The breadth of primary care: a systematic literature review of its core dimensions

Background: Even though there is general agreement that primary care is the linchpin of effective health care delivery, to date no efforts have been made to systematically review the scientific evidence supporting this supposition. The aim of this study was to examine the breadth of primary care by identifying its core dimensions and to assess the evidence for their interrelations and their relevance to outcomes at (primary) health system level. Methods: A systematic review of the primary care literature was carried out, restricted to English language journals reporting original research or systematic reviews. Studies published between 2003 and July 2008 were searched in MEDLINE, Embase, Cochrane Library, CINAHL, King's Fund Database, IDEAS Database, and EconLit. Results: Eighty-five studies were identified. This review was able to provide insight in the complexity of primary care as a multidimensional system, by identifying ten core dimensions that constitute a primary care system. The structure of a primary care system consists of three dimensions: 1. governance; 2. economic conditions; and 3. workforce development. The primary care process is determined by four dimensions: 4. access; 5. continuity of care; 6. coordination of care; and 7. comprehensiveness of care. The outcome of a primary care system includes three dimensions: 8. quality of care; 9. efficiency care; and 10. equity in health. There is a considerable evidence base showing that primary care contributes through its dimensions to overall health system performance and health. Conclusions: A primary care system can be defined and approached as a multidimensional system contributing to overall health system performance and health

Measurement of health-related quality by multimorbidity groups in primary health care

[EN] Background: Increased life expectancy in Western societies does not necessarily mean better quality of life. To improve resources management, management systems have been set up in health systems to stratify patients according to morbidity, such as Clinical Risk Groups (CRG). The main objective of this study was to evaluate the effect of multimorbidity on health-related quality of life (HRQL) in primary care. Methods: An observational cross-sectional study, based on a representative random sample (n = 306) of adults from a health district (N = 32,667) in east Spain (Valencian Community), was conducted in 2013. Multimorbidity was measured by stratifying the population with the CRG system into nine mean health statuses (MHS). HRQL was assessed by EQ-5D dimensions and the EQ Visual Analogue Scale (EQ VAS). The effect of the CRG system, age and gender on the utility value and VAS was analysed by multiple linear regression. A predictive analysis was run by binary logistic regression with all the sample groups classified according to the CRG system into the five HRQL dimensions by taking the ¿healthy¿ group as a reference. Multivariate logistic regression studied the joint influence of the nine CRG system MHS, age and gender on the five EQ-5D dimensions. Results: Of the 306 subjects, 165 were female (mean age of 53). The most affected dimension was pain/discomfort (53%), followed by anxiety/depression (42%). The EQ-5D utility value and EQ VAS progressively lowered for the MHS with higher morbidity, except for MHS 6, more affected in the five dimensions, save self-care, which exceeded MHS 7 patients who were older, and MHS 8 and 9 patients, whose condition was more serious. The CRG system alone was the variable that best explained health problems in HRQL with 17%, which rose to 21% when associated with female gender. Age explained only 4%. Conclusions: This work demonstrates that the multimorbidity groups obtained by the CRG classification system can be used as an overall indicator of HRQL. These utility values can be employed for health policy decisions based on cost-effectiveness to estimate incremental quality-adjusted life years (QALY) with routinely e-health data. Patients under 65 years with multimorbidity perceived worse HRQL than older patients or disease severity. Knowledge of multimorbidity with a stronger impact can help primary healthcare doctors to pay attention to these population groups.The authors would like to thank the Conselleria de Sanitat Universal i Sanitat Pública of the Generalitat Valenciana (the Regional Valencian Health Government) for providing the study data. We would also like to thank Helen Warbuton for editing the English.Milá-Perseguer, M.; Guadalajara Olmeda, MN.; Vivas-Consuelo, D.; Usó-Talamantes, R. (2019). Measurement of health-related quality by multimorbidity groups in primary health care. Health and Quality of Life Outcomes. 17(8):1-10. https://doi.org/10.1186/s12955-018-1063-zS110178Ministerio de Sanidad SS, Igualdad e. Indicadores de Salud 2013. Evolución de los indicadores del estado de salud en España y su magnitud en el contexto de la Unión Europea. Madrid: Ministerio de Sanidad, Servicios Sociales e Igualdad; 2014.OECD/EU: Health at a Glance: Europe 2016 – State of Health in the EU Cycle, OECD Publishing, Paris. In.; 2016.WHO: Disability and health. In. Edited by WHO; 2017.Nicholson K, Makovski TT, Griffith LE, Raina P, Stranges S, van den Akker M. Multimorbidity and comorbidity revisited: refining the concepts for international health research. J Clin Epidemiol. 2018.Palmer K, Marengoni A, Forjaz MJ, Jureviciene E, Laatikainen T, Mammarella F, Muth C, Navickas R, Prados-Torres A, Rijken M, et al. Multimorbidity care model: recommendations from the consensus meeting of the joint action on chronic diseases and promoting healthy ageing across the life cycle (JA-CHRODIS). Health Policy. 2018;122(1):4–11.WHO: Innovative Care for Chronic Conditions. Building blocks for action. In.: WHO; 2014.Fortin M, Bravo G, Hudon C, Vanasse A, Lapointe L. Prevalence of multimorbidity among adults seen in family practice. Ann Fam Med. 2005;3(3):223–8.Inoriza JM, Coderch J, Carreras M, Vall-Llosera L, Garcia-Goni M, Lisbona JM, Ibern P. Measurement of morbidity attended in an integrated health care organization. Gac Sanit. 2009;23(1):29–37.Hunger M, Thorand B, Schunk M, Döring A, Menn P, Peters A, Holle R. Multimorbidity and health-related quality of life in the older population: results from the German KORA-age study. Health Qual Life Outcomes. 2011;9:53.de Miguel P, Caballero I, Rivas FJ, Manera J, de Vicente MA, Gómez Á. Morbidity observed in a health area: impact on professionals and funding. Aten Primaria. 2015;47(5):301–7.Agborsangaya CB, Lau D, Lahtinen M, Cooke T, Johnson JA. Multimorbidity prevalence and patterns across socioeconomic determinants: a cross-sectional survey. BMC Public Health. 2012;12:201.Orueta JF, García-Álvarez A, García-Goñi M, Paolucci F, Nuño-Solinís R. Prevalence and costs of multimorbidity by deprivation levels in the Basque Country: a population based study using health administrative databases. PLoS One. 2014;9(2):e89787.Mujica-Mota RE, Roberts M, Abel G, Elliott M, Lyratzopoulos G, Roland M, Campbell J. Common patterns of morbidity and multi-morbidity and their impact on health-related quality of life: evidence from a national survey. Qual Life Res. 2015;24(4):909–18.Caballer Tarazona V, Guadalajara Olmeda N, Vivas Consuelo D, Clemente Collado A. Impact of morbidity on health care costs of a Department of Health through clinical risk groups. Valencian Community, Spain. Rev Esp Salud Publica. 2016;90:e1–e15.Calderon-Larranaga A, Abrams C, Poblador-Plou B, Weiner JP, Prados-Torres A. Applying diagnosis and pharmacy-based risk models to predict pharmacy use in Aragon, Spain: the impact of a local calibration. BMC Health Serv Res. 2010;10:22.Hughes JS, Averill RF, Eisenhandler J, Goldfield NI, Muldoon J, Neff JM, Gay JC. Clinical risk groups (CRGs): a classification system for risk-adjusted capitation-based payment and health care management. Med Care. 2004;42(1):81–90.Vivas-Consuelo D, Uso-Talamantes R, Trillo-Mata JL, Caballer-Tarazona M, Barrachina-Martinez I, Buigues-Pastor L. Predictability of pharmaceutical spending in primary health services using clinical risk groups. Health Policy. 2014;116(2–3):188–95.Milla Perseguer M, Guadalajara Olmeda N, Vivas Consuelo D. Impact of cardiovascular risk factors on the consumption of resources in primary care according to clinical risk groups. Aten Primaria. 2018.WHOQOL. The World Health Organization quality of life assessment (WHOQOL): development and general psychometric properties. Soc Sci Med. 1998;46(12):1569–85.Badia X, Carne X. The evaluation of quality of life in clinical trials. Medicina Clinica. 1998;110(14):550–6.Revicki DA. Health-related quality of life in the evaluation of medical therapy for chronic illness. J Fam Pract. 1989;29(4):377–80.Agborsangaya CB, Lau D, Lahtinen M, Cooke T, Johnson JA. Health-related quality of life and healthcare utilization in multimorbidity: results of a cross-sectional survey. Qual Life Res. 2013;22(4):791–9.Romero M, Vivas-Consuelo D, Alvis-Guzman N. Is health related quality of life (HRQoL) a valid indicator for health systems evaluation? Springerplus. 2013;2:664.Hanmer J, Feeny D, Fischhoff B, Hays RD, Hess R, Pilkonis PA, Revicki DA, Roberts MS, Tsevat J, Yu L. The PROMIS of QALYs. Health Qual Life Outcomes. 2015;13.Herdman M, Badia X, Berra S. EuroQol-5D: a simple alternative for measuring health-related quality of life in primary care. Atencion primaria / Sociedad Espanola de Medicina de Familia y Comunitaria. 2001;28(6):425–30.EuroQol G. EuroQol-a new facility for the measurement of health-related quality of life. Health Policy. 1990;16(199–208).Agborsangaya CB, Lahtinen M, Cooke T, Johnson JA. Comparing the EQ-5D 3L and 5L: measurement properties and association with chronic conditions and multimorbidity in the general population. Health Qual Life Outcomes. 2014;12:7.Real Decreto Legislativo 8/2015, de 30 de octubre, por el que se aprueba el texto refundido de la Ley General de la Seguridad Social. In. «BOE» núm. 261, de 31/10/2015.: Ministerio de Empleo y Seguridad Social.; 2015.Ministry of Health and Social Policy:. Estudios sobre la calidad de vida de pacientes afectados por determinadas patologías. [ http://www.mscbs.gob.es/organizacion/sns/planCalidadSNS/ ].Ministry of Health and Social Policy: Encuesta Nacional de Salud. España 2011/12. Calidad de vida relacionada con la salud en adultos: EQ-5D-5L. Serie Informes monográficos n° 3. Madrid: Ministerio de Sanidad, Servicios Sociales e Igualdad; 2014.Fortin M, Bravo G, Hudon C, Lapointe L, Almirall J, Dubois MF, Vanasse A. Relationship between multimorbidity and health-related quality of life of patients in primary care. Qual Life Res. 2006;15(1):83–91.Fortin M, Dubois MF, Hudon C, Soubhi H, Almirall J. Multimorbidity and quality of life: a closer look. Health Qual Life Outcomes. 2007;5:52.Brazier JE, Yang Y, Tsuchiya A, Rowen DL. A review of studies mapping (or cross walking) non-preference based measures of health to generic preference-based measures. Eur J Health Econ. 2010;11.Peak J, Goranitis I, Day E, Copello A, Freemantle N, Frew E. Predicting health-related quality of life (EQ-5D-5 L) and capability wellbeing (ICECAP-A) in the context of opiate dependence using routine clinical outcome measures: CORE-OM, LDQ and TOP. Health Qual Life Outcomes. 2018;16(1):106.Rivero-Arias O, Ouellet M, Gray A, Wolstenholme J, Rothwell PM, Luengo-Fernandez R. Mapping the modified Rankin scale (mRS) measurement into the generic EuroQol (EQ-5D) health outcome. Med Decis Mak. 2010;30.Argimon Pallás JM, Jiménez Villa J: Métodos de investigación clínica y epidemiológica, vol. Capítulo 15. Tamaño de la muestra; 2013.Yepes-Núñez JJ, García García HI: Preferencias de estados de salud y medidas de utilidad. In., vol. 24. Iatreia; 2011: 365–377.Attema AE, Edelaar-Peeters Y, Versteegh MM, Stolk EA. Time trade-off: one methodology, different methods. Eur J Health Econ. 2013;14(Suppl 1):S53–64.Badia X, Roset M, Herdman M, Kind P. A comparison of United Kingdom and Spanish general population time trade-off values for EQ-5D health states. Med Decis Mak. 2001;21(1):7–16.Garin N, Olaya B, Moneta MV, Miret M, Lobo A, Ayuso-Mateos JL, Haro JM. Impact of multimorbidity on disability and quality of life in the Spanish older population. PLoS One. 2014;9(11):e111498.Mielck A, Vogelmann M, Leidl R. Health-related quality of life and socioeconomic status: inequalities among adults with a chronic disease. Health Qual Life Outcomes. 2014;12:58.Usó Talamantes R: Análisis y desarrollo de un modelo predictivo del gasto farmacéutico ambulatorio ajustado a morbilidad y riesgo clínico [tesis doctoral]. Universidad Politécnica de Valencia; 2015. https://www.educacion.gob.es/teseo/mostrarRef.do?ref=1183638 .Sánchez Mollá M, Candela García I, Gómez-Romero FJ, Orozco Beltrán D, Ollero Baturone M. Concordance between stratification systems and identification of patients with multiple chronic diseases in primary care. Rev Calid Asist. 2017;32(1):10–6.Vivas-Consuelo D, Uso-Talamantes R, Guadalajara-Olmeda N, Trillo-Mata J-L, Sancho-Mestre C, Buigues-Pastor L. Pharmaceutical cost management in an ambulatory setting using a risk adjustment tool. BMC Health Serv Res. 2014;14:462.Coderch J, Sánchez-Pérez I, Ibern P, Carreras M, Pérez-Berruezo X, Inoriza JM. Predicting individual risk of high healthcare cost to identify complex chronic patients. Gac Sanit. 2014;28(4):292–300.Osca Guadalajara M, Guadalajara Olmeda N, Escartín Martínez R. Impact of Teriparatide on quality of life in osteoporotic patients. Rev Esp Salud Publica. 2015;89(2):215–25.Prazeres F, Santiago L. Relationship between health-related quality of life, perceived family support and unmet health needs in adult patients with multimorbidity attending primary care in Portugal: a multicentre cross-sectional study. Health Qual Life Outcomes. 2016;14(1):156.Brettschneider C, Leicht H, Bickel H, Dahlhaus A, Fuchs A, Gensichen J, Maier W, Group MS. Relative impact of multimorbid chronic conditions on health-related quality of life--results from the MultiCare cohort study. PLoS One. 2013;8(6):e66742

Study protocol: The Intensive Care Outcome Network ('ICON') study

<p>Abstract</p> <p>Background</p> <p>Extended follow-up of survivors of ICU treatment has shown many patients suffer long-term physical and psychological consequences that affect their health-related quality of life. The current lack of rigorous longitudinal studies means that the true prevalence of these physical and psychological problems remains undetermined.</p> <p>Methods/Design</p> <p>The ICON (Intensive Care Outcome Network) study is a multi-centre, longitudinal study of survivors of critical illness. Patients will be recruited prior to hospital discharge from 20–30 ICUs in the UK and will be assessed at 3, 6, and 12 months following ICU discharge for health-related quality of life as measured by the Short Form-36 (SF-36) and the EuroQoL (EQ-5D); anxiety and depression as measured by the Hospital Anxiety and Depression Scale (HADS); and post traumatic stress disorder (PTSD) symptoms as measured by the PTSD Civilian Checklist (PCL-C). Postal questionnaires will be used.</p> <p>Discussion</p> <p>The ICON study will create a valuable UK database detailing the prevalence of physical and psychological morbidity experienced by patients as they recover from critical illness. Knowledge of the prevalence of physical and psychological morbidity in ICU survivors is important because research to generate models of causality, prognosis and treatment effects is dependent on accurate determination of prevalence. The results will also inform economic modelling of the long-term burden of critical illness.</p> <p>Trial Registration</p> <p>ISRCTN69112866</p

Efficacy and safety of acupuncture for the treatment of non-specific acute low back pain: a randomised controlled multicentre trial protocol [ISRCTN65814467]

BACKGROUND: Low back pain and its associated incapacitating effects constitute an important healthcare and socioeconomic problem, as well as being one of the main causes of disability among adults of working age. The prevalence of non-specific low back pain is very high among the general population, and 60–70% of adults are believed to have suffered this problem at some time. Nevertheless, few randomised clinical trials have been made of the efficacy and efficiency of acupuncture with respect to acute low back pain. The present study is intended to assess the efficacy of acupuncture for acute low back pain in terms of the improvement reported on the Roland Morris Questionnaire (RMQ) on low back pain incapacity, to estimate the specific and non-specific effects produced by the technique, and to carry out a cost-effectiveness analysis. METHODS/DESIGN: Randomised four-branch controlled multicentre prospective study made to compare semi-standardised real acupuncture, sham acupuncture (acupuncture at non-specific points), placebo acupuncture and conventional treatment. The patients are blinded to the real, sham and placebo acupuncture treatments. Patients in the sample present symptoms of non specific acute low back pain, with a case history of 2 weeks or less, and will be selected from working-age patients, whether in paid employment or not, referred by General Practitioners from Primary Healthcare Clinics to the four clinics participating in this study. In order to assess the primary and secondary result measures, the patients will be requested to fill in a questionnaire before the randomisation and again at 3, 12 and 48 weeks after starting the treatment. The primary result measure will be the clinical relevant improvement (CRI) at 3 weeks after randomisation. We define CRI as a reduction of 35% or more in the RMQ results. DISCUSSION: This study is intended to obtain further evidence on the effectiveness of acupuncture on acute low back pain and to isolate the specific and non-specific effects of the treatment

Reliability of home CPAP titration with different automatic CPAP devices

<p>Abstract</p> <p>Background</p> <p>CPAP titration may be completed by automatic apparatus. However, differences in pressure behaviour could interfere with the reliability of pressure recommendations. Our objective was to compare pressure behaviour and effective pressure recommendations between three Automatic CPAP machines (Autoset Spirit, Remstar Auto, GK 420).</p> <p>Methods</p> <p>Sixteen untreated obstructive sleep apnea patients were randomly allocated to one of the 3 tested machines for a one-week home titration trial in a crossover design with a 10 days washout period between trials.</p> <p>Results</p> <p>The median pressure value was significantly lower with machine GK 420 (5.9 +/- 1.8 cm H₂O) than with the other devices both after one night and one week of CPAP titration (7.4 +/- 1.3 and 6.6 +/- 1.9 cm H₂O). The maximal pressure obtained over the one-week titration was significantly higher with Remstar Auto (12.6 +/- 2.4 cm H₂O, Mean +/- SD) than with the two other ones (10.9 +/- 1.0 and 11.0 +/- 2.4 cm H₂O). The variance in pressure recommendation significantly differed between the three machines after one night and between Autoset Spirit and the two other machines after 1 week.</p> <p>Conclusion</p> <p>Pressure behaviour and pressure recommendation significantly differ between Auto CPAP machines both after one night and one week of home titration.</p

Trazodone for the treatment of fibromyalgia: an open-label, 12-week study

Background: Despite its frequent use as a hypnotic, trazodone has not been systematically assessed in fibromyalgia patients. In the present study have we evaluated the potential effectiveness and tolerability of trazodone in the treatment of fibromyalgia. Methods: A flexible dose of trazodone (50-300 mg/day), was administered to 66 fibromyalgia patients for 12 weeks. The primary outcome measure was the Pittsburgh Sleep Quality Index (PSQI). Secondary outcome measures included the Fibromyalgia Impact Questionnaire (FIQ), the Beck Depression Inventory (BDI), the Hospital Anxiety and Depression Scale (HADS), the Brief Pain Inventory (BPI), the Short-Form Health Survey (SF-36), and the Patients' Global Improvement Scale (PGI). Trazodone's emergent adverse reactions were recorded. Data were analyzed with repeated measures one-way ANOVA and paired Student's t test. Results: Trazodone markedly improved sleep quality, with large effect sizes in total PSQI score as well on sleep quality, sleep duration and sleep efficiency. Significant improvement, although with moderate effect sizes, were also observed in total FIQ scores, anxiety and depression scores (both HADS and BDI), and pain interference with daily activities. Unexpectedly, the most frequent and severe side effect associated with trazodone in our sample was tachycardia, which was reported by 14 (21.2%) patients. Conclusions: In doses higher than those usually prescribed as hypnotic, the utility of trazodone in fibromyalgia management surpasses its hypnotic activity. However, the emergence of tachycardia should be closely monitored. Trial registration: This trial has been registered with ClinicalTrials.gov number NCT-00791739

Trazodone plus pregabalin combination in the treatment of fibromyalgia: a two-phase, 24-week, open-label uncontrolled study

<p>Abstract</p> <p>Background</p> <p>Although trazodone is frequently used by fibromyalgia patients, its efficacy on this disease has not been adequately studied. If effective, pregabalin, whose beneficial effects on pain and sleep quality in fibromyalgia have been demonstrated, could complement the antidepressant and anxiolytic effects of trazodone. The aim of the present study was to assess the effectiveness of trazodone alone and in combination with pregabalin in the treatment of fibromyalgia.</p> <p>Methods</p> <p>This was an open-label uncontrolled study. Trazodone, flexibly dosed (50-300 mg/day), was administered to 66 fibromyalgia patients during 12 weeks; 41 patients who completed the treatment accepted to receive pregabalin, also flexibly dosed (75-450 mg/day), added to trazodone treatment for an additional 12-week period. Outcome measures included the Fibromyalgia Impact Questionnaire (FIQ), the Pittsburgh Sleep Quality Index (PSQI), the Beck Depression Inventory (BDI), the Hospital Anxiety and Depression Scale (HADS), the Brief Pain Inventory (BPI), the Short-Form Health Survey (SF-36), and the Patients' Global Improvement scale (PGI). Emergent adverse reactions were recorded. Data were analyzed with repeated measures one-way ANOVA and paired Student's t test.</p> <p>Results</p> <p>Treatment with trazodone significantly improved global fibromyalgia severity, sleep quality, and depression, as well as pain interference with daily activities although without showing a direct effect on bodily pain. After pregabalin combination additional and significant improvements were seen on fibromyalgia severity, depression and pain interference with daily activities, and a decrease in bodily pain was also apparent. During the second phase of the study, only two patients dropped out due to side effects.</p> <p>Conclusions</p> <p>Trazodone significantly improved fibromyalgia severity and associated symptomatology. Its combination with pregabalin potentiated this improvement and the tolerability of the drugs in association was good.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov: <a href="http://www.clinicaltrials.gov/ct2/show/NCT00791739">NCT00791739</a></p

Experience-based VAS values for EQ-5D-3L health states in a national general population health survey in China

Purpose: To investigate the feasibility of deriving experience-based visual analogue scale (VAS) values for EQ-5D-3L health states using national general population health survey data in China. Methods: The EQ-5D-3L was included in the National Health Services Survey (n = 120,709, aged 15–103 years) to measure health-related quality of life. The respondents reported their current health status on a VAS and completed the EQ-5D-3L questionnaire, enabling modelling of the association between the experience-based VAS values and self-reported problems on EQ-5D dimensions and severity levels. Results: VAS values were generally negatively associated with problems reported on the EQ-5D dimensions, and the anxiety/depression dimension had the greatest impact on VAS values. A previously obtained value for dead allowed the values for all 243 EQ-5D-3L health states to be transformed to the 0–1 scale (0 = dead, 1 = full health). Conclusions: This study presents the feasibility of deriving an experience-based VAS values for EQ-5D-3L health states in China. The analysis of these VAS data raises more fundamental issues concerning the universal nature of the classification system and the extent to which Chinese respondents utilise the same concepts of health as defined by this classification system

The IRYSS-COPD appropriateness study: objectives, methodology, and description of the prospective cohort

<p>Abstract</p> <p>Background</p> <p>Patients with chronic obstructive pulmonary disease (COPD) often experience exacerbations of the disease that require hospitalization. Current guidelines offer little guidance for identifying patients whose clinical situation is appropriate for admission to the hospital, and properly developed and validated severity scores for COPD exacerbations are lacking. To address these important gaps in clinical care, we created the IRYSS-COPD Appropriateness Study.</p> <p>Methods/Design</p> <p>The RAND/UCLA Appropriateness Methodology was used to identify appropriate and inappropriate scenarios for hospital admission for patients experiencing COPD exacerbations. These scenarios were then applied to a prospective cohort of patients attending the emergency departments (ED) of 16 participating hospitals. Information was recorded during the time the patient was evaluated in the ED, at the time a decision was made to admit the patient to the hospital or discharge home, and during follow-up after admission or discharge home. While complete data were generally available at the time of ED admission, data were often missing at the time of decision making. Predefined assumptions were used to impute much of the missing data.</p> <p>Discussion</p> <p>The IRYSS-COPD Appropriateness Study will validate the appropriateness criteria developed by the RAND/UCLA Appropriateness Methodology and thus better delineate the requirements for admission or discharge of patients experiencing exacerbations of COPD. The study will also provide a better understanding of the determinants of outcomes of COPD exacerbations, and evaluate the equity and variability in access and outcomes in these patients.</p