52, 95% CI = 0.31–0.87, p = 0.013). The propor-tion of patients who had a preventable hospitalizationsignificantly increased with regard to the number of hos-pital admissions in the previous year (OR = 1.76, 95% CI= 1.06–2.93, p = 0.03) and to the number of patients for each PCP (OR = 2.25, 95% CI = 1.62–3.13, p < 0.001), with lower number of PCP accesses (OR = 0.52, 95% CI =0.3–0.93, p = 0.027) and PCP medical visits in the previ-ous year (OR = 0.1, 95% CI = 0.05–0.23, p < 0.001), withless satisfaction about PCP health services (OR = 0.34,95% CI = 0.2–0.58, p < 0.001), and, finally, with worseself-reported health status (OR = 0.53, 95% CI = 0.31–0.89, p = 0.017) and shorter length of hospital stay (OR =0.95, 95% CI = 0.91–0.99, p = 0.011) (Model 1 in Table2).Preventable hospitalizations for cardiovascular diseases were significantly more common for higher number of patients for each PCP (OR = 2.2, 95% CI = 1.5–3.22, p <0.001) and for lower number of PCP accesses (OR = 0.52,95% CI = 0.27–0.98, p = 0.044) and PCP medical visits(OR = 0.12, 95% CI = 0.05–0.3, p < 0.001) in the previous year. Moreover patients who had a preventable hospitali-zation for cardiovascular diseases were significantly morelikely to be less satisfied for PCP health services (OR =0.31, 95% CI = 0.17–0.57, p < 0.001), retired (OR = 0.37,95% CI = 0.13–0.97, p = 0.044), with worse self-reportedhealth status (OR = 0.5, 95% CI = 0.27–0.93, p = 0.027)and shorter length of hospital stay (OR = 0.94, 95% CI =0.9–0.99, p = 0.013) (Model 2 in Table 2).Preventable hospitalizations for respiratory diseases weresignificantly associated with higher number of patients for each PCP (OR = 2.86, 95% CI = 1.66–4.94, p < 0.001) andemergency accesses in the previous year (OR = 2.71, 95%CI = 1.2–6.11, p = 0.016), with males (OR = 0.27, 95% CI= 0.11–0.64, p = 0.003), worse satisfaction for PCP healthservices (OR = 0.27, 95% CI = 0.13–0.58, p = 0.001) andlower number of PCP accesses (OR = 0.34, 95% CI =0.14–0.82, p = 0.017) and PCP medical visits (OR = 0.11,95% CI = 0.03–0.4, p = 0.001) in the previous year (Model 3 in Table 2).Finally, preventable hospitalizations for diabetes were sig-nificantly higher with the number of hospital admissionsin the previous year (OR = 9.74, 95% CI = 1.14–83.39, p= 0.038) and the number of patients for each PCP (OR =4.75, 95% CI = 1.22–18.48, p = 0.025) (Model 4 in Table2). Discussion One of the main findings of our study was that more than30% of the hospitalizations were considered preventableaccording to the PQI indicators. Although most of the Table 1: Selected characteristics of the study population CharacteristicN*%SexMale23648Female25652Age group, years< 6510621.565–7413928.375–8419639.8 ≥  855110.4Median75Education levelNo formal education17736Primary school18637.8Secondary school or higher12926.2Marital statusMarried28658.1Others20641.9Living conditionWith family36874.8Other12425.2Additional persons in the householdNone11022.4120541.6> 117736Working activityRetired41183.5Other8116.5Distance from home to hospital, km ≤  522746.16–3515331.1> 3511222.8Median20Type of admissionEmergency physician43287.8Other6012.2Length of hospital stay, daysMedian9Age-adjusted Charlson et al. comorbidity indexMedian4Self-reported health status on a 10 points scale ≤  421142.9 ≥  528157.1PCP accesses in the previous yearNone40.81–1212926.2> 1235973PCP medical visits in the previous year ≤  1230462.3> 1218437.7Satisfaction with PCP health servicesNo/few13527.7Rather/much35372.3Difficulty of access to PCP health servicesNo/few40482.8Rather/much8417.2Patients for each PCP< 100014629.91000–130013728.1> 130020542District health services accesses in the previous yearNone31063.5 ≥  117836.5Emergency accesses in the previous yearNone26052.8 ≥  123247.2Hospital admissions in the previous yearNone27555.9 ≥  121744.1*The numbers that do not add to 492 are due to not applicable data for the variable.PCP, primary care physician.  BMC Health Services Research  2007, 7 :134 5 of 8 (page number not for citation purposes) Table 2: Logistic regression models results 1,2 VariableORSE95% CIp Model 1. Outcome: Overall preventable hospitalizationLog-likelihood = -194.19, χ 2 = 220.14, p < 0.001, Number of observations = 488 Number of PCP medical visits in the previous year0.10.040.05–0.23< 0.001Number of patients for each PCP2.250.381.62–3.13< 0.001Satisfaction with PCP health services0.340.090.2–0.58< 0.001Length of hospital stay0.950.020.91–0.990.011Sex0.520.140.31–0.870.013Self-reported health status0.530.140.31–0.890.017Number of PCP accesses in the previous year0.520.150.3–0.930.027Age1.030.011.01–1.050.027Number of hospital admissions in the previous year1.760.461.06–2.930.03Additional persons in the household0.750.130.53–1.060.105Type of admission0.570.240.25–1.30.18Distance between patient's home and hospital0.990.010.98–1.010.399 Model 2. Outcome: Preventable hospitalization for cardiovascular diseasesLog-likelihood = -150.13, χ 2 = 153.38, p < 0.001, Number of observations = 429 Number of patients for each PCP2.20.431.5–3.22< 0.001Satisfaction with PCP health services0.310.090.17–0.57< 0.001Number of PCP medical visits in the previous year0.120.060.05–0.3< 0.001Length of hospital stay0.940.020.9–0.990.013Self-reported health status0.50.160.27–0.930.027Number of PCP accesses in the previous year0.520.170.27–0.980.044Working activity0.370.180.13–0.970.044Sex0.620.180.35–1.10.106Number of hospital admissions in the previous year1.530.460.85–2.770.156Additional persons in the household0.760.150.51–1.130.172Age-adjusted Charlson et al. comorbidity index1.080.070.96–1.220.19 Model 3. Outcome: Preventable hospitalization for respiratory diseasesLog-likelihood = -92.36, χ 2 = 116.38, p < 0.001, Number of observations = 385 Number of patients for each PCP2.860.81.66–4.94< 0.001Satisfaction with PCP health services0.270.110.13–0.580.001Number of PCP medical visits in the previous year0.110.070.03–0.40.001Sex0.270.120.11–0.640.003Number of emergency accesses in the previous year2.711.121.2–6.110.016Number of PCP accesses in the previous year0.340.150.14–0.820.017Type of admission0.20.170.04–1.050.058Living condition2.351.080.95–5.810.063Self-reported health status0.490.210.21–1.120.092Age1.030.020.99–1.070.131Age-adjusted Charlson et al. comorbidity index0.880.080.73–1.050.159Length of hospital stay0.970.030.92–1.020.232 Model 4. Outcome: Preventable hospitalization for diabetesLog-likelihood = -21.54, χ 2 = 18.77, p = 0.0277, Number of observations = 144 Number of patients for each PCP4.753.291.22–18.480.025Number of hospital admissions in the previous year9.7410.671.14–83.390.038Number of PCP accesses in the previous year0.150.170.02–1.340.090Education level0.270.230.05–1.460.129Length of hospital stay0.880.090.72–1.080.216Number of specialist visits in community health services0.360.370.05–2.790.326Self-reported health status2.612.570.38–180.332Sex2.472.330.39–15.650.338Age1.040.050.95–1.140.340 1 Significance level is set at p ≤  0.05 2 The variables are presented in order of decreasing significance.PCP, primary care physician.
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